Peyravian Noshad, Nobili Stefania, Pezeshkian Zahra, Olfatifar Meysam, Moradi Afshin, Baghaei Kaveh, Anaraki Fakhrosadat, Nazari Kimia, Asadzadeh Aghdaei Hamid, Zali Mohammad Reza, Mini Enrico, Nazemalhosseini Mojarad Ehsan
Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, P.O. Box 19875-17411, Tehran, Iran.
Department of Neurosciences, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, 66100 Chieti, Italy.
J Pers Med. 2021 Feb 14;11(2):126. doi: 10.3390/jpm11020126.
This study aimed at building a prognostic signature based on a candidate gene panel whose expression may be associated with lymph node metastasis (LNM), thus potentially able to predict colorectal cancer (CRC) progression and patient survival. The mRNA expression levels of 20 candidate genes were evaluated by RT-qPCR in cancer and normal mucosa formalin-fixed paraffin-embedded (FFPE) tissues of CRC patients. Receiver operating characteristic curves were used to evaluate the prognosis performance of our model by calculating the area under the curve (AUC) values corresponding to stage and metastasis. A total of 100 FFPE primary tumor tissues from stage I-IV CRC patients were collected and analyzed. Among the 20 candidate genes we studied, only the expression levels of significantly varied between patients with and without LNMs ( = 0.02). Additionally, the AUC value of the 20-gene panel was found to have the highest predictive performance (i.e., AUC = 79.84%) for LNMs compared with that of two subpanels including 5 and 10 genes. According to our results, gene expression levels are able to estimate LNMs in different stages of CRC. After a proper validation in a wider case series, the evaluation of gene expression and that of the 20-gene panel signature could help in the future in the prediction of CRC progression.
本研究旨在基于一个候选基因面板构建一个预后特征,该基因面板的表达可能与淋巴结转移(LNM)相关,从而有可能预测结直肠癌(CRC)的进展和患者生存情况。通过RT-qPCR评估了20个候选基因在CRC患者癌组织和正常黏膜福尔马林固定石蜡包埋(FFPE)组织中的mRNA表达水平。采用受试者工作特征曲线,通过计算与分期和转移相对应的曲线下面积(AUC)值来评估我们模型的预后性能。共收集并分析了100例I-IV期CRC患者的FFPE原发性肿瘤组织。在我们研究的20个候选基因中,只有 基因的表达水平在有和没有LNM的患者之间有显著差异( = 0.02)。此外,与包括5个和10个基因的两个子面板相比,发现20基因面板对LNM的AUC值具有最高的预测性能(即AUC = 79.84%)。根据我们的结果, 基因表达水平能够估计CRC不同阶段的LNM。在更广泛的病例系列中进行适当验证后,对 基因表达和20基因面板特征的评估未来可能有助于预测CRC的进展。