The Functional Impact of Alternative Splicing in Cancer

A Prediction Model Using Alternative Splicing Events and the Immune Microenvironment Signature in Lung Adenocarcinoma

Background

Alternative splicing (AS) is a gene regulatory mechanism that drives protein diversity. Dysregulation of AS is thought to play an essential role in cancer initiation and development. This study aimed to construct a prognostic signature based on AS and explore the role in the tumor immune microenvironment (TIME) in lung adenocarcinoma.

Methods

We analyzed transcriptome profiling and clinical lung adenocarcinoma data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq. Prognosis-related AS events were analyzed by univariate Cox regression analysis. Gene set enrichment analyses (GSEA) were performed for functional annotation. Prognostic signatures were identified and validated using univariate and multivariate Cox regression, LASSO regression, Kaplan–Meier survival analyses, and proportional hazards model. The context of TIME in lung adenocarcinoma was also analyzed. Gene and protein expression data of Cyclin-Dependent Kinase Inhibitor 2A (CDKN2A) were obtained from ONCOMINE and Human Protein Atlas. Splicing factor (SF) regulatory networks were visualized.

Results

A total of 19,054 survival-related AS events in lung adenocarcinoma were screened in 1,323 genes. Exon skip (ES) and mutually exclusive exons (ME) exhibited the most and fewest AS events, respectively. Based on AS subtypes, eight AS prognostic signatures were constructed. Patients with high-risk scores were associated with poor overall survival. A nomogram with good validity in prognostic prediction was generated. AUCs of risk scores at 1, 2, and 3 years were 0.775, 0.736, and 0.759, respectively. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. Low-risk patients had a higher StromalScore, ImmuneScore, and ESTIMATEScore. AS-based risk score signature was positively associated with CD8+ T cells. CDKN2A was also found to be a prognostic factor in lung adenocarcinoma. Finally, potential functions of SFs were determined by regulatory networks.

Conclusion

Taken together, our findings show a clear association between AS and immune cell infiltration events and patient outcome, which could provide a basis for the identification of novel markers and therapeutic targets for lung adenocarcinoma. SF networks provide information of regulatory mechanisms.

The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment

Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.

Functional enrichment of alternative splicing events with NEASE reveals insights into tissue identity and diseases

Alternative splicing (AS) is an important aspect of gene regulation. Nevertheless, its role in molecular processes and pathobiology is far from understood. A roadblock is that tools for the functional analysis of AS-set events are lacking. To mitigate this, we developed NEASE, a tool integrating pathways with structural annotations of protein-protein interactions to functionally characterize AS events. We show in four application cases how NEASE can identify pathways contributing to tissue identity and cell type development, and how it highlights splicing-related biomarkers. With a unique view on AS, NEASE generates unique and meaningful biological insights complementary to classical pathways analysis.

Systematic Genome-Wide Profiles Reveal Alternative Splicing Landscape and Implications of Splicing Regulator DExD-Box Helicase 21 in Aggressive Progression of Adrenocortical Carcinoma

Alternative splicing (AS) in the tumor biological process has provided a novel perspective on carcinogenesis. However, the clinical significance of individual AS patterns of adrenocortical carcinoma (ACC) has been underestimated, and in-depth investigations are lacking. We selected 76 ACC samples from the Cancer Genome Atlas (TCGA) SpliceSeq and SpliceAid2 databases, and 39 ACC samples from Fudan University Shanghai Cancer Center (FUSCC). Prognosis-related AS events (PASEs) and survival analysis were evaluated based on prediction models constructed by machine-learning algorithm. In total, 23,984 AS events and 3,614 PASEs were detected in the patients with ACC. The predicted risk score of each patient suggested that eight PASEs groups were significantly correlated with the clinical outcomes of these patients (p < 0.001). Prognostic models produced AUC values of 0.907 in all PASEs' groups. Eight splicing factors (SFs), including BAG2, CXorf56, DExD-Box Helicase 21 (DDX21), HSPB1, MBNL3, MSI1, RBMXL2, and SEC31B, were identified in regulatory networks of ACC. DDX21 was identified and validated as a novel clinical promoter and therapeutic target in 115 patients with ACC from TCGA and FUSCC cohorts. In conclusion, the strict standards used in this study ensured the systematic discovery of profiles of AS events using genome-wide cohorts. Our findings contribute to a comprehensive understanding of the landscape and underlying mechanism of AS, providing valuable insights into the potential usages of DDX21 for predicting prognosis for patients with ACC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-021-00026-x.

Probing Isoform Switching Events in Various Cancer Types: Lessons From Pan-Cancer Studies

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. In cancer, alternative splicing is frequently disturbed, leading to changes in the expression of alternatively spliced protein isoforms. Advances in sequencing technologies and analysis methods led to new insights into the extent and functional impact of disturbed alternative splicing events. In this review, we give a brief overview of the molecular mechanisms driving alternative splicing, highlight the function of alternative splicing in healthy tissues and describe how alternative splicing is disrupted in cancer. We summarize current available computational tools for analyzing differential transcript usage, isoform switching events, and the pathogenic impact of cancer-specific splicing events. Finally, the strategies of three recent pan-cancer studies on isoform switching events are compared. Their methodological similarities and discrepancies are highlighted and lessons learned from the comparison are listed. We hope that our assessment will lead to new and more robust methods for cancer-specific transcript detection and help to produce more accurate functional impact predictions of isoform switching events.

Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Although transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood. Short-read transcript sequencing has prevented researchers from directly exploring full-length transcripts, forcing them to focus on individual splice sites. Here, we develop a pipeline for Multi-Sample long-read Transcriptome Assembly (MuSTA), which enables construction of a transcriptome from long-read sequence data. Using the constructed transcriptome as a reference, we analyze RNA extracted from 22 clinical breast cancer specimens. We identify a comprehensive set of subtype-specific and differentially used isoforms, which extended our knowledge of isoform regulation to unannotated isoforms including a short form TNS3. We also find that the exon-intron structure of fusion transcripts depends on their genomic context, and we identify double-hop fusion transcripts that are transcribed from complex structural rearrangements. For example, a double-hop fusion results in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and is thought to protect fetus from maternal rejection; expression is elevated in several TCGA samples with ERVFRD-1 fusions. Our analyses provide direct evidence that full-length transcript sequencing of clinical samples can add to our understanding of cancer biology and genomics in general.

Identification of heterogeneous nuclear ribonucleoprotein as a candidate biomarker for diagnosis and prognosis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high mortality rate. However, spliceosomal genes are still lacking in the diagnosis and prognosis of HCC.

Methods

Identification of differentially expressed genes (DEGs) was performed using the limma package in R software. Modules highly related to HCC were obtained by weighted gene co-expression network analysis (WGCNA), and the module genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The biomarker for diagnosing HCC was determined by receiver operating characteristic (ROC) curve analysis, and the effect of the biomarker in the diagnosis of HCC was evaluated by performing five-fold cross-validation with logistic regression. HCC specimens from preoperatively treated patients were tested for biomarker by real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-Meier analysis was used to assess the relationship between biomarker and patient survival. The role of biomarker was evaluated using ESTIMATE analysis in the tumor microenvironment.

