A comprehensive characterization of cis-acting splicing-associated variants in human cancer

Relevance of mutation-derived neoantigens and non-classical antigens for anticancer therapies

Efficacy of cancer immunotherapies relies on correct recognition of tumor antigens by lymphocytes, eliciting thus functional responses capable of eliminating tumor cells. Therefore, important efforts have been carried out in antigen identification, with the aim of understanding mechanisms of response to immunotherapy and to design safer and more efficient strategies. In addition to classical tumor-associated antigens identified during the last decades, implementation of next-generation sequencing methodologies is enabling the identification of neoantigens (neoAgs) arising from mutations, leading to the development of new neoAg-directed therapies. Moreover, there are numerous non-classical tumor antigens originated from other sources and identified by new methodologies. Here, we review the relevance of neoAgs in different immunotherapies and the results obtained by applying neoAg-based strategies. In addition, the different types of non-classical tumor antigens and the best approaches for their identification are described. This will help to increase the spectrum of targetable molecules useful in cancer immunotherapies.

The Neo-Open Reading Frame Peptides That Comprise the Tumor Framome Are a Rich Source of Neoantigens for Cancer Immunotherapy

Identification of immunogenic cancer neoantigens as targets for therapy is challenging. Here, we integrate the whole-genome and long-read transcript sequencing of cancers to identify the collection of neo-open reading frame peptides (NOP) expressed in tumors. We termed this collection of NOPs the tumor framome. NOPs represent tumor-specific peptides that are different from wild-type proteins and may be strongly immunogenic. We describe a class of hidden NOPs that derive from structural genomic variants involving an upstream protein coding gene driving expression and translation of noncoding regions of the genome downstream of a rearrangement breakpoint, i.e., where no gene annotation or evidence for transcription exists. The entire collection of NOPs represents a vast number of possible neoantigens particularly in tumors with many structural genomic variants and a low number of missense mutations. We show that NOPs are immunogenic and epitopes derived from NOPs can bind to MHC class I molecules. Finally, we provide evidence for the presence of memory T cells specific for hidden NOPs in peripheral blood from a patient with lung cancer. This work highlights NOPs as a major source of possible neoantigens for personalized cancer immunotherapy and provides a rationale for analyzing the complete cancer genome and transcriptome as a basis for the detection of NOPs.

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

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

Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes

Innovations in sequencing technology have led to the discovery of novel mutations that cause inherited diseases. However, many patients with suspected genetic diseases remain undiagnosed. Long-read sequencing technologies are expected to significantly improve the diagnostic rate by overcoming the limitations of short-read sequencing. In addition, Oxford Nanopore Technologies (ONT) offers adaptive sampling and computationally driven target enrichment technology. This enables more affordable intensive analysis of target gene regions compared to standard non-selective long-read sequencing. In this study, we developed an efficient computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) and evaluated it through application to 33 genomes collected from suspected hereditary cancer patients. Our workflow can identify single nucleotide variants with nearly the same accuracy as the short-read platform and elucidate complex forms of structural variations. We also newly identified several SINE-R/VNTR/Alu (SVA) elements affecting the APC gene in two patients with familial adenomatous polyposis, as well as their sites of origin. In addition, we demonstrated that off-target reads from adaptive sampling, which is typically discarded, can be effectively used to accurately genotype common single-nucleotide polymorphisms (SNPs) across the entire genome, enabling the calculation of a polygenic risk score. Furthermore, we identified allele-specific MLH1 promoter hypermethylation in a Lynch syndrome patient. In summary, our workflow with TAS-LRS can simultaneously capture monogenic risk variants including complex structural variations, polygenic background as well as epigenetic alterations, and will be an efficient platform for genetic disease research and diagnosis.

Subclonal accumulation of immune escape mechanisms in microsatellite instability-high colorectal cancers

BACKGROUND

Intratumor heterogeneity (ITH) in microsatellite instability-high (MSI-H) colorectal cancer (CRC) has been poorly studied. We aimed to clarify how the ITH of MSI-H CRCs is generated in cancer evolution and how immune selective pressure affects ITH.

METHODS

We reanalyzed public whole-exome sequencing data on 246 MSI-H CRCs. In addition, we performed a multi-region analysis from 6 MSI-H CRCs. To verify the process of subclonal immune escape accumulation, a novel computational model of cancer evolution under immune pressure was developed.

RESULTS

Our analysis presented the enrichment of functional genomic alterations in antigen-presentation machinery (APM). Associative analysis of neoantigens indicated the generation of immune escape mechanisms via HLA alterations. Multiregion analysis revealed the clonal acquisition of driver mutations and subclonal accumulation of APM defects in MSI-H CRCs. Examination of variant allele frequencies demonstrated that subclonal mutations tend to be subjected to selective sweep. Computational simulations of tumour progression with the interaction of immune cells successfully verified the subclonal accumulation of immune escape mutations and suggested the efficacy of early initiation of an immune checkpoint inhibitor (ICI) -based treatment.

CONCLUSIONS

Our results demonstrate the heterogeneous acquisition of immune escape mechanisms in MSI-H CRCs by Darwinian selection, providing novel insights into ICI-based treatment strategies.

Precise characterization of somatic complex structural variations from tumor/control paired long-read sequencing data with nanomonsv

We present our novel software, nanomonsv, for detecting somatic structural variations (SVs) using tumor and matched control long-read sequencing data with a single-base resolution. The current version of nanomonsv includes two detection modules, Canonical SV module, and Single breakend SV module. Using tumor/control paired long-read sequencing data from three cancer and their matched lymphoblastoid lines, we demonstrate that Canonical SV module can identify somatic SVs that can be captured by short-read technologies with higher precision and recall than existing methods. In addition, we have developed a workflow to classify mobile element insertions while elucidating their in-depth properties, such as 5' truncations, internal inversions, as well as source sites for 3' transductions. Furthermore, Single breakend SV module enables the detection of complex SVs that can only be identified by long-reads, such as SVs involving highly-repetitive centromeric sequences, and LINE1- and virus-mediated rearrangements. In summary, our approaches applied to cancer long-read sequencing data can reveal various features of somatic SVs and will lead to a better understanding of mutational processes and functional consequences of somatic SVs.

