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Journal articles on the topic 'Passenger mutations'

Author: Grafiati

Published: 24 September 2021

Last updated: 30 July 2025

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1

Stein, Lincoln David, Wei Jiao, Gurnit Atwal, and Quaid Morris. "Abstract 5046: DeepTumour: Identify tumor origin from whole genome sequences." Cancer Research 82, no. 12_Supplement (2022): 5046. http://dx.doi.org/10.1158/1538-7445.am2022-5046.

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Abstract The DeepTumour algorithm predicts the tissue of origin of a tumor based on the pattern of passenger mutations identified by whole genome sequencing. "Passengers" are incidental mutations that accrue in the genome over time due to random mutational processes, and are functionally distinct from the "driver" mutations that are responsible for the cancer's malignant behavior. In adult cancers, passenger mutations typically outnumber drivers by a hundred or thousand-fold; critically, the vast majority of passengers arise in the normal cell lineage that precedes the malignant transformation

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2

Banerjee, Shayantan, Karthik Raman, and Balaraman Ravindran. "Sequence Neighborhoods Enable Reliable Prediction of Pathogenic Mutations in Cancer Genomes." Cancers 13, no. 10 (2021): 2366. http://dx.doi.org/10.3390/cancers13102366.

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Identifying cancer-causing mutations from sequenced cancer genomes hold much promise for targeted therapy and precision medicine. “Driver” mutations are primarily responsible for cancer progression, while “passengers” are functionally neutral. Although several computational approaches have been developed for distinguishing between driver and passenger mutations, very few have concentrated on using the raw nucleotide sequences surrounding a particular mutation as potential features for building predictive models. Using experimentally validated cancer mutation data in this study, we explored var

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Buisson, Rémi, Adam Langenbucher, Danae Bowen, et al. "Passenger hotspot mutations in cancer driven by APOBEC3A and mesoscale genomic features." Science 364, no. 6447 (2019): eaaw2872. http://dx.doi.org/10.1126/science.aaw2872.

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Cancer drivers require statistical modeling to distinguish them from passenger events, which accumulate during tumorigenesis but provide no fitness advantage to cancer cells. The discovery of driver genes and mutations relies on the assumption that exact positional recurrence is unlikely by chance; thus, the precise sharing of mutations across patients identifies drivers. Examining the mutation landscape in cancer genomes, we found that many recurrent cancer mutations previously designated as drivers are likely passengers. Our integrated bioinformatic and biochemical analyses revealed that the

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Zeineddine, Fadl, Benjamin Garmezy, Timothy A. Yap, and John Paul Y. C. Shen. "PMC: A more precise classifier of POLE mutations to identify candidates for immune therapy." Journal of Clinical Oncology 39, no. 15_suppl (2021): 3548. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.3548.

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3548 Background: Specific somatic mutations in DNA polymerase epsilon ( POLE) can cause a hypermutant phenotype with tumor mutation burden (TMB) in excess of 100 mutations per megabase. It has been reported that POLE mutant tumors are enriched in response to immune therapy and this association is being tested in multiple active clinical trials. However, most POLE mutations are passenger mutations and have no pathogenic role. Current methods to classify POLE mutations are limited in both accuracy and completeness, which could lead to inappropriate use of immune agents in tumor such as MSS CRC,

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Wang, Lihua, Haiyang Sun, Zhenyu Yue, Junfeng Xia, and Xiaoyan Li. "CDMPred: a tool for predicting cancer driver missense mutations with high-quality passenger mutations." PeerJ 12 (September 6, 2024): e17991. http://dx.doi.org/10.7717/peerj.17991.

