Significance of alternative splicing in cancer cells

Splicing factor hnRNPA1 regulates alternative splicing of LOXL2 to enhance the production of LOXL2Δ13

Lysyl oxidase-like 2 (LOXL2) is a member of the lysyl oxidase family and has the ability to catalyze the cross-linking of extracellular matrix collagen and elastin. High expression of LOXL2 is related to tumor cell proliferation, invasion, and metastasis. LOXL2 contains 14 exons. Previous studies have found that LOXL2 has abnormal alternative splicing and exon skipping in a variety of tissues and cells, resulting in a new alternatively spliced isoform denoted LOXL2Δ13. LOXL2Δ13 lacks LOXL2WT exon 13, but its encoded protein has greater ability to induce tumor cell proliferation, invasion, and metastasis. However, the molecular events that produce LOXL2Δ13 are still unclear. In this study, we found that overexpression of the splicing factor hnRNPA1 in cells can regulate the alternative splicing of LOXL2 and increase the expression of LOXL2Δ13. The exonic splicing silencer exists at the 3' splice site and 5' splice site of LOXL2 exon 13. HnRNPA1 can bind to the exonic splicing silencer and inhibit the inclusion of exon 13. The RRM domain of hnRNPA1 and phosphorylation of hnRNPA1 at S91 and S95 are important for the regulation of LOXL2 alternative splicing. These results show that hnRNPA1 is a splicing factor that enhances the production of LOXL2Δ13.

MAPP unravels frequent co-regulation of splicing and polyadenylation by RNA-binding proteins and their dysregulation in cancer

Maturation of eukaryotic pre-mRNAs via splicing and polyadenylation is modulated across cell types and conditions by a variety of RNA-binding proteins (RBPs). Although there exist over 1,500 RBPs in human cells, their binding motifs and functions still remain to be elucidated, especially in the complex environment of tissues and in the context of diseases. To overcome the lack of methods for the systematic and automated detection of sequence motif-guided pre-mRNA processing regulation from RNA sequencing (RNA-Seq) data we have developed MAPP (Motif Activity on Pre-mRNA Processing). Applying MAPP to RBP knock-down experiments reveals that many RBPs regulate both splicing and polyadenylation of nascent transcripts by acting on similar sequence motifs. MAPP not only infers these sequence motifs, but also unravels the position-dependent impact of the RBPs on pre-mRNA processing. Interestingly, all investigated RBPs that act on both splicing and 3' end processing exhibit a consistently repressive or activating effect on both processes, providing a first glimpse on the underlying mechanism. Applying MAPP to normal and malignant brain tissue samples unveils that the motifs bound by the PTBP1 and RBFOX RBPs coordinately drive the oncogenic splicing program active in glioblastomas demonstrating that MAPP paves the way for characterizing pre-mRNA processing regulators under physiological and pathological conditions.

Comprehensive analysis of CPSF4-related alternative splice genes in hepatocellular carcinoma

BACKGROUND

An important stage in controlling gene expression is RNA alternative splicing (AS), and aberrant AS can trigger the development and spread of malignancies, including hepatocellular carcinoma (HCC). A crucial component of AS is cleavage and polyadenylation-specific factor 4 (CPSF4), a component of the CPSF complex, but it is unclear how CPSF4-related AS molecules describe immune cell infiltration in the total tumor microenvironment (TME).

METHODS

Using RNA-sequencing data and clinical data from TCGA-LIHC from the Cancer Genome Atlas (TCGA) database, the AS genes with differential expression were found. The univariate Cox analysis, KM analysis, and Spearman analysis were used to identify the AS genes related to prognosis. Screening of key AS genes that are highly correlated with CPSF4. Key genes were screened using Cox regression analysis and stepwise regression analysis, and prognosis prediction models and the topography of TME cell infiltration were thoroughly analyzed.

