ReviewOncogene2025
Adaptive cancer therapy: can non-genetic factors become its achilles heel?
Review in Oncogene, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Article
- Disruption of cellular timekeeping in cancer: links between circadian clocks, metabolism, and tumor progression.Molecular biology reports · 2026Review
- The Role of Monoclonal Antibody Targeted Therapy (Panitumumab) in the Treatment of Metastatic Colorectal Cancer-A Narrative Review of Current Evidence and Emerging Therapeutic Strategies.International journal of molecular sciences · 2026Review
- Endocrine therapy-specific lineage and partial epithelial-mesenchymal reprogramming defines divergent resistant cell-states in ER+ breast cancer.bioRxiv : the preprint server for biology · 2026Article
- Article
- Editorial for Special Issue "Technological Advances Around Next-Generation Sequencing".Current issues in molecular biology · 2026Article
- The Divide-Survive Matrix: decoupling proliferative drive from intrinsic survival architecture in oncology.Frontiers in oncology · 2026Article
- Targeting tumor transition windows.Exploration of targeted anti-tumor therapy · 2026Review
- A Systematic Review of Evidence for the Cost of Therapeutic Resistance in Cancer.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The recurrence of clinically advanced cancers is an evolutionary consequence of standard-of-care chemotherapies generally administered at maximum tolerated doses to kill as many cancer cells as possible. The inevitable appearance of resistance raises the possibility of shifting treatment goals from complete tumor eradication to long-term disease control. The latter approach is employed by adaptive therapy, which aims to inhibit the evolutionary dynamics governing the spread of resistant tumor phenotypes. Adaptive therapy changes focus from the cancer cells that are responsive to therapy to those that are resistant and ultimately govern outcome. This therapeutic approach retains a pool of sensitive cancer cells to compete with the therapy-resistant ones through dynamic dose modulation and/or timing. Thus, fluctuations of treatment-sensitive cells are used to control the resistant population and prolong tumor control with existing therapy agents. Here, we explore non-genetic mechanisms of resistance, including the protective role of the tumor stroma, the epithelial-to-mesenchymal transition, the overexpression of drug efflux pumps, and the extracellular vesicle-mediated transfer of them. These mechanisms can increase the size of the resistant population at the expense of the sensitive one, reducing the ability of adaptive therapy to force tumor evolution into controllable cycles.
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.