Department of Biochemistry and Immunology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.
Regional Blood Center of Ribeirão Preto and Center for Cell Based Therapy, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil; Department of Gynecology and Obstetrics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil.
Biochim Biophys Acta Proteins Proteom. 2021 Jun;1869(6):140623. doi: 10.1016/j.bbapap.2021.140623. Epub 2021 Feb 17.
Ovarian cancer (OvCA) is the most lethal neoplasia among gynecologic malignancies and faces high rates of new cases particularly in South America. In special, the High Grade Serous Ovarian Carcinoma (HGSC) presents very poor prognosis with deaths caused mainly by metastasis. Among several mechanisms involved in metastasis, the Epithelial to Mesenchymal Transition (EMT) molecular reprogramming represents a model for latest stages of cancer progression. EMT promotes important cellular changes in cellular adhesion and cell-cell communication, which particularly depends on the paracrine signaling from neighbor cells. Considering the importance of cellular communication during EMT and metastasis, here we analyzed the changes in the secretome of the ovarian cancer cell line Caov-3 induced to EMT by Epidermal Growth Factor (EGF). Using a combination of GEL-LC-MS/MS and stable isotopic metabolic labelling (SILAC), we identified up-regulated candidates during EMT as a starting point to identify relevant proteins for HGSC. Based on public databases, our candidate proteins were validated and prioritized for further analysis. Importantly, several of the protein candidates were associated with cellular vesicles, which are important to the cell-cell communication and metastasis. Furthermore, the association of candidate proteins with gene expression data uncovered a subset of proteins correlated with the mesenchymal subtype of ovarian cancer. Based on this relevant molecular signature for aggressive ovarian cancer, supported by protein and gene expression data, we developed a targeted proteomic method to evaluate individual OvCA clinical samples. The quantitative information obtained for 33 peptides, representative of 18 proteins, was able to segregate HGSC from other tumor types. Our study highlighted the richness of the secretome and EMT to reveal relevant proteins for HGSC, which could be used in further studies and larger patient cohorts as a potential stratification signature for ovarian cancer tumor that could guide clinical conduct for patient treatment.
卵巢癌 (OvCA) 是妇科恶性肿瘤中最致命的肿瘤，在南美洲新发病例率尤其高。特别是高级别浆液性卵巢癌 (HGSC) 预后非常差，主要由转移引起。在转移涉及的几种机制中，上皮间质转化 (EMT) 分子重编程代表了癌症进展的最新阶段的模型。EMT 促进了细胞黏附和细胞间通讯的重要细胞变化，这主要依赖于来自相邻细胞的旁分泌信号。考虑到 EMT 和转移过程中细胞通讯的重要性，我们在这里分析了卵巢癌细胞系 Caov-3 在表皮生长因子 (EGF) 诱导 EMT 过程中分泌组的变化。我们使用 GEL-LC-MS/MS 和稳定同位素代谢标记 (SILAC) 的组合，鉴定了 EMT 过程中上调的候选蛋白，作为鉴定 HGSC 相关蛋白的起点。基于公共数据库，我们对候选蛋白进行了验证，并对其进行了进一步分析。重要的是，候选蛋白中的几个与细胞小泡相关，细胞小泡对于细胞间通讯和转移很重要。此外，候选蛋白与基因表达数据的关联揭示了与卵巢癌间质亚型相关的蛋白子集。基于该具有侵袭性卵巢癌的相关分子特征，以及蛋白质和基因表达数据的支持，我们开发了一种靶向蛋白质组学方法来评估个体 OvCA 临床样本。代表 18 种蛋白质的 33 种肽的定量信息能够将 HGSC 与其他肿瘤类型区分开来。我们的研究强调了分泌组和 EMT 的丰富性，以揭示与 HGSC 相关的相关蛋白，这些蛋白可以在进一步的研究和更大的患者队列中作为卵巢癌肿瘤的潜在分层特征，指导患者治疗的临床实践。
