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

Computational immunogenomic approaches to predict response to cancer immunotherapies

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.

Neoantigen cancer vaccines: a new star on the horizon

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells. One of the most exciting advances within this field is the targeting of neoantigens, which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells. Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment, early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors. Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens. Consequently, personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences. This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines, and also discusses challenges and future perspectives for this innovative approach, particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

RBFOX2 deregulation promotes pancreatic cancer progression and metastasis through alternative splicing

RNA splicing is an important biological process associated with cancer initiation and progression. However, the contribution of alternative splicing to pancreatic cancer (PDAC) development is not well understood. Here, we identify an enrichment of RNA binding proteins (RBPs) involved in splicing regulation linked to PDAC progression from a forward genetic screen using Sleeping Beauty insertional mutagenesis in a mouse model of pancreatic cancer. We demonstrate downregulation of RBFOX2, an RBP of the FOX family, promotes pancreatic cancer progression and liver metastasis. Specifically, we show RBFOX2 regulates exon splicing events in transcripts encoding proteins involved in cytoskeletal remodeling programs. These exons are differentially spliced in PDAC patients, with enhanced exon skipping in the classical subtype for several RBFOX2 targets. RBFOX2 mediated splicing of ABI1, encoding the Abelson-interactor 1 adapter protein, controls the abundance and localization of ABI1 protein isoforms in pancreatic cancer cells and promotes the relocalization of ABI1 from the cytoplasm to the periphery of migrating cells. Using splice-switching antisense oligonucleotides (AONs) we demonstrate the ABI1 ∆Ex9 isoform enhances cell migration. Together, our data identify a role for RBFOX2 in promoting PDAC progression through alternative splicing regulation.

RPL22 is a tumor suppressor in MSI-high cancers and a key splicing regulator of MDM4

Microsatellite instability high (MSI-H) tumors are malignant tumors that, despite harboring a high mutational burden, often have intact TP53. One of the most frequent mutations in MSI-H tumors is a frameshift mutation in RPL22, a ribosomal protein. Here, we identified RPL22 as a modulator of MDM4 splicing through an alternative splicing switch in exon 6. RPL22 loss increases MDM4 exon 6 inclusion, cell proliferation, and augments resistance to the MDM inhibitor Nutlin-3a. RPL22 represses expression of its paralog, RPL22L1, by mediating the splicing of a cryptic exon corresponding to a truncated transcript. Therefore, damaging mutations in RPL22 drive oncogenic MDM4 induction and reveal a common splicing circuit in MSI-H tumors that may inform therapeutic targeting of the MDM4-p53 axis and oncogenic RPL22L1 induction.

Comparison of Alternative Splicing Landscapes Revealed by Long-Read Sequencing in Hepatocyte-Derived HepG2 and Huh7 Cultured Cells and Human Liver Tissue

The long-read RNA sequencing developed by Oxford Nanopore Technologies provides a direct quantification of transcript isoforms, thereby making it possible to present alternative splicing (AS) profiles as arrays of single splice variants with different abundances. Additionally, AS profiles can be presented as arrays of genes characterized by the degree of alternative splicing (the DAS-the number of detected splice variants per gene). Here, we successfully utilized the DAS to reveal biological pathways influenced by the alterations in AS in human liver tissue and the hepatocyte-derived malignant cell lines HepG2 and Huh7, thus employing the mathematical algorithm of gene set enrichment analysis. Furthermore, analysis of the AS profiles as abundances of single splice variants by using the graded tissue specificity index τ provided the selection of the groups of genes expressing particular splice variants specifically in liver tissue, HepG2 cells, and Huh7 cells. The majority of these splice variants were translated into proteins products and appeal to be in focus regarding further insights into the mechanisms underlying cell malignization. The used metrics are intrinsically suitable for transcriptome-wide AS profiling using long-read sequencing.

Long-Read Sequencing Reveals Alternative Splicing-Driven, Shared Immunogenic Neoepitopes Regardless of SF3B1 Status in Uveal Melanoma

Tumor-specific neoepitopes are promising targets in cancer immunotherapy. However, the identification of functional tumor-specific neoepitopes remains challenging. In addition to the most common source, single-nucleotide variants (SNV), alternative splicing (AS) represents another rich source of neoepitopes and can be utilized in cancers with low SNVs such as uveal melanoma (UM). UM, the most prevalent adult ocular malignancy, has poor clinical outcomes due to a lack of effective therapies. Recent studies have revealed the promise of harnessing tumor neoepitopes to treat UM. Previous studies have focused on neoepitope targets associated with mutations in splicing factor 3b subunit 1 (SF3B1), a key splicing factor; however, little is known about the neoepitopes that are commonly shared by patients independent of SF3B1 status. To identify the AS-derived neoepitopes regardless of SF3B1 status, we herein used a comprehensive nanopore long-read-sequencing approach to elucidate the landscape of AS and novel isoforms in UM. We also performed high-resolution mass spectrometry to further validate the presence of neoepitope candidates and analyzed their structures using the AlphaFold2 algorithm. We experimentally evaluated the antitumor effects of these neoepitopes and found they induced robust immune responses by stimulating interferon (IFN)γ production and activating T cell-based UM tumor killing. These results provide novel insights into UM-specific neoepitopes independent of SF3B1 and lay the foundation for developing therapies by targeting these actionable neoepitopes.

A hidden translatome in tumors-the coding lncRNAs

Long noncoding RNAs (lncRNAs) have been extensively identified in eukaryotic genomes and have been shown to play critical roles in the development of multiple cancers. Through the application and development of ribosome analysis and sequencing technologies, advanced studies have discovered the translation of lncRNAs. Although lncRNAs were originally defined as noncoding RNAs, many lncRNAs actually contain small open reading frames that are translated into peptides. This opens a broad area for the functional investigation of lncRNAs. Here, we introduce prospective methods and databases for screening lncRNAs with functional polypeptides. We also summarize the specific lncRNA-encoded proteins and their molecular mechanisms that promote or inhibit cancerous. Importantly, the role of lncRNA-encoded peptides/proteins holds promise in cancer research, but some potential challenges remain unresolved. This review includes reports on lncRNA-encoded peptides or proteins in cancer, aiming to provide theoretical basis and related references to facilitate the discovery of more functional peptides encoded by lncRNA, and to further develop new anti-cancer therapeutic targets as well as clinical biomarkers of diagnosis and prognosis.

