Proteomics Laboratory, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
J Proteome Res. 2011 Sep 2;10(9):4196-207. doi: 10.1021/pr200344n. Epub 2011 Jul 29.
In principle, targeted therapies have optimal activity against a specific subset of tumors that depend upon the targeted molecule or pathway for growth, survival, or metastasis. Consequently, it is important in drug development and clinical practice to have predictive biomarkers that can reliably identify patients who will benefit from a given therapy. We analyzed tumor cell-line secretomes (conditioned cell media) to look for predictive biomarkers; secretomes represent a potential source for potential biomarkers that are expressed in intracellular signaling and therefore may reflect changes induced by targeted therapy. Using Gene Ontology, we classified by function the secretome proteins of 12 tumor cell lines of different histotypes. Representations and hierarchical relationships among the functional groups differed among the cell lines. Using bioinformatics tools, we identified proteins involved in intracellular signaling pathways. For example, we found that secretome proteins related to TGF-beta signaling in thyroid cancer cells, such as vasorin, CD109, and βIG-H3 (TGFBI), were sensitive to RPI-1 and dasatinib treatments, which have been previously demonstrated to be effective in blocking cell proliferation. The secretome may be a valuable source of potential biomarkers for detecting cancer and measuring the effectiveness of cancer therapies.
原则上，靶向治疗对依赖于靶向分子或通路生长、存活或转移的特定肿瘤亚群具有最佳活性。因此，在药物开发和临床实践中，拥有能够可靠识别将从特定治疗中受益的患者的预测性生物标志物非常重要。我们分析了肿瘤细胞系的分泌组（条件细胞培养基），以寻找预测性生物标志物；分泌组代表了一种潜在的生物标志物来源，这些生物标志物在细胞内信号传导中表达，因此可能反映了靶向治疗诱导的变化。使用基因本体论，我们按功能对 12 种不同组织类型的肿瘤细胞系的分泌组蛋白进行了分类。细胞系之间的功能组的表示和层次关系不同。使用生物信息学工具，我们鉴定了参与细胞内信号通路的蛋白质。例如，我们发现甲状腺癌细胞中与 TGF-β 信号相关的分泌组蛋白，如 vasorin、CD109 和βIG-H3（TGFBI），对 RPI-1 和 dasatinib 治疗敏感，这两种药物先前已被证明可有效阻断细胞增殖。分泌组可能是检测癌症和衡量癌症治疗效果的潜在生物标志物的有价值来源。
