Pan-cancer analysis of clinical relevance of alternative splicing events in 31 human cancers

Expression of Truncated Products at the 5'-Terminal Region of RIPK2 and Evolutive Aspects that Support Their Biological Importance

Alternative splicing is the process of generating different mRNAs from the same primary transcript, which contributes to increase the transcriptome and proteome diversity. Abnormal splicing has been associated with the development of several diseases including cancer. Given that mutations and abnormal levels of the RIPK2 transcript and RIP-2 protein are frequent in tumors, and that RIP-2 modulates immune and inflammatory responses, we investigated alternative splicing events that result in partial deletions of the kinase domain at the N-terminus of RIP-2. We also investigated the structure and expression of the RIPK2 truncated variants and isoforms in different environments. In addition, we searched data throughout Supraprimates evolution that could support the biological importance of RIPK2 alternatively spliced products. We observed that human variants and isoforms were differentially regulated following temperature stress, and that the truncated transcript was more expressed than the long transcript in tumor samples. The inverse was found for the longer protein isoform. The truncated variant was also detected in chimpanzee, gorilla, hare, pika, mouse, rat, and tree shrew. The fact that the same variant has been preserved in mammals with divergence times up to 70 million years raises the hypothesis that it may have a functional significance.

CaTCH: Calculating transcript complexity of human genes

The findings based on whole transcriptome sequencing suggest that alternative splicing occurs in approximately 95% of human multi-exon genes, thus, playing a crucial role in promoting proteome diversity. According to the latest GENCODE annotations, most genes have less than four transcripts, positively correlating with the number of exons. Thus, it is more accurate to measure the splice variant efficiency of a gene with respect to the number of exons, which is a measure of Transcript Complexity (TC). In addition to that, the theoretical number of transcripts is substantially higher than the actual number of transcripts produced by Alternative Splicing Events, and the features restricting this phenomenon need to be explored. In this method, we have extracted the data of various features contributing to TC from different databases. Linear regression is used to identify the determinant features and to train and test the model of TC. The results indicate that exon length is the determining feature of TC, followed by coding potential, presence of chromatin signature, and 5' splice site dinucleotide, all of which negatively affect a gene's TC, except exon length. To further classify the genes based on TC, random forest is used to identify the determinant features.•The splicing efficiency of a gene can be inferred by the transcript complexity, which is the number of transcripts per exon.•CaTCH is a linear regression-based model to calculate the transcript complexity of human genes, which can be calculated from the exon length, coding potentiality, presence of chromatin signature/s, and 5' splice site dinucleotide.

Expression landscape of cancer-FOXP3 and its prognostic value in pancreatic adenocarcinoma

FOXP3, a key identifier of Treg, has also been identified in tumor cells, which is referred to as cancer-FOXP3 (c-FOXP3). Human c-FOXP3 undergoes multiple alternative splicing events, generating several isoforms, like c-FOXP3FL and c-FOXP3Δ3. Previous research on c-FOXP3 often ignore its cellular source (immune or tumor cells) and isoform expression patterns, which may obscure our understanding of its clinical significance. Our immunohistochemistry investigations which conducted across 18 tumors using validated c-FOXP3 antibodies revealed distinct expression landscapes for c-FOXP3 and its variants, with the majority of tumors exhibited a predominantly expression of c-FOXP3Δ3. In pancreatic ductal adenocarcinoma (PDAC), we further discovered a potential link between nuclear c-FOXP3Δ3 in tumor cells and poor prognosis. Overexpression of c-FOXP3Δ3 in tumor cells was associated with metastasis. This work elucidates the expression pattern of c-FOXP3 in pan-cancer and indicates its potential as a prognostic biomarker in clinical settings, offering new perspectives for its clinical application.

Alternative splicing in prostate cancer progression and therapeutic resistance

Prostate cancer (CaP) remains the second leading cause of cancer deaths in western men. CaP mortality results from diverse molecular mechanisms that mediate resistance to the standard of care treatments for metastatic disease. Recently, alternative splicing has been recognized as a hallmark of CaP aggressiveness. Alternative splicing events cause treatment resistance and aggressive CaP behavior and are determinants of the emergence of the two major types of late-stage treatment-resistant CaP, namely castration-resistant CaP (CRPC) and neuroendocrine CaP (NEPC). Here, we review recent multi-omics data that are uncovering the complicated landscape of alternative splicing events during CaP progression and the impact that different gene transcript isoforms can have on CaP cell biology and behavior. We discuss renewed insights in the molecular machinery by which alternative splicing occurs and contributes to the failure of systemic CaP therapies. The potential for alternative splicing events to serve as diagnostic markers and/or therapeutic targets is explored. We conclude by considering current challenges and promises associated with splicing-modulating therapies, and their potential for clinical translation into CaP patient care.

Alternative Polyadenylation Regulatory Factors Signature for Survival Prediction in Kidney Renal Cell Carcinoma

Background

Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors.

Objective

Whether APA regulatory factors affect the prognosis of renal cell carcinoma remains unclear, and this is the main topic of this study.

Methods

We downloaded the transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database. We used the Lasso regression system to construct an APA model for analyzing the relationship between common APA regulatory factors and renal cell carcinoma. We also validated our APA model using independent GEO datasets (GSE29609, GSE76207).

Results

It was found that the expression levels of 5 APA regulatory factors (CPSF1, CPSF2, CSTF2, PABPC1, and PABPC4) were significantly associated with tumor gene mutation burden (TMB) score in renal clear cell carcinoma, and the risk score constructed using the expression level of 5 key APA regulatory factors could be used to predict the outcome of renal clear cell carcinoma. The TMB score is associated with the remodeling of the immune microenvironment.

Conclusions

By identifying key APA regulatory factors in renal cell carcinoma and constructing risk scores for key APA regulatory factors, we showed that key APA regulators affect prognosis of renal clear cell carcinoma patients. In addition, the risk score level is associated with TMB, indicating that APA may affect the efficacy of immunotherapy through immune microenvironment-related genes. This helps us better understand the mRNA processing mechanism of renal clear cell carcinoma.

Large-scale analysis reveals splicing biomarkers for tuberculosis progression and prognosis

BACKGROUND

Emerging evidence suggests that aberrant alternative splicing (AS) may play an important role in tuberculosis (TB). However, current knowledge regarding the value of AS in TB progression and prognosis remains unclear.

METHOD

Public RNA-seq datasets related to TB progression and prognosis were searched and AS analyses were conducted based on SUPPA2. Percent spliced in (PSI) was used for quantifying AS events and multiple machine learning (ML) methods were employed to construct predictive models. Area under curve (AUC), sensitivity and specificity were calculated to evaluate the model performance.

RESULTS

A total of 1587 samples from 7 datasets were included. Among 923 TB-progression related differential AS events (DASEs), 3 events (GET1-skipping exon (SE), TPD52-alternative first exons (AF) and TIMM10-alternative 5' splice site (A5)) were selected as candidate biomarkers; however, their predictive performance was limited. For TB prognosis, 5 events (PHF23-AF, KIF1B-SE, MACROD2-alternative 3' splice site (A3), CD55-retained intron (RI) and GALNT11-AF) were selected as candidates from the 1282 DASEs. Six ML methods were used to integrate these 5 events and XGBoost outperformed than others. AUC, sensitivity and specificity of XGBoost model were 0.875, 81.1% and 83.5% in training set, while they were 0.805, 68.4% and 73.2% in test set.

CONCLUSION

GET1-SE, TPD52-AF and TIMM10-A5 showed limited role in predicting TB progression, while PHF23-AF, KIF1B-SE, MACROD2-A3, CD55-RI and GALNT11-AF could well predict TB prognosis and work as candidate biomarkers. This work preliminarily explored the value of AS in predicting TB progression and prognosis and offered potential targets for further research.

An Inflammatory Checkpoint Generated by IL1RN Splicing Offers Therapeutic Opportunity for KRAS-Mutant Intrahepatic Cholangiocarcinoma

KRAS mutations are causally linked to protumor inflammation and are identified as driving factors in tumorigenesis. Here, using multiomics data gathered from a large set of patients, we showed that KRAS mutation was associated with a specific landscape of alternative mRNA splicing that connected to myeloid inflammation in intrahepatic cholangiocarcinoma (iCCA). Then, we identified a negative feedback mechanism in which the upregulation of interleukin 1 receptor antagonist (IL1RN)-201/203 due to alternative splicing confers vital anti-inflammatory effects in KRAS-mutant iCCA. In KRAS-mutant iCCA mice, both IL1RN-201/203 upregulation and anakinra treatment ignited a significant antitumor immune response by altering neutrophil recruitment and phenotypes. Furthermore, anakinra treatment synergistically enhanced anti-PD-1 therapy to activate intratumoral GZMB+ CD8+ T cells in KRAS-mutant iCCA mice. Clinically, we found that high IL1RN-201/203 levels in patients with KRAS-mutant iCCA were significantly associated with superior response to anti-PD-1 immunotherapy.

