Alternative mRNA splicing in cancer immunotherapy

Downregulation of HNRNPA1 induced neoantigen generation via regulating alternative splicing

BACKGROUND

Immunotherapies effectively treat human malignancies, but the low response and resistance are major obstacles. Neoantigen is an emerging target for tumor immunotherapy that can enhance anti-tumor immunity and improve immunotherapy. Aberrant alternative splicing is an important source of neoantigens. HNRNPA1, an RNA splicing factor, was found to be upregulated in the majority of tumors and play an important role in the tumor immunosuppressive microenvironment.

METHODS

Whole transcriptome sequencing was performed on shHNRNPA1 SKOV3 cells and transcriptomic data of shHNRNPA1 HepG2, MCF-7M, K562, and B-LL cells were downloaded from the GEO database. Enrichment analysis was performed to elucidate the mechanisms underlying the activation of anti-tumor immunity induced by HNRNPA1 knockdown. mRNA alternative splicing was analyzed and neoantigens were predicted by JCAST v.0.3.5 and Immune epitope database. The immunogenicity of candidate neoantigens was calculated by Class I pMHC Immunogenicity and validated by the IFN-γ ELISpot assay. The effect of shHNRNPA1 on tumor growth and immune cells in vivo was evaluated by xenograft model combined with immunohistochemistry.

RESULTS

HNRNPA1 was upregulated in a majority of malignancies and correlated with immunosuppressive status of the tumor immune microenvironment. Downregulation of HNRNPA1 could induce the activation of immune-related pathways and biological processes. Disruption of HNRNPA1 resulted in aberrant alternative splicing events and generation of immunogenic neoantigens. Downregulation of HNRNPA1 inhibited tumor growth and increased CD8+ T cell infiltration in vivo.

CONCLUSION

Our study demonstrated that targeting HNRNPA1 could produce immunogenic neoantigens that elicit anti-tumor immunity by inducing abnormal mRNA splicing. It suggests that HNRNPA1 may be a potential target for immunotherapy.

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.

Role of alternative splicing in fish immunity

Alternative splicing serves as a pivotal source of complexity in the transcriptome and proteome, selectively connecting various coding elements to generate a diverse array of mRNAs. This process encodes multiple proteins with either similar or distinct functions, contributing significantly to the intricacies of cellular processes. The role of alternative splicing in mammalian immunity has been well studied. Remarkably, the immune system of fish shares substantial similarities with that of humans, and alternative splicing also emerges as a key player in the immune processes of fish. In this review, we offer an overview of alternative splicing and its associated functions in the immune processes of fish, and summarize the research progress on alternative splicing in the fish immunity. Furthermore, we review the impact of alternative splicing on the fish immune system's response to external stimuli. Finally, we present our perspectives on future directions in this field. Our aim is to provide valuable insights for the future investigations into the role of alternative splicing in immunity.

Immunogenicity of Non-Mutated Ovarian Cancer-Specific Antigens

Epithelial ovarian cancer (EOC) has not significantly benefited from advances in immunotherapy, mainly because of the lack of well-defined actionable antigen targets. Using proteogenomic analyses of primary EOC tumors, we previously identified 91 aberrantly expressed tumor-specific antigens (TSAs) originating from unmutated genomic sequences. Most of these TSAs derive from non-exonic regions, and their expression results from cancer-specific epigenetic changes. The present study aimed to evaluate the immunogenicity of 48 TSAs selected according to two criteria: presentation by highly prevalent HLA allotypes and expression in a significant fraction of EOC tumors. Using targeted mass spectrometry analyses, we found that pulsing with synthetic TSA peptides leads to a high-level presentation on dendritic cells. TSA abundance correlated with the predicted binding affinity to the HLA allotype. We stimulated naïve CD8 T cells from healthy blood donors with TSA-pulsed dendritic cells and assessed their expansion with two assays: MHC-peptide tetramer staining and TCR Vβ CDR3 sequencing. We report that these TSAs can expand sizeable populations of CD8 T cells and, therefore, represent attractive targets for EOC immunotherapy.

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy

Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy. AI-driven algorithms can process extensive amounts of data, identify patterns, and make predictions that were once challenging to achieve. However, the integration of AI comes with its own set of challenges, leaving space for further research. With particular focus on the computational approaches, in this article we have explored the current landscape of neoantigen prediction, the fundamental concepts behind, the challenges and their potential solutions providing a comprehensive overview of this rapidly evolving field.

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.

SR proteins in cancer: function, regulation, and small inhibitor

Alternative splicing of pre-mRNAs is a fundamental step in RNA processing required for gene expression in most metazoans. Serine and arginine-rich proteins (SR proteins) comprise a family of multifunctional proteins that contain an RNA recognition motif (RRM) and the ultra-conserved arginine/serine-rich (RS) domain, and play an important role in precise alternative splicing. Increasing research supports SR proteins as also functioning in other RNA-processing-related mechanisms, such as polyadenylation, degradation, and translation. In addition, SR proteins interact with N6-methyladenosine (m6A) regulators to modulate the methylation of ncRNA and mRNA. Dysregulation of SR proteins causes the disruption of cell differentiation and contributes to cancer progression. Here, we review the distinct biological characteristics of SR proteins and their known functional mechanisms during carcinogenesis. We also summarize the current inhibitors that directly target SR proteins and could ultimately turn SR proteins into actionable therapeutic targets in cancer therapy.

RNA Isoforms as Broad Targets for Cancer Immunotherapy

While immunotherapy is typically reserved for cancer patients with a high mutational burden, neoantigens produced from post-transcriptional regulation provide a possible untapped reservoir of common immunogenic targets for new targeted cancer therapies. In this review, we describe new and emerging technologies, unconventional molecular targets and challenges for the precision immune targeting of diverse malignancies. In particular, we focus on the unique potential of targeting alternative mRNA isoforms as a source for broadly presented neoantigens and cell surface proteins. Finally, we discuss emerging challenges for alternative isoform immune targeting, with an emphasis in silico prioritization and high-throughput target validation.

