Deng Benyuan, Yang Min, Wang Ming, Liu Zhongwu
West China Health Care Hospital of Sichuan University.
Department of Pediatric Surgery, West China Hospital of Sichuan University.
Medicine (Baltimore). 2020 May 22;99(21):e20422. doi: 10.1097/MD.0000000000020422.
Primary hepatic carcinoma is 1 of the most common malignant tumors globally, of which hepatocellular carcinoma (HCC) accounts for 85% to 90%. Due to the high degree of deterioration and low early detection rate of HCC, most patients are diagnosed when they are already in the middle and advanced stages, and the prognosis are always poor.RNA sequencing data from the cancer genome atlas was used to explore differences in lncRNA expression profiles. LncRNA was extracted by gdcRNAtools in R package. Multivariate cox analysis was performed on the screened lncRNAs. The relationship between the lncRNA model and prognosis as well as clinical characteristics of patients with HCC was analyzed. Finally, a predictive nomogram in the the cancer genome atlas cohort was established and verified internallyBased on the RNA sequencing survival analysis, a 9- lncRNAs prognosis model, including TMCC1-AS1, AC008892.1, AL031985.3, L34079.2, U95743.1, KDM4A-AS1, SACS-AS1, AC005534.1, LINC01116 was established. The 9-lncRNA prognosis model was a reliable tool for predicting prognosis of HCC, and the nomogram of this prognosis model could help clinicians to choose personalized treatment for HCC patientsThis model was significant to complement clinic characteristics of HCC and to promote personalized management of patients, it also provided a new idea for researches on the prognosis of HCC.
原发性肝癌是全球最常见的恶性肿瘤之一，其中肝细胞癌（HCC）占85%至90%。由于HCC恶化程度高且早期检出率低，大多数患者在中晚期才被诊断出来，预后往往很差。利用来自癌症基因组图谱的RNA测序数据来探索长链非编码RNA（lncRNA）表达谱的差异。lncRNA通过R包中的gdcRNAtools进行提取。对筛选出的lncRNAs进行多变量cox分析。分析lncRNA模型与HCC患者预后及临床特征之间的关系。最后，在癌症基因组图谱队列中建立并进行内部验证了一个预测列线图。基于RNA测序生存分析，建立了一个包含TMCC1-AS1、AC008892.1、AL031985.3、L34079.2、U95743.1、KDM4A-AS1、SACS-AS1、AC005534.1、LINC01116的9-lncRNAs预后模型。该9-lncRNA预后模型是预测HCC预后的可靠工具，该预后模型的列线图可帮助临床医生为HCC患者选择个性化治疗。该模型对于补充HCC的临床特征和促进患者的个性化管理具有重要意义，也为HCC预后研究提供了新思路。
