Intra-tumor genetic heterogeneity and alternative driver genetic alterations in breast cancers with heterogeneous HER2 gene amplification

Background HER2 is overexpressed and amplified in approximately 15% of invasive breast cancers, and is the molecular target and predictive marker of response to anti-HER2 agents. In a subset of these cases, heterogeneous distribution of HER2 gene amplification can be found, which creates clinically challenging scenarios. Currently, breast cancers with HER2 amplification/overexpression in just over 10% of cancer cells are considered HER2-positive for clinical purposes; however, it is unclear as to whether the HER2-negative components of such tumors would be driven by distinct genetic alterations. Here we sought to characterize the pathologic and genetic features of the HER2-positive and HER2-negative components of breast cancers with heterogeneous HER2 gene amplification and to define the repertoire of potential driver genetic alterations in the HER2-negative components of these cases.Results We separately analyzed the HER2-negative and HER2-positive components of 12 HER2 heterogeneous breast cancers using gene copy number profiling and massively parallel sequencing, and identified potential driver genetic alterations restricted to the HER2-negative cells in each case. In vitro experiments provided functional evidence to suggest that BRF2 and DSN1 overexpression/amplification, and the HER2 I767M mutation may be alterations that compensate for the lack of HER2 amplification in the HER2-negative components of HER2 heterogeneous breast cancers.Conclusions Our results indicate that even driver genetic alterations, such as HER2 gene amplification, can be heterogeneously distributed within a cancer, and that the HER2-negative components are likely driven by genetic alterations not present in the HER2-positive components, including BRF2 and DSN1 amplification and HER2 somatic mutations

The Landscape of Somatic Genetic Alterations in Metaplastic Breast Carcinomas

Purpose:; Metaplastic breast carcinoma (MBC) is a rare and aggressive histologic type of breast cancer, predominantly of triple-negative phenotype, and characterized by the presence of malignant cells showing squamous and/or mesenchymal differentiation. We sought to define the repertoire of somatic genetic alterations and the mutational signatures of MBCs.; Experimental Design:; Whole-exome sequencing was performed in 35 MBCs, with 16, 10, and 9 classified as harboring chondroid, spindle, and squamous metaplasia as the predominant metaplastic component. The genomic landscape of MBCs was compared with that of triple-negative invasive ductal carcinomas of no special type (IDC-NST) from The Cancer Genome Atlas. Wnt and PI3K/AKT/mTOR pathway activity was assessed using a qPCR assay.; Results:; MBCs harbored complex genomes with frequent; TP53; (69%) mutations. In contrast to triple-negative IDC-NSTs, MBCs more frequently harbored mutations in; PIK3CA; (29%),; PIK3R1; (11%),; ARID1A; (11%),; FAT1; (11%), and; PTEN; (11%).; PIK3CA; mutations were not found in MBCs with chondroid metaplasia. Compared with triple-negative IDC-NSTs, MBCs significantly more frequently harbored mutations in PI3K/AKT/mTOR pathway-related (57% vs. 22%) and canonical Wnt pathway-related (51% vs. 28%) genes. MBCs with somatic mutations in PI3K/AKT/mTOR or Wnt pathway-related genes displayed increased activity of the respective pathway.; Conclusions:; MBCs are genetically complex and heterogeneous, and are driven by a repertoire of somatic mutations distinct from that of triple-negative IDC-NSTs. Our study highlights the genetic basis and the importance of PI3K/AKT/mTOR and Wnt pathway dysregulation in MBCs and provides a rationale for the metaplastic phenotype and the reported responses to PI3K/AKT/mTOR inhibitors in these tumors

Genomic and transcriptomic heterogeneity in metaplastic carcinomas of the breast

Metaplastic breast cancer (MBC) is a rare special histologic type of triple-negative breast cancer, characterized by the presence of neoplastic cells showing differentiation towards squamous epithelium and/or mesenchymal elements. Here we sought to define whether histologically distinct subgroups of MBCs would be underpinned by distinct genomic and/or transcriptomic alterations. Microarray-based copy number profiling identified limited but significant differences between the distinct MBC subtypes studied here, despite the limited sample size (; n; = 17). In particular, we found that, compared to MBCs with chondroid or squamous cell metaplasia, MBCs with spindle cell differentiation less frequently harbored gain of 7q11.22-23 encompassing; CLDN3; and; CLDN4; , consistent with their lower expression of claudins and their association with the claudin-low molecular classification. Microarray-based and RNA-sequencing-based gene expression profiling revealed that MBCs with spindle cell differentiation differ from MBCs with chondroid or squamous cell metaplasia on the expression of epithelial-to-mesenchymal transition-related genes, including down-regulation of; CDH1; and; EPCAM; . In addition, RNA-sequencing revealed that the histologic patterns observed in MBCs are unlikely to be underpinned by a highly recurrent expressed fusion gene or a pathognomonic expressed mutation in cancer genes. Loss of PTEN expression or mutations affecting; PIK3CA; or; TSC2; observed in 8/17 MBCs support the contention that PI3K pathway activation plays a role in the development of MBCs. Our data demonstrate that despite harboring largely similar patterns of gene copy number alterations, MBCs with spindle cell, chondroid and squamous differentiation are distinct at the transcriptomic level but are unlikely to be defined by specific pathognomonic genetic alterations

Robust BRCA1-like classification of copy number profiles of samples repeated across different datasets and platforms.

