Abstract
SummaryCancer is an evolutionary process characterized by profound intratumor heterogeneity (ITH), which can be quantified using in silico estimates of cancer cell fractions (CCFs) of tumor-specific somatic mutations. We demonstrate a data-driven approach based on CCF distributions to identify 4 robust pan-cancer evolutionary signatures from 4,146 tumors across 17 cancer types in The Cancer Genome Atlas (TCGA). These signatures define a continuum of cancer cell fractions reflecting neutral evolution, clonal expansion, and clonal fixation. Correlating evolutionary signatures with mutational and biological programs reveals that tumors enriched for clonal expansion and fixation are associated with immune evasion and distinct changes in the tumor immune microenvironment. Our analysis reveals a dynamic shift from adaptive to innate immune programs as tumors progress toward clonal fixation and escape immune surveillance, accompanied by the clonal expansion of driver genes modulating tumor-stroma interactions. These evolutionary dynamic subtypes are further associated with clinical outcomes and immunotherapy responses.
| Original language | English (US) |
|---|---|
| Article number | 117098 |
| Journal | Cell Reports |
| Volume | 45 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 24 2026 |
Keywords
- cancer evolution
- evolutionary dynamics
- intratumor heterogeneity
- machine learning
- pan-cancer
- tumor immune microenvironment
ASJC Scopus subject areas
- General Biochemistry, Genetics and Molecular Biology
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