Survival-related Alternative Splicing Events Research Articles

The comprehensive and systematic identification of BLCA-specific SF-regulated, survival-related AS events

Bladder urothelial carcinoma (BLCA) is a complex disease with high morbidity and mortality. Changes in alternative splicing (AS) and splicing factor (SF) can affect gene expression, thus playing an essential role in tumorigenesis. This study downloaded 412 patients' clinical information and 433 samples of transcriptome profiling data from TCGA. And we collected 48 AS signatures from SpliceSeq. LASSO and Cox analyses were used for identifying survival-related AS events in BLCA. Finally, 1,645 OS-related AS events in 1,129 genes were validated by Kaplan-Meier (KM) survival analysis, ROC analysis, risk curve analysis, and independent prognostic analysis. Finally, our survey provides an AS-SF regulation network consisting of five SFs and 46 AS events. In the end, we profiled genes that AS occurred in pan-cancer and five SFs’ expression in tumor and normal samples in BLCA. We selected CLIP-seq data for validation the interaction regulated by RBP. Our study paves the way for potential therapeutic targets of BLCA.

Identification and Validation of Novel Immune-Related Alternative Splicing Signatures as a Prognostic Model for Colon Cancer.

BackgroundIndividual immune-related alternative splicing (AS) events have been found to be significant in immune regulation and cancer prognosis. However, a comprehensive analysis of AS events in cancer cells based on immune-related genes (IRGs) has not been performed, and its clinical value is unknown.MethodsColon cancer cases with AS data were obtained from TCGA, and then, we identified overall survival-related AS events (OS-ASEs) based on IRGs by univariate analyses. Using Lasso regression, multivariate Cox regression, Kaplan–Meier analysis and nomograms, we constructed an AS risk model based on the calculated risk score. Furthermore, associations of the risk score with clinical and immune features were confirmed through the Wilcoxon rank sum test, association analysis, etc. Finally, by qRT–PCR, cell coculture and CCK-8 analyses, we validated the significance of OS-ASEs in colon cancer cell lines and clinical samples.ResultsA total of 3,119 immune-related AS events and 183 OS-ASEs were identified, and 9 OS-ASEs were ultimately used to construct a comprehensive risk model for colon cancer patients. Low-risk patients had better OS and DFS rates than high risk patients. Furthermore, a high risk score corresponded to high numbers of multiple tumour-infiltrating immune cells and high expression of HLA-D region genes and immune checkpoint genes. Notably, we identified for the first time that anti-PD-L1 or anti-CTLA-4 antibodies may decrease the OS of specific colon cancer patients in the low-risk group. Additionally, the in vitro experiment validated that CD46-9652-ES and PSMC5-43011-ES are positively correlated with the infiltration of immune cells and promote the growth of colon cancer cells. CD46-9652-ES can contribute to T cell-mediated tumour cell killing. PSMC5-43011-ES was observed to induce M2 polarization of macrophages.ConclusionsThis study identified and validated immune-related prognostic AS signatures that can be used as a novel AS prognostic model and provide a novel understanding of the relationship between the immune microenvironment and clinical outcomes.

Identification of prognostic alternative splicing signature in gastric cancer

BackgroundAberrant alternative splicing (AS) events could be viewed as prognostic indicators in a large number of malignancies. This study aims to identify prognostic AS events, illuminate the function of the splicing variants biomarkers and provide reliable evidence for formulating public health strategies for gastric cancer (GC) surveillance.MethodsRNA-Seq data, clinical information and percent spliced in (PSI) values were available in The cancer genome atlas (TCGA) and TCGA SpliceSeq data portal. A three-step regression method was conducted to identify prognostic AS events and construct multi-AS-based signatures. The associations between prognostic AS events and splicing factors were also investigated.ResultsWe identified a total of 1,318 survival-related AS events in GC, parent genes of which were implicated in numerous oncogenic pathways. The final prognostic signatures stratified by seven types of AS events or not stratified performed well in risk prediction for GC patients. Moreover, five signatures based on AA, AD, AT, ES and RI events function as independent prognostic indicators after multivariate adjustment of other clinical variables. Splicing network also showed marked correlation between the expression of splicing factors and PSI value of AS events in GC patients.ConclusionOur findings provide a landscape of AS events and regulatory network in GC, indicating that AS events might serve as prognostic biomarkers and therapeutic targets for GC.

