Intron retention is a robust marker of intertumoral heterogeneity in pancreatic ductal adenocarcinoma

Exon-Skipping-Based Subtyping of Colorectal Cancers

BACKGROUND & AIMS

The identification of colorectal cancer (CRC) molecular subtypes has prognostic and potentially diagnostic value for patients, yet reliable subtyping remains unavailable in the clinic. The current consensus molecular subtype (CMS) classification in CRCs is based on complex RNA expression patterns quantified at the gene level. The clinical application of these methods, however, is challenging due to high uncertainty of single-sample classification and associated costs. Alternative splicing, which strongly contributes to transcriptome diversity, has rarely been used for tissue type classification. Here, we present an AS-based CRC subtyping framework sensitive to differential exon use that can be adapted for clinical application.

METHODS

Unsupervised clustering was used to measure the strength of association between different categories of alternative splicing and CMS. To build a classifier, the ground truth for CMS labels was derived from expression data quantified at the gene level. Feature selection was achieved through bootstrapping and L1-penalized estimation. The resulting feature space was used to construct a subtype prediction framework applicable to single and multiple samples. The performance of the models was evaluated on unseen CRCs from 2 independent sources (Indivumed, n = 129; The Cancer Genome Atlas, n = 99).

RESULTS

We developed a CRC subtype identifier based on 29 exon-skipping events that accurately classifies unseen tumors and enables more precise differentiation of subtypes characterized by distinct biological and prognostic features as compared to classifiers based on gene expression.

CONCLUSIONS

Here, we demonstrate that a small number of exon-skipping events can reliably classify CRC subtypes using individual patient specimens in a manner suitable to clinical application.

Transcriptome Responses to Different Salinity Conditions in Litoditis marina, Revealed by Long-Read Sequencing

The marine nematode Litoditis marina is widely distributed in intertidal zones around the globe, yet the mechanisms underlying its broad adaptation to salinity remain elusive. In this study, we applied ONT long-read sequencing technology to unravel the transcriptome responses to different salinity conditions in L. marina. Through ONT sequencing under 3‱, 30‱ and 60‱ salinity environments, we obtained 131.78 G clean data and 26,647 non-redundant long-read transcripts, including 6464 novel transcripts. The DEGs obtained from the current ONT lrRNA-seq were highly correlated with those identified in our previously reported Illumina short-read RNA sequencing data. When we compared the 30‱ to the 3‱ salinity condition, we found that GO terms such as oxidoreductase activity, cation transmembrane transport and ion transmembrane transport were shared between the ONT lrRNA-seq and Illumina data. Similarly, GO terms including extracellular space, structural constituents of cuticle, substrate-specific channel activity, ion transport and substrate-specific transmembrane transporter activity were shared between the ONT and Illumina data under 60‱ compared to 30‱ salinity. In addition, we found that 79 genes significantly increased, while 119 genes significantly decreased, as the salinity increased. Furthermore, through the GO enrichment analysis of 214 genes containing DAS, in 30‱ compared to 3‱ salinity, we found that GO terms such as cellular component assembly and coenzyme biosynthetic process were enriched. Additionally, we observed that GO terms such as cellular component assembly and coenzyme biosynthetic process were also enriched in 60‱ compared to 30‱ salinity. Moreover, we found that 86, 125, and 81 genes that contained DAS were also DEGs, in comparisons between 30‱ and 3‱, 60‱ and 30‱, and 60‱ and 3‱ salinity, respectively. In addition, we demonstrated the landscape of alternative polyadenylation in marine nematode under different salinity conditions This report provides several novel insights for the further study of the mechanisms by which euryhalinity formed and evolved, and it might also contribute to the investigation of salinity dynamics induced by global climate change.

Unleashing the potential of catalytic RNAs to combat mis-spliced transcripts

Human transcriptome can undergo RNA mis-splicing due to spliceopathies contributing to the increasing number of genetic diseases including muscular dystrophy (MD), Alzheimer disease (AD), Huntington disease (HD), myelodysplastic syndromes (MDS). Intron retention (IR) is a major inducer of spliceopathies where two or more introns remain in the final mature mRNA and account for many intronic expansion diseases. Potential removal of such introns for therapeutic purposes can be feasible when utilizing bioinformatics, catalytic RNAs, and nano-drug delivery systems. Overcoming delivery challenges of catalytic RNAs was discussed in this review as a future perspective highlighting the significance of utilizing synthetic biology in addition to high throughput deep sequencing and computational approaches for the treatment of mis-spliced transcripts.