RESULTS

A model consisting of seven AS genes (STMN1, CLSPN, MDK, RNFT2, PRR11, RNF157, GHR) was constructed that was aimed to predict prognostic condition. The outcomes of the HCC samples in the high-risk group were considerably worse than those in the lower risk group (p < 0.0001), and different risk patient groups were formed. According to the calibration curves and the area under the ROC curve (AUC) values for survival at 1, 2, and 3 years, the clinical nomogram performs well in predicting survival in HCC patients. These values were 0.76, 0.70, and 0.69, respectively. Moreover, prognostic signature was markedly related to immune infiltration and immune checkpoint genes expression.

CONCLUSION

By shedding light on the function of CPSF4 and the seven AS genes in the formation and progression of HCC, this research analysis contributes to the development of more useful prognostic, diagnostic, and possibly therapeutic biomarkers.

Principal Component Analysis of Alternative Splicing Profiles Revealed by Long-Read ONT Sequencing in Human Liver Tissue and Hepatocyte-Derived HepG2 and Huh7 Cell Lines

The long-read RNA sequencing developed by Oxford Nanopore Technology provides a direct quantification of transcript isoforms. That makes the number of transcript isoforms per gene an intrinsically suitable metric for alternative splicing (AS) profiling in the application to this particular type of RNA sequencing. By using this simple metric and recruiting principal component analysis (PCA) as a tool to visualize the high-dimensional transcriptomic data, we were able to group biospecimens of normal human liver tissue and hepatocyte-derived malignant HepG2 and Huh7 cells into clear clusters in a 2D space. For the transcriptome-wide analysis, the clustering was observed regardless whether all genes were included in analysis or only those expressed in all biospecimens tested. However, in the application to a particular set of genes known as pharmacogenes, which are involved in drug metabolism, the clustering worsened dramatically in the latter case. Based on PCA data, the subsets of genes most contributing to biospecimens' grouping into clusters were selected and subjected to gene ontology analysis that allowed us to determine the top 20 biological processes among which translation and processes related to its regulation dominate. The suggested metrics can be a useful addition to the existing metrics for describing AS profiles, especially in application to transcriptome studies with long-read sequencing.

Splicing Characterization and Isoform Switch Events in Human Keratinocytes Carrying Oncogenes from High-Risk HPV-16 and Low-Risk HPV-84

Infection of epithelial cells with high-risk HPV (HR-HPV) types, followed by expression of virus oncogenic proteins (E5, E6, and E7), leads to genomic imbalance, suppression of tumor inhibitors, and induction of oncogenes. Low-risk HPV (LR-HPV) may slow the rate at which cervical cancer spreads to an invasive stage since co-infection with LR-HPV is linked to a decreased risk of future invasive cancer than infection with HR-HPV alone. We then propose that cancer-progressing changes may be distinguished through identifying the functional differences between LR-HPV and HR-HPV. Lentiviral strategies were followed to establish HaCaT cells with constitutive expression of HPV oncogenes. RNAseq experiments were designed to analyze the transcriptome modulations caused by each of the E5, E6, and E7 oncogenes of HPV-16 and HPV-84 in HaCaT cells. We identified enhanced RNA degradation, spliceosome, and RNA polymerase pathways related to mRNA processing. ATTS (alternative transcription termination site) was discovered to be more prevalent in cells with HPV-16E5 than HPV-84E5. In HPV-16E6-infected cells, ATTS gain was significantly higher than ATTS loss. Cells with HPV-16E7 had more isoforms with intron retention (IR) than those with HPV-84E7. We identified switches in ADAM10, CLSPN, and RNPS1 that led to greater expression of the coding isoforms in HR-HPV. The results of this work highlight differences between LR-HPV and HR-HPV in mRNA processing. Moreover, crucial cervical cancer-related switch events were detected.

Identification of TSGA10 and GGNBP2 splicing variants in 5' untranslated region with distinct expression profiles in brain tumor samples

Introduction

Brain tumors (BTs) are perceived as one of the most common malignancies among children. The specific regulation of each gene can play a critical role in cancer progression. The present study aimed to determine the transcripts of the TSGA10 and GGNBP2 genes, considering the alternative 5'UTR region, and investigating the expression of these different transcripts in BTs.