Neoantigen Identification and Dendritic Cell-Based Vaccines for Lung Cancer Immunotherapy

Immunotherapies can treat many cancers, including difficult-to-treat cases such as lung cancer. Due to its tolerability, long-lasting therapeutic responses, and efficacy in a wide spectrum of patients, immunotherapy can also help to treat lung cancer, which has few treatment choices. Tumor-specific antigens (TSAs) for cancer vaccinations and T-cell therapies are difficult to discover. Neoantigens (NeoAgs) from genetic mutations, irregular RNA splicing, protein changes, or viral genetic sequences in tumor cells provide a solution. NeoAgs, unlike TSAs, are non-self and can cause an immunological response. Next-generation sequencing (NGS) and bioinformatics can swiftly detect and forecast tumor-specific NeoAgs. Highly immunogenic NeoAgs provide personalized or generalized cancer immunotherapies. Dendritic cells (DCs), which originate and regulate T-cell responses, are widely studied potential immunotherapeutic therapies for lung cancer and other cancers. DC vaccines are stable, reliable, and safe in clinical trials. The purpose of this article is to evaluate the current status, limitations, and prospective clinical applications of DC vaccines, as well as the identification and selection of major histocompatibility complex (MHC) class I and II genes for NeoAgs. Our goal is to explain DC biology and activate DC manipulation to help researchers create extremely potent cancer vaccines for patients.

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.

Precision Medicine Approaches in Acute Myeloid Leukemia with Adverse Genetics

The treatment of acute myeloid leukemia (AML) with adverse genetics remains unsatisfactory, with very low response rates to standard chemotherapy and shorter durations of remission commonly observed in these patients. The complex biology of AML with adverse genetics is continuously evolving. Herein, we discuss recent advances in the field focusing on the contribution of molecular drivers of leukemia biogenesis and evolution and on the alterations of the immune system that can be exploited with immune-based therapeutic strategies. We focus on the biological rationales for combining targeted therapy and immunotherapy, which are currently being investigated in ongoing trials, and could hopefully ameliorate the poor outcomes of patients affected by AML with adverse genetics.

pXg: Comprehensive Identification of Noncanonical MHC-I-Associated Peptides From De Novo Peptide Sequencing Using RNA-Seq Reads

Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as noncanonical major histocompatibility complex-I (MHC-I)-associated peptides (ncMAPs), that bind to MHC-I may make good immunotherapeutic targets. De novo peptide sequencing is a great way to find ncMAPs since it can detect peptide sequences from their tandem mass spectra without using any sequence databases. However, this strategy has not been widely applied for ncMAP identification because there is not a good way to estimate its false-positive rates. In order to completely and accurately identify immunopeptides using de novo peptide sequencing, we describe a unique pipeline called proteomics X genomics. In contrast to current pipelines, it makes use of genomic data, RNA-Seq abundance and sequencing quality, in addition to proteomic features to increase the sensitivity and specificity of peptide identification. We show that the peptide-spectrum match quality and genetic traits have a clear relationship, showing that they can be utilized to evaluate peptide-spectrum matches. From 10 samples, we found 24,449 canonical MHC-I-associated peptides and 956 ncMAPs by using a target-decoy competition. Three hundred eighty-seven ncMAPs and 1611 canonical MHC-I-associated peptides were new identifications that had not yet been published. We discovered 11 ncMAPs produced from a squirrel monkey retrovirus in human cell lines in addition to the two ncMAPs originating from a complementarity determining region 3 in an antibody thanks to the unrestricted search space assumed by de novo sequencing. These entirely new identifications show that proteomics X genomics can make the most of de novo peptide sequencing's advantages and its potential use in the search for new immunotherapeutic targets.

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.

Recruitment of BAG2 to DNAJ-PKAc scaffolds promotes cell survival and resistance to drug-induced apoptosis in fibrolamellar carcinoma

The DNAJ-PKAc fusion kinase is a defining feature of fibrolamellar carcinoma (FLC). FLC tumors are notoriously resistant to standard chemotherapies, with aberrant kinase activity assumed to be a contributing factor. By combining proximity proteomics, biochemical analyses, and live-cell photoactivation microscopy, we demonstrate that DNAJ-PKAc is not constrained by A-kinase anchoring proteins. Consequently, the fusion kinase phosphorylates a unique array of substrates, including proteins involved in translation and the anti-apoptotic factor Bcl-2-associated athanogene 2 (BAG2), a co-chaperone recruited to the fusion kinase through association with Hsp70. Tissue samples from patients with FLC exhibit increased levels of BAG2 in primary and metastatic tumors. Furthermore, drug studies implicate the DNAJ-PKAc/Hsp70/BAG2 axis in potentiating chemotherapeutic resistance. We find that the Bcl-2 inhibitor navitoclax enhances sensitivity to etoposide-induced apoptosis in cells expressing DNAJ-PKAc. Thus, our work indicates BAG2 as a marker for advanced FLC and a chemotherapeutic resistance factor in DNAJ-PKAc signaling scaffolds.

Structure-aware deep model for MHC-II peptide binding affinity prediction

The prediction of major histocompatibility complex (MHC)-peptide binding affinity is an important branch in immune bioinformatics, especially helpful in accelerating the design of disease vaccines and immunity therapy. Although deep learning-based solutions have yielded promising results on MHC-II molecules in recent years, these methods ignored structure knowledge from each peptide when employing the deep neural network models. Each peptide sequence has its specific combination order, so it is worth considering adding the structural information of the peptide sequence to the deep model training. In this work, we use positional encoding to represent the structural information of peptide sequences and validly combine the positional encoding with existing models by different strategies. Experiments on three datasets show that the introduction of position-coding information can further improve the performance built upon the existing model. The idea of introducing positional encoding to this field can provide important reference significance for the optimization of the deep network structure in the future.

SRSF10 facilitates HCC growth and metastasis by suppressing CD8+T cell infiltration and targeting SRSF10 enhances anti-PD-L1 therapy

BACKGROUND AND AIMS

RNA splicing is an essential step in regulating the gene posttranscriptional expression. Serine/arginine-rich splicing factors (SRSFs) are splicing regulators with vital roles in various tumors. Nevertheless, the expression patterns and functions of SRSFs in hepatocellular carcinoma (HCC) are not fully understood.

METHODS

Flow cytometry and immunofluorescent staining were used to determine the CD8+T cell infiltration. Orthotopic HCC model, lung metastasis model, DEN/CCl4 model, Srsf10△hep model, and Srsf10HepOE model were established to evaluate the role of SRSF10 in HCC and the efficacy of combination treatment.