Alternative splicing events in tumor immune infiltration in renal clear cell carcinomas.

Alternative splicing (AS) is a gene regulatory mechanism that drives protein diversity and dysregulation of AS plays a significant role in tumorigenesis. This study aimed to develop a prognostic signature based on AS and elucidate the role in tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC). The 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 analysis, and proportional hazards model. The context of TIME in ccRCC was also analyzed. Gene and protein expression data of C4orf19 were obtained from ONCOMINE website and Human Protein Altas. Splicing factors (SFs) regulatory networks were visualized. 4431 survival-related AS events in ccRCC were screened. Based on splicing subtypes, eight AS prognostic signatures were constructed. A nomogram with good prognostic prediction was generated. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. C4orf19 was the only gene whose expression levels were downregulated among the prognostic AS-related genes, which is considered as a promising prognostic factor in ccRCC. Potential functions of SFs were determined by splicing regulatory networks. In our study, AS patterns of novel indicators for prognostic prediction of ccRCC were explored. The AS-SF networks provide information of regulatory mechanisms. Players of AS events related to TIME were investigated, which contribute to prognosis monitoring of ccRCC.

A Novel Nomogram Combining Alternative Splicing Events and Clinical Factors for Prognosis Prediction in Head and Neck Squamous Cell Carcinoma.

Due to limitations of sensitive biomarkers, the clinical prognosis of patients with head and neck squamous cell carcinoma (HNSCC) remains poor. Alternative splicing (AS) is the basis of both transcriptome and proteome richness, so more and more evidence indicates an important relationship between AS and tumor progression. The aim of this study was to offer a comprehensive analysis on AS events and then investigate its potentials as a new biomarker for patients with squamous cell carcinoma of the head and neck. In this study, univariate assays were conducted to examine the prognosis-associated AS events, and we screened 4068 survival-related AS events in 2573 genes. Then, the AS events related to survival were further determined and analyzed using LASSO regression and multivariate assays, and an eleven-AS signature was developed. Kaplan–Meier assays indicated patients with high-risk scores exhibited a shorter OS than those with low-risk scores. Multivariate assays further demonstrated that the signature's risk score was independent of HNSCC survivals. Meanwhile, we analyzed the clinical association of AS-based prognostic signature in HNSCC patients and observed that tumor specimens with advanced stages and grades exhibited a high risk score. In addition, the results of survival nomogram revealed that predicted outcomes and actual outcomes were highly consistent. Overall, our group showed an eleven-AS signature of HNSCC, which could be regarded as a separate prognostic factor.

Immunological significance of survival-related alternative splicing in uveal melanoma.

Uveal melanoma (UM) is a highly malignant intraocular tumor. The imbalance of alternative splicing (AS) is a landmark of tumor initiation and progression. However, there are few studies of AS in UM. Thus, this study aimed to identify a new AS-based prognostic signature and reveal its relationship with tumor-infiltrating immune cells. Univariable Cox regression analysis identified survival-related AS events. The prognostic signature was constructed using the univariable and multivariable Cox regression analyses. Kaplan-Meier survival analysis, the proportional hazard model, and receiver operating characteristic curves verified its prognostic value. Single-sample gene set enrichment analysis was used to analyze immune cell enrichment. The correlation of the risk score with tumor-infiltrating immune cells and immune checkpoint blockade (ICB) genes was examined. We screened 2886 survival-related AS events, of which five were selected to build a prognostic predictor. The risk score was positively relevant with ICB key targets (HAVCR2, IDO1, and PDCD1) and the infiltration of T cells, MDSC, and activated B cells. We provided novel and effective indices, including a risk score and clinical nomogram, for prognostic prediction in UM and discussed the potential relationship between survival-related AS events and immune cell infiltration, which is crucial for developing immune-targeted therapy to improve prognosis.

