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Ryser, Marc D., Byung-Hoon Min, Kimberly D. Siegmund, and Darryl Shibata. "Spatial mutation patterns as markers of early colorectal tumor cell mobility." Proceedings of the National Academy of Sciences 115, no. 22 (2018): 5774–79. http://dx.doi.org/10.1073/pnas.1716552115.
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A growing body of evidence suggests that a subset of human cancers grows as single clonal expansions. In such a nearly neutral evolution scenario, it is possible to infer the early ancestral tree of a full-grown tumor. We hypothesized that early tree reconstruction can provide insights into the mobility phenotypes of tumor cells during their first few cell divisions. We explored this hypothesis by means of a computational multiscale model of tumor expansion incorporating the glandular structure of colorectal tumors. After calibrating the model to multiregional and single gland data from 19 human colorectal tumors using approximate Bayesian computation, we examined the role of early tumor cell mobility in shaping the private mutation patterns of the final tumor. The simulations showed that early cell mixing in the first tumor gland can result in side-variegated patterns where the same private mutations could be detected on opposite tumor sides. In contrast, absence of early mixing led to nonvariegated, sectional mutation patterns. These results suggest that the patterns of detectable private mutations in colorectal tumors may be a marker of early cell movement and hence the invasive and metastatic potential of the tumor at the start of the growth. In alignment with our hypothesis, we found evidence of early abnormal cell movement in 9 of 15 invasive colorectal carcinomas (“born to be bad”), but in none of 4 benign adenomas. If validated with a larger dataset, the private mutation patterns may be used for outcome prediction among screen-detected lesions with unknown invasive potential.
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Bernardis, Alessia, Marco Bullo, Luca Giovanni Campana, et al. "Electric field computation and measurements in the electroporation of inhomogeneous samples." Open Physics 15, no. 1 (2017): 790–96. http://dx.doi.org/10.1515/phys-2017-0092.
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AbstractIn clinical treatments of a class of tumors,e.g. skin tumors, the drug uptake of tumor tissue is helped by means of a pulsed electric field, which permeabilizes the cell membranes. This technique, which is called electroporation, exploits the conductivity of the tissues: however, the tumor tissue could be characterized by inhomogeneous areas, eventually causing a non-uniform distribution of current. In this paper, the authors propose a field model to predict the effect of tissue inhomogeneity, which can affect the current density distribution. In particular, finite-element simulations, considering non-linear conductivity against field relationship, are developed. Measurements on a set of samples subject to controlled inhomogeneity make it possible to assess the numerical model in view of identifying the equivalent resistance between pairs of electrodes.
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Eddy, James A., Vésteinn Thorsson, Andrew E. Lamb, et al. "CRI iAtlas: an interactive portal for immuno-oncology research." F1000Research 9 (August 24, 2020): 1028. http://dx.doi.org/10.12688/f1000research.25141.1.
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The Cancer Research Institute (CRI) iAtlas is an interactive web platform for data exploration and discovery in the context of tumors and their interactions with the immune microenvironment. iAtlas allows researchers to study immune response characterizations and patterns for individual tumor types, tumor subtypes, and immune subtypes. iAtlas supports computation and visualization of correlations and statistics among features related to the tumor microenvironment, cell composition, immune expression signatures, tumor mutation burden, cancer driver mutations, adaptive cell clonality, patient survival, expression of key immunomodulators, and tumor infiltrating lymphocyte (TIL) spatial maps. iAtlas was launched to accompany the release of the TCGA PanCancer Atlas and has since been expanded to include new capabilities such as (1) user-defined loading of sample cohorts, (2) a tool for classifying expression data into immune subtypes, and (3) integration of TIL mapping from digital pathology images. We expect that the CRI iAtlas will accelerate discovery and improve patient outcomes by providing researchers access to standardized immunogenomics data to better understand the tumor immune microenvironment and its impact on patient responses to immunotherapy.
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Neeru Saxena. "Ensemble XMOB Approach for Brain Tumor Detection Based on Feature Extraction." Tuijin Jishu/Journal of Propulsion Technology 45, no. 03 (2024): 593–607. http://dx.doi.org/10.52783/tjjpt.v45.i03.7253.
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Brain tumors are a serious health threat in adults. These fast-growing abnormal cell masses disrupt normal brain function. Doctors use various imaging techniques to identify the specific type, size, and location of brain tumors in patients. Accurately identifying and classifying brain tumors is crucial for understanding how they develop and progress. Magnetic Resonance Imaging (MRI), a well-established medical imaging technique, plays a vital role in this process by assisting radiologists in investigating the location of the tumor. Previous models frequently encounter a compromise between accuracy and computational efficiency, lacking an approach that successfully integrates both aspects.This study introduces an innovative ensemble model termed as “XMob Approach” that combines the deep features extraction abilities of Xception with computational efficiency of MobleNet for binary classification of brain Tumor. The Xmob Approach leverages the strengths of both architectures : Xception depthwise seperable convolutions allow for detailed feature extraction whereas MobileNet’s lightweight structure ensures efficient computation making it suitable for real life application. This combination aims to enhance in medical diagnostics, promising enhanced accuracy and efficiency. This study explores the potential of integrating these pre-trained architectures to provide real-time, automated diagnostic assistance, improving the speed and precision of brain tumor detection. In our methodology pre-processed MRI scans undergo feature extraction through Xception model, capturing complicated patterns indicative of tumor presence. Simultaneously MobileNet processed these images emphasizing computational efficiency without compromising on performance.The output of both the modesl are then integrated using ensemble technique to improve overall classification accuracy. By integrating the complementary strengths of Xception and MobileNet , the XMob Approach represent a significant step towards the field of medical diagnostic promising improved outcomes for patients through advanced technology. DOI: https://doi.org/10.52783/tjjpt.v45.i03.7253
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Zhang, Bing, and Michal Bassani-Sternberg. "Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery." Journal for ImmunoTherapy of Cancer 11, no. 10 (2023): e007073. http://dx.doi.org/10.1136/jitc-2023-007073.
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Identification of tumor antigens presented by the human leucocyte antigen (HLA) molecules is essential for the design of effective and safe cancer immunotherapies that rely on T cell recognition and killing of tumor cells. Mass spectrometry (MS)-based immunopeptidomics enables high-throughput, direct identification of HLA-bound peptides from a variety of cell lines, tumor tissues, and healthy tissues. It involves immunoaffinity purification of HLA complexes followed by MS profiling of the extracted peptides using data-dependent acquisition, data-independent acquisition, or targeted approaches. By incorporating DNA, RNA, and ribosome sequencing data into immunopeptidomics data analysis, the proteogenomic approach provides a powerful means for identifying tumor antigens encoded within the canonical open reading frames of annotated coding genes and non-canonical tumor antigens derived from presumably non-coding regions of our genome. We discuss emerging computational challenges in immunopeptidomics data analysis and tumor antigen identification, highlighting key considerations in the proteogenomics-based approach, including accurate DNA, RNA and ribosomal sequencing data analysis, careful incorporation of predicted novel protein sequences into reference protein database, special quality control in MS data analysis due to the expanded and heterogeneous search space, cancer-specificity determination, and immunogenicity prediction. The advancements in technology and computation is continually enabling us to identify tumor antigens with higher sensitivity and accuracy, paving the way toward the development of more effective cancer immunotherapies.
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Bloom, Alexander B., and Muhammad H. Zaman. "Influence of the microenvironment on cell fate determination and migration." Physiological Genomics 46, no. 9 (2014): 309–14. http://dx.doi.org/10.1152/physiolgenomics.00170.2013.
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Several critical cell functions are influenced not only by internal cellular machinery but also by external mechanical and biochemical cues from the surrounding microenvironment. Slight changes to the microenvironment can result in dramatic changes to the cell's phenotype; for example, a change in the nutrients or pH of a tumor microenvironment can result in increased tumor metastasis. While cellular fate and the regulators of cell fate have been studied in detail for several decades now, our understanding of the extracellular regulators remains qualitative and far from comprehensive. In this review, we discuss the microenvironment influence on cell fate in terms of adhesion, migration, and differentiation and focus on both developments in experimental and computation tools to analyze cellular fate.
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Trusov, P. V., N. V. Zaitseva, and V. М. Chigvintsev. "Predicting a risk of tumor evolution considering regulatory mechanisms of the body and angiogenesis." Health Risk Analysis, no. 4 (December 2023): 134–45. http://dx.doi.org/10.21668/health.risk/2023.4.13.eng.
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Adverse environmental and lifestyle factors produce considerable effects on occurrence of cancerous tumors, both directly and indirectly through impaired functionality of the body protection mechanisms. Investigation of these effects has practical significance for risk assessment and development of effective cancer preventive strategies. Mathematical modeling is an eligible method for considering complex multicomponent interactions between elements of various systems involved in tumor growth. This article presents an approach to assessing risks of cancerous tumors by using a created predictive model that describes dynamics of abnormal cells considering regulatory mechanisms and angiogenesis. An evolution approach is applied to estimate accumulated functional disorders of the immune system due to natural ageing and chemical environmental exposures. The Monte Carlo simulation is employed to estimate a likely outcome of cancerous tumor evolution given different possible properties of abnormal cells. The article provides the results of accomplished computation experiments aimed at describing dynamics of changes in cell population properties in an analyzed organ tissue. Development of a vessel system is described considering different effects of the most significant factors. Computation results are analyzed within various scenarios that describe cancerous tumor growth in dynamics considering how angiogenesis develops under different parameters of the immune system dysfunction and different properties of abnormal cells. Risks of tumor development are assessed considering parameters that determine the overall state of the body (the immune system) and properties of abnormal cells. This approach makes it possible to develop a system of preventive and sanitary-hygienic activities in areas where envi-ronmental conditions are unfavorable in order to reduce cancer incidence.
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Trusov, P. V., N. V. Zaitseva, and V. М. Chigvintsev. "Predicting a risk of tumor evolution considering regulatory mechanisms of the body and angiogenesis." Health Risk Analysis, no. 4 (December 2023): 134–45. http://dx.doi.org/10.21668/health.risk/2023.4.13.
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Adverse environmental and lifestyle factors produce considerable effects on occurrence of cancerous tumors, both directly and indirectly through impaired functionality of the body protection mechanisms. Investigation of these effects has practical significance for risk assessment and development of effective cancer preventive strategies. Mathematical modeling is an eligible method for considering complex multicomponent interactions between elements of various systems involved in tumor growth. This article presents an approach to assessing risks of cancerous tumors by using a created predictive model that describes dynamics of abnormal cells considering regulatory mechanisms and angiogenesis. An evolution approach is applied to estimate accumulated functional disorders of the immune system due to natural ageing and chemical environmental exposures. The Monte Carlo simulation is employed to estimate a likely outcome of cancerous tumor evolution given different possible properties of abnormal cells. The article provides the results of accomplished computation experiments aimed at describing dynamics of changes in cell population properties in an analyzed organ tissue. Development of a vessel system is described considering different effects of the most significant factors. Computation results are analyzed within various scenarios that describe cancerous tumor growth in dynamics considering how angiogenesis develops under different parameters of the immune system dysfunction and different properties of abnormal cells. Risks of tumor development are assessed considering parameters that determine the overall state of the body (the immune system) and properties of abnormal cells. This approach makes it possible to develop a system of preventive and sanitary-hygienic activities in areas where envi-ronmental conditions are unfavorable in order to reduce cancer incidence.
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Satomi, Kaishi, Ryo Nishikawa, Masao Matsutani, Koichi Ichimura, and Hirokazu Takami. "PATH-42. PROGNOSTIC FACTORS OF CNS GERM CELL TUMORS; MOLECULAR AND HISTOPATHOLOGICAL ANALYSES ON 154 CASES FROM THE IGCT CONSORTIUM." Neuro-Oncology 23, Supplement_6 (2021): vi124—vi125. http://dx.doi.org/10.1093/neuonc/noab196.494.
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Abstract BACKGROUND Germ cell tumors (GCTs) preferentially occurs in pediatric and young adult age groups. Chemo- and radiation therapies cause long-term sequelae in their later lives. We searched for clinical and histopathological features to predict the prognosis and affect treatment response, with a future goal of treatment stratification. METHODS A total of 154 GCT cases were included in the analysis. Total of 114 germinoma cases underwent measurement of tumor cell content on H-E specimen, and 82 GCT cases underwent 450K methylation analysis. 12p gain was determined on methylation-based copy number computation and FISH. Association with progression-free and overall survival (PFS/OS) was investigated. RESULTS The tumor cell content was widely distributed from < 5% to 90% in the specimens, with a median value of 50%. Patients with a higher tumor cell content (≥50%) showed shorter PFS than those with a lower tumor cell content (< 50 %) (p=0.03). In multivariate analysis with tumor location, tumor cell content was the sole statistically significant prognostic factor (p=0.04). 12p gain was found in 25-out-of-82 cases (30%) and was more frequent in NGGCTs, particularly in cases with malignant components. The presence of 12p gain correlated with shorter PFS and OS, even with histology and tumor markers incorporated in the multivariate analysis. Among NGGCTs, 12p gain still had prognostic significance for PFS and OS. The 12p copy number status was shared among histological components in mixed GCTs. Whole-genome amplification was suggested by FISH. CONCLUSIONS We found that tumor cell content significantly affected the prognosis of germinomas. 12p gain predicts the presence of malignant components of NGGCTs, and poor prognosis of the patients. Furthermore, 12p is likely to be an early event in the tumorigenesis of GCT. These potentially open the possibility of leveraging these pathological and molecular factors in future clinical trials when stratifying the treatment intensity.
