Dataset Information

Unique evolutionary trajectories of breast cancers with distinct genomic and spatial heterogeneity.

ABSTRACT: Breast cancers exhibit intratumoral heterogeneity associated with disease progression and therapeutic resistance. To define the sources and the extent of heterogeneity, we performed an in-depth analysis of the genomic architecture of three chemoradiation-naïve breast cancers with well-defined clinical features including variable ER, PR, ERBB2 receptor expression and two distinct pathogenic BRCA2^mut genotypes. The latter included a germ line carrier and a patient with a somatic variant. In each case we combined DNA content-based flow cytometry with whole exome sequencing and genome wide copy number variant (CNV) analysis of distinct populations sorted from multiple (4-18) mapped biopsies within the tumors and involved lymph nodes. Interrogating flow-sorted tumor populations from each biopsy provided an objective method to distinguish fixed and variable genomic lesions in each tumor. Notably we show that tumors exploit CNVs to fix mutations and deletions in distinct populations throughout each tumor. The identification of fixed genomic lesions that are shared or unique within each tumor, has broad implications for the study of tumor heterogeneity including the presence of tumor markers and therapeutic targets, and of candidate neoepitopes in breast and other solid tumors that can advance more effective treatment and clinical management of patients with disease.

SUBMITTER: Phung TN

PROVIDER: S-EPMC8134446 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe breast cancer genome dynamically evolves during malignant progression and recurrence. We investigated the genomic profiles of primary early-stage breast cancers and matched relapses to elucidate the molecular underpinnings of the metastatic process, focusing on potentially actionable alterations in the recurrences.MethodsA mono-institutional cohort of 128 patients with breast cancers (n = 68 luminal B HER2, n = 6 luminal B HER2+, n = 1 HER2+ non-luminal, n = 56 triple negative) and at least one recurrence in a timeframe of 17 years was evaluated. Next-generation sequencing comprehensive genomic profiling was performed on 289 formalin-fixed paraffin-embedded (FFPE) samples, including primary tumors and matched relapses. Correlations of genomic aberrations with clinicopathologic factors and time to breast cancer relapse were analyzed.ResultsGenomic data were available for 188 of 289 FFPE samples that achieved the sequencing quality parameters (failure rate 34.9%), including 106 primary tumors and 82 relapses. All primary and relapse samples harbored at least one genomic alteration, with a median number of six alterations per sample (range 1-16). The most frequent somatic genomic alterations were mutations of TP53 (primary tumors = 49%, relapses = 49%) and PIK3CA (primary tumors = 33%, relapses = 30%). Distinctive genomic alterations of primary tumors were significantly associated with molecular subtypes. TP53, PIK3R1, and NF1 somatic alterations were more frequently detected in triple negative tumors (p value < 0.05); CCND1, FGF3, and FGFR1 copy number gains were recurrently identified in luminal cases (p value < 0.05). Moreover, TP53 mutations and MYC amplification were significantly and independently associated with a shorter time to relapse (p value < 0.05). Molecular subtype changes between primary tumors and relapses were seen in 10 of 128 (7.8%) cases. Most driver genomic alterations (55.8%) were shared between primary tumors and matched recurrences. However, in 39 of 61 cases (63.9%), additional private alterations were detected in the relapse samples only, including 12 patients with potentially actionable aberrations.ConclusionsSpecific genomic aberrations of primary breast cancers were associated with time to relapse. Primary tumors and matched recurrences showed a core of shared driver genomic aberrations but private actionable alterations have been identified in the relapses.

Dataset Information

Unique evolutionary trajectories of breast cancers with distinct genomic and spatial heterogeneity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets