RNA processing as an alternative route to attack glioblastoma

SERBP1 interacts with PARP1 and is present in PARylation-dependent protein complexes regulating splicing, cell division, and ribosome biogenesis

RNA binding proteins (RBPs) containing intrinsically disordered regions (IDRs) are present in diverse molecular complexes where they function as dynamic regulators. Their characteristics promote liquid-liquid phase separation (LLPS) and the formation of membraneless organelles such as stress granules and nucleoli. IDR-RBPs are particularly relevant in the nervous system and their dysfunction is associated with neurodegenerative diseases and brain tumor development. SERBP1 is a unique member of this group, being mostly disordered and lacking canonical RNA-binding domains. Using a proteomics approach followed by functional analysis, we defined SERBP1's interactome. We uncovered novel SERBP1 roles in splicing, cell division, and ribosomal biogenesis and showed its participation in pathological stress granules and Tau aggregates in Alzheimer's disease brains. SERBP1 preferentially interacts with other G-quadruplex (G4) binders, implicated in different stages of gene expression, suggesting that G4 binding is a critical component of SERBP1 function in different settings. Similarly, we identified important associations between SERBP1 and PARP1/polyADP-ribosylation (PARylation). SERBP1 interacts with PARP1 and its associated factors and influences PARylation. Moreover, protein complexes in which SERBP1 participates contain mostly PARylated proteins and PAR binders. Based on these results, we propose a feedback regulatory model in which SERBP1 influences PARP1 function and PARylation, while PARylation modulates SERBP1 functions and participation in regulatory complexes.

Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance

RNA splicing shapes the gene regulatory programs that underlie various physiological and disease processes. Here, we present the SCASL (single-cell clustering based on alternative splicing landscapes) method for interrogating the heterogeneity of RNA splicing with single-cell RNA-seq data. SCASL resolves the issue of biased and sparse data coverage on single-cell RNA splicing and provides a new scheme for classifications of cell identities. With previously published datasets as examples, SCASL identifies new cell clusters indicating potentially precancerous and early-tumor stages in triple-negative breast cancer, illustrates cell lineages of embryonic liver development, and provides fine clusters of highly heterogeneous tumor-associated CD4 and CD8 T cells with functional and physiological relevance. Most of these findings are not readily available via conventional cell clustering based on single-cell gene expression data. Our study shows the potential of SCASL in revealing the intrinsic RNA splicing heterogeneity and generating biological insights into the dynamic and functional cell landscapes in complex tissues.

Investigating the effects of arginine methylation inhibitors on microdissected brain tumour biopsies maintained in a miniaturised perfusion system

Arginine methylation is a post-translational modification that consists of the transfer of one or two methyl (CH3) groups to arginine residues in proteins. Several types of arginine methylation occur, namely monomethylation, symmetric dimethylation and asymmetric dimethylation, which are catalysed by different protein arginine methyltransferases (PRMTs). Inhibitors of PRMTs have recently entered clinical trials to target several types of cancer, including gliomas (NCT04089449). People with glioblastoma (GBM), the most aggressive form of brain tumour, are among those with the poorest quality of life and likelihood of survival of anyone diagnosed with cancer. There is currently a lack of (pre)clinical research on the possible application of PRMT inhibitors to target brain tumours. Here, we set out to investigate the effects of clinically-relevant PRMT inhibitors on GBM biopsies. We present a new, low-cost, easy to fabricate perfusion device that can maintain GBM tissue in a viable condition for at least eight days post-surgical resection. The miniaturised perfusion device enables the treatment of GBM tissue with PRMT inhibitors ex vivo, and we observed a two-fold increase in apoptosis in treated samples compared to parallel control experiments. Mechanistically, we show thousands of differentially expressed genes after treatment, and changes in the type of arginine methylation of the RNA binding protein FUS that are consistent with hundreds of differential gene splicing events. This is the first time that cross-talk between different types of arginine methylation has been observed in clinical samples after treatment with PRMT inhibitors.