RESULTS

SRSF10 was one of the most survival-relevant genes among SRSF members and was an independent prognostic factor for HCC. SRSF10 facilitated HCC growth and metastasis by suppressing CD8+T cell infiltration. Mechanistically, SRSF10 down-regulated the p53 protein by preventing the exon 6 skipping (exon 7 in mouse) mediated degradation of MDM4 transcript, thus inhibiting CD8+T cell infiltration. Elimination of CD8+T cells or overexpression of MDM4 removed the inhibitory role of SRSF10 knockdown in HCC growth and metastasis. SRSF10 also inhibited the IFNα/γ signaling pathway and promoted the HIF1α-mediated up-regulation of PD-L1 in HCC. Hepatocyte-specific SRSF10 deficiency alleviated the DEN/CCl4-induced HCC progression and metastasis, whereas hepatocyte-specific SRSF10 overexpression deteriorated these effects. Finally, SRSF10 knockdown enhanced the anti-PD-L1-mediated anti-tumor activity.

CONCLUSIONS

SRSF10 promoted HCC growth and metastasis by repressing CD8+T cell infiltration mediated by the MDM4-p53 axis. Furthermore, SRSF10 suppressed the IFNα/γ signaling pathway and induced the HIF1α signal mediated PD-L1 up-regulation. Targeting SRSF10 combined with anti-PD-L1 therapy showed promising efficacy.

FusionNeoAntigen: a resource of fusion gene-specific neoantigens

Among the diverse sources of neoantigens (i.e. single-nucleotide variants (SNVs), insertions or deletions (Indels) and fusion genes), fusion gene-derived neoantigens are generally more immunogenic, have multiple targets per mutation and are more widely distributed across various cancer types. Therefore, fusion gene-derived neoantigens are a potential source of highly immunogenic neoantigens and hold great promise for cancer immunotherapy. However, the lack of fusion protein sequence resources and knowledge prevents this application. We introduce 'FusionNeoAntigen', a dedicated resource for fusion-specific neoantigens, accessible at https://compbio.uth.edu/FusionNeoAntigen. In this resource, we provide fusion gene breakpoint crossing neoantigens focused on ∼43K fusion proteins of ∼16K in-frame fusion genes from FusionGDB2.0. FusionNeoAntigen provides fusion gene information, corresponding fusion protein sequences, fusion breakpoint peptide sequences, fusion gene-derived neoantigen prediction, virtual screening between fusion breakpoint peptides having potential fusion neoantigens and human leucocyte antigens (HLAs), fusion breakpoint RNA/protein sequences for developing vaccines, information on samples with fusion-specific neoantigen, potential CAR-T targetable cell-surface fusion proteins and literature curation. FusionNeoAntigen will help to develop fusion gene-based immunotherapies. We will report all potential fusion-specific neoantigens from all possible open reading frames of ∼120K human fusion genes in future versions.

Hyperbranched Polymer-Based Vaccines for Cancer Immunotherapy

Recently, several immunotherapeutic strategies are extensively studied and entered clinical investigation, suggesting their potential to lead a new generation of cancer therapy. Particularly, a cancer vaccine that combines tumor-associated antigens and immune adjuvants with a nanocarrier holds huge promise for inducing specific antitumor immune responses. Hyperbranched polymers, such as dendrimers and branched polyethylenimine (PEI) possessing abundant positively charged amine groups and inherent proton sponge effect are ideal carriers of antigens. Much effort is devoted to design dendrimer/branched PEI-based cancer vaccines. Herein, the recent advances in the design of dendrimer/branched PEI-based cancer vaccines for immunotherapy are reviewed. The future perspectives with regard to the development of dendrimer/branched PEI-based cancer vaccines are also briefly discussed.

Titin as a potential novel therapeutic target in colorectal cancer

Colorectal cancer (CRC) is identified as a primary cause of death around the world. The current chemotherapies are not cost-effective. Therefore, finding novel potential therapeutic target is urgent. Titin (TTN) is a muscle protein that is critical in hypertrophic cardiomyopathy. However, its role in CRC is not well understood. The study focused on exploring the possible role of TTN in CRC carcinogenesis. TTN mRNA and protein expression levels presented an obvious downregulation in CRC tissue samples, relative to normal control (p < 0.05). TTN expression significantly correlated with the clinical stage (normal vs. Stage 1, p < 0.05; normal vs. Stage 4, p < 0.05), node metastasis (normal vs. N1, p < 0.05; N1 vs. N2, p < 0.05), histological type (normal vs. adenocarcinoma, p < 0.05), race (Caucasian vs. Asian, p < 0.05; African-American vs. Asian, p < 0.05) and TP53 mutation (normal vs. TP53 mutation, p < 0.05), considering The Cancer Genome Atlas database. However, for patients who had higher TTN expression, the overall survival was remarkably shorter than patients who had low TTN expression. Furthermore, TTN was lowly expressed in four CRC cell lines. TTN overexpression facilitated CRC cells in terms of the proliferation, metastasis and invasion. Based on gene set enrichment analysis, the ERB pathway might be responsible for TTN-related CRC. Besides, TTN was involved in the response to azacitidine. Overall, TTN might serve as a potential novel therapeutic target for treating and overcoming chemotherapy resistance in CRC.

RNA splicing alterations in lung cancer pathogenesis and therapy

RNA splicing alterations are widespread and play critical roles in cancer pathogenesis and therapy. Lung cancer is highly heterogeneous and causes the most cancer-related deaths worldwide. Large-scale multi-omics studies have not only characterized the mutational landscapes but also discovered a plethora of transcriptional and post-transcriptional changes in lung cancer. Such resources have greatly facilitated the development of new diagnostic markers and therapeutic options over the past two decades. Intriguingly, altered RNA splicing has emerged as an important molecular feature and therapeutic target of lung cancer. In this review, we provide a brief overview of splicing dysregulation in lung cancer and summarize the recent progress on key splicing events and splicing factors that contribute to lung cancer pathogenesis. Moreover, we describe the general strategies targeting splicing alterations in lung cancer and highlight the potential of combining splicing modulation with currently approved therapies to combat this deadly disease. This review provides new mechanistic and therapeutic insights into splicing dysregulation in cancer.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

