ArticlePLoS computational biology2015
An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 30 citations in OpenAlex.
- A latent variable model for evaluating mutual exclusivity and co-occurrence between driver mutations in cancer.bioRxiv : the preprint server for biology · 2024Article
- Uncovering the subtype-specific disease module and the development of drug response prediction models for glioma.Heliyon · 2024Article
- Identification of Novel Mutations in Colorectal Cancer Patients Using AmpliSeq Comprehensive Cancer Panel.Journal of personalized medicine · 2021Article
- Article
- Clonal evolution driven by superdriver mutations.BMC evolutionary biology · 2020Article
- On measuring selection in cancer from subclonal mutation frequencies.PLoS computational biology · 2019Article
- Motion, fixation probability and the choice of an evolutionary process.PLoS computational biology · 2019Article
- Computer simulations of the signalling network in FLT3BMC bioinformatics · 2018Article
- Population-based statistical inference for temporal sequence of somatic mutations in cancer genomes.BMC medical genomics · 2018Article
- SIApopr: a computational method to simulate evolutionary branching trees for analysis of tumor clonal evolution.Bioinformatics (Oxford, England) · 2017Article
- An agent-based model of triple-negative breast cancer: the interplay between chemokine receptor CCR5 expression, cancer stem cells, and hypoxia.BMC systems biology · 2017Article
- Mathematical Modeling Links Pregnancy-Associated Changes and Breast Cancer Risk.Cancer research · 2017Article
- LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.BMC bioinformatics · 2016Article
- Punctuated copy number evolution and clonal stasis in triple-negative breast cancer.Nature genetics · 2016Article
- Targeted Cancer Therapy: Vital Oncogenes and a New Molecular Genetic Paradigm for Cancer Initiation Progression and Treatment.International journal of molecular sciences · 2016Review
- Computational Cancer Biology: An Evolutionary Perspective.PLoS computational biology · 2016Review
- The mathematics of cancer: integrating quantitative models.Nature reviews. Cancer · 2015Review
- Stochasticity and determinism in cancer creation and progression.Convergent science physical oncology · 2015Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such "driver" mutations from innocuous "passenger" events is critical for prioritizing the validation of candidate mutations in disease-relevant models. We design a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set, and apply it to a mutational data set in colorectal cancer. Our methodology is based upon a population dynamics model of mutation accumulation and selection in colorectal tissue prior to cancer initiation as well as during tumorigenesis. This methodology can be used to aid in the prioritization of candidate mutations for functional validation and contributes to the process of drug discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.