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Takami, Hirokazu, Kaishi Satomi, Kohei Fukuoka, et al. "BOT-3 Prognostic Factors of CNS Germ Cell Tumors; Molecular and Histopathological Analyses on 154 Cases from the iGCT Consortium." Neuro-Oncology Advances 3, Supplement_6 (2021): vi8—vi9. http://dx.doi.org/10.1093/noajnl/vdab159.031.
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Abstract Background: Germ cell tumors (GCTs) preferentially occurs in pediatric and young adult age groups. Chemo- and radiation therapies cause long-term sequelae in their later lives. We searched for clinical and histopathological features to predict the prognosis and affect treatment response, with a future goal of treatment stratification.Methods: A total of 154 GCT cases were included in the analysis. Total of 114 germinoma cases underwent measurement of tumor cell content on H-E specimen, and 82 GCT cases underwent 450K methylation analysis. 12p gain was determined on methylation-based copy number computation and FISH. Association with progression-free and overall survival (PFS/OS) was investigated. Results: The tumor cell content was widely distributed from <5% to 90% in the specimens, with a median value of 50%. Patients with a higher tumor cell content (>=50%) showed shorter PFS than those with a lower tumor cell content (<50 %) (p=0.03). In the multivariate analysis with tumor location, tumor cell content was the sole statistically significant prognostic factor (p=0.04). 12p gain was found in 25-out-of-82 cases (30%) and was more frequent in NGGCTs, particularly in cases with malignant components. The presence of 12p gain correlated with shorter PFS and OS, even with histology and tumor markers incorporated in the multivariate analysis. Among NGGCTs, 12p gain still had prognostic significance for PFS and OS. The 12p copy number status was shared among histological components in mixed GCTs. Whole-genome amplification was suggested by FISH.Conclusions: We found that tumor cell content significantly affected the prognosis of germinomas. 12p gain predicts the presence of malignant components of NGGCTs, and poor prognosis of the patients. Furthermore, 12p is likely to be an early event in the tumorigenesis of CNS GCT. These potentially open the possibility of leveraging these pathological and molecular factors in the future clinical trials when stratifying the treatment intensity.
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Anderson, Hannah, Gregory P. Takacs, Christian Kreiger, et al. "209 A CTS Team Approach to Modeling Migration and Suppression of CCR2+/CX3CR1+ Myeloid Cells in Glioblastoma." Journal of Clinical and Translational Science 6, s1 (2022): 32. http://dx.doi.org/10.1017/cts.2022.111.
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OBJECTIVES/GOALS: Evaluate the migration and immune suppressive functions of CCR2+/CX3CR1+ myeloid-derived suppressor cells (MDSCs). Integrate experimental data and biologically relevant mathematical models of infiltrating MDSCs in the context of glioblastoma (GBM). METHODS/STUDY POPULATION: CCR2+/CX3CR1+ cells were enriched from bone marrow obtained from CCR2(+/RFP)/CX3CR1(+/GFP) glioma-bearing mice to evaluate their immune-suppressive phenotype and ability to migrate to CCL2 and CCL7. Fluorescent imaging and quantification were performed on a range of tumor sizes to acquire vasculature, tumor, T cell, and MDSC densities. A system of ordinary differential equations was constructed to represent the temporal dynamics of glioma cells, T cells, and MDSCs within the tumor microenvironment. The Approximate Bayesian Computation method was used to determine probability distributions of important parameters, such as the suppression rate of T cells by MDSCs. RESULTS/ANTICIPATED RESULTS: CCR2+/CX3CR1+ M-MDSCs isolated from the bone marrow of tumor-bearing mice suppress CD8+ T cell proliferation and IFNγ production. CCR2+/CX3CR1+ cells migrate to recombinant and KR158B glioma sourced CCL2 and CCL7. Parameter values determined by the Approximate Bayesian Computation method agreed with parameter values from experimental data. This result further validated the structure and results of the mathematical model when performing computer simulations; thus, we can predict CCR2+/CX3CR1+ M-MDSC infiltration over time. DISCUSSION/SIGNIFICANCE: The immune-suppressive microenvironment in GBM contributes to poor outcomes despite standard of care. This study integrates biological and mathematical models to better understand infiltrating immune-suppressive cells, namely CCR2+/CX3CR1+ M-MDSCs. Future directions include modeling immunotherapies.
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Liu, Zichao, Xiaofei Song, Jiang He, et al. "Abstract 1143: Dissection of melanoma and cutaneous lymphoma spatial molecular architecture by multimodal single-cell and spatial transcriptomics with generative AI." Cancer Research 84, no. 6_Supplement (2024): 1143. http://dx.doi.org/10.1158/1538-7445.am2024-1143.
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Abstract Advances in single-cell multiomic technologies have revolutionized our understanding of how heterogeneous cell types and cell states shape the tumor microenvironment (TME). However, dissociated single cell profiling lacks spatial context. To resolve the organization, cell-cell communication, and granular structures in the TME, new single-cell spatial transcriptomic (ST) characterizations are needed. Here, we dissected the spatial molecular architecture of the melanoma (30 tumors, 30 patients) and transformed cutaneous T-cell lymphoma (tCTCL, 12 tumors, 6 patients) TMEs by Multiplexed Error-Robust FISH (305 gene MERFISH), with benchmarking scRNAseq data from matched tissues (6 melanoma scFFPEseq, 6 tCTCL scVDJ/RNAseq) for cross-platform validation. We profiled 565,122 cells in melanoma and 92584 cells in tCTCL by MERFISH. We interrogated both datasets using a novel computational framework that includes cell typing by Leiden clustering and marker genes, spatial neighborhood and receptor-ligand (R-L) analyses, and spatial/scRNA imputation via deep learning. In the melanoma dataset, we identified tumor cells, major TME cell types, and rare immune cell types (TCF7+ stem-like T-cells and CD3+TCRα+PAX5+CD79a+ B/T dual-expressor lymphocytes enriched in tertiary lymphoid structures). All cell types were validated in scFFPEseq. As immune R-L interactions are critical therapeutic targets, we developed a novel computation method to quantify spatial R-L interactions by accounting for cell-cell distance, identifying spatially informed R-L pairs that differ from dissociation-based inferences. CNV inference from melanoma scFFPEseq revealed intratumoral heterogeneity (ITH). We therefore adapted the conditional variational autoencoder ENVI to simultaneously incorporate scRNA and MERFISH spatial data into a unified latent embedding. ENVI-ITH successfully learned ITH subgroup information, enabling imputation of phylogenetic lineages on spatial MERFISH. CTCL MERFISH data revealed major TME cell types, yet separation of malignant vs benign T-cells by clustering and marker approaches is hindered by their overlapping gene expression. To overcome this barrier, we deployed ENVI to impute patient-specific malignant and benign TCR clonotypes by training on the matched scVDJ/RNA data, yielding an ENVI-TCR pipeline that can delineate malignant vs benign T-cells in situ. We validated the spatial pattern of malignant T-cells by patient-specific in situ TCR probes. In sum, we have interrogated the melanoma and CTCL TME by MERFISH and presented a novel computational framework for robustly co-embedding scRNA data with imaging-based ST to spatially resolve melanoma ITH and malignant/benign T-cell populations. We believe this approach will be highly impactful for melanoma and CTCL and can be broadly applied to other solid tumors and lymphomas. Citation Format: Zichao Liu, Xiaofei Song, Jiang He, Justin He, Jodi Balasi, Jeffrey H. Chuang, Pei-Ling Chen. Dissection of melanoma and cutaneous lymphoma spatial molecular architecture by multimodal single-cell and spatial transcriptomics with generative AI [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1143.
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Wesseling, Pieter, Carlo Vermeulen, Marc Pages-Gallego, et al. "INNV-36. ULTRA-FAST DEEP-LEARNED CNS TUMOR CLASSIFICATION USING NANOPORE-SEQUENCING DURING SURGERY." Neuro-Oncology 25, Supplement_5 (2023): v164—v165. http://dx.doi.org/10.1093/neuonc/noad179.0625.
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Abstract BACKGROUND Preoperative imaging and intraoperative histological analysis provide important guidance during CNS tumor surgery but are not always precise enough. Also, the diagnosis of CNS tumors increasingly requires a combination of morphological and molecular analysis. Illumina DNA methylation array analysis provides information on hundreds of thousands of methylation sites genome-wide but is relatively time-consuming and expensive. Nanopore sequencing enables real-time generation of an increasingly precise methylation profile. AIM: To exploit the potential of nanopore sequencing as a tool for intraoperative molecular diagnostics of CNS tumors. METHODS We developed Sturgeon, a patient-agnostic, transfer-learned neural network approach. Sturgeon leverages publicly available Illumina 450K DNA methylation profiles to simulate millions of nanopore sequencing experiments, which were used to train and validate classifier models. Subsequently, snap-frozen archival samples of 50 CNS tumors were analyzed, as well as fresh tumor samples of an additional 25 CNS tumors intraoperatively. RESULTS Sturgeon delivers models capable of classifying 81 different CNS tumor types based on relatively sparse, randomly distributed nanopore sequencing data. Sturgeon was able to suggest within 40 minutes after the start of sequencing the correct diagnosis with high confidence in 45 out of 50 archival CNS tumor samples; in the remaining cases Sturgeon abstained from a diagnosis. In the real-life scenario, in 18 out of 25 cases (72%) the suggested diagnosis was correct, and in 7 cases the required confidence threshold was not reached (mostly because of low tumor cell percentage). Importantly, the Sturgeon models are portable, work across patients and sequence depths, and require less than a minute of computation on a laptop CPU. CONCLUSIONS Intraoperative nanopore sequencing can assist neurosurgical decision making and opens avenues for starting tumor-specific therapy already during operation. Furthermore, this diagnostic approach has the potential to reduce the costs of methylation profiling analysis and speed-up the multidisciplinary decision-making process.
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McFall, Thomas, Jolene K. Diedrich, Meron Mengistu, et al. "A systems mechanism for KRAS mutant allele–specific responses to targeted therapy." Science Signaling 12, no. 600 (2019): eaaw8288. http://dx.doi.org/10.1126/scisignal.aaw8288.
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Cancer treatment decisions are increasingly guided by which specific genes are mutated within each patient’s tumor. For example, agents inhibiting the epidermal growth factor receptor (EGFR) benefit many colorectal cancer (CRC) patients, with the general exception of those whose tumor includes a KRAS mutation. However, among the various KRAS mutations, that which encodes the G13D mutant protein (KRASG13D) behaves differently; for unknown reasons, KRASG13D CRC patients benefit from the EGFR-blocking antibody cetuximab. Controversy surrounds this observation, because it contradicts the well-established mechanisms of EGFR signaling with regard to RAS mutations. Here, we identified a systems-level, mechanistic explanation for why KRASG13D cancers respond to EGFR inhibition. A computational model of RAS signaling revealed that the biophysical differences between the three most common KRAS mutants were sufficient to generate different sensitivities to EGFR inhibition. Integrated computation with experimentation then revealed a nonintuitive, mutant-specific dependency of wild-type RAS activation by EGFR that is determined by the interaction strength between KRAS and the tumor suppressor neurofibromin (NF1). KRAS mutants that strongly interacted with and competitively inhibited NF1 drove wild-type RAS activation in an EGFR-independent manner, whereas KRASG13D weakly interacted with and could not competitively inhibit NF1 and, thus, KRASG13D cells remained dependent on EGFR for wild-type RAS activity. Overall, our work demonstrates how systems approaches enable mechanism-based inference in genomic medicine and can help identify patients for selective therapeutic strategies.
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Pan, Weiling, Hui Wang, Fangfei Qi, et al. "Abstract C130: Discovery and characterization of an MTA-cooperative and brain-penetrant PRMT5 inhibitor." Molecular Cancer Therapeutics 22, no. 12_Supplement (2023): C130. http://dx.doi.org/10.1158/1535-7163.targ-23-c130.
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Abstract Introduction: MTAP is homozygous deleted in ~50% in glioblastoma and many other cancers. PRMT5*MTA inhibition has been shown to be synthetic lethal with MTAP deletion. First generation PRMT5 inhibitors could not distinguish between PRMT5*MTA or PRMT5 alone, thus limited by their shallow therapeutic windows in clinical use. Development of selective PRMT5*MTA inhibitors may improve not only safety but also therapeutic efficacy. Leveraging advanced computation-aided structural analysis and medicinal chemistry design, we have discovered a potent and selective MTA-cooperative and brain-penetrable PRMT5 inhibitor ABK-PRMT5-1, which demonstrates strong anti-tumor activity and brain-penetrating activity in various preclinical models. Method: Isogenic cell line pairs (MTAP-/- and MTAP+/+) were used to determine the effects of ABSK-PRMT5-1 on cell proliferation and PRMT5-dependednt downstream signaling. Cancer cell line panel was also used to confirm its activity and selectivity. Its in vivo efficacy was evaluated in cell line derived xenograft (CDX) mouse models with tumors harboring MTAP gene deletion. Results: ABSK-PRMT5-1 strongly inhibits cell proliferation in MTAP-deleted cancer cell lines, with minimal effects on MTAP wildtype cell lines. Furthermore, it significantly reduces SDMA in MTAP-deleted cancer cell lines. Oral administration of ABSK-PRMT5-1 strongly inhibits tumor growth in MTAP-deleted xenograft tumor models. In addition, ABSK-PRMT5-1 demonstrates strong brain penetration with excellent Kp values in animals. DMPK and safety profiling shows good overall drug-like properties of ABK-PRMT5-1. Conclusion: ABK-PRMT5-1, presented here by Abbisko Therapeutics, is a highly selective MTA-cooperative and brain-penetrable PRMT5 inhibitor. Its superior profile supports fast-track preclinical development. Citation Format: Weiling Pan, Hui Wang, Fangfei Qi, Haibing Deng, Fei Yang, Hongping Yu, Yao-Chang Xu, Zhui Chen, Haiyan Ying. Discovery and characterization of an MTA-cooperative and brain-penetrant PRMT5 inhibitor [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C130.
