Systematic identification of pathological mechanisms, prognostic biomarkers and therapeutic targets by integrating lncRNA expression variation in salivary gland mucoepidermoid carcinoma

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 10, 2025

Biological processes intricately intertwine with tumorigenesis, significantly influencing treatment outcomes and prognosis. However, the mechanisms fostering mucoepidermoid carcinoma (MEC) remain inadequately elucidated. This research utilizes expression profiles of lncRNAs from clinical MEC tissues matched normal glandular tissues, integrating public data to explore biological immune microenvironment characteristics tumorigenesis. Gene set enrichment analysis identified key pathways, a customized epithelial-mesenchymal transition (EMT) score elucidated relationship between pathological prognosis, while an signature revealed tumor characteristics. MECs exhibited significant in EMT pathway, genes such as Secretogranin II, tissue factor pathway inhibitor 2, periostin contributors process. High scores correlated upregulated response activity, indicating poor Single-sample gene unveiled tumors' infiltration signature, suggesting active antigen presentation positive for immunotherapy. Additionally, SLC2A1-AS1 CERS6-AS1 were potential mediators environment. study provides insights into tumorigenesis identifies therapeutic targets future research.

Language: Английский

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Comprehensive analysis of cuproptosis-related lncRNAs for prognostic significance and immune microenvironment characterization in hepatocellular carcinoma

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 13

Published: Jan. 4, 2023

Cuproptosis was characterized as a novel type of programmed cell death. Recently, however, the role cuproptosis-related long noncoding RNAs (CRLs) in tumors has not yet been studied. Identifying predictive CRL signature hepatocellular carcinoma (HCC) and investigating its putative molecular function were goals this work. Initially, Pearson’s test used to assess relationship between lncRNAs cuproptosis-associated genes obtained from HCC data The Cancer Genome Atlas (TCGA). By implementing differential expression univariate Cox analysis, 61 prognostic CRLs subsequent least absolute shrinkage selection operator (LASSO) regression analysis. A risk score model then constructed evaluate ability predict patients’ survival when combined with clinicopathological parameters HCC. five-lncRNA categorized patients into high- low-risk groups. group exhibited more sensitivity elesclomol than high-risk one. Surprisingly, distinct mitochondrial metabolism pathways connected cuproptosis pivotal immune-related observed two groups via gene set enrichment analysis (GSEA). Meanwhile, there substantial differences terms tumor-infiltrating immune cells (TIICs). Furthermore, positive shown checkpoints. Additionally, five confirmed our own samples lines RT-qPCR. Finally, vitro assays that WARS2-AS1 MKLN1-AS knockdown could sensitize elesclomol-induced cuproptosis. Overall, may prognosis an independent manner, give better understanding how work HCC, offer therapeutic reference for

Language: Английский

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Comprehensive analysis of anoikis-related long non-coding RNA immune infiltration in patients with bladder cancer and immunotherapy

Frontiers in Immunology, Journal Year: 2022, Volume and Issue: 13

Published: Nov. 25, 2022

Anoikis is a form of programmed cell death or death(PCD) for short. Studies suggest that anoikis involves in the decisive steps tumor progression and cancer metastasis spread, but what part it plays bladder remains unclear. We sought to screen anoikis-correlated long non-coding RNA (lncRNA) so we can build risk model understand its ability predict prognosis immune landscape.We screened seven anoikis-related lncRNAs (arlncRNAs) from The Cancer Genome Atlas (TCGA) designed model. It was validated through ROC curves clinicopathological correlation analysis, demonstrated be an independent factor prediction by uni- multi-COX regression. In meantime, Kyoto Encyclopedia Genes Genomes (KEGG) enrichment infiltration, half-maximal inhibitory concentration (IC50) were implemented with Moreover, divided patients into three subtypes consensus clustering analysis further study differences prognosis, infiltration level, checkpoints, drug susceptibility.We arlncRNAs, proved accuracy using curves. COX regression indicated might prognosis. KEGG showed enriched tumors immune-related pathways among people at high risk. Immune susceptibility results had higher have better immunotherapy efficacy high-risk groups. Of classified cluster 3 revealed positive 2 highest level sensitive most chemistries. This helpful us discover more precise patients.In nutshell, found arlncRNAs built identify different patients. Immune-related sensitivity researches demonstrate provide individual therapeutic schedule greater precision

Language: Английский

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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

Frontiers in Oncology, Journal Year: 2023, Volume and Issue: 13

Published: March 29, 2023

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

Language: Английский

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Explore Key Genes and Mechanisms Involved in Colon Cancer Progression Based on Bioinformatics Analysis

Applied Biochemistry and Biotechnology, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 31, 2024

Language: Английский

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Prognostic value of ferroptosis-related genes and long non-coding RNAs in colorectal cancer: a meta and bioinformatics analysis

Network Modeling Analysis in Health Informatics and Bioinformatics, Journal Year: 2025, Volume and Issue: 14(1)

Published: March 6, 2025

Language: Английский

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A novel signature of cuproptosis-related lncRNAs predicts prognosis in glioma: Evidence from bioinformatic analysis and experiments

