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Journal articles on the topic 'Molecular medicine, gene expression analysis, clinical samples, technical optimization'

Author: Grafiati

Published: 11 March 2023

Last updated: 31 July 2025

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1

García Aranda, Marilina, Inmaculada López-Rodríguez, Susana García-Gutiérrez, et al. "Laboratory protocol for the digital multiplexed gene expression analysis of nasopharyngeal swab samples using the NanoString nCounter system." F1000Research 11 (September 30, 2022): 133. http://dx.doi.org/10.12688/f1000research.103533.2.

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This paper describes a laboratory protocol to perform the NanoString nCounter Gene Expression Assay from nasopharyngeal swab samples. It is urgently necessary to identify factors related to severe symptoms of respiratory infectious diseases, such as COVID-19, in order to assess the possibility of establishing preventive or preliminary therapeutic measures and to plan the services to be provided on hospital admission. At present, the samples recommended for microbiological diagnosis are those taken from the upper and/or the lower respiratory tract. The NanoString nCounter Gene Expression Assay

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García Aranda, Marilina, Inmaculada López-Rodríguez, Susana García-Gutiérrez, et al. "Laboratory protocol for the digital multiplexed gene expression analysis of nasopharyngeal swab samples using the NanoString nCounter system." F1000Research 11 (February 2, 2022): 133. http://dx.doi.org/10.12688/f1000research.103533.1.

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This paper describes a laboratory protocol to perform the NanoString nCounter Gene Expression Assay from nasopharyngeal swab samples. It is urgently necessary to identify factors related to severe symptoms of respiratory infectious diseases, such as COVID-19, in order to assess the possibility of establishing preventive or preliminary therapeutic measures and to plan the services to be provided on hospital admission. At present, the samples recommended for microbiological diagnosis are those taken from the upper and/or the lower respiratory tract. The NanoString nCounter Gene Expression Assay

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Bhende, Manisha, Anuradha Thakare, Bhasker Pant, Piyush Singhal, Swati Shinde, and V. Saravanan. "Deep Learning-Based Real-Time Discriminate Correlation Analysis for Breast Cancer Detection." BioMed Research International 2022 (June 28, 2022): 1–12. http://dx.doi.org/10.1155/2022/4609625.

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Breast cancer is the most common cancer in women, and the breast mass recognition model can effectively assist doctors in clinical diagnosis. However, the scarcity of medical image samples makes the recognition model prone to overfitting. A breast mass recognition model integrated with deep pathological information mining is proposed: constructing a sample selection strategy, screening high-quality samples across different mammography image datasets, and dealing with the scarcity of medical image samples from the perspective of data enhancement; mining the pathology contained in limited labele

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Teng, Pai-Chi, Yu Jen Jan, Jie-Fu Chen, et al. "Prostate cancer CTC-RNA Assay: A new method for contemporary genomics and precision medicine via liquid biopsy." Journal of Clinical Oncology 38, no. 6_suppl (2020): 170. http://dx.doi.org/10.1200/jco.2020.38.6_suppl.170.

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170 Background: Transcriptome-based analysis has begun to reshape the approach to prostate cancer (PC). Two different gene expression signatures have shown that PC can be divided into 3 subclasses reflecting luminal-basal biology. These subtypes point toward biological drivers that may strongly influence how care should be personalized including optimization of androgen receptor targeted therapy. The majority of work done in this area has been based on tissue-based gene expression. With the advent of newer nanotechnology platforms for isolation of circulating tumor cells (CTCs), profiling of P

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Williams, Marc A. "Article Commentary: Stabilizing the Code–-Methods to Preserve RNA Prove Their Worth." Biomarker Insights 5 (January 2010): BMI.S6094. http://dx.doi.org/10.4137/bmi.s6094.