Results

In this study, 389 DEGs were screened out from three Gene Expression Omnibus (GEO) datasets. We also found that the turquoise module of 123 genes from The Cancer Genome Atlas (TCGA) data was the key module with the highest correlation with HCC traits. Then, 123 genes were analyzed using the KEGG enrichment pathway, and eight genes were found to be most significantly related to the spliceosome pathway. We selected 8 genes and 389 DEGs shared genes, and finally got the only gene, heterogeneous nuclear ribonucleoprotein (hnRNPU). The high expression of hnRNPU was associated with poor prognosis of HCC, and hnRNPU was a biomarker for diagnosing HCC. In the tissues of patients with excellent HCC treatment hnRNPU messenger RNA (mRNA) was lower than in the tissues of patients with poor HCC treatment. High expression of hnRNPU was significantly increased in HCC patients with low stromal (P<0.05), low immune (P<0.05), and low estimation scores (P<0.05), and with high tumor purity (P<0.05) and high malignant progression (P<0.05) of the HCC.

Conclusions

The hnRNPU gene identified in this study may become a new biomarker for the diagnosis and prognosis of HCC.

Prognostic Significance of Alternative Splicing Genes in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Background

Alternative splicing (AS) acts on many tumors and its relationship with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) needs to be researched.

Methods

RNA sequencing data and clinical information of CESC cohorts were obtained from the Cancer Genome Atlas (TCGA) and SpliceSeq was used to analyze the splicing profile of mRNA in CESC. UpSetR displayed the intersections among AS events and univariate analysis chose survival-associated AS and splicing factor (SF) genes. Functional analysis was operated on Enrichr, STRING database and MCODE analysis were used to evaluate protein-protein interaction (PPI) information. LASSO and multivariate analysis constructed prognostic model and risk analysis of tumor infiltrating immune cells was also conducted.

Results

A total of 402 AS-generated genes were found to be associated with CESC prognosis. Functional analysis showed that Golgi to lysosome transport was enriched. PPI network suggested that UBA52 was most functional. Dendritic cells activated, dendritic cells resting, macrophages M0, mast cells resting, T cells CD4 memory activated and T cells CD8 were most correlative with the risk score.

Conclusion

SFs and AS events can directly or indirectly affect the prognosis of CESC patients and this study identified SNRPA and CELF2 as two CESC-engaged SFs.

Analysis of Genome-Wide Alternative Splicing Profiling and Development of Potential Drugs in Lung Adenocarcinoma

Alternative splicing (AS) is significantly related to tumor development as well as a patient’s clinical characteristics. This study was designed to systematically analyze the survival-associated AS signatures in Lung adenocarcinoma (LUAD). Among 30,735 AS events in 9,635 genes, we found that there were 1,429 AS in 1,125 genes which were conspicuously related to the overall survival of LUAD patients. Then, according to the seven types of AS events, we established AS signatures and constructed a new combined prognostic model. The Kaplan-Meier curve results showed that seven types of AS signatures and the combined prognostic model could divide patients into distinct prognoses. The ROC curve shows that all eight AS signatures had powerful predictive properties with different AUCs ranging from 0.708 to 0.849. Additionally, the elevated risk scores were positively related to higher TNM stage and metastasis. Interestingly, AS events and splicing factors (SFs) network shed light on a meaningful connection between prognostic AS genes and corresponding SFs. Moreover, we found that the combined prognostic model signature has a higher predictive ability than the mRNA signature. Furthermore, tumors at high risk might evade immune recognition by decreasing the expression of antigen presentation genes. Finally, we predicted the three most significant small molecule drugs to inhibit LUAD. Among them, NVP-AUY922 had the lowest IC50 value and might become a potential drug to prolong a patient’s survival. In conclusion, our study established a potential prognostic signature for LUAD patients, revealed a splicing network between AS and SFs and possible immune escape mechanism, and provided several small-molecule drugs to inhibit tumorigenesis.

SAM Competitive PRMT5 Inhibitor PF-06939999 Demonstrates Antitumor Activity in Splicing Dysregulated NSCLC with Decreased Liability of Drug Resistance

Protein arginine methyltransferase 5 (PRMT5) over-expression in hematological and solid tumors methylates arginine residues on cellular proteins involved in important cancer functions including cell cycle regulation, mRNA splicing, cell differentiation, cell signaling, and apoptosis. PRMT5 methyltransferase function has been linked with high rates of tumor cell proliferation and decreased overall survival, and PRMT5 inhibitors are currently being explored as an approach for targeting cancer-specific dependencies due to PRMT5 catalytic function. Here we describe the discovery of potent and selective S-adenosylmethionine (SAM) competitive PRMT5 inhibitors, with in vitro and in vivo characterization of clinical candidate PF-06939999. Acquired resistance mechanisms were explored through the development of drug resistant cell lines. Our data highlight compound-specific resistance mutations in the PRMT5 enzyme that demonstrate structural constraints in the co-factor binding site that prevent emergence of complete resistance to SAM site inhibitors. PRMT5 inhibition by PF-06939999 treatment reduced proliferation of NSCLC cancer cells, with dose-dependent decreases in symmetric dimethyl arginine (SDMA) levels and changes in alternative splicing of numerous pre-mRNAs. Drug sensitivity to PF-06939999 in NSCLC cells associates with cancer pathways including MYC, cell cycle and spliceosome, and with mutations in splicing factors such as RBM10. Translation of efficacy in mouse tumor xenograft models with splicing mutations provides rationale for therapeutic use of PF-06939999 in the treatment of splicing dysregulated NSCLC.

NOVA1-Mediated SORBS2 Isoform Promotes Colorectal Cancer Migration by Activating the Notch Pathway

Background: Gene expression and alternative splicing (AS) can promote cancer development via complex mechanisms. We aimed to identify and verify the hub AS events and splicing factors associated with the progression of colorectal cancer (CRC).

Methods: RNA-Seq data, clinical data, and AS events of 590 CRC 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 five CRCs.

Results: In this study, we first compared differentially expressed genes and gene AS events between normal and tumor tissues. Differentially expressed genes were different from genes with differentially expressed AS events. Prognostic analysis and co-expression network analysis of gene expression and gene AS events were conducted to screen five hub gene AS events involved in CRC progression: EPB41L2, CELF2, TMEM130, VCL, and SORBS2. Using qRT-PCR, we also verified that the gene AS events SORBS2 were downregulated in tumor tissue, and gene AS events EPB41L2, CELF2, TMEM130, and VCL were upregulated in tumor tissue. The genes whose mRNA levels were significantly related to the five hub gene AS events were significantly enriched in the GO term of cell division and Notch signaling pathway. Further coexpression of gene AS events and alternative splicing factor genes revealed NOVA1 as a crucial factor regulating the hub gene AS event expression in CRC. Through in vitro experiments, we found that NOVA1 inhibited gene AS event SORBS2, which induced the migration of CRC cells via the Notch pathway.

Conclusion: Integrated analysis of gene expression and gene AS events and further experiments revealed that NOVA1-mediated SORBS2 promoted the migration of CRC, indicating its potential as a therapeutic target.

Methylation Modification, Alternative Splicing, and Noncoding RNA Play a Role in Cancer Metastasis through Epigenetic Regulation

Metastasis is the leading cause of cancer-related deaths. Understanding the pathogenesis of metastasis at the molecular levels is of great significance for cancer research. However, the molecular diagnosis or treatment of cancer metastasis is limited. Accumulating and growing evidence shows that epigenetic changes are present in all human cancers, and epigenetic regulation is an indispensable factor to promote tumor metastasis. With the deepening of research and the advancement of technology, the function and mechanism of epigenetic regulation, including DNA methylation, histone/RNA modification, and precursor messenger RNA alternative splicing and noncoding RNAs, has become more increasingly clear. At present, the application of epigenetic therapies in tumor treatment is becoming a feasible therapeutic route. In this review, we looked for the key molecules in epigenetic regulation and discuss their relative regulating mechanisms in cancer metastasis. Furthermore, we highlight promising therapeutic strategies, including monitoring serum DNA for diagnostic purposes and early phase clinical trial therapies that target DNA and histone methylation. This may also be beneficial in finding new targets for further prognosis and diagnosis of cancer metastasis.