SIGNIFICANCE

This work describes a novel inflammatory checkpoint mediated by IL1RN alternative splicing variants that may serve as a promising basis to develop therapeutic options for KRAS-mutant iCCA and other cancers. This article is featured in Selected Articles from This Issue, p. 2109.

Identification of alternative splicing associated with clinical features: from pan-cancers to genitourinary tumors

Background

Alternative splicing events (ASEs) are vital causes of tumor heterogeneity in genitourinary tumors and many other cancers. However, the clinicopathological relevance of ASEs in cancers has not yet been comprehensively characterized.

Methods

By analyzing splicing data from the TCGA SpliceSeq database and phenotype data for all TCGA samples from the UCSC Xena database, we identified differential clinical feature-related ASEs in 33 tumors. CIBERSORT immune cell infiltration data from the TIMER2.0 database were used for differential clinical feature-related immune cell infiltration analysis. Gene function enrichment analysis was used to analyze the gene function of ASEs related to different clinical features in tumors. To reveal the regulatory mechanisms of ASEs, we integrated race-related ASEs and splicing quantitative trait loci (sQTLs) data in kidney renal clear cell carcinoma (KIRC) to comprehensively assess the impact of SNPs on ASEs. In addition, we predicted regulatory RNA binding proteins in bladder urothelial carcinoma (BLCA) based on the enrichment of motifs around alternative exons for ASEs.

Results

Alternative splicing differences were systematically analyzed between different groups of 58 clinical features in 33 cancers, and 30 clinical features in 24 cancer types were identified to be associated with more than 50 ASEs individually. The types of immune cell infiltration were found to be significantly different between subgroups of primary diagnosis and disease type. After integrating ASEs with sQTLs data, we found that 63 (58.9%) of the race-related ASEs were significantly SNP-correlated ASEs in KIRC. Gene function enrichment analyses showed that metastasis-related ASEs in KIRC mainly enriched Rho GTPase signaling pathways. Among those ASEs associated with metastasis, alternative splicing of GIT2 and TUBB3 might play key roles in tumor metastasis in KIRC patients. Finally, we identified several RNA binding proteins such as PCBP2, SNRNP70, and HuR, which might contribute to splicing differences between different groups of neoplasm grade in BLCA.

Conclusion

We demonstrated the significant clinical relevance of ASEs in multiple cancer types. Furthermore, we identified and validated alternative splicing of TUBB3 and RNA binding proteins such as PCBP2 as critical regulators in the progression of urogenital cancers.

Integrated multiomic analysis and high-throughput screening reveal potential gene targets and synergetic drug combinations for osteosarcoma therapy

Although great advances have been made over the past decades, therapeutics for osteosarcoma are quite limited. We performed long-read RNA sequencing and tandem mass tag (TMT)-based quantitative proteome on osteosarcoma and the adjacent normal tissues, next-generation sequencing (NGS) on paired osteosarcoma samples before and after neoadjuvant chemotherapy (NACT), and high-throughput drug combination screen on osteosarcoma cell lines. Single-cell RNA sequencing data were analyzed to reveal the heterogeneity of potential therapeutic target genes. Additionally, we clarified the synergistic mechanisms of doxorubicin (DOX) and HDACs inhibitors for osteosarcoma treatment. Consequently, we identified 2535 osteosarcoma-specific genes and several alternative splicing (AS) events with osteosarcoma specificity and/or patient heterogeneity. Hundreds of potential therapeutic targets were identified among them, which showed the core regulatory roles in osteosarcoma. We also identified 215 inhibitory drugs and 236 synergistic drug combinations for osteosarcoma treatment. More interestingly, the multiomic analysis pointed out the pivotal role of HDAC1 and TOP2A in osteosarcoma. HDAC inhibitors synergized with DOX to suppress osteosarcoma both in vitro and in vivo. Mechanistically, HDAC inhibitors synergized with DOX by downregulating SP1 to transcriptionally modulate TOP2A expression. This study provided a comprehensive view of molecular features, therapeutic targets, and synergistic drug combinations for osteosarcoma.

Integrated Analysis of Transcriptome Changes in Osteoarthritis: Gene Expression, Pathways and Alternative Splicing

OBJECTIVE

Osteoarthritis (OA) is the most prevalent joint disease characterized by the degeneration of articular cartilage and the remodeling of its underlying bones, resulting in pain and loss of function in the knees and hips. As far as we know, no curative treatments are available except for the joint replacement. The precise molecular mechanisms which are involved in the degradation of cartilage matrix and development of osteoarthritis are still unclear.

DESIGN

By analyzing RNA-seq data, we found the molecular changes at the transcriptome level such as alternative splicing, gene expression, and molecular pathways in OA knees cartilage.

RESULTS

Expression analysis have identified 457 differential expressed genes including 266 up-regulated genes such as TNFSF15, ST6GALNAC5, TGFBI, ASPM, and TYM, and 191 down-regulated genes such as ADM, JUN, IRE2, PIGA, and MAFF. Gene set enrichment analysis (GSEA) analysis identified down-regulated pathways related to translation, transcription, immunity, PI3K/AKT, and circadian as well as disturbed pathways related to extracellular matrix and collagen. Splicing analysis identified 442 differential alternative splicing events within 284 genes in osteoarthritis, including genes involved in extracellular matrix (ECM) and alternative splicing, and TIA1 was identified as a key regulator of these splicing events.

CONCLUSIONS

These findings provide insights into disease etiology, and offer favorable information to support the development of more effective interventions in response to the global clinical challenge of osteoarthritis.

Alternative splicing: a new breakthrough for understanding tumorigenesis and potential clinical applications

BACKGROUND

Alternative splicing (AS) is a post-transcriptional process that produces transcript variants, thus leading to transcriptome complexity. Recently, the scope of AS studies has been greatly expanded toward clinical applications owing to the abundance of RNA sequencing data.

OBJECTIVE

This review consists of two parts. We first summarize bioinformatic resources that are useful for large-scale cancer-related AS studies. We then highlight the research efforts to utilize AS events for predicting clinical outcomes and planning therapeutic strategies.

RESULTS

Computational approaches to interrogate AS events have been reviewed under three categories: (1) databases to provide functional and clinical annotation of AS events, (2) analytical tools to identify cancer-associated AS event, and (3) methods to identify splicing-related DNA variants and splicing-derived neoantigens. We also present the recent progress in exploring the clinical utility of AS under four categories: (1) identification of AS events for cancer prognosis, (2) utilization of AS events in molecular classification of various cancers, (3) regulatory mechanisms of AS underlying drug resistance, and (4) potential use of AS in cancer therapy.

CONCLUSION

This review will be helpful for understanding the biological implications of AS in cancer and facilitate the development of AS markers for cancer prognosis and treatment. We anticipate that future studies will lead to the application of genome-wide AS profiles in cancer precision medicine.

COL3A1: Potential prognostic predictor for head and neck cancer based on immune-microenvironment alternative splicing

We aimed to identify a novel prognostic biomarker for head and neck squamous cell carcinoma (HNSCC) based on tumor immunology-related alternative splicing (AS). Data for 502 HNSCC and 44 normal samples were obtained from the TCGA database and used to establish an AS-related risk model through univariate, least absolute shrinkage, and selection operator Cox regression analyses. Fresh HNSCC and normal oral tissues were surgically obtained from 44 HNSCC patients. Western blotting and quantitative reverse transcription-PCR were used to assess gene expression levels. Kaplan-Meier was performed to evaluate patients' overall survival (OS) rate. The CIBERSORT algorithm, single-sample gene set enrichment analysis, and immune checkpoint analyses were performed to compare immune activities between subgroups. The risk model was established using 10 pivotal AS events first. Collagen Type III Alpha 1 Chain (COL3A1) were screened based on |log2FC| ≥ 1 and FDR < 0.05 criteria. COL3A1 expression levels in HNSCC tissues were elevated relative to normal tissues (p < 0.001). Moreover, COL3A1 was a reliable biomarker for HNSCC patients' prognostic prediction in both cohorts (p < 0.001, p = 0.0085, respectively). COL3A1 protein (p = 0.0054) and mRNA (p < 0.0001) levels were correlated with HNSCC differentiation. Furthermore, the T stage was correlated with COL3A1 expression (p = 0.043), and COL3A1 expression was an independent prognostic predictor for HNSCC patients (p = 0.006). Compared with the risk model, COL3A1 was better at evaluating immune cell infiltrations, immune activities, and immune checkpoint gene expressions of HNSCC lesions.

