Insights on the association of anthropometric and metabolic variables with tumor features and genomic risk in luminal early breast cancer: Results of a multicentric prospective study

Background: Hormone receptor-positive (HR+)/HER2-negative (HER2-) early-stage breast cancers (EBC) are treated with adjuvant endocrine therapy (ET), with chemotherapy (CT) reserved for high-risk cases. Obesity is linked to increased recurrence risk. The Oncotype DX® assay predicts prognosis and CT benefit. The PRO BONO study evaluated Oncotype DX test's impact on treatment decisions and explored associations between genomic risk, tumor features, and patient metabolic profiles. Materials and Methods: Patients with HR+ /HER2-EBC undergoing Oncotype DX testing were enrolled. Body mass index (BMI), tumor characteristics (ER, PR, Ki67, grading, size, nodal status), a large panel of metabolic analytes, and Oncotype DX Recurrence Score® (RS) results were collected. Treatment recommendations (ET vs CT-ET) were recorded pre- and post-Oncotype DX, and concordance was determined using Cohen's Kappa. Associations were tested using Chi-Square test and Spearman Correlation. Results: Of the 248 EBC patients (2019–2021), Oncotype DX testing reduced CT use by 47.7 %. Higher RS positively correlated with serum triglycerides and inversely with GIP (all p < 0.05). No significant association was found between patient BMI and RS result. Conversely, tumor size positively correlated with BMI (p = 0.0286) and with serum levels of leptin (p = 0.0079), PAI-1 (p = 0.0083), C-peptide (p = 0.0124), GIP (p = 0.0036), GLP-1 (p = 0.0476), glucagon (p = 0.0224), and insulin (p = 0.0327). A BMI≥ 30 and higher GLP-1 levels (>148.85pg/ml) were independently associated with increased odds of having larger tumor size (>2 cm). Conclusions: Recurrence Score result significantly impacts treatment decisions in HR+ /HER2-EBC. RS result was not associated with BMI, although unfavorable metabolic profiles and obesity-related markers correlated with larger tumors. These findings highlight the need to further investigate the link between metabolic profiles and breast cancer biology.