The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment.
Ontology highlight
ABSTRACT:
SUBMITTER: Wang G
PROVIDER: S-EPMC8647402 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundAlternative splicing (AS) is a gene regulatory mechanism that drives protein diversity. Dysregulation of AS is thought to play an essential role in cancer initiation and development. This study aimed to construct a prognostic signature based on AS and explore the role in the tumor immune microenvironment (TIME) in lung adenocarcinoma.MethodsWe analyzed transcriptome profiling and clinical lung adenocarcinoma data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq. Prognosis-related AS events were analyzed by univariate Cox regression analysis. Gene set enrichment analyses (GSEA) were performed for functional annotation. Prognostic signatures were identified and validated using univariate and multivariate Cox regression, LASSO regression, Kaplan-Meier survival analyses, and proportional hazards model. The context of TIME in lung adenocarcinoma was also analyzed. Gene and protein expression data of Cyclin-Dependent Kinase Inhibitor 2A (CDKN2A) were obtained from ONCOMINE and Human Protein Atlas. Splicing factor (SF) regulatory networks were visualized.ResultsA total of 19,054 survival-related AS events in lung adenocarcinoma were screened in 1,323 genes. Exon skip (ES) and mutually exclusive exons (ME) exhibited the most and fewest AS events, respectively. Based on AS subtypes, eight AS prognostic signatures were constructed. Patients with high-risk scores were associated with poor overall survival. A nomogram with good validity in prognostic prediction was generated. AUCs of risk scores at 1, 2, and 3 years were 0.775, 0.736, and 0.759, respectively. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. Low-risk patients had a higher StromalScore, ImmuneScore, and ESTIMATEScore. AS-based risk score signature was positively associated with CD8+ T cells. CDKN2A was also found to be a prognostic factor in lung adenocarcinoma. Finally, potential functions of SFs were determined by regulatory networks.ConclusionTaken together, our findings show a clear association between AS and immune cell infiltration events and patient outcome, which could provide a basis for the identification of novel markers and therapeutic targets for lung adenocarcinoma. SF networks provide information of regulatory mechanisms.
| S-EPMC8728792 | biostudies-literature
Project description:PurposePancreatic adenocarcinoma (PAAD) is characterized by low antitumour immune cell infiltration in an immunosuppressive microenvironment. This study aimed to systematically explore the impact on prognostic alternative splicing events (ASs) of tumour immune microenvironment (TIME) in PAAD.MethodsThe ESTIMATE algorithm was implemented to compute the stromal/immune-related scores of each PAAD patient, followed by Kaplan-Meier (KM) survival analysis of patients with different scores grouped by X-tile software. TIME-related differentially expressed ASs (DEASs) were determined and evaluated through functional annotation analysis. In addition, Cox analyses were implemented to construct a TIME-related signature and an AS clinical nomogram. Moreover, comprehensive analyses, including gene set enrichment analysis (GSEA), immune infiltration, immune checkpoint gene expression, and tumour mutation were performed between the two risk groups to understand the potential mechanisms. Finally, Cytoscape was implemented to illuminate the AS-splicing factor (SF) regulatory network.ResultsA total of 437 TIME-related DEASs significantly related to PAAD tumorigenesis and the formation of the TIME were identified. Additionally, a robust TIME-related prognostic signature based on seven DEASs was generated, and an AS clinical nomogram combining the signature and four clinical predictors also exhibited prominent discrimination by ROC (0.762 ~ 0.804) and calibration curves. More importantly, the fractions of CD8 T cells, regulatory T cells and activated memory CD4 T cells were lower, and the expression of four immune checkpoints-PD-L1, CD47, CD276, and PVR-was obviously higher in high-risk patients. Finally, functional analysis and tumour mutations revealed that aberrant immune signatures and activated carcinogenic pathways in high-risk patients may be the cause of the poor prognosis.ConclusionWe extracted a list of DEASs associated with the TIME through the ESTIMATE algorithm and constructed a prognostic signature on the basis of seven DEASs to predict the prognosis of PAAD patients, which may guide advanced decision-making for personalized precision intervention.