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Most computational methods for predicting driver mutations have been trained using positive samples, while negative samples are typically derived from statistical methods or putative samples. The representativeness of these negative samples in capturing the diversity of passenger mutations remains to be determined. To tackle these issues, we curated a balanced dataset comprising driver mutations sourced from the COSMIC database and high-quality passenger mutations obtained from the Cancer Passenger Mutation database. Subsequently, we encoded the distinctive features of these mutations. Utilizi

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Miyagi, Hiroko, Joshua Linscott, Billie Gould, et al. "Differential mutation profiles between benign and cancerous urothelium in patients with non-muscle invasive bladder cancer (NMIBC)." Journal of Clinical Oncology 42, no. 4_suppl (2024): 675. http://dx.doi.org/10.1200/jco.2024.42.4_suppl.675.

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675 Background: Differentiating passenger and driver mutations of oncogenesis is essential in understanding disease biology and developing biomarkers that use genomic mutations for diagnosis or prognostication. Accumulating research shows normal urothelium harbors many mutations commonly reported in molecular profiling of urothelial carcinoma. This is especially true of NMIBC. Here, genetic profiling of the mutational landscape of pathologic NMIBC tumors (pNMIBC) was performed and compared to matched pathologically benign urothelial tissue (pBT) to determine the frequency of passenger mutation

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Hess, Julian M., Andre Bernards, Jaegil Kim, et al. "Passenger Hotspot Mutations in Cancer." Cancer Cell 36, no. 3 (2019): 288–301. http://dx.doi.org/10.1016/j.ccell.2019.08.002.

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8

Fulmer, Tim. "Passenger mutations take the wheel." Science-Business eXchange 5, no. 35 (2012): 915. http://dx.doi.org/10.1038/scibx.2012.915.

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9

Cross, Frederick R., Michal Breker, and Kristi Lieberman. "Validated Bayesian Differentiation of Causative and Passenger Mutations." G3 Genes|Genomes|Genetics 7, no. 7 (2017): 2081–94. http://dx.doi.org/10.1534/g3.117.039016.

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Abstract In many contexts, the problem arises of determining which of many candidate mutations is the most likely to be causative for some phenotype. It is desirable to have a way to evaluate this probability that relies as little as possible on previous knowledge, to avoid bias against discovering new genes or functions. We have isolated mutants with blocked cell cycle progression in Chlamydomonas and determined mutant genome sequences. Due to the intensity of UV mutagenesis required for efficient mutant collection, the mutants contain multiple mutations altering coding sequence. To provide a

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Skead, Kimberly, Armande Ang Houle, Sagi Abelson, et al. "Opposing Evolutionary Pressures Drive Clonal Evolution and Health Outcomes in the Aging Blood System." Blood 136, Supplement 1 (2020): 37. http://dx.doi.org/10.1182/blood-2020-142086.

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The age-associated accumulation of somatic mutations and large-scale structural variants (SVs) in the early hematopoietic hierarchy have been linked to premalignant stages for cancer and cardiovascular disease (CVD). However, only a small proportion of individuals harboring these mutations progress to disease, and mechanisms driving the transformation to malignancy remains unclear. Hematopoietic evolution, and cancer evolution more broadly, has largely been studied through a lens of adaptive evolution and the contribution of functionally neutral or mildly damaging mutations to early disease-as

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11

Pon, Julia R., and Marco A. Marra. "Driver and Passenger Mutations in Cancer." Annual Review of Pathology: Mechanisms of Disease 10, no. 1 (2015): 25–50. http://dx.doi.org/10.1146/annurev-pathol-012414-040312.

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12

Salvadores, Marina, David Mas-Ponte, and Fran Supek. "Passenger mutations accurately classify human tumors." PLOS Computational Biology 15, no. 4 (2019): e1006953. http://dx.doi.org/10.1371/journal.pcbi.1006953.

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13

Gopakumar, Jk, Joshua Weinstock, Bala B. Burugula, et al. "Clonal Hematopoiesis Is Driven By Aberrant Activation of TCL1A." Blood 138, Supplement 1 (2021): 597. http://dx.doi.org/10.1182/blood-2021-153242.