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.

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.

BUB1B and circBUB1B_544aa aggravate multiple myeloma malignancy through evoking chromosomal instability

Multiple myeloma (MM) is an incurable plasma cell malignancy in the bone marrow characterized by chromosome instability (CIN), which contributes to the acquisition of heterogeneity, along with MM progression, drug resistance, and relapse. In this study, we elucidated that the expression of BUB1B increased strikingly in MM patients and was closely correlated with poor outcomes. Overexpression of BUB1B facilitated cellular proliferation and induced drug resistance in vitro and in vivo, while genetic targeting BUB1B abrogated this effect. Mechanistic studies unveiled that enforced expression of BUB1B evoked CIN resulting in MM poor outcomes mainly through phosphorylating CEP170. Interestingly, we discovered the existence of circBUB1B_544aa containing the kinase catalytic center of BUB1B, which was translated by a circular RNA of BUB1B. The circBUB1B_544aa elevated in MM peripheral blood samples was closely associated with MM poor outcomes and played a synergistic effect with BUB1B on evoking CIN. In addition, MM cells could secrete circBUB1B_544aa and interfere the MM microenvironmental cells in the same manner as BUB1B full-length protein. Intriguingly, BUB1B siRNA, targeting the kinase catalytic center of both BUB1B and circBUB1B_544aa, significantly inhibited MM malignancy in vitro and in vivo. Collectively, BUB1B and circBUB1B_544aa are promising prognostic and therapeutic targets of MM.

Mucin Expression and Splicing Determine Novel Subtypes and Patient Mortality in Pancreatic Ductal Adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy demonstrating aberrant and progressive expression of mucins. The contribution of individual mucins has been extensively investigated in PDAC; however, comprehensive mucin profiling including splice variants in PDAC tumors has not been reported.

EXPERIMENTAL DESIGN

Using publicly available RNA sequencing (RNA-seq) datasets, we assess the expression of mucin family members and their splice variants (SV) in PDAC tumor samples for the first time. Mucin SVs that are correlated with PDAC patient survival are validated in a cohort of patient tumor samples. Further, we use computational methods to derive novel pancreatic tumor subtypes using mucin expression signatures and their associated activated pathways.

RESULTS

Principal component analysis identified four novel mucin-based PDAC subtypes. Pathway analysis implicated specific biological signatures for each subtype, labeled (i) immune activated, (ii) progressive, (iii) pancreatitis-initiated, and (iv) anti-inflammatory/PanIN-initiated. Assessing mucin SVs, significantly longer survival is observed with higher expression of 4 MUC1 and 1 MUC13 SVs, whereas patients expressing 2 MUC4 and 1 MUC16 SVs had shorter survival. Using a whole-transcriptome correlation, a three-gene panel, including ESRP2, PTK6, and MAGEH1, is designated to assess PDAC tumor sample cellularity by PCR. One MUC4 SV and one MUC13 SV are quantified in a separate PDAC patient cohort, and their effects on survival are experimentally validated.

CONCLUSIONS

Altogether, we demonstrate the unique expression pattern of mucins, four mucin-based PDAC subtypes, and the contribution of MUC1, MUC4, and MUC16 SVs in PDAC patient survival.

The Big Picture of Glioblastoma Malignancy: A Meta-Analysis of Glioblastoma Proteomics to Identify Altered Biological Pathways

Glioblastoma is a highly malignant cancer with no effective treatment. It is vital to elucidate the mechanisms which drive glioblastoma in order to identify therapeutic targets. The differences in protein expression between glioblastoma, grade I-III glioma, and normal brain tissue reflect the functional alterations driving malignancy. However, proteomic analysis of glioblastoma has been hampered by the heterogeneity of glioblastoma and the variety of methodology used in its study. To reduce these inconsistencies, we performed a meta-analysis of the literature published since 2015, including 14 datasets from eight papers comparing the whole proteome of glioblastoma to normal brain or grade I-III glioma. We found that 154 proteins were commonly upregulated and 116 proteins were commonly downregulated in glioblastoma compared to normal brain. Meanwhile, 240 proteins were commonly upregulated and 125 proteins were commonly downregulated in glioblastoma compared to grade I-III glioma. Functional enrichment analysis revealed upregulation of proteins involved in mRNA splicing and the immune system and downregulation of proteins involved in synaptic signaling and glucose and glutamine metabolism. The identification of these altered biological pathways provides a basis for deeper investigation in the pursuit of an effective treatment for glioblastoma.

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.

USP39 promotes malignant proliferation and angiogenesis of renal cell carcinoma by inhibiting VEGF-A165b alternative splicing via regulating SRSF1 and SRPK1

Background

The benefit of targeted therapy for renal cell carcinoma (RCC) is largely crippled by drug resistance. Rapid disease progression and poor prognosis occur in patients with drug resistance. New treatments demand prompt exploration for clinical therapies. Ubiquitin-specific peptidase 39 (USP39) serves as the pro-tumor factor in several previous studies of other malignant tumors. To investigate the function and mechanism of USP39 in promoting malignant proliferation and angiogenesis of RCC.

Methods

We applied ONCOMINE database to analyze the correlation between USP39 expression level and the clinical characteristics of RCC. USP39 knockdown or overexpression plasmids were transfected into 786-O and ACHN cells. The HUVEC received cell supernatants of 786-O and ACHN cells with knockdown or overexpression USP39.The effect of USP39 on RCC was evaluated by MTT assay, cell cycle analysis, colony formation assay and tubule formation assay. The interaction between USP39 and VEGF-A alternative splicing was assessed by affinity purification and mass spectrometry, co-immunoprecipitation and Western blot assays.

Results

The mRNA expression level of USP39 in RCC was significantly higher than that in normal renal tissue (P < 0.001), and negatively correlated with the survival rate of RCC patients (P < 0.01). Silencing of USP39 in 786-O and ACHN cells inhibited cell proliferation and colony formation, and induced S phase arrest. USP39 overexpression significantly increased the number of tubules (P < 0.05) and branches (P < 0.01) formed by HUVEC cells, and USP39 knockdown produced an opposite effect (P < 0.05). The USP39 _(101–565) fragment directly mediated its binding to SRSF1 and SRPK1, and promoted the phosphorylation of SRSF1 to regulate VEGF-A alternative splicing. USP39 knockdown upregulated the expression of VEGF-A_165b, and USP39 overexpression downregulated the expression of VEGF-A_165b significantly (both P < 0.05).

Conclusion

USP39 acted as a pro-tumor factor by motivating the malignant biological processes of RCC, probably through inhibiting VEGF-A^165b alternative splicing and regulating SRSF1 and SRPK1. USP39 may prove to be a potential therapeutic target for RCC.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02161-x.

ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer

Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.

A pan-cancer analysis of alternative splicing of splicing factors in 6904 patients

Great progress has been made in the investigation on mutation and expression of splicing factor. However, little is known on the role of alternative splicing of splicing factors across cancers. Here, we reported a pan-cancer analysis of alternative splicing of splicing factors spanning 6904 patients across 16 cancer types, and identified 167 splicing factors with implications regulating cancer-specific splicing patterns through alternative splicing. Furthermore, we found that abnormal splicing events of splicing factors could serve as potential common regulators for alternative splicing in different cancers. In addition, we developed a splicing-derived neoepitopes database (ASPNs), which provided the corresponding putative alternative splicing-derived neoepitopes of 16 cancer types. Our results suggested that alternative splicing of splicing factors involved in the pre-RNA splicing process was common across cancer types and may represent an underestimated hallmark of tumorigenesis.

