Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients

RPS24 alternative splicing is a marker of cancer progression and epithelial-mesenchymal transition

Although alternative splicing (AS) is a major mechanism that adds diversity to gene expression patterns, its precise role in generating variability in ribosomal proteins, known as ribosomal heterogeneity, remains unclear. The ribosomal protein S24 (RPS24) gene, encoding a ribosomal component, undergoes AS; however, in-depth studies have been challenging because of three microexons between exons 4 and 6. We conducted a detailed analysis of RPS24 AS isoforms using a direct approach to investigate the splicing junctions related to these microexons, focusing on four AS isoforms. Each of these isoforms showed tissue specificity and relative differences in expression among cancer types. Significant differences in the proportions of these RPS24 AS isoforms between cancerous and normal tissues across diverse cancer types were also observed. Our study highlighted a significant correlation between the expression levels of a specific RPS24 AS isoform and the epithelial-mesenchymal transition process in lung and breast cancers. Our research contributes to a better understanding of the intricate regulatory mechanisms governing AS of ribosomal protein genes and highlights the biological implications of RPS24 AS isoforms in tissue development and tumorigenesis.

Targeting Neoantigens in Cancer: Possibilities and Opportunities in Breast Cancer

As one of the most prevalent forms of cancer worldwide, breast cancer has garnered significant attention within the clinical research setting. While traditional treatment employs a multidisciplinary approach including a variety of therapies such as chemotherapy, hormone therapy, and even surgery, researchers have since directed their attention to the budding role of neoantigens. Neoantigens are defined as tumor-specific antigens that result from a multitude of genetic alterations, the most prevalent of which is the single nucleotide variant. As a result of their foreign nature, neoantigens elicit immune responses upon presentation by Major Histocompatibility Complexes I and II followed by recognition by T cell receptors. Previously, researchers have been able to utilize these immunogenic properties and manufacture neoantigen-specific T-cells and neoantigen vaccines. Within the context of breast cancer, biomarkers such as tumor protein 53 (TP53), Survivin, Partner and Localizer of BRCA2 (PALB2), and protein tyrosine phosphatase receptor T (PTPRT) display exceeding potential to serve as neoantigens. However, despite their seemingly limitless potential, neoantigens must overcome various obstacles if they are to be fairly distributed to patients. For instance, a prolonged period between the identification of a neoantigen and the dispersal of treatment poses a serious risk within the context of breast cancer. Regardless of these current obstacles, it appears highly promising that future research into neoantigens will make an everlasting impact on the health outcomes within the realm of breast cancer. The purpose of this literature review is to comprehensively discuss the etiology of various forms of breast cancer and current treatment modalities followed by the significance of neoantigens in cancer therapeutics and their application to breast cancer. Further, we have discussed the limitations, future directions, and the role of transcriptomics in neoantigen identification and personalized medicine. The concepts discussed in the original and review articles were included in this review article.

IMMUNOTAR - Integrative prioritization of cell surface targets for cancer immunotherapy

Cancer remains a leading cause of mortality globally. Recent improvements in survival have been facilitated by the development of less toxic immunotherapies; however, identifying targets for immunotherapies remains a challenge in the field. To address this challenge, we developed IMMUNOTAR, a computational tool that systematically prioritizes and identifies candidate immunotherapeutic targets. IMMUNOTAR integrates user-provided RNA-sequencing or proteomics data with quantitative features extracted from publicly available databases based on predefined optimal immunotherapeutic target criteria and quantitatively prioritizes potential surface protein targets. We demonstrate the utility and flexibility of IMMUNOTAR using three distinct datasets, validating its effectiveness in identifying both known and new potential immunotherapeutic targets within the analyzed cancer phenotypes. Overall, IMMUNOTAR enables the compilation of data from multiple sources into a unified platform, allowing users to simultaneously evaluate surface proteins across diverse criteria. By streamlining target identification, IMMUNOTAR empowers researchers to efficiently allocate resources and accelerate immunotherapy development.

DNA damage response and neoantigens: A favorable target for triple-negative breast cancer immunotherapy and vaccine development

Triple-negative breast cancer (TNBC) poses a significant clinical challenge due to its aggressive nature and limited therapeutic options. The interplay between DNA damage response (DDR) mechanisms and the emergence of neoantigens represents a promising avenue for developing targeted immunotherapeutic strategies and vaccines for TNBC. The DDR is a complex network of cellular mechanisms designed to maintain genomic integrity. In TNBC, where genetic instability is a hallmark, dysregulation of DDR components plays a pivotal role in tumorigenesis and progression. This review explores the intricate relationship between DDR and neoantigens, shedding light on the potential vulnerabilities of TNBC cells. Neoantigens, arising from somatic mutations in cancer cells, represent unique antigens that can be recognized by the immune system. TNBC's propensity for genomic instability leads to an increased mutational burden, consequently yielding a rich repertoire of neoantigens. The convergence of DDR and neoantigens in TNBC offers a distinctive opportunity for immunotherapeutic targeting. Immunotherapy has revolutionized cancer treatment by harnessing the immune system to selectively target cancer cells. The unique immunogenicity conferred by DDR-related neoantigens in TNBC positions them as ideal targets for immunotherapeutic interventions. This review also explores various immunotherapeutic modalities, including immune checkpoint inhibitors (ICIs), adoptive cell therapies, and cancer vaccines, that leverage the DDR and neoantigen interplay to enhance anti-tumor immune responses. Moreover, the potential for developing vaccines targeting DDR-related neoantigens opens new frontiers in preventive and therapeutic strategies for TNBC. The rational design of vaccines tailored to the individual mutational landscape of TNBC holds promise for precision medicine approaches. In conclusion, the convergence of DDR and neoantigens in TNBC presents a compelling rationale for the development of innovative immunotherapies and vaccines. Understanding and targeting these interconnected processes may pave the way for personalized and effective interventions, offering new hope for patients grappling with the challenges posed by TNBCs.

Exploring Splicing Modulation as an Innovative Approach to Combat Pancreatic Cancer: SF3B1 Emerges as a Prognostic Indicator and Therapeutic Target

Pancreatic ductal adenocarcinoma (PDAC) poses significant challenges in terms of prognosis and treatment. Recent research has identified splicing deregulation as a new cancer hallmark. Herein, we investigated the largely uncharacterized alternative splicing profile and the key splicing factor SF3B1 in PDAC pancreatic cells and tissues as a potential discovery source of plausible drug targets and new predictive biomarkers of clinical outcome. The research involved a transcriptome-wide analysis, comparing profiles of splicing profiles in PDAC primary cells with normal ductal cells. This revealed more than 400 significant differential splicing events in genes involved in regulation of gene expression, primarily related to mRNA splicing, and metabolism of nucleic acids. PDAC cultures were highly sensitive to the SF3B1 modulators, E7107 and Pladienolide-B, showing IC50s in the low nanomolar range. These compounds induced apoptosis, associated to induction of the MCL-1/S splice variant. and reduced cell migration, associated to RON mis-splicing. In an orthotopic mouse model, E7107 showed promising results. Furthermore, we evaluated SF3B1 expression in specimens from 87 patients and found a significant association of SF3B1 expression with progression-free and overall survival. In conclusion, SF3B1 emerges as both a potential prognostic factor and therapeutic target in PDAC, impacting cell proliferation, migration, and apoptosis. These findings warrant future studies on this new therapeutic strategy against PDAC.

Clinically relevant immune subtypes based on alternative splicing landscape of immune-related genes for lung cancer advanced PPPM approach

Background

Alternative splicing (AS) occurs in the process of gene post-transcriptional process, which is very important for the correct synthesis and function of protein. The change of AS pattern may lead to the change of expression level or function of lung cancer-related genes, and then affect the occurrence and development of lung cancers. The specific AS pattern might be used as a biomarker for early warning and prognostic assessment of a cancer in the framework of predictive, preventive, and personalized medicine (PPPM; 3PM). AS events of immune-related genes (IRGs) were closely associated with tumor progression and immunotherapy. We hypothesize that IRG-AS events are significantly different in lung adenocarcinomas (LUADs) vs. controls or in lung squamous cell carcinomas (LUSCs) vs. controls. IRG-AS alteration profiling was identified to construct IRG-differentially expressed AS (IRG-DEAS) signature models. Study on the selective AS events of specific IRGs in lung cancer patients might be of great significance for further exploring the pathogenesis of lung cancer, realizing early detection and effective monitoring of lung cancer, finding new therapeutic targets, overcoming drug resistance, and developing more effective therapeutic strategies, and better used for the prediction, diagnosis, prevention, and personalized medicine of lung cancer.