Neoantigens: promising targets for cancer therapy

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

Sources of Cancer Neoantigens beyond Single-Nucleotide Variants

The success of checkpoint blockade therapy against cancer has unequivocally shown that cancer cells can be effectively recognized by the immune system and eliminated. However, the identity of the cancer antigens that elicit protective immunity remains to be fully explored. Over the last decade, most of the focus has been on somatic mutations derived from non-synonymous single-nucleotide variants (SNVs) and small insertion/deletion mutations (indels) that accumulate during cancer progression. Mutated peptides can be presented on MHC molecules and give rise to novel antigens or neoantigens, which have been shown to induce potent anti-tumor immune responses. A limitation with SNV-neoantigens is that they are patient-specific and their accurate prediction is critical for the development of effective immunotherapies. In addition, cancer types with low mutation burden may not display sufficient high-quality [SNV/small indels] neoantigens to alone stimulate effective T cell responses. Accumulating evidence suggests the existence of alternative sources of cancer neoantigens, such as gene fusions, alternative splicing variants, post-translational modifications, and transposable elements, which may be attractive novel targets for immunotherapy. In this review, we describe the recent technological advances in the identification of these novel sources of neoantigens, the experimental evidence for their presentation on MHC molecules and their immunogenicity, as well as the current clinical development stage of immunotherapy targeting these neoantigens.

The RNA-Binding Protein Musashi1 Regulates a Network of Cell Cycle Genes in Group 4 Medulloblastoma

Medulloblastoma is the most common malignant brain tumor in children. Treatment with surgery, irradiation, and chemotherapy has improved survival in recent years, but patients are frequently left with devastating neurocognitive and other sequelae. Patients in molecular subgroups 3 and 4 still experience a high mortality rate. To identify new pathways contributing to medulloblastoma development and create new routes for therapy, we have been studying oncogenic RNA-binding proteins. We defined Musashi1 (Msi1) as one of the main drivers of medulloblastoma development. The high expression of Msi1 is prevalent in Group 4 and correlates with poor prognosis while its knockdown disrupted cancer-relevant phenotypes. Genomic analyses (RNA-seq and RIP-seq) indicated that cell cycle and division are the main biological categories regulated by Msi1 in Group 4 medulloblastoma. The most prominent Msi1 targets include CDK2, CDK6, CCND1, CDKN2A, and CCNA1. The inhibition of Msi1 with luteolin affected the growth of CHLA-01 and CHLA-01R Group 4 medulloblastoma cells and a synergistic effect was observed when luteolin and the mitosis inhibitor, vincristine, were combined. These findings indicate that a combined therapeutic strategy (Msi1 + cell cycle/division inhibitors) could work as an alternative to treat Group 4 medulloblastoma.

Genome-wide profiling of alternative splicing in glioblastoma and their clinical value

Background

Alternative splicing (AS), one of the main post-transcriptional biological regulation mechanisms, plays a key role in the progression of glioblastoma (GBM). Systematic AS profiling in GBM is limited and urgently needed.

Methods

TCGA SpliceSeq data and the corresponding clinical data were downloaded from the TCGA data portal. Survival-related AS events were identified through Kaplan–Meier survival analysis and univariate Cox analysis. Then, splicing correlation network was constructed based on these AS events and associated splicing factors. LASSO regression followed by multivariate Cox analysis was performed to validate independent AS biomarkers and to construct a risk prediction model. Enrichment analysis was subsequently conducted to explore potential signaling pathways of these AS events.

Results

A total of 132 TCGA GBM samples and 45,610 AS events were included in our study, among which 416 survival-related AS events were identified. An AS correlation network, including 54 AS events and 94 splicing factors, was constructed, and further functional enrichment was performed. Moreover, the novel risk prediction model we constructed displayed moderate performance (the area under the curves were > 0.7) at both one, two and three years.

Conclusions

Survival-related AS events may be vital factors of both biological function and prognosis. Our findings in this study can deepen the understanding of the complicated mechanisms of AS in GBM and provide novel insights for further study. Moreover, our risk prediction model is ready for preliminary clinical applications. Further verification is required.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08681-z.

Molecular Mechanisms of Drug Resistance in Glioblastoma

Glioblastoma multiforme (GBM) is the most common and fatal primary brain tumor, is highly resistant to conventional radiation and chemotherapy, and is not amenable to effective surgical resection. The present review summarizes recent advances in our understanding of the molecular mechanisms of therapeutic resistance of GBM to already known drugs, the molecular characteristics of glioblastoma cells, and the barriers in the brain that underlie drug resistance. We also discuss the progress that has been made in the development of new targeted drugs for glioblastoma, as well as advances in drug delivery across the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB).

Functional and conformational impact of cancer-associated SF3B1 mutations depends on the position and the charge of amino acid substitution

The hotspot mutations of SF3B1, the most frequently mutated splicing gene in cancers, contribute to oncogenesis by corrupting the mRNA splicing. Further SF3B1 mutations have been reported in cancers but their consequences remain unclear. Here, we screened for SF3B1 mutations in the vicinity of the hotspot region in tumors. We then performed in-silico prediction of the functional outcome followed by in-cellulo modelling of different SF3B1 mutants. We show that cancer-associated SF3B1 mutations present varying functional consequences that are loosely predicted by the in-silico algorithms. Analysis of the tertiary structure of SF3B1 mutants revealed that the resulting splicing errors may be due to a conformational change in SF3B1 N-terminal region, which mediates binding with other splicing factors. Our study demonstrates a varying functional impact of SF3B1 mutations according to the mutated codon and the amino acid substitution, implying unequal pathogenic and prognostic potentials of SF3B1 mutations in cancers.

