Transcriptomic analysis of breast cancer patients sensitive and resistant to chemotherapy: Looking for overall survival and drug resistance biomarkers. Transcriptomic analysis of breast cancer patients sensitive and resistant to chemotherapy: Looking for overall survival and drug resistance biomarkers

Purpose: Neoadjuvant chemotherapy is one important therapeutic strategy for breast cancer with the drawback of resistance development. Chemotherapy has adverse effects that combined with resistance could contribute to lower overall survival. This work aimed to evaluate the molecular profile of patients who received neoadjuvant chemotherapy trying to discover differentially expressed genes (DEGs) that could be used as biomarkers of chemotherapy response and overall survival. Methods: Breast cancer patients who received neoadjuvant chemotherapy were enrolled in this study and according to their pathological response were assigned as sensitive or resistant. To evaluate DEGs, GO, KEGG and protein-protein interactions, RNAseq information from all patients was obtained by next generation sequencing. Results: A total of 1985 DEGs were found and KEGG analysis indicated a great number of DEGs in metabolic pathways, pathways in cancer, cytokine-cytokine receptor interactions, and neuroactive ligand-receptor interactions. A selection of 73 DEGs were used further for an analysis of overall survival using the METABRIC study. Seven of those DEGs were found to correlated with overall survival, of them the sub-expression of C1QTNF3, CTF1, OLFML3, PLA2R1, PODN and the over expression of TUBB and TCP1 were found in resistant patients and related to patients with lower overall survival. Conclusions: This work highlights differences at the level of gene expression in patients resistant and sensitive to neoadjuvant chemotherapy. Cellular components related to extracellular region and plasma membrane were mainly involved. Furthermore, 73 DEGs were able to discriminate patients resistant and sensitive to neoadjuvant chemotherapy, and 7 of them were able to predict overall survival. Overall design: A total of 22 mRNA profile of breast cancer patients prior treatment who were then treated with neoadjuvant chemotherapy

研究目的：新辅助化疗（neoadjuvant chemotherapy）是乳腺癌的重要治疗策略之一，但其存在诱导耐药性产生的固有弊端。化疗本身具有不良反应，若与耐药性叠加，可能会导致患者总生存期缩短。本研究旨在对接受新辅助化疗的乳腺癌患者进行分子谱分析，以期筛选可作为化疗应答及总生存期生物标志物的差异表达基因（differentially expressed genes, DEGs）。
研究方法：本研究纳入接受新辅助化疗的乳腺癌患者，根据其病理应答情况分为敏感组与耐药组。为分析差异表达基因、基因本体（Gene Ontology, GO）富集分析、京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）富集分析以及蛋白质相互作用，本研究通过下一代测序（next-generation sequencing, NGS）获取所有患者的RNA测序（RNA sequencing, RNA-seq）数据。
研究结果：本研究共筛选得到1985个差异表达基因；KEGG富集分析显示，大量差异表达基因富集于代谢通路、癌症相关通路、细胞因子-细胞因子受体相互作用通路以及神经活性配体-受体相互作用通路。随后选取73个差异表达基因，采用乳腺癌国际联盟分子分型研究（METABRIC）队列进行总生存期分析。其中7个差异表达基因与患者总生存期显著相关：耐药患者中C1QTNF3、CTF1、OLFML3、PLA2R1、PODN呈低表达，TUBB与TCP1呈高表达，且上述基因表达水平与患者更短的总生存期密切相关。
研究结论：本研究揭示了新辅助化疗敏感与耐药乳腺癌患者之间的基因表达谱差异，相关差异主要涉及细胞外区域及质膜相关的细胞组分。此外，73个差异表达基因可有效区分新辅助化疗敏感与耐药患者，其中7个基因可用于预测患者总生存期。
研究设计：本研究共纳入22例乳腺癌患者的mRNA表达谱，所有患者均在接受新辅助化疗前采集样本并随后接受新辅助化疗。