Methods

The transcriptomic, clinical, and AS data of LUADs and LUSCs were downloaded from TCGA and its SpliceSeq databases. IRG-DEAS events were identified in LUAD and LUSC, followed by their functional characteristics, and overall survival (OS) analyses. OS-related IRG-DEAS prognostic models were constructed for LUAD and LUSC with Lasso regression, which were used to classify LUADs and LUSCs into low- and high-risk score groups. Furthermore, the immune cell distribution, immune-related scores, drug sensitivity, mutation status, and GSEA/GSVA status were analyzed between low- and high-risk score groups. Also, low- and high-immunity clusters and AS factor (SF)-OS-related-AS co-expression network and verification of cell function of CELF6 were analyzed in LUAD and LUSC.

Results

Comprehensive analysis of transcriptomic, clinical, and AS data of LUADs and LUSCs identified IRG-AS events in LUAD (n = 1607) and LUSC (n = 1656), including OS-related IRG-AS events in LUAD (n = 127) and LUSC (n = 105). A total of 66 IRG-DEAS events in LUAD and 89 IRG-DEAS events in LUSC were identified compared to controls. The overlapping analysis between IRG-DEASs and OS-related IRG-AS events revealed 14 OS-related IRG-DEAS events for LUAD and 16 OS-related IRG-DEAS events for LUSC, which were used to identify and optimize a 12-OS-related-IRG-DEAS signature prognostic model for LUAD and an 11-OS-related-IRG-DEAS signature prognostic model for LUSC. These two prognostic models effectively divided LUAD or LUSC samples into low- and high-risk score groups that were closely associated with OS, clinical characteristics, and tumor immune microenvironment, with significant gene sets and pathways enriched in the two groups. Moreover, weighted gene co-expression network (WGCNA) and nonnegative matrix factorization method (NMF) analyses identified four OS-relevant subtypes of LUAD and six OS-relevant subtypes of LUSC, and ssGSEA identified five immunity-relevant subtypes of LUAD and five immunity-relevant subtypes of LUSC. Interestingly, splicing factors-OS-related-AS network revealed hub molecule CELF6 was significantly related to the malignant phenotype in lung cancer cells.

Conclusions

This study established two reliable IRG-DEAS signature prognostic models and constructed interesting splicing factor-splicing event networks in LUAD and LUSC, which can be used to construct clinically relevant immune subtypes, patient stratification, prognostic prediction, and personalized medical services in the PPPM practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00366-4.

Emerging measurements for tumor-infiltrating lymphocytes in breast cancer

Tumor-infiltrating lymphocytes are a general term for lymphocytes or immune cells infiltrating the tumor microenvironment. Numerous studies have demonstrated tumor-infiltrating lymphocytes to be robust prognostic and predictive biomarkers in breast cancer. Recently, immune checkpoint inhibitors, which directly target tumor-infiltrating lymphocytes, have become part of standard of care treatment for triple-negative breast cancer. Surprisingly, tumor-infiltrating lymphocytes quantified by conventional methods do not predict response to immune checkpoint inhibitors, which highlights the heterogeneity of tumor-infiltrating lymphocytes and the complexity of the immune network in the tumor microenvironment. Tumor-infiltrating lymphocytes are composed of diverse immune cell populations, including cytotoxic CD8-positive T lymphocytes, B cells and myeloid cells. Traditionally, tumor-infiltrating lymphocytes in tumor stroma have been evaluated by histology. However, the standardization of this approach is limited, necessitating the use of various novel technologies to elucidate the heterogeneity in the tumor microenvironment. This review outlines the evaluation methods for tumor-infiltrating lymphocytes from conventional pathological approaches that evaluate intratumoral and stromal tumor-infiltrating lymphocytes such as immunohistochemistry, to the more recent advancements in computer tissue imaging using artificial intelligence, flow cytometry sorting and multi-omics analyses using high-throughput assays to estimate tumor-infiltrating lymphocytes from bulk tumor using immune signatures or deconvolution tools. We also discuss higher resolution technologies that enable the analysis of tumor-infiltrating lymphocytes heterogeneity such as single-cell analysis and spatial transcriptomics. As we approach the era of personalized medicine, it is important for clinicians to understand these technologies.

In silico identification of a novel Cdc2-like kinase 2 (CLK2) inhibitor in triple negative breast cancer

Dysregulation of RNA splicing processes is intricately linked to tumorigenesis in various cancers, especially breast cancer. Cdc2-like kinase 2 (CLK2), an oncogenic RNA-splicing kinase pivotal in breast cancer, plays a significant role, particularly in the context of triple-negative breast cancer (TNBC), a subtype marked by substantial medical challenges due to its low survival rates. In this study, we employed a structure-based virtual screening (SBVS) method to identify potential CLK2 inhibitors with novel chemical structures for treating TNBC. Compound 670551 emerged as a novel CLK2 inhibitor with a 50% inhibitory concentration (IC50) value of 619.7 nM. Importantly, Compound 670551 exhibited high selectivity for CLK2 over other protein kinases. Functionally, this compound significantly reduced the survival and proliferation of TNBC cells. Results from a cell-based assay demonstrated that this inhibitor led to a decrease in RNA splicing proteins, such as SRSF4 and SRSF6, resulting in cell apoptosis. In summary, we identified a novel CLK2 inhibitor as a promising potential treatment for TNBC therapy.

Alternative splicing in EMT and TGF-β signaling during cancer progression

Epithelial to mesenchymal transition (EMT) is a physiological process during development where epithelial cells transform to acquire mesenchymal characteristics, which allows them to migrate and colonize secondary tissues. Many cellular signaling pathways and master transcriptional factors exert a myriad of controls to fine tune this vital process to meet various developmental and physiological needs. Adding to the complexity of this network are post-transcriptional and post-translational regulations. Among them, alternative splicing has been shown to play important roles to drive EMT-associated phenotypic changes, including actin cytoskeleton remodeling, cell-cell junction changes, cell motility and invasiveness. In advanced cancers, transforming growth factor-β (TGF-β) is a major inducer of EMT and is associated with tumor cell metastasis, cancer stem cell self-renewal, and drug resistance. This review aims to provide an overview of recent discoveries regarding alternative splicing events and the involvement of splicing factors in the EMT and TGF-β signaling. It will emphasize the importance of various splicing factors involved in EMT and explore their regulatory mechanisms.

Development and validation of AI/ML derived splice-switching oligonucleotides

Splice-switching oligonucleotides (SSOs) are antisense compounds that act directly on pre-mRNA to modulate alternative splicing (AS). This study demonstrates the value that artificial intelligence/machine learning (AI/ML) provides for the identification of functional, verifiable, and therapeutic SSOs. We trained XGboost tree models using splicing factor (SF) pre-mRNA binding profiles and spliceosome assembly information to identify modulatory SSO binding sites on pre-mRNA. Using Shapley and out-of-bag analyses we also predicted the identity of specific SFs whose binding to pre-mRNA is blocked by SSOs. This step adds considerable transparency to AI/ML-driven drug discovery and informs biological insights useful in further validation steps. We applied this approach to previously established functional SSOs to retrospectively identify the SFs likely to regulate those events. We then took a prospective validation approach using a novel target in triple negative breast cancer (TNBC), NEDD4L exon 13 (NEDD4Le13). Targeting NEDD4Le13 with an AI/ML-designed SSO decreased the proliferative and migratory behavior of TNBC cells via downregulation of the TGFβ pathway. Overall, this study illustrates the ability of AI/ML to extract actionable insights from RNA-seq data.

Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates

Motivation

Neoantigens are promising targets for cancer immunotherapies and might arise from alternative splicing. However, detecting tumor-specific splicing is challenging because many non-canonical splice junctions identified in tumors also appear in healthy tissues. To increase tumor-specificity, we focused on splicing caused by somatic mutations as a source for neoantigen candidates in individual patients.