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Abstract Introduction: Clonal hematopoiesis of indeterminate potential (CHIP) may occur when a hematopoietic stem cell (HSC) acquires a fitness-increasing mutation resulting in its clonal expansion. A diverse set of driver genes, such as regulators of DNA methylation, splicing, and chromatin remodeling, have been associated with CHIP, but it remains largely unknown why HSCs bearing these mutations are positively selected. It has been challenging to identify the genetic and environmental factors mediating clonal expansion in humans, partially due to a lack of large cohorts with longitudinal blo

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Wodarz, Dominik, Alan C. Newell, and Natalia L. Komarova. "Passenger mutations can accelerate tumour suppressor gene inactivation in cancer evolution." Journal of The Royal Society Interface 15, no. 143 (2018): 20170967. http://dx.doi.org/10.1098/rsif.2017.0967.

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Carcinogenesis is an evolutionary process whereby cells accumulate multiple mutations. Besides the ‘driver mutations’ that cause the disease, cells also accumulate a number of other mutations with seemingly no direct role in this evolutionary process. They are called passenger mutations. While it has been argued that passenger mutations render tumours more fragile due to reduced fitness, the role of passenger mutations remains understudied. Using evolutionary computational models, we demonstrate that in the context of tumour suppressor gene inactivation (and hence fitness valley crossing), the

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Al-Issa, Karam, Mikkael A. Sekeres, Alek d. Nielsen, et al. "TP53 Mutations and Outcome in Patients with Myelodysplastic Syndromes (MDS)." Blood 128, no. 22 (2016): 4336. http://dx.doi.org/10.1182/blood.v128.22.4336.4336.

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Abstract Objectives: TP53, a tumor suppressor gene, is frequently mutated in myeloid malignancies. The negative impact of TP53 mutations in myelodysplastic syndromes (MDS) has been described previously but there is controversy regarding the prognostic impact of the mutation's characteristics (location, type, passenger vs. driver, and others). Methods: We sequenced DNA samples from 732 patients (pts) with MDS and related myeloid malignancies for the presence of TP53 mutations and 61 other genes that have been described as recurrently mutated in MDS. Overall survival (OS) was measured from the t

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Auslander, Noam, Yuri I. Wolf, and Eugene V. Koonin. "In silico learning of tumor evolution through mutational time series." Proceedings of the National Academy of Sciences 116, no. 19 (2019): 9501–10. http://dx.doi.org/10.1073/pnas.1901695116.

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Cancer arises through the accumulation of somatic mutations over time. Understanding the sequence of mutation occurrence during cancer progression can assist early and accurate diagnosis and improve clinical decision-making. Here we employ long short-term memory (LSTM) networks, a class of recurrent neural network, to learn the evolution of a tumor through an ordered sequence of mutations. We demonstrate the capacity of LSTMs to learn complex dynamics of the mutational time series governing tumor progression, allowing accurate prediction of the mutational burden and the occurrence of mutations

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17

Reimand, Jüri, and Oliver Ocsenas. "Abstract 1508: Chromatin accessibility of primary human cancers ties regional mutational processes with tissues of origin." Cancer Research 82, no. 12_Supplement (2022): 1508. http://dx.doi.org/10.1158/1538-7445.am2022-1508.

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Abstract Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. However, the underlying mechanisms of this mutagenesis and its functional and genetic determinants remain poorly understood. Somatic regional mutagenesis is known to correlate with DNA replication timing and chromatin accessibility; however, these studies have used epigenetic information from common cell lines while the epigenomes of primary human cancers remain uncharacterized in this context. Here we model megabase-scale mutation frequencies of single nucleotide variants (SNVs) in th

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Freischel, Audrey R., Jamie K. Teer, Kimberly Luddy, et al. "Evolutionary Analysis of TCGA Data Using Over- and Under- Mutated Genes Identify Key Molecular Pathways and Cellular Functions in Lung Cancer Subtypes." Cancers 15, no. 1 (2022): 18. http://dx.doi.org/10.3390/cancers15010018.

