RNAseq gene expression profiles of 87 pre-treatment biopsies of breast cancer patients to study neoadjuvant treatment response

When locally advanced breast cancer is treated with neoadjuvant chemotherapy, the recurrence risk is significantly higher if no complete pathologic response is achieved. Identification of the underlying resistance mechanisms is essential to select treatments with maximal efficacy and minimal toxicity. Here we employed gene expression profiles derived from 317 HER2-negative treatment-naïve breast cancer biopsies of patients who underwent neoadjuvant chemotherapy, deep whole exome and RNA-sequencing profiles of 22 matched pre- and post-treatment tumors, and treatment outcome data to identifiy biomarkers of response and resistance mechanims. Molecular profiling of treatment-naïve breast cancer samples revealed that expression levels of proliferation, immune response and extracellular matrix (ECM) organization combined predict response to chemotherapy. Triple negative patients with high proliferation, high immune response and low ECM expression had a significantly better treatment response and survival benefit (HR 0.29, 95% CI 0.10-0.85; p=0.02), while in ER+ patients the opposite was seen (HR 4.73, 95% CI 1.51-14.8; 0=0.008). The characterization of paired pre-and post-treatment samples revealed that aberrations of known cancer genes were either only present in the pre-treatmane sample (CDKN1B) or in the post-treatment sample(TP53, APC, CTNNB1). Proliferation-associated genes were frequently down-regulated in post-treatment ER+ tumors, but not in triple negative tumors. Genes involved in ECM were upregulated in the majority of post-chemotherapy samples. Genomic and transcriptomic differences between pre- and post-chemotherapy samples are common and may reveal potential mechanisms of therapy resistance. Our results show a wide range of distinct, but related mechanisms, with a prominent role for proliferation- and ECM-related genes. Triple negative and luminal type breast cancer patients scheduled to receive neoadjuvant chemotherapy were included in this study. RNA was isolated from fresh-frozen biopsies. Illumina sequencing libraries were made and sequencing was performed on Illumina HiSeq 2000. Data was analyzed together with GSE34138, resulting in a larger dataset of n=317 neoadjuvant gene expression profiles. **RAW data was deposited at EGA (EGAD00001008433)**

局部晚期乳腺癌接受新辅助化疗时，若未获得完全病理缓解，复发风险将显著升高。明确其潜在耐药机制，对于筛选疗效最大化、毒性最小化的治疗方案至关重要。
本研究纳入了317例未经治疗的HER2（人表皮生长因子受体2）阴性乳腺癌活检样本的基因表达谱，以及22例配对的治疗前后肿瘤的深度全外显子组和RNA测序谱，结合治疗结局数据，以鉴定化疗应答与耐药机制的生物标志物。
对未经治疗的乳腺癌样本进行分子分型分析发现，增殖、免疫应答及细胞外基质（extracellular matrix, ECM）组织相关基因的表达水平联合可预测化疗应答情况。三阴性乳腺癌患者中，高增殖、高免疫应答且低ECM表达者的治疗应答与生存获益均显著更优（风险比0.29，95%置信区间0.10~0.85；P=0.02）；而雌激素受体阳性（ER+）患者则呈现相反趋势（风险比4.73，95%置信区间1.51~14.8；P=0.008）。
配对治疗前后样本的特征分析显示，已知癌基因的异常要么仅存在于治疗前样本（如CDKN1B），要么仅出现在治疗后样本（如TP53、APC、CTNNB1）。
增殖相关基因在治疗后ER+乳腺癌样本中普遍下调，但在三阴性乳腺癌样本中未出现该现象。而ECM相关基因在多数化疗后样本中呈上调趋势。
化疗前后样本的基因组与转录组差异十分常见，可揭示潜在的化疗耐药机制。
本研究结果揭示了一系列独特且相互关联的机制，其中增殖相关与ECM相关基因发挥了关键作用。本研究纳入了计划接受新辅助化疗的三阴性乳腺癌与管腔型乳腺癌患者。
从新鲜冰冻活检组织中分离RNA，构建Illumina测序文库，并在Illumina HiSeq 2000平台上完成测序。
本研究结合GSE34138数据集进行联合分析，最终得到包含317例新辅助化疗患者基因表达谱的更大规模数据集。
原始数据已提交至欧洲基因组档案库（EGA，EGAD00001008433）