Systemic characterization of alternative splicing related to prognosis, immune infiltration, and drug sensitivity analysis in ovarian cancer.

BackgroundAlternative splicing (AS) plays an essential role in tumorigenesis and progression. This study intended to construct an innovative prognostic model based on AS events to gain more precise survival prediction and search for potential therapeutic targets in ovarian cancer.MethodsSeven types of AS events in ovarian serous cystadenocarcinoma (OV) patients with RNA-seq were obtained using The Cancer Genome Atlas (TCGA) SpliceSeq tool and database. Cox and Kaplan-Meier curve analyses were employed to establish the prognostic models. Relying on drug sensitivity data from the CellMiner database, Genomics of Drug Sensitivity (GDS) was adopted to estimate the platinum-sensitive analysis. Furthermore, a prognostic splicing factor (SF)-AS network was constructed using Cytoscape. Finally, in order to explore the influence of the tumor microenvironment on the prognosis of OV patients, we first combined a similar network fusion and consensus clustering (SNF-CC) algorithm to identify three OV subtypes based on survival-related AS events and then utilized single-sample Gene Set Enrichment Analysis (ssGSEA) method to perform immune cell infiltration analysis.ResultsA total of 48,049 AS events and 21,841 related genes were selected from 318 OV samples, and 2,206 AS events associated with disease-free survival (DFS) were identified. Multivariate Cox and Kaplan-Meier curve analyses were then employed to establish the prognostic models. Receiver operating characteristic (ROC) analysis from 0.59 to 0.75 showed that these models were highly efficient in distinguishing patient survival. GDS was adopted with the CellMiner database to provide some insights for platinum-sensitive analysis of OV. Furthermore, a prognostic SF-AS network, which discovered a significant connection between SFs and prognostic AS genes, was constructed using Cytoscape. The combined SNF-CC algorithm revealed three distinct OV subtypes based on the prognostic AS events, and the associations between this novel molecular classification and immune cell infiltration were further explored.ConclusionsWe developed a powerful prognostic AS signature for OV and provided a deeper understanding of SF-AS network regulatory mechanisms, as well as platinum-sensitive and cancer immune microenvironments. These results revealed various candidate biomarkers and potential targets for OV treatment strategies.

A prediction model of alternative splicing events reveals the prognostic predictors and immune microenvironment signatures in lung adenocarcinoma

In tumor development and microenvironment formation, alternative splicing (AS) has become increasingly important. Nevertheless, the clinical significance of AS in lung adenocarcinoma (LUAD) remains unclear. A comprehensive assessment of AS events in 455 LUAD patients was performed using data from The Cancer Genome Atlas (TCGA) database in this study. Lasso and Cox regression analyses were performed to identify survival-related significant AS events. The tumor microenvironment was assessed using CIBERSORT, a single-sample gene set enrichment analysis, and the ESTIMATE software package. Fifteen AS events screened by Lasso regression were constructed to build a risk prediction model. <i>FAXDC2</i>, <i>CDKN2A</i>, and <i>LAMA3</i> were identified in this study. In addition, immune scores, stromal scores, and tumor purity in different risk groups were assessed. The risk score was also correlated with tumor infiltrating immune cells. This study suggests that AS events are associated with tumor development and the immune microenvironment, and three genes, <i>FAXDC2</i>, <i>CDKN2A</i>, and <i>LAMA3</i> are identified, which may be potential markers of prognosis in LUAD.

Ral GEF with the PH Domain and SH3 Binding Motif 1 Regulated by Splicing Factor Junction Plakoglobin and Pyrimidine Metabolism Are Prognostic in Uterine Carcinosarcoma.

