Department of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China (mainland).
Department of Pathology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China (mainland).
Med Sci Monit. 2017 Sep 7;23:4321-4327. doi: 10.12659/msm.903272.
BACKGROUND This study aimed to identify key genes contributing to pathological complete response (pCR) to chemotherapy by mRNA sequencing (RNA-seq). MATERIAL AND METHODS RNA was extracted from the frozen biopsy tissue of patients with pathological complete response and patients with non-pathological complete response. Sequencing was performed on the HiSeq2000 platform. Differentially expressed genes (DEGs) were identified between the pCR group and non-pCR (NpCR) group. Pathway enrichment analysis of DEGs was performed. A protein-protein interaction network was constructed, then module analysis was performed to identify a subnetwork. Finally, transcription factors were predicted. RESULTS A total of 673 DEGs were identified, including 419 upregulated ones and 254 downregulated ones. The PPI network constructed consisted of 276 proteins forming 471 PPI pairs, and a subnetwork containing 18 protein nodes was obtained. Pathway enrichment analysis revealed that PLCB4 and ADCY6 were enriched in pathways renin secretion, gastric acid secretion, gap junction, inflammatory mediator regulation of TRP channels, retrograde endocannabinoid signaling, melanogenesis, cGMP-PKG signaling pathway, calcium signaling pathway, chemokine signaling pathway, cAMP signaling pathway, and rap1 signaling pathway. CNR1 was enriched in the neuroactive ligand-receptor interaction pathway, retrograde endocannabinoid signaling pathway, and rap1 signaling pathway. The transcription factor-gene network consists of 15 transcription factors and 16 targeted genes, of which 5 were downregulated and 10 were upregulated. CONCLUSIONS We found key genes that may contribute to pCR to chemotherapy, such as PLCB4, ADCY6, and CNR1, as well as some transcription factors.
本研究旨在通过 mRNA 测序(RNA-seq)鉴定导致化疗病理完全缓解(pCR)的关键基因。
从病理完全缓解患者和非病理完全缓解(NpCR)患者的冷冻活检组织中提取 RNA。在 HiSeq2000 平台上进行测序。在 pCR 组和非 pCR(NpCR)组之间鉴定差异表达基因(DEGs)。对 DEGs 进行通路富集分析。构建蛋白质-蛋白质相互作用网络,然后进行模块分析以识别子网络。最后,预测转录因子。
共鉴定出 673 个 DEGs,其中 419 个上调,254 个下调。构建的 PPI 网络包含 276 个蛋白质,形成 471 个 PPI 对,获得了一个包含 18 个蛋白质节点的子网络。通路富集分析显示,PLCB4 和 ADCY6 富集于肾素分泌、胃酸分泌、缝隙连接、TRP 通道炎症介质调节、逆行内源性大麻素信号、黑色素生成、cGMP-PKG 信号通路、钙信号通路、趋化因子信号通路、cAMP 信号通路和 rap1 信号通路。CNR1 富集于神经活性配体-受体相互作用通路、逆行内源性大麻素信号通路和 rap1 信号通路。转录因子-基因网络包含 15 个转录因子和 16 个靶向基因,其中 5 个下调,10 个上调。
我们发现了一些可能与化疗 pCR 相关的关键基因,如 PLCB4、ADCY6 和 CNR1,以及一些转录因子。