Introme accurately predicts the impact of coding and noncoding variants on gene splicing, with clinical applications

Predicting the impact of coding and noncoding variants on splicing is challenging, particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing splice prediction tools are complementary but knowing which to use for each splicing context remains difficult. Here, we describe Introme, which uses machine learning to integrate predictions from several splice detection tools, additional splicing rules, and gene architecture features to comprehensively evaluate the likelihood of a variant impacting splicing. Through extensive benchmarking across 21,000 splice-altering variants, Introme outperformed all tools (auPRC: 0.98) for the detection of clinically significant splice variants. Introme is available at https://github.com/CCICB/introme .

Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53, CDKN2A, and B2M, and other genes.

Multiancestry genomic and transcriptomic analysis of gastric cancer

Gastric cancer is among the most common malignancies worldwide, characterized by geographical, epidemiological and histological heterogeneity. Here, we report an extensive, multiancestral landscape of driver events in gastric cancer, involving 1,335 cases. Seventy-seven significantly mutated genes (SMGs) were identified, including ARHGAP5 and TRIM49C. We also identified subtype-specific drivers, including PIGR and SOX9, which were enriched in the diffuse subtype of the disease. SMGs also varied according to Epstein-Barr virus infection status and ancestry. Non-protein-truncating CDH1 mutations, which are characterized by in-frame splicing alterations, targeted localized extracellular domains and uniquely occurred in sporadic diffuse-type cases. In patients with gastric cancer with East Asian ancestry, our data suggested a link between alcohol consumption or metabolism and the development of RHOA mutations. Moreover, mutations with potential roles in immune evasion were identified. Overall, these data provide comprehensive insights into the molecular landscape of gastric cancer across various subtypes and ancestries.

Aberrant splicing in human cancer: An RNA structural code point of view

Alternative splicing represents an essential process that occurs widely in eukaryotes. In humans, most genes undergo alternative splicing to ensure transcriptome and proteome diversity reflecting their functional complexity. Over the last decade, aberrantly spliced transcripts due to mutations in cis- or trans-acting splicing regulators have been tightly associated with cancer development, largely drawing scientific attention. Although a plethora of single proteins, ribonucleoproteins, complexed RNAs, and short RNA sequences have emerged as nodal contributors to the splicing cascade, the role of RNA secondary structures in warranting splicing fidelity has been underestimated. Recent studies have leveraged the establishment of novel high-throughput methodologies and bioinformatic tools to shed light on an additional layer of splicing regulation in the context of RNA structural elements. This short review focuses on the most recent available data on splicing mechanism regulation on the basis of RNA secondary structure, emphasizing the importance of the complex RNA G-quadruplex structures (rG4s), and other specific RNA motifs identified as splicing silencers or enhancers. Moreover, it intends to provide knowledge on newly established techniques that allow the identification of RNA structural elements and highlight the potential to develop new RNA-oriented therapeutic strategies against cancer.

The Role of the Exonic lncRNA PRKDC-210 in Transcription Regulation

In recent years, long noncoding RNAs (lncRNAs) have received increasing attention and have been reported to be associated with various genetic abnormalities. However, the functions of many lncRNAs, including those of long exonic noncoding RNAs (lencRNAs), have not yet been elucidated. Here, we used a novel tethering luciferase assay to analyze the transcriptional regulatory functions of five lencRNAs that are upregulated in cancer. We found that the lencRNA PRKDC-210 interacts with MED12, a component of the CDK8 complex, to regulate the transcription of several genes. The transcriptional activation ability of PRKDC-210 was abolished in siRNA-treated CDK8-depleted cells. We also confirmed the enrichment of PRKDC-210 on RNA polymerase II. RNA-seq analysis of cells in which PRKDC-210 or PRKDC mRNA was knocked down using antisense oligonucleotides revealed that PRKDC-210 can affect the expression levels of genes related to fatty acid metabolism. Finally, we used a ChIRP assay to examine PRKDC-210-enriched sites in the genome. Overall, our findings demonstrate that the lencRNA PRKDC-210 promotes transcription through the CDK8 complex pathway at the transcription initiation site. We propose that PRKDC-210 can affect the transcription of adjacent genes after its transcription and splicing.

Integrating machine learning to construct aberrant alternative splicing event related classifiers to predict prognosis and immunotherapy response in patients with hepatocellular carcinoma

Introduction: In hepatocellular carcinoma (HCC), alternative splicing (AS) is related to tumor invasion and progression.

Methods: We used HCC data from a public database to identify AS subtypes by unsupervised clustering. Through feature analysis of different splicing subtypes and acquisition of the differential alternative splicing events (DASEs) combined with enrichment analysis, the differences in several subtypes were explored, cell function studies have also demonstrated that it plays an important role in HCC.

Results: Finally, in keeping with the differences between these subtypes, DASEs identified survival-related AS times, and were used to construct risk proportional regression models. AS was found to be useful for the classification of HCC subtypes, which changed the activity of tumor-related pathways through differential splicing effects, affected the tumor microenvironment, and participated in immune reprogramming.

Conclusion: In this study, we described the clinical and molecular characteristics providing a new approach for the personalized treatment of HCC patients.

Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data

Many disease-associated genomic variants disrupt gene function through abnormal splicing. With the advancement of genomic medicine, identifying disease-associated splicing associated variants has become more important than ever. Most bioinformatics approaches to detect splicing associated variants require both genome and transcriptomic data. However, there are not many datasets where both of them are available. In this study, we develop a methodology to detect genomic variants that cause splicing changes (more specifically, intron retention), using transcriptome sequencing data alone. After evaluating its sensitivity and precision, we apply it to 230,988 transcriptome sequencing data from the publicly available repository and identified 27,049 intron retention associated variants (IRAVs). In addition, by exploring positional relationships with variants registered in existing disease databases, we extract 3,000 putative disease-associated IRAVs, which range from cancer drivers to variants linked with autosomal recessive disorders. The in-silico screening framework demonstrates the possibility of near-automatically acquiring medical knowledge, making the most of massively accumulated publicly available sequencing data. Collections of IRAVs identified in this study are available through IRAVDB (https://iravdb.io/).

