Tracing cancer evolution and heterogeneity using Hi-C

Dan Daniel Erdmann-Pham, Sanjit Singh Batra, Timothy K. Turkalo, James Durbin, Marco Blanchette, Iwei Yeh, Hunter Shain, Boris C. Bastian, Yun S. Song (), Daniel S. Rokhsar () and Dirk Hockemeyer ()
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Dan Daniel Erdmann-Pham: University of California
Sanjit Singh Batra: University of California
Timothy K. Turkalo: University of California
James Durbin: Dovetail Genomics, Enterprise Way
Marco Blanchette: Dovetail Genomics, Enterprise Way
Iwei Yeh: University of California, San Francisco
Hunter Shain: University of California, San Francisco
Boris C. Bastian: University of California, San Francisco
Yun S. Song: University of California
Daniel S. Rokhsar: University of California
Dirk Hockemeyer: University of California

Nature Communications, 2023, vol. 14, issue 1, 1-17

Abstract: Abstract Chromosomal rearrangements can initiate and drive cancer progression, yet it has been challenging to evaluate their impact, especially in genetically heterogeneous solid cancers. To address this problem we developed HiDENSEC, a new computational framework for analyzing chromatin conformation capture in heterogeneous samples that can infer somatic copy number alterations, characterize large-scale chromosomal rearrangements, and estimate cancer cell fractions. After validating HiDENSEC with in silico and in vitro controls, we used it to characterize chromosome-scale evolution during melanoma progression in formalin-fixed tumor samples from three patients. The resulting comprehensive annotation of the genomic events includes copy number neutral translocations that disrupt tumor suppressor genes such as NF1, whole chromosome arm exchanges that result in loss of CDKN2A, and whole-arm copy-number neutral loss of homozygosity involving PTEN. These findings show that large-scale chromosomal rearrangements occur throughout cancer evolution and that characterizing these events yields insights into drivers of melanoma progression.

Date: 2023
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DOI: 10.1038/s41467-023-42651-2

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