Material and methods

Public data on brain tumor microarray datasets in GEO were analyzed with R software to evaluate the expression levels of TSGA10 and GGNBP2 genes (the Pheatmap package in R was also used to plot DEGs in a heat map). In addition, to validate our in-silico data analysis, RT-PCR was performed to determine the splicing variants of TSGA10 and GGNBP2 genes in testis and brain tumor samples. The expression levels of splice variants of these genes were analyzed in 30 brain tumor samples and two testicular tissue samples as a positive control.

Results

In silico results show that the differential expression levels of TSGA10 and GGNBP2 were significant in the GEO datasets of BTs compared to normal samples (with adjusted p-value<0.05 and log fold change > 1). This study's experimental results showed that the TSGA10 gene produces four different transcripts with two distinct promoter regions and splicing exon 4. The relative mRNA expression of transcripts without exon 4 was higher than transcripts with exon 4 in BT samples (p-value<001). In GGNBP2, exon 2 in the 5'UTR region and exon 6 in the coding sequence were spliced. The expression analysis results showed that the relative mRNA expression of transcript variants without exon 2 was higher than other transcript variants with exon 2 in BT samples (p-value<001).

Conclusion

The decreased expression levels of transcripts with longer 5'UTR in BT samples than in testicular or low-grade brain tumor samples may decrease their translation efficiency. Therefore, decreased amounts of TSGA10 and GGNBP2 as potential tumor suppressor proteins, especially in high-grade brain tumors, may cause cancer development by angiogenesis and metastasis.

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.

The Grb2 splice variant, Grb3-3, is a negative regulator of RAS activation

Activation of RAS is crucial in driving cellular outcomes including proliferation, differentiation, migration and apoptosis via the MAPK pathway. This is initiated on recruitment of Grb2, as part of a Grb2-Sos complex, to an up-regulated receptor tyrosine kinase (RTK), enabling subsequent interaction of Sos with the plasma membrane-localised RAS. Aberrant regulation at this convergence point for RTKs in MAPK signalling is a key driver of multiple cancers. Splicing of the GRB2 gene produces a deletion variant, Grb3-3, that is incapable of binding to RTKs. We show that, despite maintaining the ability to bind to Sos, the Grb3-3-Sos complex remains in the cytoplasm, unable to engage with RAS. Competition between Grb2 and Grb3-3 for binding to C-terminal proline-rich sequences on Sos modulates MAPK signalling. Additionally, we demonstrate that splicing is regulated by heterogenous nuclear riboproteins C1/C2, and that normal and malignant colon tissue show differential Grb3-3 expression.

Bilayer Forming Phospholipids as Targets for Cancer Therapy

Phospholipids represent a crucial component for the structure of cell membranes. Phosphatidylcholine and phosphatidylethanolamine are two phospholipids that comprise the majority of cell membranes. De novo biosynthesis of phosphatidylcholine and phosphatidylethanolamine occurs via the Kennedy pathway, and perturbations in the regulation of this pathway are linked to a variety of human diseases, including cancer. Altered phosphatidylcholine and phosphatidylethanolamine membrane content, phospholipid metabolite levels, and fatty acid profiles are frequently identified as hallmarks of cancer development and progression. This review summarizes the research on how phospholipid metabolism changes over oncogenic transformation, and how phospholipid profiling can differentiate between human cancer and healthy tissues, with a focus on colorectal cancer, breast cancer, and non-small cell lung cancer. The potential for phospholipids to serve as biomarkers for diagnostics, or as anticancer therapy targets, is also discussed.

