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Computational Approaches to Reconstruct the Evolutionary History of Cancer Metastases

Award Number: R01CA299449
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 06/01/2026
PERIOD OF PERFORMANCE END DATE: 05/31/2031

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Computational Approaches to Reconstruct the Evolutionary History of Cancer Metastases - PROJECT SUMMARY Metastasis is the leading cause of cancer-related death. Cancer development, progression and metastasis happens through an evolutionary process, selecting for tumor clones with higher growth potential, resistance to treatment and immune pressures, and increased fitness to thrive in a new environment. While the early stages of tumor evolution leading to the development of primary tumors are quite well understood, the genetic makeup and evolutionary dynamics of cancer metastases remain less explored. Deeper study of the evolution of metastatic cancer holds immense promise, potentially paving the way for interventions that could prevent as much as 90% of cancer-related deaths. The PI on this proposal, Dr. Peter Van Loo, is an expert in leveraging DNA sequencing to infer cancer’s evolutionary history. These approaches, collectively coined Molecular Archeology of Cancer, have led to important biological insight into how tumors evolve in multiple cancer types. Across cancers, they showed that intra-tumor heterogeneity is pervasive and that primary tumors evolve over many years to decades and follow somewhat ordered paths. The genomes of cancer metastases typically show higher frequencies of aneuploidy and whole-genome duplication than those of primary tumors. This both necessitates the development of molecular archeology of cancer approaches bespoke to the analysis of cancer metastases, and provides opportunities for more detailed inference. The Van Loo lab recently developed a novel chromosomal gain timing approach, GRITIC, specifically designed to time complex copy number gains in cancer metastases. Further development of these molecular archeology of cancer metastasis methods will lead to key opportunities to advance understanding of these deadly diseases. Here, we will develop novel molecular archeology of cancer approaches to elucidate the evolutionary history of cancer metastases and demonstrate their effectiveness through application to small-cell lung cancer, one of the deadliest cancer types, often diagnosed at the metastatic stage. We will achieve this in three aims: Aim 1: Develop novel clonal evolutionary timing approaches to time genomic events in metastatic cancer evolution. Aim 2: Develop novel approaches to elucidate trajectories of mutational process activity over clonal evolutionary time with fine resolution. Aim 3: Elucidate the evolutionary history of metastatic small cell lung cancer through ctDNA profiling and research autopsy.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $688,073 )
2026	2026	THE UNIVERISTY OF TEXAS M.D. ANDERSON CANCER CENTER	1515 HOLCOMBE BLVD	HOUSTON	TX	77030	HARRIS	USA	Cancer Biology Research	000	1	5/5/2026	NEW	$688,073
														Subtotal = $688,073

Grand Total All Awards = $688,073

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Computational Approaches to Reconstruct the Evolutionary History of Cancer Metastases

Award Number: R01CA299449

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 06/01/2026

PERIOD OF PERFORMANCE END DATE: 05/31/2031

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