Uterine carcinosarcoma (UCS) is a highly invasive malignant tumor that originated from the uterine epithelium. Many studies suggested that the abnormal changes of alternative splicing (AS) of pre-mRNA are related to the occurrence and metastasis of the tumor. This study investigates the mechanism of alternative splicing events (ASEs) in the tumorigenesis and metastasis of UCS. RNA-seq of UCS samples and alternative splicing event (ASE) data of UCS samples were downloaded from The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases, several times. Firstly, we performed the Cox regression analysis to identify the overall survival-related alternative splicing events (OSRASEs). Secondly, a multivariate model was applied to approach the prognostic values of the risk score. Afterwards, a coexpressed network between splicing factors (SFs) and OSRASEs was constructed. In order to explore the relationship between the potential prognostic signaling pathways and OSRASEs, we fabricated a network between these pathways and OSRASEs. Finally, validations from multidimension platforms were used to explain the results unambiguously. 1,040 OSRASEs were identified by Cox regression. Then, 6 OSRASEs were incorporated in a multivariable model by Lasso regression. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve was 0.957. The risk score rendered from the multivariate model was corroborated to be an independent prognostic factor (P < 0.001). In the network of SFs and ASEs, junction plakoglobin (JUP) noteworthily regulated RALGPS1-87608-AT (P < 0.001, R = 0.455). Additionally, RALGPS1-87608-AT (P = 0.006) showed a prominent relationship with distant metastasis. KEGG pathways related to prognosis of UCS were selected by gene set variation analysis (GSVA). The pyrimidine metabolism (P < 0.001, R = −0.470) was the key pathway coexpressed with RALGPS1. We considered that aberrant JUP significantly regulated RALGPS1-87608-AT and the pyrimidine metabolism pathway might play a significant part in the metastasis and prognosis of UCS.

Systemic characterization of alternative splicing related to prognosis and immune infiltration in malignant mesothelioma

BackgroundMalignant mesothelioma (MM) is a relatively rare and highly lethal tumor with few treatment options. Thus, it is important to identify prognostic markers that can help clinicians diagnose mesothelioma earlier and assess disease activity more accurately. Alternative splicing (AS) events have been recognized as critical signatures for tumor diagnosis and treatment in multiple cancers, including MM.MethodsWe systematically examined the AS events and clinical information of 83 MM samples from TCGA database. Univariate Cox regression analysis was used to identify AS events associated with overall survival. LASSO analyses followed by multivariate Cox regression analyses were conducted to construct the prognostic signatures and assess the accuracy of these prognostic signatures by receiver operating characteristic (ROC) curve and Kaplan–Meier survival analyses. The ImmuCellAI and ssGSEA algorithms were used to assess the degrees of immune cell infiltration in MM samples. The survival-related splicing regulatory network was established based on the correlation between survival-related AS events and splicing factors (SFs).ResultsA total of 3976 AS events associated with overall survival were identified by univariate Cox regression analysis, and ES events accounted for the greatest proportion. We constructed prognostic signatures based on survival-related AS events. The prognostic signatures proved to be an efficient predictor with an area under the curve (AUC) greater than 0.9. Additionally, the risk score based on 6 key AS events proved to be an independent prognostic factor, and a nomogram composed of 6 key AS events was established. We found that the risk score was significantly decreased in patients with the epithelioid subtype. In addition, unsupervised clustering clearly showed that the risk score was associated with immune cell infiltration. The abundances of cytotoxic T (Tc) cells, natural killer (NK) cells and T-helper 17 (Th17) cells were higher in the high-risk group, whereas the abundances of induced regulatory T (iTreg) cells were lower in the high-risk group. Finally, we identified 3 SFs (HSPB1, INTS1 and LUC7L2) that were significantly associated with MM patient survival and then constructed a regulatory network between the 3 SFs and survival-related AS to reveal potential regulatory mechanisms in MM.ConclusionOur study provided a prognostic signature based on 6 key events, representing a better effective tumor-specific diagnostic and prognostic marker than the TNM staging system. AS events that are correlated with the immune system may be potential therapeutic targets for MM.