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Commercially available platforms to stabilize messenger RNA (mRNA) and microRNA are critically designed to optimize and ensure the quality and integrity of those nucleic acids. This is not only essential for gene expression analyses, but would provide technical utility in providing concordant standard operating procedures in preserving the structural integrity of RNA species in multicenter clinical research programs and biobanking of cells or tissues for subsequent isolation of intact RNA. The major challenge is that the presence of degraded samples may adversely influence the interpretation o

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Hether, Tyler, Tim Howes, Christine Spencer, et al. "305 Technical considerations for normalizing digital spatial profiling data with multiple within-patient samples." Journal for ImmunoTherapy of Cancer 8, Suppl 3 (2020): A332. http://dx.doi.org/10.1136/jitc-2020-sitc2020.0305.

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BackgroundNanoString’s GeoMx Digital Spatial Profiling (DSP) technology enables profiling of gene or protein expression from fresh or archival tissues. Specific regions of interest (ROIs) are identified via fluorescently labeled visualization markers. Within a given ROI, oligonucleotide tags from labeled, incubated antibodies can be released by area of interest (AOI)-specific exposure to UV light. With DSP, multiple AOIs can be collected within an individual tissue and/or within an individual patient. As with other technologies, technical variation that needs to be accounted before meaningful

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Zhang, Kefen, Kaisheng Xie, Xin Huo, et al. "Development and Optimization of a Prognostic Model Associated with Stemness Genes in Hepatocellular Carcinoma." BioMed Research International 2022 (October 5, 2022): 1–28. http://dx.doi.org/10.1155/2022/9168441.

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Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide, which is associated with a variety of risk factors. Cancer stem cells are self-renewal cells, which can promote the occurrence and metastasis of tumors and enhance the drug resistance of tumor treatment. This study aimed to develop a stemness score model to assess the prognosis of hepatocellular carcinoma (HCC) patients for the optimization of treatment. The single-cell sequencing data GSE149614 was downloaded from the GEO database. Then, we compared the gene expression of hepatic stem cells and other hepatocytes in tu

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Xu, Congdi, Xinyu Hu, Yantao Fan, Ling Zhang, Zhengliang Gao, and Chunhui Cai. "Wif1 Mediates Coordination of Bone Morphogenetic Protein and Wnt Signaling in Neural and Glioma Stem Cells." Cell Transplantation 31 (January 2022): 096368972211345. http://dx.doi.org/10.1177/09636897221134540.

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Wnts, bone morphogenetic protein (BMP), and fibroblast growth factor (FGF) are paracrine signaling pathways implicated in the niche control of stem cell fate decisions. BMP-on and Wnt-off are the dominant quiescent niche signaling pathways in many cell types, including neural stem cells (NSCs). However, among the multiple inhibitory family members of the Wnt pathway, those with direct action after BMP4 stimulation in NSCs remain unclear. We examined 11 Wnt inhibitors in NSCs after BMP4 treatment. Wnt inhibitory factor 1 (Wif1) has been identified as the main factor reacting to BMP4 stimuli. RN

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Kryuchko, T., V. Shcherbak, L. Bubyr, O. Izmailova, and O. Tkachenko. "STUDY OF THE CIRCADIAN MOLECULAR CLOCK IN PAEDIATRIC PATIENTS WITH SEASONAL ALLERGIC RHINITIS: POTENTIAL APPROACHES TO TREATMENT." Neonatology, surgery and perinatal medicine 8, no. 4(50) (2023): 49–56. http://dx.doi.org/10.24061/2413-4260.xiii.4.50.2023.6.

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Understanding of the relationship between the circadian molecular clock and allergic diseases continues to be studied and may be of practical importance for further selection of optimal treatment. The aim of this study was to evaluate the degree of mRNA expression of the circadian molecular clock genes bmal1 and per1 in buccal epithelial cells and to investigate the effi cacy of protocol treatment in children with seasonal allergic rhinitis, taking into account the time dependence. Material and methods. The study included 20 patients aged 6 to 17 years with a confi rmed diagnosis of seasonal a

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Harding, Taylor, Qidi Yang, Brittany Mineo, et al. "73 Characterization of tumor-infiltrating T-cell repertoire in human cancers." Journal for ImmunoTherapy of Cancer 9, Suppl 2 (2021): A81. http://dx.doi.org/10.1136/jitc-2021-sitc2021.073.