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We identify critical conserved and mutated genes through a theoretical model linking a gene’s fitness contribution to its observed mutational frequency in a clinical cohort. “Passenger” gene mutations do not alter fitness and have mutational frequencies determined by gene size and the mutation rate. Driver mutations, which increase fitness (and proliferation), are observed more frequently than expected. Non-synonymous mutations in essential genes reduce fitness and are eliminated by natural selection resulting in lower prevalence than expected. We apply this “evolutionary triage” principle to

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19

Oh, David, Steph Owen, Luka Opasic, and Jacob Scott. "Abstract A006: Modeling the impact of driver mutations on local tumor heterogeneity." Cancer Research 82, no. 10_Supplement (2022): A006. http://dx.doi.org/10.1158/1538-7445.evodyn22-a006.

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Abstract Tumors consist of an accumulation of somatic mutations, some of which are “passenger” mutations which do not contribute to positive selection of cancer cells and others of which are “driver” mutations which confer a growth advantage, the benefit of which may vary depending on the type of mutation, to tumor cells. As genomic sequencing to identify driver mutations is typically only done on small samples of a tumor, identification of these driver mutations may be complicated by intra-tumor spatial heterogeneity. With this in mind, we decided to create a basic model of different classes

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Cho, Ara, Jung Eun Shim, Eiru Kim, Fran Supek, Ben Lehner, and Insuk Lee. "MUFFINN: cancer gene discovery via network analysis of somatic mutation data." Genome Biology 17, no. 1 (2016): 129. https://doi.org/10.1186/s13059-016-0989-x.

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A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of

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21

Cutigi, Jorge Francisco, Adriane Feijo Evangelista, and Adenilso Simao. "Approaches for the identification of driver mutations in cancer: A tutorial from a computational perspective." Journal of Bioinformatics and Computational Biology 18, no. 03 (2020): 2050016. http://dx.doi.org/10.1142/s021972002050016x.

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Cancer is a complex disease caused by the accumulation of genetic alterations during the individual’s life. Such alterations are called genetic mutations and can be divided into two groups: (1) Passenger mutations, which are not responsible for cancer and (2) Driver mutations, which are significant for cancer and responsible for its initiation and progression. Cancer cells undergo a large number of mutations, of which most are passengers, and few are drivers. The identification of driver mutations is a key point and one of the biggest challenges in Cancer Genomics. Many computational methods f

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22

Wang, Taia T. "Passenger mutations: Backseat drivers in failed translation." Science Translational Medicine 7, no. 302 (2015): 302ec148. http://dx.doi.org/10.1126/scitranslmed.aad1826.

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23

Stan, Anda, Korey Bosart, Mehak Kaur, et al. "Detection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms." PLOS ONE 19, no. 2 (2024): e0299114. http://dx.doi.org/10.1371/journal.pone.0299114.

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Analyzed endometrial cancer (EC) genomes have allowed for the identification of molecular signatures, which enable the classification, and sometimes prognostication, of these cancers. Artificial intelligence algorithms have facilitated the partitioning of mutations into driver and passenger based on a variety of parameters, including gene function and frequency of mutation. Here, we undertook an evaluation of EC cancer genomes deposited on the Catalogue of Somatic Mutations in Cancers (COSMIC), with the goal to classify all mutations as either driver or passenger. Our analysis showed that appr

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McFarland, C. D., K. S. Korolev, G. V. Kryukov, S. R. Sunyaev, and L. A. Mirny. "Impact of deleterious passenger mutations on cancer progression." Proceedings of the National Academy of Sciences 110, no. 8 (2013): 2910–15. http://dx.doi.org/10.1073/pnas.1213968110.

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25

Uccellini, Melissa B., Susana V. Bardina, Maria Teresa Sánchez-Aparicio, et al. "Passenger Mutations Confound Phenotypes of SARM1-Deficient Mice." Cell Reports 31, no. 1 (2020): 107498. http://dx.doi.org/10.1016/j.celrep.2020.03.062.

