A susceptibility gene signature for ERBB2-driven mammary tumor development and metastasis in Collaborative Cross mice with human translational value
Hui YangiD, Xinzhi WangiD, Adrián Blanco‐GómeziD, He LiiD, Natalia García‐SanchaiD, Roberto Corchado‐CobosiD, Manuel Jesús Pérez‐BaenaiD, Alejandro Jiménez‐NavasiD, Pin WangiD, Jamie L. InmaniD, Antoine M. SnijdersiD, David W. ThreadgilliD, Allan BalmainiD, Hang ChangiD, Jesús Pérez‐LosadaiD, Jian‐Hua MaoiD
Abstract
BackgroundDeeper 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-Erbb2 and 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 validated in vivo using genetically diverse MMTV-Erbb2 mice. 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 an in vivo MMTV-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.
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