Identification of drug targets and prognosis projection for uterine carcinosarcoma based on alternative splicing events

BACKGROUND

Uterine carcinosarcoma (UCS) is an invasive variant of endometrial cancer. The complicated heterogeneity and low frequency of UCS suggest the relevant research is lack. There is an urgent need to further explore the pathogenic mechanism and identify new biomarkers of UCS from different angels to improve its diagnosis and prognosis.

OBJECTIVE

This study is to explore the importance of alternative splicing (AS) events in UCS, construct AS-based prognosis model and excavate key splicing factors (SFs).

METHOD

UCS related gene transcriptome data and AS events data were collected from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq database. The AS events related to survival were determined by Cox regression analysis, Least absolute shrinkage and selection operator (Lasso) regression analysis and optimal subset analysis. The corresponding risk score was calculated and its efficiency on prognosis was evaluated by Kaplan-Meier (K-M) survival estimate and validated by the receiver operating characteristic (ROC) curve. The prognosis model was constructed with risk score and clinic characters as independent variables to predict patients' survival. On the other hand, Kendall test was applied to inspect the correlation between the SFs and the prognosis-related AS events and a AS-SF network was constructed. Finally, the key SFs were screened through network nodes analysis and survival analysis.

RESULT

Seven AS events the most related to survival were detected and the risk score was obtained. K-M survival estimate and ROC curve validation suggested the risk score was effective. Then Cox model was constructed based on the risk score and a nomogram model was obtained which provided the highest prediction accuracy of 95%. Through the AS-SF network analysis, 16 SFs were screened, among which four survival-related SFs were eventually obtained.

CONCLUSION

The prognosis model could predict the survival rate of UCS patients by their clinical characters and AS-based risk score. And four newly discovered SFs could reveal the molecular mechanism of UCS and act as the potential drug targets and prognosis biomarkers.

Knowledge mapping of alternative splicing of cancer from 2012 to 2021: A bibliometric analysis

Background

As a processing method of RNA precursors, alternative splicing (AS) is critical to normal cellular activities. Aberrant AS events are associated with cancer development and can be promising targets to treat cancer. However, no detailed and unbiased study describes the current state of AS of cancer research. We aim to measure and recognize the current state and trends of AS cancer research in this study.

Methods

The Web of Science Core Collection was used to acquire the articles. Utilizing three bibliometric tools (CiteSpace, VOSviewer, R-bibliometrix), we were able to measure and recognize the influence and collaboration data of individual articles, journals, and co-citations. Analysis of co-occurrence and burst information helped us identify the trending research areas related to AS of cancer.

Results

From 2012 to 2021, the total number of papers on AS of cancer published in 766 academic journals was 3,507, authored by 20,406 researchers in 405 institutions from 80 countries/regions. Research involving AS of cancer genes was primarily conducted in the United States and China; simultaneously, the Chinese Academy of Sciences, Fudan University, and National Cancer Institute were the institutions with strong research capabilities. Scorilas Andreas is the scholar with the most publications, while the most co-citations were generated by Wang, Eric T. Plos One published the most papers on AS of cancer, while J Biol Chem was the most co-cited academic journal in this field. The results of keyword co-occurrence analysis can be divided into three types: molecular (P53, CD44, androgen receptor, srsf3, esrp1), pathological process (apoptosis, EMT, metastasis, angiogenesis, proliferation), and disease (breast cancer, colorectal cancer, prostate cancer, hepatocellular carcinoma, gastric cancer).

Conclusion

Research on AS of cancer has been increasing in intensity over the past decade. Current AS of cancer studies focused on the hallmarks of AS in cancer and AS signatures including diagnostic and therapeutic targets. Among them, the current trends are splicing factors regulating epithelial-mesenchymal transition and other hallmarks, aberrant splicing events in tumors, and further mechanisms. These might give researchers interested in this field a forward-looking perspective and inform further research.

Broad misappropriation of developmental splicing profile by cancer in multiple organs

Oncogenesis mimics key aspects of embryonic development. However, the underlying mechanisms are incompletely understood. Here, we demonstrate that the splicing events specifically active during human organogenesis, are broadly reactivated in the organ-specific tumor. Such events are associated with key oncogenic processes and predict proliferation rates in cancer cell lines as well as patient survival. Such events preferentially target nitrosylation and transmembrane-region domains, whose coordinated splicing in multiple genes respectively affect intracellular transport and N-linked glycosylation. We infer critical splicing factors potentially regulating embryonic splicing events and show that such factors are potential oncogenic drivers and are upregulated specifically in malignant cells. Multiple complementary analyses point to MYC and FOXM1 as potential transcriptional regulators of critical splicing factors in brain and liver. Our study provides a comprehensive demonstration of a splicing-mediated link between development and cancer, and suggest anti-cancer targets including splicing events, and their upstream splicing and transcriptional regulators.

AS-CMC: a pan-cancer database of alternative splicing for molecular classification of cancer

Alternative splicing (AS) is a post-transcriptional regulation that leads to the complexity of the transcriptome. Despite the growing importance of AS in cancer research, the role of AS has not been systematically studied, especially in understanding cancer molecular classification. Herein, we analyzed the molecular subtype-specific regulation of AS using The Cancer Genome Atlas data and constructed a web-based database, named Alternative Splicing for Cancer Molecular Classification (AS-CMC). Our system harbors three analysis modules for exploring subtype-specific AS events, evaluating their phenotype association, and performing pan-cancer comparison. The number of subtype-specific AS events was found to be diverse across cancer types, and some differentially regulated AS events were recurrently found in multiple cancer types. We analyzed a subtype-specific AS in exon 11 of mitogen-activated protein kinase kinase 7 (MAP3K7) as an example of a pan-cancer AS biomarker. This AS marker showed significant association with the survival of patients with stomach adenocarcinoma. Our analysis revealed AS as an important determinant for cancer molecular classification. AS-CMC is the first web-based resource that provides a comprehensive tool to explore the biological implications of AS events, facilitating the discovery of novel AS biomarkers.

Cooperation and competition by RNA-binding proteins in cancer

Post-transcriptional regulation of gene expression plays a major role in determining the cellular proteome in health and disease. Post-transcriptional control mechanisms are disrupted in many cancers, contributing to multiple processes of tumorigenesis. RNA-binding proteins (RBPs), the main post-transcriptional regulators, often show altered expression and activity in cancer cells. Dysregulation of RBPs contributes to many cancer phenotypes, functioning in complex regulatory networks with other cellular players such as non-coding RNAs, signaling mediators and transcription factors to alter the expression of oncogenes and tumor suppressor genes. RBPs often function combinatorially, based on their binding to target sequences/structures on shared mRNA targets, to regulate the expression of cancer-related genes. This gives rise to cooperativity and competition between RBPs in mRNA binding and resultant functional outcomes in post-transcriptional processes such as mRNA splicing, stability, export and translation. Cooperation and competition is also observed in the case of interaction of RBPs and microRNAs with mRNA targets. RNA structural change is a common mechanism mediating the cooperative/competitive interplay between RBPs and between RBPs and microRNAs. RNA modifications, leading to changes in RNA structure, add a new dimension to cooperative/competitive binding of RBPs to mRNAs, further expanding the RBP regulatory landscape. Therefore, cooperative/competitive interplay between RBPs is a major determinant of the RBP interactome and post-transcriptional regulation of gene expression in cancer cells.

Harnessing gene fusion-derived neoantigens for 'cold' breast and prostate tumor immunotherapy

Breast and prostate cancers are generally considered immunologically 'cold' tumors due to multiple mechanisms rendering them unresponsive to immune checkpoint blockade therapies. With little success in garnering positive outcomes in modern immunotherapeutic clinical trials, it is prudent to re-examine the role of immunogenic neoantigens in these cold tumors. Gene fusions are driver mutations in hormone-driven cancers that can result in alternative mutation-specific neoantigens to promote immunotherapy sensitivity. This review focuses on 1) gene fusion formation mechanisms in neoantigen generation; 2) gene fusion neoantigens in cancer immunotherapeutic strategies and associated clinical trials; and 3) challenges and opportunities in computational and liquid biopsy technologies. This review is anticipated to initiate further research into gene fusion neoantigens of cold tumors for further experimental validation.