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Vukojicic, Nevena, Aleksandar Danicic, Zelia Worman, et al. "Abstract 2075: Highly customizable multi-sample single cell RNA-Seq pipeline on the CGC." Cancer Research 83, no. 7_Supplement (2023): 2075. http://dx.doi.org/10.1158/1538-7445.am2023-2075.
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Abstract Single-cell (sc) transcriptomics has revolutionized our understanding of the biological characteristics and dynamics of cancer development. It can help us identify rare cell subpopulations and understand mechanisms associated with tumor genesis, progression, and response to therapy. The most important step in the analyses of any scRNA-seq dataset is subpopulation identification, usually performed via unsupervised clustering, followed by gene marker identification. We created a highly customizable workflow for sc data analysis, implemented in Common Workflow Language (CWL) on the Cancer Genomics Cloud (CGC) platform. The NCI-funded CGC platform, powered by Seven Bridges, provides a collaborative cloud base computation infrastructure that collocates computation, over 750 bioinformatics workflows, and 3+ PB data to researchers, making the analysis of large datasets accessible from any environment. The “Multi-Sample Clustering and Gene Marker Identification with Seurat 4.1.0” workflow comprises the following steps: Loading scRNA-seq Expression Datasets, Quality Control and Preprocessing, and Clustering and Identification of Gene Markers. Our solution supports gene-cell count matrices generated by several commonly used quantifiers (for example, Cell Ranger counts, Salmon Alevin, Kallisto BUStools, STAR) from single or multiple sc datasets from different batches, as well as single or multiple single-cell samples combined in a single SingleCellExperiment object. The versatility of the pipeline is obtained using several implemented options in each of the steps. Quality control can be performed manually or automatically using several options for normalization (LogNormalize, Deconvolution, SCnorm and Linnorm) and for batch effect correction (Seurat and Harmony). For clustering, the pipeline uses Seurat's graph-based approach, with options for different clustering resolutions. After performing identification of gene markers for each cluster, a researcher can test differential expression using various packages including wilcox, bimod, roc, and DESeq2. Here, we demonstrate the application of this workflow to a typical sc analysis, by processing an open access dataset of 61k cells isolated from embryonal mouse pons and forebrain, two major brain tumor locations. We used different clustering resolutions to achieve different degrees of granularity and identified cluster-specific marker genes used to identify vulnerable cell populations. To enable researchers to use this analysis as a guideline, we made this analysis available as a public project. Further development of single-cell sequencing techniques will undoubtedly improve our understanding of tumor biology and highlight promising drug targets. CGC’s cloud base computation infrastructure, along with numerous available cancer datasets and easy-to-use single-cell data processing workflows, among others, will be instrumental in this process. Citation Format: Nevena Vukojicic, Aleksandar Danicic, Zelia Worman, Rowan Beck, Dalibor Veljkovic, Marko Matic, Jack DiGiovanna, Brandi Davis-Dusenbery. Highly customizable multi-sample single cell RNA-Seq pipeline on the CGC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2075.
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Tripodi, Lorella, Emanuele Sasso, Sara Feola, et al. "Systems Biology Approaches for the Improvement of Oncolytic Virus-Based Immunotherapies." Cancers 15, no. 4 (2023): 1297. http://dx.doi.org/10.3390/cancers15041297.
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Oncolytic virus (OV)-based immunotherapy is mainly dependent on establishing an efficient cell-mediated antitumor immunity. OV-mediated antitumor immunity elicits a renewed antitumor reactivity, stimulating a T-cell response against tumor-associated antigens (TAAs) and recruiting natural killer cells within the tumor microenvironment (TME). Despite the fact that OVs are unspecific cancer vaccine platforms, to further enhance antitumor immunity, it is crucial to identify the potentially immunogenic T-cell restricted TAAs, the main key orchestrators in evoking a specific and durable cytotoxic T-cell response. Today, innovative approaches derived from systems biology are exploited to improve target discovery in several types of cancer and to identify the MHC-I and II restricted peptide repertoire recognized by T-cells. Using specific computation pipelines, it is possible to select the best tumor peptide candidates that can be efficiently vectorized and delivered by numerous OV-based platforms, in order to reinforce anticancer immune responses. Beyond the identification of TAAs, system biology can also support the engineering of OVs with improved oncotropism to reduce toxicity and maintain a sufficient portion of the wild-type virus virulence. Finally, these technologies can also pave the way towards a more rational design of armed OVs where a transgene of interest can be delivered to TME to develop an intratumoral gene therapy to enhance specific immune stimuli.
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Liu, Jian-Guo, Min Tang, Li Wang, and Zhennan Zhou. "Analysis and computation of some tumor growth models with nutrient: From cell density models to free boundary dynamics." Discrete & Continuous Dynamical Systems - B 24, no. 7 (2019): 3011–35. http://dx.doi.org/10.3934/dcdsb.2018297.
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D'Antongiovanni, Vanessa, Serena Martinelli, Susan Richter, et al. "The microenvironment induces collective migration in SDHB-silenced mouse pheochromocytoma spheroids." Endocrine-Related Cancer 24, no. 10 (2017): 555–64. http://dx.doi.org/10.1530/erc-17-0212.
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Pheochromocytomas (Pheos) and paragangliomas (PGLs) are neuroendocrine tumors. Approximately 30–40% of Pheos/PGLs are due to germline mutations in one of the susceptibility genes, including those encoding the succinate dehydrogenase subunits A-D (SDHA-D). Up to 2/3 of patients affected bySDHBmutated Pheo/PGL develop metastatic disease with no successful cure at present. Here, for the first time, we evaluated the effects ofSDHBsilencing in a three dimension (3D) culture using spheroids of a mouse Pheo cell line silenced or not (wild type/wt/control) for the SDHB subunit. We investigated the role of the microenvironment on spheroid growth and migration/invasion by co-culturingSDHB-silenced or wt spheroids with primary cancer-activated fibroblasts (CAFs). When spheroids were co-cultured with fibroblasts,SDHB-silenced cells showed a significant increase in matrigel invasion as demonstrated by the computation of the migratory areas (P < 0.001). Moreover, cells detaching from theSDHB-silenced spheroids moved collectively, unlike the cells of wt spheroids that moved individually. Additionally,SDHB-silenced spheroids developed long filamentous formations along which clusters of cells migrated far away from the spheroid, whereas these structures were not present in wt spheroids. We found that lactate, largely secreted by CAFs, plays a specific role in promoting migration only ofSDHB-silenced cells. In this study, we demonstrated thatSDHBsilencingper seincreases tumor cell migration/invasion and that microenvironment, as represented by CAFs, plays a pivotal role in enhancing collective migration/invasion in PheoSDHB-silenced tumor cells, suggesting their role in increasing the tumor metastasizing potential.
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Liu, Francine, Andrew Zhai, Ozge Yoluk, et al. "Abstract PO5-27-05: Computational design and validation of a novel peptide-drug conjugate for treatment of triple negative breast cancer." Cancer Research 84, no. 9_Supplement (2024): PO5–27–05—PO5–27–05. http://dx.doi.org/10.1158/1538-7445.sabcs23-po5-27-05.
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Abstract Sortilin (SORT1) is a member of the vacuolar protein sorting 10 protein (Vps10p) family that functions as a receptor regulating peptide and protein trafficking between the plasma membrane, lysosomes, and trans-golgi network. As a cell surface receptor, SORT1 is able to mediate efficient endocytosis of extracellular ligands to the lysosomal compartment. Numerous reports have identified enriched SORT1 expression in a variety of tumor types, including triple-negative breast cancer (TNBC), a subtype of breast cancer associated with aggressive clinical behavior and poor disease outcomes. We sought to exploit SORT1-dependent internalization of peptides as a platform for rapid and specific chemotherapy delivery into TNBC cells. Using ProteinStudio (our proprietary computation-enabled design capabilities), we generated high-affinity SORT1 targeting peptides that exhibit efficient receptor dependent internalization and lysosomal localization. Alternative computational approaches such as AlphaFold2 failed to recapitulate the peptide design. Peptide drug conjugates (PDCs) were generated via a linkage strategy that combines our designed peptides to the antimitotic agent monomethyl auristatin E (MMAE). Our PDC molecules exhibit potent tumor regression in a MDA-MB-231 TNBC cell derived xenograft model, thereby highlighting the potential of SORT1-engaging PDCs as an efficacious targeted chemotherapeutic delivery strategy. Citation Format: Francine Liu, Andrew Zhai, Ozge Yoluk, Aron Broom, Tracy Stone, Glenn Butterfoss, Serban Popa, Tianyu Li, Lucas Siow, Christopher Ing, David White. Computational design and validation of a novel peptide-drug conjugate for treatment of triple negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-27-05.
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Oon, Ming Liang, Jing Quan Lim, Bernett Lee, et al. "T-Cell Lymphoma Clonality by Copy Number Variation Analysis of T-Cell Receptor Genes." Cancers 13, no. 2 (2021): 340. http://dx.doi.org/10.3390/cancers13020340.
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T-cell lymphomas arise from a single neoplastic clone and exhibit identical patterns of deletions in T-cell receptor (TCR) genes. Whole genome sequencing (WGS) data represent a treasure trove of information for the development of novel clinical applications. However, the use of WGS to identify clonal T-cell proliferations has not been systematically studied. In this study, based on WGS data, we identified monoclonal rearrangements (MRs) of T-cell receptors (TCR) genes using a novel segmentation algorithm and copy number computation. We evaluated the feasibility of this technique as a marker of T-cell clonality using T-cell lymphomas (TCL, n = 44) and extranodal NK/T-cell lymphomas (ENKTLs, n = 20), and identified 98% of TCLs with one or more TCR gene MRs, against 91% detected using PCR. TCR MRs were absent in all ENKTLs and NK cell lines. Sensitivity-wise, this platform is sufficiently competent, with MRs detected in the majority of samples with tumor content under 25% and it can also distinguish monoallelic from biallelic MRs. Understanding the copy number landscape of TCR using WGS data may engender new diagnostic applications in hematolymphoid pathology, which can be readily adapted to the analysis of B-cell receptor loci for B-cell clonality determination.
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Soloff, Adam C., Rebecca A. Stanton, Nicholas M. Radio, et al. "Neuropilin-2 Isoforms Regulate Distinct Functions of Tumor-associated Macrophages in Breast Cancer." Journal of Immunology 202, no. 1_Supplement (2019): 187.23. http://dx.doi.org/10.4049/jimmunol.202.supp.187.23.
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Abstract Introduction Neuropilins are neural guidance molecules which contribute to tissue development. We have shown that the two isoforms of neuropilin-2 endow opposing functionality to tumor cells due to distinct signaling pathways, with Nrp2b promoting metastatic behavior. Due to the role of macrophages (Mθ) in organogenesis and metastasis, we examine the role of Nrp2 isoforms in these cells. Methods Stable shRNA knockdown of Nrp2a or Nrp2b in Raw264.7 Mθ were generated. Phagocytosis, cytokine production, and migration were assessed in knockdowns in response to stimuli (TGFβ, HGF, VEGF, IL-10, IFNγ, LPS, β-glucan). Nrp2 isoforms in Mθ from mouse mammary tissue or EO771-induced mammary tumors were measured by FACS and RT-PCR. Mθ were phenotyped via FACS for wound-healing or inflammatory markers. Single-cell (sc)qPCR for a 96 gene panel examining components of signaling pathways, autophagy, metabolism, and pro/anti-tumor responses was performed on 576 CD11b+F4/80+ TAMs FACS-sorted from EO771 tumors. Results Nrp2b expression was significantly upregulated in TAMs compared to Mθ of the blood, spleen, or mammary tissues. 56% of the scqPCR transcripts analyzed were significantly altered in Nrp2bHigh vs. Nrp2bLow TAMs, and computation analysis (PCA/tSNE) revealed two distinct TAM subsets enriched for Nrp2b. Nrp2b+ Raw264.7 cells showed decreased ability to phagocytose tumor cells, but increased rates of division and migration in response to growth factors compared to Nrp2a+ counterparts. Conclusions We demonstrate, for the first time, that the principle neuropilin-2 isoforms are present in Mθ, regulate unique functionality, and that Nrp2b+ TAMs are both upregulated in mammary tumors and represent a phenotypically unique subtype.
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Bryan, Cassie M., Gabriel J. Rocklin, Matthew J. Bick, et al. "Computational design of a synthetic PD-1 agonist." Proceedings of the National Academy of Sciences 118, no. 29 (2021): e2102164118. http://dx.doi.org/10.1073/pnas.2102164118.
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Programmed cell death protein-1 (PD-1) expressed on activated T cells inhibits T cell function and proliferation to prevent an excessive immune response, and disease can result if this delicate balance is shifted in either direction. Tumor cells often take advantage of this pathway by overexpressing the PD-1 ligand PD-L1 to evade destruction by the immune system. Alternatively, if there is a decrease in function of the PD-1 pathway, unchecked activation of the immune system and autoimmunity can result. Using a combination of computation and experiment, we designed a hyperstable 40-residue miniprotein, PD-MP1, that specifically binds murine and human PD-1 at the PD-L1 interface with a Kd of ∼100 nM. The apo crystal structure shows that the binder folds as designed with a backbone RMSD of 1.3 Å to the design model. Trimerization of PD-MP1 resulted in a PD-1 agonist that strongly inhibits murine T cell activation. This small, hyperstable PD-1 binding protein was computationally designed with an all-beta interface, and the trimeric agonist could contribute to treatments for autoimmune and inflammatory diseases.