Breast cancers with BRCA1 germline mutation have a characteristic DNA copy number (CN) pattern. We developed a test that assigns CN profiles to be 'BRCA1-like' or 'non-BRCA1-like', which refers to resembling a BRCA1-mutated tumor or resembling a tumor without a BRCA1 mutation, respectively. Approximately one third of the BRCA1-like breast cancers have a BRCA1 mutation, one third has hypermethylation of the BRCA1 promoter and one third has an unknown reason for being BRCA1-like. This classification is indicative of patients' response to high dose alkylating and platinum containing chemotherapy regimens, which targets the inability of BRCA1 deficient cells to repair DNA double strand breaks. We investigated whether this classification can be reliably obtained with next generation sequencing and copy number platforms other than the bacterial artificial chromosome (BAC) array Comparative Genomic Hybridization (aCGH) on which it was originally developed. We investigated samples from 230 breast cancer patients for which a CN profile had been generated on two to five platforms, comprising low coverage CN sequencing, CN extraction from targeted sequencing panels (CopywriteR), Affymetrix SNP6.0, 135K/720K oligonucleotide aCGH, Affymetrix Oncoscan FFPE (MIP) technology, 3K BAC and 32K BAC aCGH. Pairwise comparison of genomic position-mapped profiles from the original aCGH platform and other platforms revealed concordance. For most cases, biological differences between samples exceeded the differences between platforms within one sample. We observed the same classification across different platforms in over 80% of the patients and kappa values of at least 0.36. Differential classification could be attributed to CN profiles that were not strongly associated to one class. In conclusion, we have shown that the genomic regions that define our BRCA1-like classifier are robustly measured by different CN profiling technologies, providing the possibility to retro- and prospectively investigate BRCA1-like classification across a wide range of CN platforms

Integrated Functional, Gene Expression and Genomic Analysis for the Identification of Cancer Targets

The majority of new drug approvals for cancer are based on existing therapeutic targets. One approach to the identification of novel targets is to perform high-throughput RNA interference (RNAi) cellular viability screens. We describe a novel approach combining RNAi screening in multiple cell lines with gene expression and genomic profiling to identify novel cancer targets. We performed parallel RNAi screens in multiple cancer cell lines to identify genes that are essential for viability in some cell lines but not others, suggesting that these genes constitute key drivers of cellular survival in specific cancer cells. This approach was verified by the identification of PIK3CA, silencing of which was selectively lethal to the MCF7 cell line, which harbours an activating oncogenic PIK3CA mutation. We combined our functional RNAi approach with gene expression and genomic analysis, allowing the identification of several novel kinases, including WEE1, that are essential for viability only in cell lines that have an elevated level of expression of this kinase. Furthermore, we identified a subset of breast tumours that highly express WEE1 suggesting that WEE1 could be a novel therapeutic target in breast cancer. In conclusion, this strategy represents a novel and effective strategy for the identification of functionally important therapeutic targets in cancer

Comparative proteomic assessment of matrisome enrichment methodologies

The matrisome is a complex and heterogeneous collection of extracellular matrix (ECM) and ECM-associated proteins that play important roles in tissue development and homeostasis. While several strategies for matrisome enrichment have been developed, it is currently unknown how the performance of these different methodologies compares in the proteomic identification of matrisome components across multiple tissue types. In the present study, we perform a comparative proteomic assessment of two widely used decellularisation protocols and two extraction methods to characterise the matrisome in four murine organs (heart, mammary gland, lung and liver). We undertook a systematic evaluation of the performance of the individual methods on protein yield, matrisome enrichment capability and the ability to isolate core matrisome and matrisome-associated components. Our data find that sodium dodecyl sulphate (SDS) decellularisation leads to the highest matrisome enrichment efficiency, while the extraction protocol that comprises chemical and trypsin digestion of the ECM fraction consistently identifies the highest number of matrisomal proteins across all types of tissue examined. Matrisome enrichment had a clear benefit over non-enriched tissue for the comprehensive identification of matrisomal components in murine liver and heart. Strikingly, we find that all four matrisome enrichment methods led to significant losses in the soluble matrisome-associated proteins across all organs. Our findings highlight the multiple factors (including tissue type, matrisome class of interest and desired enrichment purity) that influence the choice of enrichment methodology, and we anticipate that these data will serve as a useful guide for the design of future proteomic studies of the matrisome