A novel cuproptosis-related lncRNAs signature predicts prognostic and immune of bladder urothelial carcinoma.

Bladder Urothelial Carcinoma (BLCA) remains the most common urinary system tumor, and its prognosis is poor. Cuproptosis is a recently discovered novel cell death involved in the development of tumor cells. However, the use of cuproptosis to predict the prognosis and immunity of Bladder Urothelial Carcinoma remains largely unclear, and this study was designed to verify cuproptosis-related long non-coding RNAs (lncRNAs) to estimate the prognosis and immunity of Bladder Urothelial Carcinoma. In our study, we first defined the expression of cuproptosis-related genes (CRGs) in BLCA, and 10 CRGs were up- or downregulated. We then constructed a co-expression network of cuproptosis-related mRNA and long non-coding RNAs using RNA sequence data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA-BLCA), clinical features and mutation data from BLCA patients to obtain long non-coding RNAs by Pearson analysis. Afterward, univariate and multivariate COX analysis identified 21 long non-coding RNAs as independent prognostic factors and used these long non-coding RNAs to construct a prognostic model. Then, survival analysis, principal component analysis (PCA), immunoassay, and comparison of tumor mutation frequencies were performed to verify the accuracy of the constructed model, and GO and KEGG functional enrichment analysis was used to verify further whether cuproptosis-related long non-coding RNAs were associated with biological pathways. The results showed that the model constructed with cuproptosis-related long non-coding RNAs could effectively evaluate the prognosis of BLCA, and these long non-coding RNAs were involved in numerous biological pathways. Finally, we performed immune infiltration, immune checkpoint and drug sensitivity analyses on four genes (TTN, ARID1A, KDM6A, RB1) that were highly mutated in the high-risk group to evaluate the immune association of risk genes with BLCA. In conclusion, the cuproptosis-related lncRNA markers constructed in this study have evaluation value for prognosis and immunity in BLCA, which can provide a certain reference for the treatment and immunity of BLCA.

Zhou Z ，Zhou Y ，Liu W ，Dai J ... -  《Frontiers in Genetics》

Comprehensive analysis of cuproptosis-related lncRNAs signature to predict prognosis in bladder urothelial carcinoma.

Cuproptosis-related genes (CRGs) have been recently discovered to regulate the occurrence and development of various tumors by controlling cuproptosis, a novel type of copper ion-dependent cell death. Although cuproptosis is mediated by lipoylated tricarboxylic acid cycle proteins, the relationship between cuproptosis-related long noncoding RNAs (crlncRNAs) in bladder urothelial carcinoma (BLCA) and clinical outcomes, tumor microenvironment (TME) modification, and immunotherapy remains unknown. In this paper, we tried to discover the importance of lncRNAs for BLCA. The BLCA-related lncRNAs and clinical data were first obtained from The Cancer Genome Atlas (TCGA). CRGs were obtained through Coexpression, Cox regression and Lasso regression. Besides, a prognosis model was established for verification. Meanwhile, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene ontology (GO) analysis, principal component analysis (PCA), half-maximal inhibitory concentration prediction (IC50), immune status and drug susceptibility analysis were carried out. We identified 277 crlncRNAs and 16 survival-related lncRNAs. According to the 8-crlncRNA risk model, patients could be divided into high-risk group and low-risk group. Progression-Free-Survival (PFS), independent prognostic analysis, concordance index (C-index), receiver operating characteristic (ROC) curve and nomogram all confirmed the excellent predictive capability of the 8-lncRNA risk model for BLCA. During gene mutation burden survival analysis, noticeable differences were observed in high- and low-risk patients. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs. The nomogram with 8-lncRNA may help guide treatment of BLCA. More clinical studies are necessary to verify the nomogram.

Zhu S ，Li H ，Fan Y ，Tang C ... -  《BMC Urology》

Identification of a novel defined inflammation-related long noncoding RNA signature contributes to predicting prognosis and distinction between the cold and hot tumors in bladder cancer.

