Department of Medical Oncology, The Second Hospital of Harbin, Harbin, Heilongjiang Province, China.
Department of Medical Oncology, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian Province, China.
Dis Markers. 2022 Sep 17;2022:8168517. doi: 10.1155/2022/8168517. eCollection 2022.
This study is aimed at screening genes for predicting the sensitivity response and favorable outcome of neoadjuvant therapy in breast cancer. We downloaded neoadjuvant therapy genetic data of breast cancer and separated it into the pathological complete response (pCR) group and the non-pCR group. Differential expression analysis was performed to select the differentially expressed genes (DEGs). After that, we investigated the enriched biological processes and pathways of DEGs. Then, core up/down protein-protein interaction (PPI) network was, respectively, constructed to identify the hub genes. A transcription factor-target gene regulation network was built to screen core transcription factors (TFs). We found one upregulated DEG (KLHDC7B) and four downregulated DEGs (TFF1, LOC440335, SLC39A6, and MLPH) overlapped in three datasets. All DEGs were mainly enriched in pathways related to DNA biosynthesis, cell cycle, immune response, metabolism, and angiogenesis. The hub genes were KRT18, IL7R, HIST1H1A, and E2F1. The core TFs were HOXA9, SPDEF, FOXA1, E2F1, and PGR. RT-qPCR suggested that E2F1 was overexpressed in MCF-7, but HOXA9 was low-expressed. Western blot suggested that the MAPK signal pathway was inhibited in MCF-7/ADR. That is to say, some genes and core TFs can predict the sensitivity response of neoadjuvant therapy in breast cancer. And E2F1 may be involved in the process of drug resistance by regulating the MAPK signaling pathway. These might be useful as sensitive genes for the efficacy evaluation of neoadjuvant chemotherapy in breast cancer.
本研究旨在筛选基因，预测乳腺癌新辅助治疗的敏感性反应和良好结局。我们下载了乳腺癌新辅助治疗的遗传数据，并将其分为病理完全缓解（pCR）组和非 pCR 组。进行差异表达分析以选择差异表达基因（DEGs）。之后，我们研究了 DEGs 的富集生物过程和途径。然后，分别构建核心上调/下调蛋白-蛋白相互作用（PPI）网络，以鉴定枢纽基因。构建转录因子-靶基因调控网络，筛选核心转录因子（TFs）。我们在三个数据集中共发现一个上调的 DEG（KLHDC7B）和四个下调的 DEGs（TFF1、LOC440335、SLC39A6 和 MLPH）。所有 DEGs 主要富集在与 DNA 生物合成、细胞周期、免疫反应、代谢和血管生成相关的途径中。枢纽基因是 KRT18、IL7R、HIST1H1A 和 E2F1。核心 TFs 是 HOXA9、SPDEF、FOXA1、E2F1 和 PGR。RT-qPCR 表明 E2F1 在 MCF-7 中过表达，但 HOXA9 低表达。Western blot 表明 MCF-7/ADR 中 MAPK 信号通路被抑制。也就是说，一些基因和核心 TFs 可以预测乳腺癌新辅助治疗的敏感性反应。E2F1 可能通过调节 MAPK 信号通路参与耐药过程。这些可能是作为乳腺癌新辅助化疗疗效评估的敏感基因有用。