Results

We developed the tool splice2neo with multiple functionalities to integrate predicted splice effects from somatic mutations with splice junctions detected in tumor RNA-seq and to annotate the resulting transcript and peptide sequences. Additionally, we provide the tool EasyQuant for targeted RNA-seq read mapping to candidate splice junctions. Using a stringent detection rule, we predicted 1.7 splice junctions per patient as splice targets with a false discovery rate below 5% in a melanoma cohort. We confirmed tumor-specificity using independent, healthy tissue samples. Furthermore, using tumor-derived RNA, we confirmed individual exon-skipping events experimentally. Most target splice junctions encoded neoepitope candidates with predicted major histocompatibility complex (MHC)-I or MHC-II binding. Compared to neoepitope candidates from non-synonymous point mutations, the splicing-derived MHC-I neoepitope candidates had lower self-similarity to corresponding wild-type peptides. In conclusion, we demonstrate that identifying mutation-derived, tumor-specific splice junctions can lead to additional neoantigen candidates to expand the target repertoire for cancer immunotherapies.

Availability and implementation

The R package splice2neo and the python package EasyQuant are available at https://github.com/TRON-Bioinformatics/splice2neo and https://github.com/TRON-Bioinformatics/easyquant, respectively.

Genome-wide identification and analysis of epithelial-mesenchymal transition-related RNA-binding proteins and alternative splicing in a human breast cancer cell line

Exploring the mechanism of breast cancer metastasis and searching for new drug therapeutic targets are still the focuses of current research. RNA-binding proteins (RBPs) may affect breast cancer metastasis by regulating alternative splicing (AS) during epithelial-mesenchymal transition (EMT). We hypothesised that during EMT development in breast cancer cells, the expression level of RBPs and the gene AS pattern in the cell were significantly changed on a genome-wide scale. Using GEO database, this study identified differentially expressed RBPs and differential AS events at different stages of EMT in breast cancer cells. By establishing the correlation network of differential RBPs and differential AS events, we found that RBM47, PCBP3, FRG1, SRP72, RBMS3 and other RBPs may regulate the AS of ITGA6, ADGRE5, TNC, COL6A3 and other cell adhesion genes. By further analysing above EMT-related RBPs and AS in breast cancer tissues in TCGA, it was found that the expression levels of ADAT2, C2orf15, SRP72, PAICS, RBMS3, APOBEC3G, NOA1, ACO1 and the AS of TNC and COL6A3 were significantly correlated with the prognosis of breast cancer patients. The expression levels of all 8 RBPs were significantly different in breast cancer tissues without metastasis compared with normal breast tissues. Conclusively, eight RBPs such as RBMS3 and AS of TNC and COL6A3 could be used as predictors of breast cancer prognosis. These findings need to be further explored as possible targets for breast cancer treatment.

Biological relevance of alternative splicing in hematologic malignancies

Alternative splicing (AS) is a strictly regulated process that generates multiple mRNA variants from a single gene, thus contributing to proteome diversity. Transcriptome-wide sequencing studies revealed networks of functionally coordinated splicing events, which produce isoforms with distinct or even opposing functions. To date, several mechanisms of AS are deregulated in leukemic cells, mainly due to mutations in splicing and/or epigenetic regulators and altered expression of splicing factors (SFs). In this review, we discuss aberrant splicing events induced by mutations affecting SFs (SF3B1, U2AF1, SRSR2, and ZRSR2), spliceosome components (PRPF8, LUC7L2, DDX41, and HNRNPH1), and epigenetic modulators (IDH1 and IDH2). Finally, we provide an extensive overview of the biological relevance of aberrant isoforms of genes involved in the regulation of apoptosis (e. g. BCL-X, MCL-1, FAS, and c-FLIP), activation of key cellular signaling pathways (CASP8, MAP3K7, and NOTCH2), and cell metabolism (PKM).

Localization of RNAs to the mitochondria-mechanisms and functions

The mammalian mitochondrial proteome comprises over 1000 proteins, with the majority translated from nuclear-encoded messenger RNAs (mRNAs). Mounting evidence suggests many of these mRNAs are localized to the outer mitochondrial membrane (OMM) in a pre- or cotranslational state. Upon reaching the mitochondrial surface, these mRNAs are locally translated to produce proteins that are cotranslationally imported into mitochondria. Here, we summarize various mechanisms cells use to localize RNAs, including transfer RNAs (tRNAs), to the OMM and recent technological advancements in the field to study these processes. While most early studies in the field were carried out in yeast, recent studies reveal RNA localization to the OMM and their regulation in higher organisms. Various factors regulate this localization process, including RNA sequence elements, RNA-binding proteins (RBPs), cytoskeletal motors, and translation machinery. In this review, we also highlight the role of RNA structures and modifications in mitochondrial RNA localization and discuss how these features can alter the binding properties of RNAs. Finally, in addition to RNAs related to mitochondrial function, RNAs involved in other cellular processes can also localize to the OMM, including those implicated in the innate immune response and piRNA biogenesis. As impairment of messenger RNA (mRNA) localization and regulation compromise mitochondrial function, future studies will undoubtedly expand our understanding of how RNAs localize to the OMM and investigate the consequences of their mislocalization in disorders, particularly neurodegenerative diseases, muscular dystrophies, and cancers.

Comprehensive profiling of cancer neoantigens from aberrant RNA splicing

BACKGROUND

Cancer neoantigens arise from protein-altering somatic mutations in tumor and rank among the most promising next-generation immuno-oncology agents when used in combination with immune checkpoint inhibitors. We previously developed a computational framework, REAL-neo, for identification, quality control, and prioritization of both class-I and class-II human leucocyte antigen (HLA)-presented neoantigens resulting from somatic single-nucleotide mutations, small insertions and deletions, and gene fusions. In this study, we developed a new module, SPLICE-neo, to identify neoantigens from aberrant RNA transcripts from two distinct sources: (1) DNA mutations within splice sites and (2) de novo RNA aberrant splicings.

METHODS

First, SPLICE-neo was used to profile all DNA splice-site mutations in 11,892 tumors from The Cancer Genome Atlas (TCGA) and identified 11 profiles of splicing donor or acceptor site gains or losses. Transcript isoforms resulting from the top seven most frequent profiles were computed using novel logic models. Second, SPLICE-neo identified de novo RNA splicing events using RNA sequencing reads mapped to novel exon junctions from either single, double, or multiple exon-skipping events. The aberrant transcripts from both sources were then ranked based on isoform expression levels and z-scores assuming that individual aberrant splicing events are rare. Finally, top-ranked novel isoforms were translated into protein, and the resulting neoepitopes were evaluated for neoantigen potential using REAL-neo. The top splicing neoantigen candidates binding to HLA-A*02:01 were validated using in vitro T2 binding assays.

RESULTS

We identified abundant splicing neoantigens in four representative TCGA cancers: BRCA, LUAD, LUSC, and LIHC. In addition to their substantial contribution to neoantigen load, several splicing neoantigens were potent tumor antigens with stronger bindings to HLA compared with the positive control of antigens from influenza virus.

CONCLUSIONS

SPLICE-neo is the first tool to comprehensively identify and prioritize splicing neoantigens from both DNA splice-site mutations and de novo RNA aberrant splicings. There are two major advances of SPLICE-neo. First, we developed novel logic models that assemble and prioritize full-length aberrant transcripts from DNA splice-site mutations. Second, SPLICE-neo can identify exon-skipping events involving more than two exons, which account for a quarter to one-third of all skipping events.

Mutant U2AF1-Induced Mis-Splicing of mRNA Translation Genes Confers Resistance to Chemotherapy in Acute Myeloid Leukemia

Patients with primary refractory acute myeloid leukemia (AML) have a dismal long-term prognosis. Elucidating the resistance mechanisms to induction chemotherapy could help identify strategies to improve AML patient outcomes. Herein, we retrospectively analyzed the multiomics data of more than 1,500 AML cases and found that patients with spliceosome mutations had a higher risk of developing refractory disease. RNA splicing analysis revealed that the mis-spliced genes in refractory patients converged on translation-associated pathways, promoted mainly by U2AF1 mutations. Integrative analyses of binding and splicing in AML cell lines substantiated that the splicing perturbations of mRNA translation genes originated from both the loss and gain of mutant U2AF1 binding. In particular, the U2AF1S34F and U2AF1Q157R mutants orchestrated the inclusion of exon 11 (encoding a premature termination codon) in the eukaryotic translation initiation factor 4A2 (EIF4A2). This aberrant inclusion led to reduced eIF4A2 protein expression via nonsense-mediated mRNA decay. Consequently, U2AF1 mutations caused a net decrease in global mRNA translation that induced the integrated stress response (ISR) in AML cells, which was confirmed by single-cell RNA sequencing. The induction of ISR enhanced the ability of AML cells to respond and adapt to stress, contributing to chemoresistance. A pharmacologic inhibitor of ISR, ISRIB, sensitized U2AF1 mutant cells to chemotherapy. These findings highlight a resistance mechanism by which U2AF1 mutations drive chemoresistance and provide a therapeutic approach for AML through targeting the ISR pathway.