This paper proposed a novel in-silico framework for automatically screening disease-related variants and applied it to over 200,000 transcriptomes, providing an example to acquire medically relevant knowledge from publicly available sequence data.

Evaluating a therapeutic window for precision medicine by integrating genomic profiles and p53 network dynamics

The response variation to anti-cancer drugs originates from complex intracellular network dynamics of cancer. Such dynamic networks present challenges to determining optimal drug targets and stratifying cancer patients for precision medicine, although several cancer genome studies provided insights into the molecular characteristics of cancer. Here, we introduce a network dynamics-based approach based on attractor landscape analysis to evaluate the therapeutic window of a drug from cancer signaling networks combined with genomic profiles. This approach allows for effective screening of drug targets to explore potential target combinations for enhancing the therapeutic window of drug responses. We also effectively stratify patients into desired/undesired response groups using critical genomic determinants, which are network-specific origins of variability to drug response, and their dominance relationship. Our methods provide a viable and quantitative framework to connect genotype information to the phenotypes of drug response with regard to network dynamics determining the therapeutic window.

Empirical prediction of variant-activated cryptic splice donors using population-based RNA-Seq data

Predicting which cryptic-donors may be activated by a splicing variant in patient DNA is notoriously difficult. Through analysis of 5145 cryptic-donors (versus 86,963 decoy-donors not used; any GT or GC), we define an empirical method predicting cryptic-donor activation with 87% sensitivity and 95% specificity. Strength (according to four algorithms) and proximity to the annotated-donor appear important determinants of cryptic-donor activation. However, other factors such as splicing regulatory elements, which are difficult to identify, play an important role and are likely responsible for current prediction inaccuracies. We find that the most frequently recurring natural mis-splicing events at each exon-intron junction, summarised over 40,233 RNA-sequencing samples (40K-RNA), predict with accuracy which cryptic-donor will be activated in rare disease. 40K-RNA provides an accurate, evidence-based method to predict variant-activated cryptic-donors in genetic disorders, assisting pathology consideration of possible consequences of a variant for the encoded protein and RNA diagnostic testing strategies.

Genetic variants affecting the consensus splicing motifs can alter binding of spliceosomal components and induce mis-splicing. Here, the authors develop a method, showing that ranking the most common recurring mis-splicing events in public RNA-Seq data can predict the activation of cryptic-donors.

Gene architecture directs splicing outcome in separate nuclear spatial regions

How the splicing machinery defines exons or introns as the spliced unit has remained a puzzle for 30 years. Here, we demonstrate that peripheral and central regions of the nucleus harbor genes with two distinct exon-intron GC content architectures that differ in the splicing outcome. Genes with low GC content exons, flanked by long introns with lower GC content, are localized in the periphery, and the exons are defined as the spliced unit. Alternative splicing of these genes results in exon skipping. In contrast, the nuclear center contains genes with a high GC content in the exons and short flanking introns. Most splicing of these genes occurs via intron definition, and aberrant splicing leads to intron retention. We demonstrate that the nuclear periphery and center generate different environments for the regulation of alternative splicing and that two sets of splicing factors form discrete regulatory subnetworks for the two gene architectures. Our study connects 3D genome organization and splicing, thus demonstrating that exon and intron definition modes of splicing occur in different nuclear regions.

The variant rs77559646 associated with aggressive prostate cancer disrupts ANO7 mRNA splicing and protein expression

Prostate cancer is among the most common cancers in men, with a large fraction of the individual risk attributable to heritable factors. A majority of the diagnosed cases does not lead to a lethal disease, and hence biological markers that can distinguish between indolent and fatal forms of the disease are of great importance for guiding treatment decisions. Although over 300 genetic variants are known to be associated with prostate cancer risk, few have been associated with the risk of an aggressive disease. One such variant is rs77559646 located in ANO7. This variant has a dual function. It constitutes a missense mutation in the short isoform of ANO7 and a splice region mutation in full-length ANO7. In this study, we have analyzed the impact of the variant allele of rs77559646 on ANO7 mRNA splicing using a minigene splicing assay and by performing splicing analysis with the tools IRFinder (intron retention finder), rMATS (replicate multivariate analysis of transcript splicing) and LeafCutter on RNA sequencing data from prostate tissue of six rs77559646 variant allele carriers and 43 non-carriers. The results revealed a severe disruption of ANO7 mRNA splicing in rs77559646 variant allele carriers. Immunohistochemical analysis of prostate samples from patients homozygous for the rs77559646 variant allele demonstrated a loss of apically localized ANO7 protein. Our study is the first to provide a mechanistic explanation for the impact of a prostate cancer risk SNP on ANO7 protein production. Furthermore, the rs77559646 variant is the first known germline loss-of-function mutation described for ANO7. We suggest that loss of ANO7 contributes to prostate cancer progression.

Impact of Alternative Splicing Variants on Liver Cancer Biology

Simple Summary

Among the top ten deadly solid tumors are the two most frequent liver cancers, hepatocellular carcinoma, and intrahepatic cholangiocarcinoma, whose development and malignancy are favored by multifactorial conditions, which include aberrant maturation of pre-mRNA due to abnormalities in either the machinery involved in the splicing, i.e., the spliceosome and associated factors, or the nucleotide sequences of essential sites for the exon recognition process. As a consequence of cancer-associated aberrant splicing in hepatocytes- and cholangiocytes-derived cancer cells, abnormal proteins are synthesized. They contribute to the dysregulated proliferation and eventually transformation of these cells to phenotypes with enhanced invasiveness, migration, and multidrug resistance, which contributes to the poor prognosis that characterizes these liver cancers.

