In this study, we analyzed the prediction accuracy of an autophagy-related long non-coding RNA (lncRNA) prognostic signature using bladder urothelial carcinoma (BLCA) patient data from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses showed significant correlations between five autophagy-related lncRNAs, LINC02178, AC108449.2, Z83843.1, FAM13A-AS1 and USP30−AS1, and overall survival (OS) among BCLA patients. The risk scores based on the autophagy-related lncRNA prognostic signature accurately distinguished high- and low-risk BCLA patients that were stratified according to age; gender; grade; and AJCC, T, and N stages. The autophagy-related lncRNA signature was an independent prognostic predictor with an AUC value of 0.710. The clinical nomogram with the autophagy-related lncRNA prognostic signature showed a high concordance index of 0.73 and accurately predicted 1-, 3-, and 5-year survival times among BCLA patients in the high- and low-risk groups. The lncRNA-mRNA co-expression network contained 77 lncRNA-mRNA links among 5 lncRNAs and 49 related mRNAs. Gene set enrichment analysis showed that cancer- and autophagy-related pathways were significantly enriched in the high-risk group, and immunoregulatory pathways were enriched in the low-risk group. These findings demonstrate that an autophagy-related lncRNA signature accurately predicts the prognosis of BCLA patients.

Kidney renal clear cell carcinoma (KIRC) is the predominant pathological subtype of renal cell carcinoma (RCC) in adults. Long non-coding RNAs (lncRNAs) are an important class of gene expression regulators and serve fundamental roles in immune regulation. The intent of this study is to develop a novel immune-related lncRNA signature to accurately predict the prognosis for KIRC patients. Here, we performed genome-wide comparative analysis of lncRNA expression profiles in 537 KIRC patients from The Cancer Genome Atlas (TCGA) database. Cox regression model-identified immune-related lncRNAs were extracted for constructing a novel five immune-related lncRNA signature (AC008105.3, LINC02084, AC243960.1, AC093278.2, and AC108449.2) with the ability to predict the prognosis of KIRC patients. Univariate and multivariate Cox regression analyses demonstrated that the signature could act as an independent prognostic predictor for overall survival (OS). With the further investigation on different clinicopathological parameters, we found that the signature could divide KIRC samples into high-risk groups with shorter OS and low-risk groups with longer OS in different subgroups. Principal component analysis suggested that the five immune-related lncRNA signature drew a clear distinction between high-and low-risk groups based on the immune-related lncRNAs. The different immune status between the two groups was observed in gene set enrichment analysis and the ESTIMATE algorithm. Except for AC093278.2, the expressions of the other four lncRNAs expression were significantly upregulated in tumor tissues. In summary, the identified immune-lncRNA signature had important clinical implications in prognosis prediction and could be exploited as underlying immune therapeutic targets for KIRC patients.

BackgroundPrevious studies have demonstrated that glial cells play an important role in the generation and maintenance of neuropathic pain. Activated glial cells produce numerous mediators such as proinflammatory cytokines that facilitate neuronal activity and synaptic plasticity. Similarly, bladder pain syndrome/interstitial cystitis shares many characteristics of neuropathic pain. However, related report on the involvement of spinal glia in bladder pain syndrome/interstitial cystitis-associated pathological pain and the underlying mechanisms are still lacking. The present study investigated spinal glial activation and underlying molecular mechanisms in a rat model of bladder pain syndrome/interstitial cystitis.ResultsA rat model of bladder pain syndrome/interstitial cystitis was established via systemic injection with cyclophosphamide. Mechanical allodynia was tested with von Frey monofilaments and up-down method. Moreover, Western blots and double immunofluorescence were used to detect the expression and location of glial fibrillary acidic protein, OX42/Iba1, P-P38, NeuN, interleukin (IL)-1β, phosphorylation of N-methyl-D-aspartate receptor 1 (P-NR1), and IL-1 receptor I (IL-1RI) in the L6-S1 spinal cord. We found that glial fibrillary acidic protein rather than OX42/Iba1 or P-P38 was significantly increased in the spinal cord of cyclophosphamide-induced cystitis. L-alpha-aminoadipate but not minocycline markedly attenuated the allodynia. Furthermore, we found that spinal IL-1β was dramatically increased in cyclophosphamide-induced cystitis, and activated astrocytes were the only source of IL-1β release, which contributed to allodynia in cystitis rats. Besides, spinal P-NR1 was statistically increased in cyclophosphamide-induced cystitis and only localized in IL-1RI positive neurons in spinal dorsal horn. Additionally, NR antagonist significantly attenuated the cystitis-induced pain. Interestingly, the time course of the P-NR1 expression paralleled to that of IL-1β or glial fibrillary acidic protein.ConclusionsOur results demonstrated that astrocytic activation but not microglial activation contributed to the allodynia in cyclophosphamide-induced cystitis and IL-1β released from astrocytes might bind to its endogenous receptor on the neurons inducing the phosphorylation of NR1 subunit, leading to sensory neuronal hyperexcitability and pathological pain.

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Background Clear cell renal cell carcinoma (ccRCC) is the most common and lethal renal cell carcinoma (RCC) histological subtype. Ferroptosis is a newly discovered programmed cell death and serves an essential role in tumor occurrence and development. The purpose of this study is to analyze ferroptosis-related gene (FRG) expression profiles and to construct a multi-gene signature for predicting the prognosis of ccRCC patients. Methods RNA-sequencing data and clinicopathological data of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed FRGs between ccRCC and normal tissues were identified using ‘limma’ package in R. GO and KEGG enrichment analyses were conducted to elucidate the biological functions and pathways of differentially expressed FRGs. Consensus clustering was used to investigate the relationship between the expression of FRGs and clinical phenotypes. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to screen genes related to prognosis and construct the optimal signature. Then, a nomogram was established to predict individual survival probability by combining clinical features and prognostic signature. Results A total of 19 differentially expressed FRGs were identified. Consensus clustering identified two clusters of ccRCC patients with distinguished prognostic. Functional analysis revealed that metabolism-related pathways were enriched, especially lipid metabolism. A 7-gene ferroptosis-related prognostic signature was constructed to stratify the TCGA training cohort into high- and low-risk groups where the prognosis was significantly worse in the high-risk group. The signature was identified as an independent prognostic indicator for ccRCC. These findings were validated in the testing cohort, the entire cohort, and the International Cancer Genome Consortium (ICGC) cohort. We further demonstrated that the signature-based risk score was highly associated with the ccRCC progression. Further stratified survival analysis showed that the high-risk group had a significantly lower overall survival (OS) rate than those in the low-risk group. Moreover, we constructed a nomogram that had a strong ability to forecast the OS of the ccRCC patients. Conclusions We constructed a ferroptosis-related prognostic signature, which might provide a reliable prognosis assessment tool for the clinician to guide clinical decision-making and outcomes research.