Targeting alternative splicing in cancer immunotherapy

Tumor immunotherapy has made great progress in cancer treatment but still faces several challenges, such as a limited number of targetable antigens and varying responses among patients. Alternative splicing (AS) is an essential process for the maturation of nearly all mammalian mRNAs. Recent studies show that AS contributes to expanding cancer-specific antigens and modulating immunogenicity, making it a promising solution to the above challenges. The organoid technology preserves the individual immune microenvironment and reduces the time/economic costs of the experiment model, facilitating the development of splicing-based immunotherapy. Here, we summarize three critical roles of AS in immunotherapy: resources for generating neoantigens, targets for immune-therapeutic modulation, and biomarkers to guide immunotherapy options. Subsequently, we highlight the benefits of adopting organoids to develop AS-based immunotherapies. Finally, we discuss the current challenges in studying AS-based immunotherapy in terms of existing bioinformatics algorithms and biological technologies.

mRNA vaccine in cancer therapy: Current advance and future outlook

Messenger ribonucleic acid (mRNA) vaccines are a relatively new class of vaccines that have shown great promise in the immunotherapy of a wide variety of infectious diseases and cancer. In the past 2 years, SARS-CoV-2 mRNA vaccines have contributed tremendously against SARS-CoV2, which has prompted the arrival of the mRNA vaccine research boom, especially in the research of cancer vaccines. Compared with conventional cancer vaccines, mRNA vaccines have significant advantages, including efficient production of protective immune responses, relatively low side effects and lower cost of acquisition. In this review, we elaborated on the development of cancer vaccines and mRNA cancer vaccines, as well as the potential biological mechanisms of mRNA cancer vaccines and the latest progress in various tumour treatments, and discussed the challenges and future directions for the field.

Proteogenomics of clear cell renal cell carcinoma response to tyrosine kinase inhibitor

The tyrosine kinase inhibitor (TKI) Sunitinib is one the therapies approved for advanced renal cell carcinoma. Here, we undertake proteogenomic profiling of 115 tumors from patients with clear cell renal cell carcinoma (ccRCC) undergoing Sunitinib treatment and reveal the molecular basis of differential clinical outcomes with TKI therapy. We find that chromosome 7q gain-induced mTOR signaling activation is associated with poor therapeutic outcomes with Sunitinib treatment, whereas the aristolochic acid signature and VHL mutation synergistically caused enhanced glycolysis is correlated with better prognosis. The proteomic and phosphoproteomic analysis further highlights the responsibility of mTOR signaling for non-response to Sunitinib. Immune landscape characterization reveals diverse tumor microenvironment subsets in ccRCC. Finally, we construct a multi-omics classifier that can detect responder and non-responder patients (receiver operating characteristic-area under the curve, 0.98). Our study highlights associations between ccRCC molecular characteristics and the response to TKI, which can facilitate future improvement of therapeutic responses.

A risk score combining co-expression modules related to myeloid cells and alternative splicing associates with response to PD-1/PD-L1 blockade in non-small cell lung cancer

Background

Comprehensive analysis of transcriptomic profiles of non-small cell lung cancer (NSCLC) may provide novel evidence for biomarkers associated with response to PD-1/PD-L1 immune checkpoint blockade (ICB).

Methods

We utilized weighted gene co-expression network analysis (WGCNA) to analyze transcriptomic data from two NSCLC datasets from Gene Expression Omnibus (GSE135222 and GSE126044) that involved patients received ICB treatment. We evaluated the correlation of co-expression modules with ICB responsiveness and functionally annotated ICB-related modules using pathway enrichment analysis, single-cell RNA sequencing, flow cytometry and alternative splicing analysis. We built a risk score using Lasso-COX regression based on hub genes from ICB-related modules. We investigated the alteration of tumor microenvironment between high- and low- risk groups and the association of the risk score with previously established predictive biomarkers.

Results

Our results identified a black with positive correlation and a blue module with negative correlation to ICB responsiveness. The black module was enriched in pathway of T cell activation and antigen processing and presentation, and the genes assigned to it were consistently expressed on myeloid cells. We observed decreased alternative splicing events in samples with high signature scores of the blue module. The Lasso-COX analysis screened out three genes (EVI2B, DHX9, HNRNPM) and constructed a risk score from the hub genes of the two modules. We validated the predictive value of the risk score for poor response to ICB therapy in an in-house NSCLC cohort and a pan-cancer cohort from the KM-plotter database. The low-risk group had more immune-infiltrated microenvironment, with higher frequencies of precursor exhausted CD8⁺ T cells, tissue-resident CD8⁺ T cells, plasmacytoid dendritic cells and type 1 conventional dendritic cells, and a lower frequency of terminal exhausted CD8⁺ T cells, which may explain its superior response to ICB therapy. The significant correlation of the risk score to gene signature of tertiary lymphoid structure also implicated the possible mechanism of this predictive biomarker.

Conclusions

Our study identified two co-expression modules related to ICB responsiveness in NSCLC and developed a risk score accordingly, which could potentially serve as a predictive biomarker for ICB response.

Recruitment of BAG2 to DNAJ-PKAc scaffolds promotes cell survival and resistance to drug-induced apoptosis in fibrolamellar carcinoma

The DNAJ-PKAc fusion kinase is a defining feature of the adolescent liver cancer fibrolamellar carcinoma (FLC). A single lesion on chromosome 19 generates this mutant kinase by creating a fused gene encoding the chaperonin binding domain of Hsp40 (DNAJ) in frame with the catalytic core of protein kinase A (PKAc). FLC tumors are notoriously resistant to standard chemotherapies. Aberrant kinase activity is assumed to be a contributing factor. Yet recruitment of binding partners, such as the chaperone Hsp70, implies that the scaffolding function of DNAJ- PKAc may also underlie pathogenesis. By combining proximity proteomics with biochemical analyses and photoactivation live-cell imaging we demonstrate that DNAJ-PKAc is not constrained by A-kinase anchoring proteins. Consequently, the fusion kinase phosphorylates a unique array of substrates. One validated DNAJ-PKAc target is the Bcl-2 associated athanogene 2 (BAG2), a co-chaperone recruited to the fusion kinase through association with Hsp70. Immunoblot and immunohistochemical analyses of FLC patient samples correlate increased levels of BAG2 with advanced disease and metastatic recurrences. BAG2 is linked to Bcl-2, an anti-apoptotic factor that delays cell death. Pharmacological approaches tested if the DNAJ- PKAc/Hsp70/BAG2 axis contributes to chemotherapeutic resistance in AML12 DNAJ-PKAc hepatocyte cell lines using the DNA damaging agent etoposide and the Bcl-2 inhibitor navitoclax. Wildtype AML12 cells were susceptible to each drug alone and in combination. In contrast, AML12 DNAJ-PKAc cells were moderately affected by etoposide, resistant to navitoclax, but markedly susceptible to the drug combination. These studies implicate BAG2 as a biomarker for advanced FLC and a chemotherapeutic resistance factor in DNAJ-PKAc signaling scaffolds.

