Identification and validation of a twelve immune infiltration-related lncRNA prognostic signature for bladder cancer

Liu, Chen‐Qian; Xia, Qi‐Dong; Sun, Jian‐Xuan; Xu, Jin‐Zhou; Lu, Junlin; Liu, Zheng; Hu, Jia; Wang, Shaogang

doi:10.18632/aging.203889

Cited by 12 publications

(11 citation statements)

References 36 publications

(38 reference statements)

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“…To predict the OS and therapeutic responses in bladder cancer, Wu et al (2020) constructed a TP53-associated immune prognostic signature. Moreover, another study developed a prognostic signature for bladder cancer based on twelve immune infiltration-related lncRNAs ( Liu et al, 2022 ). In our study, we firstly identified a pyroptosis-related prognostic signature for bladder cancer and we could predict the prognosis of each patient by calculating the risk score.…”

Section: Discussionmentioning

confidence: 99%

Identification and verification of the pyroptosis-related prognostic signature and its associated regulatory axis in bladder cancer

Ding

Mao

2022

Front. Cell Dev. Biol.

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Background: Pyroptosis is an inflammatory form of cell death triggered by certain inflammasomes. Accumulating studies have shown the involvement of pyroptosis in the proliferation, invasion, and metastasis and prognosis of cancer. The prognostic value of pyroptosis-related genes (PRGs) and their association with immune infiltration in bladder cancer have not yet been elucidated.Methods: We performed a comprehensive analysis of the prognostic value and immune infiltrates of PRGs in bladder cancer using the TCGA dataset. qRT-PCR was also performed to verify our result.Results: Among 33 PRGs, 14 PRGs were upregulated or downregulated in bladder cancer tissue versus normal tissue. We also summarized copy number variations and somatic mutations of PRGs in bladder cancer. By using consensus clustering analysis of PRGs with prognostic significance, we divided the bladder cancer cohort into two subtypes significantly by different prognosis and immune infiltration. Using the LASSO Cox regression analysis, a prognostic signature including six PRGs was constructed for bladder cancer and the patients could be classified into a low- or high-risk group. Interestingly, this prognostic signature had a favorable performance for predicting the prognosis of bladder cancer patients. Moreover, further analysis demonstrated a significant difference in gender, tumor grade, clinical stage, TNM stage, immunoScore, and immune cell infiltration between the high- and low-risk groups in bladder cancer. We also identified an lncRNA SNHG14/miR-20a-5p/CASP8 regulatory axis in bladder cancer by constructing a ceRNA network.Conclusion: We identified a PRG-associated prognostic signature associated with the prognosis and immune infiltrates for bladder cancer and targeting pyroptosis may be an alternative approach for therapy. Further vivo and vitro experiments are necessary to verify these results.

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Section: Discussionmentioning

confidence: 99%

Identification and verification of the pyroptosis-related prognostic signature and its associated regulatory axis in bladder cancer

Ding

Mao

2022

Front. Cell Dev. Biol.

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“…The link between AC008750.1 and NK cells was studied by Sage et al, who revealed that the expression of AC008750.1 was elevated in activated NK cells, and antitumor capabilities of NK cells can be repressed when knocking down the expression of AC008750.1 [ 44 ]. In addition, AL591806.1 and LINC02207 are also potential immune-associated lncRNA signatures in BC and other cancer [ 45 , 46 ]. And LYPLAL1-AS1 has also been verified to engage in the adipogenic differentiation and senescence of human stem cell [ 47 , 48 ].…”