SRSF1 governs progenitor-specific alternative splicing to maintain adult epithelial tissue homeostasis and renewal

Alternative splicing generates distinct mRNA variants and is essential for development, homeostasis, and renewal. Proteins of the serine/arginine (SR)-rich splicing factor family are major splicing regulators that are broadly required for organ development as well as cell and organism viability. However, how these proteins support adult organ function remains largely unknown. Here, we used the continuously growing mouse incisor as a model to dissect the functions of the prototypical SR family protein SRSF1 during tissue homeostasis and renewal. We identified an SRSF1-governed alternative splicing network that is specifically required for dental proliferation and survival of progenitors but dispensable for the viability of differentiated cells. We also observed a similar progenitor-specific role of SRSF1 in the small intestinal epithelium, indicating a conserved function of SRSF1 across adult epithelial tissues. Thus, our findings define a regulatory mechanism by which SRSF1 specifically controls progenitor-specific alternative splicing events to support adult tissue homeostasis and renewal.

SRSF3 Promotes Angiogenesis in Colorectal Cancer by Splicing SRF

SRSF3, an important member of the serine/arginine-rich protein (SRp) family, is highly expressed in various tumors and plays an important role in tumor cell proliferation, migration and invasion. However, it is still unclear whether SRSF3 is involved in tumor angiogenesis. In this study, we first revealed that SRSF3 regulated the expression of numerous genes related to angiogenesis, including proangiogenic SRF. Then, we confirmed that SRSF3 was highly expressed in colorectal cancer (CRC) and was positively correlated with SRF. Mechanistic studies revealed that SRSF3 directly bound to the “CAUC” motif in exon 6 of SRF and induced the exclusion of introns. Knockdown of SRSF3 significantly reduced the secretion of VEGF from CRC cells. Conditioned medium from SRSF3-knockdown CRC cells significantly inhibited the migration, invasion and tube formation of human umbilical vein endothelial cells (HUVECs). In addition, SRF silencing inhibited angiogenesis, while SRF overexpression reversed the antiangiogenic effects of SRSF3 knockdown on tube formation. These findings indicate that SRSF3 is involved in the splicing of SRF and thereby regulates the angiogenesis of CRC, which offers novel insight into antiangiogenic therapy in CRC.

Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers

Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cases to an unfavourable prognosis. Current predictive algorithms used to estimate the risk of having Ovarian Cancer fail to provide sufficient sensitivity and specificity to be used widely in clinical practice. The use of additional biomarkers or parameters such as age or menopausal status to overcome these issues showed only weak improvements. It is necessary to identify novel molecular signatures and the development of new predictive algorithms able to support the diagnosis of HGSOC, and at the same time, deepen the understanding of this elusive disease, with the final goal of improving patient survival. Here, we apply a Machine Learning-based pipeline to an open-source HGSOC Proteomic dataset to develop a decision support system (DSS) that displayed high discerning ability on a dataset of HGSOC biopsies. The proposed DSS consists of a double-step feature selection and a decision tree, with the resulting output consisting of a combination of three highly discriminating proteins: TOP1, PDIA4, and OGN, that could be of interest for further clinical and experimental validation. Furthermore, we took advantage of the ranked list of proteins generated during the feature selection steps to perform a pathway analysis to provide a snapshot of the main deregulated pathways of HGSOC. The datasets used for this study are available in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data portal (https://cptac-data-portal.georgetown.edu/).

Identification of tumour immune microenvironment-related alternative splicing events for the prognostication of pancreatic adenocarcinoma

PURPOSE

Pancreatic adenocarcinoma (PAAD) is characterized by low antitumour immune cell infiltration in an immunosuppressive microenvironment. This study aimed to systematically explore the impact on prognostic alternative splicing events (ASs) of tumour immune microenvironment (TIME) in PAAD.

METHODS

The ESTIMATE algorithm was implemented to compute the stromal/immune-related scores of each PAAD patient, followed by Kaplan-Meier (KM) survival analysis of patients with different scores grouped by X-tile software. TIME-related differentially expressed ASs (DEASs) were determined and evaluated through functional annotation analysis. In addition, Cox analyses were implemented to construct a TIME-related signature and an AS clinical nomogram. Moreover, comprehensive analyses, including gene set enrichment analysis (GSEA), immune infiltration, immune checkpoint gene expression, and tumour mutation were performed between the two risk groups to understand the potential mechanisms. Finally, Cytoscape was implemented to illuminate the AS-splicing factor (SF) regulatory network.