Decoding human cancer with whole genome sequencing: a review of PCAWG Project studies published in February 2020

Cancer is underlined by genetic changes. In an unprecedented international effort, the Pan-Cancer Analysis of Whole Genomes (PCAWG) of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) sequenced the tumors of over two thousand five hundred patients across 38 different cancer types, as well as the corresponding healthy tissue, with the aim of identifying genome-wide mutations exclusively found in cancer and uncovering new genetic changes that drive tumor formation. What set this project apart from earlier efforts is the use of whole genome sequencing (WGS) that enabled to explore alterations beyond the coding DNA, into cancer's non-coding genome. WGS of the entire cohort allowed to tease apart driving mutations that initiate and support carcinogenesis from passenger mutations that do not play an overt role in the disease. At least one causative mutation was found in 95% of all cancers, with many tumors showing an average of 5 driver mutations. The PCAWG Project also assessed the transcriptional output altered in cancer and rebuilt the evolutionary history of each tumor showing that initial driver mutations can occur years if not decades prior to a diagnosis. Here, I provide a concise review of the Pan-Cancer Project papers published on February 2020, along with key computational tools and the digital framework generated as part of the project. This represents an historic effort by hundreds of international collaborators, which provides a comprehensive understanding of cancer genetics, with publicly available data and resources representing a treasure trove of information to advance cancer research for years to come.

Genome-wide profiling of alternative splicing in glioblastoma and their clinical value

Background

Alternative splicing (AS), one of the main post-transcriptional biological regulation mechanisms, plays a key role in the progression of glioblastoma (GBM). Systematic AS profiling in GBM is limited and urgently needed.

Methods

TCGA SpliceSeq data and the corresponding clinical data were downloaded from the TCGA data portal. Survival-related AS events were identified through Kaplan–Meier survival analysis and univariate Cox analysis. Then, splicing correlation network was constructed based on these AS events and associated splicing factors. LASSO regression followed by multivariate Cox analysis was performed to validate independent AS biomarkers and to construct a risk prediction model. Enrichment analysis was subsequently conducted to explore potential signaling pathways of these AS events.

Results

A total of 132 TCGA GBM samples and 45,610 AS events were included in our study, among which 416 survival-related AS events were identified. An AS correlation network, including 54 AS events and 94 splicing factors, was constructed, and further functional enrichment was performed. Moreover, the novel risk prediction model we constructed displayed moderate performance (the area under the curves were > 0.7) at both one, two and three years.

Conclusions

Survival-related AS events may be vital factors of both biological function and prognosis. Our findings in this study can deepen the understanding of the complicated mechanisms of AS in GBM and provide novel insights for further study. Moreover, our risk prediction model is ready for preliminary clinical applications. Further verification is required.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08681-z.

Comprehensive Characterization of RNA Processing Factors in Gastric Cancer Identifies a Prognostic Signature for Predicting Clinical Outcomes and Therapeutic Responses

RNA processing converts primary transcript RNA into mature RNA. Altered RNA processing drives tumor initiation and maintenance, and may generate novel therapeutic opportunities. However, the role of RNA processing factors in gastric cancer (GC) has not been clearly elucidated. This study presents a comprehensive analysis exploring the clinical, molecular, immune, and drug response features underlying the RNA processing factors in GC. This study included 1079 GC cases from The Cancer Genome Atlas (TCGA, training set), our hospital cohort, and two other external validation sets (GSE15459, GSE62254). We developed an RNA processing-related prognostic signature using Cox regression with the least absolute shrinkage and selection operator (LASSO) penalty. The prognostic value of the signature was evaluated using a multiple-method approach. The genetic variants, pathway activation, immune heterogeneity, drug response, and splicing features associated with the risk signature were explored using bioinformatics methods. Among the tested 819 RNA processing genes, we identified five distinct RNA processing patterns with specific clinical outcomes and biological features. A 10-gene RNA processing-related prognostic signature, involving ZBTB7A, METTL2B, CACTIN, TRUB2, POLDIP3, TSEN54, SUGP1, RBMS1, TGFB1, and PWP2, was further identified. The signature was a powerful and robust prognosis factor in both the training and validation datasets. Notably, it could stratify the survival of patients with GC in specific tumor-node-metastasis (TNM) classification subgroups. We constructed a composite prognostic nomogram to facilitate clinical practice by integrating this signature with other clinical variables (TNM stage, age). Patients with low-risk scores were characterized with good clinical outcomes, proliferation, and metabolism hallmarks. Conversely, poor clinical outcome, invasion, and metastasis hallmarks were enriched in the high-risk group. The RNA processing signature was also involved in tumor microenvironment reprogramming and regulating alternative splicing, causing different drug response features between the two risk groups. The low-risk subgroup was characterized by high genomic instability, high alternative splicing and might benefit from the immunotherapy. Our findings highlight the prognostic value of RNA processing factors for patients with GC and provide insights into the specific clinical and molecular features underlying the RNA processing-related signature, which may be important for patient management and targeting treatment.

Identification of prognostic and bone metastatic alternative splicing signatures in bladder cancer

Bladder cancer (BLCA), originating from the epithelium of the urinary bladder, was the second most common malignancy in the urinary system with a high metastasis rate and poor post-metastasis prognosis. Alternative splicing events (ASEs) were regarded as important markers of tumor progression and prognosis, however, their roles in bladder cancer bone metastasis have not been recognized. In this study, we constructed a predictive model based on ASEs and explored the molecular mechanism of ASEs in BLCA bone metastasis, based on data from the Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases. We proposed the hypothesis that the splicing events of ITGB4 was regulated by the splicing factor JUP, and this regulation might play a key role in BLCA bone metastasis through the glycosphingolipid biosynthesis ganglio series pathway.

CircURI1 interacts with hnRNPM to inhibit metastasis by modulating alternative splicing in gastric cancer

Circular RNAs (circRNAs) have emerged as key regulators of human cancers, yet their modes of action in gastric cancer (GC) remain largely unknown. Here, we identified circURI1 back-spliced from exons 3 and 4 of unconventional prefoldin RPB5 interactor 1 (URI1) from circRNA profiling of five-paired human gastric and the corresponding nontumor adjacent specimens (paraGC). CircURI1 exhibits the significantly higher expression in GC compared with paraGC and inhibitory effects on cell migration and invasion in vitro and GC metastasis in vivo. Mechanistically, circURI1 directly interacts with heterogeneous nuclear ribonucleoprotein M (hnRNPM) to modulate alternative splicing of genes, involved in the process of cell migration, thus suppressing GC metastasis. Collectively, our study expands the current knowledge regarding the molecular mechanism of circRNA-mediated cancer metastasis via modulating alternative splicing.

Maturation State-Specific Alternative Splicing in FLT3-ITD and NPM1 Mutated AML

Simple Summary

In hematological malignancies, genome-wide sequencing studies found the process of splicing to be surprisingly frequently disrupted. While recent studies characterized altered splicing in relation to splicing factor mutations in AML, this study explored differential splicing profiles associated with two most common aberrations in AML: FLT3-ITD and NPM1 mutations. We identified the differential splicing of FAB-type specific gene sets in FLT3-ITD+/NPM1+ specimens as compared to FLT3-ITD−/NPM1− samples. The primary functions perturbed by differential splicing in all three FAB types included cell cycle control and DNA damage response. Interestingly, differential expression mainly affected genes involved in hematopoietic differentiation. Our findings increase our understanding of how genetic mutations translate to phenotypic features of AML cells to further improve response predictions and to find innovative therapeutic approaches. Altogether, to the best of our knowledge, this is the first study to report differential splicing profiles associated with FLT3-ITD with a concomitant NPM1 mutation in AML.