| S-EPMC8590242 | biostudies-literature
Project description:BACKGROUND The exact mechanisms of lung adenocarcinoma (LUAD) etiology and pathogenesis remain unclear. MATERIAL AND METHODS In this study, we evaluated alternative splicing (AS) events in LUAD. We separately analyzed LUAD data from The Cancer Genome Atlas (TCGA) database and AS-related feature lists from SpliceSeq to develop risk models for AS events and further validated risk models for AS events. The association between immune-related features and the risk model of AS events was evaluated. RESULTS We found that exon skip (ES) and mutually exclusive exons (ME) exhibited the most and least AS events, respectively. The risk score and stage of LUAD patients were strongly associated with prognosis and were independent influences on the prognosis of LUAD. The pathological stage (stage, T, N) and risk model were incorporated to construct a column line graph with better predictive ability. Risk models were associated with tumor microenvironment, and higher risk score values were associated with higher M2 macrophage content and lower M0 macrophage and helper T lymphocyte content. The correlation between core genes and immunity was further assessed by analyzing differentially-expressed genes between risk models. These results suggest an association between the level of risk for AS events and the density of immune cell infiltration. CONCLUSIONS Our findings suggest a clear association between AS risk model and patient prognosis, and was performed to confirm the biological relationship between AS and immunity.
| S-EPMC8656114 | biostudies-literature
Project description:Alternative splicing (AS), contributing to vast protein diversity from a rather limited number of genes in eukaryotic transcripts, has emerged as an important signature for tumor initiation and progression. However, a systematic understanding of its functional impact and relevance to gastric cancer (GC) tumorigenesis is lacking. Differentially expressed AS (DEAS) was verified among GC-associated AS events based on RNA-seq profiles from the TCGA database. Functional enrichment analysis, unsupervised clustering analysis and prognostic models were used to infer the potential roles of DEAS events and their molecular, clinical and immune features. In total, 12,225 AS events were detected from 5,199 genes, among which 314 AS events were identified as DEAS events in GC. The parental genes of the DEAS events were significantly enriched in the regulation of GC-related processes. The splicing correlation network suggested a significant relationship between DEAS events and splicing factors (SFs). Three clusters of DEAS events were identified to be different in prognosis, cancer-specific signatures and immune features between distinct clusters. Univariate and multivariate analyses regarded 3 DEAS events as independent prognostic indicators. Profiling of the AS landscape in GC elucidated the functional roles of the splicing network in GC and might serve as a novel prognostic indicator and therapeutic target.
| S-EPMC7906195 | biostudies-literature
Project description:BackgroundAlternative splicing (AS), e.g. the tandem alternative polyadenylation (TAPA), has emerged as major post-transcriptional modification events in human disease. However, the roles of the AS and TAPA in early-onset gastric cancer (EOGC) have not been revealed.MethodsThe global AS profiles of 80 EOGC patients were analyzed. The EOGC-specific AS events (ESASs) were identified in both the EOGC and adjacent non-tumor tissues. The functional enrichment analysis, Splicing network, Alternative Polyadenylation (APA) core factor network, and cell abundancy analysis were performed. Furthermore, the landscapes of the AS events in the varied subtypes of the EOGC patients were evaluated.ResultsOverall, 66,075 AS events and 267 ESASs were identified in the EOGC. Furthermore, 4809 genes and 6152 gene isoforms were found to be aberrantly expressed in the EOGC. The Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analyses showed that the significant pathway alterations might exist in these AS events, genes, and gene isoforms. Moreover, the Protein-protein interaction (PPI) network analysis revealed that the UBC, NEK2, EPHB2, and DCTN1 genes were the hub genes in the AS events in the EOGC. The immune cell infiltration analysis indicated a correlation between the AS events and the cancer immune microenvironment. The distribution of the AS events in varied EOGC subtypes, protein phosphorylation and glycosylation was uneven.ConclusionThe study highlighted the vital roles of the AS in the EOGC, including modulating the specific protein modification and reshaping the cancer immune microenvironment, and yielded new insights into the diagnosis of the EOGC as well as cancer treatment.