IRIS: Discovery of cancer immunotherapy targets arising from pre-mRNA alternative splicing

Alternative splicing (AS) is prevalent in cancer, generating an extensive but largely unexplored repertoire of novel immunotherapy targets. We describe Isoform peptides from RNA splicing for Immunotherapy target Screening (IRIS), a computational platform capable of discovering AS-derived tumor antigens (TAs) for T cell receptor (TCR) and chimeric antigen receptor T cell (CAR-T) therapies. IRIS leverages large-scale tumor and normal transcriptome data and incorporates multiple screening approaches to discover AS-derived TAs with tumor-associated or tumor-specific expression. In a proof-of-concept analysis integrating transcriptomics and immunopeptidomics data, we showed that hundreds of IRIS-predicted TCR targets are presented by human leukocyte antigen (HLA) molecules. We applied IRIS to RNA-seq data of neuroendocrine prostate cancer (NEPC). From 2,939 NEPC-associated AS events, IRIS predicted 1,651 epitopes from 808 events as potential TCR targets for two common HLA types (A*02:01 and A*03:01). A more stringent screening test prioritized 48 epitopes from 20 events with "neoantigen-like" NEPC-specific expression. Predicted epitopes are often encoded by microexons of ≤30 nucleotides. To validate the immunogenicity and T cell recognition of IRIS-predicted TCR epitopes, we performed in vitro T cell priming in combination with single-cell TCR sequencing. Seven TCRs transduced into human peripheral blood mononuclear cells (PBMCs) showed high activity against individual IRIS-predicted epitopes, providing strong evidence of isolated TCRs reactive to AS-derived peptides. One selected TCR showed efficient cytotoxicity against target cells expressing the target peptide. Our study illustrates the contribution of AS to the TA repertoire of cancer cells and demonstrates the utility of IRIS for discovering AS-derived TAs and expanding cancer immunotherapies.

Stimuli-Responsive Polymeric Nanovaccines Toward Next-Generation Immunotherapy

The development of nanovaccines that employ polymeric delivery carriers has garnered substantial interest in therapeutic treatment of cancer and a variety of infectious diseases due to their superior biocompatibility, lower toxicity and reduced immunogenicity. Particularly, stimuli-responsive polymeric nanocarriers show great promise for delivering antigens and adjuvants to targeted immune cells, preventing antigen degradation and clearance, and increasing the uptake of specific antigen-presenting cells, thereby sustaining adaptive immune responses and improving immunotherapy for certain diseases. In this review, the most recent advances in the utilization of stimulus-responsive polymer-based nanovaccines for immunotherapeutic applications are presented. These sophisticated polymeric nanovaccines with diverse functions, aimed at therapeutic administration for disease prevention and immunotherapy, are further classified into several active domains, including pH, temperature, redox, light and ultrasound-sensitive intelligent nanodelivery systems. Finally, the potential strategies for the future design of multifunctional next-generation polymeric nanovaccines by integrating materials science with biological interface are proposed.

LENS: Landscape of Effective Neoantigens Software

MOTIVATION

Elimination of cancer cells by T cells is a critical mechanism of anti-tumor immunity and cancer immunotherapy response. T cells recognize cancer cells by engagement of T cell receptors with peptide epitopes presented by major histocompatibility complex molecules on the cancer cell surface. Peptide epitopes can be derived from antigen proteins coded for by multiple genomic sources. Bioinformatics tools used to identify tumor-specific epitopes via analysis of DNA and RNA-sequencing data have largely focused on epitopes derived from somatic variants, though a smaller number have evaluated potential antigens from other genomic sources.

RESULTS

We report here an open-source workflow utilizing the Nextflow DSL2 workflow manager, Landscape of Effective Neoantigens Software (LENS), which predicts tumor-specific and tumor-associated antigens from single nucleotide variants, insertions and deletions, fusion events, splice variants, cancer-testis antigens, overexpressed self-antigens, viruses, and endogenous retroviruses. The primary advantage of LENS is that it expands the breadth of genomic sources of discoverable tumor antigens using genomics data. Other advantages include modularity, extensibility, ease of use, and harmonization of relative expression level and immunogenicity prediction across multiple genomic sources. We present an analysis of 115 acute myeloid leukemia samples to demonstrate the utility of LENS. We expect LENS will be a valuable platform and resource for T cell epitope discovery bioinformatics, especially in cancers with few somatic variants where tumor-specific epitopes from alternative genomic sources are an elevated priority.

AVAILABILITY AND IMPLEMENTATION

More information about LENS, including code, workflow documentation, and instructions, can be found at (https://gitlab.com/landscape-of-effective-neoantigens-software).

mRNA isoform balance in neuronal development and disease

Balanced mRNA isoform diversity and abundance are spatially and temporally regulated throughout cellular differentiation. The proportion of expressed isoforms contributes to cell type specification and determines key properties of the differentiated cells. Neurons are unique cell types with intricate developmental programs, characteristic cellular morphologies, and electrophysiological potential. Neuron-specific gene expression programs establish these distinctive cellular characteristics and drive diversity among neuronal subtypes. Genes with neuron-specific alternative processing are enriched in key neuronal functions, including synaptic proteins, adhesion molecules, and scaffold proteins. Despite the similarity of neuronal gene expression programs, each neuronal subclass can be distinguished by unique alternative mRNA processing events. Alternative processing of developmentally important transcripts alters coding and regulatory information, including interaction domains, transcript stability, subcellular localization, and targeting by RNA binding proteins. Fine-tuning of mRNA processing is essential for neuronal activity and maintenance. Thus, the focus of neuronal RNA biology research is to dissect the transcriptomic mechanisms that underlie neuronal homeostasis, and consequently, predispose neuronal subtypes to disease. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Alternative mRNA Splicing and Promising Therapies in Cancer

Cancer is among the leading causes of mortality worldwide. While considerable attention has been given to genetic and epigenetic sources of cancer-specific cellular activities, the role of alternative mRNA splicing has only recently received attention as a major contributor to cancer initiation and progression. The distribution of alternate mRNA splicing variants in cancer cells is different from their non-cancer counterparts, and cancer cells are more sensitive than non-cancer cells to drugs that target components of the splicing regulatory network. While many of the alternatively spliced mRNAs in cancer cells may represent "noise" from splicing dysregulation, certain recurring splicing variants have been shown to contribute to tumor progression. Some pathogenic splicing disruption events result from mutations in cis-acting splicing regulatory sequences in disease-associated genes, while others may result from shifts in balance among naturally occurring alternate splicing variants among mRNAs that participate in cell cycle progression and the regulation of apoptosis. This review provides examples of cancer-related alternate splicing events resulting from each step of mRNA processing and the promising therapies that may be used to address them.

