SpliceWiz: interactive analysis and visualization of alternative splicing in R.

Alternative splicing (AS) is a crucial mechanism for regulating gene expression and isoform diversity in eukaryotes. However, the analysis and visualization of AS events from RNA sequencing data remains challenging. Most tools require a certain level of computer literacy and the available means of visualizing AS events, such as coverage and sashimi plots, have limitations and can be misleading. To address these issues, we present SpliceWiz, an R package with an interactive Shiny interface that allows easy and efficient AS analysis and visualization at scale. A novel normalization algorithm is implemented to aggregate splicing levels within sample groups, thereby allowing group differences in splicing levels to be accurately visualized. The tool also offers downstream gene ontology enrichment analysis, highlighting ASEs belonging to functional pathways of interest. SpliceWiz is optimized for speed and efficiency and introduces a new file format for coverage data storage that is more efficient than BigWig. Alignment files are processed orders of magnitude faster than other R-based AS analysis tools and on par with command-line tools. Overall, SpliceWiz streamlines AS analysis, enabling reliable identification of functionally relevant AS events for further characterization. SpliceWiz is a Bioconductor package and is also available on GitHub (https://github.com/alexchwong/SpliceWiz).

Identifying cancer driver genes in individual tumours.

Cancer is a heterogeneous disease with a strong genetic component making it suitable for precision medicine approaches aimed at identifying the underlying molecular drivers within a tumour. Large scale population-level cancer sequencing consortia have identified many actionable mutations common across both cancer types and sub-types, resulting in an increasing number of successful precision medicine programs. Nonetheless, such approaches fail to consider the effects of mutations unique to an individual patient and may miss rare driver mutations, necessitating personalised approaches to driver-gene prioritisation. One approach is to quantify the functional importance of individual mutations in a single tumour based on how they affect the expression of genes in a gene interaction network (GIN). These GIN-based approaches can be broadly divided into those that utilise an existing reference GIN and those that construct de novo patient-specific GINs. These single-tumour approaches have several limitations that likely influence their results, such as use of reference cohort data, network choice, and approaches to mathematical approximation, and more research is required to evaluate the in vitro and in vivo applicability of their predictions. This review examines the current state of the art methods that identify driver genes in single tumours with a focus on GIN-based driver prioritisation.

The application of long-read sequencing in clinical settings.

Long-read DNA sequencing technologies have been rapidly evolving in recent years, and their ability to assess large and complex regions of the genome makes them ideal for clinical applications in molecular diagnosis and therapy selection, thereby providing a valuable tool for precision medicine. In the third-generation sequencing duopoly, Oxford Nanopore Technologies and Pacific Biosciences work towards increasing the accuracy, throughput, and portability of long-read sequencing methods while trying to keep costs low. These trades have made long-read sequencing an attractive tool for use in research and clinical settings. This article provides an overview of current clinical applications and limitations of long-read sequencing and explores its potential for point-of-care testing and health care in remote settings.

A signal-seeking Phase 2 study of olaparib and durvalumab in advanced solid cancers with homologous recombination repair gene alterations.

PURPOSE: To determine the safety and efficacy of PARP plus PD-L1 inhibition (olaparib + durvalumab, O + D) in patients with advanced solid, predominantly rare cancers harbouring homologous recombination repair (HRR) defects. PATIENTS AND METHODS: In total, 48 patients were treated with O + D, 16 with BRCA1/2 alterations (group 1) and 32 with other select HRR alterations (group 2). Overall, 32 (66%) patients had rare or less common cancers. The primary objective of this single-arm Phase II trial was a progression-free survival rate at 6 months (PFS6). Post hoc exploratory analyses were conducted on archival tumour tissue and serial bloods. RESULTS: The PFS6 rate was 35% and 38% with durable objective tumour responses (OTR) in 3(19%) and 3(9%) in groups 1 and 2, respectively. Rare cancers achieving an OTR included cholangiocarcinoma, perivascular epithelioid cell (PEComa), neuroendocrine, gallbladder and endometrial cancer. O + D was safe, with five serious adverse events related to the study drug(s) in 3 (6%) patients. A higher proportion of CD38 high B cells in the blood and higher CD40 expression in tumour was prognostic of survival. CONCLUSIONS: O + D demonstrated no new toxicity concerns and yielded a clinically meaningful PFS6 rate and durable OTRs across several cancers with HRR defects, including rare cancers.