Alternative splicing signatures of congenital heart disease and induced pluripotent stem cell-derived cardiomyocytes from congenital heart disease patients

Congenital heart disease (CHD) is the most serious congenital defect in newborns with higher mortality. Alternative splicing (AS) plays an essential role in numerous heart diseases. However, our understanding of the link between mRNA splicing and CHD in humans is limited. Here, we try to investigate the genome-wide AS events in CHD using bioinformatics methods. We collected available RNA-seq datasets of CHD-induced pluripotent stem cell-cardiomyocytes (iPSC-CMs) (including single ventricle disease [SVD] and tetralogy of Fallot [TOF]) and non-CHD from the Gene Expression Omnibus database. Then, we unprecedentedly performed AS profiles in CHD-iPSC-CMs and non-CHD-iPSC-CMs. The rMAPS was used to generate RNA-maps for the analysis of RNA-binding proteins' (RBPs) binding sites. We used StringTie to identify and quantify the transcripts from aligned RNA-Seq reads. A quantification matrix was generated with respect to different groups by extracting the transcripts per million values from StringTie outputs. Then, this matrix was used for correlation analysis between the expression level of RBP and AS level. Finally, we validated our AS results using RNA-seq data from CHD and non-CHD patient tissue samples. We identified CHD-related AS events using CHD-iPSC-CMs and CHD samples from patients. The results showed that functional enrichment of abnormal AS in SVD and TOF was transcription factor-related. Using rMAPS, RNA-binding proteins which regulated these AS were also determined, and RBP-AS regulatory network was constructed. Overall, we identified abnormal AS in CHD-iPSC-CMs and CHD samples from patients. We predicted AS regulators in SVD and TOF, respectively. At last, we concluded that AS played a key role in the pathogenesis of CHD.

The Role of Alternative Splicing in Cancer: Regulatory Mechanism, Therapeutic Strategy, and Bioinformatics Application

[Formula: see text] Alternative splicing (AS) can generate distinct transcripts and subsequent isoforms that play differential functions from the same pre-mRNA. Recently, increasing numbers of studies have emerged, unmasking the association between AS and cancer. In this review, we arranged AS events that are closely related to cancer progression and presented promising treatments based on AS for cancer therapy. Obtaining proliferative capacity, acquiring invasive properties, gaining angiogenic features, shifting metabolic ability, and getting immune escape inclination are all splicing events involved in biological processes. Spliceosome-targeted and antisense oligonucleotide technologies are two novel strategies that are hopeful in tumor therapy. In addition, bioinformatics applications based on AS were summarized for better prediction and elucidation of regulatory routines mingled in. Together, we aimed to provide a better understanding of complicated AS events associated with cancer biology and reveal AS a promising target of cancer treatment in the future.

Deciphering associations between three RNA splicing-related genetic variants and lung cancer risk

Limited efforts have been made in assessing the effect of genome-wide profiling of RNA splicing-related variation on lung cancer risk. In the present study, we first identified RNA splicing-related genetic variants linked to lung cancer in a genome-wide profiling analysis and then conducted a two-stage (discovery and replication) association study in populations of European ancestry. Discovery and validation were conducted sequentially with a total of 29,266 cases and 56,450 controls from both the Transdisciplinary Research in Cancer of the Lung and the International Lung Cancer Consortium as well as the OncoArray database. For those variants identified as significant in the two datasets, we further performed stratified analyses by smoking status and histological type and investigated their effects on gene expression and potential regulatory mechanisms. We identified three genetic variants significantly associated with lung cancer risk: rs329118 in JADE2 (P = 8.80E-09), rs2285521 in GGA2 (P = 4.43E-08), and rs198459 in MYRF (P = 1.60E-06). The combined effects of all three SNPs were more evident in lung squamous cell carcinomas (P = 1.81E-08, P = 6.21E-08, and P = 7.93E-04, respectively) than in lung adenocarcinomas and in ever smokers (P = 9.80E-05, P = 2.70E-04, and P = 2.90E-05, respectively) than in never smokers. Gene expression quantitative trait analysis suggested a role for the SNPs in regulating transcriptional expression of the corresponding target genes. In conclusion, we report that three RNA splicing-related genetic variants contribute to lung cancer susceptibility in European populations. However, additional validation is needed, and specific splicing mechanisms of the target genes underlying the observed associations also warrants further exploration.

The exon 12-containing LHX6 isoforms promote cervical cancer cell proliferation by regulating the MAPK signaling pathway

LIM homeobox 6 (LHX6) has been reported to be downregulated and inhibits cell proliferation in various cancers. Alternative splicing of LHX6 leads to six annotated isoforms, which can be found in the NCBI database. However, the expression patterns and potential roles of these isoforms remain poorly characterized in cervical cancer. Here, we demonstrated that the LHX6 isoforms containing exon 12 (LHX6^EX(+12) group) and isoforms lacking exon 12 (LHX6^EX(-12) group) were differentially expressed in cervical tissue by qRT-PCR. The mRNA expression level of LHX6^EX(+12) group was higher than that of LHX6^EX(-12) group in cervical cancer tissue. Knockdown of LHX6^EX(+12) group and all LHX6 isoforms (LHX6^All group) inhibited cell growth, increased cell apoptosis, and induced cell cycle arrest from G0/G1 phase to S phase in vitro. Consistently, overexpression of the LHX6^EX(+12) group promoted cervical cancer cell proliferation in vitro. In contrast, no significant differences in cell proliferation were found between LHX6^EX(-12) isoform knockdown group and its control. RNA-sequencing suggested that the LHX6^EX(+12) isoform group might exert its cancer-promoting effects in cervical cancer via regulating MAPK signaling pathway. Downregulation of the LHX6^EX(+12) group significantly suppressed the phosphorylation of MRK, ERK, JNK, and P38 at the protein level. We also identified some unique biological processes and signaling pathways in which each isoform group might be involved. In summary, our results indicated that LHX6^EX(+12) isoform group was the dominant oncogenic type of LHX6 in cervical cancer, which may be a new biomarker and a potential precise therapeutic target for cervical cancer in the future.

Dissection of molecular and histological subtypes of papillary thyroid cancer using alternative splicing profiles

Despite growing evidence of the relevance of alternative splicing (AS) to cancer development and progression, the biological implications of AS for tumor behaviors, including papillary thyroid cancer (PTC), remain elusive. With the aim of further understanding the molecular and histological subtypes of PTC, we in this study explored whether AS events might act as new molecular determinants. For this purpose, AS profiles were analyzed in RNA-sequencing data from The Cancer Genome Atlas (TCGA) and from a Korean patient dataset. A total of 23 distinct exon-skipping (ES) events that correlated significantly with PTC oncogenic activity and differentiation scores were identified. The two top-ranked ES events, NUMA1_17515 in exon 18 of NUMA1 and TUBB3_38175 in exon 6 of TUBB3, showed high correlations with oncogenic activities and discriminated histological and molecular subtypes of PTC. Furthermore, two novel intron-retention (IR) events for TUBB3 were uncovered. All ES and IR events for the TUBB3 gene were predicted to induce nonsense-mediated mRNA decay. The relative abundances of intron reads in the PTC dataset from TCGA showed IR levels to differ significantly among PTC subtypes, possibly reflecting their different tumor behaviors. This study provides a landscape of AS changes among PTC subtypes and identified two significant AS events, NUMA1_17515 and TUBB3_38175, as potential AS biomarkers for PTC subclassification and characterization. The AS events identified in this study may be involved in the development of phenotypic differences underlying the functional characteristics and histological differentiation of PTCs.

Two potential biomarkers uncovered by scientists in South Korea may help more accurately classify subtypes of papillary thyroid cancer, the most common form of thyroid cancer, and improve treatment regimens. Ascertaining the correct papillary thyroid cancer (PTC) subtype is important for patient prognoses and treatment plans. Growing evidence suggests that cancer progression may be influenced by ‘alternative splicing’ events, alterations to mRNA that change the structure of mRNA transcripts and affect the function of encoded proteins. Yeun-Jun Chung and Sug Hyung Lee at the Catholic University of Korea, Seoul, and co-workers explored alternative splicing events in PTC patient samples. They identified 25 distinct events associated with oncogenic activity and differentiation between PTC subtypes. Of these, two events associated with two separate genes are particularly significant and could prove useful as biomarkers for disease classification and characterisation.