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26

Ocsenas, Oliver, and Jüri Reimand. "Chromatin accessibility of primary human cancers ties regional mutational processes and signatures with tissues of origin." PLOS Computational Biology 18, no. 8 (2022): e1010393. http://dx.doi.org/10.1371/journal.pcbi.1010393.

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Somatic mutations in cancer genomes are associated with DNA replication timing (RT) and chromatin accessibility (CA), however these observations are based on normal tissues and cell lines while primary cancer epigenomes remain uncharacterised. Here we use machine learning to model megabase-scale mutation burden in 2,500 whole cancer genomes and 17 cancer types via a compendium of 900 CA and RT profiles covering primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than those of normal tissues, are most predictive of regional mutagenesis in most cancer types. F

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Madhumita, Madhumita, Jon Teague, Philip A. Beer, and Zbyslaw Sondka. "Abstract 7507: Towards transparent and context-specific annotation of driver and passenger mutations in cancer." Cancer Research 85, no. 8_Supplement_1 (2025): 7507. https://doi.org/10.1158/1538-7445.am2025-7507.

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Abstract Cancer arises from the accumulation of somatic genetic alterations, with only a subset acting as "drivers" that promote malignant transformation. Distinguishing between driver and passenger mutations is fundamental for both clinical and research applications, yet current in-silico variant annotation tools often fall short. Our previous evaluation of multiple algorithms revealed a concerning reliance on pre-computed, black-box models that are rarely updated and typically limited to missense mutations. These tools also lack transparency and biological context, leading to inconsistent pr

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Kostakioti, Maria, та Christos Stathopoulos. "Role of the α-Helical Linker of the C-Terminal Translocator in the Biogenesis of the Serine Protease Subfamily of Autotransporters". Infection and Immunity 74, № 9 (2006): 4961–69. http://dx.doi.org/10.1128/iai.00103-06.

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ABSTRACT Autotransporters are secreted virulence factors that comprise three domains: an N-terminal signal peptide, an internal passenger domain, and a C-terminal β-domain. The mechanism of passenger translocation across the outer membrane remains undefined, with four models having been proposed: the “hairpin,” the “threading,” the “multimeric,” and the “Omp85 (YaeT)” models. In an attempt to understand autotransporter biogenesis, we screened the sequences of the serine protease subfamily of autotransporters (SPATEs) for conserved features indicative of a common secretion mechanism. Our analys

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Murray, Gemma G. R., André E. R. Soares, Ben J. Novak, et al. "Natural selection shaped the rise and fall of passenger pigeon genomic diversity." Science 358, no. 6365 (2017): 951–54. http://dx.doi.org/10.1126/science.aao0960.

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The extinct passenger pigeon was once the most abundant bird in North America, and possibly the world. Although theory predicts that large populations will be more genetically diverse, passenger pigeon genetic diversity was surprisingly low. To investigate this disconnect, we analyzed 41 mitochondrial and 4 nuclear genomes from passenger pigeons and 2 genomes from band-tailed pigeons, which are passenger pigeons’ closest living relatives. Passenger pigeons’ large population size appears to have allowed for faster adaptive evolution and removal of harmful mutations, driving a huge loss in their

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Alejandre, Carla, Jorge Calle-Espinosa, and Jaime Iranzo. "Synergistic epistasis among cancer drivers can rescue early tumors from the accumulation of deleterious passengers." PLOS Computational Biology 20, no. 4 (2024): e1012081. http://dx.doi.org/10.1371/journal.pcbi.1012081.

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Epistasis among driver mutations is pervasive and explains relevant features of cancer, such as differential therapy response and convergence towards well-characterized molecular subtypes. Furthermore, a growing body of evidence suggests that tumor development could be hampered by the accumulation of slightly deleterious passenger mutations. In this work, we combined empirical epistasis networks, computer simulations, and mathematical models to explore how synergistic interactions among driver mutations affect cancer progression under the burden of slightly deleterious passengers. We found tha

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Walter, Matthew J. "Biology of Myelodysplasia Clonality: Clinical Implications of Whole-Genome Sequencing." Blood 120, no. 21 (2012): SCI—32—SCI—32. http://dx.doi.org/10.1182/blood.v120.21.sci-32.sci-32.

