Genome-Wide Profiling of Prognostic Alternative Splicing Signature in Colorectal Cancer

Targeting FABP4 in elderly mice rejuvenates liver metabolism and ameliorates aging-associated metabolic disorders

INTRODUCTION

Aging is characterized by progressive metabolic dyshomeostasis that increases morbidity and mortality. Solutions for optimizing healthy aging are challenged by lacking appropriate biomarkers. Moreover, druggable targets to rejuvenate the aging-associated metabolic phenotypes remain unavailable.

METHODS

Proteomics analysis was performed in a cohort of young and elderly adults. Circulating levels of insulin-like growth factor 1 (IGF-1) and fatty acid binding protein 4 (FABP4) were evaluated by ELISA. FABP4 was silenced in elderly mice by adeno-associated virus. Metabolic activities were measured by metabolic cages. Cognitive function was evaluated by Morris water maze. Glucose and lipid metabolism were evaluated by biochemistry assays with blood samples. RNA-seq in mouse liver was performed for transcriptome analysis.

RESULTS

Among 9 aging-sensitive proteins shared by both male and female, FABP4 was identified as a reliable aging biomarker in both human and mouse. Silencing FABP4 in elderly mice significantly rejuvenated the aging-associated decline in metabolic activities. FABP4 knockdown reversed the aging-associated metabolic disorders by promoting degradation of cholesterol and fatty acids, while suppressing gluconeogenesis. Transcriptome analysis revealed a restoration of the pro-aging gene reprogramming towards inflammation and metabolic disorders in the liver after FABP4 knockdown. FABP4 overexpression promoted human LO2 cell senescence. Moreover, administration of an FABP4 inhibitor BMS309403 delivered metabolic benefits in elderly mice.

CONCLUSION

Our findings demonstrate FABP4 as a reliable aging biomarker as well as a practicable target to improve healthy aging in the elderly.

N6-Methyladenosine-related alternative splicing events play a role in bladder cancer

This study investigated the role of N6-methyladenosine (m6A) and alternative splicing (AS) in bladder cancer (BLCA). The BLCA-related RNA expression profiles and AS events were downloaded from the UCSC Xena and SpliceSeq databases, respectively. Differentially expressed AS (DEAS) was screened, and prognostic-related DEAS events were used to construct prognostic risk models based on Cox proportional hazards regression analysis. Receiver operating characteristic curves and multivariate Cox analysis were used to evaluate the predictive efficiency and independence of these models. We also constructed a protein-to-protein interaction (PPI) network and a regulation network of splicing factors (SFs) and DEAS events. In total, 225 m6A-related prognostic-related DEAS events were identified. The predictive ability of each prognostic model was good, and the alternate terminator model showed the best performance when the area under the curve was 0.793. The risk score of the model was an independent prognostic factor for BLCA. The PPI network revealed that AKT serine/threonine kinase 1, serine- and arginine-rich SF6, and serine- and arginine-rich SF2 had higher-node degrees. A complex regulator correlation was shown in the SF and DEAS networks. This study provides insights for the subsequent understanding of the role of AS events in BLCA.

Identification of prognostic alternative splicing signature in gastric cancer

Background

Aberrant 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.

Methods

RNA-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.

Results

We 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.

Conclusion

Our 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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00894-3.

The Role of Autophagy in Tumor Immune Infiltration in Colorectal Cancer

Objective. This study is aimed at exploring the association between autophagy and tumor immune infiltration (TII) in colorectal cancer (CRC). Methods and Materials. We downloaded the transcriptome profiling and clinical data for CRC from The Cancer Genome Atlas (TCGA) database and obtained the normal colon transcriptome profiling data from Genotype-Tissue Expression Project (GTEx) database. The list of autophagy-related signatures was obtained from the Human Autophagy Database. We isolated the autophagy-related genes from the CRC gene expression matrix and constructed an autophagy-related prognostic (ARP) risk model. Then, we constructed a multiROC curve to validate the prognostic ability of the ARP risk model. CIBERSORT was used to determine the fractions of 22 immune cells in each CRC sample, and the association between these TII cells and CRC clinical variables was further investigated. Finally, we estimated the association of 3 hub-ARP signatures and 20 different types of TII cell distribution. Results. We classified 447 CRC patients into 224 low-risk and 223 high-risk patients using the median ARP risk score. According to the univariate survival test results, except for gender ( $P=0.672$ ), age ( $P=0.008$ ), cancer stage, and pathological stage T, M, and N were closely correlated with the prognosis of CRC patients ( $P<0.001$ ). Multivariate survival analysis results indicate that age and rescore were the only independent prognostic indicators with significant differences ( $P<0.05$ ). After merging the immune cell distribution (by CIBERSORT) with the CRC clinical data, the results indicate that activated macrophage M0 cells exhibited the highest clinical response, which included cancer stage and stage T, N, and M. Additionally, six immune cells were closely associated with cancer stage, including regulatory T cells (Tregs), gamma delta T cells, follicular helper T cells, activated memory CD4 T cells, activated NK cells, and resting dendritic cells. Finally, we evaluated the correlation of ARP signatures with TII cell distribution. Compared with the other correlation, NRG1 and plasma cells (↑), risk score and macrophage M1 (↑), NRG1 and dendritic cell activated (↑), CDKN2A and T cell CD4 memory resting (↓), risk score and T cell CD8 (↑), risk score and T cell CD4 memory resting (↓), and DAPK1 and T cell CD4 memory activated (↓) exhibited a stronger association ( $P<0.0001$ ). Conclusions. In summary, we explored the correlation between the risk of autophagy and the TII microenvironment in CRC patients. Furthermore, we integrated different CAR signatures with tumor-infiltrating immune cells and found robust associations between different levels of CAR signature expression and immune cell infiltrating density.

