ArticleOncotarget2018
Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Article
- Profibrotic Inflammatory Cytokines and Growth Factors Are Predicted as the Key Targets ofPharmaceuticals (Basel, Switzerland) · 2024Article
- Synergistic epistasis among cancer drivers can rescue early tumors from the accumulation of deleterious passengers.PLoS computational biology · 2024Article
- Pairwise and higher-order epistatic effects among somatic cancer mutations across oncogenesis.Mathematical biosciences · 2023Article
- Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools.Journal of molecular evolution · 2023Review
- Author Reply: In Response to "De NovoJTO clinical and research reports · 2022Article
- The somatic molecular evolution of cancer: Mutation, selection, and epistasis.Progress in biophysics and molecular biology · 2021Article
- Getting quantitative on the effects of somatic mutation on cancer.Oncoscience · 2020Article
- Eleven grand challenges in single-cell data science.Genome biology · 2020Review
- Molecular Biology and Evolution of Cancer: From Discovery to Action.Molecular biology and evolution · 2020Article
- Effect Sizes of Somatic Mutations in Cancer.Journal of the National Cancer Institute · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Currently, drug development efforts and clinical trials to test them are often prioritized by targeting genes with high frequencies of somatic variants among tumors. However, differences in oncogenic mutation rate-not necessarily the effect the variant has on tumor growth-contribute enormously to somatic variant frequency. We argue that decoupling the contributions of mutation and cancer lineage selection to the frequency of somatic variants among tumors is critical to understanding-and predicting-the therapeutic potential of different interventions. To provide an indicator of that strength of selection and therapeutic potential, the frequency at which we observe a given variant across patients must be modulated by our expectation given the mutation rate and target size to provide an indicator of that strength of selection and therapeutic potential. Additionally, antagonistic and synergistic epistasis among mutations also impacts the potential therapeutic benefit of targeted drug development. Quantitative approaches should be fostered that use the known genetic architectures of cancer types, decouple mutation rate, and provide rigorous guidance regarding investment in targeted drug development. By integrating evolutionary principles and detailed mechanistic knowledge into those approaches, we can maximize our ability to identify those targeted therapies most likely to yield substantial clinical benefit.
Indexed as
Identifiers
What OpenQuestion holds
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.