Pan-Cancer Transcriptome and Immune Infiltration Analyses Reveal the Oncogenic Role of Far Upstream Element-Binding Protein 1 (FUBP1)

Despite increasing evidence to support the relationship between FUBP1 and tumorigenesis in some types of cancers, there have been no analyses from a pan-cancer perspective. Here, we are the first to investigate the putative oncogenic role of FUBP1 in 33 cancer types based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Dysregulated FUBP1 expression was observed in most cancer types, and high FUBP1 expression suggests poor prognosis in cancers such as ACC, KICH, LIHC, LUAD, LUSC, SARC, CESC, and SKCM. Missense mutation is the most common type of FUBP1 mutation, and R430 in KH_4 is a predominant mutation site. Enhanced phosphorylation of FUBP1 at the S120 site has been observed in clear cell RCC, lung adenocarcinoma, and pediatric brain cancer specimens from African-American and Asian individuals. The expression of FUBP1 was found to be negatively correlated with the infiltration of CD8+ T lymphocytes in GBM, HNSC-HPV- and UCEC but positively correlated with that of tumor-associated fibroblasts in CESC, ESCA, HNSC, LIHC, LUAD, PAAD, and THYM. Furthermore, RNA splicing and spliceosome signaling were predominantly enriched in both GO and KEGG analyses of the functional mechanism of FUBP1. Briefly, this pan-cancer analysis comprehensively revealed the multifaceted characteristics and oncogenic role of FUBP1 in different human cancers.

Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer

Recent evidence suggests that splicing factors (SFs) and alternative splicing (AS) play important roles in cancer progression. We constructed four SF-risk-models using 12 survival-related SFs. In Luminal-A, Luminal-B, Her-2, and Basal-Like BRCA, SF-risk-models for three genes (PAXBP1, NKAP, and NCBP2), four genes (RBM15B, PNN, ACIN1, and SRSF8), three genes (LSM3, SNRNP200, and SNU13), and three genes (SRPK3, PUF60, and PNN) were constructed. These models have a promising prognosis-predicting power. The co-expression and protein-protein interaction analysis suggest that the 12 SFs are highly functional-connected. Pathway analysis and gene set enrichment analysis suggests that the functional role of the selected 12 SFs is highly context-dependent among different BRCA subtypes. We further constructed four AS-risk-models with good prognosis predicting ability in four BRCA subtypes by integrating the four SF-risk-models and 21 survival-related AS-events. This study proposed that SFs and ASs were potential multidimensional biomarkers for the diagnosis, prognosis, and treatment of BRCA.

OncoSplicing: an updated database for clinically relevant alternative splicing in 33 human cancers

Alternative splicing (AS) represents a crucial method in mRNA level to regulate gene expression and contributes to the protein complexity. Abnormal splicing has been reported to play roles in several diseases, including cancers. We developed the OncoSplicing database for visualization of survival-associated and differential alternative splicing in 2019. Here, we provide an updated version of OncoSplicing for an integrative view of clinically relevant alternative splicing based on 122 423 AS events across 33 cancers in the TCGA SpliceSeq project and 238 558 AS events across 32 cancers in the TCGA SplAdder project. The new version of the database contains several useful features, such as annotation of alternative splicing-associated transcripts, survival analysis based on median and optimal cut-offs, differential analysis between TCGA tumour samples and adjacent normal samples or GTEx normal samples, pan-cancer views of alternative splicing, splicing differences and results of Cox’PH regression, identification of clinical indicator-relevant and cancer-specific splicing events, and downloadable splicing data in the SplAdder project. Overall, the substantially updated version of OncoSplicing (www.oncosplicing.com) is a user-friendly and registration-free database for browsing and searching clinically relevant alternative splicing in human cancers.

Identification of prognostic alternative splicing events in sarcoma

Sarcoma is a rare malignancy with unfavorable prognoses. Accumulating evidence indicates that aberrant alternative splicing (AS) events are generally involved in cancer pathogenesis. The aim of this study was to identify the prognostic value of AS-related survival genes as potential biomarkers, and highlight the functional roles of AS events in sarcoma. RNA-sequencing and AS-event datasets were downloaded from The Cancer Genome Atlas (TCGA) sarcoma cohort and TCGA SpliceSeq, respectively. Survival-related AS events were further assessed using a univariate analysis. A multivariate Cox regression analysis was also performed to establish a survival-gene signature to predict patient survival, and the area-under-the-curve method was used to evaluate prognostic reliability. KOBAS 3.0 and Cytoscape were used to functionally annotate AS-related genes and to assess their network interactions. We detected 9674 AS events in 40,184 genes from 236 sarcoma samples, and the 15 most significant genes were then used to construct a survival regression model. We further validated the involvement of ten potential survival-related genes (TUBB3, TRIM69, ZNFX1, VAV1, KCNN2, VGLL3, AK7, ARMC4, LRRC1, and CRIP1) in the occurrence and development of sarcoma. Multivariate survival model analyses were also performed, and validated that a model using these ten genes provided good classifications for predicting patient outcomes. The present study has increased our understanding of AS events in sarcoma, and the gene-based model using AS-related events may serve as a potential predictor to determine the survival of sarcoma patients.

Identification of Novel Alternative Splicing Events Associated With Tumorigenesis, Protein Modification, and Immune Microenvironment in Early-Onset Gastric Cancer

Background

Alternative splicing (AS), e.g. the tandem alternative polyadenylation (TAPA), has emerged as major post-transcriptional modification events in human disease. However, the roles of the AS and TAPA in early-onset gastric cancer (EOGC) have not been revealed.

Methods

The global AS profiles of 80 EOGC patients were analyzed. The EOGC-specific AS events (ESASs) were identified in both the EOGC and adjacent non-tumor tissues. The functional enrichment analysis, Splicing network, Alternative Polyadenylation (APA) core factor network, and cell abundancy analysis were performed. Furthermore, the landscapes of the AS events in the varied subtypes of the EOGC patients were evaluated.

Results

Overall, 66,075 AS events and 267 ESASs were identified in the EOGC. Furthermore, 4809 genes and 6152 gene isoforms were found to be aberrantly expressed in the EOGC. The Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analyses showed that the significant pathway alterations might exist in these AS events, genes, and gene isoforms. Moreover, the Protein-protein interaction (PPI) network analysis revealed that the UBC, NEK2, EPHB2, and DCTN1 genes were the hub genes in the AS events in the EOGC. The immune cell infiltration analysis indicated a correlation between the AS events and the cancer immune microenvironment. The distribution of the AS events in varied EOGC subtypes, protein phosphorylation and glycosylation was uneven.

Conclusion

The study highlighted the vital roles of the AS in the EOGC, including modulating the specific protein modification and reshaping the cancer immune microenvironment, and yielded new insights into the diagnosis of the EOGC as well as cancer treatment.

Characterization of alternative splicing events and prognostic signatures in breast cancer

Background

Breast cancer (BRCA) is one of the most common cancers worldwide. Abnormal alternative splicing (AS) frequently observed in cancers. This study aims to demonstrate AS events and signatures that might serve as prognostic indicators for BRCA.

Methods

Original data for all seven types of splice events were obtained from TCGA SpliceSeq database. RNA-seq and clinical data of BRCA cohorts were downloaded from TCGA database. Survival-associated AS events in BRCA were analyzed by univariate COX proportional hazards regression model. Prognostic signatures were constructed for prognosis prediction in patients with BRCA based on survival-associated AS events. Pearson correlation analysis was performed to measure the correlation between the expression of splicing factors (SFs) and the percent spliced in (PSI) values of AS events. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted to demonstrate pathways in which survival-associated AS event is enriched.

Results

A total of 45,421 AS events in 21,232 genes were identified. Among them, 1121 AS events in 931 genes significantly correlated with survival for BRCA. The established AS prognostic signatures of seven types could accurately predict BRCA prognosis. The comprehensive AS signature could serve as independent prognostic factor for BRCA. A SF-AS regulatory network was therefore established based on the correlation between the expression levels of SFs and PSI values of AS events.

Conclusions

This study revealed survival-associated AS events and signatures that may help predict the survival outcomes of patients with BRCA. Additionally, the constructed SF-AS networks in BRCA can reveal the underlying regulatory mechanisms in BRCA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08305-6.