Identification of survival-related alternative splicing signatures in acute myeloid leukemia.

Aberrant RNA alternative splicing (AS) variants play critical roles in tumorigenesis and prognosis in human cancers. Here, we conducted a comprehensive profiling of aberrant AS events in acute myeloid leukemia (AML). RNA AS profile, including seven AS types, and the percent spliced in (PSI) value for each patient were generated by SpliceSeq using RNA-seq data from TCGA. Univariate followed by multivariate Cox regression analysis were used to identify survival-related AS events and develop the AS signatures. A nomogram was developed, and its predictive efficacy was assessed. About 27,892 AS events and 3,178 events were associated with overall survival (OS) after strict filtering. Parent genes of survival-associated AS events were mainly enriched in leukemia-associated processes including chromatin modification, autophagy, and T-cell receptor signaling pathway. The 10 AS signature based on seven types of AS events showed better efficacy in predicting OS of patients than those built on a single AS event type. The area under curve (AUC) value of the 10 AS signature for 3-year OS was 0.91. Gene set enrichment analysis (GSEA) confirmed that these survival-related AS events contribute to AML progression. Moreover, the nomogram showed good predictive performance for patient's prognosis. Finally, the correlation network of AS variants with splicing factor genes found potential important regulatory genes in AML. The present study presented a systematic analysis of survival-related AS events and developed AS signatures for predicting the patient’s survival. Further studies are needed to validate the signatures in independent AML cohorts and might provide a promising perspective for developing therapeutic targets.

Identification of Mutator-Derived Alternative Splicing Signatures of Genomic Instability for Improving the Clinical Outcome of Cholangiocarcinoma.

BackgroundCholangiocarcinoma is an aggressive carcinoma with increasing incidence and poor outcomes worldwide. Genomic instability and alternative splicing (AS) events are hallmarks of carcinoma development and progression. The relationship between genomic instability, AS events, and tumor immune microenvironment remain unclear.MethodsThe splicing profiles of patients with cholangiocarcinoma were obtained from The Cancer Genome Atlas (TCGA) spliceSeq database. The transcriptomics, simple nucleotide variation (SNP) and clinical data of patients with cholangiocarcinoma were obtained from TCGA database. Patients were divided into genomic unstable (GU-like) and genomic stable (GS-like) groups according to their somatic mutations. Survival-related differential AS events were identified through integrated analysis of splicing profiling and clinical data. Kyoto Encyclopedia of Genes and Genomes enrichment analysis was used to identify AS events occurring in genes enriched in cancer pathways. Pearson correlation was applied to analyze the splicing factors regulating AS events. CIBERSORT was used identify differentially infiltrating immune cells.ResultsA prognostic signature was constructed with six AS events. Using this signature, the hazard ratio of risk score for overall survival is 2.362. For TCGA patients with cholangiocarcinoma, the area under the receiver operating characteristic curve is 0.981. CDK11A is a negative regulator of survival associated AS events. Additionally, the CD8+ T cell proportion and PD-L1 expression are upregulated in patients with cholangiocarcinoma and high splicing signatures.ConclusionWe provide a prognostic signature for cholangiocarcinoma overall survival. The CDK11A splicing factor and SLC46A1-39899-ES and IARS-86836-ES AS events may be potential targets for cholangiocarcinoma therapy. Patients with high AS risk score may be more sensitive to anti-PD-L1/PD1 immunotherapy.

An alternative splicing signature model for predicting hepatocellular carcinoma-specific survival.

