ArticleeLife2021
Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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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
15 citing papers in PubMed.
- Comprehensive Genomic Analysis of Normal and Cancer Cells Elucidates the Elevated Mutational Burden in Cancer.Cancer research · 2026Article
- Senescent obesity signature in breast cancer: a paradigm of reverse cardio-oncology.European heart journal · 2026Review
- An investigative network analysis mapping global cancer epidemiology.Theory in biosciences = Theorie in den Biowissenschaften · 2026Article
- Adiposity and cancer: epidemiology, mechanisms and future perspectives.Nature metabolism · 2026Review
- Definition of Sporadic Early-Onset Invasive Solid Organ Cancers in Adults.Oncology and therapy · 2026Article
- Identifying somatic fingerprints of cancers defined by germline and environmental risk factors.Genetic epidemiology · 2024Article
- A review on trends in development and translation of omics signatures in cancer.Computational and structural biotechnology journal · 2024Review
- Accurate and sensitive mutational signature analysis with MuSiCal.Nature genetics · 2024Article
- Obesity-associated changes in molecular biology of primary breast cancer.Nature communications · 2023Article
- Evaluating cancer etiology and risk with a mathematical model of tumor evolution.Nature communications · 2022Article
- Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis.Diagnostics (Basel, Switzerland) · 2022Review
- Genome-wide mutational signatures in low-coverage whole genome sequencing of cell-free DNA.Nature communications · 2022Article
- Mutational signatures and processes in hepatobiliary cancers.Nature reviews. Gastroenterology & hepatology · 2022Review
- Premetastatic shifts of endogenous and exogenous mutational processes support consolidative therapy in EGFR-driven lung adenocarcinoma.Cancer letters · 2022Article
- Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Determining the etiologic basis of the mutations that are responsible for cancer is one of the fundamental challenges in modern cancer research. Different mutational processes induce different types of DNA mutations, providing 'mutational signatures' that have led to key insights into cancer etiology. The most widely used signatures for assessing genomic data are based on unsupervised patterns that are then retrospectively correlated with certain features of cancer. We show here that supervised machine-learning techniques can identify signatures, called SuperSigs, that are more predictive than those currently available. Surprisingly, we found that aging yields different SuperSigs in different tissues, and the same is true for environmental exposures. We were able to discover SuperSigs associated with obesity, the most important lifestyle factor contributing to cancer in Western populations.
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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.