ArticleCell chemical biology2018
Combining Mutational Signatures, Clonal Fitness, and Drug Affinity to Define Drug-Specific Resistance Mutations in Cancer.
Article in Cell chemical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 24 citations in OpenAlex.
- Resistance to Allosteric Inhibitors.Journal of molecular biology · 2025Review
- Article
- DexDesign: an OSPREY-based algorithm for designing de novo D-peptide inhibitors.Protein engineering, design & selection : PEDS · 2024Article
- Disruptor: Computational identification of oncogenic mutants disrupting protein-protein and protein-DNA interactions.Communications biology · 2023Article
- RESISTOR: A New OSPREY Module to Predict Resistance Mutations.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- Resistor: An algorithm for predicting resistance mutations via Pareto optimization over multistate protein design and mutational signatures.Cell systems · 2022Article
- Review
- Dissecting mechanisms of resistance to targeted drug combination therapy in human colorectal cancer.Oncogene · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The emergence of mutations that confer resistance to molecularly targeted therapeutics is dependent upon the effect of each mutation on drug affinity for the target protein, the clonal fitness of cells harboring the mutation, and the probability that each variant can be generated by DNA codon base mutation. We present a computational workflow that combines these three factors to identify mutations likely to arise upon drug treatment in a particular tumor type. The Osprey-based workflow is validated using a comprehensive dataset of ERK2 mutations and is applied to small-molecule drugs and/or therapeutic antibodies targeting KIT, EGFR, Abl, and ALK. We identify major clinically observed drug-resistant mutations for drug-target pairs and highlight the potential to prospectively identify probable drug resistance mutations.
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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.