ArticleScientific reports2022
Collateral responses to classical cytotoxic chemotherapies are heterogeneous and sensitivities are sparse.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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.
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Who cites it
4 citing papers in PubMed.
- Targeting programmed cell death: a novel therapeutic paradigm for cancer based on mode-of-death classification.Apoptosis : an international journal on programmed cell death · 2026Review
- Molecular and Functional Interactions Between Cisplatin and Nicotinamide: A Combined Computational, Spectroscopic, and Biological Study.International journal of molecular sciences · 2026Article
- Programming tumor evolution with selection gene drives to proactively combat drug resistance.Nature biotechnology · 2025Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Chemotherapy resistance is a major obstacle to curing cancer patients. Combination drug regimens have shown promise as a method to overcome resistance; however, to date only some cancers have been cured with this method. Collateral sensitivity-the phenomenon whereby resistance to one drug is co-occurrent with sensitivity to a second drug-has been gaining traction as a promising new concept to guide rational design of combination regimens. Here we evolved over 100 subclones of the Eµ-Myc; p19
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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.