The Many Facets of Therapy Resistance and Tumor Recurrence in Glioblastoma

Glioblastoma (GBM) is the most lethal type of primary brain cancer. Standard care using chemo- and radio-therapy modestly increases the overall survival of patients; however, recurrence is inevitable, due to treatment resistance and lack of response to targeted therapies. GBM therapy resistance has been attributed to several extrinsic and intrinsic factors which affect the dynamics of tumor evolution and physiology thus creating clinical challenges. Tumor-intrinsic factors such as tumor heterogeneity, hypermutation, altered metabolomics and oncologically activated alternative splicing pathways change the tumor landscape to facilitate therapy failure and tumor progression. Moreover, tumor-extrinsic factors such as hypoxia and an immune-suppressive tumor microenvironment (TME) are the chief causes of immunotherapy failure in GBM. Amid the success of immunotherapy in other cancers, GBM has occurred as a model of resistance, thus focusing current efforts on not only alleviating the immunotolerance but also evading the escape mechanisms of tumor cells to therapy, caused by inter- and intra-tumoral heterogeneity. Here we review the various mechanisms of therapy resistance in GBM, caused by the continuously evolving tumor dynamics as well as the complex TME, which cumulatively contribute to GBM malignancy and therapy failure; in an attempt to understand and identify effective therapies for recurrent GBM.

SRRM4 Expands the Repertoire of Circular RNAs by Regulating Microexon Inclusion

High-throughput RNA sequencing (RNA-seq) and dedicated bioinformatics pipelines have synergized to identify an expansive repertoire of unique circular RNAs (circRNAs), exceeding 100,000 variants. While the vast majority of these circRNAs comprise canonical exonic and intronic sequences, microexons (MEs)-which occur in 30% of functional mRNA transcripts-have been entirely overlooked. CircRNAs which contain these known MEs (ME-circRNAs) could be identified with commonly utilized circRNA prediction pipelines, CIRCexplorer2 and CIRI2, but were not previously recognized as ME-circRNAs. In addition, when employing a bespoke bioinformatics pipeline for identifying RNA chimeras, called Hyb, we could also identify over 2000 ME-circRNAs which contain novel MEs at their backsplice junctions, that are uncalled by either CIRCexplorer2 or CIRI2. Analysis of circRNA-seq datasets from gliomas of varying clinical grades compared with matched control tissue has shown circRNAs have potential as prognostic markers for stratifying tumor from healthy tissue. Furthermore, the abundance of microexon-containing circRNAs (ME-circRNAs) between tumor and normal tissues is correlated with the expression of a splicing associated factor, Serine/arginine repetitive matrix 4 (SRRM4). Overexpressing SRRM4, known for regulating ME inclusion in mRNAs critical for neural differentiation, in human HEK293 cells resulted in the biogenesis of over 2000 novel ME-circRNAs, including ME-circEIF4G3, and changes in the abundance of many canonical circRNAs, including circSETDB2 and circLBRA. This shows SRRM4, in which its expression is correlated with poor prognosis in gliomas, acts as a bona fide circRNA biogenesis factor. Given the known roles of MEs and circRNAs in oncogenesis, the identification of these previously unrecognized ME-circRNAs further increases the complexity and functional purview of this non-coding RNA family.

Genomic analyses of early responses to radiation inglioblastoma reveal new alterations at transcription,splicing, and translation levels

High-dose radiation is the main component of glioblastoma therapy. Unfortunately, radio-resistance is a common problem and a major contributor to tumor relapse. Understanding the molecular mechanisms driving response to radiation is critical for identifying regulatory routes that could be targeted to improve treatment response. We conducted an integrated analysis in the U251 and U343 glioblastoma cell lines to map early alterations in the expression of genes at three levels: transcription, splicing, and translation in response to ionizing radiation. Changes at the transcriptional level were the most prevalent response. Downregulated genes are strongly associated with cell cycle and DNA replication and linked to a coordinated module of expression. Alterations in this group are likely driven by decreased expression of the transcription factor FOXM1 and members of the E2F family. Genes involved in RNA regulatory mechanisms were affected at the mRNA, splicing, and translation levels, highlighting their importance in radiation-response. We identified a number of oncogenic factors, with an increased expression upon radiation exposure, including BCL6, RRM2B, IDO1, FTH1, APIP, and LRIG2 and lncRNAs NEAT1 and FTX. Several of these targets have been previously implicated in radio-resistance. Therefore, antagonizing their effects post-radiation could increase therapeutic efficacy. Our integrated analysis provides a comprehensive view of early response to radiation in glioblastoma. We identify new biological processes involved in altered expression of various oncogenic factors and suggest new target options to increase radiation sensitivity and prevent relapse.