| S-EPMC8217769 | biostudies-literature
Project description:BackgroundRecent studies identified correlations between splicing factors (SFs) and tumor progression and therapy. However, the potential roles of SFs in immune regulation and the tumor microenvironment (TME) remain unknown.MethodsWe used UpSet plots to screen for prognostic-related alternative splicing (AS) events. We evaluated SF patterns in specific immune landscapes. Single sample gene set enrichment analysis (ssGSEA) algorithms were used to quantify relative infiltration levels in immune cell subsets. Principal component analysis (PCA) algorithm-based SFscore were used to evaluate SF patterns in individual tumors with an immune response.ResultsFrom prognosis-related AS events, 16 prognosis-related SFs were selected to construct three SF patterns. Further TME analyses showed these patterns were highly consistent with immune-inflamed, immune-excluded, and immune-desert landscapes. Based on SFscore constructed using differentially expressed genes (DEGs) between SF patterns, patients were classified into two immune-subtypes associated with differential pharmacogenomic landscapes and cell features. A low SFscore was associated with high immune cell infiltration, high tumor mutation burden (TMB), and elevated expression of immune check points (ICPs), indicating a better immune response.ConclusionsSFs are significantly associated with TME remodeling. Evaluating different SF patterns enhances our understanding of the TME and improves effective immunotherapy strategies.
| S-EPMC9467413 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, and its 5-year survival rate is less than 20%, despite various treatments being available. Increasing evidence indicates that alternative splicing (AS) plays a nonnegligible role in the formation and development of the tumor microenvironment (TME). However, the comprehensive analysis of the impact on prognostic AS events on immune-related perspectives in HCC is lacking but urgently needed.MethodsThe transcriptional data and clinical information of HCC patients were downloaded from TCGA (The Cancer Genome Atlas) database for calculating immune and stromal scores by ESTIMATE algorithm. We then divided patients into high/low score groups and explored their prognostic significance using Kaplan-Meier curves. Based on stromal and immune scores, differentially expressed AS events (DEASs) were screened and evaluated with functional enrichment analysis. Additionally, a risk score model was established by applying univariate and multivariate Cox regression analyses. Finally, gene set variation analysis (GSVA) was adopted to explore differences in biological behaviors between the high- and low-risk subgroups.ResultsA total of 370 HCC patients with complete and qualified corresponding data were included in the subsequent analysis. According to the results of ESTIMATE analysis, we observed that the high immune/stromal score group had a longer survival probability, which was significantly correlated with prognosis in HCC patients. In addition, 467 stromal/immune score-related DEASs were identified, and enrichment analysis revealed that DEASs were significantly enriched in pathways related to HCC tumorigenesis and the immune microenvironment. More importantly, the final prognostic signature containing 16 DEASs showed powerful predictive ability. Finally, GSVA demonstrated that activation of carcinogenic pathways and immune-related pathways in the high-risk group may lead to poor prognosis.ConclusionsCollectively, these outcomes revealed prognostic AS events related to carcinogenesis and the immune microenvironment, which may yield new directions for HCC immunotherapy.
