GepiClock: a proposed epigenetic clock for cancer and age-linked drug sensitivities
The abstract describes GepiClock, an epigenetic clock trained on DNA methylation from 32 cancer types, which predicted age in tumour and normal samples; in cell lines, younger-predicted lines were more sensitive to mTOR, MEK1/2 and HSP90 inhibitors, older-predicted lines to AKT and PI3Kα inhibitors. [1]
Automatic summary · not editorially reviewed
The key findings
Epigenetic clocks estimate biological age from DNA methylation but perform poorly in cancer due to extensive epigenetic reprogramming, limiting study of ageing in tumour biology. [1]
GepiClock, based on 4,862 CpG sites, accurately predicted age across both tumour and normal samples. [1]
In cancer cell lines, younger-predicted lines were more sensitive to mTOR, MEK1/2 and HSP90 inhibitors, while older-predicted lines were more sensitive to AKT and PI3Kα inhibitors. [1]
The source at a glance
- Study type / format
- Research abstract describing development and application of an epigenetic clock
- Population / context
- DNA methylation data from 32 cancer types in The Cancer Genome Atlas, plus molecularly profiled cancer cell lines with drug response and CRISPR screening data.
- Summary based on
- Study abstract
- Publication status
- Preprint · peer-review status not confirmed
- Original publication
- June 26, 2026
Why cancer needed a new methylation clock
The abstract states that epigenetic clocks estimate biological age from DNA methylation patterns but perform poorly in cancer because of extensive epigenetic reprogramming, which limits the study of ageing in tumour biology. The authors therefore developed GepiClock, described as an epigenetic clock trained on DNA methylation data from 32 cancer types in The Cancer Genome Atlas. This is a proposed research tool, not a validated clinical test.
Supporting source [1]
Age prediction across tumours and normal samples
GepiClock is based on 4,862 CpG sites (DNA positions where methylation is measured). According to the abstract, it accurately predicts age across both tumour and normal samples, which the authors say indicates that core ageing-associated methylation programmes remain detectable despite malignant transformation. The abstract does not report sample sizes, prediction error values or validation in independent cohorts.
Supporting source [1]
Predicted age and drug sensitivity in cell lines
Applying GepiClock to molecularly profiled cancer cell lines with matched drug response and CRISPR screening data revealed age-associated vulnerabilities. Younger-predicted cell lines were more sensitive to mTOR, MEK1/2 and HSP90 inhibitors, whereas older-predicted lines showed increased sensitivity to AKT and PI3Kα inhibitors. Additional cancer-type-specific patterns and age-associated genetic dependencies were identified. These are associations in cell lines, not evidence of benefit in patients; the abstract gives no effect sizes or numbers of cell lines.
Supporting source [1]
How to interpret this
This explainer is based only on the abstract; the full text was not reviewed. The abstract reports no sample sizes, prediction-error values, effect sizes or independent validation, and the drug-sensitivity findings come from cell lines, so they are associations rather than evidence of patient benefit.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Fernández-Rebollo I, Digilio A, Oikonomou A, Trastulla L, Esteller M, Iorio F. · europepmc.org · June 26, 2026