Systemic Analysis of RNA Alternative Splicing Signals Related to the Prognosis for Head and Neck Squamous Cell Carcinoma

Alternative splicing (AS) is an important mechanism that is responsible for the production of protein diversity. An increasing body of evidence has suggested that out-of-control AS is closely related to the genesis and development of cancer. Systematic analysis of genome-wide AS in head and neck squamous cell carcinoma (HNSCC) has not yet been carried out, and consideration of this topic remains at the preliminary stage and requires further investigation. In this study, systemic bioinformatic analysis was carried out on the genome-wide AS events of 555 clinical HNSCC samples from the TCGA database. Firstly, we statistically analyzed the distributions of seven AS event types in HNSCC samples. Then, through univariate survival analysis, we observed the relationship between AS and the prognosis of the disease and found that 437 intersections of AS events were significantly related to overall survival. Among them, 335 cross-genes showed a high degree of consistency in the genes associated with overall survival and recurrence. The overall survival was significantly related to AS events. Besides, the frequency of overall survival-related ES events was evidently reduced, while the AP and the AT events were increased. In addition, AT events accounted for the largest proportion. Further, multiple regression model analysis proved that AS could become a new classification method for HNSCC, and KEGG enrichment analysis proved that most genes and proteins interacting with AS events had different biological functions and were associated with a variety of diseases. Finally, through the selection of characteristic HNSCC genes and the construction of a prognostic model, seven cross-genes related to survival and recurrence were screened out, and these characteristic genes were verified by multivariate survival model analysis so as to classify the prognosis at different splicing times and gene expression levels. These results have laid a solid foundation for our further research and play a decisive role in showing the correlation of AS with the prognosis of HNSCC.

Putatively cancer-specific exon-exon junctions are shared across patients and present in developmental and other non-cancer cells

This study probes the distribution of putatively cancer-specific junctions across a broad set of publicly available non-cancer human RNA sequencing (RNA-seq) datasets. We compared cancer and non-cancer RNA-seq data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) Project and the Sequence Read Archive. We found that (i) averaging across cancer types, 80.6% of exon–exon junctions thought to be cancer-specific based on comparison with tissue-matched samples (σ = 13.0%) are in fact present in other adult non-cancer tissues throughout the body; (ii) 30.8% of junctions not present in any GTEx or TCGA normal tissues are shared by multiple samples within at least one cancer type cohort, and 87.4% of these distinguish between different cancer types; and (iii) many of these junctions not found in GTEx or TCGA normal tissues (15.4% on average, σ = 2.4%) are also found in embryological and other developmentally associated cells. These findings refine the meaning of RNA splicing event novelty, particularly with respect to the human neoepitope repertoire. Ultimately, cancer-specific exon–exon junctions may have a substantial causal relationship with the biology of disease.

Proneural and mesenchymal glioma stem cells display major differences in splicing and lncRNA profiles

Therapy resistance and recurrence in high-grade gliomas are driven by their populations of glioma stem cells (GSCs). Thus, detailed molecular characterization of GSCs is needed to develop more effective therapies. We conducted a study to identify differences in the splicing profile and expression of long non-coding RNAs in proneural and mesenchymal GSC cell lines. Genes related to cell cycle, DNA repair, cilium assembly, and splicing showed the most differences between GSC subgroups. We also identified genes distinctly associated with survival among patients of mesenchymal or proneural subgroups. We determined that multiple long non-coding RNAs with increased expression in mesenchymal GSCs are associated with poor survival of glioblastoma patients. In summary, our study established critical differences between proneural and mesenchymal GSCs in splicing profiles and expression of long non-coding RNA. These splicing isoforms and lncRNA signatures may contribute to the uniqueness of GSC subgroups, thus contributing to cancer phenotypes and explaining differences in therapeutic responses.

Genome-wide analysis reveals the association between alternative splicing and DNA methylation across human solid tumors

Background

Dysregulation of alternative splicing (AS) is a critical signature of cancer. However, the regulatory mechanisms of cancer-specific AS events, especially the impact of DNA methylation, are poorly understood.

