scholarly journals AI-Driver: an ensemble method for identifying driver mutations in personal cancer genomes

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Haoxuan Wang ◽  
Tao Wang ◽  
Xiaolu Zhao ◽  
Honghu Wu ◽  
Mingcong You ◽  
...  
Keyword(s):  
Human Cancer ◽  
Ensemble Method ◽  
Driver Mutations ◽  
Missense Mutations ◽  
Gene Level ◽  
Cancer Genomes ◽  
Sequencing Studies ◽  
Stable Performance ◽  
Overall Performance ◽  
Improved Methods

Abstract The current challenge in cancer research is to increase the resolution of driver prediction from gene-level to mutation-level, which is more closely aligned with the goal of precision cancer medicine. Improved methods to distinguish drivers from passengers are urgently needed to dig out driver mutations from increasing exome sequencing studies. Here, we developed an ensemble method, AI-Driver (AI-based driver classifier, https://github.com/hatchetProject/AI-Driver), to predict the driver status of somatic missense mutations based on 23 pathogenicity features. AI-Driver has the best overall performance compared with any individual tool and two cancer-specific driver predicting methods. We demonstrate the superior and stable performance of our model using four independent benchmarks. We provide pre-computed AI-Driver scores for all possible human missense variants (http://aidriver.maolab.org/) to identify driver mutations in the sea of somatic mutations discovered by personal cancer sequencing. We believe that AI-Driver together with pre-computed database will play vital important roles in the human cancer studies, such as identification of driver mutation in personal cancer genomes, discovery of targeting sites for cancer therapeutic treatments and prediction of tumor biomarkers for early diagnosis by liquid biopsy.

scholarly journals Origins and functional consequences of somatic mitochondrial DNA mutations in human cancer

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Young Seok Ju ◽  
Ludmil B Alexandrov ◽  
Moritz Gerstung ◽  
Inigo Martincorena ◽  
Serena Nik-Zainal ◽  
...  
Keyword(s):  
Human Cancer ◽  
Missense Mutations ◽  
Mtdna Mutations ◽  
Dna Mutations ◽  
Mtdna Sequence ◽  
Sequencing Studies ◽  
Functional Consequences ◽  
Somatic Alterations ◽  
Mtdna Replication ◽  
Tumor Types

Recent sequencing studies have extensively explored the somatic alterations present in the nuclear genomes of cancers. Although mitochondria control energy metabolism and apoptosis, the origins and impact of cancer-associated mutations in mtDNA are unclear. In this study, we analyzed somatic alterations in mtDNA from 1675 tumors. We identified 1907 somatic substitutions, which exhibited dramatic replicative strand bias, predominantly C > T and A > G on the mitochondrial heavy strand. This strand-asymmetric signature differs from those found in nuclear cancer genomes but matches the inferred germline process shaping primate mtDNA sequence content. A number of mtDNA mutations showed considerable heterogeneity across tumor types. Missense mutations were selectively neutral and often gradually drifted towards homoplasmy over time. In contrast, mutations resulting in protein truncation undergo negative selection and were almost exclusively heteroplasmic. Our findings indicate that the endogenous mutational mechanism has far greater impact than any other external mutagens in mitochondria and is fundamentally linked to mtDNA replication.

scholarly journals Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma

2016 ◽  
Vol 113 (42) ◽  
pp. E6409-E6417 ◽  
Author(s):  
David G. McFadden ◽  
Katerina Politi ◽  
Arjun Bhutkar ◽  
Frances K. Chen ◽  
Xiaoling Song ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Mouse Models ◽  
Cancer Progression ◽  
Large Scale ◽  
Human Cancer ◽  
Genetically Engineered ◽  
Model Systems ◽  
Driver Mutations ◽  
Genetic Profile ◽  
Genetically Engineered Mouse Models

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity.

scholarly journals Regression Modeling and Meta-Analysis of Diagnostic Accuracy of SNP-Based Pathogenicity Detection Tools for UGT1A1 Gene Mutation

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Fakher Rahim ◽  
Hamid Galehdari ◽  
Javad Mohammadi-asl ◽  
Najmaldin Saki
Keyword(s):  
Meta Analysis ◽  
Genomic Variation ◽  
Missense Mutations ◽  
Suggested Model ◽  
Pathogenicity Prediction ◽  
Mutation Score ◽  
Functional Scores ◽  
Comprehensive Search ◽  
Overall Performance

Aims. This review summarized all available evidence on the accuracy of SNP-based pathogenicity detection tools and introduced regression model based on functional scores, mutation score, and genomic variation degree. Materials and Methods. A comprehensive search was performed to find all mutations related to Crigler-Najjar syndrome. The pathogenicity prediction was done using SNP-based pathogenicity detection tools including SIFT, PHD-SNP, PolyPhen2, fathmm, Provean, and Mutpred. Overall, 59 different SNPs related to missense mutations in the UGT1A1 gene, were reviewed. Results. Comparing the diagnostic OR, our model showed high detection potential (diagnostic OR: 16.71, 95% CI: 3.38–82.69). The highest MCC and ACC belonged to our suggested model (46.8% and 73.3%), followed by SIFT (34.19% and 62.71%). The AUC analysis showed a significance overall performance of our suggested model compared to the selected SNP-based pathogenicity detection tool (P=0.046). Conclusion. Our suggested model is comparable to the well-established SNP-based pathogenicity detection tools that can appropriately reflect the role of a disease-associated SNP in both local and global structures. Although the accuracy of our suggested model is not relatively high, the functional impact of the pathogenic mutations is highlighted at the protein level, which improves the understanding of the molecular basis of mutation pathogenesis.