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Abstract Abstract SCI-32 The discovery of acquired genetic mutations associated with myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) has rapidly expanded with the use of next-generation sequencing technologies. The distinction between MDS and de novo or secondary AML (arising after MDS) and therapeutic recommendations are largely based on the presence of morphologic dysplasia and the percentage of bone marrow myeloblasts. Using whole genome sequencing to define the allele burden of hundreds of mutations, our group has shown that nearly all the bone marrow cells in seven patien

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Graim, Kiley. "Abstract 5030: Intra-patient tumor evolution analysis in dogs with many mammary tumors identifies signatures of tumor aggression in early-stage breast cancers." Cancer Research 82, no. 12_Supplement (2022): 5030. http://dx.doi.org/10.1158/1538-7445.am2022-5030.

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Abstract Despite tremendous improvements in breast cancer detection, it remains unclear which early-stage tumors will later become aggressive. Dogs provide a unique opportunity to unravel early-stage tumor evolution, as dogs frequently develop multiple naturally occurring mammary tumors. To identify which early-stage human breast tumors will later become malignant, we analyzed mutational profiles of mammary tumors from two canine cohorts to identify patterns of tumor evolution. We compared our dog tumor signatures with human breast cancers. We found that dogs and humans share many known cancer

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Pipek, Orsolya, Laura Vizkeleti, Viktória Doma, et al. "The Driverless Triple-Wild-Type (BRAF, RAS, KIT) Cutaneous Melanoma: Whole Genome Sequencing Discoveries." Cancers 15, no. 6 (2023): 1712. http://dx.doi.org/10.3390/cancers15061712.

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The genetic makeup of the triple-wild-type melanoma (BRAF, NRAS and NF1) has been known for some time, but those studies grouped together rare histopathological versions with common ones, as well as mucosal and even uveal ones. Here we used whole genome sequencing to genetically characterize the triple-wild-type melanoma (TWM), termed here as BRAF, RAS and KIT wild type (the most frequent oncogenic drivers of skin melanoma), using the most common histological forms and excluding rare ones. All these tumors except one were clearly induced by UV based on the mutational signature. The tumor mutat

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Bozic, I., T. Antal, H. Ohtsuki, et al. "Accumulation of driver and passenger mutations during tumor progression." Proceedings of the National Academy of Sciences 107, no. 43 (2010): 18545–50. http://dx.doi.org/10.1073/pnas.1010978107.

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35

McFarland, Christopher D., Julia A. Yaglom, Jonathan W. Wojtkowiak, et al. "The Damaging Effect of Passenger Mutations on Cancer Progression." Cancer Research 77, no. 18 (2017): 4763–72. http://dx.doi.org/10.1158/0008-5472.can-15-3283-t.

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van Vlijmen, B. J. M., and R. J. Westrick. "Backseat drivers: passenger mutations take control of experimental phenotypes." Journal of Thrombosis and Haemostasis 14, no. 8 (2016): 1615–17. http://dx.doi.org/10.1111/jth.13373.

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Bozic, Ivana, Jeffrey M. Gerold, and Martin A. Nowak. "Quantifying Clonal and Subclonal Passenger Mutations in Cancer Evolution." PLOS Computational Biology 12, no. 2 (2016): e1004731. http://dx.doi.org/10.1371/journal.pcbi.1004731.

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Nechanitzky, Robert, and Tak Wah Mak. "Passenger Mutations Identified in the Blink of an Eye." Immunity 43, no. 1 (2015): 9–11. http://dx.doi.org/10.1016/j.immuni.2015.07.004.