Frontiers in Pharmacology, Journal Year: 2023, Volume and Issue: 14

Published: April 10, 2023

Background: Glioma patients often experience unfavorable outcomes and elevated mortality rates. Our study established a prognostic signature utilizing cuproptosis-associated long non-coding RNAs (CRLs) identified novel biomarkers therapeutic targets for glioma. Methods: The expression profiles related data of glioma were obtained from Cancer Genome Atlas, an accessible online database. We then constructed using CRLs evaluated the prognosis by means Kaplan-Meier survival curves receiver operating characteristic curves. A nomogram based on clinical features was employed to predict individual probability patients. Functional enrichment analysis conducted identify crucial CRL-related enriched biological pathways. role LEF1-AS1 in validated two cell lines (T98 U251). Results: developed model with 9 CRLs. Patients low-risk had considerably longer overall (OS). CRL may serve independently as indicator In addition, functional revealed significant multiple immunological Notable differences observed between risk groups terms immune infiltration, function, checkpoints. further four drugs their different IC50 values groups. Subsequently, we discovered molecular subtypes (cluster one cluster two), subtype exhibiting remarkably OS compared subtype. Finally, that inhibition curbed proliferation, migration, invasion cells. Conclusion: signatures confirmed reliable therapy response Inhibition effectively suppressed growth, gliomas; therefore, presents itself promising biomarker potential target

Language: Английский

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A novel inflammation‑associated prognostic signature for clear cell renal cell carcinoma

Oncology Letters, Journal Year: 2022, Volume and Issue: 24(3)

Published: July 12, 2022

Clear cell renal carcinoma (ccRCC) are typically situated in a complex inflammatory and immune microenvironment, which has been reported to contribute the unfavorable prognosis of patients with ccRCC. There would be beneficial clinical implications for elucidating roles its molecular characteristics microenvironment. This is because it facilitate development reliable biomarkers pre-stratification prior designation individualized treatment strategies. In present study, RNA-sequencing data from 607 were retrospectively analyzed elucidate profile molecules. Based on this, an prognostic signature (IPS) was developed further validated using ccRCC samples. Subsequently, associated mechanisms terms microenvironment pathways then investigated. proposed IPS found exhibit superior accuracy compared criterion good model prediction patient [area under receiver operating characteristic curve (AUC)=0.811] addition being independent factor risk stratification [hazard ratio: 11.73 (95% CI, 26.98-5.10); log-rank test, P<0.001]. Pathologically, cells identified as high-risk according their presented more malignant tumor structure, including voluminous eosinophilic cytoplasm, acinar/lamellar/tubular growth patterns atypic nuclei. High-risk also exhibited higher infiltration levels by four types cells, T regulatory but lower mast cells. Pathways immune-inflammation interaction, IL-17 pathway, upregulated IPS-identified Furthermore, combining factors, integrated index increasing risk-stratification (AUC=0.911). conclusion, involved ccRCC-inflammation coupled potential, systematically elucidated study. may have important furthering understanding into underlying this can turn exploited identifying designing strategy.

Language: Английский

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In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma

Current Oncology, Journal Year: 2022, Volume and Issue: 29(9), P. 6573 - 6593

Published: Sept. 15, 2022

Background: Colon adenocarcinoma (COAD) is the most common subtype of colon cancer, and cuproptosis a recently newly defined form cell death that plays an important role in development several malignant cancers. However, studies cuproptosis-related lncRNAs (CRLs) involved regulating are limited. The purpose this study to develop new prognostic CRLs signature explore its underlying biological mechanism. Methods: In study, we downloaded RNA-seq profiles, clinical data tumor mutational burden (TMB) from TCGA database, identified cuproptosis-associated using univariate Cox, lasso regression analysis multivariate Cox analysis, constructed model with risk score based on these lncRNAs. COAD patients were divided into high- low-risk subgroups score. was also used test whether they independent factors. accuracy further validated by receiver operating characteristic curve (ROC), C-index Nomogram. addition, lncRNA/miRNA/mRNA competing endogenous RNA (ceRNA) network protein–protein interaction (PPI) weighted gene co-expression (WGCNA). Results: We 15 validation results showed (HR = 1.003, 95% CI 1.001–1.004; p < 0.001) could serve as factor accurate credible predictive power. had highest AUC (0.793) among various factors such score, stage, gender age, indicating predict patient survival better than other characteristics. Meanwhile, possible mechanisms explored ceRNA PPI WGCNA. Conclusion: has reliable power effectively outcomes patients.

Language: Английский

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Development of a necroptosis-related gene signature and the immune landscape in ovarian cancer

Journal of Ovarian Research, Journal Year: 2023, Volume and Issue: 16(1)

Published: April 25, 2023

Necroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role necroptosis in ovarian cancer (OC) remains unclear. The present study investigated prognostic value necroptosis-related genes (NRGs) and immune landscape OC. gene expression profiling clinical information were downloaded TCGA GTEx databases. Differentially expressed NRGs (DE-NRGs) between OC normal tissueswere identified. regression analyses conducted to screen construct predictive risk model. Patients then divided into high- low-risk groups, GO KEGG performed explore bioinformatics functions two groups. Subsequently, level status correlations assessed through ESTIMATE CIBERSORT algorithms. tumor mutation burden (TMB) drug sensitivity also analyzed based on two-NRG signature Totally 42 DE-NRGs identified screened out (MAPK10 STAT4) with values for overall survival. ROC curve showed better ability five-year OS using score. Immune-related significantly enriched group. Macrophages M1, T cells CD4 memory activated, CD8, regulatory infiltration associated lower microenvironment score was demonstrated high-risk TMB group prognosis, TIDE suggested checkpoint inhibitor response Besides, cisplatin paclitaxel found be more sensitive MAPK10 STAT4 can important prognosis factors OC, two-gene performs well predicting survival outcomes. Our provided ways estimation potential treatment strategy.

Language: Английский

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