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Deregulating MYC in a model of HER2+ breast cancer mimics human intertumoral heterogeneity.

ABSTRACT: The c-MYC (MYC) oncoprotein is often overexpressed in human breast cancer; however, its role in driving disease phenotypes is poorly understood. Here, we investigate the role of MYC in HER2+ disease, examining the relationship between HER2 expression and MYC phosphorylation in HER2+ patient tumors and characterizing the functional effects of deregulating MYC expression in the murine NeuNT model of amplified-HER2 breast cancer. Deregulated MYC alone was not tumorigenic, but coexpression with NeuNT resulted in increased MYC Ser62 phosphorylation and accelerated tumorigenesis. The resulting tumors were metastatic and associated with decreased survival compared with NeuNT alone. MYC;NeuNT tumors had increased intertumoral heterogeneity including a subtype of tumors not observed in NeuNT tumors, which showed distinct metaplastic histology and worse survival. The distinct subtypes of MYC;NeuNT tumors match existing subtypes of amplified-HER2, estrogen receptor-negative human tumors by molecular expression, identifying the preclinical utility of this murine model to interrogate subtype-specific differences in amplified-HER2 breast cancer. We show that these subtypes have differential sensitivity to clinical HER2/EGFR-targeted therapeutics, but small-molecule activators of PP2A, the phosphatase that regulates MYC Ser62 phosphorylation, circumvents these subtype-specific differences and ubiquitously suppresses tumor growth, demonstrating the therapeutic utility of this approach in targeting deregulated MYC breast cancers.

SUBMITTER: Risom T

PROVIDER: S-EPMC6934197 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Deregulating MYC in a model of HER2+ breast cancer mimics human intertumoral heterogeneity.

Risom Tyler T Wang Xiaoyan X Liang Juan J Zhang Xiaoli X Pelz Carl C Campbell Lydia G LG Eng Jenny J Chin Koei K Farrington Caroline C Narla Goutham G Langer Ellen M EM Sun Xiao-Xin XX Su Yulong Y Daniel Colin J CJ Dai Mu-Shui MS Löhr Christiane V CV Sears Rosalie C RC

The Journal of clinical investigation 20200101 1

The c-MYC (MYC) oncoprotein is often overexpressed in human breast cancer; however, its role in driving disease phenotypes is poorly understood. Here, we investigate the role of MYC in HER2+ disease, examining the relationship between HER2 expression and MYC phosphorylation in HER2+ patient tumors and characterizing the functional effects of deregulating MYC expression in the murine NeuNT model of amplified-HER2 breast cancer. Deregulated MYC alone was not tumorigenic, but coexpression with NeuN ...[more]

PMID: 31763993

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Project description:BackgroundBreast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.MethodsTumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman's rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan-Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.ResultsHerein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.ConclusionsWe conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

Project description:ObjectiveHER2 status in breast cancer is an essential parameter in individual therapeutic decision-making and is routinely assessed in primary tumors in accordance with international recommendations. Reports of HER2 heterogeneity raise the question of basing treatment decisions on HER2 status in metastases, if present. We investigated the degree and clinical implications of HER2 heterogeneity in lymph node-positive breast cancer. Because of recent recognition of therapeutic opportunities in this group of tumors, we especially focused on cases involving low-level HER2 expression.MethodsThe HER2 status of primary tumors and of corresponding lymph node metastases was determined in archived material at the protein and gene levels using the gene- protein assay and interpreted in accordance with 2018 ASCO/CAP criteria. HER2-low status was defined as protein expression levels 1+ or 2+ with negative amplification status.ResultsWe analyzed a series of 43 cases of primary infiltrating breast cancer, each with at least two axillary nodes harboring macrometastases (>2 mm), in total 206 such nodes. In 7% of cases, we detected intertumoral HER2 heterogeneity. Three of nine HER2-positive primary tumors were associated with HER2-negative metastases. No cases with HER2-negative primary tumors had HER2-positive metastases, but 55% (6/11) of HER2 0 primary tumors had HER2 1+ and/or 2+ metastases, and 19% (3/16) HER2 1+ cases had exclusively HER2 0 metastases. All metastases in HER2 2+ cases showed HER2-low protein expression levels. Internodal HER2 heterogeneity at low protein expression levels (presence of HER2 0, HER2 1+, and/or HER2 2+ metastatic deposits within the same axilla) was seen in 40% (17/43) of cases. We found no statistically significant association between HER2 heterogeneity and other tumor-related parameters. Survival data indicated worse outcomes in the HER2-low group compared with the rest of the cohort.ConclusionOur results indicate a substantial instability of HER2 protein expression, leading to considerable intertumoral and internodal HER2 heterogeneity in lymph node-positive breast carcinomas. This heterogeneity is particularly relevant in HER2-low tumors in which the corrective effects of HER2 gene copy number analysis definitionally is absent. Our findings suggest that determining HER2 status in metastatic lymph nodes may generate relevant information for therapeutic decision-making.

Dataset Information

Deregulating MYC in a model of HER2+ breast cancer mimics human intertumoral heterogeneity.

Publications

Deregulating MYC in a model of HER2+ breast cancer mimics human intertumoral heterogeneity.

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