Methods

By using The Cancer Genome Atlas (TCGA) SpliceSeq and TCGA data for ten solid tumor types, association analysis was performed to characterize the potential link between cancer-specific AS and DNA methylation. Functional and pathway enrichment analyses were performed, and the protein-protein interaction (PPI) network was constructed with the String website. The prognostic analysis was carried out with multivariate Cox regressions models.

Results

15,818 AS events in 3955 annotated genes were identified across ten solid tumor types. The different DNA methylation patterns between tumor and normal tissues at the corresponding alternative spliced exon boundaries were shown, and 51.3% of CpG sites (CpGs) revealed hypomethylated in tumors. Notably, 607 CpGs were found to be highly correlated with 369 cancer-specific AS events after permutation tests. Among them, the hypomethylated CpGs account for 52.7%, and the number of down-regulated exons was 173. Furthermore, we found 38 AS events in 35 genes could serve as new molecular biomarkers to predict patient survival.

Conclusions

Our study described the relationship between DNA methylation and AS events across ten human solid tumor types and provided new insights into intragenic DNA methylation and exon usage during the AS process.

The Roles of Alternative Splicing in Tumor-immune Cell Interactions

Alternative splicing (AS) plays a significant role in the hallmarks of cancer and can provide neoantigens for immunotherapy. Here, we summarize recent advances in immune system associated tumor specific-antigens (TSAs) produced by AS. We further discuss the regulating mechanisms involved in AS-mediated innate and adaptive immune responses and the anti-tumoral and protumoral roles in different types of cancer. For example, ULBP1_RI, MLL5Δ21spe, NKp44-1Δ5, MHC-IΔ7, CD200SΔ1, 2, PVR α/β/γ/δ and IL-33 variants 1/2/3 act as regulators in solid tumors and IPAK4-L and, FOXP1ΔN100 exhibit functions in hematological cancers.

Schwann cell-specific Dp116 is expressed in glioblastoma cells, revealing two novel DMD gene splicing patterns

Background

The DMD gene is one of the largest human genes, being composed of 79 exons. Dystrophin Dp116 expressed from the promoter in intron 55 is a Schwann cell-specific isoform. The pathophysiological roles of Dp116 are largely unknown, because of its limited expression. This study assessed the expression of Dp116 in glioblastoma cells and evaluated the splicing patterns of the DMD gene in these cells.

Methods

Full-length Dp116 cDNA was PCR amplified from U-251 glioblastoma cells. Dp116 protein was analyzed by Western blotting.

Results

Full-length Dp116 cDNA, extending from exon S1 to exon 79, was PCR amplified to avoid confusion with other DMD isoforms. The full-length Dp116 transcript was amplified as nearly 3 kb in size. Western blotting of U-251 cell lysates revealed a signal at a position corresponding to vector-expressed Dp116 protein, indicating that Dp116 is expressed in glioblastoma cells. Sequencing of the amplified product revealed five splice variants, all skipping exon 78. The most abundant transcript lacked only exon 78 (Dp116b), whereas the second most abundant transcript lacked both exons 71 and 78 (Dp116ab). A third transcript lacking exons 71–74 and 78 was also identified (Dp116bc). Two novel splicing patterns were also observed, one with a deletion of exons 68 and 69 (Dp116bΔ68-69) and the other with a 100 bp deletion in the 5’ terminal end of exon 75 (75s), which was produced by the activation of a cryptic splice acceptor site (Dp116b75s). However, the splicing patterns in glioblastoma cells of DMD exons in Dp116 and Dp71 showed no significant differences.

Conclusions

Dp116 is expressed in glioblastoma cells as five splicing variants, with Dp116b being the most abundant. Two novel splicing patterns of DMD exons were observed.

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Dp116 is a Schwann cell-specific dystrophin isoform.

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Dp116 was shown to be expressed in glioblastoma, a lethal cerebral malignancy.

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Skipping of exon 78 was the default pathway.

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Of the five alternatively spliced variants detected, Dp116b was the most abundant.

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DMD exons showed two novel splicing patterns, one with cryptic splice activation.

Classification of glioma based on prognostic alternative splicing

BACKGROUND

Previously developed classifications of glioma have provided enormous advantages for the diagnosis and treatment of glioma. Although the role of alternative splicing (AS) in cancer, especially in glioma, has been validated, a comprehensive analysis of AS in glioma has not yet been conducted. In this study, we aimed at classifying glioma based on prognostic AS.

METHODS

Using the TCGA glioblastoma (GBM) and low-grade glioma (LGG) datasets, we analyzed prognostic splicing events. Consensus clustering analysis was conducted to classified glioma samples and correlation analysis was conducted to characterize regulatory network of splicing factors and splicing events.

