Recurrent ESR1CCDC170 rearrangements in an aggressive subset of oestrogen receptor-positive breast cancers

Abstract

Characterizing the genetic alterations leading to the more aggressive forms of oestrogen receptor-positive (ER+) breast cancers is of critical significance in breast cancer management. Here we identify recurrent rearrangements between the oestrogen receptor gene ESR1 and its neighbour CCDC170, which are enriched in the more aggressive and endocrine-resistant luminal B tumours, through large-scale analyses of breast cancer transcriptome and copy number alterations. Further screening of 200 ER+ breast cancers identifies eight ESR1CCDC170-positive tumours. These fusions encode amino-terminally truncated CCDC170 proteins (ΔCCDC170). When introduced into ER+ breast cancer cells, ΔCCDC170 leads to markedly increased cell motility and anchorage-independent growth, reduced endocrine sensitivity and enhanced xenograft tumour formation. Mechanistic studies suggest that ΔCCDC170 engages Gab1 signalosome to potentiate growth factor signalling and enhance cell motility. Together, this study identifies neoplastic ESR1CCDC170 fusions in a more aggressive subset of ER+ breast cancer, which suggests a new concept of ER pathobiology in breast cancer.

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Figure 1: Discovering recurrent gene fusions in invasive breast cancer.
Figure 2: Characterization of the ESR1CCDC170 fusion in breast cancer cell lines and tissues.
Figure 3: Characterization of ESR1–CCDC170 protein products and their transforming activity in MCF10A breast epithelial cells.
Figure 4: ESR1CCDC170 endows more aggressive phenotypes in T47D ER+ breast cancer cells.
Figure 5: Evaluating the function of the endogenous ESR1CCDC170 fusion in HCC1428 breast cancer cells by genetic inhibition.
Figure 6: ESR1CCDC170 may engage Gab1 to enhance cell motility and augment growth factor signalling.

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Acknowledgements

The results published here are in part based on data generated by TCGA (dbGaP accession: phs000178.v6.p6). We thank Dr Joe W. Gray for providing the genomic data for breast cancer cell lines. We thank Zhongqiu Guo and Sufeng Mao for help with Ki67 IHC assays, Sabrina Herrera for help with pathology analysis, and the Antibody-based Proteomics Core of the Dan L. Duncan Cancer Center (DLDCC) at BCM (supported by NCI P30-125123) for help with cell line extracts. The computational infrastructure was supported by the DLDCC Biostatistics and Informatics Shared Resource and the Rice University BlueBioU Computer Cluster (supported by a 2010 IBM Award and NIH grant NCRR S10RR02950). This study was supported by CDMRP grants W81XWH-12-1-0166 (X.-S.W.), W81XWH-12-1-0167 (R.S.), W81XWH-13-1-0201 (X.-X.C) and W81XWH-13-1-0431 (J.V.), Nancy Owens Memorial foundation (X.-S.W.), Susan G. Komen Foundation PDF12231561 (J.A.K.), and PG12221410 (X.-S.W., R.S., S.G.H.). NIH grant CA183976 (X.-S.W.), P30-125123-06 (S.G.H.), and CPRIT grant RP130135 (E.C.C.). All breast tumour tissues were provided by the Tumor Bank of the BCM Breast Center.

Author information

X.-S.W. conceived and supervised the study, performed bioinformatics analysis, analysed the data and wrote the manuscript. J.V. designed and performed cell biology, mechanistic and in vivo experiments, analysed the data and co-wrote the manuscript. Y.T. designed and performed molecular biology experiments, analysed the data and co-wrote the manuscript. X.-X.C. performed cell biology experiments and pathology studies. J.A.K. helped develop stable overexpression cell lines. X.W. assisted in the in vivo studies. S.N.M. and L.J.N.C. helped perform Nanostring assay. D.P.E. provided breast cancer cell lines and RNA extracts. A.C. helped with pathology studies. S.G.H performed the statistical analysis. G.C.C. edited the manuscript. R.S. and E.C.C. advised on the study and revised the manuscript.

Correspondence to Xiao-Song Wang.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Figures and Tables

Supplementary Figures 1-12 and Supplementary Tables 1-3 (PDF 1052 kb)

Supplementary Data 1

380 recurrent fusion candidates associated with recurring somatic unbalanced breakpoints computed based on copy number data. Note: , 5' and 3' genes locate at the same strand with 5' gene placed upstream of 3' gene; 5' and 3' genes locate at the same strand but 3' gene is placed upstream of 5' gene; <> 5' and 3' genes are in different strand. AdjN, paired adjacent normal breast tissues. The number of tumor or blood samples harboring meaningful copy number breakpoints in 5' or 3' partner genes are shown in the last column. 5'break, 5'partner gene has copy number breakpoint resulting in 5' amplification or 3' deletion of the gene. 3'break, 3'partner gene has copy number breakpoint resulting in 5' deletion or 3' amplification of the gene. Note, there is slight difference in the incidence of ESR1-CCDC170 and associated copy number breakpoints computed by the Fusion Zoom pipeline and that of final results curated based on newer release of TCGA data. Also not all ESR1/CCDC170 breakpoint positive cases are identified as ESR1-CCDC170 positive by RNAseq data analysis. (XLS 129 kb)

Supplementary Data 2

Reconstructed putative fusion-variant sequences by randomly combining each of ESR1 exons with each of the CCDC170 exons. (TXT 4017 kb)

Supplementary Data 3

The sequences of ESR1-CCDC170 chimerical mate-pair reads detected from TCGA breast tumors and the manual curation results. (XLS 143 kb)

Supplementary Data 4

ESR1-CCDC170 genomic fusion sequences of fusion-positive breast cancer cell lines and tumors identified by genomic PCR and capillary sequencing. (TXT 5 kb)

Supplementary Data 5

The predicted open-reading frame sequences of ESR1-CCDC170 fusion variant E2-E6, E2-E7, E2-E8, and E2-E10. (TXT 3 kb)

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Veeraraghavan, J., Tan, Y., Cao, X. et al. Recurrent ESR1CCDC170 rearrangements in an aggressive subset of oestrogen receptor-positive breast cancers. Nat Commun 5, 4577 (2014). https://doi.org/10.1038/ncomms5577

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