Interaction of a Novel Alternatively Spliced Variant of HSD11B1L with Parkin Enhances the Carcinogenesis Potential of Glioblastoma: Peiminine Interferes with This Interaction

Glioblastoma (GBM) is a primary brain tumor of unknown etiology. It is extremely aggressive, incurable and has a short average survival time for patients. Therefore, understanding the precise molecular mechanisms of this diseases is essential to establish effective treatments. In this study, we cloned and sequenced a splice variant of the hydroxysteroid 11-β dehydrogenase 1 like gene (HSD11B1L) and named it HSD11B1L-181. HSD11 B1L-181 was specifically expressed only in GBM cells. Overexpression of this variant can significantly promote the proliferation, migration and invasion of GBM cells. Knockdown of HSD11B1L-181 expression inhibited the oncogenic potential of GBM cells. Furthermore, we identified the direct interaction of parkin with HSD11B1L-181 by screening the GBM cDNA expression library via yeast two-hybrid. Parkin is an RBR E3 ubiquitin ligase whose mutations are associated with tumorigenesis. Small interfering RNA treatment of parkin enhanced the proliferative, migratory and invasive abilities of GBM. Finally, we found that the alkaloid peiminine from the bulbs of Fritillaria thunbergii Miq blocks the interaction between HSD11B1L-181 and parkin, thereby lessening carcinogenesis of GBM. We further confirmed the potential of peiminine to prevent GBM in cellular, ectopic and orthotopic xenograft mouse models. Taken together, these findings not only provide insight into GBM, but also present an opportunity for future GBM treatment.

Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment.

Recent advances in aptamer-based therapeutic strategies for targeting cancer stem cells

Cancer stem cells (CSCs) are believed to be the main cause of chemotherapy resistance and tumor relapse. Various therapeutic strategies to eliminate CSCs have been developed recently. Aptamers, also called "chemical antibodies", can specifically bind with their molecular targets through special tertiary structures. The advantages of aptamers, such as lower immunogenicity and smaller size, make them superior to conventional antibodies. Therefore, aptamers have been used widely as targeting ligands for CSC-targeted therapeutic strategies in different tumor types. To date, various therapeutic cargoes have been conjugated to aptamers to kill CSCs, such as chemotherapy drugs, small interfering RNAs, and microRNAs. Aptamer-based targeted therapies for CSCs have made great progress in recent years, especially the development of multifunctional aptamer-based therapeutic strategies. Besides, cell-systematic evolution of ligands by exponential enrichment has been applied to screen new aptamers that might have a higher binding ability for CSCs. In this review, we focus on recent advances and introduce some new modalities of aptamer-drug conjugates against CSCs. Some considerations of the advantages and limitations of different aptamer-based targeted therapies for CSCs are also discussed.

RNA splicing dysregulation and the hallmarks of cancer

Dysregulated RNA splicing is a molecular feature that characterizes almost all tumour types. Cancer-associated splicing alterations arise from both recurrent mutations and altered expression of trans-acting factors governing splicing catalysis and regulation. Cancer-associated splicing dysregulation can promote tumorigenesis via diverse mechanisms, contributing to increased cell proliferation, decreased apoptosis, enhanced migration and metastatic potential, resistance to chemotherapy and evasion of immune surveillance. Recent studies have identified specific cancer-associated isoforms that play critical roles in cancer cell transformation and growth and demonstrated the therapeutic benefits of correcting or otherwise antagonizing such cancer-associated mRNA isoforms. Clinical-grade small molecules that modulate or inhibit RNA splicing have similarly been developed as promising anticancer therapeutics. Here, we review splicing alterations characteristic of cancer cell transcriptomes, dysregulated splicing's contributions to tumour initiation and progression, and existing and emerging approaches for targeting splicing for cancer therapy. Finally, we discuss the outstanding questions and challenges that must be addressed to translate these findings into the clinic.

Human FOXP3 and tumour microenvironment

The tumour microenvironment (TME) is a complex system composed of cancer cells, stromal cells and immune cells. Regulatory T cells (Tregs) in the TME impede immune surveillance of tumours and suppress antitumor immune responses. Transcription factor forkhead box protein 3 (FOXP3) is the main marker of Tregs, which dominates the function of Tregs. FOXP3 was originally thought to be a Tregs-specific expression molecule, and recent studies have found that FOXP3 is expressed in a variety of tumours with inconsistent functional roles. This review summarizes the recent progress of infiltrating Treg-FOXP3 and tumour-FOXP3 in TME, discusses the communication mechanism between FOXP3⁺ cells and effector T cells in TME, the relationship between FOXP3 and clinical prognosis, and the potential of FOXP3-targeted therapy.

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

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

Position-dependent effects of RNA-binding proteins in the context of co-transcriptional splicing

Alternative splicing is an important step in eukaryotic mRNA pre-processing which increases the complexity of gene expression programs, but is frequently altered in disease. Previous work on the regulation of alternative splicing has demonstrated that splicing is controlled by RNA-binding proteins (RBPs) and by epigenetic DNA/histone modifications which affect splicing by changing the speed of polymerase-mediated pre-mRNA transcription. The interplay of these different layers of splicing regulation is poorly understood. In this paper, we derived mathematical models describing how splicing decisions in a three-exon gene are made by combinatorial spliceosome binding to splice sites during ongoing transcription. We additionally take into account the effect of a regulatory RBP and find that the RBP binding position within the sequence is a key determinant of how RNA polymerase velocity affects splicing. Based on these results, we explain paradoxical observations in the experimental literature and further derive rules explaining why the same RBP can act as inhibitor or activator of cassette exon inclusion depending on its binding position. Finally, we derive a stochastic description of co-transcriptional splicing regulation at the single-cell level and show that splicing outcomes show little noise and follow a binomial distribution despite complex regulation by a multitude of factors. Taken together, our simulations demonstrate the robustness of splicing outcomes and reveal that quantitative insights into kinetic competition of co-transcriptional events are required to fully understand this important mechanism of gene expression diversity.