Screening and Identification of Survival-Associated Splicing Factors in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LUSC) is a disease with high morbidity and mortality. Many studies have shown that aberrant alternative splicing (AS) can lead to tumorigenesis, and splicing factors (SFs) serve as an important function during AS. In this research, we propose an analysis method based on synergy to screen key factors that regulate the initiation and progression of LUSC. We first screened alternative splicing events (ASEs) associated with survival in LUSC patients by bivariate Cox regression analysis. Then an association network consisting of OS-ASEs, SFs, and their targeting relationship was constructed to identify key SFs. Finally, 10 key SFs were selected in terms of degree centrality. The validation on TCGA and cross-platform GEO datasets showed that some SFs were significantly differentially expressed in cancer and paracancer tissues, and some of them were associated with prognosis, indicating that our method is valid and accurate. It is expected that our method would be applied to a wide range of research fields and provide new insights in the future.

Analyzing large scale gene expression data in colorectal cancer reveals important clues; CLCA1 and SELENBP1 downregulated in CRC not in normal and not in adenoma

Early detection of colorectal cancer (CRC) increases the chances of survival and reduces the therapeutic problems and costs of treatment. Since molecular biomarkers can help us diagnose colorectal cancer early, we need to identify novel gene for predicting the early stages of tumorigenesis. Here, we integrated five independent CRC gene expression datasets derived from expression profiling by array comparing CRC with normal samples in: GSE21510, GSE4107, GSE25071, GSE15781 dataset, and GSE8671 dataset, including 64 samples from 32 patients comparing 32 colonic normal mucosa with 32 colorectal adenoma. To detect genes that expressed differentially in experimental circumstances of these datasets, we used web tool of GEO2R to compare groups of samples in the GEO data series. Furthermore, we constructed the protein-protein interactions network by STRING database for mostly downregulated genes and the expression of their members in PPI network were studied into five datasets separately. Also, the level of expression of selected biomarker genes in different stages of CRC compared to normal was studied. Our data revealed 17 common downregulated genes (average fold change (FC) in five tests ≥6) in CRC in comparison with normal (Test 1 to Test 4) and in adenoma compared with normal (Test 5). Studying of gene expression of PPI network members of these downregulated genes led to identifying of CLCA1, SELENBP1, CWC25, ACOT11, GUCY2C and ALDH1A1 as suppressor genes and PTGS2, PROCR, MOCS3 and NFS1 as oncogenes which respectively downregulated and upregulated in CRC. Since decreasing of gene expression was seen in CRC comparing with normal and due to no different expression seen for these 10 genes in adenoma, they, especially CLCA1 and SELENBP1, could be considered as biomarkers for early detection of CRC. Before using these signature genes in the clinic; however, further validations are required.

Comprehensive analysis of aberrant alternative splicing related to carcinogenesis and prognosis of papillary thyroid cancer

As a key mechanism, alternative splicing (AS) plays a role in the cancer initiation and development. However, in papillary thyroid cancer (PTC), data for the comprehensive AS event profile and its clinical implications are lacking. Herein, a genome-wide AS event profiling using RNA-Seq data and its correlation with matched clinical information was performed using a 389 PTC patient cohort from the project of The Cancer Genome Atlas (TCGA). We identified 1,925 cancer-associated AS events (CASEs) by comparing paired tumors and neighboring healthy tissues. Parent genes with CASEs remarkably enriched in the pathways were linked with carcinogenesis, such as P53, KRAS, IL6-JAK-STAT3, apoptosis, and MYC signaling. The regulatory networks of AS implied an obvious correlation between the expression of splicing factor and CASE. We identified eight CASEs as predictors for overall survival (OS) and disease-free survival (DFS). The established risk score model based on DFS-associated CASEs successfully predicted the prognosis of PTC patients. From the unsupervised clustering analysis results, it is found that different clusters based on AS correlated with prognosis, molecular features, and immune characteristics. Taken together, the comprehensive genome-wide AS landscape analysis in PTC showed new AS events linked with tumorigenesis and prognosis, which provide new insights for clinical monitoring and therapy for PTC.

SIRT7-Induced PHF5A Decrotonylation Regulates Aging Progress Through Alternative Splicing-Mediated Downregulation of CDK2

Dysregulation of protein posttranslational modification (PTM) can lead to a variety of pathological processes, such as abnormal sperm development, malignant tumorigenesis, depression, and aging process. SIRT7 is a NAD⁺-dependent protein deacetylase. Besides known deacetylation, SIRT7 may also have the capacity to remove other acylation. However, the roles of SIRT7-induced other deacylation in aging are still largely unknown. Here, we found that the expression of SIRT7 was significantly increased in senescent fibroblasts and aged tissues. Knockdown or overexpression of SIRT7 can inhibit or promote fibroblast senescence. Knockdown of SIRT7 led to increased pan-lysine crotonylation (Kcr) levels in senescent fibroblasts. Using modern mass spectrometry (MS) technology, we identified 5,149 Kcr sites across 1,541 proteins in senescent fibroblasts, and providing the largest crotonylome dataset to date in senescent cells. Specifically, among the identified proteins, we found SIRT7 decrotonylated PHF5A, an alternative splicing (AS) factor, at K25. Decrotonylation of PHF5A K25 contributed to decreased CDK2 expression by retained intron (RI)-induced abnormal AS, thereby accelerating fibroblast senescence, and supporting a key role of PHF5A K25 decrotonylation in aging. Collectively, our data revealed the molecular mechanism of SIRT7-induced k25 decrotonylation of PHF5A regulating aging and provide new ideas and molecular targets for drug intervention in cellular aging and the treatment of aging-related diseases, and indicating that protein crotonylation has important implications in the regulation of aging progress.

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.

The underlying molecular mechanisms and prognostic factors of RNA binding protein in colorectal cancer: a study based on multiple online databases

BACKGROUND

RNA binding protein (RBP) is an active factor involved in the occurrence and development of colorectal cancer (CRC). Therefore, the potential mechanism of RBP in CRC needs to be clarified by dry-lab analyses or wet-lab experiments.

METHODS

The differential RBP gene obtained from the GEPIA 2 (Gene Expression Profiling Interactive Analysis 2) were performed functional enrichment analysis. Then, the alternative splicing (AS) events related to survival were acquired by univariate regression analysis, and the correlation between RBP and AS was analyzed by R software. The online databases were conducted to analyze the mutation and methylation of RBPs in CRC. Moreover, 5 key RBP signatures were obtained through univariate and multivariate Cox regression analysis and established as RBP prognosis model. Subsequently, the above model was verified through another randomized group of TCGA CRC cohorts. Finally, multiple online databases and qRT-PCR analysis were carried to further confirm the expression of the above 5 RBP signatures in CRC.