RESULTS

A total of 437 TIME-related DEASs significantly related to PAAD tumorigenesis and the formation of the TIME were identified. Additionally, a robust TIME-related prognostic signature based on seven DEASs was generated, and an AS clinical nomogram combining the signature and four clinical predictors also exhibited prominent discrimination by ROC (0.762 ~ 0.804) and calibration curves. More importantly, the fractions of CD8 T cells, regulatory T cells and activated memory CD4 T cells were lower, and the expression of four immune checkpoints-PD-L1, CD47, CD276, and PVR-was obviously higher in high-risk patients. Finally, functional analysis and tumour mutations revealed that aberrant immune signatures and activated carcinogenic pathways in high-risk patients may be the cause of the poor prognosis.

CONCLUSION

We extracted a list of DEASs associated with the TIME through the ESTIMATE algorithm and constructed a prognostic signature on the basis of seven DEASs to predict the prognosis of PAAD patients, which may guide advanced decision-making for personalized precision intervention.

Analysis of Prognostic Alternative Splicing Reveals the Landscape of Immune Microenvironment in Thyroid Cancer

Background

The incidence of thyroid cancer (THCA) continues to increase in recent decades. Accumulating evidence showed that the unbalanced alternative splicing (AS) promotes the occurrence of cancers and leads to poor prognosis of patients. However, the research on alternative splicing events in THCA is lacking, and its underlying mechanism is not fully understood. This study identifies a novel prognostic signature based on AS events to reveal the relationship of AS with tumor immune microenvironment.

Methods

Based on the AS data, transcriptional data, and clinical information, the differentially expressed alternative splicings (DEASs) were screened out. Least absolute shrinkage and selection operator (LASSO) regression and multi-Cox regression analyses were employed to identify prognostic results related to AS events and establish a prognostic signature. The predictive ability of the signature was assessed by Kaplan-Meier (K-M) survival curve, risk plots, and receiver operating characteristic (ROC) curves. Furthermore, correlations between tumor-infiltrating immune cells, immune checkpoints, immune score and prognostic signature were analyzed.

Results

According to the LASSO regression analysis, a total of five AS events were selected to construct the signature. K-M survival curve showed that the higher the risk score, the worse the OS of the patients. Risk plots further confirmed this result. ROC curves indicated the high predictive efficiency of the prognostic signature. As for tumor immune microenvironment, patients in the high-risk group had a higher proportion of immune cells, including plasma cell, CD8+ T cell, macrophages (M0 and M2), and activated dendritic cell. Immune checkpoint proteins, such as PDCD1LG2, HAVCR2, CD274, etc., were significantly higher in the high-risk group. We also found that the ESTIMATE score, stromal score, and immune score were lower in the high-risk group, while the result of tumor purity was the opposite.

Conclusions

Collectively, a prognostic signature consisting of five AS events in THCA was established. Furthermore, there was an inextricable correlation between immune cell infiltration, immune checkpoint proteins, and AS events. This study will provide a basis for THCA immunotherapy in the future.

Combining Multiple RNA-Seq Data Analysis Algorithms Using Machine Learning Improves Differential Isoform Expression Analysis

RNA sequencing has become the standard technique for high resolution genome-wide monitoring of gene expression. As such, it often comprises the first step towards understanding complex molecular mechanisms driving various phenotypes, spanning organ development to disease genesis, monitoring and progression. An advantage of RNA sequencing is its ability to capture complex transcriptomic events such as alternative splicing which results in alternate isoform abundance. At the same time, this advantage remains algorithmically and computationally challenging, especially with the emergence of even higher resolution technologies such as single-cell RNA sequencing. Although several algorithms have been proposed for the effective detection of differential isoform expression from RNA-Seq data, no widely accepted golden standards have been established. This fact is further compounded by the significant differences in the output of different algorithms when applied on the same data. In addition, many of the proposed algorithms remain scarce and poorly maintained. Driven by these challenges, we developed a novel integrative approach that effectively combines the most widely used algorithms for differential transcript and isoform analysis using state-of-the-art machine learning techniques. We demonstrate its usability by applying it on simulated data based on several organisms, and using several performance metrics; we conclude that our strategy outperforms the application of the individual algorithms. Finally, our approach is implemented as an R Shiny application, with the underlying data analysis pipelines also available as docker containers.

