Abstract Introduction Epidermal growth factor receptor 2 (HER2)-targeted therapies are effective treatments for HER2+ breast cancers (BC), but intrinsic and acquired resistance hampers their clinical benefit. Therefore, new biological insights into HER2-driven cancers are needed to conquer drug resistance. Here, we used a genetically diverse and population-based Collaborative Cross (CC) mouse model to identify genetic susceptibility to tumor development and metastasis driven by HER2. Materials and methods 732 F1 hybrid mice were generated from a cross between FVB/N MMTV-ErbB2 and 30 CC strains and were monitored for mammary tumor development within two years. Tumor onset, multiplicity and metastasis were assessed. Genome wide association study (GWAS) was used to identify genetic variations controlling different tumor phenotypes. Polygenetic risk score was created for each phenotype using multivariate analysis. We systematically evaluated the clinical value regarding prognosis and therapeutic responses of mouse tumor susceptibility gene signature (mTSGS) in human breast cancer (BC) using publicly available cohorts including I-SPY2 clinical trial cohorts. Results We observed huge differences in tumor onset, multiplicities, and metastasis across 30 CC strains. In addition to lung metastasis, we found liver/kidney metastasis in some CC strains. GWAS identified 1,525 SNPs significantly associated with tumor onset (p<1.00E-30) corresponding to 287 known genes, 800 SNPs significantly associated with number of tumors (p<1.00E-15) corresponding to 203 known genes, 568 SNPs significantly associated with lung metastasis (p<1.00E-4) corresponding to 189 known genes, and 23 SNPs significantly associated with liver metastasis (p<1.00E-4) corresponding to 12 known genes. Multivariate analyses identified the SNPs in 8 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b and Rer1) independently associated with age onset, in 11 genes (Stx6, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a and Oxr1) independently associated with number of tumors, and in 2 genes (Plxna2 and Tbc1d31) independently associated with tumor metastasis, which were pooled together as mTSGS. To evaluate the impact of mTSGS on human BC, we established mTSGS score (mTSGSS) based on their transcriptional levels in BC. We found that mTSGSS is significantly and independently associated with overall, disease free and progression free survival compared to clinical factors and PAM50 molecular subtype in different cohorts. Additionally, patients with low mTSGSS have a higher pathological complete response (pCR) rate in comparison to these with high mTSGSS for 6 of 13 treatment regimens in I-SPY2 cohort. Multivariate logistic regression analysis showed that predictive value of mTSGSS in pCR is independent of MammaPrint (MP) score in these treatment regimens. Conclusion Our findings lead significantly to biological insights into ErbB2-driven cancers and indicate that mTSGSS can serve as a biomarker for tailoring treatment to BC patients. Citation Format: Hang Chang, Jamie L Inman, Antoine M Snijders, Jian-Hua Mao. Identification of genetic susceptibility loci for ErbB2-driven mammary tumor development and metastasis using Collaborative Cross mice and human relevant validation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A004.
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