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BackgroundTCR and BCR repertoire profiling is a promising technique that can provide a clinically useful window into the complex interactions between tumor cells and infiltrating lymphocytes. Despite recent advances in repertoire sequencing methods, the characterization of tumor-infiltrating T-cell repertoires has been limited to small sample sizes due to technical and material constraints. In this study, we constructed a large multidimensional database of repertoire data covering a diverse landscape of HLA genotypes and tumor neoantigens from routine clinical sequencing. We present a descript

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Rudqvist, Nils-Petter, Roberta Zappasodi, Daniel Wells, et al. "P854 Construction of the immune landscape of durable response to checkpoint blockade therapy by integrating publicly available datasets." Journal for ImmunoTherapy of Cancer 8, Suppl 1 (2020): A5.2—A6. http://dx.doi.org/10.1136/lba2019.8.

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BackgroundImmune checkpoint blockade (ICB) has revolutionized cancer treatment. However, long-term benefits are only achieved in a small fraction of patients. Understanding the mechanisms underlying ICB activity is key to improving the efficacy of immunotherapy. A major limitation to uncovering these mechanisms is the limited number of responders within each ICB trial. Integrating data from multiple studies of ICB would help overcome this issue and more reliably define the immune landscape of durable responses. Towards this goal, we formed the TimIOs consortium, comprising researchers from the

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Van Vliet, Martin H., Rowan Kuiper, Belinda Dumee, et al. "Single Sample Application of the EMC92/SKY92 Signature Using the Mmprofiler." Blood 124, no. 21 (2014): 2026. http://dx.doi.org/10.1182/blood.v124.21.2026.2026.

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Abstract Introduction Multiple Myeloma (MM) is a heterogeneous disease with diverse gene expression patterns (GEP) across patients. This has led to the development of various signatures allowing virtual karyotyping, defining different clusters of patients, and prognostication by high risk signatures (e.g. EMC92/SKY92). Several GEP datasets exist, but may have scaling/offset differences (batch effects) in the data, e.g. due to differences in reagents used, location, etc. Batch wise normalization approaches can reduce batch effects, and have allowed successful validation of those signatures acro

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Sivasankar, R., SV Subbareddy, K. Ramaiah, V. Udaykiran, and K. Chennaiah. "Recovery of antioxidant enzymes by red grape extract due to Nicotine induced changes in the liver tissue of male albino rats with reference to the aging." Biolife 3, no. 1 (2022): 212–27. https://doi.org/10.5281/zenodo.7252629.

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<strong>ABSTRACT</strong> The beneficial effects of Red grape (Vitis vinifera) extract as an antioxidant has been assessed in nicotine administered rats to examine the effects of nicotine on the antioxidant defense systems in liver tissue of male albino rat. Age matched rats were be divided into 4 groups of six in each group and treated as follows: Group I. Normal Control (NC) (Control rats received 0.9% saline). Group II. Nicotine treated (Nt) (at a dose of 0.6 mg/ kg body weight by subcutaneous injection for a period of 2 months). Group III. Red grape extract treated (RGEt). (Red grape extra

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Griffin, Jon, Jenny Down, Lewis A. Quayle, et al. "Verification of molecular subtyping of bladder cancer in the GUSTO clinical trial." Journal of Pathology: Clinical Research 10, no. 2 (2024). http://dx.doi.org/10.1002/2056-4538.12363.

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AbstractThe GUSTO clinical trial (Gene expression subtypes of Urothelial carcinoma: Stratified Treatment and Oncological outcomes) uses molecular subtypes to guide neoadjuvant therapies in participants with muscle‐invasive bladder cancer (MIBC). Before commencing the GUSTO trial, we needed to determine the reliability of a commercial subtyping platform (Decipher Bladder; Veracyte) when performed in an external trial laboratory as this has not been done previously. Here, we report our pre‐trial verification of the TCGA molecular subtyping model using gene expression profiling. Formalin‐fixed pa

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Rocque, Brittany, Kate Guion, Pranay Singh, et al. "Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease." Scientific Reports 14, no. 1 (2024). http://dx.doi.org/10.1038/s41598-024-53993-2.