RESULTS

Through a comprehensive bioinformatics analysis, it was revealed that RBPs had genetic and epigenetic changes in CRC. We obtained 300 differentially expressed RBPs in CRC samples. The functional analysis suggested that they mainly participated in spliceosome. Then, a regulatory network for RBP was established to participate in AS and DDX39B was detected to act as a potentially essential factor in the regulation of AS in CRC. Our analysis discovered that 11 differentially expressed RBPs with a mutation frequency higher than 5%. Furthermore, we found that 10 differentially expressed RBPs had methylation sites related to the prognosis of CRC, and a prognostic model was constructed by the 5 RBP signatures. In another randomized group of TCGA CRC cohorts, the prognostic performance of the 5 RBP signatures was verified.

CONCLUSION

The potential mechanisms that regulate the aberrant expression of RBPs in the development of CRC was explored, a network that regulated AS was established, and the RBP-related prognosis model was constructed and verified, which could improve the individualized prognosis prediction of CRC.

Alternative Splicing Events in Tumor Immune Infiltration in Colorectal Cancer

Despite extensive research, the exact mechanisms involved in colorectal cancer (CRC) etiology and pathogenesis remain unclear. This study aimed to examine the correlation between tumor-associated alternative splicing (AS) events and tumor immune infiltration (TII) in CRC. We analyzed transcriptome profiling and clinical CRC data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq and Innate databases, respectively to develop and validate a risk model of differential AS events and subsequently a TII risk model. We then conducted a two-factor survival analysis to study the association between TII and AS risk and evaluated the associations between immune signatures and six types of immune cells based on the TIMER database. Subsequently, we studied the distribution of six types of TII cells in high- and low-risk groups for seven AS events and in total. We obtained the profiles of AS events/genes for 484 patients, which included 473 CRC tumor samples and 41 corresponding normal samples, and detected 22581 AS events in 8122 genes. Exon Skip (ES) (8446) and Mutually Exclusive Exons (ME) (74) exhibited the most and fewest AS events, respectively. We then classified the 433 patients with CRC into low-risk (n = 217) and high-risk (n = 216) groups based on the median risk score in different AS events. Compared with patients with low-risk scores (mortality = 11.8%), patients with high-risk scores were associated with poor overall survival (mortality = 27.6%). The risk score, cancer stage, and pathological stage (T, M, and N) were closely correlated with prognosis in patients with CRC (P < 0.001). We identified 6479 differentially expressed genes from the transcriptome profiles of CRC and intersected 468 differential immune-related signatures. High-AS-risk and high-TII-risk predicted a poor prognosis in CRC. Different AS types were associated with different TII risk characteristics. Alternate Acceptor site (AA) and Alternate Promoter (AP) events directly affected the concentration of CD4T cells, and the level of CD8T cells was closely correlated with Alternate Terminator (AT) and Exon Skip (ES) events. Thus, the concentration of CD4T and CD8T cells in the CRC immune microenvironment was not specifically modulated by AS. However, B cell, dendritic cell, macrophage, and neutrophilic cell levels were strongly correlated with AS events. These results indicate adverse associations between AS event risk levels and immune cell infiltration density. Taken together, our findings show a clear association between tumor-associated alternative splicing and immune cell infiltration events and patient outcome and could form a basis for the identification of novel markers and therapeutic targets for CRC and other cancers in the future.

Signature of gene aberrant alternative splicing events in pancreatic adenocarcinoma prognosis

Alternative splicing (AS), as an effective and universal mechanism of transcriptional regulation, is involved in the development and progression of cancer. Therefore, systematic analysis of alternative splicing in pancreatic adenocarcinoma (PAAD) is warranted. The corresponding clinical information of the RNA-Seq data and PAAD cohort was downloaded from the TCGA data portal. Then, a java application, SpliceSeq, was used to evaluate the RNA splicing pattern and calculate the splicing percentage index (PSI). Differentially expressed AS events (DEAS) were identified based on PSI values between PAAD cancer samples and normal samples of adjacent tissues. Kaplan-Meier and Cox regression analyses were used to assess the association between DEAS and patient clinical characteristics. Unsupervised cluster analysis used to reveal four clusters with different survival patterns. At the same time, GEO and TCGA combined with GTEx to verify the differential expression of AS gene and splicing factor. After rigorous filtering, a total of 45,313 AS events were identified, 1,546 of which were differentially expressed AS events. Nineteen DEAS were found to be associated with OS with a five-year overall survival rate of 0.946. And the subtype clusters results indicate that there are differences in the nature of individual AS that affect clinical outcomes. Results also identified 15 splicing factors associated with the prognosis of PAAD. And the splicing factors ESRP1 and RBM5 played an important role in the PAAD-associated AS events. The PAAD-associated AS events, splicing networks, and clusters identified in this study are valuable for deciphering the underlying mechanisms of AS in PAAD and may facilitate the establishment of therapeutic goals for further validation.

Alternative splicing of lncRNAs in human diseases

Alternative splicing (AS), a vital post-transcription process for eukaryote gene expression regulating, can efficiently improve gene utilization and increase the variety of RNA transcripts and proteins. However, AS of non-coding RNAs (ncRNAs) has not been paid enough attention to compared with that of protein-coding RNAs (mRNAs) for a long time. In fact, AS of ncRNAs, especially long noncoding RNAs (lncRNAs), also plays a significant regulatory role in the human disease. Recently, some bifunctional genes transcribed into both mRNA and lncRNA transcripts by AS have been observed. Here, we focus on the AS of lncRNAs and bifunctional genes producing lncRNA transcripts and propose a strategy for the future research of lncRNA AS.

Alternative splicing: An important regulatory mechanism in colorectal carcinoma

Alternative splicing (AS) is a process that produces various mRNA splicing isoforms via different splicing patterns of mRNA precursors (pre-mRNAs). AS is the primary mechanism for increasing the types and quantities of proteins to improve biodiversity and influence multiple biological processes, including chromatin modification, signal transduction, and protein expression. It has been reported that AS is involved in the tumorigenesis and development of colorectal carcinoma (CRC). In this review, we delineate the concept, types, regulatory processes, and technical advances of AS and focus on the role of AS in CRC initiation, progression, treatment, and prognosis. This summary of the current knowledge about AS will contribute to our understanding of CRC initiation and development. This study will help in the discovery of novel biomarkers and therapeutic targets for CRC prognosis and treatment.