Alternative splicing (AS) is a transcriptional regulation mechanism, which can expand the coding ability of genome and contribute to the occurrence and development of cancer. A systematic analysis of AS in hepatocellular carcinoma (HCC) is lacking and urgently needed. Univariate and multivariate Cox regression analyses were used to distinguish survival-related AS events and to calculate the risk score. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the AS events' clinical significance to build a risk model in HCC. Data of AS events was obtained from the Splice-Seq database. The corresponding clinical information of HCC was downloaded from The Cancer Genome Atlas (TCGA) data portal. We analyzed 78,878 AS events from 13,045 genes in HCC patients. A total of 2,440 and 2,888 AS events were significantly related to HCC patients' disease-free survival (DFS) and overall survival (OS). The two prognostic models (DFS and OS) were constructed based on a total of seven AS types from survival-related AS events above. The area under the curve (AUC) of the ROC curves was 0.769 in the DFS cohort and 0.886 in the OS cohort. The prognostic model constructed by AS events can be used to predict the prognosis of HCC patients and provide potential therapeutic targets for further validation.

Identification of Survival-Associated Alternative Splicing Signatures in Lung Squamous Cell Carcinoma.

Purpose: Alternative splicing (AS) is a post-transcriptional process that plays a significant role in enhancing the diversity of transcription and protein. Accumulating evidences have demonstrated that dysregulation of AS is associated with oncogenic processes. However, AS signature specifically in lung squamous cell carcinoma (LUSC) remains unknown. This study aimed to evaluate the prognostic values of AS events in LUSC patients.Methods: The RNA-seq data, AS events data and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis was performed to identify survival-related AS events and survival-related parent genes were subjected to Gene Ontology enrichment analysis and gene network analysis. The least absolute shrinkage and selection operator (LASSO) method and multivariate Cox regression analysis were used to construct prognostic prediction models, and their predictive values were assessed by Kaplan-Meier analysis and receiver operating characteristic (ROC) curves. Then a nomogram was established to predict the survival of LUSC patients. And the interaction network of splicing factors (SFs) and survival-related AS events was constructed by Spearman correlation analysis and visualized by Cytoscape.Results: Totally, 467 LUSC patients were included in this study and 1,991 survival-related AS events within 1,433 genes were identified. SMAD4, FOS, POLR2L, and RNPS1 were the hub genes in the gene interaction network. Eight prognostic prediction models (seven types of AS and all AS) were constructed and all exhibited high efficiency in distinguishing good or poor survival of LUSC patients. The final integrated prediction model including all types of AS events exhibited the best prognostic power with the maximum AUC values of 0.778, 0.816, 0.814 in 1, 3, 5 years ROC curves, respectively. Meanwhile, the nomogram performed well in predicting the 1-, 3-, and 5-year survival of LUSC patients. In addition, the SF-AS regulatory network uncovered a significant correlation between SFs and survival-related AS events.Conclusion: This is the first comprehensive study to analyze the role of AS events in LUSC specifically, which improves our understanding of the prognostic value of survival-related AS events for LUSC. And these survival-related AS events might serve as novel prognostic biomarkers and drug therapeutic targets for LUSC.

Comprehensive analysis and establishment of a prediction model of alternative splicing events reveal the prognostic predictor and immune microenvironment signatures in triple negative breast cancer

BackgroundTriple-negative breast cancer (TNBC) is widely concerning because of high malignancy and poor prognosis. There is increasing evidence that alternative splicing (AS) plays an important role in the development of cancer and the formation of the tumour microenvironment. However, comprehensive analysis of AS signalling in TNBC is still lacking and urgently needed.MethodsTranscriptome and clinical data of 169 TNBC tissues and 15 normal tissues were obtained and integrated from the cancer genome atlas (TCGA), and an overview of AS events was downloaded from the SpliceSeq database. Then, differential comparative analysis was performed to obtain cancer-associated AS events (CAAS). Metascape was used to perform parent gene enrichment analysis based on CAAS. Unsupervised cluster analysis was performed to analyse the characteristics of immune infiltration in the microenvironment. A splicing network was established based on the correlation between CAAS events and splicing factors (SFs). We then constructed prediction models and assessed the accuracy of these models by receiver operating characteristic (ROC) curve and Kaplan–Meier survival analyses. Furthermore, a nomogram was adopted to predict the individualized survival rate of TNBC patients.ResultsWe identified 1194 cancer-associated AS events (CAAS) and evaluated the enrichment of 981 parent genes. The top 20 parent genes with significant differences were mostly related to cell adhesion, cell component connection and other pathways. Furthermore, immune-related pathways were also enriched. Unsupervised clustering analysis revealed the heterogeneity of the immune microenvironment in TNBC. The splicing network also suggested an obvious correlation between SFs expression and CAAS events in TNBC patients. Univariate and multivariate Cox regression analyses showed that the survival-related AS events were detected, including some significant participants in the carcinogenic process. A nomogram incorporating risk, AJCC and radiotherapy showed good calibration and moderate discrimination.ConclusionOur study revealed AS events related to tumorigenesis and the immune microenvironment, elaborated the potential correlation between SFs and CAAS, established a prognostic model based on survival-related AS events, and created a nomogram to better predict the individual survival rate of TNBC patients, which improved our understanding of the relationship between AS events and TNBC.