RESULTS

We analyzed prognostic splicing events and proposed novel splicing classifications across pan-glioma samples (labeled pST1-7) and across GBM samples (labeled ST1-3). Distinct splicing profiles between GBM and LGG were observed, and the primary discriminator for the pan-glioma splicing classification was tumor grade. Subtype-specific splicing events were identified; one example is AS of zinc finger proteins, which is involved in glioma prognosis. Furthermore, correlation analysis of splicing factors and splicing events identified SNRPB and CELF2 as hub splicing factors that upregulated and downregulated oncogenic AS, respectively.

CONCLUSION

A comprehensive analysis of AS in glioma was conducted in this study, shedding new light on glioma heterogeneity and providing new insights into glioma diagnosis and treatment.

Targeting mRNA processing as an anticancer strategy

Discoveries in the past decade have highlighted the potential of mRNA as a therapeutic target for cancer. Specifically, RNA sequencing revealed that, in addition to gene mutations, alterations in mRNA can contribute to the initiation and progression of cancer. Indeed, precursor mRNA processing, which includes the removal of introns by splicing and the formation of 3' ends by cleavage and polyadenylation, is frequently altered in tumours. These alterations result in numerous cancer-specific mRNAs that generate altered levels of normal proteins or proteins with new functions, leading to the activation of oncogenes or the inactivation of tumour-suppressor genes. Abnormally spliced and polyadenylated mRNAs are also associated with resistance to cancer treatment and, unexpectedly, certain cancers are highly sensitive to the pharmacological inhibition of splicing. This Review summarizes recent progress in our understanding of how splicing and polyadenylation are altered in cancer and highlights how this knowledge has been translated for drug discovery, resulting in the production of small molecules and oligonucleotides that modulate the spliceosome and are in clinical trials for the treatment of cancer.

RNA processing genes characterize RNA splicing and further stratify lower-grade glioma

BACKGROUND

Aberrant expression of RNA processing genes may drive the alterative RNA profile in lower-grade gliomas (LGGs). Thus, we aimed to further stratify LGGs based on the expression of RNA processing genes.

METHODS

This study included 446 LGGs from The Cancer Genome Atlas (TCGA, training set) and 171 LGGs from the Chinese Glioma Genome Atlas (CGGA, validation set). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was conducted to develop a risk-signature. The receiver operating characteristic (ROC) curves and Kaplan-Meier curves were used to study the prognosis value of the risk-signature.

RESULTS

Among the tested 784 RNA processing genes, 276 were significantly correlated with the OS of LGGs. Further LASSO Cox regression identified a 19-gene risk-signature, whose risk score was also an independently prognosis factor (P<0.0001, multiplex Cox regression) in the validation dataset. The signature had better prognostic value than the traditional factors "age", "grade" and "WHO 2016 classification" for 3- and 5-year survival both two datasets (AUCs > 85%). Importantly, the risk-signature could further stratify the survival of LGGs in specific subgroups of WHO 2016 classification. Furthermore, alternative splicing events for genes such as EGFR and FGFR were found to be associated with the risk score. mRNA expression levels for genes, which participated in cell proliferation and other processes, were significantly correlated to the risk score.

CONCLUSIONS

Our results highlight the role of RNA processing genes for further stratifying the survival of patients with LGGs and provide insight into the alternative splicing events underlying this role.

Systematically profiling the expression of eIF3 subunits in glioma reveals the expression of eIF3i has prognostic value in IDH-mutant lower grade glioma

Background

Abnormal expression of the eukaryotic initiation factor 3 (eIF3) subunits plays critical roles in tumorigenesis and progression, and also has potential prognostic value in cancers. However, the expression and clinical implications of eIF3 subunits in glioma remain unknown.

Methods

Expression data of eIF3 for patients with gliomas were obtained from the Chinese Glioma Genome Atlas (CGGA) (n = 272) and The Cancer Genome Atlas (TCGA) (n = 595). Cox regression, the receiver operating characteristic (ROC) curves and Kaplan–Meier analysis were used to study the prognostic value. Gene oncology (GO) and gene set enrichment analysis (GSEA) were utilized for functional prediction.

