Robust somatic copy number estimation using coarse-to-fine segmentation

Abstract

Cancers routinely exhibit chromosomal instability, resulting in the accumulation of changes in the abundance of genomic material, known as copy number variants (CNVs). Unfortunately, the detection of these variants in cancer genomes is difficult. We developed Ploidetect, a software package that effectively identifies CNVs within whole-genome sequenced tumors. Ploidetect was more sensitive to CNVs in cancer related genes within advanced, pre-treated metastatic cancers than other tools, while also segmenting the most contiguously. Chromosomal instability, as measured by segment contiguity, was associated with several biological and clinical variables, including tumor mutation burden, tumor type, duration of therapy and immune microenvironment, highlighting the relevance of measuring CNV across the cancer genome. Investigation of gene mutations in samples revealed and the mutation status of several genes including ROCK2 and AC074391.1. Leveraging our heightened ability to detect CNVs, we identified 282 genes which were recurrently homozygously deleted in metastatic tumors. Further analysis of one recurrently deleted gene, MACROD2, identified a putative fragile tumor suppressor locus associated with response to chromosomal instability and chemotherapeutic agents. Our results outline the multifaceted impacts of CNVs in cancer by providing evidence of their involvement in tumorigenic behaviors and their utility as biomarkers for biological processes. We propose that increasingly accurate determination of CNVs is critical for their productive study in cancer, and our work demonstrates advances made possible by progress in this regard.

IMPALA: A Comprehensive Pipeline for Detecting and Elucidating Mechanisms of Allele Specific Expression in Cancer

“…IMPALA can incorporate CNV data estimated from aligned tumor and normal DNA samples using the Ploidetect (v. 1.4.1) software (Culibrk et al . 2021).…”

“…The IMPALA pipeline also uniquely accepts optional genomic files to elucidate the underlying mechanisms of ASE. These data types include copy number variant data (Culibrk et al . 2021), allelic methylation data (Akbari et al .…”

Genomic structures and regulation patterns at HPV integration sites in cervical cancer

“…The copy number profiles were obtained for TCGA-A5-A1BL and HTMCP-03-06-02054 and other translocation event-containing samples. The Ploidetect 56 (v. 3.0) pipeline was ran using the “short” sequence type for HTMCP samples and the “ont” sequence type for TCGA samples since high-coverage short-read WGS was unavailable (see https://github.com/lculibrk/Ploidetect-pipeline, section 1.1.4). The results were selected for the first predicted model that did not have a ploidy of 1.…”