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Kirson, Eilon David, Moshe Giladi, Rosa S. Schneiderman, et al. "Effect of tumor-treating fields on DNA repair in cancer cell lines." Journal of Clinical Oncology 31, no. 15_suppl (2013): e22138-e22138. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.e22138.
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e22138 Background: TTFields Therapy is an antimitotic treatment modality approved by FDA for the treatment of patients with recurrent glioblastoma (GBM). TTFields act by disruption of spindle microtubule arrangement during metaphase and interference with cytokinesis during anaphase and telophase. These effects are the result of rotation of charged and/or polar macromolecules in the direction of the applied antimitotic fields. We hypothesized that the negatively charged, double stranded DNA fragments induced by ionizing radiation (RT) or ultraviolet light (UV) undergo similar rotation. Double strand break repair relies on proper alignment of the strands during the process of homologous recombination. Thus application of TTFields during the DNA repair process holds the potential of interfering with normal DNA repair. Methods: Cancer cells (786-O renal cell carcinoma) were exposed to TTFields for various durations up to 4 hours after UV or RT treatment. The extent of DNA repair over time was evaluated using the alkaline comet assay (Trevigen, USA). This assay allows the computation of the relative proportion of intact DNA strands and DNA fragments in individual cells after inducing DNA breaks. Results: Exposure of UV treated cells to TTFields for 4 hours led to a significant increase in the content of DNA fragments per cell compared to the content without TTFields exposure (45 + 14%; p=0.012). This increase was accompanied by a significant decrease in the intact DNA content per cell compared to the content of cells not exposed to TTFields (47 + 14%; p=0.005). Inhibition of DNA repair was apparent 1-4 hours after irradiation depending on the extent of DNA damage. Similar results were seen after exposure of the cultures to 2Gy RT (17% increase in DNA fragment content and 14% decrease in intact DNA content at 4 hours). Interestingly, while TTFields did not lead to any DNA damage when applied alone, the application of TTFields for one hour after UV exposure led to a 27 + 29% (p=0.02) increase in the extent of the DNA damage (fragment content). Conclusions: This is the first demonstration that, in addition to its known anti-mitotic effect, TTFields Therapy also inhibits DNA repair and may thus lead to an increase in the cytotoxic effects of therapeutic irradiation.
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Yu, Jin-Hai, Dong-Xiang Wu, Zhi-Pu Yu, et al. "New e:b-Friedo-Hopane Type Triterpenoids from Euphorbia peplus with Simiarendiol Possessing Significant Cytostatic Activity against HeLa Cells by Induction of Apoptosis and S/G2 Cell Cycle Arrest." Molecules 24, no. 17 (2019): 3106. http://dx.doi.org/10.3390/molecules24173106.
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Seven rare e:b-friedo-hopane-type triterpenoids including four new (1–4) and three known (5–7) ones with 5 being first reported as a natural product, together with five other known triterpenoids (8–12), were isolated from the nonpolar fractions of the ethanolic extract of Euphorbia peplus. Structural assignments for these compounds were based on spectroscopic analyses and quantum chemical computation method. The structural variations for the C-21 isopropyl group, including dehydrogenation (1 and 3) and hydroxylation at C-22 (simiarendiol, 2), were the first cases among e:b-friedo-hopane-type triterpenoids. Simiarendiol (2) bearing a 22-OH showed significant cytostatic activity against HeLa and A549 human tumor cell lines with IC50 values of 3.93 ± 0.10 and 7.90 ± 0.31 μM, respectively. The DAPI staining and flow cytometric analysis revealed that simiarendiol (2) effectively induced cell apoptosis and arrested cell cycle at the S/G2 phases in a dose-dependent manner in HeLa cells.
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Ying, Haiyan, Wenqun Xin, Haibing Deng, et al. "Abstract LB317: Discovery and characterization of a next-generation FGFR inhibitor overcoming FGFR resistant mutations." Cancer Research 83, no. 8_Supplement (2023): LB317. http://dx.doi.org/10.1158/1538-7445.am2023-lb317.
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Abstract Introduction: FGFRs play important roles in cancer development and inhibition of FGFR could disrupt tumor cell proliferation and growth. Four selective FGFR inhibitors have been approved (erdafitinib, pemigatinib, infigratinib, and futibatinib) and several others are in clinical development. Unfortunately upon treatment with these first-generation FGFR inhibitors, acquired resistance often develops and is frequently associated with the emergence of secondary FGFR2/3 kinase domain mutations. Therefore, selectively targeting FGFR2/3 as well as their resistant mutations may render a second-generation treatment approach for the refractory/relapsed patients. Using advanced computation-aided structural analysis and medicinal chemistry design, we have discovered a novel, next-generation, and highly selective FGFR inhibitor, ABSK121. This novel inhibitor demonstrated robust anti-tumor activity in FGFR-dependent tumor models with strong activities against not only de novo but also acquired resistant mutations. Method: ABSK121 was evaluated in biochemical and cellular proliferation experiments for its inhibition on wile type FGFR enzymatic activity and FGFR-dependent cancer cell proliferation. Its potency against FGFR mutations was also analyzed in relevant biochemical and cellular experiments. Efficacy studies were conducted in multiple tumor models to confirm its in vivo activities. Preliminary selectivity profile and ADME profiles were also evaluated. Results: ABSK121 inhibited wild type FGFRs with IC50&lt;10 nM in biochemical assay. ABSK121 also displayed great potency against resistant kinase domain mutations. In cell lines harboring FGFR amplification, fusions, or resistant mutations, ABSK121 demonstrated strong anti-proliferation activity as well as strong inhibition of FGFR downstream signaling activities. In preclinical in vivo studies, oral administration of ABSK121 strongly inhibited the growth of subcutaneous xenograft tumors dependent on wild type or resistant mutant FGFR. Suppression of tumor growth was dose-dependent and well correlated with pharmacodynamic inhibition of FGFR signaling. ABSK121 also showed great kinase selectivity with no CYP or hERG inhibition. Conclusion: ABSK121, presented here by Abbisko Therapeutics, is a highly potent, selective, and next-generation small molecule FGFR inhibitor with great potency against resistant FGFR mutations. Its superior profile supports fast-track preclinical and clinical development. Citation Format: Haiyan Ying, Wenqun Xin, Haibing Deng, Yuan Zhao, Hongping Yu, Zhui Chen, Yao-chang Xu. Discovery and characterization of a next-generation FGFR inhibitor overcoming FGFR resistant mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB317.
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Emadi, Ali, Tomasz Lipniacki, Andre Levchenko, and Ali Abdi. "Single-Cell Measurements and Modeling and Computation of Decision-Making Errors in a Molecular Signaling System with Two Output Molecules." Biology 12, no. 12 (2023): 1461. http://dx.doi.org/10.3390/biology12121461.
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A cell constantly receives signals and takes different fates accordingly. Given the uncertainty rendered by signal transduction noise, a cell may incorrectly perceive these signals. It may mistakenly behave as if there is a signal, although there is none, or may miss the presence of a signal that actually exists. In this paper, we consider a signaling system with two outputs, and introduce and develop methods to model and compute key cell decision-making parameters based on the two outputs and in response to the input signal. In the considered system, the tumor necrosis factor (TNF) regulates the two transcription factors, the nuclear factor κB (NFκB) and the activating transcription factor-2 (ATF-2). These two system outputs are involved in important physiological functions such as cell death and survival, viral replication, and pathological conditions, such as autoimmune diseases and different types of cancer. Using the introduced methods, we compute and show what the decision thresholds are, based on the single-cell measured concentration levels of NFκB and ATF-2. We also define and compute the decision error probabilities, i.e., false alarm and miss probabilities, based on the concentration levels of the two outputs. By considering the joint response of the two outputs of the signaling system, one can learn more about complex cellular decision-making processes, the corresponding decision error rates, and their possible involvement in the development of some pathological conditions.
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Wu, Ran, Puwei Yuan, Yang Xie, et al. "Abstract 1871: Discovery and characterization of NXV01c, an EGFR × cMET bispecific nanobody drug conjugate with potent anti-tumor activity." Cancer Research 84, no. 6_Supplement (2024): 1871. http://dx.doi.org/10.1158/1538-7445.am2024-1871.
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Abstract EGFR and cMET are proven cancer targets co-expressed in diverse tumor types. EGFR × cMET bispecific antibody has been approved for the treatment of NSCLC, supporting a simultaneous targeting strategy. In addition to this dual targeting benefit, bispecific antibody drug conjugates (ADCs) targeting EGFR and cMET have also been developed to further improve anti-tumor activity and tissue selectivity. Sufficient target affinity, good cellular internalization and high tumor infiltration are critical for an ADC to mediate therapeutic activity. To this end, we developed the first EGFR × cMET bispecific nanobody conjugated with monomethyl auristatin E (MMAE) as payload (NXV01c). Lead nanobodies against EGFR and cMET were respectively selected from immune libraries by phage display, followed by highly efficient humanization and optimization by neoX’s computation platform. The bispecific nanobody with Fc (NXV01) was constructed by “knobs-into-holes” heterodimerization and then homogeneously conjugated with MMAE via a lysosomal cleavable valine-citrulline dipeptide linker. The resulting bispecific nanobody drug conjugate (NDC), NXV01c, was evaluated in multiple tumor cell lines and tumor xenograft models. NXV01, the pre-conjugate bispecific nanobody, bound EGFR and cMET with nanomolar potency (BLI) and inhibited the phosphorylation of cellular EGFR and cMET with nanomolar IC50 (ELISA). Moreover, it did not activate cellular cMET. Importantly, the NDC NXV01c is highly homogeneous: it has an average DAR of 3.87 and &gt;95% of NXV01c has a DAR of 4. To examine stability of conjugation, NXV01C was incubated in human plasma (37°C) for 14 days, the maximum free drug release rate (by LC/MS/MS) is 0.68%, which is much lower than that of DS8201. In vitro, NXV01c was rapidly internalized into H1975 cells which co-expressed EGFR and cMET. It inhibited the growth of H1975 (lung) and SNU5 (gastric) cancer cells with picomolar activity but spared normal keratinocytes. NXV01c also inhibited the proliferation of additional cell lines derived from lung, gastric, esophageal, and liver cancer, and the level of inhibition positively associated with the expression density of both targets. In an H1975 cell line-derived xenograft model, NXV01C exhibited potent and dose-dependent anti-tumor activity. Treatments at 3 and 10 mg/kg once per week for 2 weeks led to shrinkage and complete regression of tumor, respectively. In patient-derived xenograft models of NSCLC and esophageal cancer, NXV01C led to tumor regression and elimination without noticeable toxic effects. EGFR × cMET bispecific nanobody drug conjugate NXV01c has favorable drug-like properties and demonstrated superior anti-tumor effect in vitro and in vivo. The results suggest NXV01C can be an effective solution for EGFR/cMET bearing tumors commonly found in diverse malignancies. Citation Format: Ran Wu, Puwei Yuan, Yang Xie, Jianxiu Guo, Fei Zhang, Fan Liu, Taylor B. Guo. Discovery and characterization of NXV01c, an EGFR × cMET bispecific nanobody drug conjugate with potent anti-tumor activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1871.
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Sade, Hadassah, Ansh Kapil, Philipp Wortmann, et al. "Abstract 468: Quantitative assessment of IHC using computational pathology allows superior patient selection for biomarker-informed patients." Cancer Research 82, no. 12_Supplement (2022): 468. http://dx.doi.org/10.1158/1538-7445.am2022-468.
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Abstract Many targeted cancer therapies rely on biomarkers, which are assessed by standard pathologist scoring of immunohistochemically stained tissue. However, this process is subjective, semi-quantitative and does not assess expression heterogeneity. A quantitative method to measure IHC markers might therefore significantly improve patient selection particularly of proteins expressed at low levels. To address these challenges, we have developed the Quantitative Continuous Scoring (QCS) that deploys the power of fully supervised Deep Learning (DL) algorithms to provide objective and continuous data of biomarkers in digitized IHC whole slide images (WSI). The two DL-based algorithms, developed using pathologist input as the ground truth, identify areas of invasive tumor and segment each individual tumor cell across the WSI into pixels that represent cell nuclei, cytoplasm and/or membrane. This allows to compute biomarker expression as mean Optical Density (OD) in each of these subcellular compartments based on the Hue-Saturation-Density (HSD) model. Of note, this also allows computation of the spatial distribution of tumor cells across the WSI. The measured OD for each cell is aggregated as a histogram to quantitative continuous readouts for each patient sample. The method’s ability to accurately detect low expression range facilitates selection of antibody clones for IHC assays, has been successfully used to delineate mode of action and PK/PD mechanisms, has provided surrogate markers of spatial expression heterogeneity to predict potential bystander activity and has facilitated marker co-expression analysis to inform rational combination therapies. In retrospective clinical trials analysis, QCS showed superior performance in identifying a patient population gaining maximum treatment benefit. QCS-based quantification of PD-L1 membrane expression was able to stratify anti-PD-L1 treated late-stage non-small cell lung cancer (NSCLC) patients [NCT01693562] with a higher prevalence and more significant log rank p-value (64%, p=0.0001) for OS compared to pathologist TPS (59%, p=0.01). In summary, we describe a computational pathology-based approach for precise biomarker quantification and superior patient selection with broad applicability and the potential to transform pathology, thus addressing one of the key challenges of precision oncology. Citation Format: Hadassah Sade, Ansh Kapil, Philipp Wortmann, Andreas Spitzmueller, Nicolas Triltsch, Lina Meinecke, Susanne Haneder, Anatoliy Shumilov, Jan Lesniak, Valeria Bertani, Tze-Heng Tan, Ana Hidalgo-Sastre, Simon Christ, Andrea Storti, Regina Alleze, Dasa Medrikova, Jessica Chan, Simon Lanzmich, Markus Schick, Guenter Schmidt, J. Carl Barrett. Quantitative assessment of IHC using computational pathology allows superior patient selection for biomarker-informed patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 468.