Single-cell and long-read sequencing to enhance modelling of splicing and cell-fate determination.

Single-cell sequencing technologies have revolutionised the life sciences and biomedical research. Single-cell sequencing provides high-resolution data on cell heterogeneity, allowing high-fidelity cell type identification, and lineage tracking. Computational algorithms and mathematical models have been developed to make sense of the data, compensate for errors and simulate the biological processes, which has led to breakthroughs in our understanding of cell differentiation, cell-fate determination and tissue cell composition. The development of long-read (a.k.a. third-generation) sequencing technologies has produced powerful tools for investigating alternative splicing, isoform expression (at the RNA level), genome assembly and the detection of complex structural variants (at the DNA level). In this review, we provide an overview of the recent advancements in single-cell and long-read sequencing technologies, with a particular focus on the computational algorithms that help in correcting, analysing, and interpreting the resulting data. Additionally, we review some mathematical models that use single-cell and long-read sequencing data to study cell-fate determination and alternative splicing, respectively. Moreover, we highlight the emerging opportunities in modelling cell-fate determination that result from the combination of single-cell and long-read sequencing technologies.

Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors.

The microsatellite stable/epithelial-mesenchymal transition (MSS/EMT) subtype of gastric cancer represents a highly aggressive class of tumors associated with low rates of survival and considerably high probabilities of recurrence. In the era of precision medicine, the accurate and prompt diagnosis of tumors of this subtype is of vital importance. In this study, we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify a differentially expressed co-expression module of mRNAs in EMT-type gastric tumors. Using network analysis and linear discriminant analysis, we identified mRNA motifs and microRNA-based models with strong prognostic and diagnostic relevance: three models comprised of (i) the microRNAs miR-199a-5p and miR-141-3p, (ii) EVC/EVC2/GLI3, and (iii) PDE2A/GUCY1A1/GUCY1B1 gene expression profiles distinguish EMT-type tumors from other gastric tumors with high accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.995, AUC = 0.9742, and AUC = 0.9717; respectively). Additionally, the DMD/ITGA1/CAV1 motif was identified as the top motif with consistent relevance to prognosis (hazard ratio > 3). Molecular functions of the members of the identified models highlight the central roles of MAPK, Hh, and cGMP/cAMP signaling in the pathology of the EMT subtype of gastric cancer and underscore their potential utility in precision therapeutic approaches.

Overview of Computational and Experimental Methods to Identify Tissue-Specific MicroRNA Targets.

As ubiquitous posttranscriptional regulators of gene expression, microRNAs (miRNAs) play key roles in cell physiology and function across taxa. In the last two decades, we have gained a good understanding about miRNA biogenesis pathways, modes of action, and consequences of miRNA-mediated gene regulation. More recently, research has focused on exploring causes for miRNA dysregulation, miRNA-mediated crosstalk between genes and signaling pathways, and the role of miRNAs in disease.This chapter discusses methods for the identification of miRNA-target interactions and causes for tissue-specific miRNA-target regulation. Computational approaches for predicting miRNA target sites and assessing tissue-specific target regulation are discussed. Moreover, there is an emphasis on features that affect miRNA target recognition and how high-throughput sequencing protocols can help in assessing miRNA-mediated gene regulation on a genome-wide scale. In addition, this chapter introduces some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA-target interactions.

Recent advances in cancer fusion transcript detection.

Extensive investigation of gene fusions in cancer has led to the discovery of novel biomarkers and therapeutic targets. To date, most studies have neglected chromosomal rearrangement-independent fusion transcripts and complex fusion structures such as double or triple-hop fusions, and fusion-circRNAs. In this review, we untangle fusion-related terminology and propose a classification system involving both gene and transcript fusions. We highlight the importance of RNA-level fusions and how long-read sequencing approaches can improve detection and characterization. Moreover, we discuss novel bioinformatic tools to identify fusions in long-read sequencing data and strategies to experimentally validate and functionally characterize fusion transcripts.

Towards resolution of the intron retention paradox in breast cancer.