DHX38 restricts chemoresistance by regulating the alternative pre-mRNA splicing of RELL2 in pancreatic ductal adenocarcinoma

Intron retention plays an important role in cancer progression and chemotherapy resistance and seems to be essential for the maintenance of genome stability in cancer. Here, our goal was to analyze the role of receptor expressed in lymphoid tissue (Relt)-like 2 (RELL2) intron 4 retention in promoting pancreatic ductal adenocarcinoma (PDAC) progression. Our results showed that intron retention (IR) occurs at the fourth intron of RELL2 transcript in gemcitabine resistant PDAC cells, however, the regulatory mechanism and the clinical implications of IR of RELL2 are unclear. Firstly, we found that RELL2 plays an anti-oncogenic role in PDAC by performing in vitro functional assays including cell proliferation, GEM cytotoxicity assay and apoptosis. Subsequently, we identified the upstream gene of RELL2, DEAH-Box Helicase 38 (DHX38), and demonstrated the direct interaction between DHX38 and RELL2 by RIP-qPCR. We also found that altered expression of DHX38 resulted in corresponding changes in intron 4 retention of RELL2. Importantly, we unveiled that overexpression of DHX38 on the basis of knocking down of the fourth intron of RELL2 resulted in an impaired intron 4 intention. Overall, our study identified a new IR site in PDAC, which could be a possible target for PDAC therapy.

Intron-Retention Neoantigen Load Predicts Favorable Prognosis in Pancreatic Cancer

PURPOSE

High tumor mutation burden (TMB) in many cancer types is associated with the production of tumor-specific neoantigens, a favorable outcome and response to immune checkpoint blockade (ICB) therapy. Besides mutation-derived neoantigens, aberrant intron retention also produces tumor neopeptides that could trigger an immune response. The relationship between intron-retention-derived tumor neoantigens (IR-neoAg) and clinical outcomes in pancreatic cancer remains uncertain. Here, we quantify IR-neoAg in pancreatic cancer and evaluate whether IR-neoAg load might serve as a biomarker for selecting patients who may benefit from ICB therapy.

METHODS

We developed a computational approach to estimate patient-specific IR-neoAg load from transcriptome data available in The Cancer Genome Atlas pancreatic cancer cohort. Associations between IR-neoAg load and patient overall survival were evaluated using Kaplan-Meier estimates and Cox regression. Differential expression of immune checkpoint and HLA-I genes was evaluated in tumors with high IR-neoAg load.

RESULTS

High IR-neoAg load predicted better overall survival in pancreatic cancer, although no association was found for TMB. IR-neoAg load remained a significant prognostic factor after adjusting for patient age, sex, tumor stage and grade, and TMB. Moreover, pancreatic tumors with both high IR-neoAg load and high HLA-I gene expression had similar gene expression profiles as other tumor types that showed response to anti-programmed cell death protein 1 therapy.

CONCLUSION

IR-neoAg load is associated with favorable survival in pancreatic cancer. These findings provide strong evidence for considering IR-neoAgs when selecting patients who might benefit from ICB therapy.

Alternative RNA splicing in tumour heterogeneity, plasticity and therapy

Alternative splicing is a process by which a single gene is able to encode multiple different protein isoforms. It is regulated by the inclusion or exclusion of introns and exons that are joined in different patterns prior to protein translation, thus enabling transcriptomic and proteomic diversity. It is now widely accepted that alternative splicing is dysregulated across nearly all cancer types. This widespread dysregulation means that nearly all cellular processes are affected - these include processes synonymous with the hallmarks of cancer - evasion of apoptosis, tissue invasion and metastasis, altered cellular metabolism, genome instability and drug resistance. Emerging evidence indicates that the dysregulation of alternative splicing also promotes a permissive environment for increased tumour heterogeneity and cellular plasticity. These are fundamental regulators of a patient's response to therapy. In this Review, we introduce the mechanisms of alternative splicing and the role of aberrant splicing in cancer, with particular focus on newfound evidence of alternative splicing promoting tumour heterogeneity, cellular plasticity and altered metabolism. We discuss recent in vivo models generated to study alternative splicing and the importance of these for understanding complex tumourigenic processes. Finally, we review the effects of alternative splicing on immune evasion, cell death and genome instability, and how targeting these might enhance therapeutic efficacy.