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Gopalan, Vishaka, and Sridhar Hannenhalli. "Abstract LB275: Transcriptomic reversal analysis yields cytokines and drugs mediating tumor microenvironmental reprogramming during cancer progression and therapy response." Cancer Research 83, no. 8_Supplement (2023): LB275. http://dx.doi.org/10.1158/1538-7445.am2023-lb275.
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Abstract Recent computational work links therapy response to a drug based on the drug’s ability to reverse a tumor’s transcriptome towards a healthy state. This idea of reversal has been used to mine databases of cell-line transcriptional responses against drug libraries to prioritize anti-cancer drugs. However, there are two key shortcomings in these approaches: (1) though cytokines and their receptors are proposed as modulators of therapy response, there is no reversal-based method to prioritize cytokines as potential drugs or targets, and (2) responses of microenvironmental cell types to drugs, which dictate therapy response, have not been considered. We address these limitations by exploiting recent databases of cytokine transcriptional response and single-cell RNA-seq datasets of patient responses to cancer therapies. We first used a novel approach to derive drug response signatures from LINCS data that retained the coordinated nature of gene expression changes occurring during treatment. We then used these signatures to compute a transcriptional reversal score that ranks drugs by their ability to reverse TCGA RNA-seq profiles of a tumor towards its corresponding normal in GTEx. We found that FDA-approved drugs in prostate, lung, colorectal and breast adenocarcinomas have a significantly higher reversal potential than unapproved drugs, and that these drugs are more effective at in vitro cell killing amongst CTRP and GDSC cell viability measurements. Next, we extended our signature derivation and reversal computation approach to find cytokines in the CytoSig database that can reverse TCGA RNA-seq profiles. We found that the higher the reversal potential of a cytokine, the greater its association with better overall patient survival. In particular, our approach revealed the IL10 family and IL24 as potentially therapeutic cytokines based on their predicted ability to reverse cell states across tumor types and indeed found them to be associated with better overall and progression-free survival in the TCGA cohort. Finally, in two clinical cohorts where RNA-seq was carried out on breast cancer and multiple myeloma patients before and after therapy, cell types within the tumor microenvironment of responders showed a stronger reversal towards a healthy state compared to non-responders. Altogether, our work establishes the importance of transcriptional reversal in therapy response, particularly the role of microenvironmental transcriptional alterations. This allows us to refine the reversal principle based on pan-cell type transcriptional effects and to identify cytokines that mediate patient survival as a new class of drugs and drug targets. This research was supported by the Intramural Research Program of the NIH, Citation Format: Vishaka Gopalan, Sridhar Hannenhalli. Transcriptomic reversal analysis yields cytokines and drugs mediating tumor microenvironmental reprogramming during cancer progression and therapy response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB275.
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Zhang, Yongxian, Mingming Zhang, Baowei Zhao, et al. "Abstract B151: Discovery and characterization of a novel small molecule brain penetrant PD-L1 inhibitor." Molecular Cancer Therapeutics 22, no. 12_Supplement (2023): B151. http://dx.doi.org/10.1158/1535-7163.targ-23-b151.
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Abstract Introduction: Immunotherapy has revolutionized cancer treatment in the last decade. Several monoclonal PD-1 and PD-L1 antibodies have been approved for treating various cancers. Small molecule PD-L1 inhibitors with brain-penetrating ability may have potential to overcome the limitations of antibodies and bring benefit for patients with intracranial tumors. Leveraging advanced computation-aided structural analysis and medicinal chemistry design, we have successfully discovered an innovative orally available small molecule PD-L1 inhibitor ABSK044. In preclinical experiments, this compound demonstrates robust T-cell activating ability, strong anti-tumor efficacy, and brain-penetrating activity. Method: ABSK044's ability to block PD-1-PD-L1 interaction was evaluated by HTRF assay and cellular luciferase reporter assay. Its biological activity was evaluated in vitro in MLR and in vivo in syngeneic tumor models. Results: ABSK044 strongly inhibits PD-1-PD-L1 interaction with an IC50 less than 1nM in vitro and very potently rescues PD-L1-induced suppression of T cell activation signaling in cells. Furthermore, it efficiently rescues cytokine production in CD8+ T cells suppressed by PD-L1, reaching a level comparable to that of PD-L1 antibodies. In in vivo studies, oral administration of ABSK044 strongly inhibits tumor growth to an extent similar to therapeutic anti-PD-L1 antibodies. Notably, ABSK044 demonstrates excellent brain penetration with a Kp value exceeding 0.4. DMPK and safety profiling demonstrate excellent drug-like properties of ABSK044. Conclusion: ABSK044, presented here by Abbisko Therapeutics, is a highly potent and orally available small molecule PD-L1 antagonist with brain-penetrating activity. Its superior profile supports its fast-track preclinical development. Citation Format: Yongxian Zhang, Mingming Zhang, Baowei Zhao, Hongping Yu, Yao-Chang Xu, Zhui Chen, Haiyan Ying. Discovery and characterization of a novel small molecule brain penetrant PD-L1 inhibitor [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B151.
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Devi, Gayathri R., Dorababu Sannareddy, Alexandra Bennion, et al. "Abstract P3-08-06: Monitoring Lymphovascular Invasion and Tumor Growth of Inflammatory Breast Cancer in a Murine Lymphatic Reporter Window Chamber Model." Cancer Research 83, no. 5_Supplement (2023): P3–08–06—P3–08–06. http://dx.doi.org/10.1158/1538-7445.sabcs22-p3-08-06.
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Abstract Background: Lymphovascular invasion (LVI) is a major route of metastatic dissemination and recent studies indicate its value as an independent prognostic indicator for advanced breast, colorectal, squamous cell, prostate, brain cancers. LVI is a clinicopathological hallmark of inflammatory breast cancer (IBC), an understudied and most lethal breast cancer. IBC is often misdiagnosed due to an absence of a solid mass and its unique presentation of diffuse tumor cell clusters/emboli in the dermal lymphatics. Widely used mammary tumor implantation models coupled with bioluminescence or fluorescence imaging to monitor tumor growth kinetics are ineffective for evaluating spatial and temporal changes in growth and migration patterns of individual tumor cells and clusters within their microenvironmental context. The goal of this study was to develop a murine model to simulate the unique clinicopathological features of IBC patients and to assess both qualitatively and quantitatively local tumor growth, motility, and LVI. Methods: To specifically facilitate visualization of lymphatic and endothelial vessels along with tumor-vessel interactions, we generated a transgenic nude mice model (ProxTom RFP Nu/Nu) wherein, the mice exhibit red, fluorescent lymphatics [tdTomato fluorophore under control of a Prox1 promoter, which encodes a transcription factor (prospero-related homeobox 1) necessary for the formation and maintenance of lymphatic vessels]. Next, we employed a surgical technique, wherein a window chamber is placed on the dorsal skinfold of mice, which allows for microscopic examination of implanted tumor cells and ability to track dynamic changes of the tumor in its local microenvironment from the time of implantation up to 10 days. Patient-derived IBC or PDX stably transfected to express green, red fluorescent and/or dual tagged with luciferase reporters were transplanted in mice bearing window chambers. Intravital fluorescence microscopy and IVIS imaging were used to serially quantify local tumor growth, motility, length density of lymph and blood vessels, and degree of tumor cell lymphatic invasion over 0-140h. Results: Multichannel optical imaging of the window chamber in the ProxTom RFP Nu/Nu mice demonstrated co-localization of IBC tumor cells and lymphatics. Diffuse tumor cells were observed along regions of lymphatic vessels both proximal and distal to the primary tumor site. However, measurement of blood and lymph vessel density showed no significant change over time. Next, these datasets were used for quantitative analysis by setting the tumor cell channel (GFP) at a threshold to count any clusters greater than 50 pixels2 (~0.0013mm2) and with greater than the mean + 2 standard deviations of the background signal while avoiding noise/artifacts from very small regions (&lt;~0.001mm2). This allowed for computation of the total tumor area including average area of each cluster. In addition, the area moment, which describes the basic directional growth pattern of the tumor cells, was quantified by multiplying a cluster distance from the center of mass by its area. Conclusions: A key novel finding from structured illumination imaging data was the observation of LVI occurring early, similar with the clinical presentation in IBC patients. This model was able to effectively track tumor cluster migration. This approach of short-term longitudinal imaging time frame in studying transient or dynamic events of diffuse, collectively migrating tumor cells in the local environment and quantitative analysis of the tumor area, motility and vessel characteristics is an innovation that can be used to investigate other cancer cell types exhibiting LVI. Funding in part by DoD W81XWH-17-1-0297; W81XWH201053 (GRD); ACS Mission Boost grant MBG-20-141-01 (GRD) and NIH grant P30-CA014236 (Imaging Core/GMP) Citation Format: Gayathri R Devi, Dorababu Sannareddy, Alexandra Bennion, Ashlyn Rickard, Douglas C Rouse, Mark W Dewhirst, Gregory M Palmer. Monitoring Lymphovascular Invasion and Tumor Growth of Inflammatory Breast Cancer in a Murine Lymphatic Reporter Window Chamber Model [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-08-06.
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Gustavson, Mark, Markus Schick, Ansh Kapil, Anatoliy Shumilov, Carl Barrett, and Hadassah Sade. "Abstract PO4-26-01: Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine." Cancer Research 84, no. 9_Supplement (2024): PO4–26–01—PO4–26–01. http://dx.doi.org/10.1158/1538-7445.sabcs23-po4-26-01.
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Abstract While targeted cancer therapies often rely on subjective and semi-quantitative visual assessment of protein biomarkers by pathologists through immunohistochemically stained tissue, the transformative force of computational pathology is reshaping healthcare by unleashing unprecedented diagnostic accuracy and unlocking personalized treatments. In recent years, we have established a large integrated computational pathology unit to foster collaboration between interdisciplinary teams of computer scientists, pathologists, molecular biologists, and data scientists. This integration of cutting-edge technologies enabled us to develop a computational pathology approach called Quantitative Continuous Scoring (QCS). QCS deploys the power of Deep Learning (DL) to provide objective and continuous expression data of biomarkers in digitized IHC whole slide images (WSI), particularly of proteins expressed at low levels. While manual scoring of IHC WSIs is limited by subjectivity and semi-quantitative assessment of protein expression, QCS overcomes these limitations with an unprecedented accuracy. QCS utilizes two DL-based algorithms, which we developed fully supervised by using pathologist input as the reference standard. These algorithms identify invasive tumour areas and segment each tumour cell across the WSI into cell nuclei, cytoplasm and membrane. Based on an accurate subcellular segmentation, we can compute biomarker expression, on a continuous scale, as mean Optical Density (OD) in each subcellular compartment based on the Hue-Saturation-Density (HSD) model. Therefore, this approach enables precise detection of the low biomarker expression range with single-cell resolution. Importantly, it also allows the computation of the spatial distribution of tumour cells across the WSI. We have successfully used QCS to drive the selection of antibody clones for IHC assays and to delineate the mode of action and PK/PD mechanisms. Of note, the combination of assessing continuous target expression and capturing the spatial distribution of tumor cells has provided surrogate markers to predict potential bystander activity of antibody drug conjugates (ADCs). This approach outperformed traditional pathologist scoring in identifying patient populations having maximum treatment benefit through retrospective analysis of multiple clinical trials. At present, all computational pathology approaches are developed based on conventional IHC assays that have been optimized for manual scoring. Importantly, we draw a vision in which the assay serves as a critical catalyst for unleashing the full potential of computational pathology by providing high-quality, standardized data inputs. We suggest an approach utilizing orthogonal methods as a reference standard to develop highly sensitive IHC assays, capable of detecting even subtle molecular and cellular changes with precision and exhibiting exceptional specificity for accurately identifying and distinguishing target biomarkers from background noise. In summary, we here describe and discuss a computational pathology-based approach for precise biomarker quantification and superior patient selection with broad applicability and the potential to transform the very fabric of how we diagnose and treat cancer. Citation Format: Mark Gustavson, Markus Schick, Ansh Kapil, Anatoliy Shumilov, Carl Barrett, Hadassah Sade. Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-01.
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R, Usha, and Perumal K. "A modified fractal texture image analysis based on grayscale morphology for multi-model views in MR Brain." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 154–63. https://doi.org/10.11591/ijeecs.v21.i1.pp154-163.
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This paper presents a modified fractal texture feature analysis with the use of grayscale image morphology for automatic image classification of different views in MR brain images into normal and abnormal. This main contribution of this approach is a reduction of the total number of a threshold value, and the number of image decomposition, in which only the number of extract threshold value two or three are enough for tumor region extraction compared to four or more is required in the previous method of SFTA (segmentation based fractal texture analysis). This is achieved by preprocessing of hierarchical transformation technique (HTT), which make use of morphological image transformations with the desired structural element. From this decomposed images, mean, area, fractal dimension and selective shape features are extracted and fed into KNN and ensemble bagged tree classifiers. Finally, some of the post-processing is handled for tumor region extraction and tumor cells computation. It is found that this proposed approach has superior results in the segmentation of diseased tissue from normal tissue and the prediction of image classes in terms of accuracy with the less number of threshold extraction and image decomposition rather than the SFTA algorithm.
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Lee, Alexander, Yang Pan, Aaron Mochizuki, et al. "IMMU-02. NEOANTIGENS ARISING FROM ALTERNATIVE SPLICING EVENTS MAY BE TARGETED BY TUMOR INFILTRATING LYMPHOCYTES IN GLIOBLASTOMAS." Neuro-Oncology 21, Supplement_6 (2019): vi118—vi119. http://dx.doi.org/10.1093/neuonc/noz175.496.