Neoantigens: promising targets for cancer therapy

Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.

Alternative splicing event associated with immunological features in bladder cancer

Bladder cancer (BLCA) is the most prevalent urinary tumor with few treatments. Alternative splicing (AS) is closely related to tumor development and tumor immune microenvironment. However, the comprehensive analysis of AS and prognosis and immunological features in BLCA is still lacking. In this study, we downloaded RNA-Seq data and clinical information from The Cancer Genome Atlas (TCGA) database, and AS events were acquired from the TCGA Splice-seq. A total of eight prognostic AS events (C19orf57|47943|ES, ANK3|11845|AP, AK9|77203|AT, GRIK2|77096|AT, DYM|45472|ES, PTGER3|3415|AT, ACTG1|44120|RI, and TRMU|62711|AA) were identified by univariate analysis and least absolute shrinkage and selection operator (LASSO) regression analysis to construct a risk score model. The Kaplan-Meier analysis revealed that the high-risk group had a worse prognosis compared with the low-risk group. The area under the receiver operating characteristic (ROC) curves (AUCs) for this risk score model in 1, 3, and 5 years were 0.698, 0.742, and 0.772, respectively. One of the prognostic AS event-related genes, TRMU, was differentially expressed between tumor and normal tissues in BLCA. The single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithm showed that both the risk score model and TRMU were significantly associated with tumor immune microenvironment and immune status (immune cells, immune-related pathway, and immune checkpoint) in BLCA patients. The TIMER database confirmed the relationship between the expression of TRMU and immune cells and checkpoint genes. Furthermore, Cytoscape software 3.8.0 was used to construct the regulatory network between AS and splicing factors (SFs). Our study demonstrated that AS events were powerful biomarkers to predict the prognosis and immune status in BLCA, which may be potential therapeutic targets in BLCA.

3D genome organization around nuclear speckles drives mRNA splicing efficiency

The nucleus is highly organized such that factors involved in transcription and processing of distinct classes of RNA are organized within specific nuclear bodies. One such nuclear body is the nuclear speckle, which is defined by high concentrations of protein and non-coding RNA regulators of pre-mRNA splicing. What functional role, if any, speckles might play in the process of mRNA splicing remains unknown. Here we show that genes localized near nuclear speckles display higher spliceosome concentrations, increased spliceosome binding to their pre-mRNAs, and higher co-transcriptional splicing levels relative to genes that are located farther from nuclear speckles. We show that directed recruitment of a pre-mRNA to nuclear speckles is sufficient to drive increased mRNA splicing levels. Finally, we show that gene organization around nuclear speckles is highly dynamic with differential localization between cell types corresponding to differences in Pol II occupancy. Together, our results integrate the longstanding observations of nuclear speckles with the biochemistry of mRNA splicing and demonstrate a critical role for dynamic 3D spatial organization of genomic DNA in driving spliceosome concentrations and controlling the efficiency of mRNA splicing.

Increased Expression of SRSF1 Predicts Poor Prognosis in Multiple Myeloma

Background

Multiple myeloma (MM) is a clonal plasma cell disorder which still lacks sufficient prognostic factors. The serine/arginine-rich splicing factor (SRSF) family serves as an important splicing regulator in organ development. Among all members, SRSF1 plays an important role in cell proliferation and renewal. However, the role of SRSF1 in MM is still unknown.

Methods

SRSF1 was selected from the primary bioinformatics analysis of SRSF family members, and then we integrated 11 independent datasets and analyzed the relationship between SRSF1 expression and MM clinical characteristics. Gene set enrichment analysis (GSEA) was conducted to explore the potential mechanism of SRSF1 in MM progression. ImmuCellAI was used to estimate the abundance of immune infiltrating cells between the SRSF1^high and SRSF1^low groups. The ESTIMATE algorithm was used to evaluate the tumor microenvironment in MM. The expression of immune-related genes was compared between the groups. Additionally, SRSF1 expression was validated in clinical samples. SRSF1 knockdown was conducted to explore the role of SRSF1 in MM development.

Results

SRSF1 expression showed an increasing trend with the progression of myeloma. Besides, SRSF1 expression increased as the age, ISS stage, 1q21 amplification level, and relapse times increased. MM patients with higher SRSF1 expression had worse clinical features and poorer outcomes. Univariate and multivariate analysis indicated that upregulated SRSF1 expression was an independent poor prognostic factor for MM. Enrichment pathway analysis confirmed that SRSF1 takes part in the myeloma progression via tumor-associated and immune-related pathways. Several checkpoints and immune-activating genes were significantly downregulated in the SRSF1^high groups. Furthermore, we detected that SRSF1 expression was significantly higher in MM patients than that in control donors. SRSF1 knockdown resulted in proliferation arrest in MM cell lines.

Conclusion

The expression value of SRSF1 is positively associated with myeloma progression, and high SRSF1 expression might be a poor prognostic biomarker in MM patients.

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 Emerging Role of uORF-Encoded uPeptides and HLA uLigands in Cellular and Tumor Biology

Recent technological advances have facilitated the detection of numerous non-canonical human peptides derived from regulatory regions of mRNAs, long non-coding RNAs, and other cryptic transcripts. In this review, we first give an overview of the classification of these novel peptides and summarize recent improvements in their annotation and detection by ribosome profiling, mass spectrometry, and individual experimental analysis. A large fraction of the novel peptides originates from translation at upstream open reading frames (uORFs) that are located within the transcript leader sequence of regular mRNA. In humans, uORF-encoded peptides (uPeptides) have been detected in both healthy and malignantly transformed cells and emerge as important regulators in cellular and immunological pathways. In the second part of the review, we focus on various functional implications of uPeptides. As uPeptides frequently act at the transition of translational regulation and individual peptide function, we describe the mechanistic modes of translational regulation through ribosome stalling, the involvement in cellular programs through protein interaction and complex formation, and their role within the human leukocyte antigen (HLA)-associated immunopeptidome as HLA uLigands. We delineate how malignant transformation may lead to the formation of novel uORFs, uPeptides, or HLA uLigands and explain their potential implication in tumor biology. Ultimately, we speculate on a potential use of uPeptides as peptide drugs and discuss how uPeptides and HLA uLigands may facilitate translational inhibition of oncogenic protein messages and immunotherapeutic approaches in cancer therapy.