Xeroderma Pigmentosum: Gene Variants and Splice Variants

The nucleotide excision repair (NER) is essential for the repair of ultraviolet (UV)-induced DNA damage, such as cyclobutane pyrimidine dimers (CPDs) and 6,4-pyrimidine-pyrimidone dimers (6,4-PPs). Alterations in genes of the NER can lead to DNA damage repair disorders such as Xeroderma pigmentosum (XP). XP is a rare autosomal recessive genetic disorder associated with UV-sensitivity and early onset of skin cancer. Recently, extensive research has been conducted on the functional relevance of splice variants and their relation to cancer. Here, we focus on the functional relevance of alternative splice variants of XP genes.

Alternative RNA Splicing-The Trojan Horse of Cancer Cells in Chemotherapy

Almost all transcribed human genes undergo alternative RNA splicing, which increases the diversity of the coding and non-coding cellular landscape. The resultant gene products might have distinctly different and, in some cases, even opposite functions. Therefore, the abnormal regulation of alternative splicing plays a crucial role in malignant transformation, development, and progression, a fact supported by the distinct splicing profiles identified in both healthy and tumor cells. Drug resistance, resulting in treatment failure, still remains a major challenge for current cancer therapy. Furthermore, tumor cells often take advantage of aberrant RNA splicing to overcome the toxicity of the administered chemotherapeutic agents. Thus, deciphering the alternative RNA splicing variants in tumor cells would provide opportunities for designing novel therapeutics combating cancer more efficiently. In the present review, we provide a comprehensive outline of the recent findings in alternative splicing in the most common neoplasms, including lung, breast, prostate, head and neck, glioma, colon, and blood malignancies. Molecular mechanisms developed by cancer cells to promote oncogenesis as well as to evade anticancer drug treatment and the subsequent chemotherapy failure are also discussed. Taken together, these findings offer novel opportunities for future studies and the development of targeted therapy for cancer-specific splicing variants.

Characterization of a Novel Viral Interleukin 8 (vIL-8) Splice Variant Encoded by Marek's Disease Virus

Marek’s disease virus (MDV) is a highly cell-associated oncogenic alphaherpesvirus that causes lymphomas in various organs in chickens. Like other herpesviruses, MDV has a large and complex double-stranded DNA genome. A number of viral transcripts are generated by alternative splicing, a process that drastically extends the coding capacity of the MDV genome. One of the spliced genes encoded by MDV is the viral interleukin 8 (vIL-8), a CXC chemokine that facilitates the recruitment of MDV target cells and thereby plays an important role in MDV pathogenesis and tumorigenesis. We recently identified a novel vIL-8 exon (vIL-8-E3′) by RNA-seq; however, it remained elusive whether the protein containing the vIL-8-E3′ is expressed and what role it may play in MDV replication and/or pathogenesis. To address these questions, we first generated recombinant MDV harboring a tag that allows identification of the spliced vIL-8-E3′ protein, revealing that it is indeed expressed. We subsequently generated knockout viruses and could demonstrate that the vIL-8-E3′ protein is dispensable for MDV replication as well as secretion of the functional vIL-8 chemokine. Finally, infection of chickens with this vIL-8-E3′ knockout virus revealed that the protein is not important for MDV replication and pathogenesis in vivo. Taken together, our study provides novel insights into the splice forms of the CXC chemokine of this highly oncogenic alphaherpesvirus.

Identification of prognostic alternative splicing events related to the immune microenvironment of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, and its 5-year survival rate is less than 20%, despite various treatments being available. Increasing evidence indicates that alternative splicing (AS) plays a nonnegligible role in the formation and development of the tumor microenvironment (TME). However, the comprehensive analysis of the impact on prognostic AS events on immune-related perspectives in HCC is lacking but urgently needed.