Genetic Effects on Transcriptome Profiles in Colon Epithelium Provide Functional Insights for Genetic Risk Loci

BACKGROUND & AIMS

The association of genetic variation with tissue-specific gene expression and alternative splicing guides functional characterization of complex trait-associated loci and may suggest novel genes implicated in disease. Here, our aims were as follows: (1) to generate reference profiles of colon mucosa gene expression and alternative splicing and compare them across colon subsites (ascending, transverse, and descending), (2) to identify expression and splicing quantitative trait loci (QTLs), (3) to find traits for which identified QTLs contribute to single-nucleotide polymorphism (SNP)-based heritability, (4) to propose candidate effector genes, and (5) to provide a web-based visualization resource.

METHODS

We collected colonic mucosal biopsy specimens from 485 healthy adults and performed bulk RNA sequencing. We performed genome-wide SNP genotyping from blood leukocytes. Statistical approaches and bioinformatics software were used for QTL identification and downstream analyses.

RESULTS

We provided a complete quantification of gene expression and alternative splicing across colon subsites and described their differences. We identified thousands of expression and splicing QTLs and defined their enrichment at genome-wide regulatory regions. We found that part of the SNP-based heritability of diseases affecting colon tissue, such as colorectal cancer and inflammatory bowel disease, but also of diseases affecting other tissues, such as psychiatric conditions, can be explained by the identified QTLs. We provided candidate effector genes for multiple phenotypes. Finally, we provided the Colon Transcriptome Explorer web application.

CONCLUSIONS

We provide a large characterization of gene expression and splicing across colon subsites. Our findings provide greater etiologic insight into complex traits and diseases influenced by transcriptomic changes in colon tissue.

Comprehensive Characterization of Alternative mRNA Splicing Events in Glioblastoma: Implications for Prognosis, Molecular Subtypes, and Immune Microenvironment Remodeling

Alternative splicing (AS) of pre-mRNA has been widely reported to be associated with the progression of malignant tumors. However, a systematic investigation into the prognostic value of AS events in glioblastoma (GBM) is urgently required. The gene expression profile and matched AS events data of GBM patients were obtained from The Cancer Genome Atlas Project (TCGA) and TCGA SpliceSeq database, respectively. 775 AS events were identified as prognostic factors using univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) cox model was performed to narrow down candidate AS events, and a risk score model based on several AS events were developed subsequently. The risk score-based signature was proved as an efficient predictor of overall survival and was closely related to the tumor purity and immunosuppression in GBM. Combined similarity network fusion and consensus clustering (SNF-CC) analysis revealed two distinct GBM subtypes based on the prognostic AS events, and the associations between this novel molecular classification and clinicopathological factors, immune cell infiltration, as well as immunogenic features were further explored. We also constructed a regulatory network to depict the potential mechanisms that how prognostic splicing factors (SFs) regulate splicing patterns in GBM. Finally, a nomogram incorporating AS events signature and other clinical-relevant covariates was built for clinical application. This comprehensive analysis highlights the potential implications for predicting prognosis and clinical management in GBM.

Alternative splicing: Human disease and quantitative analysis from high-throughput sequencing

Alternative splicing contributes to the majority of protein diversity in higher eukaryotes by allowing one gene to generate multiple distinct protein isoforms. It adds another regulation layer of gene expression. Up to 95% of human multi-exon genes undergo alternative splicing to encode proteins with different functions. Moreover, around 15% of human hereditary diseases and cancers are associated with alternative splicing. Regulation of alternative splicing is attributed to a set of delicate machineries interacting with each other in aid of important biological processes such as cell development and differentiation. Given the importance of alternative splicing events, their accurate mapping and quantification are paramount for downstream analysis, especially for associating disease with alternative splicing. However, deriving accurate isoform expression from high-throughput RNA-seq data remains a challenging task. In this mini-review, we aim to illustrate I) mechanisms and regulation of alternative splicing, II) alternative splicing associated human disease, III) computational tools for the quantification of isoforms and alternative splicing from RNA-seq.

Intron retention is a robust marker of intertumoral heterogeneity in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with a 5-year survival rate of <8%. Unsupervised clustering of 76 PDAC patients based on intron retention (IR) events resulted in two clusters of tumors (IR-1 and IR-2). While gene expression-based clusters are not predictive of patient outcome in this cohort, the clusters we developed based on intron retention were associated with differences in progression-free interval. IR levels are lower and clinical outcome is worse in IR-1 compared with IR-2. Oncogenes were significantly enriched in the set of 262 differentially retained introns between the two IR clusters. Higher IR levels in IR-2 correlate with higher gene expression, consistent with detention of intron-containing transcripts in the nucleus in IR-2. Out of 258 genes encoding RNA-binding proteins (RBP) that were differentially expressed between IR-1 and IR-2, the motifs for seven RBPs were significantly enriched in the 262-intron set, and the expression of 25 RBPs were highly correlated with retention levels of 139 introns. Network analysis suggested that retention of introns in IR-2 could result from disruption of an RBP protein-protein interaction network previously linked to efficient intron removal. Finally, IR-based clusters developed for the majority of the 20 cancer types surveyed had two clusters with asymmetrical distributions of IR events like PDAC, with one cluster containing mostly intron loss events. Taken together, our findings suggest IR may be an important biomarker for subclassifying tumors.

Prognostic significance of survival-associated alternative splicing events in gastric cancer

Alternative splicing events are a major source of transcript and protein diversity in eukaryotes. Aberrant alternative splicing events have been increasingly reported in various cancers, including gastric cancer. To further explore the prognostic significance of alternative splicing events in gastric cancer patients, a comprehensive and systematic investigation was conducted by integrating alternative splicing event data and clinical information. Univariate Cox regression analysis identified 1383 alternative splicing events to be significantly associated with the overall survival of gastric cancer patients. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were performed for the development of prognostic signatures. The final prognostic signature based on all seven types of alternative splicing events can act as an independent prognostic indicator after multivariate adjustment of several clinical parameters. Furthermore, the correlation and function analysis identified CELF2, BAG2, RBFOX2, PTBP2 and QKI as hub splicing factors, and the focal adhesion signaling pathway was most significantly correlated with survival-associated alternative splicing events. The results of this study may establish a foundation for further research investigating the underlying mechanism of alternative splicing events in the progression of gastric cancer.

