ArticleMolecular biology and evolution2014
Studying tumorigenesis through network evolution and somatic mutational perturbations in the cancer interactome.
Article in Molecular biology and evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
53 citing papers in PubMed, 97 citations in OpenAlex.
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- NESM: a network embedding method for tumor stratification by integrating multi-omics data.G3 (Bethesda, Md.) · 2022Article
- Advances in sex disparities for cancer immunotherapy: unveiling the dilemma of Yin and Yang.Biology of sex differences · 2022Review
- A comprehensive SARS-CoV-2-human protein-protein interactome network identifies pathobiology and host-targeting therapies for COVID-19.Research square · 2022Article
- Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics.Orthodontics & craniofacial research · 2021Review
- A network-based deep learning methodology for stratification of tumor mutations.Bioinformatics (Oxford, England) · 2021Article
- My personal mutanome: a computational genomic medicine platform for searching network perturbing alleles linking genotype to phenotype.Genome biology · 2021Article
- A new precision medicine initiative at the dawn of exascale computing.Signal transduction and targeted therapy · 2021Review
- Integrated Genomic Characterization of the Human Immunome in Cancer.Cancer research · 2020Article
- A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19.PLoS biology · 2020Observational
- A Network Medicine Approach to Investigation and Population-based Validation of Disease Manifestations and Drug Repurposing for COVID-19.ChemRxiv : the preprint server for chemistry · 2020Article
- Edgetic perturbation signatures represent known and novel cancer biomarkers.Scientific reports · 2020Article
- Individualized genetic network analysis reveals new therapeutic vulnerabilities in 6,700 cancer genomes.PLoS computational biology · 2020Article
- Target identification among known drugs by deep learning from heterogeneous networks.Chemical science · 2020Article
- Article
- A Systems Pharmacology Approach Uncovers Wogonoside as an Angiogenesis Inhibitor of Triple-Negative Breast Cancer by Targeting Hedgehog Signaling.Cell chemical biology · 2019Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Cells govern biological functions through complex biological networks. Perturbations to networks may drive cells to new phenotypic states, for example, tumorigenesis. Identifying how genetic lesions perturb molecular networks is a fundamental challenge. This study used large-scale human interactome data to systematically explore the relationship among network topology, somatic mutation, evolutionary rate, and evolutionary origin of cancer genes. We found the unique network centrality of cancer proteins, which is largely independent of gene essentiality. Cancer genes likely have experienced a lower evolutionary rate and stronger purifying selection than those of noncancer, Mendelian disease, and orphan disease genes. Cancer proteins tend to have ancient histories, likely originated in early metazoan, although they are younger than proteins encoded by Mendelian disease genes, orphan disease genes, and essential genes. We found that the protein evolutionary origin (age) positively correlates with protein connectivity in the human interactome. Furthermore, we investigated the network-attacking perturbations due to somatic mutations identified from 3,268 tumors across 12 cancer types in The Cancer Genome Atlas. We observed a positive correlation between protein connectivity and the number of nonsynonymous somatic mutations, whereas a weaker or insignificant correlation between protein connectivity and the number of synonymous somatic mutations. These observations suggest that somatic mutational network-attacking perturbations to hub genes play an important role in tumor emergence and evolution. Collectively, this work has broad biomedical implications for both basic cancer biology and the development of personalized cancer therapy.
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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.