Abstract

The two most frequent primary cancers affecting the liver, whose incidence is growing worldwide, are hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), which are among the five most lethal solid tumors with meager 5-year survival rates. The common difficulty in most cases to reach an early diagnosis, the aggressive invasiveness of both tumors, and the lack of favorable response to pharmacotherapy, either classical chemotherapy or modern targeted therapy, account for the poor outcome of these patients. Alternative splicing (AS) during pre-mRNA maturation results in changes that might affect proteins involved in different aspects of cancer biology, such as cell cycle dysregulation, cytoskeleton disorganization, migration, and adhesion, which favors carcinogenesis, tumor promotion, and progression, allowing cancer cells to escape from pharmacological treatments. Reasons accounting for cancer-associated aberrant splicing include mutations that create or disrupt splicing sites or splicing enhancers or silencers, abnormal expression of splicing factors, and impaired signaling pathways affecting the activity of the splicing machinery. Here we have reviewed the available information regarding the impact of AS on liver carcinogenesis and the development of malignant characteristics of HCC and iCCA, whose understanding is required to develop novel therapeutical approaches aimed at manipulating the phenotype of cancer cells.

A Deep Exon Cryptic Splice Site Promotes Aberrant Intron Retention in a Von Willebrand Disease Patient

A translationally silent single nucleotide mutation in exon 44 (E44) of the von Willebrand factor (VWF) gene is associated with inefficient removal of intron 44 in a von Willebrand disease (VWD) patient. This intron retention (IR) event was previously attributed to reordered E44 secondary structure that sequesters the normal splice donor site. We propose an alternative mechanism: the mutation introduces a cryptic splice donor site that interferes with the function of the annotated site to favor IR. We evaluated both models using minigene splicing reporters engineered to vary in secondary structure and/or cryptic splice site content. Analysis of splicing efficiency in transfected K562 cells suggested that the mutation-generated cryptic splice site in E44 was sufficient to induce substantial IR. Mutations predicted to vary secondary structure at the annotated site also had modest effects on IR and shifted the balance of residual splicing between the cryptic site and annotated site, supporting competition among the sites. Further studies demonstrated that introduction of cryptic splice donor motifs at other positions in E44 did not promote IR, indicating that interference with the annotated site is context dependent. We conclude that mutant deep exon splice sites can interfere with proper splicing by inducing IR.

Probing Isoform Switching Events in Various Cancer Types: Lessons From Pan-Cancer Studies

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. In cancer, alternative splicing is frequently disturbed, leading to changes in the expression of alternatively spliced protein isoforms. Advances in sequencing technologies and analysis methods led to new insights into the extent and functional impact of disturbed alternative splicing events. In this review, we give a brief overview of the molecular mechanisms driving alternative splicing, highlight the function of alternative splicing in healthy tissues and describe how alternative splicing is disrupted in cancer. We summarize current available computational tools for analyzing differential transcript usage, isoform switching events, and the pathogenic impact of cancer-specific splicing events. Finally, the strategies of three recent pan-cancer studies on isoform switching events are compared. Their methodological similarities and discrepancies are highlighted and lessons learned from the comparison are listed. We hope that our assessment will lead to new and more robust methods for cancer-specific transcript detection and help to produce more accurate functional impact predictions of isoform switching events.

Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Although transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood. Short-read transcript sequencing has prevented researchers from directly exploring full-length transcripts, forcing them to focus on individual splice sites. Here, we develop a pipeline for Multi-Sample long-read Transcriptome Assembly (MuSTA), which enables construction of a transcriptome from long-read sequence data. Using the constructed transcriptome as a reference, we analyze RNA extracted from 22 clinical breast cancer specimens. We identify a comprehensive set of subtype-specific and differentially used isoforms, which extended our knowledge of isoform regulation to unannotated isoforms including a short form TNS3. We also find that the exon-intron structure of fusion transcripts depends on their genomic context, and we identify double-hop fusion transcripts that are transcribed from complex structural rearrangements. For example, a double-hop fusion results in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and is thought to protect fetus from maternal rejection; expression is elevated in several TCGA samples with ERVFRD-1 fusions. Our analyses provide direct evidence that full-length transcript sequencing of clinical samples can add to our understanding of cancer biology and genomics in general.

Comprehensive characterization of somatic variants associated with intronic polyadenylation in human cancers

Somatic single nucleotide variants (SNVs) in cancer genome affect gene expression through various mechanisms depending on their genomic location. While somatic SNVs near canonical splice sites have been reported to cause abnormal splicing of cancer-related genes, whether these SNVs can affect gene expression through other mechanisms remains an open question. Here, we analyzed RNA sequencing and exome data from 4,998 cancer patients covering ten cancer types and identified 152 somatic SNVs near splice sites that were associated with abnormal intronic polyadenylation (IPA). IPA-associated somatic variants favored the localization near the donor splice sites compared to the acceptor splice sites. A proportion of SNV-associated IPA events overlapped with premature cleavage and polyadenylation events triggered by U1 small nuclear ribonucleoproteins (snRNP) inhibition. GC content, intron length and polyadenylation signal were three genomic features that differentiated between SNV-associated IPA and intron retention. Notably, IPA-associated SNVs were enriched in tumor suppressor genes (TSGs), including the well-known TSGs such as PTEN and CDH1 with recurrent SNV-associated IPA events. Minigene assay confirmed that SNVs from PTEN, CDH1, VEGFA, GRHL2, CUL3 and WWC2 could lead to IPA. This work reveals that IPA acts as a novel mechanism explaining the functional consequence of somatic SNVs in human cancer.

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.

Depressed Colorectal Cancer: A New Paradigm in Early Colorectal Cancer

INTRODUCTION:

In contrast to most colorectal carcinomas arising from pedunculated or sessile protruded adenomas, submucosal-invasive (pT1) colorectal carcinoma exhibiting a depressed surface (hereinafter, “depressed colorectal carcinoma,” identified by means of high-definition endoscopy) is considered to be derived from depressed precursors. We hypothesized that depressed colorectal neoplasms have unique clinicopathological features different that are different from those of protruded and flat colorectal neoplasms.