Genome-Wide Analysis of Prognostic Alternative Splicing Signature and Splicing Factors in Lung Adenocarcinoma

Analysis of The Cancer Genome Atlas data revealed that alternative splicing (AS) events could serve as prognostic biomarkers in various cancer types. This study examined lung adenocarcinoma (LUAD) tissues for AS and assessed AS events as potential indicators of prognosis in our cohort. RNA sequencing and bioinformatics analysis were performed. We used SUPPA2 to analyze the AS profiles. Using univariate Cox regression analysis, overall survival (OS)-related AS events were identified. Genes relating to the OS-related AS events were imported into Cytoscape, and the CytoHubba application was run. OS-related splicing factors (SFs) were explored using the log-rank test. The relationship between the percent spliced-in value of the OS-related AS events and SF expression was identified by Spearman correlation analysis. We found 1957 OS-related AS events in 1151 genes, and most were protective factors. Alternative first exon splicing was the most frequent type of splicing event. The hub genes in the gene network of the OS-related AS events were FBXW11, FBXL5, KCTD7, UBB and CDC27. The area under the curve of the MIX prediction model was 0.847 for 5-year survival based on seven OS-related AS events. Overexpression of SFs CELF2 and SRSF5 was associated with better OS. We constructed a correlation network between SFs and OS-related AS events. In conclusion, we identified prognostic predictors using AS events that stratified LUAD patients into high- and low-risk groups. The discovery of the splicing networks in this study provides an insight into the underlying mechanisms.

The SRSF3-MBNL1-Acin1 circuit constitutes an emerging axis to lessen DNA fragmentation in colorectal cancer via an alternative splicing mechanism

Altered alternative splicing (AS) events are considered pervasive causes that result in the development of carcinogenesis. Herein, we identified reprogrammed expression and splicing profiles of Muscle blind-like protein 1 (MBNL1) transcripts in tumorous tissues compared to those of adjacent normal tissues dissected from individual colorectal cancer (CRC) patients using whole-transcriptome analyses. MBNL1 transcript 8 (MBNL1₈) containing exons 5 and 7 was majorly generated by cancerous tissues and CRC-derived cell lines compared with those of the normal counterparts. Interplay between the exonic CA-rich element and upregulated SRSF3 facilitated the inclusion of MBNL1 exons 5 and 7, which encode a bipartite nuclear localization signal (NLS) and conformational NLS. Moreover, abundant SRSF3 interfered with the autoregulatory mechanism involved in utilization of MBNL1 exons 5 and 7, resulting in enrichment of the MBNL1₈ isoform in cultured CRC cell lines. Subsequently, an increase in the MBNL1₈ isoform drove a shift in the apoptotic chromatin condensation inducer in nucleus 1-S (Acin1-S) isoform to the Acin1-L isoform, leading to diminished DNA fragmentation in cultured CRC cells under oxidative stress. Taken together, SRSF3-MBNL1-Acin1 was demonstrated to constitute an emerging axis which is relevant to proapoptotic signatures and post-transcriptional events of CRC cells.

Apoptosis in Cancer Cells Is Induced by Alternative Splicing of hnRNPA2/B1 Through Splicing of Bcl-x, a Mechanism that Can Be Stimulated by an Extract of the South African Medicinal Plant, Cotyledon orbiculata

Alternative splicing is deregulated in cancer and alternatively spliced products can be linked to cancer hallmarks. Targeting alternative splicing could offer novel effective cancer treatments. We investigated the effects of the crude extract of a South African medicinal plant, Cotyledon orbiculata, on cell survival of colon (HCT116) and esophageal (OE33 and KYSE70) cancer cell lines. Using RNASeq, we discovered that the extract interfered with mRNA regulatory pathways. The extract caused hnRNPA2B1 to splice from the hnRNPB1 to the hnRNPA2 isoform, resulting in a switch in the BCL2L1 gene from Bcl-xL to Bcl-xS causing activation of caspase-3-cleavage and apoptosis. Similar splicing effects were induced by the known anti-cancer splicing modulator pladienolide B. Knockdown of hnRNPB1 using siRNA resulted in decreased cell viability and increased caspase-3-cleavage, and over-expression of hnRNPB1 prevented the effect of C. orbiculata extract on apoptosis and cell survival. The effect of the hnRNPA2/B1 splicing switch by the C. orbiculata extract increased hnRNPA2B1 binding to Bcl-xl/s, BCL2, MDM2, cMYC, CD44, CDK6, and cJUN mRNA. These findings suggest that apoptosis in HCT116, OE33, and KYSE cancer cells is controlled by switched splicing of hnRNPA2B1 and BCL2L1, providing evidence that hnRNPB1 regulates apoptosis. Inhibiting this splicing could have therapeutic potential for colon and esophageal cancers. Targeting hnRNPA2B1 splicing in colon cancer regulates splicing of BCL2L1 to induce apoptosis. This approach could be a useful therapeutic strategy to induce apoptosis and restrain cancer cell proliferation and tumor progression. Here, we found that the extract of Cotyledon orbiculata, a South African medicinal plant, had an anti-proliferative effect in cancer cells, mediated by apoptosis induced by alternative splicing of hnRNPA2B1 and BCL2L1.

Identification of an alternative splicing signature as an independent factor in colon cancer

BACKGROUND

Colon cancer is a common malignant tumor with a poor prognosis. Abnormal alternative splicing (AS) events played a part in the occurrence and metastasis of the tumor. We aimed to develop a survival-associated AS signature in colon cancer.

METHODS

The Percent Spliced In values of AS events were available in The Cancer Genome Atlas (TCGA) SpliceSeq database. Univariate Cox analysis was carried out to detect the prognosis-related AS events. We created a predictive model on account of the survival-associated AS events, which was further validated with a training-testing group design. Kaplan-Meier analysis was applied to assess patient survival. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of this model. Meanwhile, the clinical relevance of the signature and its regulatory relationship with splicing factors (SFs) were also evaluated.