Abstract

Despite substantial progress achieved in unraveling the genetics of AML in the past decade, its treatment outcome has not substantially improved. Therefore, it is important to better understand how genetic mutations translate to phenotypic features of AML cells to further improve response predictions and to find innovative therapeutic approaches. In this respect, aberrant splicing is a crucial contributor to the pathogenesis of hematological malignancies. Thus far, altered splicing is well characterized in relation to splicing factor mutations in AML. However, splicing profiles associated with mutations in other genes remain largely unexplored. In this study, we explored differential splicing profiles associated with two of the most common aberrations in AML: FLT3-ITD and NPM1 mutations. Using RNA-sequencing data of a total of 382 primary AML samples, we found that the co-occurrence of FLT3-ITD and mutated NPM1 is associated with differential splicing of FAB-type specific gene sets. Despite the FAB-type specificity of particular gene sets, the primary functions perturbed by differential splicing in all three FAB types include cell cycle control and DNA damage response. Interestingly, we observed functional divergence between alternatively spliced and differentially expressed genes in FLT3-ITD+/NPM1+ samples in all analyzed FAB types, with differential expression affecting genes involved in hematopoietic differentiation. Altogether, these observations indicate that concomitant FLT3-ITD and mutated NPM1 are associated with the maturation state-specific differential splicing of genes with potential oncogenic relevance.

Base editing-mediated perturbation of endogenous PKM1/2 splicing facilitates isoform-specific functional analysis in vitro and in vivo

OBJECTIVES

PKM1 and PKM2, which are generated from the alternative splicing of PKM gene, play important roles in tumourigenesis and embryonic development as rate-limiting enzymes in glycolytic pathway. However, because of the lack of appropriate techniques, the specific functions of the 2 PKM splicing isoforms have not been clarified endogenously yet.

MATERIALS AND METHODS

In this study, we used CRISPR-based base editors to perturbate the endogenous alternative splicing of PKM by introducing mutations into the splicing junction sites in HCT116 cells and zebrafish embryos. Sanger sequencing, agarose gel electrophoresis and targeted deep sequencing assays were utilized for identifying mutation efficiencies and detecting PKM1/2 splicing isoforms. Cell proliferation assays and RNA-seq analysis were performed to describe the effects of perturbation of PKM1/2 splicing in tumour cell growth and zebrafish embryo development.

RESULTS

The splicing sites of PKM, a 5' donor site of GT and a 3' acceptor site of AG, were efficiently mutated by cytosine base editor (CBE; BE4max) and adenine base editor (ABE; ABEmax-NG) with guide RNAs (gRNAs) targeting the splicing sites flanking exons 9 and 10 in HCT116 cells and/or zebrafish embryos. The mutations of the 5' donor sites of GT flanking exons 9 or 10 into GC resulted in specific loss of PKM1 or PKM2 expression as well as the increase in PKM2 or PKM1 respectively. Specific loss of PKM1 promoted cell proliferation of HCT116 cells and upregulated the expression of cell cycle regulators related to DNA replication and cell cycle phase transition. In contrast, specific loss of PKM2 suppressed cell growth of HCT116 cells and resulted in growth retardation of zebrafish. Meanwhile, we found that mutation of PKM1/2 splicing sites also perturbated the expression of non-canonical PKM isoforms and produced some novel splicing isoforms.

CONCLUSIONS

This work proved that CRISPR-based base editing strategy can be used to disrupt the endogenous alternative splicing of genes of interest to study the function of specific splicing isoforms in vitro and in vivo. It also reminded us to notice some novel or undesirable splicing isoforms by targeting the splicing junction sites using base editors. In sum, we establish a platform to perturbate endogenous RNA splicing for functional investigation or genetic correction of abnormal splicing events in human diseases.

Assessing conservation of alternative splicing with evolutionary splicing graphs

Understanding how protein function has evolved and diversified is of great importance for human genetics and medicine. Here, we tackle the problem of describing the whole transcript variability observed in several species by generalizing the definition of splicing graph. We provide a practical solution to construct parsimonious evolutionary splicing graphs where each node is a minimal transcript building block defined across species. We show a clear link between the functional relevance, tissue regulation, and conservation of alternative transcripts on a set of 50 genes. By scaling up to the whole human protein-coding genome, we identify a few thousand genes where alternative splicing modulates the number and composition of pseudorepeats. We have implemented our approach in ThorAxe, an efficient, versatile, robust, and freely available computational tool.

The role of NUMB/NUMB isoforms in cancer stem cells

Cancer stem cells (CSCs) are a subpopulation of cancer that can self-renew and differentiate into large tumor masses. Evidence accumulated to date shows that CSCs affect tumor proliferation, recurrence, and resistance to chemotherapy. Recent studies have shown that, like stem cells, CSCs maintain cells with self-renewal capacity by means of asymmetric division and promote cell proliferation by means of symmetric division. This cell division is regulated by fate determinants, such as the NUMB protein, which recently has also been confirmed as a tumor suppressor. Loss of NUMB expression leads to uncontrolled proliferation and amplification of the CSC pool, which promotes the Notch signaling pathway and reduces the expression of the p53 protein. NUMB genes are alternatively spliced to produce six functionally distinct isoforms. An interesting recent discovery is that the protein NUMB isoform produced by alternative splicing of NUMB plays an important role in promoting carcinogenesis. In this review, we summarize the known functions of NUMB and NUMB isoforms related to the proliferation and generation of CSCs.

Identification and Functional Characterization of Novel MYC-Regulated Long Noncoding RNAs in Group 3 Medulloblastoma

Simple Summary

Medulloblastoma is the most common malignant pediatric brain tumor, which accounts for approximately 20% of all childhood brain tumors. To date, no pharmacological approaches are decisive in the treatment of this cancer, while the secondary effects of conventional therapies as chemotherapy, radiotherapy or surgical interventions heavily affect the quality of life of patients. This requires the rapid development of alternative molecular therapies, which are the future challenge of personalized medicine. In this context, we addressed our research towards the most aggressive form of Medulloblastoma to identify novel genes responsible for its onset and/or progression. We discovered three newly implicated genes, for which we highlighted a contribution in the control of cancer cell features. Deepening into the Medulloblastoma biology, this study represents a further step forward for the development of molecular therapies in the era of precision oncology.

Abstract

The impact of protein-coding genes on cancer onset and progression is a well-established paradigm in molecular oncology. Nevertheless, unveiling the contribution of the noncoding genes—including long noncoding RNAs (lncRNAs)—to tumorigenesis represents a great challenge for personalized medicine, since they (i) constitute the majority of the human genome, (ii) are essential and flexible regulators of gene expression and (iii) present all types of genomic alterations described for protein-coding genes. LncRNAs have been increasingly associated with cancer, their highly tissue- and cancer type-specific expression making them attractive candidates as both biomarkers and therapeutic targets. Medulloblastoma is one of the most common malignant pediatric brain tumors. Group 3 is the most aggressive subgroup, showing the highest rate of metastasis at diagnosis. Transcriptomics and reverse genetics approaches were combined to identify lncRNAs implicated in Group 3 Medulloblastoma biology. Here we present the first collection of lncRNAs dependent on the activity of the MYC oncogene, the major driver gene of Group 3 Medulloblastoma. We assessed the expression profile of selected lncRNAs in Group 3 primary tumors and functionally characterized these species. Overall, our data demonstrate the direct involvement of three lncRNAs in Medulloblastoma cancer cell phenotypes.

