A susceptibility gene signature for ERBB2-driven mammary tumor development and metastasis in Collaborative Cross mice with human translational value

Author:

Yang Hui,Wang Xinzhi,Blanco-Gómez Adrián,He Li,García-Sancha Natalia,Corchado-Cobos Roberto,Pérez-Baena Manuel Jesús,Jiménez-Navas Alejandro,Wang Pin,Inman Jamie L,Snijders Antoine M,Threadgill David W,Balmain AllanORCID,Chang Hang,Perez-Losada Jesus,Mao Jian-HuaORCID

Abstract

AbstractBackgroundDeeper insights into ERBB2-driven cancers are essential to develop novel treatment avenues for ERBB2+ breast cancers (BCs). We employed Collaborative Cross (CC) mouse model, along with human translational evaluation, to unearth genetic factors underpinning Erbb2-driven mammary tumor development and metastasis.Methods732 F1 hybrid female mice between FVB/N MMTV-Erbb2and 30 CC strains were monitored for mammary tumor phenotypes. GWAS pinpointed SNPs that influence various tumor phenotypes. Clinical value of a mouse tumor susceptibility gene signature (mTSGS) was evaluated using public datasets, encompassing TCGA, METABRIC and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validatedin vivousing genetically diverse MMTV-Erbb2mice.ResultsDistinct variances in tumor onset, multiplicity, and metastatic patterns were observed across CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified 1525 SNPs, 800 SNPs, 568 SNPs, and 23 SNPs significantly associated with tumor onset, multiplicity, lung metastasis, and liver metastasis, respectively. Multivariate analyses flagged SNPs in 20 genes independently tied to various tumor characteristics, designated as mTSGS. These 20 genes were transcriptionally altered in human BCs. We then established mTSGS scores (mTSGSS) based on their transcriptional levels. The mTSGSS showed prognostic values, superseding clinical factors and PAM50 molecular subtype across cohorts. Moreover, mTSGSS predicted pathological complete response (pCR) to six of thirteen treatment regimens, including chemotherapy only, in I-SPY2 study. Importantly, the predictive value of the mTSGSS for pCR stood independent of the MammaPrint score. The power of mTSGSS for predicting chemotherapy response was validated in anin vivoMMTV-Erbb2 model, showing that like findings in human patients, mouse tumors with low mTSGSS were most likely to respond to treatment.ConclusionOur investigation has unveiled many novel genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that mTSGSS holds promise as a biomarker to refine treatment strategies for BC patients.

Publisher

Cold Spring Harbor Laboratory

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