Alternative splicing perturbation landscape identifies RNA binding proteins as potential therapeutic targets in cancer

Alternative splicing (AS) plays an important role in gene regulation, and AS perturbations are frequently observed in cancer. RNA binding protein (RBP) is one of the molecular determinants of AS, and perturbations in RBP-gene network activity are causally associated with cancer development. Here, we performed a systematic analysis to characterize the perturbations in AS events across 18 cancer types. We showed that AS alterations were prevalent in cancer and involved in cancer-related pathways. Given that the extent of AS perturbation was associated with disease severity, we proposed a computational pipeline to identify RBP regulators. Pan-cancer analysis identified a number of conserved RBP regulators, which play important roles in regulating AS of genes involved in cancer hallmark pathways. Our application analysis revealed that the expression of 68 RBP regulators helped in cancer subtyping. Specifically, we identified four subtypes of kidney cancer with differences in cancer hallmark pathway activities and prognosis. Finally, we identified the small molecules that can potentially target the RBP genes and suggested potential candidates for cancer therapy. In summary, our comprehensive AS perturbation landscape analysis identified RBPs as potential therapeutic targets in cancer and provided novel insights into the regulatory functions of RBPs in cancer.

Comprehensive characterization of alternative splicing in renal cell carcinoma

Irregular splicing was associated with tumor formation and progression in renal cell carcinoma (RCC) and many other cancers. By using splicing data in the TCGA SpliceSeq database, RCC subtype classification was performed and splicing features and their correlations with clinical course, genetic variants, splicing factors, pathways activation and immune heterogeneity were systemically analyzed. In this research, alternative splicing was found useful for classifying RCC subtypes. Splicing inefficiency with upregulated intron retention and cassette exon was associated with advanced conditions and unfavorable overall survival of patients with RCC. Splicing characteristics like splice site strength, guanine and cytosine content and exon length may be important factors disrupting splicing balance in RCC. Other than cis-acting and trans-acting regulation, alternative splicing also differed in races and tissue types and is also affected by mutation conditions, pathway settings and the response to environmental changes. Severe irregular splicing in tumor not only indicated terrible intra-cellular homeostasis, but also changed the activity of cancer-associated pathways by different splicing effects including isoforms switching and expression regulation. Moreover, irregular splicing and splicing-associated antigens were involved in immune reprograming and formation of immunosuppressive tumor microenvironment. Overall, we have described several clinical and molecular features in RCC splicing subtypes, which may be important for patient management and targeting treatment.

Genome-Wide Analyses of Prognostic and Therapeutic Alternative Splicing Signatures in Bladder Urothelial Carcinoma

Background

Alternative splicing (AS) is an indispensable post-transcriptional modification applied during the maturation of mRNA, and AS defects have been associated with many cancers. This study was designed to thoroughly analyze AS events in bladder urothelial carcinoma (BLCA) at the genome-wide level.

Methods

We adopted a gap analysis to screen for significant differential AS events (DASEs) associated with BLCA. DASEs with prognostic value for OS and the disease-free interval (DFI) were identified by Cox analysis. In addition, a differential AS network and AS clusters were identified using unsupervised cluster analysis. We examined differences in the sensitivity to chemotherapy and immunotherapy between BLCA patients with high and low overall survival (OS) risk.

Results

An extensive number of DASEs (296) were found to be clinically relevant in BLCA. A prognosis model was established based prognostic value of OS and DFI. CUGBP elav-like family member 2 (CELF2) was identified as a hub splicing factor for AS networks. We also identified AS clusters associated with OS using unsupervised cluster analysis, and we predicted that the effects of cisplatin and gemcitabine chemotherapy would be different between high- and low-risk groups based on OS prognosis.

Conclusion

We completed a comprehensive analysis of AS events in BLCA at the genome-wide level. The present findings revealed that DASEs and splicing factors tended to impact BLCA patient survival and sensitivity to chemotherapy drugs, which may provide novel prospects for BLCA therapies.

Alternative splicing events implicated in carcinogenesis and prognosis of thyroid gland cancer

Alternative splicing (AS), a critical post-transcriptional regulatory mechanism, expands gene expression patterns, thereby leading to increased protein diversity. Indeed, more than 95% of human genes undergo alternative splicing events (ASEs). In this study, we drew an all-around AS profile of thyroid cancer cells based on RNA-seq data. In total, there were 45,150 AS in 10,446 thyroid cancer cell genes derived from 506 patients, suggesting that ASEs is a common process in TC. Moreover, 1819 AS signatures were found to be significantly associated with the overall survival (OS) of TC patients. Kaplan–Meier survival analyses suggested that seven types of ASEs were associated with poor prognosis of TC (P < 0.05). Among them, exon skipping (ES) was the most common, with alternate promoter (AP) and alternate terminator (AT) coming second and third, respectively. Our results indicated that acceptor sites (AA) (AUC: 0.937), alternate donor sites (AD) (AUC: 0.965), AT (AUC: 0.964), ES (AUC: 0.999), mutually exclusive exons (ME) (AUC: 0.999), and retained intron (RI) (AUC: 0.837) exhibited an AUC greater than 0.6. In addition, age and risk score (All) were risk factors for TC patients. We also evaluated whether TC-ASEs are regulated by various splicing factors (SFs). We found that the expression of 90 SFs was associated with 469 ASEs and OS of TC patients. Our findings provide an insight into the role of spliceosomes in TC, which may offer novel perspectives in tumor research.

Development and validation of an individual alternative splicing prognostic signature in gastric cancer

Gastric cancer (GC) is a heterogeneous disease with different clinical manifestations and prognoses. Alternative splicing (AS) is a determinant of gene expression and contributes to protein diversity from a rather limited gene transcript in metazoans. AS events are associated with different aspects of cancer biology, including cell proliferation, apoptosis, invasion, etc. Here, we present a comprehensive analysis of the prognostic AS profile in GC. GC-specific AS (GCAS) events were analyzed, and overall survival-associated GCAS (OS-GCAS) events were verified among the genome-wide AS events identified in The Cancer Genome Atlas (TCGA) database. In total, 1,287 GCAS events of 837 genes and 173 OS-GCAS events of 130 genes were identified. The parental genes of OS-GCAS events were significantly enriched in the development of GC. Protein-protein interaction (PPI) and OS-GCAS-associated splicing factor (SF) interaction networks were constructed. Multivariate Cox regression analysis with least absolute shrinkage and selection operator (LASSO) penalty was performed to establish a prognostic risk formula, representing 23 OS-GCAS events. The low-risk group had better OS than the high-risk group and lower immune and stromal scores. Cox proportional hazard regression was applied to generate an AS-clinical integrated prognostic model with a considerable area under the curve (AUC) value in both the training and validation datasets. Our study provides a profile of OS-GCAS events and an AS-clinical nomogram to predict the prognosis of GC.

Discovery of Functional Alternatively Spliced PKM Transcripts in Human Cancers

Simple Summary

Pyruvate kinase muscle type (PKM) is a key enzyme in glycolysis and is a mediator of the Warburg effect in tumors. The association of PKM with survival of cancer patients is controversial. In this study, we investigated the associations of the alternatively spliced transcripts of PKM with cancer patients’ survival outcomes and explained the conflicts in previous studies. We discovered three poorly studied alternatively spliced PKM transcripts that exhibited opposite prognostic indications in different human cancers based on integrative systems analysis. We also detected their protein products and explored their potential biological functions based on in-vitro experiments. Our analysis demonstrated that alternatively spliced transcripts of not only PKM but also other genes should be considered in cancer studies, since it may enable the discovery and targeting of the right protein product for development of the efficient treatment strategies.

Abstract

Pyruvate kinase muscle type (PKM) is a key enzyme in glycolysis and plays an important oncological role in cancer. However, the association of PKM expression and the survival outcome of patients with different cancers is controversial. We employed systems biology methods to reveal prognostic value and potential biological functions of PKM transcripts in different human cancers. Protein products of transcripts were shown and detected by western blot and mass spectrometry analysis. We focused on different transcripts of PKM and investigated the associations between their mRNA expression and the clinical survival of the patients in 25 different cancers. We find that the transcripts encoding PKM2 and three previously unstudied transcripts, namely ENST00000389093, ENST00000568883, and ENST00000561609, exhibited opposite prognostic indications in different cancers. Moreover, we validated the prognostic effect of these transcripts in an independent kidney cancer cohort. Finally, we revealed that ENST00000389093 and ENST00000568883 possess pyruvate kinase enzymatic activity and may have functional roles in metabolism, cell invasion, and hypoxia response in cancer cells. Our study provided a potential explanation to the controversial prognostic indication of PKM, and could invoke future studies focusing on revealing the biological and oncological roles of these alternative spliced variants of PKM.