METHODS:

We classified 27,129 colorectal neoplasms (909 pT1 carcinomas and 26,220 adenomas) resected between 2001 and 2017 into depressed (211 carcinomas and 109 adenomas), flat (304 carcinomas and 11,246 adenomas), and protruded subtypes (394 carcinomas and 14,865 adenomas) and compared their clinicopathological features. As exploratory analyses of pT1 carcinomas, we conducted whole-exome sequencing for 19 depressed and 8 protruded subtypes and RNA sequencing for 8 depressed and 8 protruded subtypes.

RESULTS:

pT1 carcinomas were more common in depressed lesions (66%) than in protruded (2.6%) and flat lesions (2.6%) (P < 0.001). Compared with nondepressed pT1 carcinomas, depressed pT1 carcinomas were positively correlated with lymphovascular invasion, tumor budding, and massive submucosal invasion and inversely correlated with the presence of an adenoma component (all P < 0.001). Depressed adenomas were more likely to contain high-grade dysplasia than nondepressed adenomas (49% vs 11%, P < 0.001). A KRAS mutation was observed only in one of the 19 depressed pT1 carcinomas. Relative to protruded carcinomas, depressed carcinomas generally exhibited higher expression of genes related to angiogenesis and epithelial-mesenchymal transition.

DISCUSSION:

Depressed colorectal neoplasms may harbor a unique combination of malignant histopathological phenotypes and molecular features.

Transcript Identification Through Long-Read Sequencing

RNA-seq using long-read sequencing, such as nanopore and SMRT (Single Molecule, Real-Time) sequencing, enabled the identification of the full-length structure of RNA molecules. Several tools for long-read RNA-seq were developed recently. In this section, we introduce an analytical pipeline of long-read RNA-seq for isoform identification and the estimation of expression levels using minimap2, TranscriptClean, and TALON. We applied this pipeline to the public direct RNA-seq data of the HAP1 and HEK293 cell lines to identify transcript isoforms which can be detected only using long-read RNA-seq data.

Genetic and non-genetic clonal diversity in cancer evolution

The observation and analysis of intra-tumour heterogeneity (ITH), particularly in genomic studies, has advanced our understanding of the evolutionary forces that shape cancer growth and development. However, only a subset of the variation observed in a single tumour will have an impact on cancer evolution, highlighting the need to distinguish between functional and non-functional ITH. Emerging studies highlight a role for the cancer epigenome, transcriptome and immune microenvironment in functional ITH. Here, we consider the importance of both genetic and non-genetic ITH and their role in tumour evolution, and present the rationale for a broad research focus beyond the cancer genome. Systems-biology analytical approaches will be necessary to outline the scale and importance of functional ITH. By allowing a deeper understanding of tumour evolution this will, in time, encourage development of novel therapies and improve outcomes for patients.

A prometastatic splicing program regulated by SNRPA1 interactions with structured RNA elements

Aberrant alternative splicing is a hallmark of cancer, yet the underlying regulatory programs that control this process remain largely unknown. Here, we report a systematic effort to decipher the RNA structural code that shapes pathological splicing during breast cancer metastasis. We discovered a previously unknown structural splicing enhancer that is enriched near cassette exons with increased inclusion in highly metastatic cells. We show that the spliceosomal protein small nuclear ribonucleoprotein polypeptide A' (SNRPA1) interacts with these enhancers to promote cassette exon inclusion. This interaction enhances metastatic lung colonization and cancer cell invasion, in part through SNRPA1-mediated regulation of PLEC alternative splicing, which can be counteracted by splicing modulating morpholinos. Our findings establish a noncanonical regulatory role for SNRPA1 as a prometastatic splicing enhancer in breast cancer.

Biology of the mRNA Splicing Machinery and Its Dysregulation in Cancer Providing Therapeutic Opportunities

Dysregulation of messenger RNA (mRNA) processing—in particular mRNA splicing—is a hallmark of cancer. Compared to normal cells, cancer cells frequently present aberrant mRNA splicing, which promotes cancer progression and treatment resistance. This hallmark provides opportunities for developing new targeted cancer treatments. Splicing of precursor mRNA into mature mRNA is executed by a dynamic complex of proteins and small RNAs called the spliceosome. Spliceosomes are part of the supraspliceosome, a macromolecular structure where all co-transcriptional mRNA processing activities in the cell nucleus are coordinated. Here we review the biology of the mRNA splicing machinery in the context of other mRNA processing activities in the supraspliceosome and present current knowledge of its dysregulation in lung cancer. In addition, we review investigations to discover therapeutic targets in the spliceosome and give an overview of inhibitors and modulators of the mRNA splicing process identified so far. Together, this provides insight into the value of targeting the spliceosome as a possible new treatment for lung cancer.

Comprehensive characterization of alternative splicing in renal cell carcinoma

Irregular splicing was associated with tumor formation and progression in renal cell carcinoma (RCC) and many other cancers. By using splicing data in the TCGA SpliceSeq database, RCC subtype classification was performed and splicing features and their correlations with clinical course, genetic variants, splicing factors, pathways activation and immune heterogeneity were systemically analyzed. In this research, alternative splicing was found useful for classifying RCC subtypes. Splicing inefficiency with upregulated intron retention and cassette exon was associated with advanced conditions and unfavorable overall survival of patients with RCC. Splicing characteristics like splice site strength, guanine and cytosine content and exon length may be important factors disrupting splicing balance in RCC. Other than cis-acting and trans-acting regulation, alternative splicing also differed in races and tissue types and is also affected by mutation conditions, pathway settings and the response to environmental changes. Severe irregular splicing in tumor not only indicated terrible intra-cellular homeostasis, but also changed the activity of cancer-associated pathways by different splicing effects including isoforms switching and expression regulation. Moreover, irregular splicing and splicing-associated antigens were involved in immune reprograming and formation of immunosuppressive tumor microenvironment. Overall, we have described several clinical and molecular features in RCC splicing subtypes, which may be important for patient management and targeting treatment.