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AbstractSingle cell and spatially resolved ‘omic’ techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict

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Hubbard, Erika L., Prathyusha Bachali, Kathryn M. Kingsmore, et al. "Analysis of transcriptomic features reveals molecular endotypes of SLE with clinical implications." Genome Medicine 15, no. 1 (2023). http://dx.doi.org/10.1186/s13073-023-01237-9.

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Abstract Background Systemic lupus erythematosus (SLE) is known to be clinically heterogeneous. Previous efforts to characterize subsets of SLE patients based on gene expression analysis have not been reproduced because of small sample sizes or technical problems. The aim of this study was to develop a robust patient stratification system using gene expression profiling to characterize individual lupus patients. Methods We employed gene set variation analysis (GSVA) of informative gene modules to identify molecular endotypes of SLE patients, machine learning (ML) to classify individual patient

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Chen, Duojiao, Mohammad I. Abu Zaid, Jill L. Reiter, et al. "Cryopreservation Preserves Cell-Type Composition and Gene Expression Profiles in Bone Marrow Aspirates From Multiple Myeloma Patients." Frontiers in Genetics 12 (April 21, 2021). http://dx.doi.org/10.3389/fgene.2021.663487.

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Single-cell RNA sequencing reveals gene expression differences between individual cells and also identifies different cell populations that are present in the bulk starting material. To obtain an accurate assessment of patient samples, single-cell suspensions need to be generated as soon as possible once the tissue or sample has been collected. However, this requirement poses logistical challenges for experimental designs involving multiple samples from the same subject since these samples would ideally be processed at the same time to minimize technical variation in data analysis. Although cr

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Kong, Xiang-Zhen, Yu Song, Jin-Xing Liu, et al. "Joint Lp-Norm and L2,1-Norm Constrained Graph Laplacian PCA for Robust Tumor Sample Clustering and Gene Network Module Discovery." Frontiers in Genetics 12 (February 23, 2021). http://dx.doi.org/10.3389/fgene.2021.621317.

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The dimensionality reduction method accompanied by different norm constraints plays an important role in mining useful information from large-scale gene expression data. In this article, a novel method named Lp-norm and L2,1-norm constrained graph Laplacian principal component analysis (PL21GPCA) based on traditional principal component analysis (PCA) is proposed for robust tumor sample clustering and gene network module discovery. Three aspects are highlighted in the PL21GPCA method. First, to degrade the high sensitivity to outliers and noise, the non-convex proximal Lp-norm (0 &lt; p &a

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Wang, Fengfeng, Chi Wai Cheung, and Stanley Sau Ching Wong. "Use of pain-related gene features to predict depression by support vector machine model in patients with fibromyalgia." Frontiers in Genetics 14 (March 29, 2023). http://dx.doi.org/10.3389/fgene.2023.1026672.

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The prevalence rate of depression is higher in patients with fibromyalgia syndrome, but this is often unrecognized in patients with chronic pain. Given that depression is a common major barrier in the management of patients with fibromyalgia syndrome, an objective tool that reliably predicts depression in patients with fibromyalgia syndrome could significantly enhance the diagnostic accuracy. Since pain and depression can cause each other and worsen each other, we wonder if pain-related genes can be used to differentiate between those with major depression from those without. This study develo

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Qiao, Yanchun, Jie Li, Dandan Liu, Chenying Zhang, Yang Liu, and Shuguo Zheng. "Identification and experimental validation of key m6A modification regulators as potential biomarkers of osteoporosis." Frontiers in Genetics 13 (January 6, 2023). http://dx.doi.org/10.3389/fgene.2022.1072948.