The Functional Impact of Alternative Splicing on the Survival Prognosis of Triple-Negative Breast Cancer

Purpose

Triple-negative breast cancer (TNBC) is a type of breast cancer (BC) showing a high recurrence ratio and a low survival probability, which requires novel actionable molecular targets. The involvement of alternative splicing (AS) in TNBC promoted us to study the potential roles of AS events in the survival prognosis of TNBC patients.

Methods

A total of 150 TNBC patients from The Cancer Genome Atlas (TCGA) were involved in this work. To study the effects of AS in the recurrence-free survival (RFS) prognosis of TNBC, we performed the analyses as follows. First, univariate Cox regression model was applied to identify RFS-related AS events. Their host genes were analyzed by Metascape to discover the potential functions and involved pathways. Next, least absolute shrinkage and selection operator (LASSO) method was used to select the most informative RFS-related AS events to constitute an AS risk factor for RFS prognosis, which was evaluated by Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves in all the data and also in different clinical subgroups. Furthermore, we analyzed the relationships between splicing factors (SFs) and these RFS-related AS events to seek the possibility that SFs regulated AS events to influence RFS. Then, we evaluated the potential of these RFS-related AS events in the overall survival (OS) prognosis from all the above aspects.

Results

We identified a total of 546 RFS-related AS events, which were enriched in some splicing and TNBC-associated pathways. Among them, seven RFS-related events were integrated into a risk factor, exhibiting satisfactory RFS prognosis alone and even better performance when combined with clinical tumor–node–metastasis stages. Furthermore, the correlation analysis between SFs and the seven AS events revealed the hypotheses that SRPK3 might upregulate PCYT2_44231_AA to have an effect on RFS prognosis and that three other SFs may work together to downregulate FLAD1_7874_RI to influence RFS prognosis. In addition, the seven RFS-related AS events were validated to be promising in the OS prognosis of TNBC as well.

Conclusion

The abnormal AS events regulated by SFs may act as a kind of biomarker for the survival prognosis of TNBC.

Survival-Associated Alternative Splicing Events and Prognostic Signatures in Pancreatic Cancer

Background

Alternative splicing (AS) is reported to be related to the biological process of multiple malignancies. This study is conducted to identify survival-associated AS events and prognostic signatures that may serve as prognostic indicators for pancreatic cancer (PC).

Methods

Univariate Cox analysis was used to determine the survival-associated AS events in PC. Prognostic signatures were constructed by LASSO Cox analysis based on seven types of survival-associated AS events. The correlation between the expression of splicing factors (SFs) and the percent spliced in values of AS events was analyzed by Pearson correlation analysis. Risk scores were calculated to determine high- or low-risk patients with different types of AS events. Gene functional annotation analysis was performed to reveal pathways in which prognostic AS is enriched.

Results

A total of 45,313 AS events in 10,624 genes were observed, and there were 1,565 AS events in 1,223 genes significantly correlated with overall survival for PC. Kaplan–Meier analysis, receiver-operator characteristic curve, univariate and multivariate Cox analyses showed that AS prognostic signatures could effectively predict prognosis of patients with PC. Splicing factors–AS regulatory networks were established to demonstrate the interaction between AS events and SFs.

Conclusion

The survival-associated AS events and prognostic signatures identified in this study can serve as useful tool for predicting prognosis of patients with PC. Moreover, the SF–AS regulatory networks may provide clues for the mechanisms underlying AS in PC.

Aberrant RNA Splicing Events Driven by Mutations of RNA-Binding Proteins as Indicators for Skin Cutaneous Melanoma Prognosis

The worldwide incidence of skin cutaneous melanoma (SKCM) is increasing at a more rapid rate than other tumors. Aberrant alternative splicing (AS) is found to be common in cancer; however, how this process contributes to cancer prognosis still remains largely unknown. Mutations in RNA-binding proteins (RBPs) may trigger great changes in the splicing process. In this study, we comprehensively analyzed DNA and RNA sequencing data and clinical information of SKCM patients, together with widespread changes in splicing patterns induced by RBP mutations. We screened mRNA expression-related and prognosis-related mutations in RBPs and investigated the potential affections of RBP mutations on splicing patterns. Mutations in 853 RBPs were demonstrated to be correlated with splicing aberrations (p < 0.01). Functional enrichment analysis revealed that these alternative splicing events (ASEs) may participate in tumor progress by regulating the modification process, cell-cycle checkpoint, metabolic pathways, MAPK signaling, PI3K-Akt signaling, and other important pathways in cancer. We also constructed a prediction model based on overall survival-related AS events (OS-ASEs) affected by RBP mutations, which exhibited a good predict efficiency with the area under the curve of 0.989. Our work highlights the importance of RBP mutations in splicing alterations and provides effective biomarkers for prediction of prognosis of SKCM.

Identification and validation of critical alternative splicing events and splicing factors in gastric cancer progression

Gene expression and alternative splicing (AS) interact in complex ways to regulate biological process which is associated with cancer development. Here, by integrated analysis of gene expression and AS events, we aimed to identify the hub AS events and splicing factors relevant in gastric cancer development (GC). RNA‐seq data, clinical data and AS events of 348 GC samples were obtained from the TCGA and TCGASpliceSeq databases. Cox univariable and multivariable analyses, KEGG and GO pathway analyses were performed to identify hub AS events and splicing factor/spliceosome genes, which were further validated in 53 GCs. By bioinformatics methods, we found that gene AS event‐ and gene expression‐mediated GC progression shared the same mechanisms, such as PI3K/AKT pathway, but the involved genes were different. Though expression of 17 hub AS events were confirmed in 53 GC tissues, only 10 AS events in seven genes were identified as critical candidates related to GC progression, notably the AS events (Exon Skip) in CLSTN1 and SEC16A. Expression of these AS events in GC correlated with activation of the PI3K/AKT pathway. Genes with AS events associated with clinical parameters and prognosis were different from the genes whose mRNA levels were related to clinical parameters and prognosis. Besides, we further revealed that QKI and NOVA1 were the crucial splicing factors regulating expression of AS events in GC, but not spliceosome genes. Our integrated analysis revealed hub AS events in GC development, which might be the potential therapeutic targets for GC.

Circular RNA circCTNNA1 promotes colorectal cancer progression by sponging miR-149-5p and regulating FOXM1 expression

Circular RNAs (circRNAs) are an emerging class of non-coding RNAs, identified to participate in multiple malignancies. Nevertheless, the clinical significance, biological function, and regulatory mechanisms of circRNAs in colon cancer (CC) remain largely unclear. In this study, the circRNA expression profile in CC and matched normal tissues was analyzed using circRNA microarrays. A novel circRNA, circCTNNA1, was significantly upregulated in CC, and its level was associated with advanced tumor–node–metastasis stage and poor prognosis of patients with CC. Functional experiments, including Cell Counting Kit-8, colony formation, 5‐ethynyl‐2′‐deoxyuridine, transwell, wound healing, flow cytometric analysis, and in vivo tumorigenesis assay were then performed to investigate the oncogenic role of circCTNNA1. The results revealed that circCTNNA1 promoted CC cell proliferation, migration, and invasion in vitro and in vivo. Mechanistically, RNA pull-down, RNA immunoprecipitation, dual-luciferase reporter assays, and fluorescent in situ hybridization were performed to unveil that circCTNNA1 can serve as a competing endogenous RNA of miR-149-5p to counteract the suppressive effect of miR-149-5p on downstream target Forkhead Box M1 (FOXM1). In summary, our study demonstrated that circCTNNA1 facilitated CC proliferation and invasion via the circCTNNA1/miR-149-5p/FOXM1 axis, and it might function as a novel diagnostic or therapeutic target for patients with CC.