Results

In both the CGGA and TCGA datasets, the expression levels of eIF3d, eIF3e, eIF3f, eIF3h and eIF3l highly were associated with the IDH mutant status of gliomas. The expression of eIF3b, eIF3i, eIF3k and eIF3m was increased with the tumor grade, and was associated with poorer overall survival [All Hazard ratio (HR) > 1 and P < 0.05]. By contrast, the expression of eIF3a and eIF3l was decreased in higher grade gliomas and was associated with better overall survival (Both HR < 1 and P < 0.05). Importantly, the expression of eIF3i (located on chromosome 1p) and eIF3k (Located on chromosome 19q) were the two highest risk factors in both the CGGA [eIF3i HR = 2.068 (1.425–3.000); eIF3k HR = 1.737 (1.166–2.588)] and TCGA [eIF3i HR = 1.841 (1.642–2.064); eIF3k HR = 1.521 (1.340–1.726)] databases. Among eIF3i, eIF3k alone or in combination, the expression of eIF3i was the more robust in stratifying the survival of glioma in various pathological subgroups. The expression of eIF3i was an independent prognostic factor in IDH-mutant lower grade glioma (LGG) and could also predict the 1p/19q codeletion status of IDH-mutant LGG. Finally, GO and GSEA analysis showed that the elevated expression of eIF3i was significantly correlated with the biological processes of cell proliferation, mRNA processing, translation, T cell receptor signaling, NF-κB signaling and others.

Conclusions

Our study reveals the expression alterations during glioma progression, and highlights the prognostic value of eIF3i in IDH-mutant LGG.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0867-1) contains supplementary material, which is available to authorized users.

RNA Sequencing of the NCI-60: Integration into CellMiner and CellMiner CDB

CellMiner (http://discover.nci.nih.gov/cellminer) and CellMinerCDB (https://discover.nci.nih.gov/cellminercdb/) are web-based applications for mining publicly available genomic, molecular, and pharmacologic datasets of human cancer cell lines including the NCI-60, Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, NCI/DTP small cell lung cancer, and NCI Almanac cell line sets. Here, we introduce our RNA sequencing (RNA-seq) data for the NCI-60 and their access and integration with the other databases. Correlation to transcript microarray expression levels for identical genes and identical cell lines across CellMinerCDB demonstrates the high quality of these new RNA-seq data. We provide composite and isoform transcript expression data and demonstrate diversity in isoform composition for individual cancer- and pharmacologically relevant genes, including HRAS, PTEN, EGFR, RAD51, ALKBH2, BRCA1, ERBB2, TP53, FGFR2, and CTNND1. We reveal cell-specific differences in the overall levels of isoforms and show their linkage to expression of RNA processing and splicing genes as well as resultant alterations in cancer and pharmacologic gene sets. Gene-drug pairings linked by pathways or functions show specific correlations to isoforms compared with composite gene expression, including ALKBH2-benzaldehyde, AKT3-vandetanib, BCR-imatinib, CDK1 and 20-palbociclib, CASP1-imexon, and FGFR3-pazopanib. Loss of MUC1 20 amino acid variable number tandem repeats, which is used to elicit immune response, and the presence of the androgen receptor AR-V4 and -V7 isoforms in all NCI-60 tissue of origin types demonstrate translational relevance. In summary, we introduce RNA-seq data to our CellMiner and CellMinerCDB web applications, allowing their exploration for both research and translational purposes. SIGNIFICANCE: The current study provides RNA sequencing data for the NCI-60 cell lines made accessible through both CellMiner and CellMinerCDB and is an important pharmacogenomics resource for the field.

Oligonucleotide Therapeutics as a New Class of Drugs for Malignant Brain Tumors: Targeting mRNAs, Regulatory RNAs, Mutations, Combinations, and Beyond

Malignant brain tumors are rapidly progressive and often fatal owing to resistance to therapies and based on their complex biology, heterogeneity, and isolation from systemic circulation. Glioblastoma is the most common and most aggressive primary brain tumor, has high mortality, and affects both children and adults. Despite significant advances in understanding the pathology, multiple clinical trials employing various treatment strategies have failed. With much expanded knowledge of the GBM genome, epigenome, and transcriptome, the field of neuro-oncology is getting closer to achieve breakthrough-targeted molecular therapies. Current developments of oligonucleotide chemistries for CNS applications make this new class of drugs very attractive for targeting molecular pathways dysregulated in brain tumors and are anticipated to vastly expand the spectrum of currently targetable molecules. In this chapter, we will overview the molecular landscape of malignant gliomas and explore the most prominent molecular targets (mRNAs, miRNAs, lncRNAs, and genomic mutations) that provide opportunities for the development of oligonucleotide therapeutics for this class of neurologic diseases. Because malignant brain tumors focally disrupt the blood-brain barrier, this class of diseases might be also more susceptible to systemic treatments with oligonucleotides than other neurologic disorders and, thus, present an entry point for the oligonucleotide therapeutics to the CNS. Nevertheless, delivery of oligonucleotides remains a crucial part of the treatment strategy. Finally, synthetic gRNAs guiding CRISPR-Cas9 editing technologies have a tremendous potential to further expand the applications of oligonucleotide therapeutics and take them beyond RNA targeting.

