Darryl Shibata | Search PubMed

PubMed2026

Differences between mitotically old and young endometrial tumors.

Human tumors likely differ in their mitotic ages, reflecting how many divisions elapse between the final tumor progenitor cell and surgical removal. We used a rapidly fluctuating CpG (fCpG) methylation clock to infer relative endometrial adenocarcinomas (EAC) mitotic ages. Experimentally, young tumors initiated from single cells show low-diversity, high-variance fCpG distributions with trimodal peaks near 0%, 50%, and 100%, reflecting inherited progenitor methylation states. fCpG methylation becomes polymorphic with divisions, and older tumors exhibit higher diversity, lower variance, and unimodal distributions centered around 50%. Mitotic ages varied across EAC samples. Synchronous hyperplasia and invasive regions generally shared similar ages, and primary-metastatic EAC pairs showed both synchronous and stepwise progression. The Cancer Genome Atlas (TCGA) EACs also showed variable mitotic ages: younger tumors were enriched for proliferation pathways, whereas older tumors showed more immune infiltration, immune-pathway activation, and evidence of T-cell exhaustion. These results show that human tumors can be ranked by mitotic age and suggest that the growth of older cancers is restrained by immune surveillance. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Humans↗

PubMed2025

Fluctuating DNA methylation tracks cancer evolution at clinical scale.

Cancer development and response to treatment are evolutionary processes1,2, but characterizing evolutionary dynamics at a clinically meaningful scale has remained challenging3. Here we develop a new methodology called EVOFLUx, based on natural DNA methylation barcodes fluctuating over time4, that quantitatively infers evolutionary dynamics using only a bulk tumour methylation profile as input. We apply EVOFLUx to 1,976 well-characterized lymphoid cancer samples spanning a broad spectrum of diseases and show that initial tumour growth rate, malignancy age and epimutation rates vary by orders of magnitude across disease types. We measure that subclonal selection occurs only infrequently within bulk samples and detect occasional examples of multiple independent primary tumours. Clinically, we observe faster initial tumour growth in more aggressive disease subtypes, and that evolutionary histories are strong independent prognostic factors in two series of chronic lymphocytic leukaemia. Using EVOFLUx for phylogenetic analyses of aggressive Richter-transformed chronic lymphocytic leukaemia samples detected that the seed of the transformed clone existed decades before presentation. Orthogonal verification of EVOFLUx inferences is provided using additional genetic data, including long-read nanopore sequencing, and clinical variables. Collectively, we show how widely available, low-cost bulk DNA methylation data precisely measure cancer evolutionary dynamics, and provides new insights into cancer biology and clinical behaviour.

Humans↗