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Breast cancer (BC) is the most common malignancy among women in Canada. Adjuvant treatment in early BC can reduce the risk of BC recurrence. Historically, the decision for adjuvant chemotherapy for early BC was made only based on clinical and tumour characteristics. In recent years, there has been an effort toward developing genomic assays as a predictive and prognostic tool to improve precision in estimating disease recurrence, sensitivity to systemic treatment and ultimately with clinical utility for guidance regarding adjuvant systemic treatment(s). There are various commercial genomic tests available for early-stage ER+/HER-2 negative BC. This paper will review the Oncotype DX 21-gene Recurrence Score (RS), MammaPrint, EndoPredict, Prosigna®, and Breast Cancer Index (BCI) genomic assays. We will also focus on these genomic assays' clinical application and utility in node-positive early-stage BC based on the most recent evidence and guidance recommendations. [ABSTRACT FROM AUTHOR]

Introduction: Carcinogenesis is driven by an array of complex genomic patterns; these patterns can render an individual resistant or sensitive to certain chemotherapy agents. The Personalized Oncogenomics (POG) project at BC Cancer has performed integrative genomic analysis of whole tumour genomes and transcriptomes for over 700 patients with advanced cancers, with an aim to predict therapeutic sensitivities. The aim of this study was to utilize the POG genomic data to evaluate a discrete set of biomarkers associated with chemo-sensitivity or-resistance in advanced stage breast and colorectal cancer POG patients. Methods: This was a retrospective multi-centre analysis across all BC CANCER sites. All breast and colorectal cancer patients enrolled in the POG program between July 1, 2012 and November 30, 2016 were eligible for inclusion. Within the breast cancer population, those treated with capecitabine, paclitaxel, and everolimus were analyzed, and for the colorectal cancer patients, those treated with capecitabine, bevacizumab, irinotecan, and oxaliplatin were analyzed. The expression levels of the selected biomarkers of interest (EPHB4, FIGF, CD133, DICER1, DPYD, TYMP, TYMS, TAP1, TOP1, CKDN1A, ERCC1, GSTP1, BRCA1, PTEN, ABCB1, TLE3, and TXNDC17) were reported as mRNA percentiles. Results: For the breast cancer population, there were 32 patients in the capecitabine cohort, 15 in the everolimus cohort, and 12 in the paclitaxel cohort. For the colorectal cancer population, there were 29 patients in the bevacizumab cohort, 12 in the oxaliplatin cohort, 29 in the irinotecan cohort, and 6 in the capecitabine cohort. Of the biomarkers evaluated, the strongest associations were found between Bevacizumab-based therapy and DICER1 (P = 0.0445); and between capecitabine therapy and TYMP (P = 0.0553). Conclusions: Among breast cancer patients, higher TYMP expression was associated with sensitivity to capecitabine. Among colorectal cancer patients, higher DICER1 expression was associated with sensitivity to bevacizumab-based therapy. This study supports further assessment of the potential predictive value of mRNA expression of these genomic biomarkers. [ABSTRACT FROM AUTHOR]