Comparative RNA-Seq Analysis Revealed Tissue-Specific Splicing Variations during the Generation of the PDX Model

Tissue-specific gene expression generates fundamental differences in the function of each tissue and affects the characteristics of the tumors that are created as a result. However, it is unclear how much the tissue specificity is conserved during grafting of the primary tumor into an immune-compromised mouse model. Here, we performed a comparative RNA-seq analysis of four different primary-patient derived xenograft (PDX) tumors. The analysis revealed a conserved RNA biotype distribution of primary-PDX pairs, as revealed by previous works. Interestingly, we detected significant changes in the splicing pattern of PDX, which was mainly comprised of skipped exons. This was confirmed by splicing variant-specific RT-PCR analysis. On the other hand, the correlation analysis for the tissue-specific genes indicated overall strong positive correlations between the primary and PDX tumor pairs, with the exception of gastric cancer cases, which showed an inverse correlation. These data propose a tissue-specific change in splicing events during PDX formation as a variable factor that affects primary-PDX integrity.

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

DASES: a database of alternative splicing for esophageal squamous cell carcinoma

Esophageal carcinoma ranks as the sixth leading cause of cancer-related mortality globally, with esophageal squamous cell carcinoma (ESCC) being particularly prevalent among Asian populations. Alternative splicing (AS) plays a pivotal role in ESCC development and progression by generating diverse transcript isoforms. However, the current landscape lacks a specialized database focusing on alternative splicing events (ASEs) derived from a large number of ESCC cases. Additionally, most existing AS databases overlook the contribution of long non-coding RNAs (lncRNAs) in ESCC molecular mechanisms, predominantly focusing on mRNA-based ASE identification. To address these limitations, we deployed DASES (http://www.hxdsjzx.cn/DASES). Employing a combination of publicly available and in-house ESCC RNA-seq datasets, our extensive analysis of 346 samples, with 93% being paired tumor and adjacent non-tumor tissues, led to the identification of 257 novel lncRNAs in esophageal squamous cell carcinoma. Leveraging a paired comparison of tumor and adjacent normal tissues, DASES identified 59,094 ASEs that may be associated with ESCC. DASES fills a critical gap by providing comprehensive insights into ASEs in ESCC, encompassing lncRNAs and mRNA, thus facilitating a deeper understanding of ESCC molecular mechanisms and serving as a valuable resource for ESCC research communities.

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

Background

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 neoantigens.

Results

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 neoantigens that could be targeted by antibodies and chimeric antigen receptor (CAR)-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas [TCGA]) and 9,166 normal tissue samples (from the Genotype-Tissue Expression project [GTEx]), 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 neoantigens.

Conclusions

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.

Harnessing tumor immunogenomics: Tumor neoantigens in ovarian cancer and beyond

Ovarian cancer is a major cause of death among gynecological cancers due to its highly aggressive nature. Immunotherapy has emerged as a promising avenue for ovarian cancer treatment, offering targeted approaches with reduced off-target effects. With the advent of next-generation sequencing, it has become possible to identify genomic alterations that can serve as potential targets for immunotherapy. Furthermore, immunogenomics research has revealed the importance of genetic alterations in shaping the cancer immune responses. However, the heterogeneity of immunogenicity and the low tumor mutation burden pose challenges for neoantigen-based immunotherapies. Further research is needed to identify neoantigen-specific tumor-infiltrating lymphocytes (TIL) and establish guidelines for patient inclusion criteria in TIL-based therapy. The study of neoantigens and their implications in ovarian cancer immunotherapy holds great promise, and efforts focused on personalized treatment strategies, refined neoantigen selection, and optimized therapeutic combinations will contribute to improving patient outcomes in the future.

Genetic Control of Alternative Splicing and its Distinct Role in Colorectal Cancer Mechanisms

BACKGROUND & AIMS

Dysregulation of alternative splicing is implicated in many human diseases, and understanding the genetic variation underlying transcript splicing is essential to dissect the molecular mechanisms of cancers. We aimed to provide a comprehensive functional dissection of splicing quantitative trait loci (sQTLs) in cancer and focus on elucidating its distinct role in colorectal cancer (CRC) mechanisms.

METHODS

We performed a comprehensive sQTL analysis to identify genetic variants that control messenger RNA splicing across 33 cancer types from The Cancer Genome Atlas and independently validated in our 154 CRC tissues. Then, large-scale, multicenter, multi-ethnic case-control studies (34,585 cases and 76,023 controls) were conducted to examine the association of these sQTLs with CRC risk. A series of biological experiments in vitro and in vivo were performed to investigate the potential mechanisms of the candidate sQTLs and target genes.

RESULTS

The molecular characterization of sQTL revealed its distinct role in cancer susceptibility. Tumor-specific sQTL further showed better response to cancer development. In addition, functionally informed polygenic risk score highlighted the potentiality of sQTLs in the CRC prediction. Complemented by large-scale population studies, we identified that the risk allele (T) of a multi-ancestry-associated sQTL rs61746794 significantly increased the risk of CRC in Chinese (odds ratio, 1.20; 95% CI, 1.12-1.29; P = 8.82 × 10-7) and European (odds ratio, 1.11; 95% CI, 1.07-1.16; P = 1.13 × 10-7) populations. rs61746794-T facilitated PRMT7 exon 16 splicing mediated by the RNA-binding protein PRPF8, thus increasing the level of canonical PRMT7 isoform (PRMT7-V2). Overexpression of PRMT7-V2 significantly enhanced the growth of CRC cells and xenograft tumors compared with PRMT7-V1. Mechanistically, PRMT7-V2 functions as an epigenetic writer that catalyzes the arginine methylation of H4R3 and H3R2, subsequently regulating diverse biological processes, including YAP, AKT, and KRAS pathway. A selective PRMT7 inhibitor, SGC3027, exhibited antitumor effects on human CRC cells.