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Osteoporosis (OP) is a severe systemic bone metabolic disease that occurs worldwide. During the coronavirus pandemic, prioritization of urgent services and delay of elective care attenuated routine screening and monitoring of OP patients. There is an urgent need for novel and effective screening diagnostic biomarkers that require minimal technical and time investments. Several studies have indicated that N6-methyladenosine (m6A) regulators play essential roles in metabolic diseases, including OP. The aim of this study was to identify key m6A regulators as biomarkers of OP through gene expressi

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Sun, Yisong, Jie Gao, and Juehua Jing. "Exploration of biomarkers associated with histone lactylation modification in spinal cord injury." Frontiers in Genetics 16 (July 2, 2025). https://doi.org/10.3389/fgene.2025.1609439.

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IntroductionThe biological roles of histone lactylation (HLA) modification-related genes (HLMRGs) in spinal cord injury (SCI) remain unclear. This study aimed to investigate the expression patterns and molecular mechanisms of HLMRGs in SCI through bioinformatics approaches.MethodsData from GSE151371, GSE47681, and 10 HLMRGs were analyzed. Subsequently, biomarkers were identified based on receiver operating characteristic (ROC) curves, followed by logistic regression modeling and nomogram construction. Gene set enrichment analysis (GSEA) was performed to assess the functional roles of these bio

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Liu, Yiran E., Sirle Saul, Aditya Manohar Rao, et al. "An 8-gene machine learning model improves clinical prediction of severe dengue progression." Genome Medicine 14, no. 1 (2022). http://dx.doi.org/10.1186/s13073-022-01034-w.

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Abstract Background Each year 3–6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed. Methods We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patient

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Wu, Sunny Z., Daniel L. Roden, Ghamdan Al-Eryani, et al. "Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis." Genome Medicine 13, no. 1 (2021). http://dx.doi.org/10.1186/s13073-021-00885-z.

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Abstract Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human

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Sugino, Yusuke, Xin Bao, Takumi Kageyama, et al. "Narrative Review of Patient Cancer Tissue–Derived Zebrafish Xenograft Models for Evaluating Drug Sensitivity as an Avatar Model for Clinical Application." Cancer Medicine 14, no. 13 (2025). https://doi.org/10.1002/cam4.70942.

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ABSTRACTIn the pursuit of optimal medical care, treatment selection based on the molecular analysis of genomes, transcriptomes, and proteomes has been explored; however, this approach relies on data from large patient groups, resulting in limited accuracy in predicting treatment efficacy. Diseases involve complex pathological networks, requiring treatments that target multiple key molecules in these networks. Drug screening using these networks, which cannot be achieved through a gene expression analysis alone, requires animal models. Zebrafish embryos have an immature immune system, allowing

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Yang, Minglei, Chenghao Lin, Yanni Wang, Kang Chen, Haiyue Zhang, and Weizhong Li. "Identification of a cytokine-dominated immunosuppressive class in squamous cell lung carcinoma with implications for immunotherapy resistance." Genome Medicine 14, no. 1 (2022). http://dx.doi.org/10.1186/s13073-022-01079-x.

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Abstract Background Immune checkpoint blockade (ICB) therapy has revolutionized the treatment of lung squamous cell carcinoma (LUSC). However, a significant proportion of patients with high tumour PD-L1 expression remain resistant to immune checkpoint inhibitors. To understand the underlying resistance mechanisms, characterization of the immunosuppressive tumour microenvironment and identification of biomarkers to predict resistance in patients are urgently needed. Methods Our study retrospectively analysed RNA sequencing data of 624 LUSC samples. We analysed gene expression patterns from tumo

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sprotocols. "Engineering of ultra-small diagnostic nanoprobes through oriented conjugation of single-domain antibodies and quantum dots." January 7, 2015. https://doi.org/10.5281/zenodo.13799.

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Authors: Alyona Sukhanova, Klervi Even-Desrumeaux, Patrick Chames, Daniel Baty, Mikhail Artemyev, Vladimir Oleinikov & Igor Nabiev ### Abstract Nanoparticle-based biodetection commonly employs monoclonal antibodies (mAbs) for targeting. Although several types of conjugates have been used for biomarker labeling, the large size of mAbs limits the number of ligands per nanoparticle, impedes their intratumoral distribution, and limits intracellular penetration. Furthermore, the conditions of mAb conjugation using conventional techniques provide nanoprobes with irregular orientation of mAbs on

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