Identification of a Novel Splice Variant of Neural Cell Adhesion Molecule in Glioblastoma Through Proteogenomics Analysis

Splice variants are known to be important in the pathophysiology of tumors, including the brain cancers. We applied a proteogenomics pipeline to identify splice variants in glioblastoma (GBM, grade IV glioma), a highly malignant brain tumor, using in-house generated mass spectrometric proteomic data and public domain RNASeq dataset. Our analysis led to the identification of a novel exon that maps to the long isoform of Neural cell adhesion molecule 1 (NCAM1), expressed on the surface of glial cells and neurons, important for cell adhesion and cell signaling. The presence of the novel exon is supported with the identification of five peptides spanning it. Additional peptides were also detected in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gel separated proteins from GBM patient tissue, underscoring the presence of the novel peptides in the intact brain protein. The novel exon was detected in the RNASeq dataset in 18 of 25 GBM samples and separately validated in additional 10 GBM tumor tissues using quantitative real-time-polymerase chain reaction (qRT-PCR). Both transcriptomic and proteomic data indicate downregulation of NCAM1, including the novel variant, in GBM. Domain analysis of the novel NCAM1 sequence indicates that the insertion of the novel exon contributes extra low-complexity region in the protein that may be important for protein-protein interactions and hence for cell signaling associated with tumor development. Taken together, the novel NCAM1 variant reported in this study exemplifies the importance of future multiomics research and systems biology applications in GBM.

Aberrant RNA Splicing in Cancer and Drug Resistance

More than 95% of the 20,000 to 25,000 transcribed human genes undergo alternative RNA splicing, which increases the diversity of the proteome. Isoforms derived from the same gene can have distinct and, in some cases, opposing functions. Accumulating evidence suggests that aberrant RNA splicing is a common and driving event in cancer development and progression. Moreover, aberrant splicing events conferring drug/therapy resistance in cancer is far more common than previously envisioned. In this review, aberrant splicing events in cancer-associated genes, namely BCL2L1, FAS, HRAS, CD44, Cyclin D1, CASP2, TMPRSS2-ERG, FGFR2, VEGF, AR and KLF6, will be discussed. Also highlighted are the functional consequences of aberrant splice variants (BCR-Abl35INS, BIM-γ, IK6, p61 BRAF V600E, CD19-∆2, AR-V7 and PIK3CD-S) in promoting resistance to cancer targeted therapy or immunotherapy. To overcome drug resistance, we discuss opportunities for developing novel strategies to specifically target the aberrant splice variants or splicing machinery that generates the splice variants. Therapeutic approaches include the development of splice variant-specific siRNAs, splice switching antisense oligonucleotides, and small molecule inhibitors targeting splicing factors, splicing factor kinases or the aberrant oncogenic protein isoforms.

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

Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects alternative splicing events and tumor variants by reanalyzing RNA and whole-exome sequencing data. Tumors have up to 30% more alternative splicing events than normal samples. Association analysis of somatic variants with alternative splicing events confirmed known trans associations with variants in SF3B1 and U2AF1 and identified additional trans-acting variants (e.g., TADA1, PPP2R1A). Many tumors have thousands of alternative splicing events not detectable in normal samples; on average, we identified ≈930 exon-exon junctions ("neojunctions") in tumors not typically found in GTEx normals. From Clinical Proteomic Tumor Analysis Consortium data available for breast and ovarian tumor samples, we confirmed ≈1.7 neojunction- and ≈0.6 single nucleotide variant-derived peptides per tumor sample that are also predicted major histocompatibility complex-I binders ("putative neoantigens").

Messenger RNA Life-Cycle in Cancer Cells: Emerging Role of Conventional and Non-Conventional RNA-Binding Proteins?

Functional specialization of cells and tissues in metazoans require specific gene expression patterns. Biological processes, thus, need precise temporal and spatial coordination of gene activity. Regulation of the fate of messenger RNA plays a crucial role in this context. In the present review, the current knowledge related to the role of RNA-binding proteins in the whole mRNA life-cycle is summarized. This field opens up a new angle for understanding the importance of the post-transcriptional control of gene expression in cancer cells. The emerging role of non-classic RNA-binding proteins is highlighted. The goal of this review is to encourage readers to view, through the mRNA life-cycle, novel aspects of the molecular basis of cancer and the potential to develop RNA-based therapies.