Dataset Information

Mutational mechanisms of amplifications revealed by analysis of clustered rearrangements in breast cancers.

ABSTRACT:

Background

Complex clusters of rearrangements are a challenge in interpretation of cancer genomes. Some clusters of rearrangements demarcate clear amplifications of driver oncogenes but others are less well understood. A detailed analysis of rearrangements within these complex clusters could reveal new insights into selection and underlying mutational mechanisms.

Patients and methods

Here, we systematically investigate rearrangements that are densely clustered in individual tumours in a cohort of 560 breast cancers. Applying an agnostic approach, we identify 21 hotspots where clustered rearrangements recur across cancers.

Results

Some hotspots coincide with known oncogene loci including CCND1, ERBB2, ZNF217, chr8:ZNF703/FGFR1, IGF1R, and MYC. Others contain cancer genes not typically associated with breast cancer: MCL1, PTP4A1, and MYB. Intriguingly, we identify clustered rearrangements that physically connect distant hotspots. In particular, we observe simultaneous amplification of chr8:ZNF703/FGFR1 and chr11:CCND1 where deep analysis reveals that a chr8-chr11 translocation is likely to be an early, critical, initiating event.

Conclusions

We present an overview of complex rearrangements in breast cancer, highlighting a potential new way for detecting drivers and revealing novel mechanistic insights into the formation of two common amplicons.

SUBMITTER: Glodzik D

PROVIDER: S-EPMC6290883 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Publications

Mutational mechanisms of amplifications revealed by analysis of clustered rearrangements in breast cancers.

Głodzik D D Purdie C C Rye I H IH Simpson P T PT Staaf J J Span P N PN Russnes H G HG Nik-Zainal S S

Annals of oncology : official journal of the European Society for Medical Oncology 20181101 11

<h4>Background</h4>Complex clusters of rearrangements are a challenge in interpretation of cancer genomes. Some clusters of rearrangements demarcate clear amplifications of driver oncogenes but others are less well understood. A detailed analysis of rearrangements within these complex clusters could reveal new insights into selection and underlying mutational mechanisms.<h4>Patients and methods</h4>Here, we systematically investigate rearrangements that are densely clustered in individual tumour ...[more]

PMID: 30252041

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Project description:BackgroundMajor advances have been achieved in the characterization of early breast cancer (eBC) genomic profiles. Metastatic breast cancer (mBC) is associated with poor outcomes, yet limited information is available on the genomic profile of this disease. This study aims to decipher mutational profiles of mBC using next-generation sequencing.Methods and findingsWhole-exome sequencing was performed on 216 tumor-blood pairs from mBC patients who underwent a biopsy in the context of the SAFIR01, SAFIR02, SHIVA, or Molecular Screening for Cancer Treatment Optimization (MOSCATO) prospective trials. Mutational profiles from 772 primary breast tumors from The Cancer Genome Atlas (TCGA) were used as a reference for comparing primary and mBC mutational profiles. Twelve genes (TP53, PIK3CA, GATA3, ESR1, MAP3K1, CDH1, AKT1, MAP2K4, RB1, PTEN, CBFB, and CDKN2A) were identified as significantly mutated in mBC (false discovery rate [FDR] < 0.1). Eight genes (ESR1, FSIP2, FRAS1, OSBPL3, EDC4, PALB2, IGFN1, and AGRN) were more frequently mutated in mBC as compared to eBC (FDR < 0.01). ESR1 was identified both as a driver and as a metastatic gene (n = 22, odds ratio = 29, 95% CI [9-155], p = 1.2e-12) and also presented with focal amplification (n = 9) for a total of 31 mBCs with either ESR1 mutation or amplification, including 27 hormone receptor positive (HR+) and HER2 negative (HER2-) mBCs (19%). HR+/HER2- mBC presented a high prevalence of mutations on genes located on the mechanistic target of rapamycin (mTOR) pathway (TSC1 and TSC2) as compared to HR+/HER2- eBC (respectively 6% and 0.7%, p = 0.0004). Other actionable genes were more frequently mutated in HR+ mBC, including ERBB4 (n = 8), NOTCH3 (n = 7), and ALK (n = 7). Analysis of mutational signatures revealed a significant increase in APOBEC-mediated mutagenesis in HR+/HER2- metastatic tumors as compared to primary TCGA samples (p < 2e-16). The main limitations of this study include the absence of bone metastases and the size of the cohort, which might not have allowed the identification of rare mutations and their effect on survival.ConclusionsThis work reports the results of the analysis of the first large-scale study on mutation profiles of mBC. This study revealed genomic alterations and mutational signatures involved in the resistance to therapies, including actionable mutations.

Dataset Information

Mutational mechanisms of amplifications revealed by analysis of clustered rearrangements in breast cancers.

Background

Patients and methods

Results

Conclusions

Publications

Mutational mechanisms of amplifications revealed by analysis of clustered rearrangements in breast cancers.

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