CONCLUSIONS

Our study provides an informative sQTLs resource and insights into the regulatory mechanisms linking splicing variants to cancer risk and serving as biomarkers and therapeutic targets.

Nanopore long-read RNA sequencing reveals functional alternative splicing variants in human vascular smooth muscle cells

Vascular smooth muscle cells (VSMCs) are the major contributor to vascular repair and remodeling, which showed high level of phenotypic plasticity. Abnormalities in VSMC plasticity can lead to multiple cardiovascular diseases, wherein alternative splicing plays important roles. However, alternative splicing variants in VSMC plasticity are not fully understood. Here we systematically characterized the long-read transcriptome and their dysregulation in  human aortic smooth muscle cells (HASMCs) by employing the Oxford Nanopore Technologies long-read RNA sequencing in HASMCs that are separately treated with platelet-derived growth factor, transforming growth factor, and hsa-miR-221-3P transfection. Our analysis reveals frequent alternative splicing events and thousands of unannotated transcripts generated from alternative splicing. HASMCs treated with different factors exhibit distinct transcriptional reprogramming modulated by alternative splicing. We also found that unannotated transcripts produce different open reading frames compared to the annotated transcripts. Finally, we experimentally validated the unannotated transcript derived from gene CISD1, namely CISD1-u, which plays a role in the phenotypic switch of HASMCs. Our study characterizes the phenotypic modulation of HASMCs from an insight of long-read transcriptome, which would promote the understanding and the manipulation of HASMC plasticity in cardiovascular diseases.

Splicing quality control mediated by DHX15 and its G-patch activator SUGP1

Pre-mRNA splicing is surveilled at different stages by quality control (QC) mechanisms. The leukemia-associated DExH-box family helicase hDHX15/scPrp43 is known to disassemble spliceosomes after splicing. Here, using rapid protein depletion and analysis of nascent and mature RNA to enrich for direct effects, we identify a widespread splicing QC function for DHX15 in human cells, consistent with recent in vitro studies. We find that suboptimal introns with weak splice sites, multiple branch points, and cryptic introns are repressed by DHX15, suggesting a general role in promoting splicing fidelity. We identify SUGP1 as a G-patch factor that activates DHX15's splicing QC function. This interaction is dependent on both DHX15's ATPase activity and on SUGP1's U2AF ligand motif (ULM) domain. Together, our results support a model in which DHX15 plays a major role in splicing QC when recruited and activated by SUGP1.

The role of alternative pre-mRNA splicing in cancer progression

Alternative pre-mRNA splicing is a critical mechanism that generates multiple mRNA from a single gene, thereby increasing the diversity of the proteome. Recent research has highlighted the significance of specific splicing isoforms in cellular processes, particularly in regulating cell numbers. In this review, we examine the current understanding of the role of alternative splicing in controlling cancer cell growth and discuss specific splicing factors and isoforms and their molecular mechanisms in cancer progression. These isoforms have been found to intricately control signaling pathways crucial for cell cycle progression, proliferation, and apoptosis. Furthermore, studies have elucidated the characteristics and functional importance of splicing factors that influence cell numbers. Abnormal expression of oncogenic splicing isoforms and splicing factors, as well as disruptions in splicing caused by genetic mutations, have been implicated in the development and progression of tumors. Collectively, these findings provide valuable insights into the complex interplay between alternative splicing and cell proliferation, thereby suggesting the potential of alternative splicing as a therapeutic target for cancer.

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

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

Mutant SF3B1 promotes malignancy in PDAC

The splicing factor SF3B1 is recurrently mutated in various tumors, including pancreatic ductal adenocarcinoma (PDAC). The impact of the hotspot mutation SF3B1K700E on the PDAC pathogenesis, however, remains elusive. Here, we demonstrate that Sf3b1K700E alone is insufficient to induce malignant transformation of the murine pancreas, but that it increases aggressiveness of PDAC if it co-occurs with mutated KRAS and p53. We further show that Sf3b1K700E already plays a role during early stages of pancreatic tumor progression and reduces the expression of TGF-β1-responsive epithelial-mesenchymal transition (EMT) genes. Moreover, we found that SF3B1K700E confers resistance to TGF-β1-induced cell death in pancreatic organoids and cell lines, partly mediated through aberrant splicing of Map3k7. Overall, our findings demonstrate that SF3B1K700E acts as an oncogenic driver in PDAC, and suggest that it promotes the progression of early stage tumors by impeding the cellular response to tumor suppressive effects of TGF-β.

Cancer cell-intrinsic mechanisms driving acquired immune tolerance

Immune evasion is a hallmark of cancer, enabling tumors to survive contact with the host immune system and evade the cycle of immune recognition and destruction. Here, we review the current understanding of the cancer cell-intrinsic factors driving immune evasion. We focus on T cells as key effectors of anti-cancer immunity and argue that cancer cells evade immune destruction by gaining control over pathways that usually serve to maintain physiological tolerance to self. Using this framework, we place recent mechanistic advances in the understanding of cancer immune evasion into broad categories of control over T cell localization, antigen recognition, and acquisition of optimal effector function. We discuss the redundancy in the pathways involved and identify knowledge gaps that must be overcome to better target immune evasion, including the need for better, routinely available tools that incorporate the growing understanding of evasion mechanisms to stratify patients for therapy and trials.

OutSplice: A Novel Tool for the Identification of Tumor-Specific Alternative Splicing Events

Protein variation that occurs during alternative splicing has been shown to play a major role in disease onset and oncogenesis. Due to this, we have developed OutSplice, a user-friendly algorithm to classify splicing outliers in tumor samples compared to a distribution of normal samples. Several tools have previously been developed to help uncover splicing events, each coming with varying methodologies, complexities, and features that can make it difficult for a new researcher to use or to determine which tool they should be using. Therefore, we benchmarked several algorithms to determine which may be best for a particular user's needs and demonstrate how OutSplice differs from these methodologies. We find that despite detecting a lower number of genes with significant aberrant events, OutSplice is able to identify those that are biologically impactful. Additionally, we identify 17 genes that contain significant splicing alterations in tumor tissue that were discovered across at least 5 of the tested algorithms, making them good candidates for future studies. Overall, researchers should consider a combined use of OutSplice with other splicing software to help provide additional validation for aberrant splicing events and to narrow down biologically relevant events.