Section: Discussionmentioning

confidence: 99%

A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer

Tang

Zhang

et al. 2022

Hereditas

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Background Inflammation and long noncoding RNAs (lncRNAs) are gradually becoming important in the development of bladder cancer (BC). Nevertheless, the potential of inflammatory response-related lncRNAs (IRRlncRNAs) as a prognostic signature remains unexplored in BC. Methods The Cancer Genome Atlas (TCGA) provided RNA expression profiles and clinical information of BC samples, and GSEA Molecular Signatures database provided 1171 inflammation-related genes. IRRlncRNAs were identified using Pearson correlation analysis. After that, consensus clustering was performed to form molecular subtypes. After performing least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses, a risk model constructed based on the prognostic IRRlncRNAs was validated in an independent cohort. Kaplan–Meier (KM) analysis, univariate and multivariate Cox regression, clinical stratification analysis, and time-dependent receiver operating characteristic (ROC) curves were utilized to assess clinical effectiveness and accuracy of the risk model. In clusters and risk model, functional enrichment was investigated using GSEA and GSVA, and immune cell infiltration analysis was demonstrated by ESTIMATE and CIBERSORT analysis. Results A total of 174 prognostic IRRlncRNAs were confirmed, and 406 samples were divided into 2 clusters, with cluster 2 having a significantly inferior prognosis. Moreover, cluster 2 exhibited a higher ESTIMATE score, immune infiltration, and PD-L1 expression, with close relationships with the inflammatory response. Further, 12 IRRlncRNAs were identified and applied to construct the risk model and divide BC samples into low-risk and high-risk groups successfully. KM, ROC, and clinical stratification analysis demonstrated that the risk model performed well in predicting prognosis. The risk score was identified as an independently significant indicator, enriched in immune, cell cycle, and apoptosis-related pathways, and correlated with 9 immune cells. Conclusion We developed an inflammatory response-related subtypes and steady prognostic risk model based on 12 IRRlncRNAs, which was valuable for individual prognostic prediction and stratification and outfitted new insight into inflammatory response in BC.

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“…The immune microenvironment of tumor tissue was evaluated using the estimate R package, and we calculated the evaluation scores of immune and stromal cells. The pan-cancer immune cell infiltration files were downloaded from TIMER 2.0 and used to analyze the distribution of the explored immune cells on different clusters with the help of the limma and pheatmap R packages ( 19 , 20 ). The limma and ggpub R packages were used to perform the differential analysis of the immune microenvironment and immune checkpoints.…”

Section: Methodsmentioning

confidence: 99%

N7-methylguanosine-related lncRNAs: Distinction between hot and cold tumors and construction of predictive models in colon adenocarcinoma

Cheng

Wang

et al. 2022

Front. Oncol.

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Colon adenocarcinoma (COAD) is a prevalent malignant tumor that severely threatens human health across the globe. Immunotherapy is an essential need for patients with COAD. N7-methylguanosine (m7G) has been associated with human diseases, and non-coding RNAs (lncRNAs) regulate various tumorrelated biological processes. Nonetheless, the m7G-related lncRNAs involved in COAD regulation are limited. This study aims to construct the clustering features and prognostic model of m7G-related lncRNAs in COAD. First, The Cancer Genome Atlas (TCGA) database was used to identify m7G-related differentially expressed lncRNAs (DELs), based on which COAD cases could be classified into two subtypes. Subsequently, univariate Cox analysis was used to identify 9 prognostic m7G-related lncRNAs. Further, Five candidates were screened by LASSO-Cox regression to develop new models. The patients were divided into high-risk and low-risk groups based on the median risk score. Consequently, the Kaplan-Meier survival curve demonstrated a statistically significant overall survival (OS) between the high-and low-risk groups (P<0.001). Multivariate Cox regression analysis revealed that risk score is an independent prognostic factor in COAD patients (P<0.001). This confirms the clinical applicability of the model. Additionally, we performed Gene Set Enrichment Analysis (GSEA), which uncovered the biological and functional differences between risk subgroups, i.e., enrichment of immune-related diseases in the high-risk group and enrichment of metabolic-related pathways in the low-risk group. In a drug sensitivity analysis, high-risk group were more sensitive to some chemotherapeutics and targeted drugs than lowrisk group. Eventually, the stability of the model was confirmed by qRT-PCR. Our study unraveled the features of different immune states of COAD and established a prognostic model, including five m7G-related lncRNAs for COAD Frontiers in Oncology frontiersin.org 01

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Identification and validation of a twelve immune infiltration-related lncRNA prognostic signature for bladder cancer

Cited by 12 publications

References 36 publications

Identification and verification of the pyroptosis-related prognostic signature and its associated regulatory axis in bladder cancer

Identification and verification of the pyroptosis-related prognostic signature and its associated regulatory axis in bladder cancer

A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer

N7-methylguanosine-related lncRNAs: Distinction between hot and cold tumors and construction of predictive models in colon adenocarcinoma

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