Bladder cancer (BLCA) is one of the most frequently diagnosed urological malignancies and is the 4th most common cancer in men worldwide. Molecular targets expressed in bladder cancer (BLCA) are usually used for developing targeted drug treatments. However, poor prognosis and poor immunotherapy efficacy remain major challenges for BLCA. Numerous studies have shown that long non-coding RNAs (LncRNAs) play an important role in the development of cancer. However, the role of lncRNAs related to inflammation in BLCA and their prognostic value remain unclear. Therefore, this study is aimed to explore new potential biomarkers that can predict cancer prognosis. We downloaded BLCA-related RNA sequencing data from The Cancer Genome Atlas (TCGA) and searched for inflammation-related prognostic long non-coding RNAs (lncRNAs) by univariate Cox (uniCox) regression and co-expression analysis. We used the least absolute shrinkage and selection operator (LASSO) analysis to construct an inflammation-related lncRNA prognosis risk model. Samples were divided into high-risk score (HRS) group and low-risk score (LRS) group based on the median value of risk scores. The independent variable factors were identified by univariate Cox (uni-Cox) and multivariate Cox (multi-Cox) regression analyses, and receiver operating characteristic (ROC) curves were used to compare the role of different factors in predicting outcomes. Nomogram and Calibration Plot were generated by the R package rms to analyze whether the prediction results are correct and show good consistency. Correlation coefficients were calculated by Pearson analysis. The Kaplan-Meier method was used to assess the prognostic value. The expression of 7 lncRNAs related with inflammation was also confirmed by qRT-PCR in BLCA cell lines. Kyoto Encyclopedia of Gene and Genome (KEGG) pathways that were significantly enriched (P < 0.05) in each risk group were identified by the GSEA software. The R package pRRophetic was used to predict the IC50 of common chemotherapeutic agents. TIMER, XCELL, QUANTISEQ, MCPCOUNTER, EPIC and CIBERSORT were applied to quantify the relative proportions of infiltrating immune cells. We also used package ggpubr to evaluate TME scores and immune checkpoint activation in LRS and HRS populations. R package GSEABase was used to analyze the activity of immune cells or immune function. Different clusters of principal component analysis (PCA), t-distribution random neighborhood embedding (t-SNE), and Kaplan-Meier survival were analyzed using R package Rtsne's. The R package ConsensesClusterPlus was used to class the inflammation-related lncRNAs. In this study, a model containing 7 inflammation-related lncRNAs was constructed. The calibration plot of the model was consistent with the prognosis prediction outcomes. The 1-, 3-, and 5-year ROC curve (AUC) were 0.699, 0.689, and 0.699, respectively. High-risk patients were enriched in lncRNAs related with tumor invasion and immunity, and had higher levels of immune cell infiltration and immune checkpoint activation. Hot tumors and cold tumors were effectively distinguished by clusters 2 and 3 and cluster 1, respectively, which indicated that hot tumors are more susceptible to immunotherapy. Our study showed that inflammation-related LncRNAs are closely related with BLCA, and inflammation-related lncRNA can accurately predict patient prognosis and effectively differentiate between hot and cold tumors, thus improving individualized immunotherapy for BLCA patients. Therefore, this study provides an effective predictive model and a new therapeutic target for the prognosis and clinical treatment of BLCA, thus facilitating the development of individualized tumor therapy.

Xiong X ，Chen C ，Li X ，Yang J ，Zhang W ，Wang X ，Zhang H ，Peng M ，Li L ，Luo P ... -  《Frontiers in Oncology》

A novel cuproptosis-related lncRNA signature predicts the prognosis and immune landscape in bladder cancer.

Bladder cancer (BLCA) is one of the deadliest diseases, with over 550,000 new cases and 170,000 deaths globally every year. Cuproptosis is a copper-triggered programmed cell death and is associated with the prognosis and immune response of various cancers. Long non-coding RNA (lncRNA) could serve as a prognostic biomarker and is involved in the progression of BLCA. The gene expression profile of cuproptosis-related lncRNAs was analyzed by using data from The Cancer Genome Atlas. Cox regression analysis and least absolute shrinkage and selection operator analysis were performed to construct a cuproptosis-related lncRNA prognostic signature. The predictive performance of this signature was verified by ROC curves and a nomogram. We also explored the difference in immune-related activity, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE), and drug sensitivity between the high- and low-risk groups. We successfully constructed a cuproptosis-related lncRNA prognostic signature for BLCA including eight lncRNAs (RNF139-AS1, LINC00996, NR2F2-AS1, AL590428.1, SEC24B-AS1, AC006566.1, UBE2Q1-AS1, and AL021978.1). Multivariate Cox analysis suggested that age, clinical stage, and risk score were the independent risk factors for predicting prognosis of BLCA. Further analysis revealed that this signature not only had higher diagnostic efficiency compared to other clinical features but also had a good performance in predicting the 1-year, 3-year, and 5-year overall survival rate in BLCA. Notably, BLCA patients with a low risk score seemed to be associated with an inflamed tumor immune microenvironment and had a higher TMB level than those with a high risk score. In addition, patients with a high risk score had a higher TIDE score and a higher half maximal inhibitory concentration value of many therapeutic drugs than those with a low risk score. We identified a novel cuproptosis-related lncRNA signature that could predict the prognosis and immune landscape of BLCA.