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Abstract INTRODUCTION Alternative splicing, the cellular process that converts premature mRNA to mature mRNA and allows for single genes to produce multiple protein products, is frequently dysregulated in many cancers, including glioblastoma. However, along with non-synonymous mutations in the DNA, altered splicing mechanisms in cancers may produce novel antigens (so-called neoantigens) that distinguish cancer cells from healthy cells and can thus be targeted by the immune system. METHODS We developed a new computation pipeline (IRIS – Isoform peptides from RNA splicing for Immunotherapy targets Screening) that took bulk RNA-sequencing data from 23 glioblastoma patient tumor samples and predicted neoantigens that may arise from alternative splicing events. We prioritized predicted neoantigens that arose in HLA*A02:01 and HLA*A03:01 patients and selected 8 potential neoantigens to generate peptide:MHC Class 1 dextramers. We tested PBMCs and/or ex vivo expanded tumor infiltrating lymphocytes (TIL) from 6 of our glioblastoma patients against these dextramers, sorted for any neoantigen-reactive T cells, and performed single-cell RNAsequencing on the sorted population to determine the TCR sequence. RESULTS Among the 8 predicted neoantigens tested, 7 of the neoantigens were recognized by at least 1 patient’s T cells. 1 HLA*A03:01 epitope was recognized in 3 of the 4 HLA*A03:01 patients tested and this epitope was highly positive in an expanded TIL population, representing 1.7% of all CD3+ CD8+ cells. When we sorted for those neoantigen reactive T cells from the expanded TIL population and performed single-cell RNAsequencing, we found 325 unique T cell clonotypes, but the top 10 clonotypes represented 83.6% of all TCR clonotypes. The most frequent TCR clonotype represented 39.1% of the repertoire and suggests that clonal expansion of a select few TCR clones occurred within the tumor. CONCLUSIONS In total, our data indicates that neoantigens arising from alternative splicing events may represent a potential target for immunotherapy in glioblastoma.
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van Bree, Elise, Carmen Rubio Alarcón, Soufyan Lakbir, et al. "Abstract A020: Structural variants in the pathogenesis of colorectal cancer: The elephant in the room." Cancer Research 82, no. 23_Supplement_1 (2022): A020. http://dx.doi.org/10.1158/1538-7445.crc22-a020.
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Abstract Background: Cancer is caused by somatic DNA alterations, comprising single/small nucleotide variants (SNVs), somatic copy number alterations (SCNAs) and chromosomal rearrangement structural variants (SVs). We previously demonstrated that SVs are recurrently identified in hundreds of genes and are highly prevalent in common fragile site genes, e.g., in MACROD2 in &gt;40% of colorectal cancers (CRCs). However, computational methods that discriminate SV-driver from SV-passenger events are lacking and laboratory methods to detect SVs at nucleotide resolution from routinely obtained formalin-fixed paraffin-embedded (FFPE) tumor tissue material are underdeveloped. Therefore, despite the abundant presence of SVs, knowledge about their biological and clinical impact is limited. Aim: The aim of our studies is to identify genes of which the function is frequently affected by SV, to understand how these genes contribute to CRC pathogenesis, and to translate these SVs into clinically relevant biomarkers. Methods: We made use of publicly available deep whole genome DNA sequencing data and tumor-matched RNA sequencing data from the Hartwig Medical Foundation to develop the algorithm ‘CoBRA’: Computation of Biologically Relevant Alterations. Adenoma-derived organoids were used for CRISPR/Cas9-mediated gene modulation for functional analysis of SV-driver events. Cergentis’ targeted locus capture (FFPE-TLC) technology was used to detect SVs at nucleotide resolution from FFPE material, which were translated into droplet digital PCR (ddPCR) assays for the detection of SVs in cell-free circulating tumor DNA (ctDNA) in liquid biopsies. Results: The CoBRA algorithm associated the presence of SV-events in frequently affected genes to the extent in which genome-wide RNA sequencing data were altered. In this way, CoBRA ranked SV-events in genes according to their putative impact on tumor biology. SVs in MACROD2 ranked among those with the highest impact on tumor biology. Therefore, we generated focal deletions in MACROD2 in adenoma-derived organoids for functional analyses. Moreover, using FFPE tumor tissue material we detected SVs at nucleotide resolution in MACROD2 and three other genes in 21 out of 29 patients. SVs were verified by PCR on tumor tissue and subsequently translated into ddPCR biomarker assays for detection of SVs in ctDNA in blood from the same patients. Conclusions: We developed the computational method CoBRA and succeeded to detect SVs with high impact on tumor biology. These SVs are prioritized for functional analysis in pre-malignant adenoma-derived organoids; for targeted detection in routinely obtained FFPE tumor tissue material; and for translation into liquid biopsy ctDNA assays. Proof of concept was delivered for MACROD2. Our novel computational and laboratory methodologies provide valuable tools to effectively explore the biological and clinical impact of SVs, which will contribute to our understanding of these common recurrent somatic alterations in CRC and their translation into clinically relevant biomarker applications. Citation Format: Elise van Bree, Carmen Rubio Alarcón, Soufyan Lakbir, Ellen Stelloo, Caterina Buranelli, Amber Hondema, Iris van 't Erve, Daan Vessies, Pien Delis-van Diemen, Marianne Tijssen, Anne Bolijn, Mirthe Lanfermeijer, Dorothe Linders, Joost Swennenhuis, Daan van den Broek, Jaap Heringa, Gerrit Meijer, Beatriz Carvalho, Harma Feitsma, Sanne Abeln, Remond J. A. Fijneman. Structural variants in the pathogenesis of colorectal cancer: The elephant in the room [abstract]. In: Proceedings of the AACR Special Conference on Colorectal Cancer; 2022 Oct 1-4; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_1):Abstract nr A020.
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Sun, Jijia, Baocheng Liu, Ruirui Wang, Ying Yuan, Jianying Wang, and Lei Zhang. "Computation-Based Discovery of Potential Targets for Rheumatoid Arthritis and Related Molecular Screening and Mechanism Analysis of Traditional Chinese Medicine." Disease Markers 2022 (June 4, 2022): 1–19. http://dx.doi.org/10.1155/2022/1905077.
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This study is aimed at screening potential therapeutic ingredients in traditional Chinese medicine (TCM) and identifying the key rheumatoid arthritis (RA) targets using computational simulations. Data for TCM-active ingredients with clear pharmacological effects were collected. Absorption, distribution, metabolism, excretion, and toxicity were evaluated. Potential RA targets were identified using the Gene Expression Omnibus (GEO) database, protein–protein interaction network, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and potential TCM ingredients using AutoDock Vina. To examine the mechanisms underlying small molecules, target prediction, Gene Ontology, KEGG, and network modeling analyses were conducted; the effects were verified in rat synovial cells using cell proliferation assay. The activities of tumor necrosis factor TNF-α and IL-1β and alterations in cellular target protein levels were detected by ELISA and Western blotting, respectively. In total, data for 432 TCM active ingredients with clear pharmacological effects were obtained. Five critical RA-related genes were identified; CCL5 and CXCL10 were selected for molecular docking. Target prediction and network-based proximity analysis showed that dioscin could modulate 22 known RA clinical targets. Dioscin, asiaticoside, and ginsenoside Re could effectively inhibit in vitro cell proliferation and secretion of TNF-α and IL-1β in RA rat synovial cells. Using bioinformatics and computer-aided drug design, the potential small anti-RA molecules and their mechanisms of action were comprehensively identified. Dioscin could significantly inhibit proliferation and induce apoptosis in RA rat synovial cells by reducing TNF-α and IL-1β secretion and inhibiting abnormal CCL5, CXCL10, CXCR2, and IL2 expression.
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Kode, Jyoti, Jitendra Maharana, K. Nirmal Kumar, et al. "Abstract 4222: Phenstatin based indole linked chalcone compound 9a exhibits anti-oral cancer activity through regulating NLRP3 inflammasome innate immune pathway." Cancer Research 82, no. 12_Supplement (2022): 4222. http://dx.doi.org/10.1158/1538-7445.am2022-4222.
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Abstract Oral cancer is the sixth most prevalent malignancy in the world and oral squamous cell carcinoma accounts for majority of all oral malignancies. Upregulated NLRP3 inflammasome innate immune pathway is of importance to tumor development. Current efforts are being focused on identifying small molecules that exhibit anti-cancer activity as inflammasome pathway inhibitors. Our previously published work on phenstatin based indole linked chalcone scaffold 9a with 1-methyl, 2- and 3-methoxy substituents in the aromatic ring revealed 9a as an anti-oral cancer compound. 9a was found to act through inhibiting tubulin polymerization at protein level, using in vitro models oral cancer cell line/spheroid cells and in vivo animal oral cancer xenograft model. 9a had also shown significant reduction in radiolabeled-glucose uptake in xenograft mice model. Current study was undertaken to evaluate if small molecule inhibitor 9a acts through regulating the NLRP3 pathway. Using computation approach, we predicted the binding of 9a with NLRP3NACHT domain, which revealed stable interaction as similar to that exhibited by NLRP3 inhibitors MCC950 and ADP. Further, we checked immune mechanistic activity of 9a on NLRP3 pathway intermediates in oral cancer cells. AW13516 cell line which was human tongue squamous tumor-derived cell line; indigenously developed at our department previously, was activated for NLRP3 inflammasome pathway using LPS and activator Nigericin in presence of 9a. MCC950 treated cells and only LPS or LPS/Nigericin treated cells served as controls. NLRP3, caspase-1 and mitochondrial protein expression was analyzed in these cells by immunofluorescence (IF) and found to be increased upon LPS/NIG activation and reduced significantly upon MCC950 and 9a treatment. Activation led to puncta formation which was found diffused after MCC950/9a treatment. Similarly treated AW13516 cells were also validated using western blotting experiments. Expression of 118kDa NLRP3 protein was found increased upon inflammasome activation that was significantly reduced in 9a treated cells and reduction was dose dependent. 9a had shown significant reduction in oral cancer xenograft of AW13516 in NOD-SCID mice model. We tested formalin-fixed paraffin sections of these tumors by immunohistochemistry. Tumor areas were assessed for expression of NLRP3 pathway markers and there was significant reduction in NLRP3, Caspase-1, GSDMD and IL-1β in 9a treated tumors compared to control tumors. This reduction was at par with that shown by Adriamycin. Summarizingly, 9a has been found to be regulating inflammatory immune mechanisms and can be developed further as immunomodulatory anti-cancer agent. Since macrophages are major resource immune cells of NLRP3, further studies are underway to test 9a on macrophages from nlrp3-/- and caspase-/- mice in comparison with normal mice. Citation Format: Jyoti Kode, Jitendra Maharana, K. Nirmal Kumar, Trupti Pradhan, Arvind Ingle, Madan Barkume, Meena Patkar, Namitha Thampi, Ankita Patil, Anand Vaibhaw, Jeshma Kovvuri, Ahmed Kamal. Phenstatin based indole linked chalcone compound 9a exhibits anti-oral cancer activity through regulating NLRP3 inflammasome innate immune pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4222.
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Pérez, Liliana, John E. Kerrigan, Xiaojin Li, and Huizhou Fan. "Substitution of methionine 435 with leucine, isoleucine, and serine in tumor necrosis factor alpha converting enzyme inactivates ectodomain shedding activity." Biochemistry and Cell Biology 85, no. 1 (2007): 141–49. http://dx.doi.org/10.1139/o06-179.
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Tumor necrosis factor alpha (TNF-α) converting enzyme (TACE) is a zinc metalloprotease that has emerged as a general sheddase, which is responsible for ectodomain release of numerous membrane proteins, including the proinflammatory cytokine TNF-α, the leukocyte adhesin l-selectin and epidermal growth factor receptor ligand-transforming growth factor α (TGF-α), and related family members. Structurally, TACE belongs to a large clan of proteases, designated the metzincins, because TACE possesses a conserved methionine (Met435), frequently referred to as the met-turn residue, in its active site. A vital role of this residue in the function of TACE is supported by the fact that cells expressing the M435I TACE variant are defective in ectodomain shedding. However, the importance of Met435 in TACE appears to be uncertain, since another metzincin, matrix metalloprotease-2, has been found to be enzymatically fully active with either leucine or serine in place of its met-turn residue. We constructed TACE mutants with leucine or serine in place of Met435 to further examine the role of the met-turn residue in TACE-mediated ectodomain cleavage. Similar to the M435I TACE mutant, both the M435L and M435S constructs are defective in cleaving transmembrane TNF-α, TGF-α, and l-selectin. Comparative modeling and dynamic computation detected structural perturbations, which resulted in higher energy, in the catalytic zinc complexes of the Met435 TACE mutants compared with that in the wild-type enzyme. Thus, Met435 serves to maintain the stability of the catalytic center of TACE for the hydrolysis of peptide bonds in substrates.
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Pannellini, Tania, Fabio Iannelli, Valentina Tabanelli, et al. "Abstract 2525: Translating clinically validated antibodies into a multiplexed immunofluorescent panel for the spatial profiling of lymphoid malignancies." Cancer Research 85, no. 8_Supplement_1 (2025): 2525. https://doi.org/10.1158/1538-7445.am2025-2525.