Circular RNA circβ-catenin aggravates the malignant phenotype of non-small-cell lung cancer via encoding a peptide

Background

More and more evidences demonstrate that circular RNAs (circNRAs) can encode protein. As a circRNA with translation capabilities, outcomes of circβ‐catenin in non‐small cell lung cancer (NSCLC) still need to be explored.

Method

The research methods of circβ‐catenin in the article include qRT‐PCR, wound healing assay, CCK‐8, colony formation, and Transwell assay. Western blotting and immunofluorescence were provided to detect protein expression levels and peptide encoded by circβ‐catenin, respectively.

Results

A prominently higher circβ‐catenin expression was found in NSCLC tissues. Silencing of circβ‐catenin was able to inhibit NSCLC cell migrating, invasive, and proliferative phenotypes. Overexpression of circβ‐catenin could enhance the migrating, invasive, and proliferative phenotypes of NSCLC cells. Importantly, circβ‐catenin was found to encode a peptide in NSCLC cells. Silencing or overexpression of circβ‐catenin could reduce or increase β‐catenin protein expression via suppressing the degradation of β‐catenin.

Conclusion

Circβ‐catenin could promote NSCLC cell malignant phenotypes via peptide‐regulated β‐catenin pathway. Our study provided a new understanding for the mechanisms of NSCLC.

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

BACKGROUND

Malignant mesothelioma (MM) is a relatively rare and highly lethal tumor with few treatment options. Thus, it is important to identify prognostic markers that can help clinicians diagnose mesothelioma earlier and assess disease activity more accurately. Alternative splicing (AS) events have been recognized as critical signatures for tumor diagnosis and treatment in multiple cancers, including MM.

METHODS

We systematically examined the AS events and clinical information of 83 MM samples from TCGA database. Univariate Cox regression analysis was used to identify AS events associated with overall survival. LASSO analyses followed by multivariate Cox regression analyses were conducted to construct the prognostic signatures and assess the accuracy of these prognostic signatures by receiver operating characteristic (ROC) curve and Kaplan-Meier survival analyses. The ImmuCellAI and ssGSEA algorithms were used to assess the degrees of immune cell infiltration in MM samples. The survival-related splicing regulatory network was established based on the correlation between survival-related AS events and splicing factors (SFs).

RESULTS

A total of 3976 AS events associated with overall survival were identified by univariate Cox regression analysis, and ES events accounted for the greatest proportion. We constructed prognostic signatures based on survival-related AS events. The prognostic signatures proved to be an efficient predictor with an area under the curve (AUC) greater than 0.9. Additionally, the risk score based on 6 key AS events proved to be an independent prognostic factor, and a nomogram composed of 6 key AS events was established. We found that the risk score was significantly decreased in patients with the epithelioid subtype. In addition, unsupervised clustering clearly showed that the risk score was associated with immune cell infiltration. The abundances of cytotoxic T (Tc) cells, natural killer (NK) cells and T-helper 17 (Th17) cells were higher in the high-risk group, whereas the abundances of induced regulatory T (iTreg) cells were lower in the high-risk group. Finally, we identified 3 SFs (HSPB1, INTS1 and LUC7L2) that were significantly associated with MM patient survival and then constructed a regulatory network between the 3 SFs and survival-related AS to reveal potential regulatory mechanisms in MM.

CONCLUSION

Our study provided a prognostic signature based on 6 key events, representing a better effective tumor-specific diagnostic and prognostic marker than the TNM staging system. AS events that are correlated with the immune system may be potential therapeutic targets for MM.

Identification of 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.

DoChaP: the domain change presenter

Alternative splicing results in multiple transcripts of the same gene, possibly encoding for different protein isoforms with different domains. Whereas it is possible to manually determine the effect of alternative splicing on the domain composition for a single event, the process requires the tedious integration of several data sources; it is error prone and not feasible for genome-wide characterization of domains affected by differential splicing. To fulfill the need for an automated solution, we developed the Domain Change Presenter (DoChaP, https://dochap.bgu.ac.il/), a web server for the visualization of exon-domain associations. DoChaP visualizes all transcripts of a given gene, the encoded proteins and their domains, and enables a comparison between the transcripts and between their protein products. The colors and organization make the structural effect of alternative splicing events on protein structures easily identified. To enable the study of the conservation of exons structure, alternative splicing, and the effect of alternative splicing on protein domains, DoChaP also provides a two-species comparison of exon-domain associations. DoChaP thus provides a unique and easy-to-use visualization of the exon-domain association and conservation, and will facilitate the study of the structural effects of alternative splicing in health and disease.

KRT18 Modulates Alternative Splicing of Genes Involved in Proliferation and Apoptosis Processes in Both Gastric Cancer Cells and Clinical Samples

Keratin 18 (KRT18), one of the most abundant keratins in epithelial and endothelial cells, has been reported to be aberrantly expressed in many malignancies and extensively regarded as a biomarker and important regulator in multiple cancers, including gastric cancer (GC). But the molecular regulatory mechanisms of KRT18 in GC patients and cells are largely unknown. In the present study, we analyzed the expression level of KRT18 in 450 stomach adenocarcinoma tissue samples from TCGA database and found a significantly higher expression level in tumor tissues. We then explored the potential functions of KRT18 in AGS cells (human gastric adenocarcinoma cell line) by KRT18 knockdown using siRNA and whole transcriptome RNA-seq analysis. Notably, KRT18 selectively regulates expression of cell proliferation and apoptotic genes. Beyond this, KRT18 affects the alternative splicing of genes enriched in apoptosis, cell cycle, and other cancer-related pathways, which were then validated by reverse transcription-quantitative polymerase chain reaction approach. We validated KRT18-KD promoted apoptosis and inhibited proliferation in AGS cells. We then used RNA-seq data of GC samples to further demonstrate the modulation of KRT18 on alternative splicing regulation. These results together support the conclusion that KRT18 extensively modulates diverse alternative splicing events of genes enriched in proliferation and apoptosis processes. And the dysregulated splicing factors at transcriptional or posttranscriptional level by KRT18 may contribute to the alternative splicing change of many genes, which expands the functional importance of keratins in apoptotic and cell cycle pathways at the posttranscriptional level in GC.

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 role of NUMB/NUMB isoforms in cancer stem cells

Cancer stem cells (CSCs) are a subpopulation of cancer that can self-renew and differentiate into large tumor masses. Evidence accumulated to date shows that CSCs affect tumor proliferation, recurrence, and resistance to chemotherapy. Recent studies have shown that, like stem cells, CSCs maintain cells with self-renewal capacity by means of asymmetric division and promote cell proliferation by means of symmetric division. This cell division is regulated by fate determinants, such as the NUMB protein, which recently has also been confirmed as a tumor suppressor. Loss of NUMB expression leads to uncontrolled proliferation and amplification of the CSC pool, which promotes the Notch signaling pathway and reduces the expression of the p53 protein. NUMB genes are alternatively spliced to produce six functionally distinct isoforms. An interesting recent discovery is that the protein NUMB isoform produced by alternative splicing of NUMB plays an important role in promoting carcinogenesis. In this review, we summarize the known functions of NUMB and NUMB isoforms related to the proliferation and generation of CSCs. [BMB Reports 2021; 54(7): 335-343].