Functional role of SAP18 protein: From transcriptional repression to splicing regulation

Sin3 associated protein 18 (SAP18) is an evolutionary conserved protein, originally discovered in a complex with the transcriptional regulatory protein, Sin3. Subsequent investigations revealed SAP18 as an integral splicing component of the exon junction complex (EJC)-associated apoptosis-and splicing-associated protein (ASAP)/PNN-RNPS1-SAP18 (PSAP) complex. In association with Sin3, SAP18 contributes toward transcriptional repression of genes implicated in embryonic development, stress response, human immunodeficiency virus type 1 replication, and tumorigenesis. As a part of EJC, SAP18 mediates alternative splicing events and suppresses the cryptic splice sites present within flanking regions of exon-exon junctions. In this review, we provide a thorough discussion on SAP18, focussing on its conserved dual role in transcriptional regulation and messenger RNA splicing. Recent research on the involvement of SAP18 in the emergence of cancer and human disorders has also been highlighted. The potential of SAP18 as a therapeutic target is also discussed in these recent studies, particularly related to malignancies of the myeloid lineage.

EXPANSION: a webserver to explore the functional consequences of protein-coding alternative splice variants in cancer genomics

Summary

EXPANSION (https://expansion.bioinfolab.sns.it/) is an integrated web-server to explore the functional consequences of protein-coding alternative splice variants. We combined information from Differentially Expressed (DE) protein-coding transcripts from cancer genomics, together with domain architecture, protein interaction network, and gene enrichment analysis to provide an easy-to-interpret view of the effects of protein-coding splice variants. We retrieved all the protein-coding Ensembl transcripts and mapped Interpro domains and post-translational modifications on canonical sequences to identify functionally relevant splicing events. We also retrieved isoform-specific protein-protein interactions and binding regions from IntAct to uncover isoform-specific functions via gene-set over-representation analysis. Through EXPANSION, users can analyze precalculated or user-inputted DE transcript datasets, to easily gain functional insights on any protein spliceform of interest.

Availability and Implementation

EXPANSION is freely available at http://expansion.bioinfolab.sns.it/. The code of the scripts used for EXPASION is available at: https://github.com/raimondilab/expansion. Datasets associated to this resource are available at the following URL: https://doi.org/10.5281/zenodo.8229120. The web-server was developed using Apache2 (https://https.apache.org/) and Flask (v2.0.2) (http://flask.pocoo.org/) for the web frontend and for the internal pipeline to handle back-end processes. We additionally used the following Python and JavaScript libraries at both back- and front-ends: D3 (v4), jQuery (v3.2.1), DataTables (v2.3.2), biopython (v1.79), gprofiler-officia l(v1.0.0), Mysql-connector-python (v8.0.31). To construct the API, Fast API library (v0.95.1) was used.

MkcDBGAS: a reference-free approach to identify comprehensive alternative splicing events in a transcriptome

Alternative splicing (AS) is an essential post-transcriptional mechanism that regulates many biological processes. However, identifying comprehensive types of AS events without guidance from a reference genome is still a challenge. Here, we proposed a novel method, MkcDBGAS, to identify all seven types of AS events using transcriptome alone, without a reference genome. MkcDBGAS, modeled by full-length transcripts of human and Arabidopsis thaliana, consists of three modules. In the first module, MkcDBGAS, for the first time, uses a colored de Bruijn graph with dynamic- and mixed- kmers to identify bubbles generated by AS with precision higher than 98.17% and detect AS types overlooked by other tools. In the second module, to further classify types of AS, MkcDBGAS added the motifs of exons to construct the feature matrix followed by the XGBoost-based classifier with the accuracy of classification greater than 93.40%, which outperformed other widely used machine learning models and the state-of-the-art methods. Highly scalable, MkcDBGAS performed well when applied to Iso-Seq data of Amborella and transcriptome of mouse. In the third module, MkcDBGAS provides the analysis of differential splicing across multiple biological conditions when RNA-sequencing data is available. MkcDBGAS is the first accurate and scalable method for detecting all seven types of AS events using the transcriptome alone, which will greatly empower the studies of AS in a wider field.

Neoantigen identification: Technological advances and challenges

Neoantigens have emerged as promising targets for cutting-edge immunotherapies, such as cancer vaccines and adoptive cell therapy. These neoantigens are unique to tumors and arise exclusively from somatic mutations or non-genomic aberrations in tumor proteins. They encompass a wide range of alterations, including genomic mutations, post-transcriptomic variants, and viral oncoproteins. With the advancements in technology, the identification of immunogenic neoantigens has seen rapid progress, raising new opportunities for enhancing their clinical significance. Prediction of neoantigens necessitates the acquisition of high-quality samples and sequencing data, followed by mutation calling. Subsequently, the pipeline involves integrating various tools that can predict the expression, processing, binding, and recognition potential of neoantigens. However, the continuous improvement of computational tools is constrained by the availability of datasets which contain validated immunogenic neoantigens. This review article aims to provide a comprehensive summary of the current knowledge as well as limitations in neoantigen prediction and validation. Additionally, it delves into the origin and biological role of neoantigens, offering a deeper understanding of their significance in the field of cancer immunotherapy. This article thus seeks to contribute to the ongoing efforts to harness neoantigens as powerful weapons in the fight against cancer.

Distinctive interactomes of RNA polymerase II phosphorylation during different stages of transcription

During eukaryotic transcription, RNA polymerase II undergoes dynamic post-translational modifications on the C-terminal domain (CTD) of the largest subunit, generating an information-rich PTM landscape that transcriptional regulators bind. The phosphorylation of Ser5 and Ser2 of CTD heptad occurs spatiotemporally with the transcriptional stages, recruiting different transcriptional regulators to Pol II. To delineate the protein interactomes at different transcriptional stages, we reconstructed phosphorylation patterns of the CTD at Ser5 and Ser2 in vitro. Our results showed that distinct protein interactomes are recruited to RNA polymerase II at different stages of transcription by the phosphorylation of Ser2 and Ser5 of the CTD heptads. In particular, we characterized calcium homeostasis endoplasmic reticulum protein (CHERP) as a regulator bound by phospho-Ser2 heptad. Pol II association with CHERP recruits an accessory splicing complex whose loss results in broad changes in alternative splicing events. Our results shed light on the PTM-coded recruitment process that coordinates transcription.