Comprehensive characterisation of intronic mis-splicing mutations in human cancers

Previous studies studying mis-splicing mutations were based on exome data and thus our current knowledge is largely limited to exons and the canonical splice sites. To comprehensively characterise intronic mis-splicing mutations, we analysed 1134 pan-cancer whole genomes and transcriptomes together with 3022 normal control samples. The ratio-based splicing analysis resulted in 678 somatic intronic mutations, with 46% residing in deep introns. Among the 309 deep intronic single nucleotide variants, 245 altered core splicing codes, with 38% activating cryptic splice sites, 12% activating cryptic polypyrimidine tracts, and 36% and 12% disrupting authentic polypyrimidine tracts and branchpoints, respectively. All the intronic cryptic splice sites were created at pre-existing GT/AG dinucleotides or by GC-to-GT conversion. Notably, 85 deep intronic mutations indicated gain of splicing enhancers or loss of splicing silencers. We found that 64 tumour suppressors were affected by intronic mutations and blood cancers showed higher proportion of deep intronic mutations. In particular, a telomere maintenance gene, POT1, was recurrently mis-spliced by deep intronic mutations in blood cancers. We validated a pseudoexon activation involving a splicing silencer in POT1 by CRISPR/Cas9. Our results shed light on previously unappreciated mechanisms by which noncoding mutations acting on splicing codes in deep introns contribute to tumourigenesis.

Bioinformatics workflows for clinical applications in precision oncology

High-throughput molecular profiling of tumors is a fundamental aspect of precision oncology, enabling the identification of genomic alterations that can be targeted therapeutically. In this context, a patient is matched to a specific drug or therapy based on the tumor's underlying genetic driver events rather than the histologic classification. This approach requires extensive bioinformatics methodology and workflows, including raw sequencing data processing and quality control, variant calling and annotation, integration of different molecular data types, visualization and finally reporting the data to physicians, cancer researchers and pharmacologists in a format that is readily interpretable for clinical decision making. This review comprises a broad overview of these bioinformatics aspects and discusses the multiple analytical, technical and interpretational challenges that remain to efficiently translate molecular findings into personalized treatment recommendations.

Discovery of driver non-coding splice-site-creating mutations in cancer

Non-coding mutations can create splice sites, however the true extent of how such somatic non-coding mutations affect RNA splicing are largely unexplored. Here we use the MiSplice pipeline to analyze 783 cancer cases with WGS data and 9494 cases with WES data, discovering 562 non-coding mutations that lead to splicing alterations. Notably, most of these mutations create new exons. Introns associated with new exon creation are significantly larger than the genome-wide average intron size. We find that some mutation-induced splicing alterations are located in genes important in tumorigenesis (ATRX, BCOR, CDKN2B, MAP3K1, MAP3K4, MDM2, SMAD4, STK11, TP53 etc.), often leading to truncated proteins and affecting gene expression. The pattern emerging from these exon-creating mutations suggests that splice sites created by non-coding mutations interact with pre-existing potential splice sites that originally lacked a suitable splicing pair to induce new exon formation. Our study suggests the importance of investigating biological and clinical consequences of noncoding splice-inducing mutations that were previously neglected by conventional annotation pipelines. MiSplice will be useful for automatically annotating the splicing impact of coding and non-coding mutations in future large-scale analyses.

Holding on to Junk Bonds: Intron Retention in Cancer and Therapy

Intron retention (IR) in cancer was for a long time overlooked by the scientific community, as it was previously considered to be an artifact of a dysfunctional spliceosome. Technological advancements made in the last decade offer unique opportunities to explore the role of IR as a widespread phenomenon that contributes to the transcriptional diversity of many cancers. Numerous studies in cancer have shed light on dysregulation of cellular mechanisms that lead to aberrant and pathologic IR. IR is not merely a mechanism of gene regulation, but rather it can mediate cancer pathogenesis and therapeutic resistance in various human diseases. The burden of IR in cancer is governed by perturbations to mechanisms known to regulate this phenomenon and include epigenetic variation, mutations within the gene body, and splicing factor dysregulation. This review summarizes possible causes for aberrant IR and discusses the role of IR in therapy or as a consequence of disease treatment. As neoepitopes originating from retained introns can be presented on the cancer cell surface, the development of personalized cancer vaccines based on IR-derived neoepitopes should be considered. Ultimately, a deeper comprehension about the origins and consequences of aberrant IR may aid in the development of such personalized cancer vaccines.

Spliceogen: an integrative, scalable tool for the discovery of splice-altering variants

MOTIVATION

In silico prediction tools are essential for identifying variants which create or disrupt cis-splicing motifs. However, there are limited options for genome-scale discovery of splice-altering variants.

RESULTS

We have developed Spliceogen, a highly scalable pipeline integrating predictions from some of the individually best performing models for splice motif prediction: MaxEntScan, GeneSplicer, ESRseq and Branchpointer.

AVAILABILITY AND IMPLEMENTATION

Spliceogen is available as a command line tool which accepts VCF/BED inputs and handles both single nucleotide variants (SNVs) and indels (https://github.com/VCCRI/Spliceogen). SNV databases with prediction scores are also available, covering all possible SNVs at all genomic positions within all Gencode-annotated multi-exon transcripts.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Diagnostic utility of integrated analysis of exome and transcriptome: Successful diagnosis of Au-Kline syndrome in a patient with submucous cleft palate, scaphocephaly, and intellectual disabilities

Background

A weakness of exome analysis lies in inability to characterize aberrant splicing other than those involving consensus donor‐acceptor sequence. To overcome this limitation, we developed a novel analytic method SAVNet that combines transcriptome and exome analysis which enabled the successful detection of carriers of splicing variants in the disease‐causing genes of autosomal recessive disorders within a normal cohort. However, the clinical utility of the SAVNet analysis in delineating splicing defects in patients without a diagnosis has yet to be documented.

Method

We performed SAVNet analysis using the integrated analysis of exome and transcriptome analysis from the peripheral blood of the patient. The patient is an undiagnosed Japanese female patient with submucous cleft palate, scaphocephaly and intellectual disability with no words at 8 years of age. Dysmorphic features included a long face, a short palpebral fissure, thick lips with an open month, premaxillary hypoplasia, a depressed nasal bridge, and satyr ears.