SUVA: splicing site usage variation analysis from RNA-seq data reveals highly conserved complex splicing biomarkers in liver cancer

Most of the current alternative splicing (AS) analysis tools are powerless to analyse complex splicing. To address this, we developed SUVA (Splice sites Usage Variation Analysis) that decomposes complex splicing events into five types of splice junction pairs. By analysing real and simulated data, SUVA showed higher sensitivity and accuracy in detecting AS events than the compared methods. Notably, SUVA detected extensive complex AS events and screened out 69 highly conserved and dominant AS events associated with cancer. The cancer-associated complex AS events in FN1 and the co-regulated RNA-binding proteins were significantly correlated with patient survival.

Alternative splicing associated with cancer stemness in kidney renal clear cell carcinoma

Backgroud

Cancer stemness is associated with metastases in kidney renal clear cell carcinoma (KIRC) and negatively correlates with immune infiltrates. Recent stemness evaluation methods based on the absolute expression have been proposed to reveal the relationship between stemness and cancer. However, we found that existing methods do not perform well in assessing the stemness of KIRC patients, and they overlooked the impact of alternative splicing. Alternative splicing not only progresses during the differentiation of stem cells, but also changes during the acquisition of the stemness features of cancer stem cells. There is an urgent need for a new method to predict KIRC-specific stemness more accurately, so as to provide help in selecting treatment options.

Methods

The corresponding RNA-Seq data were obtained from the The Cancer Genome Atlas (TCGA) data portal. We also downloaded stem cell RNA sequence data from the Progenitor Cell Biology Consortium (PCBC) Synapse Portal. Independent validation sets with large sample size and common clinic pathological characteristics were obtained from the Gene Expression Omnibus (GEO) database. we constructed a KIRC-specific stemness prediction model using an algorithm called one-class logistic regression based on the expression and alternative splicing data to predict stemness indices of KIRC patients, and the model was externally validated. We identify stemness-associated alternative splicing events (SASEs) by analyzing different alternative splicing event between high- and low- stemness groups. Univariate Cox and multivariable logistic regression analysisw as carried out to detect the prognosis-related SASEs respectively. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of our model.

Results

Here, we constructed a KIRC-specific stemness prediction model with an AUC of 0.968,and to provide a user-friendly interface of our model for KIRC stemness analysis, we have developed KIRC Stemness Calculator and Visualization (KSCV), hosted on the Shiny server, can most easily be accessed via web browser and the url https://jiang-lab.shinyapps.io/kscv/. When applied to 605 KIRC patients, our stemness indices had a higher correlation with the gender, smoking history and metastasis of the patients than the previous stemness indices, and revealed intratumor heterogeneity at the stemness level. We identified 77 novel SASEs by dividing patients into high- and low- stemness groups with significantly different outcome and they had significant correlations with expression of 17 experimentally validated splicing factors. Both univariate and multivariate survival analysis demonstrated that SASEs closely correlated with the overall survival of patients.

Conclusions

Basing on the stemness indices, we found that not only immune infiltration but also alternative splicing events showed significant different at the stemness level. More importantly, we highlight the critical role of these differential alternative splicing events in poor prognosis, and we believe in the potential for their further translation into targets for immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08470-8.

Multimodal detection of protein isoforms and nucleic acids from low starting cell numbers

Protein isoforms play a key role in disease progression and arise from mechanisms involving multiple molecular subtypes, including DNA, mRNA and protein. Recently introduced multimodal assays successfully link genomes and transcriptomes to protein expression landscapes. However, the specificity of the protein measurement relies on antibodies alone, leading to major challenges when measuring different isoforms of the same protein. Here we utilize microfluidic design to perform same-cell profiling of DNA, mRNA and protein isoforms (triBlot) on low starting cell numbers (1-100 s of cells). After fractionation lysis, cytoplasmic proteins are resolved by molecular mass during polyacrylamide gel electrophoresis (PAGE), adding a degree of specificity to the protein measurement, while nuclei are excised from the device in sections termed "gel pallets" for subsequent off-chip nucleic acid analysis. By assaying TurboGFP-transduced glioblastoma cells, we observe a strong correlation between protein expression prior to lysis and immunoprobed protein. We measure both mRNA and DNA from retrieved nuclei, and find that mRNA levels correlate with protein abundance in TurboGFP-expressing cells. Furthermore, we detect the presence of TurboGFP isoforms differing by an estimated <1 kDa in molecular mass, demonstrating the ability to discern different proteoforms with the same antibody probe. By directly relating nucleic acid modifications to protein isoform expression in 1-100 s of cells, the triBlot assay holds potential as a screening tool for novel biomarkers in diseases driven by protein isoform expression.

Identification of Prognostic alternative splicing signatures and their clinical significance in uveal melanoma

As a posttranscriptional regulatory mechanism, alternative splicing (AS) has the potential to generate a large amount of protein diversity from limited genes. The purpose of our study was to assess the usefulness of prognostic splicing events as novel diagnostic and therapeutic signatures for uveal melanoma (UM). The datasets, clinical traits and AS data of UM were obtained from The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database. Using bioinformatics analysis, we identified 1047 AS events as candidate AS events closely related to prognosis from 920 parent genes. The gene enrichment analysis indicated that these genes were mainly enriched in cellular components (CC) including cytosol, nucleoplasm, cytoplasm and ribosome, and in molecular functions (MF), including protein binding and poly(A) RNA binding. Furthermore, we selected all survival-associated splicing events to generate prognostic signatures, which included 4 exon skip (ES) events (DNASE1L1-90581-ES, NUDT1-78611-ES, BIN1-55198-ES, SEPN1-1195-ES) and 1 alternate promoter (AP) event (DPYSL2-83132-AP). The AS prognostic model was confirmed as independent overall survival (OS)-related factors (p = 0.014). A total of 17 splicing factors (SFs) involved in the regulation of AS were identified as related to the OS of UM patients. Our pooled data highlighted the usefulness and importance of AS biomarkers, which provided a potential strategy for the diagnosis and treatment of UM.

Long noncoding RNA DGCR5 involves in tumorigenesis of esophageal squamous cell carcinoma via SRSF1-mediated alternative splicing of Mcl-1

Long noncoding RNAs (lncRNAs) emerge as essential roles in the regulation of alternative splicing (AS) in various malignancies. Serine- and arginine-rich splicing factor 1 (SRSF1)-mediated AS events are the most important molecular hallmarks in cancer. Nevertheless, the biological mechanism underlying tumorigenesis of lncRNAs correlated with SRSF1 in esophageal squamous cell carcinoma (ESCC) remains elusive. In this study, we found that lncRNA DiGeorge syndrome critical region gene 5 (DGCR5) was upregulated in ESCC clinical samples, which associated with poor prognosis. Through RNA interference and overexpression approaches, we confirmed that DGCR5 contributed to promote ESCC cell proliferation, migration, and invasion while inhibited apoptosis in vitro. Mechanistically, DGCR5 could directly bind with SRSF1 to increase its stability and thus stimulate alternative splicing events. Furthermore, we clarified that SRSF1 regulated the aberrant splicing of myeloid cell leukemia-1 (Mcl-1) and initiated a significant Mcl-1L (antiapoptotic) isoform switch, which contributed to the expression of the full length of Mcl-1. Moreover, the cell-derived xenograft (CDX) model was validated that DGCR5 could facilitate the tumorigenesis of ESCC in vivo. Collectively, our findings identified that the key biological role of lncRNA DGCR5 in alternative splicing regulation and emphasized DGCR5 as a potential biomarker and therapeutic target for ESCC.

Survival-associated alternative splicing events interact with the immune microenvironment in stomach adenocarcinoma

BACKGROUND

Alternative splicing (AS) increases the diversity of mRNA during transcription; it might play a role in alteration of the immune microenvironment, which could influence the development of immunotherapeutic strategies against cancer.