Cas13d-mediated isoform-specific RNA knockdown with a unified computational and experimental toolbox

Alternative splicing is an essential mechanism for diversifying proteins, in which mature RNA isoforms produce proteins with potentially distinct functions. Two major challenges in characterizing the cellular function of isoforms are the lack of experimental methods to specifically and efficiently modulate isoform expression and computational tools for complex experimental design. To address these gaps, we developed and methodically tested a strategy which pairs the RNA-targeting CRISPR/Cas13d system with guide RNAs that span exon-exon junctions in the mature RNA. We performed a high-throughput essentiality screen, quantitative RT-PCR assays, and PacBio long read sequencing to affirm our ability to specifically target and robustly knockdown individual RNA isoforms. In parallel, we provide computational tools for experimental design and screen analysis. Considering all possible splice junctions annotated in GENCODE for multi-isoform genes and our gRNA efficacy predictions, we estimate that our junction-centric strategy can uniquely target up to 89% of human RNA isoforms, including 50,066 protein-coding and 11,415 lncRNA isoforms. Importantly, this specificity spans all splicing and transcriptional events, including exon skipping and inclusion, alternative 5' and 3' splice sites, and alternative starts and ends.

A twin UGUA motif directs the balance between gene isoforms through CFIm and the mTORC1 signaling pathway

Alternative polyadenylation (APA) generates mRNA isoforms and diversifies gene expression. Here we report the discovery that the mTORC1 signaling pathway balances the expression of two Trim9/TRIM9 isoforms through APA regulation in human and mouse. We showed that CFIm components, CPSF6 and NUDT21, promote the short Trim9/TRIM9 isoform (Trim9-S/TRIM9-S) expression. In addition, we identified an evolutionarily conserved twin UGUA motif, UGUAYUGUA, in TRIM9-S polyadenylation site (PAS) that is critical for its regulation by CPSF6. We found additional CPSF6-regulated PASs with similar twin UGUA motifs in human and experimentally validated the twin UGUA motif functionality in BMPR1B, MOB4, and BRD4-L. Importantly, we showed that inserting a twin UGUA motif into a heterologous PAS was sufficient to confer regulation by CPSF6 and mTORC1. Our study reveals an evolutionarily conserved mechanism to regulate gene isoform expression by mTORC1 and implicates possible gene isoform imbalance in cancer and neurological disorders with mTORC1 pathway dysregulation.

The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes

Most cancer types exhibit aberrant transcriptional activity, including derepression of retrotransposable elements (RTEs). However, the degree, specificity and potential consequences of RTE transcriptional activation may differ substantially among cancer types and subtypes. Representing one extreme of the spectrum, we characterize the transcriptional activity of RTEs in cohorts of esophageal adenocarcinoma (EAC) and its precursor Barrett's esophagus (BE) from the OCCAMS (Oesophageal Cancer Clinical and Molecular Stratification) consortium, and from TCGA (The Cancer Genome Atlas). We found exceptionally high RTE inclusion in the EAC transcriptome, driven primarily by transcription of genes incorporating intronic or adjacent RTEs, rather than by autonomous RTE transcription. Nevertheless, numerous chimeric transcripts straddling RTEs and genes, and transcripts from stand-alone RTEs, particularly KLF5- and SOX9-controlled HERVH proviruses, were overexpressed specifically in EAC. Notably, incomplete mRNA splicing and EAC-characteristic intronic RTE inclusion was mirrored by relative loss of the respective fully-spliced, functional mRNA isoforms, consistent with compromised cellular fitness. Defective RNA splicing was linked with strong transcriptional activation of a HERVH provirus on Chr Xp22.32 and defined EAC subtypes with distinct molecular features and prognosis. Our study defines distinguishable RTE transcriptional profiles of EAC, reflecting distinct underlying processes and prognosis, thus providing a framework for targeted studies.

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.

Genetic pathways regulating the longitudinal acquisition of cocaine self-administration in a panel of inbred and recombinant inbred mice

To identify addiction genes, we evaluate intravenous self-administration of cocaine or saline in 84 inbred and recombinant inbred mouse strains over 10 days. We integrate the behavior data with brain RNA-seq data from 41 strains. The self-administration of cocaine and that of saline are genetically distinct. We maximize power to map loci for cocaine intake by using a linear mixed model to account for this longitudinal phenotype while correcting for population structure. A total of 15 unique significant loci are identified in the genome-wide association study. A transcriptome-wide association study highlights the Trpv2 ion channel as a key locus for cocaine self-administration as well as identifying 17 additional genes, including Arhgef26, Slc18b1, and Slco5a1. We find numerous instances where alternate splice site selection or RNA editing altered transcript abundance. Our work emphasizes the importance of Trpv2, an ionotropic cannabinoid receptor, for the response to cocaine.

MEN1 is a regulator of alternative splicing and prevents R-loop-induced genome instability through suppression of RNA polymerase II elongation

The fidelity of alternative splicing (AS) patterns is essential for growth development and cell fate determination. However, the scope of the molecular switches that regulate AS remains largely unexplored. Here we show that MEN1 is a previously unknown splicing regulatory factor. MEN1 deletion resulted in reprogramming of AS patterns in mouse lung tissue and human lung cancer cells, suggesting that MEN1 has a general function in regulating alternative precursor mRNA splicing. MEN1 altered exon skipping and the abundance of mRNA splicing isoforms of certain genes with suboptimal splice sites. Chromatin immunoprecipitation and chromosome walking assays revealed that MEN1 favored the accumulation of RNA polymerase II (Pol II) in regions encoding variant exons. Our data suggest that MEN1 regulates AS by slowing the Pol II elongation rate and that defects in these processes trigger R-loop formation, DNA damage accumulation and genome instability. Furthermore, we identified 28 MEN1-regulated exon-skipping events in lung cancer cells that were closely correlated with survival in patients with lung adenocarcinoma, and MEN1 deficiency sensitized lung cancer cells to splicing inhibitors. Collectively, these findings led to the identification of a novel biological role for menin in maintaining AS homeostasis and link this role to the regulation of cancer cell behavior.