| S-EPMC8034091 | biostudies-literature
Project description:Alternative splicing (AS) has emerged as a key event in tumor development and microenvironment formation. However, comprehensive analysis of AS and its clinical significance in head and neck squamous cell carcinoma (HNSC) is urgently required. Methods: Genome-wide profiling of AS events using RNA-Seq data from The Cancer Genome Atlas (TCGA) program was performed in a cohort of 464 patients with HNSC. Cancer-associated AS events (CASEs) were identified between paired HNSC and adjacent normal tissues and evaluated in functional enrichment analysis. Splicing networks and prognostic models were constructed using bioinformatics tools. Unsupervised clustering of the CASEs identified was conducted and associations with clinical, molecular and immune features were analyzed. Results: We detected a total of 32,309 AS events and identified 473 CASEs in HNSC; among these, 91 were validated in an independent cohort (n = 15). Functional protein domains were frequently altered, especially by CASEs affecting cancer drivers, such as PCSK5. CASE parent genes were significantly enriched in pathways related to HNSC and the tumor immune microenvironment, such as the viral carcinogenesis (FDR < 0.001), Human Papillomavirus infection (FDR < 0.001), chemokine (FDR < 0.001) and T cell receptor (FDR?<?0.001) signaling pathways. CASEs enriched in immune-related pathways were closely associated with immune cell infiltration and cytolytic activity. AS regulatory networks suggested a significant association between splicing factor (SF) expression and CASEs and might be regulated by SF methylation. Eighteen CASEs were identified as independent prognostic factors for overall and disease-free survival. Unsupervised clustering analysis revealed distinct correlations between AS-based clusters and prognosis, molecular characteristics and immune features. Immunogenic features and immune subgroups cooperatively depict the immune features of AS-based clusters. Conclusion: This comprehensive genome-wide analysis of the AS landscape in HNSC revealed novel AS events related to carcinogenesis and immune microenvironment, with implications for prognosis and therapeutic responses.
| S-EPMC6831462 | biostudies-literature
Project description:Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. Transcriptome data and Percent Spliced In (PSI) values of ovarian cancer patients were downloaded from TCGA database and TCGA SpliceSeq. Totally we identified 1472 AS events that were associated with survival of ovarian serous cystadenocarcinoma (OC) and exon skipping (ES) was the most important type. Univariate and multivariate Cox regression analysis were performed to identify survival-associated AS events and developed the prognostic model based on 11-AS events. The immune cells and different response to cytotoxic T lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) blockers in low-risk and high-risk group of OC patients were analyzed. Ten kinds of immune cells were found up-regulated in low-risk group. Activated B cell, natural killer T cell, natural killer cell and regulatory T cell were associated with survival of OC. The patients in low-risk group had good response to CTLA-4 and PD-1 blockers treatment. Moreover, a regulatory network was established according to the correlation between AS events and splicing factors (SFs). The present study provided valuable insights into the underlying mechanisms of OC. AS events that were correlated with the immune system might be potential therapeutic targets.
| S-EPMC8770494 | biostudies-literature
Project description:ObjectiveAlternative splicing (AS) is the mechanism by which a few genes encode numerous proteins, and it redefines the concept of gene expression regulation. Recent studies showed that dysregulation of AS was an important cause of tumorigenesis and microenvironment formation. Therefore, we performed a systematic analysis to examine the role of AS in breast cancer (Breast Cancer, BrCa) progression.MethodsThe present study included 993 BrCa patients from The Cancer Genome Atlas (TCGA) database in the genome-wide analysis of AS events. We used differential and prognostic analyses and found differentially expressed alternative splicing (DEAS) events and independent prognostic factors related to patients' overall survival (OS) and disease-free survival (DFS). We divided the patients into two groups based on these AS events and analyzed their clinical features, molecular subtyping and immune characteristics. We also constructed a splicing factor (SF) regulation network for key AS events and verified the existence of AS events in tissue samples using real-time quantitative PCR.ResultsA total of 678 AS events were identified as differentially expressed, of which 13 and 10 AS events were independent prognostic factors of patients' OS and DFS, respectively. Unsupervised clustering analysis based on these prognostic factors indicated that the Cluster 1 group had a better prognosis and more immune cell infiltration. SFs were significantly related to the expression of AS events, and AA-RPS21 was significantly upregulated in tumors.ConclusionAlternative splicing expands the mechanism of breast cancer progression from a new perspective. Notably, alternative splicing may affect the patient's prognosis by affecting the infiltration of immune cells. Our research provides important guidance for subsequent studies of AS in breast cancer.
| S-EPMC8236959 | biostudies-literature