Methods

The transcriptional data and clinical information of HCC patients were downloaded from TCGA (The Cancer Genome Atlas) database for calculating immune and stromal scores by ESTIMATE algorithm. We then divided patients into high/low score groups and explored their prognostic significance using Kaplan–Meier curves. Based on stromal and immune scores, differentially expressed AS events (DEASs) were screened and evaluated with functional enrichment analysis. Additionally, a risk score model was established by applying univariate and multivariate Cox regression analyses. Finally, gene set variation analysis (GSVA) was adopted to explore differences in biological behaviors between the high- and low-risk subgroups.

Results

A total of 370 HCC patients with complete and qualified corresponding data were included in the subsequent analysis. According to the results of ESTIMATE analysis, we observed that the high immune/stromal score group had a longer survival probability, which was significantly correlated with prognosis in HCC patients. In addition, 467 stromal/immune score-related DEASs were identified, and enrichment analysis revealed that DEASs were significantly enriched in pathways related to HCC tumorigenesis and the immune microenvironment. More importantly, the final prognostic signature containing 16 DEASs showed powerful predictive ability. Finally, GSVA demonstrated that activation of carcinogenic pathways and immune-related pathways in the high-risk group may lead to poor prognosis.

Conclusions

Collectively, these outcomes revealed prognostic AS events related to carcinogenesis and the immune microenvironment, which may yield new directions for HCC immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00294-3.

Development of alternative splicing signature in lung squamous cell carcinoma

Increasing evidence demonstrated that alternative splicing (AS) plays a vital role in tumorigenesis and clinical outcome of patient. However, systematical analysis of AS in lung squamous cell carcinoma (LUSC) is lacking and greatly necessary. Thus, this study was to systematically estimate the function of AS events served as prognostic indicators in LUSC. Among 31,345 mRNA AS events in 9633 genes, we detected 1996 AS in 1409 genes which have significant connection with overall survival (OS) of LUSC patients. Then, prognostic model based on seven types of AS events was established and we further constructed a combined prognostic model. The Kaplan–Meier curve results suggested that seven types of AS signatures and the combined prognostic model could exhibit robust performance in predicting prognosis. Patients in the high-risk group had significantly shorter OS than those in the low-risk group. The ROC showed all prognostic models had high accuracy and powerful predictive performance with different AUC ranging from 0.837 to 0.978. Moreover, the combined prognostic model had highest performance in risk stratification and predictive accuracy than single prognostic models and had higher accuracy than other mRNA model. Finally, a significant correlation network between survival-related AS genes and prognostic splicing factors (SFs) was established. In conclusion, our study provided several potential prognostic AS models and constructed splicing network between AS and SFs in LUSC, which could be used as potential indicators and treatment targets for LUSC patients.

Aberrant Splicing Events and Epigenetics in Viral Oncogenomics: Current Therapeutic Strategies

Global cancer incidence and mortality are on the rise. Although cancer is fundamentally a non-communicable disease, a large number of cancers are known to have a viral aetiology. A high burden of infectious agents (Human immunodeficiency virus (HIV), human papillomavirus (HPV), hepatitis B virus (HBV)) in certain Sub-Saharan African countries drives the rates of certain cancers. About one-third of all cancers in Africa are attributed to infection. Seven viruses have been identified with carcinogenic characteristics, namely the HPV, HBV, Hepatitis C virus (HCV), Epstein–Barr virus (EBV), Human T cell leukaemia virus 1 (HTLV-1), Kaposi’s Sarcoma Herpesvirus (KSHV), and HIV-1. The cellular splicing machinery is compromised upon infection, and the virus generates splicing variants that promote cell proliferation, suppress signalling pathways, inhibition of tumour suppressors, alter gene expression through epigenetic modification, and mechanisms to evade an immune response, promoting carcinogenesis. A number of these splice variants are specific to virally-induced cancers. Elucidating mechanisms underlying how the virus utilises these splice variants to maintain its latent and lytic phase will provide insights into novel targets for drug discovery. This review will focus on the splicing genomics, epigenetic modifications induced by and current therapeutic strategies against HPV, HBV, HCV, EBV, HTLV-1, KSHV and HIV-1.