SIGNIFICANCE

U2AF1 mutations induce the integrated stress response by disrupting splicing of mRNA translation genes that improves AML cell fitness to enable resistance to chemotherapy, which can be targeted to improve AML treatment.

Characterization of alternative splicing events and prognostic signatures in gastric cancer

BACKGROUND

Accumulating evidences indicate that the specific alternative splicing (AS) events are linked to the occurrence and prognosis of gastric cancer (GC). Nevertheless, the impact of AS is still unclear and needed to further elucidation.

METHODS

The expression profile of GC and normal samples were downloaded from TCGA. AS events were achieved from SpliceSeq database. Cox regression together with LASSO analysis were employed to identify survival-associated AS events (SASEs) and calculate risk scores. PPI and pathway enrichment analysis were implemented to determine the function and pathways of these genes. Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic Curves were used to evaluate the clinical significance of genes of SASEs. Q-PCR were applied to validate the hub genes on the survival prognosis in 47 GC samples. Drug sensitivity and immune cell infiltration analysis were conducted.

RESULTS

In total, 48 140 AS events in 10 610 genes from 361 GC and 31 normal samples were analyzed. Through univariate Cox regression, 855 SASEs in 763 genes were screened out. Further, these SASEs were analyzed by PPI and 17 hub genes were identified. Meanwhile, using Lasso and multivariate Cox regression analysis, 135 SASEs in 132 genes related to 7 AS forms were further screened and a GC prognostic model was constructed. K-M curves indicates that high-risk group has poorer prognosis. And the nomogram analysis on the basis of the multivariate Cox analysis was disclosed the interrelationships between 7 AS forms and clinical parameters in the model. Five key genes were then screened out by PPI analysis and Differential Expression Gene analysis based on TCGA and Combined-dataset, namely STAT3, RAD51B, SOCS2, POLE2 and TSR1. The expression levels of AS in STAT3, RAD51B, SOCS2, POLE2 and TSR1 were all significantly correlated with survival by qPCR verification. Nineteen drugs were sensitized to high-risk patients and eight immune cells showed significantly different infiltration between the STAD and normal groups.

CONCLUSIONS

In this research, the prognostic model constructed by SASEs can be applied to predict the prognosis of GC patients and the selected key genes are expected to become new biomarkers and therapeutical targets for GC treatment.

The Regulatory Network of hnRNPs Underlying Regulating PKM Alternative Splicing in Tumor Progression

One of the hallmarks of cancer is metabolic reprogramming in tumor cells, and aerobic glycolysis is the primary mechanism by which glucose is quickly transformed into lactate. As one of the primary rate-limiting enzymes, pyruvate kinase (PK) M is engaged in the last phase of aerobic glycolysis. Alternative splicing is a crucial mechanism for protein diversity, and it promotes PKM precursor mRNA splicing to produce PKM2 dominance, resulting in low PKM1 expression. Specific splicing isoforms are produced in various tissues or illness situations, and the post-translational modifications are linked to numerous disorders, including cancers. hnRNPs are one of the main components of the splicing factor families. However, there have been no comprehensive studies on hnRNPs regulating PKM alternative splicing. Therefore, this review focuses on the regulatory network of hnRNPs on PKM pre-mRNA alternative splicing in tumors and clinical drug research. We elucidate the role of alternative splicing in tumor progression, prognosis, and the potential mechanism of abnormal RNA splicing. We also summarize the drug targets retarding tumorous splicing events, which may be critical to improving the specificity and effectiveness of current therapeutic interventions.

Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression

Immunotherapy with chimeric antigen receptor T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify cancer specific exon targets, here we analyze 1532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We find 2933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n = 148) or the alternatively spliced isoform (n = 9) level. Expression of selected alternatively spliced targets, including the EDB domain of fibronectin 1, and gene targets, such as COL11A1, are validated in pediatric patient derived xenograft tumors. We generate T cells expressing chimeric antigen receptors specific for the EDB domain or COL11A1 and demonstrate that these have antitumor activity. The full target list, explorable via an interactive web portal ( https://cseminer.stjude.org/ ), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

DDX5 inhibits hyaline cartilage fibrosis and degradation in osteoarthritis via alternative splicing and G-quadruplex unwinding

Hyaline cartilage fibrosis is typically considered an end-stage pathology of osteoarthritis (OA), which results in changes to the extracellular matrix. However, the mechanism behind this is largely unclear. Here, we found that the RNA helicase DDX5 was dramatically downregulated during the progression of OA. DDX5 deficiency increased fibrosis phenotype by upregulating COL1 expression and downregulating COL2 expression. In addition, loss of DDX5 aggravated cartilage degradation by inducing the production of cartilage-degrading enzymes. Chondrocyte-specific deletion of Ddx5 led to more severe cartilage lesions in the mouse OA model. Mechanistically, weakened DDX5 resulted in abundance of the Fn1-AS-WT and Plod2-AS-WT transcripts, which promoted expression of fibrosis-related genes (Col1, Acta2) and extracellular matrix degradation genes (Mmp13, Nos2 and so on), respectively. Additionally, loss of DDX5 prevented the unfolding Col2 promoter G-quadruplex, thereby reducing COL2 production. Together, our data suggest that strategies aimed at the upregulation of DDX5 hold significant potential for the treatment of cartilage fibrosis and degradation in OA.

Alternative splicing in prostate cancer progression and therapeutic resistance

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

Proteomics Identifies LUC7L3 as a Prognostic Biomarker for Hepatocellular Carcinoma

Alternative splicing has been shown to participate in tumor progression, including hepatocellular carcinoma. The poor prognosis of patients with HCC calls for molecular classification and biomarker identification to facilitate precision medicine. We performed ssGSEA analysis to quantify the pathway activity of RNA splicing in three HCC cohorts. Kaplan-Meier and Cox methods were used for survival analysis. GO and GSEA were performed to analyze pathway enrichment. We confirmed that RNA splicing is significantly correlated with prognosis, and identified an alternative splicing-associated protein LUC7L3 as a potential HCC prognostic biomarker. Further bioinformatics analysis revealed that high LUC7L3 expression indicated a more progressive HCC subtype and worse clinical features. Cell proliferation-related pathways were enriched in HCC patients with high LUC7L3 expression. Consistently, we proved that LUC7L3 knockdown could significantly inhibit cell proliferation and suppress the activation of associated signaling pathways in vitro. In this research, the relevance between RNA splicing and HCC patient prognosis was outlined. Our newly identified biomarker LUC7L3 could provide stratification for patient survival and recurrence risk, facilitating early medical intervention before recurrence or disease progression.

Tumor Antigens beyond the Human Exome

With the advent of immunotherapeutics, a new era in the combat against cancer has begun. Particularly promising are neo-epitope-targeted therapies as the expression of neo-antigens is tumor-specific. In turn, this allows the selective targeting and killing of cancer cells whilst healthy cells remain largely unaffected. So far, many advances have been made in the development of treatment options which are tailored to the individual neo-epitope repertoire. The next big step is the achievement of efficacious "off-the-shelf" immunotherapies. For this, shared neo-epitopes propose an optimal target. Given the tremendous potential, a thorough understanding of the underlying mechanisms which lead to the formation of neo-antigens is of fundamental importance. Here, we review the various processes which result in the formation of neo-epitopes. Broadly, the origin of neo-epitopes can be categorized into three groups: canonical, noncanonical, and viral neo-epitopes. For the canonical neo-antigens that arise in direct consequence of somatic mutations, we summarize past and recent findings. Beyond that, our main focus is put on the discussion of noncanonical and viral neo-epitopes as we believe that targeting those provides an encouraging perspective to shape the future of cancer immunotherapeutics.