Result

A SAVNet analysis showed that a heterozygous intronic variant located at the −10 position of exon 5 of the HNRNPK gene on chromosome 9 created a new splice acceptor sequence “ag” and led to the incorporation of 9 intronic nucleotides into the coding sequence. The mutant protein would have three extra amino acid residues, Leu‐Leu‐Gln, inserted within the critical KH domain. The patient was diagnosed as having recently delineated Au–Kline syndrome, which is characterized by cleft palate, craniosynostosis, and intellectual disability.

Conclusion

The successful molecular diagnosis of the presently reported patient illustrates the diagnostic utility of the SAVNet analysis as an innovative way of implementing an integrated exome‐transcriptome analysis in clinical settings.

The Role of RNA Splicing Factors in Cancer: Regulation of Viral and Human Gene Expression in Human Papillomavirus-Related Cervical Cancer

The spliceosomal complex components, together with the heterogeneous nuclear ribonucleoproteins (hnRNPs) and serine/arginine-rich (SR) proteins, regulate the process of constitutive and alternative splicing, the latter leading to the production of mRNA isoforms coding multiple proteins from a single pre-mRNA molecule. The expression of splicing factors is frequently deregulated in different cancer types causing the generation of oncogenic proteins involved in cancer hallmarks. Cervical cancer is caused by persistent infection with oncogenic human papillomaviruses (HPVs) and constitutive expression of viral oncogenes. The aberrant activity of hnRNPs and SR proteins in cervical neoplasia has been shown to trigger the production of oncoproteins through the processing of pre-mRNA transcripts either derived from human genes or HPV genomes. Indeed, hnRNP and SR splicing factors have been shown to regulate the production of viral oncoprotein isoforms necessary for the completion of viral life cycle and for cell transformation. Target-therapy strategies against hnRNPs and SR proteins, causing simultaneous reduction of oncogenic factors and inhibition of HPV replication, are under development. In this review, we describe the current knowledge of the functional link between RNA splicing factors and deregulated cellular as well as viral RNA maturation in cervical cancer and the opportunity of new therapeutic strategies.

Genomic basis for RNA alterations in cancer

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

An Unusually Short Latent Period of Therapy-Related Myeloid Neoplasm Harboring a Rare MLL-EP300 Rearrangement: Case Report and Literature Review

Therapy-related myeloid neoplasm (t-MN) is a late and lethal complication induced by chemotherapy and/or radiation therapy. Hematological malignancy is one of the most common primary diseases in patients with t-MN. However, the occurrence of t-MN in adult T-cell leukemia/lymphoma (ATL) patients is rarely reported, possibly due to the dismal prognosis of ATL per se. Here, we report a 62-year-old female who developed t-MN only three months after the completion of conventional chemotherapy and anti-CCR4 antibody for ATL acute type. The patient presented with persistent fever and monocytosis without any evidence of infectious diseases. Bone marrow examinations revealed chronic myelomonocytic leukemia-like disease with a chromosomal translocation of t(11;22)(q23;q13) as a solo cytogenetic abnormality, resulting in the diagnosis of t-MN. Next-generation sequencing analysis identified a rare chimeric transcript, MLL-EP300, without any additional somatic mutations. Although the patient underwent allogenic hematopoietic stem cell transplantation, she died of viral encephalomyelitis at 7 months after diagnosis of t-MN. Since recent therapeutic advances have extended the survival of patients with ATL, further evaluation of the long-term risks of developing t-MN in these patients is warranted.

Effectiveness of integrated interpretation of exome and corresponding transcriptome data for detecting splicing variants of genes associated with autosomal recessive disorders

Purpose

Part of the weakness of exome analysis lies in the inability to detect aberrant splicing. An evaluation of the post-splicing mRNA sequence concurrently with genomic variants could improve the diagnostic rate. We aimed to investigate publicly available exome sequencing data and its matching transcriptomics data of phenotypically normal individuals to identify alternatively spliced variants from known genes associated with autosomal recessive disorders under the premise that some of the subjects could be carriers of such disorders.

Methods

Aberrant splicing events and their triggering genomic variants were detected with the aid of Bayesian network method “SAVNet” which was originally developed for cancer genomics.

Results

Forty aberrant splicing events including exon skipping, the creation of a new splice site, and the use of a cryptic splice site in response to the disruption of the authentic site were detected in 1916 genes among 31 of the 179 subjects from the 1000 Genomes Project. The predicted effects on proteins were either frameshift mutations (30) or large in-frame insertions or deletions (10). Five missense mutations and 2 silent mutations were reinterpreted as triggering major changes in transcript sequences. The detection rate of provisionally truncating pathogenic variants increased by 19%, compared with a conventional exome analysis.

Conclusion

The coupling interpretation of exome and transcriptome data enhances the performance of conventional exome analyses through the proper interpretation of intronic variants that are outside of the GT/AG splicing consensus sequences and also allows the reinterpretation of “missense” or “silent” substitutions that can indeed have drastic effects on splicing.

Splicing regulatory factors in breast cancer hallmarks and disease progression

By regulating transcript isoform expression levels, alternative splicing provides an additional layer of protein control. Recent studies show evidence that cancer cells use different splicing events to fulfill their requirements in order to develop, progress and metastasize. However, there has been less attention for the role of the complex catalyzing the complicated multistep splicing reaction: the spliceosome. The spliceosome consists of multiple sub-complexes in total comprising 244 proteins or splice factors and 5 associated RNA molecules. Here we discuss the role of splice factors in the oncogenic processes tumors cells need to fulfill their oncogenic properties (the so-called the hallmarks of cancer). Despite the fact that splice factors have been investigated only recently, they seem to play a prominent role in already five hallmarks of cancer: angiogenesis, resisting cell death, sustaining proliferation, deregulating cellular energetics and invasion and metastasis formation by affecting major signaling pathways such as epithelial-to-mesenchymal transition, the Warburg effect, DNA damage response and hormone receptor dependent proliferation. Moreover, we could relate expression of representative genes of four other hallmarks (enabling replicative mortality, genomic instability, avoiding immune destruction and evading growth suppression) to splice factor levels in human breast cancer tumors, suggesting that also these hallmarks could be regulated by splice factors. Since many splice factors are involved in multiple hallmarks of cancer, inhibiting splice factors might provide a new layer of oncogenic control and a powerful method to combat breast cancer progression.

