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BACKGROUND: Deeper insights into ERBB2-driven cancers are essential to develop new treatment approaches for ERBB2+ breast cancers (BCs). We employed the Collaborative Cross (CC) mouse model to unearth genetic factors underpinning Erbb2-driven mammary tumour development and metastasis. METHODS: 732 F1 hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains were monitored for mammary tumour phenotypes. GWAS pinpointed SNPs that influence various tumour phenotypes. Multivariate analyses and models were used to construct the polygenic score and to develop a mouse tumour susceptibility gene signature (mTSGS), where the corresponding human ortholog was identified and designated as hTSGS. The importance and clinical value of hTSGS in human BC was evaluated using public datasets, encompassing TCGA, METABRIC, GSE96058, and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validated in vivo using genetically diverse MMTV-Erbb2 mice. FINDINGS: Distinct variances in tumour onset, multiplicity, and metastatic patterns were observed in F1-hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified specific SNPs significantly associated with tumour onset, multiplicity, lung metastasis, and liver metastasis. Multivariate analyses flagged SNPs in 20 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b, Rer1, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a, Oxr1, Plxna2, and Tbc1d31) independently tied to various tumour characteristics, designated as a mTSGS. hTSGS scores (hTSGSS) based on their transcriptional level showed prognostic values, superseding clinical factors and PAM50 subtype across multiple human BC cohorts, and predicted pathological complete response independent of and superior to MammaPrint score in I-SPY2 study. The power of mTSGS score for predicting chemotherapy response was further validated in an in vivo mouse MMTV-Erbb2 model, showing that, like findings in human patients, mouse tumours with low mTSGS scores were most likely to respond to treatment. INTERPRETATION: Our investigation has unveiled many new genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that hTSGS holds promise as a biomarker for refining treatment strategies for patients with BC. FUNDING: The U.S. Department of Defense (DoD) Breast Cancer Research Program (BCRP) (BC190820), United States; MCIN/AEI/10.13039/501100011039 (PID2020-118527RB-I00, PDC2021-121735-I00), the European Union Next Generation EU/PRTR, the Regional Government of Castile and León (CSI144P20), European Union.

BACKGROUND: Luminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment. METHODS: We conducted a study to explore non-structural chromosome maintenance condensin I complex subunit Hs (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels. RESULTS: We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPHErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression. CONCLUSIONS: The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53 -null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care. [ABSTRACT FROM AUTHOR]

Background: Although the eighth edition of the American Joint Committee on Cancer staging system (AJCC8) provides improved prognosis stratification of cutaneous squamous cell carcinoma (CSCC) over AJCC7, T3 has a variable prognosis.Objective: To define prognostic subgroups in T3-AJCC8 CSCC.Methods: Retrospective cohort study of 196 primary T3-AJCC8 CSCCs. We conducted multidimensional scaling analysis using the 6 risk factors that define T3 CSCCs. The prognoses of the groups obtained were analyzed by means of competing risk analysis.Results: Group 1 was characterized by a tumor thickness greater than 6 mm (without invasion beyond the subcutaneous fat), alone or in combination with a tumor width of at least 4 cm. Group 2 was characterized by the presence of either invasion beyond the subcutaneous fat or by the involvement of nerves (≥0.1 mm, or deeper than the dermis). Group 3 was characterized by the combination of both T3b risk factors, or of 3 or more risk factors. Group 3 (tentatively named T3c) patients had the worst prognosis for disease-specific poor outcome events and major events, Group 2 (T3b) had intermediate risk, and Group 1 (T3a) had the best prognosis (disease-specific poor outcome events: hazard ratio [HR], 1.94; P = .00009; major events: HR, 2.55; P = .00001; disease-specific death: HR, 10.25; P = .0009).Limitations: Retrospective study.Conclusions: There is statistically significant evidence that T3-AJCC8 may be classified into distinct prognostic subgroups. [ABSTRACT FROM AUTHOR]

Introduction: The Brigham and Women's Hospital and the Tübingen cutaneous squamous cell carcinoma (SCC) stratification systems propose different criteria from the American Joint Committee on Cancer, eighth edition. Our group identified prognostic subgroups within T3 stage according to the American Joint Committee on Cancer eighth edition's classification, the most common classification for high-risk cutaneous SCCs.Objective: To compare the performance and prognostic accuracy of these staging systems in a subset of high-risk cutaneous SCCs.Methods: Homogeneity, monotonicity, and McNemar tests for pairwise comparisons were assessed. Distinctiveness and relative risk of poor outcome were calculated by stage. Prognostic accuracy was compared with respect to quality (Akaike and Bayesian information criteria), concordance (Harrell C-index and Gönen and Heller concordance probability estimate), and predictive accuracy (sensitivity, specificity, negative predictive value, positive predictive value, and global accuracy).Results: The Brigham and Women's Hospital and Salamanca systems were more distinctive, homogeneous, and monotonic than the Tübingen system. The Tübingen system was the most specific, whereas the Salamanca and Brigham and Women's Hospital systems were more sensitive. Negative predictive value was high in all 3 systems, but positive predictive value and accuracy were low overall.Conclusions: Alternative staging systems may partially overcome the heterogeneity and low prognostic accuracy of the American Joint Committee on Cancer, eighth edition and enable high-risk cutaneous SCCs to be stratified more reliably, but their prognostic accuracy is still low. Considering the accumulation of risk factors may improve high-risk cutaneous SCC risk stratification. [ABSTRACT FROM AUTHOR]