Molecular targets and mechanisms of different aberrant alternative splicing in metastatic liver cancer

Metastasis remains a major challenge in the successful management of malignant diseases. The liver is a major site of metastatic disease and a leading cause of death from gastrointestinal malignancies such as colon, stomach, and pancreatic cancers, as well as melanoma, breast cancer, and sarcoma. As an important factor that influences the development of metastatic liver cancer, alternative splicing drives the diversity of RNA transcripts and protein subtypes, which may provide potential to broaden the target space. In particular, the dysfunction of splicing factors and abnormal expression of splicing variants are associated with the occurrence, progression, aggressiveness, and drug resistance of cancers caused by the selective splicing of specific genes. This review is the first to provide a detailed summary of the normal splicing process and alterations that occur during metastatic liver cancer. It will cover the role of alternative splicing in the mechanisms of metastatic liver cancer by examining splicing factor changes, abnormal splicing, and the contribution of hypoxia to these changes during metastasis.

Genomic deletions explain the generation of alternative BRAF isoforms conferring resistance to MAPK inhibitors in melanoma

Resistance to MAPK inhibitors (MAPKi), the main cause of relapse in BRAF-mutant melanoma, is associated with the production of alternative BRAF mRNA isoforms (altBRAFs) in up to 30% of patients receiving BRAF inhibitor monotherapy. These altBRAFs have been described as being generated by alternative pre-mRNA splicing, and splicing modulation has been proposed as a therapeutic strategy to overcome resistance. In contrast, we report that altBRAFs are generated through genomic deletions. Using different in vitro models of altBRAF-mediated melanoma resistance, we demonstrate the production of altBRAFs exclusively from the BRAF V600E allele, correlating with corresponding genomic deletions. Genomic deletions are also detected in tumor samples from melanoma and breast cancer patients expressing altBRAFs. Along with the identification of altBRAFs in BRAF wild-type and in MAPKi-naive melanoma samples, our results represent a major shift in our understanding of mechanisms leading to the generation of BRAF transcripts variants associated with resistance in melanoma.

GLIMS: A two-stage gradual-learning method for cancer genes prediction using multi-omics data and co-splicing network

Identifying cancer genes is vital for cancer diagnosis and treatment. However, because of the complexity of cancer occurrence and limited cancer genes knowledge, it is hard to identify cancer genes accurately using only a few omics data, and the overall performance of existing methods is being called for further improvement. Here, we introduce a two-stage gradual-learning strategy GLIMS to predict cancer genes using integrative features from multi-omics data. Firstly, it uses a semi-supervised hierarchical graph neural network to predict the initial candidate cancer genes by integrating multi-omics data and protein-protein interaction (PPI) network. Then, it uses an unsupervised approach to further optimize the initial prediction by integrating the co-splicing network in post-transcriptional regulation, which plays an important role in cancer development. Systematic experiments on multi-omics cancer data demonstrated that GLIMS outperforms the state-of-the-art methods for the identification of cancer genes and it could be a useful tool to help advance cancer analysis.

Comprehensive Long-Read Sequencing Analysis Discloses the Transcriptome Features of Papillary Thyroid Microcarcinoma

CONTEXT

Papillary thyroid microcarcinoma (PTMC) is the most common type of thyroid cancer. It has been shown that lymph node metastasis is associated with poor prognosis in patients with PTMC.

OBJECTIVE

We aim to characterize the PTMC transcriptome landscape and identify the candidate transcripts that are associated with lateral neck lymph node metastasis of PTMC.

METHODS

We performed full-length transcriptome sequencing in 64 PTMC samples. Standard bioinformatic pipelines were applied to characterize and annotate the full-length expression profiles of 2 PTMC subtypes. Functional open reading frame (ORF) annotation of the known and novel transcripts were predicted by HMMER, DeepLoc, and DeepTMHMM tools. Candidate transcripts associated with the pN1b subtype were identified after transcript quantification and differential gene expression analyses.

RESULTS

We found that skipping exons accounted for the more than 27.82% of the alternative splicing events. At least 42.56% of the discovered transcripts were novel isoforms of annotated genes. A total of 39 193 ORFs in novel transcripts and 18 596 ORFs in known transcripts were identified. Distribution patterns of the characterized transcripts in functional domain, subcellular localization, and transmembrane structure were predicted. In total, 1033 and 1204 differentially expressed genes were identified in the pN0 and pN1b groups, respectively. Moreover, novel isoforms of FRMD3, NOD1, and SHROOM4 were highlighted for their association with pN1b subtype.

CONCLUSION

Our data provided the global transcriptome landscape of PTMC and also revealed the novel isoforms that associated with PTMC aggressiveness.

Identification of differentially expressed genes and splicing events in early-onset colorectal cancer

Background

The incidence of colorectal cancer (CRC) has been steadily increasing in younger individuals over the past several decades for reasons that are incompletely defined. Identifying differences in gene expression profiles, or transcriptomes, in early-onset colorectal cancer (EOCRC, < 50 years old) patients versus later-onset colorectal cancer (LOCRC, > 50 years old) patients is one approach to understanding molecular and genetic features that distinguish EOCRC.

Methods

We performed RNA-sequencing (RNA-seq) to characterize the transcriptomes of patient-matched tumors and adjacent, uninvolved (normal) colonic segments from EOCRC (n=21) and LOCRC (n=22) patients. The EOCRC and LOCRC cohorts were matched for demographic and clinical characteristics. We used The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) database for validation. We used a series of computational and bioinformatic tools to identify EOCRC-specific differentially expressed genes, molecular pathways, predicted cell populations, differential gene splicing events, and predicted neoantigens.

Results

We identified an eight-gene signature in EOCRC comprised of ALDOB, FBXL16, IL1RN, MSLN, RAC3, SLC38A11, WBSCR27 and WNT11, from which we developed a score predictive of overall CRC patient survival. On the entire set of genes identified in normal tissues and tumors, cell type deconvolution analysis predicted a differential abundance of immune and non-immune populations in EOCRC versus LOCRC. Gene set enrichment analysis identified increased expression of splicing machinery in EOCRC. We further found differences in alternative splicing (AS) events, including one within the long non-coding RNA, HOTAIRM1. Additional analysis of AS found seven events specific to EOCRC that encode potential neoantigens.

Conclusion

Our transcriptome analyses identified genetic and molecular features specific to EOCRC which may inform future screening, development of prognostic indicators, and novel drug targets.

NONO promotes gallbladder cancer cell proliferation by enhancing oncogenic RNA splicing of DLG1 through interaction with IGF2BP3/RBM14

Gallbladder cancer (GBC) is a highly malignant and rapidly progressing tumor of the human biliary system, and there is an urgent need to develop new therapeutic targets and modalities. Non-POU domain-containing octamer-binding protein (NONO) is an RNA-binding protein involved in the regulation of transcription, mRNA splicing, and DNA repair. NONO expression is elevated in multiple tumors and can act as an oncogene to promote tumor progression. Here, we found that NONO was highly expressed in GBC and promoted tumor cells growth. The dysregulation of RNA splicing is a molecular feature of almost all tumor types. Accordingly, mRNA-seq and RIP-seq analysis showed that NONO promoted exon6 skipping in DLG1, forming two isomers (DLG1-FL and DLG1-S). Furthermore, lower Percent-Spliced-In (PSI) values of DLG1 were detected in tumor tissue relative to the paraneoplastic tissue, and were associated with poor patient prognosis. Moreover, DLG1-S and DLG1-FL act as tumor promoters and tumor suppressors, respectively, by regulating the YAP1/JUN pathway. N6-methyladenosine (m6A) is the most common and abundant RNA modification involved in alternative splicing processes. We identified an m6A reader, IGF2BP3, which synergizes with NONO to promote exon6 skipping in DLG1 in an m6A-dependent manner. Furthermore, IP/MS results showed that RBM14 was bound to NONO and interfered with NONO-mediated exon6 skipping of DLG1. In addition, IGF2BP3 disrupted the binding of RBM14 to NONO. Overall, our data elucidate the molecular mechanism by which NONO promotes DLG1 exon skipping, providing a basis for new therapeutic targets in GBC treatment.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

[Targeting the spliceosome: A new therapeutic strategy to counteract chemotherapy resistance in lung cancer?]