RESULTS

In total, 2132 survival-related AS events were identified from colon cancer samples. We developed an eleven-AS signature, in which the 5-year AUC value was 0.911. Meanwhile, the AUC values at five years were 0.782 and 0.855 in the testing and entire cohort, respectively. Multivariate Cox regression displayed that the T category and the risk score of the signature were independent risk factors of colon cancer survival. Also, we constructed an SFs-AS network based on 11 SFs and 48 AS events.

CONCLUSIONS

We identified an eleven-AS signature of colon cancer. This signature could be treated as an independent prognostic factor.

Prognostic alternative splicing signature in cervical squamous cell carcinoma

Basing on alternative splicing events (ASEs) databases, the authors herein aim to explore potential prognostic biomarkers for cervical squamous cell carcinoma (CESC). mRNA expression profiles and relevant clinical data of 223 patients with CESC were obtained from The Cancer Genome Atlas (TCGA). Correlated genes, ASEs and percent-splice-in (PSI) were downloaded from SpliceSeq, respectively. The PSI values of survival-associated alternative splicing events (SASEs) were used to construct the basis of a prognostic index (PI). A protein-protein interaction (PPI) network of genes related to SASEs was generated by STRING and analysed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Consequently, 41,776 ASEs were discovered in 19,724 genes, 2596 of which linked with 3669 SASEs. The PPI network of SASEs related genes revealed that TP53 and UBA52 were core genes. The low-risk group had a longer survival period than high-risk counterparts, both groups being defined according to PI constructed upon the top 20 splicing events or PI on the overall splicing events. The AUC value of ROC reached up to 0.88, demonstrating the prognostic potential of PI in CESC. These findings suggested that ASEs involve in the pathogenesis of CESC and may serve as promising prognostic biomarkers for this female malignancy.

Signatures of co-deregulated genes and their transcriptional regulators in colorectal cancer

The deregulated genes in colorectal cancer (CRC) vary significantly across different studies. Thus, a systems biology approach is needed to identify the co-deregulated genes (co-DEGs), explore their molecular networks, and spot the major hub proteins within these networks. We reanalyzed 19 GEO gene expression profiles to identify and annotate CRC versus normal signatures, single-gene perturbation, and single-drug perturbation signatures. We identified the co-DEGs across different studies, their upstream regulating kinases and transcription factors (TFs). Connectivity Map was used to identify likely repurposing drugs against CRC within each group. The functional changes of the co-upregulated genes in the first category were mainly associated with negative regulation of transforming growth factor β production and glomerular epithelial cell differentiation; whereas the co-downregulated genes were enriched in cotranslational protein targeting to the membrane. We identified 17 hub proteins across the co-upregulated genes and 18 hub proteins across the co-downregulated genes, composed of well-known TFs (MYC, TCF3, PML) and kinases (CSNK2A1, CDK1/4, MAPK14), and validated most of them using GEPIA2 and HPA, but also through two signature gene lists composed of the co-up and co-downregulated genes. We further identified a list of repurposing drugs that can potentially target the co-DEGs in CRC, including camptothecin, neostigmine bromide, emetine, remoxipride, cephaeline, thioridazine, and omeprazole. Similar analyses were performed in the co-DEG signatures in single-gene or drug perturbation experiments in CRC. MYC, PML, CDKs, CSNK2A1, and MAPKs were common hub proteins among all studies. Overall, we identified the critical genes in CRC and we propose repurposing drugs that could be used against them.

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

Background

Triple-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.

Methods

Transcriptome 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.

Results

We 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.

Conclusion

Our 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.

Genome-wide analyses of the prognosis-related mRNA alternative splicing landscape and novel splicing factors based on large-scale low grade glioma cohort

Alternative splicing (AS) changes are considered to be critical in predicting treatment response. Our study aimed to investigate differential splicing patterns and to elucidate the role of splicing factor (SF) as prognostic markers of low-grade glioma (LGG). We downloaded RNA-seq data from a cohort of 516 LGG tumors in The Cancer Genome Atlas and analyzed independent prognostic factors using LASSO regression and Cox proportional regression to build a network based on the correlation between SF-related survival AS events. We collected 100 patients from our center for immunohistochemistry and analyzed survival using χ2 test and Cox and Kaplan-Meier analyses. A total of 9,616 AS events related to LGG were screened and identified as well as established related models. Through analyzing specific splicing patterns in LGG, we screened 16 genes to construct a prognostic model to stratify the risk of LGG patients. Validation revealed that the expression level of the prognostic model in LGG tissue was increased, and patients with high expression showed worse prognosis. In summary, we demonstrated the role of SFs and AS events in the progression of LGG, which may provide insights into the clinical significance and aid the future exploration of LGG-associated AS.

Prognostic Value and Potential Role of Alternative mRNA Splicing Events in Cervical Cancer

Background

Increasing evidence suggests that aberrant alternative splicing (AS) events are associated with progression of cancer. This study evaluated the prognostic value and clarify the role of AS events in cervical cancer (CC).

Methods

Based on RNA-seq AS event data and clinical information of CC patients in The Cancer Genome Atlas (TCGA) database, we sought to identify prognosis-related AS events in this setting. We selected several survival-associated AS events to construct a prognostic predictor for CC through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Moreover, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed on genes with prognosis-related AS events and constructed an AS-splicing factors (SFs) regulatory network.

Results

2770 AS events were significantly correlated with overall survival (OS). The area under the curve (AUC) values of receiver-operator characteristic curve (ROC) for the final prognostic predictor were 0.926, 0.946 and 0.902 at 3, 5, and 10 years, respectively. These values indicated efficiency in prognostic risk stratification for patients with CC. The final prognostic predictor was an independent predictor of OS (HR: 1.24; 95% CI: 1.020–1.504; P < 0.05). The AS-SFs correlation network may reveal an underlying regulatory mechanism of AS events.

Conclusion

AS events are essential participants in the prognosis of CC and hold great potentials for the prognostic stratification and development of treatment strategy.

