Cherniack, A. | Search bioRxiv

bioRxiv2024

Clinicogenomic characterization of inflammatory breast cancer

BackgroundInflammatory breast cancer (IBC) is a rare and poorly characterized type of breast cancer with an aggressive clinical presentation. The biological mechanisms driving the IBC phenotype are relatively undefined--partially due to a lack of comprehensive, large-scale genomic studies and limited clinical cohorts. Patients and MethodsA retrospective analysis of 2457 patients with metastatic breast cancer who underwent targeted tumor-only DNA-sequencing was performed at Dana-Farber Cancer Institute. Clinicopathologic, single nucleotide variant (SNV), copy number variant (CNV) and tumor mutational burden (TMB) comparisons were made between clinically confirmed IBC cases within a dedicated IBC center versus non-IBC cases. ResultsClinicopathologic differences between IBC and non-IBC cases were consistent with prior reports--including IBC being associated with younger age at diagnosis, higher grade, and enrichment with hormone receptor (HR)-negative and HER2-positive tumors. The most frequent somatic alterations in IBC involved TP53 (72%), ERBB2 (32%), PIK3CA (24%), CCND1 (12%), MYC (9%), FGFR1 (8%) and GATA3 (8%). A multivariate logistic regression analysis revealed a significant enrichment in TP53 SNVs in IBC; particularly in HER2-positive and HR-positive disease which was associated with worse outcomes. Tumor mutational burden (TMB) did not differ substantially between IBC and non-IBC cases and a pathway analysis revealed an enrichment in NOTCH pathway alterations in HER2-positive disease. ConclusionTaken together, this study provides a comprehensive, clinically informed landscape of somatic alterations in a large cohort of patients with IBC. Our data support higher frequency of TP53 mutations and a potential enrichment in NOTCH pathway activation--but overall; a lack of major genomic differences. These results both reinforce the importance of TP53 alterations in IBC pathogenesis as well as their influence on clinical outcomes; but also suggest additional analyses beyond somatic DNA-level changes are warranted.

genomics↗

bioRxiv2023

Detecting significantly recurrent genomic connections from simple and complex rearrangements in the cancer genome

The detection of somatic genetic alterations that recur across cancer genomes more than expected by chance has been a major goal of cancer genomics, as these alterations are enriched for "driver" events that promote cancer. Multiple methods have been developed to detect driver point mutations and copy-number variants, but methods to detect driver rearrangements have largely not been pursued. Unlike point mutations and copy-number alterations, which can be assigned to a single genomic locus, rearrangements connect two distant genomic loci, and possibly more in the case of complex or clustered events. Here, we explore genomic features that predict the rate at which any pair of loci will be connected by rearrangements and describe two methods to detect rearrangements that recur more often than this background rate. The first, SVSig-2D, detects pairs of loci that are directly connected by a single rearrangement; the second, SVSig-2Dc also detects loci that are recurrently connected indirectly through two or more rearrangements. When applied to a pan-cancer dataset of over 2,500 cancers, these methods identified 80 significantly recurrent simple rearrangements and 29 complex rearrangements, including both known and novel events. Intriguingly, though both recurrent simple and complex rearrangements tended to be tissue-specific, this was less true for the complex events. The detection of recurrent rearrangements with methods such as these will be an essential component of cancer genomics in the whole-genome sequencing era.

genomics↗