Lung cancer is the first cancer-related cause of death worldwide. This is in partially due to therapeutic resistance, which occurs in around 70% of patients, especially those receiving platinum salts, the gold-standard chemotherapy. The massive deregulation of alternative transcript splicing processes observed in many cancers has led to the development of a new class of pharmacological agents aimed at inhibiting the activity of the splicing machinery (spliceosome). The molecular mechanisms by which these inhibitors act remain largely unknown, as do the benefits of using them in combination with other therapies. In this context, our work is focused on an inhibitor of the SRPK1 kinase, a major regulator of the spliceosome.

Activation of ERβ hijacks the splicing machinery to trigger R-loop formation in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with aggressive behavior and poor prognosis. Current therapeutic options available for TNBC patients are primarily chemotherapy. With our evolving understanding of this disease, novel targeted therapies, including poly ADP-ribose polymerase (PARP) inhibitors, antibody-drug conjugates, and immune-checkpoint inhibitors, have been developed for clinical use. Previous reports have demonstrated the essential role of estrogen receptor β (ERβ) in TNBC, but the detailed molecular mechanisms downstream ERβ activation in TNBC are still far from elucidated. In this study, we demonstrated that a specific ERβ agonist, LY500307, potently induces R-loop formation and DNA damage in TNBC cells. Subsequent interactome experiments indicated that the residues 151 to 165 of U2 small nuclear RNA auxiliary factor 1 (U2AF1) and the Trp439 and Lys443 of ERβ were critical for the binding between U2AF1 and ERβ. Combined RNA sequencing and ribosome sequencing analysis demonstrated that U2AF1-regulated downstream RNA splicing of 5-oxoprolinase (OPLAH) could affect its enzymatic activity and is essential for ERβ-induced R-loop formation and DNA damage. In clinical samples including 115 patients from The Cancer Genome Atlas (TCGA) and 32 patients from an in-house cohort, we found a close correlation in the expression of ESR2 and U2AF1 in TNBC patients. Collectively, our study has unraveled the molecular mechanisms that explain the therapeutic effects of ERβ activation in TNBC, which provides rationale for ERβ activation-based single or combined therapy for patients with TNBC.

Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter- and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of antigens. In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface antigens that could be targeted by antibodies and chimeric antigen receptor-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas) and 9166 normal tissue samples (from the Genotype-Tissue Expression project), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN, which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative antigens. Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Overcoming cold tumors: a combination strategy of immune checkpoint inhibitors

Immune Checkpoint Inhibitors (ICIs) therapy has advanced significantly in treating malignant tumors, though most 'cold' tumors show no response. This resistance mainly arises from the varied immune evasion mechanisms. Hence, understanding the transformation from 'cold' to 'hot' tumors is essential in developing effective cancer treatments. Furthermore, tumor immune profiling is critical, requiring a range of diagnostic techniques and biomarkers for evaluation. The success of immunotherapy relies on T cells' ability to recognize and eliminate tumor cells. In 'cold' tumors, the absence of T cell infiltration leads to the ineffectiveness of ICI therapy. Addressing these challenges, especially the impairment in T cell activation and homing, is crucial to enhance ICI therapy's efficacy. Concurrently, strategies to convert 'cold' tumors into 'hot' ones, including boosting T cell infiltration and adoptive therapies such as T cell-recruiting bispecific antibodies and Chimeric Antigen Receptor (CAR) T cells, are under extensive exploration. Thus, identifying key factors that impact tumor T cell infiltration is vital for creating effective treatments targeting 'cold' tumors.

Roles and mechanisms of aberrant alternative splicing in melanoma - implications for targeted therapy and immunotherapy resistance

BACKGROUND

Despite advances in therapeutic strategies, resistance to immunotherapy and the off-target effects of targeted therapy have significantly weakened the benefits for patients with melanoma.

MAIN BODY

Alternative splicing plays a crucial role in transcriptional reprogramming during melanoma development. In particular, aberrant alternative splicing is involved in the efficacy of immunotherapy, targeted therapy, and melanoma metastasis. Abnormal expression of splicing factors and variants may serve as biomarkers or therapeutic targets for the diagnosis and prognosis of melanoma. Therefore, comprehensively integrating their roles and related mechanisms is essential. This review provides the first detailed summary of the splicing process in melanoma and the changes occurring in this pathway.

CONCLUSION

The focus of this review is to provide strategies for developing novel diagnostic biomarkers and summarize their potential to alter resistance to targeted therapies and immunotherapy.

Detecting and understanding meaningful cancerous mutations based on computational models of mRNA splicing

Cancer research has long relied on non-silent mutations. Yet, it has become overwhelmingly clear that silent mutations can affect gene expression and cancer cell fitness. One fundamental mechanism that apparently silent mutations can severely disrupt is alternative splicing. Here we introduce Oncosplice, a tool that scores mutations based on models of proteomes generated using aberrant splicing predictions. Oncosplice leverages a highly accurate neural network that predicts splice sites within arbitrary mRNA sequences, a greedy transcript constructor that considers alternate arrangements of splicing blueprints, and an algorithm that grades the functional divergence between proteins based on evolutionary conservation. By applying this tool to 12M somatic mutations we identify 8K deleterious variants that are significantly depleted within the healthy population; we demonstrate the tool's ability to identify clinically validated pathogenic variants with a positive predictive value of 94%; we show strong enrichment of predicted deleterious mutations across pan-cancer drivers. We also achieve improved patient survival estimation using a proposed set of novel cancer-involved genes. Ultimately, this pipeline enables accelerated insight-gathering of sequence-specific consequences for a class of understudied mutations and provides an efficient way of filtering through massive variant datasets - functionalities with immediate experimental and clinical applications.

The global landscape of immune-derived lncRNA signature in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a highly heterogeneous cancer. This heterogeneity has an impact on the efficacy of immunotherapy. Long noncoding RNAs (lncRNAs) have been found to play regulatory functions in cancer immunity. However, the global landscape of immune-derived lncRNA signatures has not yet been explored in colorectal cancer.

METHODS

In this study, we applied DESeq2 to identify differentially expressed lncRNAs in colon cancer. Next, we performed an integrative analysis to globally identify immune-driven lncRNA markers in CRC, including immune-associated pathways, tumor immunogenomic features, tumor-infiltrating immune cells, immune checkpoints, microsatellite instability (MSI) and tumor mutation burden (TMB).

RESULTS

We also identified dysregulated lncRNAs, such as LINC01354 and LINC02257, and their clinical relevance in CRC. Our findings revealed that the differentially expressed lncRNAs were closely associated with immune pathways. In addition, we found that RP11-354P11.3 and RP11-545G3.1 had the highest association with the immunogenomic signature. As a result, these signatures could serve as markers to assess immunogenomic activity in CRC. Among the immune cells, resting mast cells and M0 macrophages had the highest association with lncRNAs in CRC. The AC006129.2 gene was significantly associated with several immune checkpoints, for example, programmed cell death protein 1 (PD-1) and B and T lymphocyte attenuator (BTLA). Therefore, the AC006129.2 gene could be targeted to regulate the condition of immune cells or immune checkpoints to enhance the efficacy of immunotherapy in CRC patients. Finally, we identified 15 immune-related lncRNA-generated open reading frames (ORFs) corresponding to 15 cancer immune epitopes.

CONCLUSION

In conclusion, we provided a genome-wide immune-driven lncRNA signature for CRC that might provide new insights into clinical applications and immunotherapy.

Activation-induced cytidine deaminase causes recurrent splicing mutations in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma. A major mutagenic process in DLBCL is aberrant somatic hypermutation (aSHM) by activation-induced cytidine deaminase (AID), which occurs preferentially at RCH/TW sequence motifs proximal to transcription start sites. Splice sequences are highly conserved, rich in RCH/TW motifs, and recurrently mutated in DLBCL. Therefore, we hypothesized that aSHM may cause recurrent splicing mutations in DLBCL. In a meta-cohort of > 1,800 DLBCLs, we found that 77.5% of splicing mutations in 29 recurrently mutated genes followed aSHM patterns. In addition, in whole-genome sequencing (WGS) data from 153 DLBCLs, proximal mutations in splice sequences, especially in donors, were significantly enriched in RCH/TW motifs (p < 0.01). We validated this enrichment in two additional DLBCL cohorts (N > 2,000; p < 0.0001) and confirmed its absence in 12 cancer types without aSHM (N > 6,300). Comparing sequencing data from mouse models with and without AID activity showed that the splice donor sequences were the top genomic feature enriched in AID-induced mutations (p < 0.0001). Finally, we observed that most AID-related splice site mutations are clonal within a sample, indicating that aSHM may cause early loss-of-function events in lymphomagenesis. Overall, these findings support that AID causes an overrepresentation of clonal splicing mutations in DLBCL.