Identification of neoantigens derived from alternative splicing and RNA modification

The acquisition of somatic mutations is the most common event in cancer. Neoantigens expressed from genes with mutations acquired during carcinogenesis can be tumor-specific. Since the immune system recognizes tumor-specific peptides, they are potential targets for personalized neoantigen-based immunotherapy. However, the discovery of druggable neoantigens remains challenging, suggesting that a deeper understanding of the mechanism of neoantigen generation and better strategies to identify them will be required to realize the promise of neoantigen-based immunotherapy. Alternative splicing and RNA editing events are emerging mechanisms leading to neoantigen production. In this review, we outline recent work involving the large-scale screening of neoantigens produced by alternative splicing and RNA editing. We also describe strategies to predict and validate neoantigens from RNA sequencing data.

Alternative splicing in lung cancer

Lung cancer has the highest mortality rate of all cancers worldwide. Lung cancer is a very heterogeneous disease that is often diagnosed at later stages which have a poor prognosis. Aberrant alternative splicing patterns found in lung cancer contribute to important cell functions. These include changes in splicing for the BCL2L1, MDM2, MDM4, NUMB and MET genes during lung tumourigenesis, to affect pathways involved in apoptosis, cell proliferation and cellular cohesion. Global analyses of RNASeq datasets suggest there may be many more potentially influential aberrant splicing events that need to be investigated in lung cancer. Changes in expression of the splicing factors that regulate alternative splicing events have also been identified in lung cancer. Of these, changes in expression of QKI, RBM4, RBM5, RBM6, RBM10 and SRSF1 proteins regulate many of the most frequently referenced aberrant splicing events in lung cancer. The expanding list of genes known to be aberrantly spliced in lung cancer along with the altered expression of splicing factors that regulate them are providing new clues as to how lung cancer develops, and how these events can be exploited for better treatment. This article is part of a Special Issue entitled: RNA structure and splicing regulation edited by Francisco Baralle, Ravindra Singh and Stefan Stamm.

Toward a clinical diagnostic pipeline for SPINK1 intronic variants

Background

The clinical significance of SPINK1 intronic variants in chronic pancreatitis has been previously assessed by various approaches including a cell culture-based full-length gene assay. A close correlation between the results of this assay and in silico splicing prediction was apparent. However, until now, a clinical diagnostic pipeline specifically designed to classify SPINK1 intronic variants accurately and efficiently has been lacking. Herein, we present just such a pipeline and explore its efficacy and potential utility in potentiating the classification of newly described SPINK1 intronic variants.

Results

We confirm a close correlation between in silico splicing prediction and results from the cell culture-based full-length gene assay in the context of three recently reported pathogenic SPINK1 intronic variants. We then integrated in silico splicing prediction and the full-length gene assay into a stepwise approach and tested its utility in the classification of two novel datasets of SPINK1 intronic variants. The first dataset comprised 16 deep intronic variants identified in 52 genetically unexplained Chinese chronic pancreatitis patients by sequencing the entire intronic sequence of the SPINK1 gene. The second dataset comprised five novel rare proximal intronic variants identified through the routine analysis of the SPINK1 gene in French pancreatitis patients. Employing a minor allele frequency of > 5% as a population frequency filter, 6 of the 16 deep intronic variants were immediately classified as benign. In silico prediction of the remaining ten deep intronic variants and the five rare proximal intronic variants with respect to their likely impact on splice site selection suggested that only one proximal intronic variant, c.194 + 5G > A, was likely to be of functional significance. Employing the cell culture-based full-length gene assay, we functionally analyzed c.194 + 5G > A, together with seven predicted non-functional variants, thereby validating their predicted effects on splicing in all cases.

Conclusions

We demonstrated the accuracy and efficiency of in silico prediction in combination with the cell culture-based full-length gene assay for the classification of SPINK1 intronic variants. Based upon these findings, we propose an operational pipeline for classifying SPINK1 intronic variants in the clinical diagnostic setting.

Electronic supplementary material

The online version of this article (10.1186/s40246-019-0193-7) contains supplementary material, which is available to authorized users.

Using Frameshift Peptide Arrays for Cancer Neo-Antigens Screening

It has been demonstrated that DNA mutations generating neo-antigens are important for an effective immune response to tumors as evident from recent clinical studies of immune checkpoint inhibitors (ICIs). Further, it was shown that frameshift peptides (FSP) generated in tumors from insertions and deletions (INDELs) of microsatellites (MS) in coding region are a very good correlate of positive response to PD1 treatment. However, these types of DNA-sourced FSPs are infrequent in cancer. We hypothesize that tumors may also generate FSPs in transcription errors through INDELs in MS or by exon mis-splicing. Since there are a finite number of predictable sequences of such possible FSPs in the genome, we propose that peptide arrays with all possible FSPs could be used to analyze antibody reactivity to FSPs in patient sera as a FS neo-antigen screen. If this were the case it would facilitate finding common tumor neoantigens for cancer vaccines. Here we test this proposal using an array of 377 predicted FS antigens. The results of screening 9 types of dog cancer sera indicate that cancer samples had significantly higher antibody responses against FSPs than non-cancer samples. Both common reactive FSPs and cancer-type specific immune responses were detected. In addition, the protection of a common reactive FSP was tested in mouse tumor models, comparing to the non-reactive FSPs. The mouse homologs non-reactive FSPs did not offer protection in either the mouse melanoma or breast cancer models while the reactive FSP did in both models. The tumor protection was positively correlated to antibody response to the FSP. These data suggest that FSP arrays could be used for cancer neo-antigen screening.