Identification of prognostic and metastasis-related alternative splicing signatures in hepatocellular carcinoma.

As the most common neoplasm in digestive system, hepatocellular carcinoma (HCC) is one of the most important leading cause of cancer deaths worldwide. Its high-frequency metastasis and relapse rate lead to the poor survival of HCC patients. However, the mechanism of HCC metastasis is still unclear. Alternative splicing events (ASEs) have a great effect in cancer development, progression and metastasis. We downloaded RNA sequencing and seven types of ASEs data of HCC samples, in order to explore the mechanism of ASEs underlying tumorigenesis and metastasis of HCC. The data were taken from the The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases. Univariate Cox regression analysis was used to determine a total of 3197 overall survival-related ASEs (OS-SEs). And based on five OS-SEs screened by Lasso regression, we constructed a prediction model with the Area Under Curve of 0.765. With a good reliability of the model, the risk score was also proved to be an independent predictor. Among identified 390 candidate SFs, Y-box protein 3 (YBX3) was significantly correlated with OS and metastasis. Among 177 ASEs, ATP-binding cassette subfamily A member 6 (ABCA6)-43162-AT and PLIN5-46808-AT were identified both associated with OS, bone metastasis and co-expressed with SFs. Then we identified primary bile acid biosynthesis as survival-related (KEGG) pathway by Gene Set Variation Analysis (GSVA) and univariate regression analysis, which was correlated with ABCA6-43162-AT and PLIN5-46808-AT. Finally, we proposed that ABCA6-43162-AT and PLIN5-46808-AT may contribute to HCC poor prognosis and metastasis under the regulation of aberrant YBX3 through the pathway of primary bile acid biosynthesis.

Comprehensive Characterization of the Prognosis Value of Alternative Splicing Events in Acute Myeloid Leukemia.

Increasing evidence have demonstrated that dysregulated alternative splicing (AS) events promoted tumor development and was correlated with worse prognosis in the context of certain malignancies. Nevertheless, a comprehensive examination of the prognosis role of AS events in acute myeloid leukemia (AML) has not yet been illuminated. In this study, univariate and multivariate Cox regression analysis were used to identify survival-related AS events and independent prognostic predictors. The interaction between splicing factors (SFs) and AS events was visualized by Cytoscape. A total of 3013 survival-associated AS events in 1977 genes were screened in 151 AML patients. Interestingly, the majority (2031 events) were revealed to be protective factors. Furthermore, the prediction models were constructed for each type of AS and all of them displayed good performance in predicting prognosis, considering their area under curve values of the receiver operating characteristic were all above 0.7. Notably, the splicing regulatory network displayed the underlying interaction networks between SFs and AS events. Taken together, our study demonstrated the survival-related AS events in AML and uncovered the possible association between SFs and prognostic AS events, which provide new prognostic biomarkers and aid to develop novel targets for AML therapy.

Wide-ranging analysis of survival-related alternative splicing events in invasive breast carcinoma.