AIM

To obtain the transcriptomic and clinical features and AS events in stomach adenocarcinoma (STAD) from the database. The overall survival data associated with AS events were used to construct a signature prognostic model for STAD.

METHODS

Differentially expressed immune-related genes were identified between subtypes on the basis of the prognostic model. In STAD, 2042 overall-survival-related AS events were significantly enriched in various pathways and influenced several cellular functions. Furthermore, the network of splicing factors and overall-survival-associated AS events indicated potential regulatory mechanisms underlying the AS events in STAD.

RESULTS

An eleven-AS-signature prognostic model (CD44|14986|ES, PPHLN1|21214|AT, RASSF4|11351|ES, KIAA1147|82046|AP, PPP2R5D|76200|ES, LOH12CR1|20507|ES, CDKN3|27569|AP, UBA52|48486|AD, CADPS|65499|AT, SRSF7| 53276|RI, and WEE1|14328|AP) was constructed and significantly related to STAD overall survival, immune cells, and cancer-related pathways. The differentially expressed immune-related genes between the high- and low-risk score groups were significantly enriched in cancer-related pathways.

CONCLUSION

This study provided an AS-related prognostic model, potential mechanisms for AS, and alterations in the immune microenvironment (immune cells, genes, and pathways) for future research in STAD.

CD46 splice variant enhances translation of specific mRNAs linked to an aggressive tumor cell phenotype in bladder cancer

CD46 is well known to be involved in diverse biological processes. Although several splice variants of CD46 have been identified, little is known about the contribution of alternative splicing to its tumorigenic functions. In this study, we found that exclusion of CD46 exon 13 is significantly increased in bladder cancer (BCa) samples. In BCa cell lines, enforced expression of CD46-CYT2 (exon 13-skipping isoform) promoted, and CD46-CYT1 (exon 13-containing isoform) attenuated, cell growth, migration, and tumorigenicity in a xenograft model. We also applied interaction proteomics to identify exhaustively the complexes containing the CYT1 or CYT2 domain in EJ-1 cells. 320 proteins were identified that interact with the CYT1 and/or CYT2 domain, and most of them are new interactors. Using an internal ribosome entry site (IRES)-dependent reporter system, we established that CD46 could regulate mRNA translation through an interaction with the translation machinery. We also identified heterogeneous nuclear ribonucleoprotein (hnRNP)A1 as a novel CYT2 binding partner, and this interaction facilitates the interaction of hnRNPA1 with IRES RNA to promote IRES-dependent translation of HIF1a and c-Myc. Strikingly, the splicing factor SRSF1 is highly correlated with CD46 exon 13 exclusion in clinical BCa samples. Taken together, our findings contribute to understanding the role of CD46 in BCa development.

Expression and cell transformation activity of dynactin-associated protein isoforms

Overexpression of human dynactin-associated protein isoform a (dynAPa) transforms NIH3T3 cells. DynAPa is a single-pass transmembrane protein with a carboxy-terminal region exposed to the outside of cells. According to the NCBI RefSeq database, there may be two other splicing variants of the encoding gene (dynAPb and c). DynAPa and c differ in some amino-terminal residues (NH₂ -MVA in dynAPa and NH₂ -MEYQLL in dynAPc). DynAPb has the same amino-terminal residues as dynAPc, but lacks 55 residues in the intracellular region. All three isoforms have the same carboxy-terminal region, including the transmembrane domain. Expression of mRNAs of three splicing variants was found in human cancer cell lines ACHN and Caki-1. The subcellular localization and in vitro cell transformation ability of the three isoforms were examined using NIH3T3 cells overexpressing each respective isoform. All isoforms were found to be localized to the Golgi apparatus and plasma membrane, where the carboxy-terminal region was exposed to the outside of cells. Cell transformation was tested using focus formation due to loss of contact inhibition of cell proliferation, and colony formation was examined on soft agar and spheroid formation in ultralow U-bottomed wells. DynAPa robustly formed foci and colonies on soft agar and spheroid, whereas these abilities were considerably decreased for dynAPb and completely lost in dynAPc. These findings warrant dissection studies to identify the dynAP domain that is required for cell transformation.

Disease-specific interactome alterations via epichaperomics: the case for Alzheimer's disease

The increasingly appreciated prevalence of complicated stressor-to-phenotype associations in human disease requires a greater understanding of how specific stressors affect systems or interactome properties. Many currently untreatable diseases arise due to variations in, and through a combination of, multiple stressors of genetic, epigenetic, and environmental nature. Unfortunately, how such stressors lead to a specific disease phenotype or inflict a vulnerability to some cells and tissues but not others remains largely unknown and unsatisfactorily addressed. Analysis of cell- and tissue-specific interactome networks may shed light on organization of biological systems and subsequently to disease vulnerabilities. However, deriving human interactomes across different cell and disease contexts remains a challenge. To this end, this opinion article links stressor-induced protein interactome network perturbations to the formation of pathologic scaffolds termed epichaperomes, revealing a viable and reproducible experimental solution to obtaining rigorous context-dependent interactomes. This article presents our views on how a specialized 'omics platform called epichaperomics may complement and enhance the currently available conventional approaches and aid the scientific community in defining, understanding, and ultimately controlling interactome networks of complex diseases such as Alzheimer's disease. Ultimately, this approach may aid the transition from a limited single-alteration perspective in disease to a comprehensive network-based mindset, which we posit will result in precision medicine paradigms for disease diagnosis and 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 acts as an independent prognosticator in ovarian carcinoma

Alternative splicing (AS) events associated with oncogenic processes present anomalous perturbations in many cancers, including ovarian carcinoma. There are no reliable features to predict survival outcomes for ovarian cancer patients. In this study, comprehensive profiling of AS events was conducted by integrating AS data and clinical information of ovarian serous cystadenocarcinoma (OV). Survival-related AS events were identified by Univariate Cox regression analysis. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to construct the prognostic signatures within each AS type. Furthermore, we established a splicing-related network to reveal the potential regulatory mechanisms between splicing factors and candidate AS events. A total of 730 AS events were identified as survival-associated splicing events, and the final prognostic signature based on all seven types of AS events could serve as an independent prognostic indicator and had powerful efficiency in distinguishing patient outcomes. In addition, survival-related AS events might be involved in tumor-related pathways including base excision repair and pyrimidine metabolism pathways, and some splicing factors might be correlated with prognosis-related AS events, including SPEN, SF3B5, RNPC3, LUC7L3, SRSF11 and PRPF38B. Our study constructs an independent prognostic signature for predicting ovarian cancer patients’ survival outcome and contributes to elucidating the underlying mechanism of AS in tumor development.

A prometastatic splicing program regulated by SNRPA1 interactions with structured RNA elements

Aberrant alternative splicing is a hallmark of cancer, yet the underlying regulatory programs that control this process remain largely unknown. Here, we report a systematic effort to decipher the RNA structural code that shapes pathological splicing during breast cancer metastasis. We discovered a previously unknown structural splicing enhancer that is enriched near cassette exons with increased inclusion in highly metastatic cells. We show that the spliceosomal protein small nuclear ribonucleoprotein polypeptide A' (SNRPA1) interacts with these enhancers to promote cassette exon inclusion. This interaction enhances metastatic lung colonization and cancer cell invasion, in part through SNRPA1-mediated regulation of PLEC alternative splicing, which can be counteracted by splicing modulating morpholinos. Our findings establish a noncanonical regulatory role for SNRPA1 as a prometastatic splicing enhancer in breast cancer.