DataSheet4_A gene expression signature in HER2+ breast cancer patients related to neoadjuvant chemotherapy resistance, overall survival, and disease-free survival.PDF

Breast cancer ranks first in terms of mortality and incidence rates worldwide among women. The HER2+ molecular subtype is one of the most aggressive subtypes; its treatment includes neoadjuvant chemotherapy and the use of a HER2 antibody. Some patients develop resistance despite positive results obtained using this therapeutic strategy. Objective. To identify prognostic markers for treatment and survival in HER2+ patients. Methods. Patients treated with neoadjuvant chemotherapy were assigned to sensitive and resistant groups based on their treatment response. Differentially expressed genes (DEGs) were identified using RNA-seq analysis. KEGG pathway, gene ontology, and interactome analyses were performed for all DEGs. An enrichment analysis Gene set enrichment analysis was performed. All DEGs were analyzed for overall (OS) and disease-free survival (DFS). Results. A total of 94 DEGs were related to treatment resistance. Survival analysis showed that 12 genes (ATF6B, DHRS13, DIRAS1, ERAL1, GRIN2B, L1CAM, IRX3, PRTFDC1, PBX2, S100B, SLC9A3R2, and TNXB) were good predictors of disease-free survival, and eight genes (GNG4, IL22RA2, MICA, S100B, SERPINF2, HLA-A, DIRAS1, and TNXB) were good predictors of overall survival (OS). Conclusion: We highlighted a molecular expression signature that can differentiate the treatment response, overall survival, and DFS of patients with HER2+ breast cancer.

乳腺癌是全球女性发病率与死亡率均位列第一的恶性肿瘤。人表皮生长因子受体2阳性（HER2+）分子亚型是侵袭性最强的乳腺癌亚型之一，其临床治疗方案包含新辅助化疗（neoadjuvant chemotherapy）及HER2靶向抗体的应用。但部分患者即便采用该治疗策略，仍会产生治疗耐药性。
研究目的：明确HER2+乳腺癌患者治疗与生存相关的预后标志物。
研究方法：将接受新辅助化疗的患者按治疗应答情况分为敏感组与耐药组，通过RNA测序（RNA-seq）分析筛选差异表达基因（differentially expressed genes, DEGs）。对所有DEGs开展京都基因与基因组百科全书通路（KEGG pathway）分析、基因本体（gene ontology, GO）注释、互作组分析及基因集富集分析（gene set enrichment analysis, GSEA），同时对所有DEGs进行总生存期（overall survival, OS）与无病生存期（disease-free survival, DFS）的生存相关性分析。
研究结果：共计筛选出94个与治疗耐药相关的DEGs。生存分析显示，12个基因（ATF6B、DHRS13、DIRAS1、ERAL1、GRIN2B、L1CAM、IRX3、PRTFDC1、PBX2、S100B、SLC9A3R2及TNXB）可作为无病生存期的良好预测标志物，另有8个基因（GNG4、IL22RA2、MICA、S100B、SERPINF2、HLA-A、DIRAS1及TNXB）可作为总生存期的良好预测标志物。
研究结论：本研究揭示了一组可区分HER2+乳腺癌患者治疗应答、总生存期与无病生存期的分子表达特征谱。