BACKGROUND: After many years of neglect in the field of alternative splicing, the importance of intron retention (IR) in cancer has come into focus following landmark discoveries of aberrant IR patterns in cancer. Many solid and liquid tumours are associated with drastic increases in IR, and such patterns have been pursued as both biomarkers and therapeutic targets. Paradoxically, breast cancer (BrCa) is the only tumour type in which IR is reduced compared to adjacent normal breast tissue. METHODS: In this study, we have conducted a pan-cancer analysis of IR with emphasis on BrCa and its subtypes. We explored mechanisms that could cause aberrant and pathological IR and clarified why normal breast tissue has unusually high IR. RESULTS: Strikingly, we found that aberrantly decreasing IR in BrCa can be largely attributed to normal breast tissue having the highest occurrence of IR events compared to other healthy tissues. Our analyses suggest that low numbers of IR events in breast tumours are associated with poor prognosis, particularly in the luminal B subtype. Interestingly, we found that IR frequencies negatively correlate with cell proliferation in BrCa cells, i.e. rapidly dividing tumour cells have the lowest number of IR events. Aberrant RNA-binding protein expression and changes in tissue composition are among the causes of aberrantly decreasing IR in BrCa. CONCLUSIONS: Our results suggest that IR should be considered for therapeutic manipulation in BrCa patients with aberrantly low IR levels and that further work is needed to understand the cause and impact of high IR in other tumour types.

Increased chromatin accessibility facilitates intron retention in specific cell differentiation states.

Dynamic intron retention (IR) in vertebrate cells is of widespread biological importance. Aberrant IR is associated with numerous human diseases including several cancers. Despite consistent reports demonstrating that intrinsic sequence features can help introns evade splicing, conflicting findings about cell type- or condition-specific IR regulation by trans-regulatory and epigenetic mechanisms demand an unbiased and systematic analysis of IR in a controlled experimental setting. We integrated matched mRNA sequencing (mRNA-Seq), whole-genome bisulfite sequencing (WGBS), nucleosome occupancy methylome sequencing (NOMe-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq) data from primary human myeloid and lymphoid cells. Using these multi-omics data and machine learning, we trained two complementary models to determine the role of epigenetic factors in the regulation of IR in cells of the innate immune system. We show that increased chromatin accessibility, as revealed by nucleosome-free regions, contributes substantially to the retention of introns in a cell-specific manner. We also confirm that intrinsic characteristics of introns are key for them to evade splicing. This study suggests an important role for chromatin architecture in IR regulation. With an increasing appreciation that pathogenic alterations are linked to RNA processing, our findings may provide useful insights for the development of novel therapeutic approaches that target aberrant splicing.

The Role of MicroRNAs in Cancer Biology and Therapy from a Systems Biology Perspective.

Since the discovery of microRNAs (miRNAs) in Caenorhabditis elegans, our understanding of their cellular function has progressed continuously. Today, we have a good understanding of miRNA-mediated gene regulation, miRNA-mediated cross talk between genes including competing endogenous RNAs, and miRNA-mediated signaling transduction both in normal human physiology and in diseases.Besides, these noncoding RNAs have shown their value for clinical applications, especially in an oncological context. They can be used as reliable biomarkers for cancer diagnosis and prognosis and attract increasing attention as potential therapeutic targets. Many achievements made in the miRNA field are based on joint efforts from computational and molecular biologists. Systems biology approaches, which integrate computational and experimental methods, have played a fundamental role in uncovering the cellular functions of miRNAs.In this chapter, we review and discuss the role of miRNAs in oncology from a system biology perspective. We first describe biological facts about miRNA genetics and function. Next, we discuss the role of miRNAs in cancer progression and review the application of miRNAs in cancer diagnostics and therapy. Finally, we elaborate on the role that miRNAs play in cancer gene regulatory networks. Taken together, we emphasize the importance of systems biology approaches in our continued efforts to study miRNA cancer regulation.

Intron retention: importance, challenges, and opportunities.

Recent landmark discoveries have underpinned the physiological importance of intron retention (IR) across multiple domains of life and revealed an unexpected breath of functions in a large variety of biological processes. Despite significant progress in the field, some challenges remain. Once solved, opportunities will arise for discovering more functions of IR.