Splicing-Disrupting Mutations in Inherited Predisposition to Solid Pediatric Cancer

The prevalence of hereditary cancer in children was estimated to be very low until recent studies suggested that at least 10% of pediatric cancer patients carry a germline mutation in a cancer predisposition gene. A significant proportion of pathogenic variants associated with an increased risk of hereditary cancer are variants affecting splicing. RNA splicing is an essential process involved in different cellular processes such as proliferation, survival, and differentiation, and alterations in this pathway have been implicated in many human cancers. Hereditary cancer genes are highly susceptible to splicing mutations, and among them there are several genes that may contribute to pediatric solid tumors when mutated in the germline. In this review, we have focused on the analysis of germline splicing-disrupting mutations found in pediatric solid tumors, as the discovery of pathogenic splice variants in pediatric cancer is a growing field for the development of personalized therapies. Therapies developed to correct aberrant splicing in cancer are also discussed as well as the options to improve the diagnostic yield based on the increase in the knowledge in splicing.

SRSF5-Mediated Alternative Splicing of M Gene is Essential for Influenza A Virus Replication: A Host-Directed Target Against Influenza Virus

Splicing of influenza A virus (IAV) RNA is an essential process in the viral life cycle that involves the co-opting of host factors. Here, it is demonstrated that induction of host serine and arginine-rich splicing factor 5 (SRSF5) by IAV facilitated viral replication by enhancing viral M mRNA splicing. Mechanistically, SRSF5 with its RRM2 domain directly bounds M mRNA at conserved sites (M mRNA position 163, 709, and 712), and interacts with U1 small nuclear ribonucleoprotein (snRNP) to promote M mRNA splicing and M2 production. Mutations introduced to the three binding sites, without changing amino acid code, significantly attenuates virus replication and pathogenesis in vivo. Likewise, SRSF5 conditional knockout in the lung protects mice against lethal IAV challenge. Furthermore, anidulafungin, an approved antifungal drug, is identified as an inhibitor of SRSF5 that effectively blocks IAV replication in vitro and in vivo. In conclusion, SRSF5 as an activator of M mRNA splicing promotes IAV replication and is a host-derived antiviral target.

RNA and RNA Derivatives: Light and Dark Sides in Cancer Immunotherapy

Significance: Immunotherapy, which utilizes the patient's immune system to fight tumor cells, has been approved for the treatment of some types of advanced cancer. Recent Advances: The complexity and diversity of tumor immunity are responsible for the varying response rates toward current immunotherapy strategies and highlight the importance of exploring regulators in tumor immunotherapy. Several genetic factors have proved to be critical regulators of tumor immunotherapy. RNAs, including messenger RNAs and non-coding RNAs, play vital and diverse roles in tumorigenesis, metastasis, drug resistance, and immunotherapy response. RNA modifications, including N6-methyladenosine methylation, are involved in tumor immunity. Critical Issues: A critical issue is the lack of summary of the regulatory RNA molecules and their derivatives in mediating immune activities in human cancers that could provide potential applications for tumor immunotherapeutic strategy. Future Directions: This review summarizes the dual roles (the light and dark sides) of RNA and its derivatives in tumor immunotherapy and discusses the development of RNA-based therapies as novel immunotherapeutic strategies for cancer treatment. Antioxid. Redox Signal. 37, 1266-1290.

Chemical induction of splice-neoantigens attenuates tumor growth in a preclinical model of colorectal cancer

Neoantigen production is a determinant of cancer immunotherapy. However, the expansion of neoantigen abundance for cancer therapeutics is technically challenging. Here, we report that the synthetic compound RECTAS can induce the production of splice-neoantigens that could be used to boost antitumor immune responses. RECTAS suppressed tumor growth in a CD8⁺ T cell- and tumor major histocompatibility complex class I-dependent manner and enhanced immune checkpoint blockade efficacy. Subsequent transcriptome analysis and validation for immunogenicity identified six splice-neoantigen candidates whose expression was induced by RECTAS treatment. Vaccination of the identified neoepitopes elicited T cell responses capable of killing cancer cells in vitro, in addition to suppression of tumor growth in vivo upon sensitization with RECTAS. Collectively, these results provide support for the further development of splice variant-inducing treatments for cancer immunotherapy.

A Whole New Comprehension about ncRNA-Encoded Peptides/Proteins in Cancers

Simple Summary

The advent of bioinformatics and high-throughput sequencing have disclosed the complexity of ORFs in ncRNAs. Thus, there is a dire need to deep into the real role of ncRNA-encoded proteins/peptides. Considerable progress has been achieved in several fields, ranging from the mechanism translation of ORFs in ncRNAs to various reliable detection means and experimental approaches. Several studies have been stressing functions and mechanisms of ncRNA-encoded peptides/proteins in cancers, which are helpful for us to understand the specific biological regulating procedure. Innovative research on animal models confirms the potential of clinical applications, such as being tumor biomarkers, antitumor drugs and cancer vaccines. In this review, we conclude the latest discoveries of ncRNA-encoded peptides/proteins, we are looking forwards to accelerating the pace of detection and diagnosis development in cancers.

Abstract

It is generally considered that non-coding RNAs do not encode proteins; however, more recently, studies have shown that lncRNAs and circRNAs have ORFs which are regions that code for peptides/protein. On account of the lack of 5′cap structure, translation of circRNAs is driven by IRESs, m6A modification or through rolling amplification. An increasing body of evidence have revealed different functions and mechanisms of ncRNA-encoded peptides/proteins in cancers, including regulation of signal transduction (Wnt/β-catenin signaling, AKT-related signaling, MAPK signaling and other signaling), cellular metabolism (Glucose metabolism and Lipid metabolism), protein stability, transcriptional regulation, posttranscriptional regulation (regulation of RNA stability, mRNA splicing and translation initiation). In addition, we conclude the existing detection technologies and the potential of clinical applications in cancer therapy.