Globally, BC is the most frequently diagnosed cancer in women. The aim of this study was to identify novel secreted biomarkers that may indicate progression to high-grade BC malignancies and therefore predict metastatic potential. A total of 33 studies of breast cancer and 78 of other malignancies were screened via a systematic review for eligibility, yielding 26 datasets, 8 breast cancer secretome datasets, and 18 of other cancers that were included in the comparative secretome analysis. Sequential bioinformatic analysis using online resources enabled the identification of enriched GO_terms, overlapping clusters, and pathway reconstruction. This study identified putative predictors of IDC grade progression and their association with breast cancer patient mortality outcomes, namely, HSPG2, ACTG1, and LAMA5 as biomarkers of in silico pathway prediction, offering a putative approach by which the abovementioned proteins may mediate their effects, enabling disease progression. This study also identified ITGB1, FBN1, and THBS1 as putative pan-cancer detection biomarkers. The present study highlights novel, putative secretome biomarkers that may provide insight into the tumor biology and could inform clinical decision making in the context of IDC management in a non-invasive manner.
Keywords: IDC; bioinformatics; biomarkers; comparative analysis.