Prospects and challenges of cancer systems medicine: from genes to disease networks.

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

The Fusion of CLEC12A and MIR223HG Arises from a trans-Splicing Event in Normal and Transformed Human Cells.

Chimeric RNAs are often associated with chromosomal rearrangements in cancer. In addition, they are also widely detected in normal tissues, contributing to transcriptomic complexity. Despite their prevalence, little is known about the characteristics and functions of chimeric RNAs. Here, we examine the genetic structure and biological roles of CLEC12A-MIR223HG, a novel chimeric transcript produced by the fusion of the cell surface receptor CLEC12A and the miRNA-223 host gene (MIR223HG), first identified in chronic myeloid leukemia (CML) patients. Surprisingly, we observed that CLEC12A-MIR223HG is not just expressed in CML, but also in a variety of normal tissues and cell lines. CLEC12A-MIR223HG expression is elevated in pro-monocytic cells resistant to chemotherapy and during monocyte-to-macrophage differentiation. We observed that CLEC12A-MIR223HG is a product of trans-splicing rather than a chromosomal rearrangement and that transcriptional activation of CLEC12A with the CRISPR/Cas9 Synergistic Activation Mediator (SAM) system increases CLEC12A-MIR223HG expression. CLEC12A-MIR223HG translates into a chimeric protein, which largely resembles CLEC12A but harbours an altered C-type lectin domain altering key disulphide bonds. These alterations result in differences in post-translational modifications, cellular localization, and protein-protein interactions. Taken together, our observations support a possible involvement of CLEC12A-MIR223HG in the regulation of CLEC12A function. Our workflow also serves as a template to study other uncharacterized chimeric RNAs.

Structure-function relationships explain CTCF zinc finger mutation phenotypes in cancer.

CCCTC-binding factor (CTCF) plays fundamental roles in transcriptional regulation and chromatin architecture maintenance. CTCF is also a tumour suppressor frequently mutated in cancer, however, the structural and functional impact of mutations have not been examined. We performed molecular and structural characterisation of five cancer-specific CTCF missense zinc finger (ZF) mutations occurring within key intra- and inter-ZF residues. Functional characterisation of CTCF ZF mutations revealed a complete (L309P, R339W, R377H) or intermediate (R339Q) abrogation as well as an enhancement (G420D) of the anti-proliferative effects of CTCF. DNA binding at select sites was disrupted and transcriptional regulatory activities abrogated. Molecular docking and molecular dynamics confirmed that mutations in residues specifically contacting DNA bases or backbone exhibited loss of DNA binding. However, R339Q and G420D were stabilised by the formation of new primary DNA bonds, contributing to gain-of-function. Our data confirm that a spectrum of loss-, change- and gain-of-function impacts on CTCF zinc fingers are observed in cell growth regulation and gene regulatory activities. Hence, diverse cellular phenotypes of mutant CTCF are clearly explained by examining structure-function relationships.

CTCF as a regulator of alternative splicing: new tricks for an old player.

Three decades of research have established the CCCTC-binding factor (CTCF) as a ubiquitously expressed chromatin organizing factor and master regulator of gene expression. A new role for CTCF as a regulator of alternative splicing (AS) has now emerged. CTCF has been directly and indirectly linked to the modulation of AS at the individual transcript and at the transcriptome-wide level. The emerging role of CTCF-mediated regulation of AS involves diverse mechanisms; including transcriptional elongation, DNA methylation, chromatin architecture, histone modifications, and regulation of splicing factor expression and assembly. CTCF thereby appears to not only co-ordinate gene expression regulation but contributes to the modulation of transcriptomic complexity. In this review, we highlight previous discoveries regarding the role of CTCF in AS. In addition, we summarize detailed mechanisms by which CTCF mediates AS regulation. We propose opportunities for further research designed to examine the possible fate of CTCF-mediated alternatively spliced genes and associated biological consequences. CTCF has been widely acknowledged as the 'master weaver of the genome'. Given its multiple connections, further characterization of CTCF's emerging role in splicing regulation might extend its functional repertoire towards a 'conductor of the splicing orchestra'.

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.