TNNT2 as a potential biomarker for the progression and prognosis of colorectal cancer

Colorectal cancer (CRC) is the third most common cancer worldwide. At present, there are limited effective biomarkers of CRC. The present study aimed to identify potential signatures associated with the tumorigenesis and prognosis of CRC using publicly available databases, and further validate the identified biomarkers in CRC cell lines. Identification of differentially expressed mRNAs between CRC and paracancerous samples was conducted based on data from The Cancer Genome Atlas (TCGA; 471 tumor samples and 41 normal samples). Survival analysis was performed to explore the prognostic value of troponin 2 (TNNT2) in the TCGA training set, which was further validated in an external dataset, GSE17531. Functional enrichment analysis was conducted to determine the possible biological functions using GSEA 3.0. Reverse transcription-quantitative PCR (RT-qPCR) and western blotting were utilized to detect the mRNA and protein expression levels of TNNT2 between CRC and normal colorectal cells. Immunohistochemistry was performed to detect the protein expression of TNNT2 in CRC and normal tissues. TNNT2 was significantly upregulated in CRC samples compared with adjacent normal samples in the TCGA dataset. Increased expression of TNNT2 was associated with inferior prognosis in the TCGA training dataset and GSE17531 validation dataset. Functional enrichment analysis revealed that the ErbB signaling pathway and glycerophospholipid metabolism pathway were significantly activated in the TNNT2 high expression group. Overexpression of TNNT2 mRNA and TNNT2 protein in CRC tumor cells was confirmed by RT-qPCR and western blotting, respectively. Immunohistochemistry indicated increased protein expression levels of TNNT2 in CRC tissues in comparison with normal tissues. TNNT2 was associated with the tumorigenesis and prognosis of CRC, which may be useful for novel biomarker identification and targeted therapeutic strategy development.

Comprehensive analysis of prognostic alternative splicing signature in cervical cancer

Background

Alternative splicing (AS) is a key factor in protein-coding gene diversity, and is associated with the development and progression of malignant tumours. However, the role of AS in cervical cancer is unclear.

Methods

The AS data for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq website. Few prognostic AS events were identified through univariate Cox analysis. We further identified the prognostic prediction models of the seven subtypes of AS events and assessed their predictive power. We constructed a clinical prediction model through global analysis of prognostic AS events and established a nomogram using the risk score calculated from the prognostic model and relevant clinical information. Unsupervised cluster analysis was used to explore the relationship between prognostic AS events in the model and clinical features.

Results

A total of 2860 prognostic AS events in cervical cancer were identified. The best predictive effect was shown by a single alternate acceptor subtype with an area under the curve of 0.96. Our clinical prognostic model included a nine-AS event signature, and the c-index of the predicted nomogram model was 0.764. SNRPA and CCDC12 were hub genes for prognosis-associated splicing factors. Unsupervised cluster analysis through the nine prognostic AS events revealed three clusters with different survival patterns.

Conclusions

AS events affect the prognosis and biological progression of cervical cancer. The identified prognostic AS events and splicing regulatory networks can increase our understanding of the underlying mechanisms of cervical cancer, providing new therapeutic strategies.

Identification of novel alternative splicing isoform biomarkers and their association with overall survival in colorectal cancer

BACKGROUND

Alternative splicing (AS) is an important mechanism of regulating eukaryotic gene expression. Understanding the most common AS events in colorectal cancer (CRC) will help developing diagnostic, prognostic or therapeutic tools in CRC.

METHODS

Publicly available RNA-seq data of 28 pairs of CRC and normal tissues and 18 pairs of metastatic and normal tissues were used to identify AS events using PSI and DEXSeq methods.

RESULT

The highly significant splicing events were used to search a database of The Cancer Genome Atlas (TCGA). We identified AS events in 9 genes in CRC (more inclusion of CLK1-E4, COL6A3-E6, CD44v8-10, alternative first exon regulation of ARHGEF9, CHEK1, HKDC1 and HNF4A) or metastasis (decrease of SERPINA1-E1a, CALD-E5b, E6). Except for CHEK1, all other 8 splicing events were confirmed by TCGA data with 382 CRC tumors and 51 normal controls. The combination of three splicing events was used to build a logistic regression model that can predict sample type (CRC or normal) with near perfect performance (AUC = 1). Two splicing events (COL6A3 and HKDC1) were found to be significantly associated with patient overall survival. The AS features of the 9 genes are highly consistent with previous reports and/or relevant to cancer biology.

CONCLUSIONS

The significant association of higher expression of the COL6A3 E5-E6 junction and HKDC1 E1-E2 with better overall survival was firstly reported. This study might be of significant value in the future biomarker, prognosis marker and therapeutics development of CRC.

Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer

Background

Alternative 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).

Methods

The 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.

Result

A 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.

Conclusion

This study systematically analyzed the role of AS events in EC and developed the prognostic model for EC.

Post-transcriptional regulation activity through alternative splicing involved in the effects of Aloe vera on the Wnt/β-catenin and Notch pathways in colorectal cancer cells

Aloe vera (L.) Burm.f. is widely used as laxative drugs, cosmetics, and functional food due to a variety of therapeutic effects. However, several studies indicated a colonic carcinogenic activity of Aloe vera. But the underline mechanism has not been well clarified. This study aimed to explore the potential mechanism at the post-transcriptional level. Identification of Differential Expressed Alternative Splicing (DEAS) genes and events and the corresponding functional enrichment analyses were conducted on RKO cells after treated with Aloe vera aqueous extract and its two active components, aloin and aloesin. And RT-qPCR was conducted for validation. Results indicated that they induced 2200, 2342 and 2133 DEAS events, respectively. The GO enrichment and the COG classification results of DEAS genes showed that they were associated with transcription, as well as functions like signal transduction mechanisms. Moreover, DEAS genes related to the two colorectal cancerous pathways, Wnt and Notch pathways, were annotated. In conclusion, aloe extract, aloin and aloesin significantly regulated the DEAS profile of RKO cells. The colonic carcinogenicity of Aloe vera may due to its post-transcriptional regulatory activity through Alternative Splicing (AS) on genes, especially on Wnt-related and Notch-related key genes.