Proteogenomic data and resources for pan-cancer analysis

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

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.

SRSF3/AMOTL1 splicing axis promotes the tumorigenesis of nasopharyngeal carcinoma through regulating the nucleus translocation of YAP1

Dysregulation of serine/arginine splicing factors (SRSFs) and abnormal alternative splicing (AS) have been widely implicated in various cancers but scarcely investigated in nasopharyngeal carcinoma (NPC). Here we examine the expression of 12 classical SRSFs between 87 NPC and 10 control samples, revealing a significant upregulation of SRSF3 and its association with worse prognosis in NPC. Functional assays demonstrate that SRSF3 exerts an oncogenic function in NPC progression. Transcriptome analysis reveals 1,934 SRSF3-regulated AS events in genes related to cell cycle and mRNA metabolism. Among these events, we verify the generation of a long isoform of AMOTL1 (AMOTL1-L) through a direct bond of the SRSF3 RRM domain with the exon 12 of AMOTL1 to promote exon inclusion. Functional studies also reveal that AMOTL1-L promotes the proliferation and migration of NPC cells, while AMOTL1-S does not. Furthermore, overexpression of AMOTL1-L, but not -S, significantly rescues the inhibitory effects of SRSF3 knockdown. Additionally, compared with AMOTL1-S, AMOTL1-L has a localization preference in the intracellular than the cell membrane, leading to a more robust interaction with YAP1 to promote nucleus translocation. Our findings identify SRSF3/AMOTL1 as a novel alternative splicing axis with pivotal roles in NPC development, which could serve as promising prognostic biomarkers and therapeutic targets for NPC.

Surmounting Cancer Drug Resistance: New Perspective on RNA-Binding Proteins

RNA-binding proteins (RBPs), being pivotal elements in both physiological and pathological processes, possess the ability to directly impact RNA, thereby exerting a profound influence on cellular life. Furthermore, the dysregulation of RBPs not only induces alterations in the expression levels of genes associated with cancer but also impairs the occurrence of post-transcriptional regulatory mechanisms. Consequently, these circumstances can give rise to aberrations in cellular processes, ultimately resulting in alterations within the proteome. An aberrant proteome can disrupt the equilibrium between oncogenes and tumor suppressor genes, promoting cancer progression. Given their significant role in modulating gene expression and post-transcriptional regulation, directing therapeutic interventions towards RBPs represents a viable strategy for combating drug resistance in cancer treatment. RBPs possess significant potential as diagnostic and prognostic markers for diverse cancer types. Gaining comprehensive insights into the structure and functionality of RBPs, along with delving deeper into the molecular mechanisms underlying RBPs in tumor drug resistance, can enhance cancer treatment strategies and augment the prognostic outcomes for individuals afflicted with cancer.

Structure prediction of novel isoforms from uveal melanoma by AlphaFold

Alternative splicing is an important mechanism that enhances protein functional diversity. To date, our understanding of alternative splicing variants has been based on mRNA transcript data, but due to the difficulty in predicting protein structures, protein tertiary structures have been largely unexplored. However, with the release of AlphaFold, which predicts three-dimensional models of proteins, this challenge is rapidly being overcome. Here, we present a dataset of 315 predicted structures of abnormal isoforms in 18 uveal melanoma patients based on second- and third-generation transcriptome-sequencing data. This information comprises a high-quality set of structural data on recurrent aberrant isoforms that can be used in multiple types of studies, from those aimed at revealing potential therapeutic targets to those aimed at recognizing of cancer neoantigens at the atomic level.

SF3B1 hotspot mutations confer sensitivity to PARP inhibition by eliciting a defective replication stress response

SF3B1 hotspot mutations are associated with a poor prognosis in several tumor types and lead to global disruption of canonical splicing. Through synthetic lethal drug screens, we identify that SF3B1 mutant (SF3B1MUT) cells are selectively sensitive to poly (ADP-ribose) polymerase inhibitors (PARPi), independent of hotspot mutation and tumor site. SF3B1MUT cells display a defective response to PARPi-induced replication stress that occurs via downregulation of the cyclin-dependent kinase 2 interacting protein (CINP), leading to increased replication fork origin firing and loss of phosphorylated CHK1 (pCHK1; S317) induction. This results in subsequent failure to resolve DNA replication intermediates and G2/M cell cycle arrest. These defects are rescued through CINP overexpression, or further targeted by a combination of ataxia-telangiectasia mutated and PARP inhibition. In vivo, PARPi produce profound antitumor effects in multiple SF3B1MUT cancer models and eliminate distant metastases. These data provide the rationale for testing the clinical efficacy of PARPi in a biomarker-driven, homologous recombination proficient, patient population.

The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer

Although recent efforts have led to the development of highly effective androgen receptor (AR)-directed therapies for the treatment of advanced prostate cancer, a significant subset of patients will progress with resistant disease including AR-negative tumors that display neuroendocrine features [neuroendocrine prostate cancer (NEPC)]. On the basis of RNA sequencing (RNA-seq) data from a clinical cohort of tissue from benign prostate, locally advanced prostate cancer, metastatic castration-resistant prostate cancer and NEPC, we developed a multi-step bioinformatics pipeline to identify NEPC-specific, overexpressed gene transcripts that encode cell surface proteins. This included the identification of known NEPC surface protein CEACAM5 as well as other potentially targetable proteins (e.g., HMMR and CESLR3). We further showed that cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) knockdown results in reduced NEPC tumor cell proliferation and migration in vitro. We provide in vivo data including laser capture microdissection followed by RNA-seq data supporting a causal role of CELSR3 in the development and/or maintenance of the phenotype associated with NEPC. Finally, we provide initial data that suggests CELSR3 is a target for T-cell redirection therapeutics. Further work is now needed to fully evaluate the utility of targeting CELSR3 with T-cell redirection or other similar therapeutics as a potential new strategy for patients with NEPC.

Significance

The development of effective treatment for patients with NEPC remains an unmet clinical need. We have identified specific surface proteins, including CELSR3, that may serve as novel biomarkers or therapeutic targets for NEPC.

