Analysis of lung tumor evolution reveals drivers of metastasis

A Cell paper published in May co-led by scientists including Ludwig MIT’s Jonathan Weissman and Co-director Tyler Jacks reported a granular analysis of lung cancer evolution in a genetically engineered mouse model (GEMM), tracing the lineage of tumor cells in unprecedented detail. The study employed a GEMM of lung adenocarcinoma, driven by oncogenic Kras and loss of the p53 tumor suppressor, that faithfully mimics human tumor progression. The cancer was initiated in the GEMM by a virus, which also activated a CRISPR-based cell-tracing technology—a DNA barcode that changes discreetly with each cell division. This allowed the researchers to generate granular family trees of cells that ultimately seeded metastases. Their analysis revealed considerable diversity among subpopulations of tumor cells, which sampled diverse transcriptional states early in the course of tumor evolution before settling into one that conferred greatest fitness. Notably, the cells evolved mainly via inherited changes to their gene expression programs rather than mutation, and the fittest of such states came to dominate the tumor and to drive metastasis late in lung tumor evolution. The methods developed for this study can now be applied to study many other clinically relevant aspects of tumor evolution, like the development of drug resistance.

Read the study: Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution, Cell, 2022 May 5 Epub

This article appeared in the September 2022 issue of Ludwig Link. Click here to download a PDF (1 MB).


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