Alternative Splicing Events as Indicators for the Prognosis of Uveal Melanoma

Growing evidence has revealed that abnormal alternative splicing (AS) events are closely related to carcinogenic processes. However, the comprehensive study on the prognostic value of splicing events involved in uveal melanoma (UM) is still lacking. Therefore, splicing data of 80 UM patients were obtained from the Cancer Genome Atlas (TCGA) SpliceSeq and RNA sequence data of UM and patient clinical features were downloaded from the Cancer Genome Atlas (TCGA) database to identify survival related splicing events in UM. As a result, a total of 37996 AS events of 17911 genes in UM were detected, among which 5299 AS events of 3529 genes were significantly associated with UM patients’ survival. Functional enrichment analysis revealed that this survival related splicing genes are corelated with mRNA catabolic process and ribosome pathway. Based on survival related splicing events, seven types of prognostic markers and the final overall prognostic signature could independently predict the overall survival of UM patients. Finally, an 11 spliced gene was identified in the final signature. On the basis of these 11 genes, we constructed a Support Vector Machine (SVM) classifier and evaluated it with leave-one-out cross-validation. The results showed that the 11 genes could determine short- and long-term survival with a predicted accuracy of 97.5%. Besides, the splicing factors and alternative splicing events correlation network was constructed to serve as therapeutic targets for UM treatment. Thus, our study depicts a comprehensive landscape of alternative splicing events in the prognosis of UM. The correlation network and associated pathways would provide additional potential targets for therapy and prognosis.

Putatively cancer-specific exon-exon junctions are shared across patients and present in developmental and other non-cancer cells

This study probes the distribution of putatively cancer-specific junctions across a broad set of publicly available non-cancer human RNA sequencing (RNA-seq) datasets. We compared cancer and non-cancer RNA-seq data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) Project and the Sequence Read Archive. We found that (i) averaging across cancer types, 80.6% of exon–exon junctions thought to be cancer-specific based on comparison with tissue-matched samples (σ = 13.0%) are in fact present in other adult non-cancer tissues throughout the body; (ii) 30.8% of junctions not present in any GTEx or TCGA normal tissues are shared by multiple samples within at least one cancer type cohort, and 87.4% of these distinguish between different cancer types; and (iii) many of these junctions not found in GTEx or TCGA normal tissues (15.4% on average, σ = 2.4%) are also found in embryological and other developmentally associated cells. These findings refine the meaning of RNA splicing event novelty, particularly with respect to the human neoepitope repertoire. Ultimately, cancer-specific exon–exon junctions may have a substantial causal relationship with the biology of disease.

Genome-wide profiling of prognosis-related alternative splicing signatures in sarcoma

BACKGROUND

Sarcomas (SARCs) are rare malignant tumors with poor prognosis. Increasing evidence has suggested that aberrant alternative splicing (AS) is strongly associated with tumor initiation and progression. We considered whether survival-related AS events might serve as prognosis predictors and underlying targeted molecules in SARC treatment.

METHODS

RNA-Seq data of the SARC cohort were downloaded from The Cancer Genome Atlas (TCGA) database. Survival-related AS events were selected by univariate and multivariate Cox regression analyses. Metascape was used for constructing a gene interaction network and performing functional enrichment analysis. Then, prognosis predictors were established based on statistically significant survival-related AS events and evaluated by receiver operator characteristic (ROC) curve analysis. Finally, the potential regulatory network was analyzed via Pearson's correlation between survival-related AS events and splicing factors (SFs).

RESULTS

A total of 3,610 AS events and 2,291 genes were found to be prognosis-related in 261 SARC samples. The focal adhesion pathway was identified as the most critical molecular mechanism corresponding to poor prognosis. Notably, several prognosis predictors based on survival-related AS events showed excellent performance in prognosis prediction. The area under the curve of the ROC of the risk score was 0.85 in the integrated predictor. The splicing network proved complicated regulation between prognosis-related SFs and AS events. Also, driver gene mutations were significantly associated with AS in SARC patients.

CONCLUSIONS

Survival-related AS events may become ideal indictors for the prognosis prediction of SARCs. Corresponding splicing regulatory mechanisms are worth further exploration.

The Intricate Interplay between Epigenetic Events, Alternative Splicing and Noncoding RNA Deregulation in Colorectal Cancer

Colorectal cancer (CRC) results from a transformation of colonic epithelial cells into adenocarcinoma cells due to genetic and epigenetic instabilities, alongside remodelling of the surrounding stromal tumour microenvironment. Epithelial-specific epigenetic variations escorting this process include chromatin remodelling, histone modifications and aberrant DNA methylation, which influence gene expression, alternative splicing and function of non-coding RNA. In this review, we first highlight epigenetic modulators, modifiers and mediators in CRC, then we elaborate on causes and consequences of epigenetic alterations in CRC pathogenesis alongside an appraisal of the complex feedback mechanisms realized through alternative splicing and non-coding RNA regulation. An emphasis in our review is put on how this intricate network of epigenetic and post-transcriptional gene regulation evolves during the initiation, progression and metastasis formation in CRC.

Genome-Wide Profiling of Prognostic Alternative Splicing Pattern in Pancreatic Cancer

Alternative splicing (AS) has a critical role in tumor progression and prognosis. Our study aimed to investigate pancreatic cancer-specific AS events using RNA-seq data, gaining systematic insights into potential prognostic predictors. We downloaded 10,623 genes with 45,313 pancreatic cancer-specific AS events from the Cancer Genome Atlas (TCGA) and SpliceSeq database. Cox univariate analyses of overall survival suggested there was a remarkable association between 6,711 AS events and overall survival in pancreatic cancer patients (P < 0.05). The area under the curves (AUC) of the receiver operator characteristic curves (ROC) of risk score was 0.89 for final prognostic predictor. Results indicated that AS events of DAZAP1, RBM4, ESRP1, QKI, and SF1 were significantly associated with overall survival. The results of FunRich showed that transcription factors KLF7, GABPA, and SP1 were the most highly related to survival-associated AS genes. Furthermore, using DriverDBv2, we identified 13 driver genes associated with survival-associated AS events, including TP53 and CDC27. Thus, we concluded that the aberrant AS patterns in pancreatic cancer patients might serve as prognostic predictors.