Translational Research Laboratory, Department of Medicine, Autonomous University of Barcelona, Bellaterra, Barcelona, Catalonia, Spain.
Statistics and Bioinformatics Unit.
Mol Cancer Res. 2014 Sep;12(9):1254-66. doi: 10.1158/1541-7786.MCR-14-0121. Epub 2014 May 14.
The differential gene expression patterns between normal colonic fibroblasts (NCF), carcinoma-associated fibroblasts from primary tumors (CAF-PT), and CAFs from hepatic metastasis (CAF-LM) are hypothesized to be useful for predicting relapse in primary tumors. A transcriptomic profile of NCF (n = 9), CAF-PT (n = 14), and CAF-LM (n = 11) was derived. Prediction Analysis of Microarrays (PAM) was used to obtain molecular details for each fibroblast class, and differentially expressed transcripts were used to classify patients according to recurrence status. A number of transcripts (n = 277) were common to all three types of fibroblasts and whose expression level was sequentially deregulated according to the transition: NCF→CAF-PT→CAF-LM. Importantly, the gene signature was able to accurately classify patients with primary tumors according to their prognosis. This capacity was exploited to obtain a refined 19-gene classifier that predicted recurrence with high accuracy in two independent datasets of patients with colorectal cancer and correlates with fibroblast migratory potential. The prognostic power of this genomic signature is strong evidence of the link between the tumor-stroma microenvironment and cancer progression. Furthermore, the 19-gene classifier was able to identify low-risk patients very accurately, which is of particular importance for stage II patients, who would benefit from the omission of chemotherapy, especially T4N0 patients, who are clinically classified as being at high risk.
A defined stromal gene expression signature predicts relapse in patients with colorectal cancer.
假设正常结肠成纤维细胞(NCF)、原发性肿瘤相关成纤维细胞(CAF-PT)和肝转移相关成纤维细胞(CAF-LM)之间的差异基因表达模式可用于预测原发性肿瘤的复发。对 NCF(n=9)、CAF-PT(n=14)和 CAF-LM(n=11)进行了转录组谱分析。采用预测分析微阵列(PAM)获得每种成纤维细胞的分子细节,并根据复发状态对差异表达的转录物进行分类。有许多转录本(n=277)在所有三种成纤维细胞中都存在,并且其表达水平根据以下顺序逐渐失调:NCF→CAF-PT→CAF-LM。重要的是,该基因特征能够根据患者的预后准确地对原发性肿瘤患者进行分类。利用这种能力获得了一个经过改进的 19 基因分类器,该分类器可以在两个独立的结直肠癌患者数据集上准确地预测复发,并且与成纤维细胞迁移潜力相关。该基因组特征的预后能力有力地证明了肿瘤-基质微环境与癌症进展之间的联系。此外,19 基因分类器能够非常准确地识别低风险患者,这对 II 期患者尤其重要,他们将受益于化疗的省略,特别是 T4N0 患者,他们在临床上被归类为高风险。
定义明确的基质基因表达特征可预测结直肠癌患者的复发。