Kastora Stavroula L, Kounidas Georgios, Speirs Valerie, Masannat Yazan A
Institute of Medical Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen AB24 2ZD, UK.
Breast Unit, Aberdeen Royal Infirmary, Aberdeen AB25 2ZN, UK.
Cancers (Basel). 2022 Aug 9;14(16):3854. doi: 10.3390/cancers14163854.
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.
在全球范围内，乳腺癌是女性中最常被诊断出的癌症。本研究的目的是识别可能指示向高级别乳腺癌恶性肿瘤进展并因此预测转移潜力的新型分泌生物标志物。通过系统综述对总共33项乳腺癌研究和78项其他恶性肿瘤研究进行筛选以确定其是否符合条件，得到了26个数据集，8个乳腺癌分泌蛋白质组数据集，以及18个其他癌症的数据集，这些数据集被纳入比较分泌蛋白质组分析。使用在线资源进行的序贯生物信息学分析能够识别富集的基因本体术语、重叠簇和通路重建。本研究确定了浸润性导管癌（IDC）分级进展的推定预测因子及其与乳腺癌患者死亡率结果的关联，即HSPG2、ACTG1和LAMA5作为计算机通路预测的生物标志物，提供了一种上述蛋白质可能介导其作用从而促进疾病进展的推定方法。本研究还确定了整合素β1（ITGB1）、纤连蛋白1（FBN1）和血小板反应蛋白1（THBS1）作为推定的泛癌检测生物标志物。本研究突出了新型的、推定的分泌蛋白质组生物标志物，这些标志物可能为肿瘤生物学提供见解，并能够以非侵入性方式为IDC管理背景下的临床决策提供信息。