scholarly journals Investigating structure function relationships in the NOTCH family through large-scale somatic DNA sequencing studies

2020 ◽  
Author(s):  
Michael W J Hall ◽  
David Shorthouse ◽  
Philip H Jones ◽  
Benjamin A Hall
Keyword(s):  
Dna Sequencing ◽  
Structure Function ◽  
Calcium Binding ◽  
Large Scale ◽  
Driver Mutations ◽  
Missense Mutations ◽  
Mutant Selection ◽  
Ligand Interaction ◽  
Binding Interface

AbstractThe recent development of highly sensitive DNA sequencing techniques has detected large numbers of missense mutations of genes, including NOTCH1 and 2, in ageing normal tissues. Driver mutations persist and propagate in the tissue through a selective advantage over both wild-type cells and alternative mutations. This process of selection can be considered as a large scale, in vivo screen for mutations that increase clone fitness. It follows that the specific missense mutations that are observed in individual genes may offer us insights into the structure-function relationships. Here we show that the positively selected missense mutations in NOTCH1 and NOTCH2 in human oesophageal epithelium cause inactivation predominantly through protein misfolding. Once these mutations are excluded, we further find statistically significant evidence for selection at the ligand binding interface and calcium binding sites. In this, we observe stronger evidence of selection at the ligand interface on EGF12 over EGF11, suggesting that in this tissue EGF12 may play a more important role in ligand interaction. Finally, we show how a mutation hotspot in the NOTCH1 transmembrane helix arises through the intersection of both a high mutation rate and residue conservation. Together these insights offer a route to understanding the mechanism of protein function through in vivo mutant selection.

scholarly journals Mice deficient of Myc super-enhancer region reveal differential control mechanism between normal and pathological growth

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Kashyap Dave ◽  
Inderpreet Sur ◽  
Jian Yan ◽  
Jilin Zhang ◽  
Eevi Kaasinen ◽  
...  
Keyword(s):  
Human Cancer ◽  
Cancer Chemoprevention ◽  
Driver Mutations ◽  
Gene Desert ◽  
Enhancer Region ◽  
Myc Oncogene ◽  
Super Enhancer ◽  
High Conservation ◽  
Oncogenic Driver ◽  
Differential Control

The gene desert upstream of the MYC oncogene on chromosome 8q24 contains susceptibility loci for several major forms of human cancer. The region shows high conservation between human and mouse and contains multiple MYC enhancers that are activated in tumor cells. However, the role of this region in normal development has not been addressed. Here we show that a 538 kb deletion of the entire MYC upstream super-enhancer region in mice results in 50% to 80% decrease in Myc expression in multiple tissues. The mice are viable and show no overt phenotype. However, they are resistant to tumorigenesis, and most normal cells isolated from them grow slowly in culture. These results reveal that only cells whose MYC activity is increased by serum or oncogenic driver mutations depend on the 8q24 super-enhancer region, and indicate that targeting the activity of this element is a promising strategy of cancer chemoprevention and therapy.

scholarly journals STK11 (LKB1) missense somatic mutant isoforms promote tumor growth, motility and inflammation

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Paula Granado-Martínez ◽  
Sara Garcia-Ortega ◽  
Elena González-Sánchez ◽  
Kimberley McGrail ◽  
Rafael Selgas ◽  
...  
Keyword(s):  
Tumor Growth ◽  
Somatic Mutations ◽  
Human Cancer ◽  
Tumor Biology ◽  
Missense Mutations ◽  
Expression Of Genes ◽  
Promote Tumor Growth ◽  
Genes Encoding ◽  
Differential Gene ◽  
Somatic Mutant

AbstractElucidating the contribution of somatic mutations to cancer is essential for personalized medicine. STK11 (LKB1) appears to be inactivated in human cancer. However, somatic missense mutations also occur, and the role/s of these alterations to this disease remain unknown. Here, we investigated the contribution of four missense LKB1 somatic mutations in tumor biology. Three out of the four mutants lost their tumor suppressor capabilities and showed deficient kinase activity. The remaining mutant retained the enzymatic activity of wild type LKB1, but induced increased cell motility. Mechanistically, LKB1 mutants resulted in differential gene expression of genes encoding vesicle trafficking regulating molecules, adhesion molecules and cytokines. The differentially regulated genes correlated with protein networks identified through comparative secretome analysis. Notably, three mutant isoforms promoted tumor growth, and one induced inflammation-like features together with dysregulated levels of cytokines. These findings uncover oncogenic roles of LKB1 somatic mutations, and will aid in further understanding their contributions to cancer development and progression.

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