Splicing Genomics Events in Cervical Cancer: Insights for Phenotypic Stratification and Biomarker Potency

Gynaecological cancers are attributed to the second most diagnosed cancers in women after breast cancer. On a global scale, cervical cancer is the fourth most common cancer and the most common cancer in developing countries with rapidly increasing mortality rates. Human papillomavirus (HPV) infection is a major contributor to the disease. HPV infections cause prominent cellular changes including alternative splicing to drive malignant transformation. A fundamental characteristic attributed to cancer is the dysregulation of cellular transcription. Alternative splicing is regulated by several splicing factors and molecular changes in these factors lead to cancer mechanisms such as tumour development and progression and drug resistance. The serine/arginine-rich (SR) proteins and heterogeneous ribonucleoproteins (hnRNPs) have prominent roles in modulating alternative splicing. Evidence shows molecular alteration and expression levels in these splicing factors in cervical cancer. Furthermore, aberrant splicing events in cancer-related genes lead to chemo- and radioresistance. Identifying clinically relevant modifications in alternative splicing events and splicing variants, in cervical cancer, as potential biomarkers for their role in cancer progression and therapy resistance is scrutinised. This review will focus on the molecular mechanisms underlying the aberrant splicing events in cervical cancer that may serve as potential biomarkers for diagnosis, prognosis, and novel drug targets.

Genomics and splicing events of type II endometrial cancers in the black population: racial disparity, socioeconomic and geographical differences

Endometrial cancer, also known as uterine cancer, is the most common gynaecological malignancy with burgeoning incidence and mortality rates globally. Racial disparity, socioeconomic and geographical differences are important determinants of endometrial cancer incidence and mortality. Endometrial cancer is mainly categorised as type I and type II. Although less prevalent, type II is the most aggressive form of the disease and typically diagnosed at a late stage, contributing to higher mortality. Black women are at higher risk of developing aggressive, type II disease. Type I tumours are related to higher levels of circulating estrogen with lower-grade tumours that have a good prognosis and frequently related to PTEN mutations. In comparison, type II tumours are estrogen-independent, typically have poor prognosis and associated with the p53, HER2, PPP2R1A, FBXW7 and PIK3R1 mutations. The risk of developing type II malignancy is higher in women with Lynch syndrome as a result of mutations in the MMR gene family. Genetic modifications contribute to aberrant alternative splicing events that are related to tumour development, progression and resistance to therapy. Alternative splicing events are rapidly emerging as potential biomarkers and therapeutic targets. Type II endometrial cancer lacks targeted therapy and biomarkers for novel therapeutic strategies. Recent advances have illustrated a number of molecular targets that are currently explored for the treatment of advanced, late-stage endometrial cancer. The aim of this review is to outline 1) the epidemiology of type II endometrial cancer in black women, 2) discuss the correlated risk factors that contribute to the development of type II endometrial cancer and 3) the associated molecular mechanisms and genetic factors underlying the disease, and 4) aberrant splicing events and biomarkers with therapeutic potential as novel drug targets.

Alternative splicing of leptin receptor overlapping transcript in osteosarcoma

IMPACT STATEMENT

Osteosarcoma (OS, also known as osteogenic sarcoma) is the most common primary malignancy of bone in children and adolescents. The molecular mechanisms of OS are extremely complicated and its molecular mediators remain to be elucidated. We sequenced total RNA from 18 OS bone samples (paired normal-tumor biopsies). We found statistically significant (FDR <0.05) 26 differentially expressed transcript variants of LEPROT gene with different expressions in normal and tumor samples. These findings contribute to the understanding of molecular mechanisms of OS development and provide encouragement to pursue further research.