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Abstract Lymphoid malignancies present significant diagnostic challenges due to overlapping immunophenotypic features between tumor cells and reactive background cells, complicating the distinction between indolent lymphomas and benign lymph node hyperplasia [Nicolae A, Hemato, 2024, DOI:10.3390/hemato5030026]. Moreover, some Hodgkin lymphoma (HL) subtypes, such as lymphocyte-rich (LRHL) and nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) and certain variants of diffuse large B-cell lymphoma (DLBCL), exhibit similar phenotypic profiles despite having different therapeutic implications [PMID: 35741318]. This study aims to leverage sequential immunofluorescence (seqIF™, PMID: 37813886) for the spatial profiling of lymphoma to improve differential diagnosis and to uncover spatial patterns unique to each lymphoma subtype, providing insights into potential predictors of immunotherapy response. Here, we optimized a seqIF™ panel of 21 markers, using antibodies approved for clinical immunohistochemistry (IHC), to phenotype mature B-cell lymphomas on the COMET™ platform. This panel was applied to tissue microarrays prepared from representative cases of DLBCL, HL, indolent lymphomas, and benign lymph node hyperplasia. Each marker of the optimized panel was visually validated by certified pathologists, comparing seqIF™ results against corresponding IHC images. Computation of spatial matrix successfully identified tumor cells and reactive cells using thresholding of fluorescence intensity and cell diameter, particularly in HL and DLBCL cases that exhibited similar immunophenotypes at first glance. This enabled us to map classified cells events back to the tissue sections, allowing direct spatial correlation with stained images for a comprehensive analysis of cell distribution. Ongoing work aims at refining our lymphoma spatial profiles through the integration of spatial transcriptomics readout on the same sample cohort. Together these results highlight the potential of multiplex immunofluorescence (mIF) for the diagnostic phenotyping of lymphoma, transferring clinically validated antibodies into a mIF panel. The ability to assess both phenotypic and spatial characteristics of tumor and reactive cells will enhance our understanding of lymphoma biology and provide new insights into predictive markers for immunotherapy responses. Citation Format: Tania Pannellini, Fabio Iannelli, Valentina Tabanelli, Carmen De Simone, Roberto Chiarle, Samuel Aubert, Pedro Machado Almeida, Maria Giuseppina Procopio, Saska Brajkovic. Translating clinically validated antibodies into a multiplexed immunofluorescent panel for the spatial profiling of lymphoid malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2525.
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Luo, Yangkun, Lu Li, Gang Yin, and Jin Yi Lang. "Predicting tumor mutational burden in head and neck squamous cell carcinoma based on CT imaging features: A TCGA/TCIA study." Journal of Clinical Oncology 38, no. 15_suppl (2020): e15254-e15254. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e15254.
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e15254 Background: Immunotherapy has substantially changed the therapeutic strategies for cancers. Unfortunately, only 20–50% of patients with advanced solid tumours respond to treatment. There is therefore a need for the development of methods to identify patients who are most likely to respond to immunotherapy. Tumor mutation burden (TMB) have been served as the most prevalent biomarkers to predict immunotherapy response. This study was designed to investigate the ability of radiomics to predict TMB status in patients with head and neck squamous cell carcinoma (HNSCC). Methods: TMB values were calculated using genomic data obtained from the HNSCC dataset in The Cancer Genome Atlas (TCGA).We identified matching patients (n = 100) who underwent contrast-enhanced CT scan prior to treatment from The Cancer Imaging Archive (TCIA),and patients were grouped based on the cutoff value; high group(>4.2 mutations/Mb) and low group(≤4.2 mutations/Mb). A total of 249 radiomics features(9 non-texture features and 240 scan-texture-parameter features) were extracted from CT images of the tumor. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved imbalance-adjusted bootstrap resampling in the following four steps leading to final prediction model construction: (1) feature set reduction; (2) feature selection; (3) prediction performance estimation; and (4) computation of model coefficients. The performance was evaluated in terms of area under the curve (AUC), sensitivity, and specificity. Results: Among all the features, twenty features were found to have the most impact on the predictive value; the two top texture parameters were GLCM-Variance and GLCM-Sum Average. In multivariable analysis, the best performance was obtained using a combination of seven texture features that can discriminate between high mutation burden versus low mutation burden. The AUC, sensitivity, and specificity of this model were 0.97 ± 0.01, 0.92 ± 0.04, and 0.92 ±0.01, respectively. Conclusions: The proposed CT-derived predictive model can accurately predict TMB status in patients with HNSCC. It may be helpful in guiding immunotherapy in clinical practice and deserves further analysis.
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Andersson, Natalie, Adriana Mañas Nuñez, Kristina Aaltonen, et al. "Abstract PR001: Deciphering clonal evolution under chemotherapy in high-risk neuroblastoma using patient derived models." Cancer Research 82, no. 10_Supplement (2022): PR001. http://dx.doi.org/10.1158/1538-7445.evodyn22-pr001.
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Abstract Neuroblastoma is a pediatric tumor originating from the developing sympathetic nervous system, most often arising in the adrenal medulla in children below 5 years of age. After diagnosis, children with high-risk neuroblastoma are treated with COJEC, which is an aggressive chemotherapeutic treatment protocol encompassing five different chemotherapeutic agents. This is followed by surgical resection of the remaining tumor tissue. The aim of this project was to decipher how the subclonal landscape in the tumor changes during treatment with COJEC. To do this, three different patient derived xenograft (PDX) models were used by implanting dissociated tumor organoids subcutaneously in nude and NSG mice. The mice were subsequently randomized into either obtaining a mock treatment with saline solution (n=16), or treatment with the COJEC protocol (n=18). In PDX1 (3 controls, 4 treated) and in PDX2 (3 controls, 3 treated), progression or moderate response during treatment was seen respectively. In PDX3 (10 controls, 9 treated who went through surgical removal of remaining tumor tissue, 5 treated mice that didn’t undergo tumor resection) late relapses were seen in two of the mice who underwent surgery as well as two mice who did not. In the control group all tumors progressed. SNP-array analysis and RNA-sequencing was conducted on the parental sample as well as the tumors after treatment and relapses, in addition to single cell whole genome sequencing (scWGS) on a subset of samples. Array analysis was followed by computation of the proportion of cells in each sample harboring each genetic alteration, allowing phylogenetic reconstruction with DEVOLUTION. This revealed extensive convergent evolution of specific chromosomal regions across the PDX models. In PDX3 PTPRD deletions (also seen in PDX1) were found in all cells across samples before treatment. Deletions of the second PTPRD allele were detected in a total of six unique ways. Four of these were only seen in the relapses, while the remaining two were found after surgical resection. Other genes affected by convergent deletions were e.g., MACROD2 and LSAMP that were convergent in all three PDX models. High RNA expression of the genes encompassed by the affected chromosomal regions correlated with good treatment response both in the PDX models and patients, but not the copy number. Surprisingly, no significant increase in the number of genetic alterations was found after compared to before treatment. Phylogenetic reconstruction was conducted on scWGS-data for PDX1 and 3. PDX1 displayed a vast genetic diversity across tumors. In PDX3 parallel evolution of unique 1pq+ and 17q+ alterations and genetic bottlenecks with a selective sweep of 1pq/17q++ were seen in several tumors. In conclusion, both COJEC treatment and surgical resection induced bottlenecks and selective sweeps in the subclonal landscape and extensive convergent evolution was seen across tumors. Combined with the expression results, it supports the relevance of these specific genes in the evolution of neuroblastoma under treatment pressure. Citation Format: Natalie Andersson, Adriana Mañas Nuñez, Kristina Aaltonen, Karin Hansson, Alexandra Seger, Katarzyna Radke, Javanshir Esfandyari, Daniel Bexell, David Gisselsson. Deciphering clonal evolution under chemotherapy in high-risk neuroblastoma using patient derived models [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR001.
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Esmail, Abdullah, Jian Guan, Jiaqiong Xu, et al. "Prognostic value of molecular response via ctDNA measurement in predicating response of systemic therapy in patients with advanced solid cancer." Journal of Clinical Oncology 40, no. 16_suppl (2022): e13001-e13001. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e13001.
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e13001 Background: Molecular profiling of cancer can guide treatment decision, monitor response and predict clinical outcome in the era of precision medicine and individualized treatment. Emerging evidence has suggested that ctDNA change correlates with treatment response and predates radiological relapse. Thus, we aim to provide real-world data regarding the dynamic changes of ctDNA level measured via Guardant 360 Response in advanced solid cancer correlates with clinical outcome. Methods: We retrospectively reviewed data of patients with advanced solid cancer and had at least 2 timepoints of Guardant 360 Response test at Houston Methodist Cancer center from 1/1/2014- 2 /1/2022. Data collected included age, gender, type of solid cancer, mutational values, treatment started date and type of systemic therapy. Personalized mutational profiles derived from tumor tissue via whole-exome sequencing were used to design patient-specific ctDNA assays for variant detection in plasma samples. Blood samples taken at baseline and 8 weeks were analyzed to a 70-gene next-generation sequencing panel. On-therapy changes in circulating tumor DNA levels (molecular response) were measured using a ratio computation, with response defined as a decrease in mean variant allele fraction of 50% or more. Apart from ctDNA analysis, patients were also monitored using tumor markers and radiological imaging. Results: : Of 267 patients, only 93 were met the inclusions criteria with age 58.66 (±12.95) and female were the most with 77 (82.80%). Patients with breast cancer were the dominant with 62 (66.67%), Lung adenocarcinoma 20 (21.51%), Uveal Melanoma 4 (4.30%), Colorectal Cancer and Lung Squamous Cell Carcinoma 2 (2.15 %) each, Large Cell Lung Carcinoma, Sarcoma and Thymic Carcinoma were 1(1.07%) each. Patients who received Chemotherapy /Immunotherapy were 38 (41.30%), Chemotherapy/Immunotherapy/Radiation therapy were 29 (31.52%), Immunotherapy 9 (9.78%), Chemotherapy/Immunotherapy/Targeted Therapy 2 (2.17%) and Targeted Therapy /Chemotherapy 3 (3.26%).Patients samples who correlated with clinical data were 89 (95.70%) and only 4 (4.30%) were not .Follow-up time 2.15 (interquartile range: 1.10-4.12) years, patients who still alive are 24 (25.81%), median survival time 2.4 (95% CI: 1.78-2.76) years. Conclusions: Our data demonstrated that molecular response evaluation using circulating tumor DNA as a noninvasive predictor of response to systemic therapy in addition to standard of care imaging in some solid cancer. Further prospective studies are needed to confirm the validation.
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Kashyap, Abhishek, Dimpy Rani, Suresh Kumar, and Shailendra Bhatt. "Design and Computational Evaluation of New Carbamate Derivatives for the Inhibition of Monoacylglycerol Lipase Enzyme by using Docking." International Journal of Pharmaceutical Sciences and Drug Research 15, no. 05 (2023): 665–74. http://dx.doi.org/10.25004/ijpsdr.2023.150515.
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Different disorders and physiological process have been found to be associated with monoacylglycerol lipase enzyme in humans, like pain, inflammation, and neurodegenerative diseases also. The enzyme is a 33 KDa in weight and a type of serine hydrolase enzyme in nature. The presence of enzyme has been reported in both central and peripheral nervous systems and has show its importance as a key signalling factor in endocannabinoid signalling network system. The enzyme has also reported as source of free fatty acid provider for the cancer cell and tumor growth and their proliferation. In proliferative cancer cells, increased the monoacylglycerol lipase activity is observed. The growth, migration and survival of cancer cells have also found to be associated with phosphatidic acid, lysophosphatidic acid, sphingosine phosphate and prostaglandin E2, which are act as signalling molecules and are found to be derived from free fatty acid. These are also found to be related to the growth, transmission and viability of cancer cells, which increases with the enzyme activity. In the present study we performing computation screening studies of newly designed monoacylglycerol inhibitors which contains carbamate features, these molecules are designed based on previously developed monoacylglycerol carbamate inhibitors
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Ying, Haiyan, Nannan Zhang, Haibing Deng, et al. "Abstract LB328: Discovery & characterization of a next-generation FGFR4 inhibitor overcoming resistant mutations." Cancer Research 83, no. 8_Supplement (2023): LB328. http://dx.doi.org/10.1158/1538-7445.am2023-lb328.
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Abstract Introduction: Aberrant activation of FGF19-FGFR4 signaling pathway plays an essential role in the tumorigenesis of Hepatocellular carcinoma (HCC) and FGFR4 inhibitors have shown preliminary efficacy in recent clinical trials for patients with FGF19 overexpression. However, the observed responses only lasted a few months before tumors relapse. Acquired FGFR4 resistant mutations were found in ~30% of FGFR4 inhibitor responsive patients. Similar FGFR4 mutations haven also been found de novo in about 7-10% of Rhabdomyosarcoma (RMS) and ER-treated invasive lobular carcinoma patients. First generation FGFR4 inhibitors have minimal activity against these de novo or acquired resistant mutations. Therefore, next-generation of FGFR4 inhibitors are needed to overcome these resistant FGFR4 mutations to provide better treatment options for patients. Using advanced computation-aided structural analysis and medicinal chemistry design, we have discovered a next-generation small molecule FGFR4 inhibitor, ABSK012, and demonstrated its strong activities against de novo and acquired resistant FGFR4 mutations while retaining inhibition for wild-type FGFR4. Method: Inhibitory activity of ABSK012 against FGFR4 and FGFR4 mutants was evaluated by MSA assay and its inhibition on FGFR4-dependent cell proliferation was evaluated by Celltiter-Glo assay in wile type FGFR4-dependent cancer cell lines or mutant FGFR4-dependent Ba/f3 cell lines. Its selectivity against other FGFR family member and kinases was analyzed by cellular and KinomeScan profiling. Efficacy studies were conducted in HCC xenograft models and mutant FGFR4-dependent xenograft models including a RMS PDX model harboring FGFR4 V550L mutation. Results: ABSK012 demonstrated strong potency over multiple FGFR4 mutants that are insensitive to a first generation FGFR4 inhibitor BLU-554. It also inhibited wild-type FGFR4 with IC50&lt;5 nM in biochemical assay and exhibited great selectivity against other kinases. In multiple mutant and wild-type FGFR4-dependent cell lines, ABSK012 demonstrated significantly improved anti-proliferation activity. In preclinical in vivo studies in HCC models, oral administration of ABSK012 strongly inhibited the tumor growth at doses without obvious toxicities. More importantly, in a RMS PDX xenograft harboring FGFR4 V550L mutation, ABSK012 also showed significant anti-tumor activity. Other ADME and safety profiling demonstrated excellent drug-like properties of ABSK012. Conclusion: ABSK012, presented here by Abbisko Therapeutics, is a highly potent, selective, and next-generation small molecule FGFR4 inhibitor overcoming FGFR4 mutations resistant to first-generation inhibitors. Its superior preclinical profile supports its fast-track development into clinic. Citation Format: Haiyan Ying, Nannan Zhang, Haibing Deng, Fei Yang, Wenqun Xin, Bin Shen, Hongping Yu, Zhui Chen, Yao-chang Xu. Discovery & characterization of a next-generation FGFR4 inhibitor overcoming resistant mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB328.