Ctcf haploinsufficiency mediates intron retention in a tissue-specific manner.

CTCF is a master regulator of gene transcription and chromatin organisation with occupancy at thousands of DNA target sites genome-wide. While CTCF is essential for cell survival, CTCF haploinsufficiency is associated with tumour development and hypermethylation. Increasing evidence demonstrates CTCF as a key player in several mechanisms regulating alternative splicing (AS), however, the genome-wide impact of Ctcf dosage on AS has not been investigated. We examined the effect of Ctcf haploinsufficiency on gene expression and AS in five tissues from Ctcf hemizygous (Ctcf+/-) mice. Reduced Ctcf levels caused distinct tissue-specific differences in gene expression and AS in all tissues. An increase in intron retention (IR) was observed in Ctcf+/- liver and kidney. In liver, this specifically impacted genes associated with cytoskeletal organisation, splicing and metabolism. Strikingly, most differentially retained introns were short, with a high GC content and enriched in Ctcf binding sites in their proximal upstream genomic region. This study provides new insights into the effects of CTCF haploinsufficiency on organ transcriptomes and the role of CTCF in AS regulation.

Widespread Aberrant Alternative Splicing despite Molecular Remission in Chronic Myeloid Leukaemia Patients.

Vast transcriptomics and epigenomics changes are characteristic of human cancers, including leukaemia. At remission, we assume that these changes normalise so that omics-profiles resemble those of healthy individuals. However, an in-depth transcriptomic and epigenomic analysis of cancer remission has not been undertaken. A striking exemplar of targeted remission induction occurs in chronic myeloid leukaemia (CML) following tyrosine kinase inhibitor (TKI) therapy. Using RNA sequencing and whole-genome bisulfite sequencing, we profiled samples from chronic-phase CML patients at diagnosis and remission and compared these to healthy donors. Remarkably, our analyses revealed that abnormal splicing distinguishes remission samples from normal controls. This phenomenon is independent of the TKI drug used and in striking contrast to the normalisation of gene expression and DNA methylation patterns. Most remarkable are the high intron retention (IR) levels that even exceed those observed in the diagnosis samples. Increased IR affects cell cycle regulators at diagnosis and splicing regulators at remission. We show that aberrant splicing in CML is associated with reduced expression of specific splicing factors, histone modifications and reduced DNA methylation. Our results provide novel insights into the changing transcriptomic and epigenomic landscapes of CML patients during remission. The conceptually unanticipated observation of widespread aberrant alternative splicing after remission induction warrants further exploration. These results have broad implications for studying CML relapse and treating minimal residual disease.

Epithelial-to-mesenchymal transition and its association with PD-L1 and CD8 in thyroid cancer.

Programmed cell death-ligand 1 (PD-L1) has recently been shown to play a role in the regulation of epithelial-to-mesenchymal transition (EMT); however, the relationship between PD-L1 expression, EMT and the inflammatory tumour microenvironment has yet to be investigated in thyroid cancer. To address this issue, we examined the expression of CD8, PD-L1 and the EMT markers E-cadherin and vimentin in a cohort of 74 papillary thyroid cancer (PTC) patients and investigated the association of these with clinicopathologic characteristics and disease-free survival (DFS). The relationship between PD-L1 and EMT was further examined in three thyroid cancer cell lines via Western blot and live cell imaging. In order to expand our in vitro findings, the normalised gene expression profiles of 516 thyroid cancer patients were retrieved and analysed from The Cancer Genome Atlas (TCGA). PD-L1 positivity was significantly higher in PTC patients exhibiting a mesenchymal phenotype (P = 0.012). Kaplan-Meier analysis revealed that PD-L1 (P = 0.045), CD8 (P = 0.038) and EMT status (P = 0.038) were all significant predictors for DFS. Sub-analysis confirmed that the poorest DFS was evident in PD-L1 positive patients with EMT features and negative CD8 expression (P < 0.0001). IFN-γ treatment induced upregulation of PD-L1 and significantly promoted an EMT phenotype in two thyroid cancer cell lines. Our findings suggest that PD-L1 signalling may play a role in stimulating EMT in thyroid cancer. EMT, CD8 and PD-L1 expression may serve as valuable predictive biomarkers in patients with PTC.