Modification of BCLX pre-mRNA splicing has antitumor efficacy alone or in combination with radiotherapy in human glioblastoma cells

Dysregulation of anti-apoptotic and pro-apoptotic protein isoforms arising from aberrant splicing is a crucial hallmark of cancers and may contribute to therapeutic resistance. Thus, targeting RNA splicing to redirect isoform expression of apoptosis-related genes could lead to promising anti-cancer phenotypes. Glioblastoma (GBM) is the most common type of malignant brain tumor in adults. In this study, through RT-PCR and Western Blot analysis, we found that BCLX pre-mRNA is aberrantly spliced in GBM cells with a favored splicing of anti-apoptotic Bcl-xL. Modulation of BCLX pre-mRNA splicing using splice-switching oligonucleotides (SSOs) efficiently elevated the pro-apoptotic isoform Bcl-xS at the expense of the anti-apoptotic Bcl-xL. Induction of Bcl-xS by SSOs activated apoptosis and autophagy in GBM cells. In addition, we found that ionizing radiation could also modulate the alternative splicing of BCLX. In contrast to heavy (carbon) ion irradiation, low energy X-ray radiation-induced an increased ratio of Bcl-xL/Bcl-xS. Inhibiting Bcl-xL through splicing regulation can significantly enhance the radiation sensitivity of 2D and 3D GBM cells. These results suggested that manipulation of BCLX pre-mRNA alternative splicing by splice-switching oligonucleotides is a novel approach to inhibit glioblastoma tumorigenesis alone or in combination with radiotherapy.

An alternative splicing signature defines the basal-like phenotype and predicts worse clinical outcome in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extremely poor prognosis. PDAC presents with molecularly distinct subtypes, with the basal-like one being associated with enhanced chemoresistance. Splicing dysregulation contributes to PDAC; however, its involvement in subtype specification remains elusive. Herein, we uncover a subtype-specific splicing signature associated with prognosis in PDAC and the splicing factor Quaking (QKI) as a determinant of the basal-like signature. Single-cell sequencing analyses highlight QKI as a marker of the basal-like phenotype. QKI represses splicing events associated with the classical subtype while promoting basal-like events associated with shorter survival. QKI favors a plastic, quasi-mesenchymal phenotype that supports migration and chemoresistance in PDAC organoids and cell lines, and its expression is elevated in high-grade primary tumors and metastatic lesions. These studies identify a splicing signature that defines PDAC subtypes and indicate that QKI promotes an undifferentiated, plastic phenotype, which renders PDAC cells chemoresistant and adaptable to environmental changes.

Systematic characterization of protein structural features of alternative splicing isoforms using AlphaFold 2

Alternative splicing is an important cellular process in eukaryotes, altering pre-mRNA to yield multiple protein isoforms from a single gene. However, our understanding of the impact of alternative splicing events on protein structures is currently constrained by a lack of sufficient protein structural data. To address this limitation, we employed AlphaFold 2, a cutting-edge protein structure prediction tool, to conduct a comprehensive analysis of alternative splicing for approximately 3,000 human genes, providing valuable insights into its impact on the protein structural. Our investigation employed state of the art high-performance computing infrastructure to systematically characterize structural features in alternatively spliced regions and identified changes in protein structure following alternative splicing events. Notably, we found that alternative splicing tends to alter the structure of residues primarily located in coils and beta-sheets. Our research highlighted a significant enrichment of loops and highly exposed residues within human alternatively spliced regions. Specifically, our examination of the Septin-9 protein revealed potential associations between loops and alternative splicing, providing insights into its evolutionary role. Furthermore, our analysis uncovered two missense mutations in the Tau protein that could influence alternative splicing, potentially contributing to the pathogenesis of Alzheimer's disease. In summary, our work, through a thorough statistical analysis of extensive protein structural data, sheds new light on the intricate relationship between alternative splicing, evolution, and human disease.

Alternative splicing and related RNA binding proteins in human health and disease

Alternative splicing (AS) serves as a pivotal mechanism in transcriptional regulation, engendering transcript diversity, and modifications in protein structure and functionality. Across varying tissues, developmental stages, or under specific conditions, AS gives rise to distinct splice isoforms. This implies that these isoforms possess unique temporal and spatial roles, thereby associating AS with standard biological activities and diseases. Among these, AS-related RNA-binding proteins (RBPs) play an instrumental role in regulating alternative splicing events. Under physiological conditions, the diversity of proteins mediated by AS influences the structure, function, interaction, and localization of proteins, thereby participating in the differentiation and development of an array of tissues and organs. Under pathological conditions, alterations in AS are linked with various diseases, particularly cancer. These changes can lead to modifications in gene splicing patterns, culminating in changes or loss of protein functionality. For instance, in cancer, abnormalities in AS and RBPs may result in aberrant expression of cancer-associated genes, thereby promoting the onset and progression of tumors. AS and RBPs are also associated with numerous neurodegenerative diseases and autoimmune diseases. Consequently, the study of AS across different tissues holds significant value. This review provides a detailed account of the recent advancements in the study of alternative splicing and AS-related RNA-binding proteins in tissue development and diseases, which aids in deepening the understanding of gene expression complexity and offers new insights and methodologies for precision medicine.

Metabolic Enzyme SLC27A5 Regulates PIP4K2A pre-mRNA Splicing as a Noncanonical Mechanism to Suppress Hepatocellular Carcinoma Metastasis

Solute carrier family 27 member 5, a key enzyme in fatty acid transport and bile acid metabolism in the liver, is frequently expressed in low quantities in patients with hepatocellular carcinoma, resulting in poor prognosis. However, it is unclear whether SLC27A5 plays non-canonical functions and regulates HCC progression. Here, an unexpected non-canonical role of SLC27A5 is reported: regulating the alternative splicing of mRNA to inhibit the metastasis of HCC independently of its metabolic enzyme activity. Mechanistically, SLC27A5 interacts with IGF2BP3 to prevent its translocation into the nucleus, thereby inhibiting its binding to target mRNA and modulating PIP4K2A pre-mRNA splicing. Loss of SLC27A5 results in elevated levels of the PIP4K2A-S isoform, thus positively regulating phosphoinositide 3-kinase signaling via enhanced p85 stability in HCC. SLC27A5 restoration by AAV-Slc27a5 or IGF2BP3 RNA decoy oligonucleotides exerts an inhibitory effect on HCC metastasis with reduced expression of the PIP4K2A-S isoform. Therefore, PIP4K2A-S may be a novel target for treating HCC with SLC27A5 deficiency.

Epigenetic regulation of mRNA mediates the phenotypic plasticity of cancer cells during metastasis and therapeutic resistance (Review)

Plasticity, the ability of cancer cells to transition between differentiation states without genomic alterations, has been recognized as a major source of intratumoral heterogeneity. It has a crucial role in cancer metastasis and treatment resistance. Thus, targeting plasticity holds tremendous promise. However, the molecular mechanisms of plasticity in cancer cells remain poorly understood. Several studies found that mRNA, which acts as a bridge linking the genetic information of DNA and protein, has an important role in translating genotypes into phenotypes. The present review provided an overview of the regulation of cancer cell plasticity occurring via changes in the transcription and editing of mRNAs. The role of the transcriptional regulation of mRNA in cancer cell plasticity was discussed, including DNA‑binding transcriptional factors, DNA methylation, histone modifications and enhancers. Furthermore, the role of mRNA editing in cancer cell plasticity was debated, including mRNA splicing and mRNA modification. In addition, the role of non‑coding (nc)RNAs in cancer plasticity was expounded, including microRNAs, long intergenic ncRNAs and circular RNAs. Finally, different strategies for targeting cancer cell plasticity to overcome metastasis and therapeutic resistance in cancer were discussed.