Invasive breast carcinoma (BRCA) is a serious disease that threatens the survival time of those affected. Alternative splicing (AS) involved in BRCA pathogenesis may be a potential therapeutic target. However, to the best of our knowledge, a systematic analysis of survival-related alternative splicing events (SREs) has not yet been reported. The aim of the present study was to identify SREs and analyze their potential biological functions as BRCA prognostic biomarkers. An UpSet plot demonstrated AS global characteristics. Cox's proportional hazards regression model quantitatively demonstrated the prognostic relevance of AS events. Functional enrichment analysis investigated the potential pathways through which AS events affect BRCA progression. The receiver operating characteristic curve model determined the clinical significance of AS events represented using percent-spliced-in (PSI) values. The regulatory network of splicing factors (SFs) and AS events laid the foundation for studying the role of SFs in BRCA. The present study identified 1,215 SREs and their distribution characteristics, suggesting that AS events in exon skipping (ES) primarily exerted normal physiological functions, while AS events in alternative terminator sites had the most significant prognostic effect. The present study demonstrated that survival-associated genes are involved primarily in certain biological processes of ribosomal proteins. In the diagnostic model, the alternative acceptor site, alternative donor site, alternative promoter site and ES performed well. ELAVL4 was the key gene associated with prognosis and SREs. In conclusion, a number of AS events affect BRCA initiation, progression and prognosis. The PSI value of AS events has the potential to diagnose BRCA and predict a prognosis; however, this must be confirmed in additional studies.

Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer.

BackgroundAlternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC).MethodsThe splicing data and gene expression profiles of EC were obtained from The Cancer Genome Atlas. The corresponding clinical data were extracted from TCGA-CDR. With univariate Cox regression analysis, least absolute shrinkage and selection operator model, and multivariate Cox regression analysis, the survival-related AS events were selected. Functional enrichment analysis was also performed to investigate the functions of these AS events. Splicing factors and AS regulation network were constructed to understand the correlation among these AS events.ResultA total of 1826 AS events were identified as survival-related events. Functional enrichment analysis showed that these AS events were associated with several immune system-related processes. Then, the prognostic signatures were developed based on these survival-related events and acted as an independent prognostic factor for EC. Splicing factors and AS regulation network were also constructed to understand the regulatory mechanisms of AS events in EC.ConclusionThis study systematically analyzed the role of AS events in EC and developed the prognostic model for EC.

Identification of a prognostic alternative splicing signature in oral squamous cell carcinoma.

Alternative splicing (AS) is critically associated with tumorigenesis and patient's prognosis. Here, we systematically analyzed survival-associated AS signatures in oral squamous cell carcinoma (OSCC) and evaluated their prognostic predictive values. Survival-related AS events were identified by univariate and multivariate Cox regression analyses using OSCC data from the TCGA head neck squamous cell carcinoma data set. ThePercent Spliced In calculated by SpliceSeq from 0 to 1 was used to quantify seven types of AS events. A predictive model based on AS events was constructed by least absolute shrinkage and selection operator Cox regression assay and further validated using a training-testing cohort design. Patient survival was estimated using the Kaplan-Meier method and compared with Log-rank test. The receiver operating characteristics curve area under the curves was used to evaluate the predictive abilities of these predictive models. Furthermore, gene-gene interaction networks and the splicing factors (SFs)-AS regulatory network was generated by Cytoscape. A total of 825 survival-related AS events within 719 genes were identified in OSCC samples. The integrative predictive model was betteratpredicting outcomes of patients as compared to those models built with the individual AS event. The predictive model based on three AS-related genes also effectively predicted patients' survival. Moreover, seven survival-related SFs were detected in OSCC including RBM4, HNRNPD, and HNRNPC, which have been linked to tumorigenesis. The SF-AS network revealed a significant correlation between survival-related AS genes and these SFs. Our findings revealed a systemic portrait of survival-associated AS events and the splicing network in OSCC, suggesting that AS events might serve as novel prognostic biomarkers and therapeutic targets for OSCC.