Investigating Open Reading Frames in Known and Novel Transcripts using ORFanage

ORFanage is a system designed to assign open reading frames (ORFs) to known and novel gene transcripts while maximizing similarity to annotated proteins. The primary intended use of ORFanage is the identification of ORFs in the assembled results of RNA sequencing experiments, a capability that most transcriptome assembly methods do not have. Our experiments demonstrate how ORFanage can be used to find novel protein variants in RNA-seq datasets, and to improve the annotations of ORFs in tens of thousands of transcript models in the human annotation databases. Through its implementation of a highly accurate and efficient pseudo-alignment algorithm, ORFanage is substantially faster than other ORF annotation methods, enabling its application to very large datasets. When used to analyze transcriptome assemblies, ORFanage can aid in the separation of signal from transcriptional noise and the identification of likely functional transcript variants, ultimately advancing our understanding of biology and medicine.

Alternative Splicing of lncRNAs From SNHG Family Alters snoRNA Expression and Induces Chemoresistance in Hepatoblastoma

BACKGROUND & AIMS

Hepatoblastoma (HB) is a common pediatric malignant liver tumor that is characterized by a low level of genetic mutations. Alternative splicing (AS) has been shown to be closely associated with cancer progression, especially in tumors with a low mutational burden. However, the role of AS in HB remains unknown.

METHODS

Transcriptome sequencing was performed on 5 pairs of HB tissues and matched non-tumor tissues to delineate the AS landscape in HB. AS events were validated in 92 samples from 46 patients. RNA pull-down and RNA immunoprecipitation assays were carried out to identify splicing factors that regulate the AS of small nucleolar RNA host genes (SNHG). Patient-derived organoids (PDOs) were established to investigate the role of the splicing factor polyadenylate-binding nuclear protein 1 (PABPN1).

RESULTS

This study uncovered aberrant alternative splicing in HB, including lncRNAs from SNHG family that undergo intron retention in HB. Further investigations revealed that PABPN1, a significantly upregulated RNA binding protein, interacts with splicing machinery in HB, inducing the intron retention of these SNHG RNAs and the downregulation of intronic small nucleolar RNAs (snoRNAs). Functionally, PABPN1 acts as an oncofetal splicing regulator in HB by promoting cell proliferation and DNA damage repair via inducing the intron retention of SNHG19. Knock-down of PABPN1 increases the cisplatin sensitivity of HB PDOs.

CONCLUSIONS

Our findings revealed the role of intron retention in regulating snoRNA expression in hepatoblastoma, explained detailed regulatory mechanism between PABPN1 and the intron retention of SNHG RNAs, and provided insight into the development of new HB treatment options.

Comprehensive analysis of neoantigens derived from structural variation across whole genomes from 2528 tumors

BACKGROUND

Neoantigens are critical for anti-tumor immunity and have been long-envisioned as promising therapeutic targets. However, current neoantigen analyses mostly focus on single nucleotide variations (SNVs) and indel mutations and seldom consider structural variations (SVs) that are also prevalent in cancer.

RESULTS

Here, we develop a computational method termed NeoSV, which incorporates SV annotation, protein fragmentation, and MHC binding prediction together, to predict SV-derived neoantigens. Analysis of 2528 whole genomes reveals that SVs significantly contribute to the neoantigen repertoire in both quantity and quality. Whereas most neoantigens are patient-specific, shared neoantigens are identified with high occurrence rates in breast, ovarian, and gastrointestinal cancers. We observe extensive immunoediting on SV-derived neoantigens, especially on clonal events, which suggests their immunogenic potential. We also demonstrate that genomic alteration-related neoantigen burden, which integrates SV-derived neoantigens, depicts the tumor-immune interplay better than tumor neoantigen burden and may improve patient selection for immunotherapy.

CONCLUSIONS

Our study fills the gap in the current neoantigen repertoire and provides a valuable resource for cancer vaccine development.

Energy stress-induced circZFR enhances oxidative phosphorylation in lung adenocarcinoma via regulating alternative splicing

BACKGROUND

Circular RNAs (circRNAs) contribute to multiple biological functions and are also involved in pathological conditions such as cancer. However, the role of circRNAs in metabolic reprogramming, especially upon energy stress in lung adenocarcinoma (LUAD), remains largely unknown.

METHODS

Energy stress-induced circRNA was screened by circRNA profiling and glucose deprivation assays. RNA-seq, real-time cell analyzer system (RTCA) and measurement of oxygen consumption rate (OCR) were performed to explore the biological functions of circZFR in LUAD. The underlying mechanisms were investigated using circRNA pull-down, RNA immunoprecipitation, immunoprecipitation and bioinformatics analysis of alternative splicing. Clinical implications of circZFR were assessed in 92 pairs of LUAD tissues and adjacent non-tumor tissues, validated in established patient-derived tumor xenograft (PDTX) model.

RESULTS

CircZFR is induced by glucose deprivation and is significantly upregulated in LUAD compared to adjacent non-tumor tissues, enhancing oxidative phosphorylation (OXPHOS) for adaptation to energy stress. CircZFR is strongly associated with higher T stage and poor prognosis in patients with LUAD. Mechanistically, circZFR protects heterogeneous nuclear ribonucleoprotein L-like (HNRNPLL) from degradation by ubiquitination to regulate alternative splicing, such as myosin IB (MYO1B), and subsequently activates the AKT-mTOR pathway to facilitate OXPHOS.

CONCLUSION

Our study provides new insights into the role of circRNAs in anticancer metabolic therapies and expands our understanding of alternative splicing.