Towards targeting transposable elements for cancer therapy

Transposable elements (TEs) represent almost half of the human genome. Historically deemed 'junk DNA', recent technological advancements have stimulated a wave of research into the functional impact of TEs on gene-regulatory networks in evolution and development, as well as in diseases including cancer. The genetic and epigenetic evolution of cancer involves the exploitation of TEs, whereby TEs contribute directly to cancer-specific gene activities. This Review provides a perspective on the role of TEs in cancer as being a 'double-edged sword', both promoting cancer evolution and representing a vulnerability that could be exploited in cancer therapy. We discuss how TEs affect transcriptome regulation and other cellular processes in cancer. We highlight the potential of TEs as therapeutic targets for cancer. We also summarize technical hurdles in the characterization of TEs with genomic assays. Last, we outline open questions and exciting future research avenues.

Full-length isoform concatenation sequencing to resolve cancer transcriptome complexity

BACKGROUND

Cancers exhibit complex transcriptomes with aberrant splicing that induces isoform-level differential expression compared to non-diseased tissues. Transcriptomic profiling using short-read sequencing has utility in providing a cost-effective approach for evaluating isoform expression, although short-read assembly displays limitations in the accurate inference of full-length transcripts. Long-read RNA sequencing (Iso-Seq), using the Pacific Biosciences (PacBio) platform, can overcome such limitations by providing full-length isoform sequence resolution which requires no read assembly and represents native expressed transcripts. A constraint of the Iso-Seq protocol is due to fewer reads output per instrument run, which, as an example, can consequently affect the detection of lowly expressed transcripts. To address these deficiencies, we developed a concatenation workflow, PacBio Full-Length Isoform Concatemer Sequencing (PB_FLIC-Seq), designed to increase the number of unique, sequenced PacBio long-reads thereby improving overall detection of unique isoforms. In addition, we anticipate that the increase in read depth will help improve the detection of moderate to low-level expressed isoforms.

RESULTS

In sequencing a commercial reference (Spike-In RNA Variants; SIRV) with known isoform complexity we demonstrated a 3.4-fold increase in read output per run and improved SIRV recall when using the PB_FLIC-Seq method compared to the same samples processed with the Iso-Seq protocol. We applied this protocol to a translational cancer case, also demonstrating the utility of the PB_FLIC-Seq method for identifying differential full-length isoform expression in a pediatric diffuse midline glioma compared to its adjacent non-malignant tissue. Our data analysis revealed increased expression of extracellular matrix (ECM) genes within the tumor sample, including an isoform of the Secreted Protein Acidic and Cysteine Rich (SPARC) gene that was expressed 11,676-fold higher than in the adjacent non-malignant tissue. Finally, by using the PB_FLIC-Seq method, we detected several cancer-specific novel isoforms.

CONCLUSION

This work describes a concatenation-based methodology for increasing the number of sequenced full-length isoform reads on the PacBio platform, yielding improved discovery of expressed isoforms. We applied this workflow to profile the transcriptome of a pediatric diffuse midline glioma and adjacent non-malignant tissue. Our findings of cancer-specific novel isoform expression further highlight the importance of long-read sequencing for characterization of complex tumor transcriptomes.

Splicing neoantigen discovery with SNAF reveals shared targets for cancer immunotherapy

Immunotherapy has emerged as a crucial strategy to combat cancer by "reprogramming" a patient's own immune system. Although immunotherapy is typically reserved for patients with a high mutational burden, neoantigens produced from posttranscriptional regulation may provide an untapped reservoir of common immunogenic targets for new targeted therapies. To comprehensively define tumor-specific and likely immunogenic neoantigens from patient RNA-Seq, we developed Splicing Neo Antigen Finder (SNAF), an easy-to-use and open-source computational workflow to predict splicing-derived immunogenic MHC-bound peptides (T cell antigen) and unannotated transmembrane proteins with altered extracellular epitopes (B cell antigen). This workflow uses a highly accurate deep learning strategy for immunogenicity prediction (DeepImmuno) in conjunction with new algorithms to rank the tumor specificity of neoantigens (BayesTS) and to predict regulators of mis-splicing (RNA-SPRINT). T cell antigens from SNAF were frequently evidenced as HLA-presented peptides from mass spectrometry (MS) and predict response to immunotherapy in melanoma. Splicing neoantigen burden was attributed to coordinated splicing factor dysregulation. Shared splicing neoantigens were found in up to 90% of patients with melanoma, correlated to overall survival in multiple cancer cohorts, induced T cell reactivity, and were characterized by distinct cells of origin and amino acid preferences. In addition to T cell neoantigens, our B cell focused pipeline (SNAF-B) identified a new class of tumor-specific extracellular neoepitopes, which we termed ExNeoEpitopes. ExNeoEpitope full-length mRNA predictions were tumor specific and were validated using long-read isoform sequencing and in vitro transmembrane localization assays. Therefore, our systematic identification of splicing neoantigens revealed potential shared targets for therapy in heterogeneous cancers.

FLIBase: a comprehensive repository of full-length isoforms across human cancers and tissues

Regulatory processes at the RNA transcript level play a crucial role in generating transcriptome diversity and proteome composition in human cells, impacting both physiological and pathological states. This study introduces FLIBase (www.FLIBase.org), a specialized database that focuses on annotating full-length isoforms using long-read sequencing techniques. We collected and integrated long-read (351 samples) and short-read (12 469 samples) RNA sequencing data from diverse normal and cancerous human tissues and cells. The current version of FLIBase comprises a total of 983 789 full-length spliced isoforms, identified through long-read sequences and verified using short-read exon-exon splice junctions. Of these, 188 248 isoforms have been annotated, while 795 541 isoforms remain unannotated. By overcoming the limitations of short-read RNA sequencing methods, FLIBase provides an accurate and comprehensive representation of full-length transcripts. These comprehensive annotations empower researchers to undertake various downstream analyses and investigations. Importantly, FLIBase exhibits a significant advantage in identifying a substantial number of previously unannotated isoforms and tumor-specific RNA transcripts. These tumor-specific RNA transcripts have the potential to serve as a source of immunogenic recurrent neoantigens. This remarkable discovery holds tremendous promise for advancing the development of tailored RNA-based diagnostic and therapeutic strategies for various types of human cancer.

Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression

Immunotherapy with CAR T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons (CSE) present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify CSE targets, we analyzed 1,532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We found 2,933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n=148) or the alternatively spliced (AS) isoform (n=9) level. Expression of selected AS targets, including the EDB domain of FN1 (EDB), and gene targets, such as COL11A1, were validated in pediatric PDX tumors. We generated CAR T cells specific to EDB or COL11A1 and demonstrated that COL11A1-CAR T-cells have potent antitumor activity. The full target list, explorable via an interactive web portal (https://cseminer.stjude.org/), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

Splicing modulators impair DNA damage response and induce killing of cohesin-mutant MDS and AML

Splicing modulation is a promising treatment strategy pursued to date only in splicing factor-mutant cancers; however, its therapeutic potential is poorly understood outside of this context. Like splicing factors, genes encoding components of the cohesin complex are frequently mutated in cancer, including myelodysplastic syndromes (MDS) and secondary acute myeloid leukemia (AML), where they are associated with poor outcomes. Here, we showed that cohesin mutations are biomarkers of sensitivity to drugs targeting the splicing factor 3B subunit 1 (SF3B1) H3B-8800 and E-7107. We identified drug-induced alterations in splicing, and corresponding reduced gene expression, of a number of DNA repair genes, including BRCA1 and BRCA2, as the mechanism underlying this sensitivity in cell line models, primary patient samples and patient-derived xenograft (PDX) models of AML. We found that DNA damage repair genes are particularly sensitive to exon skipping induced by SF3B1 modulators due to their long length and large number of exons per transcript. Furthermore, we demonstrated that treatment of cohesin-mutant cells with SF3B1 modulators not only resulted in impaired DNA damage response and accumulation of DNA damage, but it sensitized cells to subsequent killing by poly(ADP-ribose) polymerase (PARP) inhibitors and chemotherapy and led to improved overall survival of PDX models of cohesin-mutant AML in vivo. Our findings expand the potential therapeutic benefits of SF3B1 splicing modulators to include cohesin-mutant MDS and AML.