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Andor, Noemi, Jill Barnholtz-Sloan, and Hanlee Ji. "COMP-01. MODELING THE EVOLUTION OF PLOIDY IN A RESOURCE RESTRICTED ENVIRONMENT." Neuro-Oncology 21, Supplement_6 (2019): vi61. http://dx.doi.org/10.1093/neuonc/noz175.244.
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Abstract Progression of lower-grade gliomas (LGG) to glioblastoma (GBM) is accompanied by a phenotypic switch to an invasive cell phenotype. Converging evidence from colorectal-, breast-, and lung-cancers, suggests a strong enrichment of high ploidy cells among metastatic lesions as compared to the primary. Even in normal development: trophoblast giant cells are responsible for invading the placenta during embryogenesis and these cells often have tens of copies of the genome. We formulate a mechanistic Grow-or-go model that postulates higher energy demands of high-ploidy cells as driver of invasive behavior. The unit we are modeling is a cell, that comes with a certain ploidy, proliferation-, and death-rate. Variations in ploidy emerge as a result of chromosome missegregations. For each cell we calculate the probability of cell-division as a function of energy availability in the neighborhood vs. ploidy-dependent energy demand of the cell. Underlying this comparison is the dual role of integrin signaling: integrin-mediated signals allow cells to progress from G1 to S-phase. At the same time integrins mediate cell migration. The model was implemented as a cellular automaton and 2,500 simulations were ran at variable energies and missegregation rates. In low-energy environments high-ploidy clones were enriched at the leading edge of the tumor. This was not the case in high-energy environments. We applied the model to analyze previously published exome sequencing data from 14 multi-spatial and longitudinal LGG biopsies. Using the size and ploidy of co-existing clones as summary statistics for Approximate Bayesian Computation, we infer relative chromosome missegregation rates in primary LGG. A higher missegregation rate was predictive of faster progression of LGG to GBM (multivariate Cox: HR = 7.96, P = 0.041). Future validation experiments will evaluate the potential of the model to explain differences in the prognostic power of integrin signaling and cell cycle progression between males and females.
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Cheng, Da-Chuan, Jen-Hong Chi, Shih-Neng Yang, and Shing-Hong Liu. "Organ Contouring for Lung Cancer Patients with a Seed Generation Scheme and Random Walks." Sensors 20, no. 17 (2020): 4823. http://dx.doi.org/10.3390/s20174823.
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In this study, we proposed a semi-automated and interactive scheme for organ contouring in radiotherapy planning for patients with non-small cell lung cancers. Several organs were contoured, including the lungs, airway, heart, spinal cord, body, and gross tumor volume (GTV). We proposed some schemes to automatically generate and vanish the seeds of the random walks (RW) algorithm. We considered 25 lung cancer patients, whose computed tomography (CT) images were obtained from the China Medical University Hospital (CMUH) in Taichung, Taiwan. The manual contours made by clinical oncologists were taken as the gold standard for comparison to evaluate the performance of our proposed method. The Dice coefficient between two contours of the same organ was computed to evaluate the similarity. The average Dice coefficients for the lungs, airway, heart, spinal cord, and body and GTV segmentation were 0.92, 0.84, 0.83, 0.73, 0.85 and 0.66, respectively. The computation time was between 2 to 4 min for a whole CT sequence segmentation. The results showed that our method has the potential to assist oncologists in the process of radiotherapy treatment in the CMUH, and hopefully in other hospitals as well, by saving a tremendous amount of time in contouring.
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Wu, Wen-Lian, Taishan Hu, Zhilin Deng, et al. "Abstract 1808: Discovery of highly selective novel MTA-cooperative PRMT5 inhibitors for the treatment of cancers." Cancer Research 84, no. 6_Supplement (2024): 1808. http://dx.doi.org/10.1158/1538-7445.am2024-1808.
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Abstract Protein arginine methyltransferase 5 (PRMT5), a type II PRMT catalyzing the formation of symmetric dimethylation of arginine residues on histone and non-histone proteins, regulates many biological pathways in mammalian cells, including cell growth and differentiation. Methylthioadenosine phosphorylase (MTAP) is required for the methionine salvage pathway, deletion of MTAP leads to the accumulation of inhibitory PRMT5 cofactor methylthioadenosine (MTA). MTAP gene is adjacent to and frequently co-deleted with CDKN2A gene, the most commonly deleted tumor suppressor gene in human cancers. The increase in MTA significantly reduced PRMT5 activity in MTAP-deficient cancer cells, rendering them more vulnerable to PRMT5 inhibition than normal cells. Selective Inhibitors of PRMT5-MTA complex (MTA-cooperative) are supposed to exhibit an increased therapeutic index compared to first generation PRMT5 inhibitors for the treatment of MTAP-deleted (MTAP-del) cancer patients. Guided by computation-aided drug design (CADD), binding mode analysis of known PRMT5 inhibitors has led to the design and synthesis of a novel series of MTA-cooperative PRMT5 inhibitors. Many compounds within this series were found to inhibit PRMT5/MEP50 complex with single digit nM of IC50 in enzymatic assay. Cell based activity of these compounds was assessed by measuring the symmetric demethylarginine (SDMA) and 10-day cell proliferation assays. Several compounds exhibited low double-digit nM of cellular potency in HCT116 MTAP-del cells, the inhibition of SDMA and anti-proliferation activities in HCT116 MTAP-del cells over HCT116 MTAP-WT cells have excellent selectivity (80 - 400 fold). Further optimization of in vitro and in vivo pharmacokinetic properties has yielded candidate compounds suitable for evaluation of pharmacodynamic effect in the LU99 MTAP-del NSCLC xenograft model. Tumor growth inhibition (TGI) was observed in a dose-dependent manner, accompanied by a reduction of PRMT5-mediated SDMA levels in both the tumor and bone marrow. In summary, we have identified compounds with novel scaffolds that are potent and highly selective MTA-cooperative PRMT5 inhibitors. Further development of the second-generation PRMT5 inhibitors for treatment of cancers is also planned. Citation Format: Wen-Lian Wu, Taishan Hu, Zhilin Deng, Honghai Li, Quanrong Shen, Lei Zhang, Xiaochu Ma, Peihua Sun, Cindy Cheng, Fang Liu, Xin Chen, Ye Hua, Bryan Huang. Discovery of highly selective novel MTA-cooperative PRMT5 inhibitors for the treatment of cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1808.
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Marron, Thomas, Julia Kodysh, Alex Rubinsteyn, et al. "289 PGV-001: a phase 1 trial of a personalized neoantigen peptide vaccine for the treatment of malignancies in the adjuvant setting." Journal for ImmunoTherapy of Cancer 8, Suppl 3 (2020): A316. http://dx.doi.org/10.1136/jitc-2020-sitc2020.0289.
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BackgroundThe efficacy of T cell directed immunotherapies relies on adequate priming of T cells to tumor-specific neoantigens, which some studies have augmented with synthetic neoantigen vaccines. This is the first report of a personalized genomic vaccine (PGV-001) in multiple histologies in the adjuvant setting.MethodsTumor and germline RNA and DNA were sequenced, and neoantigen peptides were selected using our OpenVax custom computation pipeline that identifies and ranks mutant sequences by a combination of predicted MHC-I binding affinity and neoantigen abundance within tumor. Up to 10 peptides were synthesized per patient and were administered over the course of 27 weeks in combination with the poly-ICLC. Primary objectives were to determine 1) the safety and tolerability; 2) the feasibility of PGV-001 production and administration; and 3) the immunogenicity of PGV-001. Secondary objectives included immunophenotyping neoantigen-specific T cells in peripheral blood, and characterization of peripheral blood lymphoid, myeloid and humoral responses. We report here for the first time on the primary endpoints.ResultsVaccine was synthesized for 15 patients. A mean of 1619 somatic variants (range 521–5106) were detected. Our pipeline identified a mean of 67.1 neoantigens/patient (range 8–193) and 9.7 peptides/patient were synthesized (range 7–10). 13 patients received PGV-001 (11 patients received all 10 doses and 2 patients received at least 8 doses) while 2 had progressive disease before vaccine initiation. Transient grade 1 injection site reactions were seen in 31% of patients, and one patient experienced grade 1 fever. There were no other significant adverse events. Ex vivo ELISpot analysis of patient blood demonstrated significant induction of T cell responses following receipt of 10 vaccines that were not present after the 6th vaccine, supporting the need for a prolonged dosing schedule. Robust responses were seen in both CD4 and CD8 T cells by intracellular cytokine staining for TNF-a, IFN-a, and IL-2 following in vitro expansion in the presence of vaccine antigens. Additional studies are ongoing to define the most immunogenic antigens.ConclusionsA personalized neoantigen vaccine of synthetic mutant peptides and adjuvant poly-ICLC was successfully synthesized for 15 patients and administered successfully to 87% patients over the course of 27 weeks. The vaccine was well tolerated, and T cell expansion and reactivity to synthetic neoantigens confirms immunogenicity of neoantigens identified with OpenVax.Trial RegistrationNCT02721043Ethics ApprovalThis study was approved by the IRB of The Mount Sinai Hospital in accordance with Federal law. HSM #15-00841.
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Montierth, Matthew, Yujie Jiang, Kaixian Yu, et al. "Abstract 7153: Subclonal mutation load predicts survival and response to immunotherapy in cancers with low to moderate TMB." Cancer Research 85, no. 8_Supplement_1 (2025): 7153. https://doi.org/10.1158/1538-7445.am2025-7153.
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Abstract Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment, yet current biomarkers like tumor mutation burden (TMB) and mismatch repair deficiency identify responders in only a small fraction of patients, particularly in low-to-moderate TMB cancers. This is critical as the majority of cancer patients (ex. approximately 90% of TCGA) have TMB&lt;10, the FDA-approved threshold for ICI therapy. As such, there is need to identify biomarkers to predict immunotherapy response in these currently overlooked patients.We developed CliPP, a novel statistical machine learning approach that performs subclonal reconstruction through regularized regression. CliPP achieves 100 - 1000 fold faster computation than existing methods while maintaining accuracy in both simulated (n=5, 515) and real patient datasets (n=1, 582 whole-genome sequences). To facilitate broad adoption, we deployed CliPP as a user-friendly web application (CliPP-on-web, companion AACR abstract, Wu et al.) facilitating use by clinicians and researchers without computational expertise. Using CliPP, we analyzed 7, 279 tumors across 32 cancer types from TCGA, 42 samples from two ICI clinical trials in metastatic prostate cancer, and 613 esophageal adenocarcinomas (EAC) from the OCCAMS consortium. Subclonal mutation load (sML) was calculated as the fraction of subclonal mutations, with comprehensive survival analyses performed.High sML showed opposing effects on survival based on TMB: beneficial in 14 cancer types with low-to-moderate TMB (HR=0.06-0.69, P&lt;0.05), but detrimental in 4 high-TMB cancers (HR=1.48-2.70, P&lt;0.05). In two separate metastatic prostate cancer trials (NCT02113657 and NCT02703623) where TMB failed to predict response, high sML predicted favorable outcomes to ipilimumab (NCT02113657: HR=0.18, P=0.004, NCT02703623: HR=0.1, P=0.007) and was associated with increased CD8+ T cell density (P=0.008). Validation in 613 WGS EAC samples with standardized clinical follow-up confirmed improved survival with high sML in moderate-TMB cancers (HR=0.6, P&lt;0.0001), with effects persistent across disease stages.These findings identify sML as a key feature of cancer and reveal an important relationship between evolutionary dynamics and the tumor microenvironment. Furthermore, sML may serve as an orthogonal approach to identify likely responders to ICI in low-to moderate TMB tumors complementing existing biomarkers and potentially broadening the therapeutic reach of checkpoint inhibitors. Citation Format: Matthew Montierth, Yujie Jiang, Kaixian Yu, Shuangxi Ji, Quang Tran, Xiaoqian Liu, Jessica Lal, Shuai Guo, Aaron Wu, Seung Shin, Ruonan Li, Shaolong Cao, Yuxin Tang, Tom Lesluyes, Scott Kopetz, Pavlos Msaouel, Anil K. Sood, Ginny Devonshire, Christopher M. Jones, Jaffer Ajani, Sumit K. Subudhi, Ana Aparicio, Padmanee Sharma, John P. Shen, Marek Kimmel, Jennifer R. Wang, Maxime Tarabichi, Rebecca C. Fitzgerald, Peter Van Loo, Hongtu Zhu, Wenyi Wang. Subclonal mutation load predicts survival and response to immunotherapy in cancers with low to moderate TMB [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7153.