Bai Y ，Zhang Q ，Liu F ，Quan J ... -  《Frontiers in Immunology》

Cuproptosis-related long non-coding RNAs model that effectively predicts prognosis in hepatocellular carcinoma.

Cuproptosis has recently been considered a novel form of programmed cell death. To date, long-chain non-coding RNAs (lncRNAs) crucial to the regulation of this process remain unelucidated. To identify lncRNAs linked to cuproptosis in order to estimate patients' prognoses for hepatocellular carcinoma (HCC). Using RNA sequence data from The Cancer Genome Atlas Live Hepatocellular Carcinoma (TCGA-LIHC), a co-expression network of cuproptosis-related genes and lncRNAs was constructed. For HCC prognosis, we developed a cuproptosis-related lncRNA signature (CupRLSig) using univariate Cox, lasso, and multivariate Cox regression analyses. Kaplan-Meier analysis was used to compare overall survival among high- and low-risk groups stratified by median CupRLSig risk score. Furthermore, comparisons of functional annotation, immune infiltration, somatic mutation, tumor mutation burden (TMB), and pharmacologic options were made between high- and low-risk groups. Three hundred and forty-three patients with complete follow-up data were recruited in the analysis. Pearson correlation analysis identified 157 cuproptosis-related lncRNAs related to 14 cuproptosis genes. Next, we divided the TCGA-LIHC sample into a training set and a validation set. In univariate Cox regression analysis, 27 LncRNAs with prognostic value were identified in the training set. After lasso regression, the multivariate Cox regression model determined the identified risk equation as follows: Risk score = (0.2659 × PICSAR expression) + (0.4374 × FOXD2-AS1 expression) + (-0.3467 × AP001065.1 expression). The CupRLSig high-risk group was associated with poor overall survival (hazard ratio = 1.162, 95%CI = 1.063-1.270; P < 0.001) after the patients were divided into two groups depending upon their median risk score. Model accuracy was further supported by receiver operating characteristic and principal component analysis as well as the validation set. The area under the curve of 0.741 was found to be a better predictor of HCC prognosis as compared to other clinicopathological variables. Mutation analysis revealed that high-risk combinations with high TMB carried worse prognoses (median survival of 30 mo vs 102 mo of low-risk combinations with low TMB group). The low-risk group had more activated natural killer cells (NK cells, P = 0.032 by Wilcoxon rank sum test) and fewer regulatory T cells (Tregs, P = 0.021) infiltration than the high-risk group. This finding could explain why the low-risk group has a better prognosis. Interestingly, when checkpoint gene expression (CD276, CTLA-4, and PDCD-1) and tumor immune dysfunction and rejection (TIDE) scores are considered, high-risk patients may respond better to immunotherapy. Finally, most drugs commonly used in preclinical and clinical systemic therapy for HCC, such as 5-fluorouracil, gemcitabine, paclitaxel, imatinib, sunitinib, rapamycin, and XL-184 (cabozantinib), were found to be more efficacious in the low-risk group; erlotinib, an exception, was more efficacious in the high-risk group. The lncRNA signature, CupRLSig, constructed in this study is valuable in prognostic estimation of HCC. Importantly, CupRLSig also predicts the level of immune infiltration and potential efficacy of tumor immunotherapy.

Huang EM ，Ma N ，Ma T ，Zhou JY ，Yang WS ，Liu CX ，Hou ZH ，Chen S ，Zong Z ，Zeng B ，Li YR ，Zhou TC ... -  《World Journal of Gastrointestinal Oncology》