Targeting CD44 Variant 5 with an Antibody-Drug Conjugate Is an Effective Therapeutic Strategy for Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is the second most frequent type of primary liver cancer. ICC is among the deadliest malignancies, highlighting that novel treatments are urgently needed. Studies have shown that CD44 variant isoforms, rather than the CD44 standard isoform, are selectively expressed in ICC cells, providing an opportunity for the development of an antibody-drug conjugate (ADC)-based targeted therapeutic strategy. In this study, we observed the specific expression of CD44 variant 5 (CD44v5) in ICC tumors. CD44v5 protein was expressed on the surface of most ICC tumors (103 of 155). A CD44v5-targeted ADC, H1D8-DC (H1D8-drug conjugate), was developed that comprises a humanized anti-CD44v5 mAb conjugated to the microtubule inhibitor monomethyl auristatin E (MMAE) via a cleavable valine-citrulline-based linker. H1D8-DC exhibited efficient antigen binding and internalization in cells expressing CD44v5 on the cell surface. Because of the high expression of cathepsin B in ICC cells, the drug was preferentially released in cancer cells but not in normal cells, thus inducing potent cytotoxicity at picomolar concentrations. In vivo studies showed that H1D8-DC was effective against CD44v5-positive ICC cells and induced tumor regression in patient-derived xenograft models, whereas no significant adverse toxicities were observed. These data demonstrate that CD44v5 is a bona fide target in ICC and provide a rationale for the clinical investigation of a CD44v5-targeted ADC-based approach.

SIGNIFICANCE

Elevated expression of CD44 variant 5 in intrahepatic cholangiocarcinoma confers a targetable vulnerability using the newly developed antibody-drug conjugate H1D8-DC, which induces potent growth suppressive effects without significant toxicity.

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.

Counting pseudoalignments to novel splicing events

MOTIVATION

Alternative splicing (AS) of introns from pre-mRNA produces diverse sets of transcripts across cell types and tissues, but is also dysregulated in many diseases. Alignment-free computational methods have greatly accelerated the quantification of mRNA transcripts from short RNA-seq reads, but they inherently rely on a catalog of known transcripts and might miss novel, disease-specific splicing events. By contrast, alignment of reads to the genome can effectively identify novel exonic segments and introns. Event-based methods then count how many reads align to predefined features. However, an alignment is more expensive to compute and constitutes a bottleneck in many AS analysis methods.

RESULTS

Here, we propose fortuna, a method that guesses novel combinations of annotated splice sites to create transcript fragments. It then pseudoaligns reads to fragments using kallisto and efficiently derives counts of the most elementary splicing units from kallisto's equivalence classes. These counts can be directly used for AS analysis or summarized to larger units as used by other widely applied methods. In experiments on synthetic and real data, fortuna was around 7× faster than traditional align and count approaches, and was able to analyze almost 300 million reads in just 15 min when using four threads. It mapped reads containing mismatches more accurately across novel junctions and found more reads supporting aberrant splicing events in patients with autism spectrum disorder than existing methods. We further used fortuna to identify novel, tissue-specific splicing events in Drosophila.

AVAILABILITY AND IMPLEMENTATION

fortuna source code is available at https://github.com/canzarlab/fortuna.

Therapeutic Targeting of RNA Splicing in Cancer

RNA splicing is a key regulatory step in the proper control of gene expression. It is a highly dynamic process orchestrated by the spliceosome, a macro-molecular machinery that consists of protein and RNA components. The dysregulation of RNA splicing has been observed in many human pathologies ranging from neurodegenerative diseases to cancer. The recent identification of recurrent mutations in the core components of the spliceosome in hematologic malignancies has advanced our knowledge of how splicing alterations contribute to disease pathogenesis. This review article will discuss our current understanding of how aberrant RNA splicing regulation drives tumor initiation and progression. We will also review current therapeutic modalities and highlight emerging technologies designed to target RNA splicing for cancer treatment.

Targeting pre-mRNA splicing in cancers: roles, inhibitors, and therapeutic opportunities

Accumulating evidence has indicated that pre-mRNA splicing plays critical roles in a variety of physiological processes, including development of multiple diseases. In particular, alternative splicing is profoundly involved in cancer progression through abnormal expression or mutation of splicing factors. Small-molecule splicing modulators have recently attracted considerable attention as a novel class of cancer therapeutics, and several splicing modulators are currently being developed for the treatment of patients with various cancers and are in the clinical trial stage. Novel molecular mechanisms modulating alternative splicing have proven to be effective for treating cancer cells resistant to conventional anticancer drugs. Furthermore, molecular mechanism-based combination strategies and patient stratification strategies for cancer treatment targeting pre-mRNA splicing must be considered for cancer therapy in the future. This review summarizes recent progress in the relationship between druggable splicing-related molecules and cancer, highlights small-molecule splicing modulators, and discusses future perspectives of splicing modulation for personalized and combination therapies in cancer treatment.

The Integrative Studies on the Functional A-to-I RNA Editing Events in Human Cancers

Adenosine-to-inosine (A-to-I) RNA editing, constituting nearly 90% of all RNA editing events in humans, has been reported to contribute to the tumorigenesis in diverse cancers. However, the comprehensive map for functional A-to-I RNA editing events in cancers is still insufficient. To fill this gap, we systematically and intensively analyzed multiple tumorigenic mechanisms of A-to-I RNA editing events in samples across 33 cancer types from The Cancer Genome Atlas. For individual candidate among ∼ 1,500,000 quantified RNA editing events, we performed diverse types of downstream functional annotations. Finally, we identified 24,236 potentially functional A-to-I RNA editing events, including the cases in APOL1, IGFBP3, GRIA2, BLCAP, and miR-589-3p. These events might play crucial roles in the scenarios of tumorigenesis, due to their tumor-related editing frequencies or probable effects on altered expression profiles, protein functions, splicing patterns, and microRNA regulations of tumor genes. Our functional A-to-I RNA editing events (https://ccsm.uth.edu/CAeditome/) will help better understand the cancer pathology from the A-to-I RNA editing aspect.

From words to complete phrases: insight into single-cell isoforms using short and long reads

The profiling of gene expression patterns to glean biological insights from single cells has become commonplace over the last few years. However, this approach overlooks the transcript contents that can differ between individual cells and cell populations. In this review, we describe early work in the field of single-cell short-read sequencing as well as full-length isoforms from single cells. We then describe recent work in single-cell long-read sequencing wherein some transcript elements have been observed to work in tandem. Based on earlier work in bulk tissue, we motivate the study of combination patterns of other RNA variables. Given that we are still blind to some aspects of isoform biology, we suggest possible future avenues such as CRISPR screens which can further illuminate the function of RNA variables in distinct cell populations.

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.