Identification of Prognostic Signatures of Alternative Splicing in Glioma

Alternative splicing (AS) is a ubiquitous mechanism in which pre-mRNA can be spliced into divergent variants and involved in carcinogenesis and progression in several cancers. In the present study, we systematically profiled prognostic AS signatures involving both low grade glioma (LGG) and glioblastoma (GBM) and investigated the association of AS signatures with tumor grade and IDH1 status in glioma. Percent spliced in (PSI) values and corresponding clinical data were obtained from TCGA SpliceSeq and TCGA data portal, respectively. Prognostic AS signatures were identified using univariate and stepwise multivariate Cox regression. Heatmap analysis was performed based on prognostic AS signatures. A prognostic signature was established with 69 and 88 AS events, including specific splicing events of MUTYH, STEAP3, and CTNNB1, in LGG and GBM cohorts, respectively. The area under the curve (AUC) of the prediction model was 0.968 at 2000 days of overall survival (OS) in the LGG cohort and 0.966 at 450 days of OS in the GBM cohort. In addition, these prognostic AS signatures could complement current molecular classification, such as IDH1 mutation, 1p/19q codeletion, and ATRX loss, of glioma and further identify potential subgroups of glioma with the same molecular features. In conclusion, our study systematically profiled prognostic AS events involving both low grade glioma and glioblastoma for the first time, which also shed light on the crosstalk between AS signatures and molecular features of glioma.

The Role of RNA Splicing Factors in Cancer: Regulation of Viral and Human Gene Expression in Human Papillomavirus-Related Cervical Cancer

The spliceosomal complex components, together with the heterogeneous nuclear ribonucleoproteins (hnRNPs) and serine/arginine-rich (SR) proteins, regulate the process of constitutive and alternative splicing, the latter leading to the production of mRNA isoforms coding multiple proteins from a single pre-mRNA molecule. The expression of splicing factors is frequently deregulated in different cancer types causing the generation of oncogenic proteins involved in cancer hallmarks. Cervical cancer is caused by persistent infection with oncogenic human papillomaviruses (HPVs) and constitutive expression of viral oncogenes. The aberrant activity of hnRNPs and SR proteins in cervical neoplasia has been shown to trigger the production of oncoproteins through the processing of pre-mRNA transcripts either derived from human genes or HPV genomes. Indeed, hnRNP and SR splicing factors have been shown to regulate the production of viral oncoprotein isoforms necessary for the completion of viral life cycle and for cell transformation. Target-therapy strategies against hnRNPs and SR proteins, causing simultaneous reduction of oncogenic factors and inhibition of HPV replication, are under development. In this review, we describe the current knowledge of the functional link between RNA splicing factors and deregulated cellular as well as viral RNA maturation in cervical cancer and the opportunity of new therapeutic strategies.

Prognostic role of alternative splicing events in head and neck squamous cell carcinoma

Background

Aberrant alternative splicing (AS) is implicated in biological processes of cancer. This study aims to reveal prognostic AS events and signatures that may serve as prognostic predictors for head and neck squamous cell carcinoma (HNSCC).

Methods

Prognostic AS events in HNSCC were identified by univariate COX analysis. Prognostic signatures comprising prognostic AS events were constructed for prognosis prediction in patients with HNSCC. The correlation between the percent spliced in (PSI) values of AS events and the expression of splicing factors (SFs) was analyzed by Pearson correlation analysis. Gene functional annotation analysis was performed to reveal pathways in which prognostic AS is enriched.

Results

A total of 27,611 AS events in 15,873 genes were observed, and there were 3433 AS events in 2624 genes significantly associated with overall survival (OS) for HNSCC. Moreover, we found that AS prognostic signatures could accurately predict HNSCC prognosis. SF-AS regulatory networks were constructed according to the correlation between PSI values of AS events and the expression levels of SFs.

Conclusions

Our study identified prognostic AS events and signatures. Furthermore, it established SF-AS networks in HNSCC that were valuable in predicting the prognosis of patients with HNSCC and elucidating the regulatory mechanisms underlying AS in HNSCC.

Transcription Factors in Cancer: When Alternative Splicing Determines Opposite Cell Fates

Alternative splicing (AS) is a finely regulated mechanism for transcriptome and proteome diversification in eukaryotic cells. Correct balance between AS isoforms takes part in molecular mechanisms that properly define spatiotemporal and tissue specific transcriptional programs in physiological conditions. However, several diseases are associated to or even caused by AS alterations. In particular, multiple AS changes occur in cancer cells and sustain the oncogenic transcriptional program. Transcription factors (TFs) represent a key class of proteins that control gene expression by direct binding to DNA regulatory elements. AS events can generate cancer-associated TF isoforms with altered activity, leading to sustained proliferative signaling, differentiation block and apoptosis resistance, all well-known hallmarks of cancer. In this review, we focus on how AS can produce TFs isoforms with opposite transcriptional activities or antagonistic functions that severely impact on cancer biology. This summary points the attention to the relevance of the analysis of TFs splice variants in cancer, which can allow patients stratification despite the presence of interindividual genetic heterogeneity. Recurrent TFs variants that give advantage to specific cancer types not only open the opportunity to use AS transcripts as clinical biomarkers but also guide the development of new anti-cancer strategies in personalized medicine.

Systematic analysis of survival-associated alternative splicing signatures in clear cell renal cell carcinoma

Alternative splicing (AS) constitutes a major reason for messenger RNA (mRNA) and protein diversity. Increasing studies have shown a link to splicing dysfunction associated with malignant neoplasia. Systematic analysis of AS events in kidney cancer remains poorly reported. Therefore, we generated AS profiles in 533 kidney renal clear cell carcinoma (KIRC) patients in The Cancer Genome Atlas (TCGA) database using RNA-seq data. Then, prognostic models were developed in a primary cohort (N = 351) and validated in a validation cohort (N = 182). In addition, splicing networks were built by integrating bioinformatics analyses. A total of 11 268 and 8083 AS variants were significantly associated with patient overall survival time in the primary and validation KIRC cohorts, respectively, including STAT1, DAZAP1, IDS, NUDT7, and KLHDC4. The AS events in the primary KIRC cohorts served as candidate AS events to screen the independent risk factors associated with survival in the primary cohort and to develop prognostic models. The area under the curve of the receiver-operator characteristic curve for prognostic prediction in the primary and validation KIRC cohorts was 0.84 and 0.82 at 2500 days of overall survival, respectively. In addition, splicing correlation networks revealed key splicing factors (SFs) in KIRC, such as HNRNPH1, HNRNPU, KHDBS1, KHDBS3, SRSF9, RBMX, SFQ, SRP54, HNRNPA0, and SRSF6. In this study, we analyzed the AS landscape in the TCGA KIRC cohort and detected predictors (prognostic) based on AS variants with high performance for risk stratification of the KIRC cohort and revealed key SFs in splicing networks, which could act as underlying mechanisms.

Identification of Prognostic and Metastatic Alternative Splicing Signatures in Kidney Renal Clear Cell Carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) is the malignancy originated from the renal epithelium, with a high rate of distant metastasis. Aberrant alternative splicing (AS) of pre-mRNA are widely reported to be involved in the tumorigenesis and metastasis of multiple cancers. The aim of this study is to explore the mechanism of alternative splicing events (ASEs) underlying tumorigenesis and metastasis of KIRC. Methods: RNA-seq of 537 KIRC samples downloaded from the TCGA database and ASEs data from the TCGASpliceSeq database were used to identify ASEs in patients with KIRC. The univariate and Lasso regression analysis were used to screen the most significant overall survival-related ASEs (OS-SEs). Based on those, the OS-SEs model was proposed. The interaction network of OS-SEs and splicing factors (SFs) with absolute value of correlation coefficient value >0.750 was constructed by Pearson correlation analysis. The OS-SEs significantly related to distant metastasis and clinical stage were identified by non-parametric test, and those were also integrated into co-expression analysis with prognosis-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways identified by Gene Set Variation Analysis (GSVA). ASEs with significance were selected for multiple online database validation. Results: A total of prognostic 6,081 overall survival-related ASEs (OS-SEs) were identified by univariate Cox regression analysis and a prediction model was constructed based on 5 OS-SEs screened by Lasso regression with the Area Under Curve of 0.788. Its risk score was also illustrated to be an independent predictor, which the good reliability of the model. Among 390 identified candidate SFs, DExD-Box Helicase 39B (DDX39B) was significantly correlated with OS and metastasis. After external database validation, Retained Intron of Ras Homolog Family Member T2 (RHOT2) and T-Cell Immune Regulator 1 (TCIRG1) were identified. In the co-expression analysis, overlapped co-expression signal pathways for RHOT2 and TCIRG1 were sphingolipid metabolism and N-glycan biosynthesis. Conclusions: Based on the results of comprehensive bioinformatic analysis, we proposed that aberrant DDX39B regulated RHOT2-32938-RI and TCIRG1-17288-RI might be associated with the tumorigenesis, metastasis, and poor prognosis of KIRC via sphingolipid metabolism or N-glycan biosynthesis pathway.