Clinical value of a cuproptosis-related differential long non-coding RNA scoring formula in clear cell renal cell carcinoma
10.3760/cma.j.cn115355-20220822-00536
- VernacularTitle:铜死亡相关差异长链非编码RNA评分公式在肾透明细胞癌中的临床价值
- Author:
Yongquan CHEN
1
;
Bo WU
;
Weijing HU
;
Xin WEI
;
Lin ZHANG
;
Dongwen WANG
Author Information
1. 山西医科大学第一临床医学院，太原 030001
- Keywords:
Kidney neoplasms;
Long non-coding RNA;
Regulated cell death;
Drug therapy
- From:
Cancer Research and Clinic
2023;35(8):584-591
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the value of a cuproptosis-related differential long non-coding RNA (lncRNA) scoring formula related to the prognosis of clear cell renal cell carcinoma (ccRCC) patients in the clinical diagnosis, prognosis prediction and treatment options based on bioinformatics.Methods:Gene matrix and clinical data of ccRCC patients were obtained from the Cancer Genome Atlas (TCGA) database (update to 29 March, 2022). The expression data of 539 ccRCC tissues and 72 paracancerous normal tissues were collected from gene matrix; the data of 530 ccRCC were collected from clinical data. Pearson correlation analysis, Wilcoxon signed rank test and univariate Cox proportional risk model were used to analyze the screened cuproptosis-related differential lncRNA related to the prognosis. R software was used to randomly divide 530 ccRCC patients with survival data into training set (266 cases) and validation set (264 cases) according to approximate 1∶1 ratio. LASSO regression analysis was used to construct a cuproptosis-related differential lncRNA scoring formula and cross-validation was performed. Receiver operating characteristic (ROC) curve analysis was used to evaluate the specificity and sensitivity of cuproptosis-related differential lncRNA scoring formula, and the area of the curve (AUC) was calculated. According to the median risk value, all patients were divided into the low-risk group and high-risk group; Kaplan-Meier method was used to analyze the difference in the overall survival (OS) of patients in the low-risk group and high-risk group. T test was used to detect the differences in the risk value of patients with different clinicopathological characteristics. R package rms was used to construct the nomogram for predicting 1-year, 3-year, 5-year OS rates of ccRCC patients, R package pRRophetic was used to predict the half-inhibitory concentration ( IC50) of common targeted drugs such as sorafenib and sunitinib in clinical treatment of ccRCC patients, and IC50 value of patients in low-risk group and high-risk group was compared by using Wilcoxon signed rank test. Tissue samples of 20 ccRCC patients who underwent radical nephrectomy and were diagnosed with pathology and the matched paracancerous normal tissues were collected from the First Hospital of Shanxi Medical University between June 2021 and December 2021. Real-time fluorescence quantitative polymerase chain reaction (qRT-PCR) was used to detect the expression of key lncRNA in ccRCC tissues. Results:Based on the expression matrix of 10 cuproptosis genes (FDX1, LIAS, LIPT1, DLD, DLAT, PDHA1, PDHB, MTF1, GLS, CDKN2A) of ccRCC patients in TCGA database, 153 cuproptosis-related differential lncRNA related to the prognosis were identified. According to LASSO regression analysis, a scoring formula of 4 cuproptosis-related differential lncRNA related to the prognosis was obtained, risk value was calculated as 0.020×AC015912.3+0.011×AC026401.3+0.063×AC103706.1+(-0.076)×EPB41L4A-DT. All patients were divided into high-risk group (≥0.76) and low-risk group (<0.76) based on the median value (0.76). ROC curve analysis showed that the scoring formula had good prediction accuracy in 1-year, 3-year, 5-year OS rates. In training set, validation set, the total cohort, the OS of patients in the high-risk group was worse than that in the low-risk group (all P < 0.001). The age, pathological degree, tumor staging, risk value calculated by cuproptosis-related differential lncRNA were independent influencing factors of OS (all P < 0.001). There were statistically significant differences in the risk value calculated by cuproptosis-related differential lncRNA scoring formula among patients with different pathological degree, tumor staging, T staging, N staging, M staging (all P < 0.01), while there were no statistically significant differences among patients with different gender and age (all P > 0.05). The established nomogram had good prediction accuracy in the 1-year, 3-year, 5-year OS rates. Sunitinib and sirolimus showed higher sensitivity in the high-risk group; axitinib, sorafenib and pazopanib showed higher sensitivity in the low-risk group. qRT-PCR results showed that relative expression level of AC015912.3 in ccRCC tissues was up-regulated compared with paracancerous tissues (1.00±0.04 vs. 0.68±0.24, t = 6.37, P < 0.01); the relative expression level of AC026401.3 in ccRCC tissues was up-regulated compared with paracancerous tissues (1.00±0.05 vs. 0.64±0.22, t = 7.29, P < 0.01); the relative expression level of AC103706.1 in ccRCC tissues was up-regulated compared with paracancerous tissues (1.00±0.04 vs. 0.64±0.21, t = 7.49, P < 0.01); the relative expression level of EPB41L4A-DT in ccRCC tissues was up-regulated compared with paracancerous tissues (1.00±0.06 vs. 0.73±0.10, t = 10.68, P < 0.01). Conclusions:Cuproptosis-related differential lncRNA scoring formula based on TCGA database can be used as a new marker for clinical diagnosis and prognosis prediction of ccRCC patients, which can help guide the clinical drug treatment of patients and facilitate accurate diagnosis and treatment.