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39

Ackert-Bicknell, Cheryl L., and Clifford J. Rosen. "Passenger Gene Mutations: Unwanted Guests in Genetically Modified Mice." Journal of Bone and Mineral Research 31, no. 2 (2016): 270–73. http://dx.doi.org/10.1002/jbmr.2772.

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40

Panja, Sukanya, Padmaja Mantri, Juan Andrade Martinez, and Marcin Imielinski. "Abstract 7369: Passenger mutations link cellular origins and transcriptional identity in human lung adenocarcinoma." Cancer Research 84, no. 6_Supplement (2024): 7369. http://dx.doi.org/10.1158/1538-7445.am2024-7369.

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Abstract Lineage plasticity hinders identification of cellular origin of cancers, as malignant cells cease to resemble benign cells from which they presumably evolved. Lung adenocarcinoma (LUAD), the most common primary lung cancer in United States is thought to arise from alveolar type II (AT2) cells. However recent mouse models have shown that LUADs may also arise from other cell types such as basal and club. Although such mouse models are considered to be gold standard for identifying cell of origin for cancers, they are generally limited to a specific genetic context and lack all cell type

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Yen, Yihfen T., Casey Tsang, Todd A. Cameron, Dennis O. Ankrah, Athina Rodou та Christos Stathopoulos. "Importance of Conserved Residues of the Serine Protease Autotransporter β-Domain in Passenger Domain Processing and β-Barrel Assembly". Infection and Immunity 78, № 8 (2010): 3516–28. http://dx.doi.org/10.1128/iai.00390-10.

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ABSTRACT Serine protease autotransporters of the family Enterobacteriaceae (SPATE) comprise a family of virulence proteins secreted by enteric Gram-negative bacteria via the autotransporter secretion pathway. A SPATE polypeptide contains a C-terminal translocator domain that inserts into the bacterial outer membrane as a β-barrel structure and mediates secretion of the passenger domain to the extracellular environment. In the present study, we examined the role of conserved residues located in the SPATE β-barrel-forming region in passenger domain secretion. Thirty-nine fully conserved residues

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Hatlen, Megan A., Kanika Arora, Vladimir Vacic, et al. "Integrative genetic analysis of mouse and human AML identifies cooperating disease alleles." Journal of Experimental Medicine 213, no. 1 (2015): 25–34. http://dx.doi.org/10.1084/jem.20150524.

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t(8;21) is one of the most frequent chromosomal abnormalities observed in acute myeloid leukemia (AML). However, expression of AML1-ETO is not sufficient to induce transformation in vivo. Consistent with this observation, patients with this translocation harbor additional genetic abnormalities, suggesting a requirement for cooperating mutations. To better define the genetic landscape in AML and distinguish driver from passenger mutations, we compared the mutational profiles of AML1-ETO–driven mouse models of leukemia with the mutational profiles of human AML patients. We identified TET2 and PT

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Uchida, Shiro, and Takashi Sugino. "ERBB2-Mutant Gastrointestinal Tumors Represent Heterogeneous Molecular Biology, Particularly in Microsatellite Instability, Tumor Mutation Burden, and Co-Mutated Genes: An In Silico Study." Current Issues in Molecular Biology 45, no. 9 (2023): 7404–16. http://dx.doi.org/10.3390/cimb45090468.

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During recent years, activating mutations in ERBB2 have been reported in solid tumors of various organs, and clinical trials targeting ERBB2-mutant tumors have been conducted. However, no effective treatment has been established for gastrointestinal tumors targeting ERBB2 mutations. ERBB2-mutant tumors have a higher tumor mutation burden (TMB) and microsatellite instability (MSI) than ERBB2 non-mutant tumors, but not all ERBB2-mutant tumors are TMB- and MSI-high. Thus, a more detailed classification of ERBB2-mutant tumors based on the underlying molecular mechanisms is required. Herein, we cla

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Meiliana, Anna, Nurrani Mustika Dewi, and Andi Wijaya. "Cancer Genetics and Epigenetics in Cancer Risk Assesment." Molecular and Cellular Biomedical Sciences 5, no. 2 (2021): 41. http://dx.doi.org/10.21705/mcbs.v5i2.198.