IRFinder-S: a comprehensive suite to discover and explore intron retention

Accurate quantification and detection of intron retention levels require specialized software. Building on our previous software, we create a suite of tools called IRFinder-S, to analyze and explore intron retention events in multiple samples. Specifically, IRFinder-S allows a better identification of true intron retention events using a convolutional neural network, allows the sharing of intron retention results between labs, integrates a dynamic database to explore and contrast available samples, and provides a tested method to detect differential levels of intron retention.

MYC- and MIZ1-Dependent Vesicular Transport of Double-Strand RNA Controls Immune Evasion in Pancreatic Ductal Adenocarcinoma

Deregulated expression of the MYC oncoprotein enables tumor cells to evade immune surveillance, but the mechanisms underlying this surveillance are poorly understood. We show here that endogenous MYC protects pancreatic ductal adenocarcinoma (PDAC) driven by KRAS^G12D and TP53^R172H from eradication by the immune system. Deletion of TANK-binding kinase 1 (TBK1) bypassed the requirement for high MYC expression. TBK1 was active due to the accumulation of double-stranded RNA (dsRNA), which was derived from inverted repetitive elements localized in introns of nuclear genes. Nuclear-derived dsRNA is packaged into extracellular vesicles and subsequently recognized by toll-like receptor 3 (TLR3) to activate TBK1 and downstream MHC class I expression in an autocrine or paracrine manner before being degraded in lysosomes. MYC suppressed loading of dsRNA onto TLR3 and its subsequent degradation via association with MIZ1. Collectively, these findings suggest that MYC and MIZ1 suppress a surveillance pathway that signals perturbances in mRNA processing to the immune system, which facilitates immune evasion in PDAC. SIGNIFICANCE: This study identifies a TBK1-dependent pathway that links dsRNA metabolism to antitumor immunity and shows that suppression of TBK1 is a critical function of MYC in pancreatic ductal adenocarcinoma.

Reboot: a straightforward approach to identify genes and splicing isoforms associated with cancer patient prognosis

Nowadays, the massive amount of data generated by modern sequencing technologies provides an unprecedented opportunity to find genes associated with cancer patient prognosis, connecting basic and translational research. However, treating high dimensionality of gene expression data and integrating it with clinical variables are major challenges to perform these analyses. Here, we present Reboot, an integrative approach to find and validate genes and transcripts (splicing isoforms) associated with cancer patient prognosis from high dimensional expression datasets. Reboot innovates by using a multivariate strategy with penalized Cox regression (LASSO method) combined with a bootstrap approach, in addition to statistical tests and plots to support the findings. Applying Reboot on data from 154 glioblastoma patients, we identified a three-gene signature (IKBIP, OSMR, PODNL1) whose increased derived risk score was significantly associated with worse patients' prognosis. Similarly, Reboot was able to find a seven-splicing isoforms signature related to worse overall survival in 177 pancreatic adenocarcinoma patients with elevated risk scores after uni- and multivariate analyses. In summary, Reboot is an efficient, intuitive and straightforward way of finding genes or splicing isoforms signatures relevant to patient prognosis, which can democratize this kind of analysis and shed light on still under-investigated cancer-related genes and splicing isoforms.

Intron retention-induced neoantigen load correlates with unfavorable prognosis in multiple myeloma

Neoantigen peptides arising from genetic alterations may serve as targets for personalized cancer vaccines and as positive predictors of response to immune checkpoint therapy. Mutations in genes regulating RNA splicing are common in hematological malignancies leading to dysregulated splicing and intron retention (IR). In this study, we investigated IR as a potential source of tumor neoantigens in multiple myeloma (MM) patients and the relationship of IR-induced neoantigens (IR-neoAg) with clinical outcomes. MM-specific IR events were identified in RNA-sequencing data from the Multiple Myeloma Research Foundation CoMMpass study after removing IR events that also occurred in normal plasma cells. We quantified the IR-neoAg load by assessing IR-induced novel peptides that were predicted to bind to major histocompatibility complex (MHC) molecules. We found that high IR-neoAg load was associated with poor overall survival in both newly diagnosed and relapsed MM patients. Further analyses revealed that poor outcome in MM patients with high IR-neoAg load was associated with high expression levels of T-cell co-inhibitory molecules and elevated interferon signaling activity. We also found that MM cells exhibiting high IR levels had lower MHC-II protein abundance and treatment of MM cells with a spliceosome inhibitor resulted in increased MHC-I protein abundance. Our findings suggest that IR-neoAg may represent a novel biomarker of MM patient clinical outcome and further that targeting RNA splicing may serve as a potential therapeutic strategy to prevent MM immune escape and promote response to checkpoint blockade.