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Compared to the normal tissues, cancer cells tend to have higher proliferation rate and often lost their ability to undergo apoptosis. In addition, cancer cells can separate themselves from their original tissue thus causing metastasis in other part of body. While undergoing program cell death, disordered cellular programming can happen. The main causes of this cellular programming anomaly are epigenetic and genetic alterations, which have been known as two separate mechanisms in carcinogenetic. A recent outcome of whole exome sequencing of thousands of human cancers has been the unexpected di

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Wang, Tao, Shasha Ruan, Xiaolu Zhao, et al. "OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers." Nucleic Acids Research 49, no. D1 (2020): D1289—D1301. http://dx.doi.org/10.1093/nar/gkaa1033.

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Abstract The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33

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Bauer, Benedikt, Reiner Siebert, and Arne Traulsen. "Cancer initiation with epistatic interactions between driver and passenger mutations." Journal of Theoretical Biology 358 (October 2014): 52–60. http://dx.doi.org/10.1016/j.jtbi.2014.05.018.

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Vanden Berghe, Tom, Paco Hulpiau, Liesbet Martens, et al. "Passenger Mutations Confound Interpretation of All Genetically Modified Congenic Mice." Immunity 43, no. 1 (2015): 200–209. http://dx.doi.org/10.1016/j.immuni.2015.06.011.

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Rogers, Mark F., Tom R. Gaunt, and Colin Campbell. "CScape-somatic: distinguishing driver and passenger point mutations in the cancer genome." Bioinformatics 36, no. 12 (2020): 3637–44. http://dx.doi.org/10.1093/bioinformatics/btaa242.

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Abstract Motivation Next-generation sequencing technologies have accelerated the discovery of single nucleotide variants in the human genome, stimulating the development of predictors for classifying which of these variants are likely functional in disease, and which neutral. Recently, we proposed CScape, a method for discriminating between cancer driver mutations and presumed benign variants. For the neutral class, this method relied on benign germline variants found in the 1000 Genomes Project database. Discrimination could, therefore, be influenced by the distinction of germline versus soma

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Lindberg, Markus, Martin Boström, Kerryn Elliott, and Erik Larsson. "Intragenomic variability and extended sequence patterns in the mutational signature of ultraviolet light." Proceedings of the National Academy of Sciences 116, no. 41 (2019): 20411–17. http://dx.doi.org/10.1073/pnas.1909021116.

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Mutational signatures can reveal properties of underlying mutational processes and are important when assessing signals of selection in cancer. Here, we describe the sequence characteristics of mutations induced by ultraviolet (UV) light, a major mutagen in several human cancers, in terms of extended (longer than trinucleotide) patterns as well as variability of the signature across chromatin states. Promoter regions display a distinct UV signature with reduced TCG > TTG transitions, and genome-wide mapping of UVB-induced DNA photoproducts (pyrimidine dimers) showed that this may be explain

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Tsang, Casey, Huma Malik, Deana Nassman, et al. "Intramolecular Interactions between the Protease and Structural Domains Are Important for the Functions of Serine Protease Autotransporters." Infection and Immunity 78, no. 8 (2010): 3335–45. http://dx.doi.org/10.1128/iai.00129-10.

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ABSTRACT Autotransporter (AT) is a protein secretion pathway found in Gram-negative bacteria featuring a multidomain polypeptide with a signal sequence, a passenger domain, and a translocator domain. An AT subfamily named serine protease ATs of the family Enterobacteriaceae (SPATEs) is characterized by the presence of a conserved serine protease motif in the passenger domain which contributes to bacterial pathogenesis. The goal of the current study is to determine the importance of the passenger domain conserved residues in the SPATE proteolytic and adhesive functions using the temperature-sen

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