The prognostic potential of alternative transcript isoforms across human tumors

Current status of artificial intelligence methods for skin cancer survival analysis: a scoping review

Skin cancer mortality rates continue to rise, and survival analysis is increasingly needed to understand who is at risk and what interventions improve outcomes. However, current statistical methods are limited by inability to synthesize multiple data types, such as patient genetics, clinical history, demographics, and pathology and reveal significant multimodal relationships through predictive algorithms. Advances in computing power and data science enabled the rise of artificial intelligence (AI), which synthesizes vast amounts of data and applies algorithms that enable personalized diagnostic approaches. Here, we analyze AI methods used in skin cancer survival analysis, focusing on supervised learning, unsupervised learning, deep learning, and natural language processing. We illustrate strengths and weaknesses of these approaches with examples. Our PubMed search yielded 14 publications meeting inclusion criteria for this scoping review. Most publications focused on melanoma, particularly histopathologic interpretation with deep learning. Such concentration on a single type of skin cancer amid increasing focus on deep learning highlight growing areas for innovation; however, it also demonstrates opportunity for additional analysis that addresses other types of cutaneous malignancies and expands the scope of prognostication to combine both genetic, histopathologic, and clinical data. Moreover, researchers may leverage multiple AI methods for enhanced benefit in analyses. Expanding AI to this arena may enable improved survival analysis, targeted treatments, and outcomes.

Extensive Alternative Splicing Patterns in Systemic Lupus Erythematosus Highlight Sexual Differences

Substantial evidence highlights divergences in immune responses between men and women. Women are more susceptible to autoimmunity, whereas men suffer from the more severe presentation of autoimmune disorders. The molecular mechanism of this sexual dimorphism remains elusive. Herein, we conducted a comprehensive analysis of sex differences in whole-blood gene expression focusing on alternative splicing (AS) events in systemic lupus erythematosus (SLE), which is a prototype sex-biased disease. This study included 79 SLE patients with active disease and 58 matched healthy controls who underwent whole-blood RNA sequencing. Sex differences in splicing events were widespread, existent in both SLE and a healthy state. However, we observed distinct gene sets and molecular pathways targeted by sex-dependent AS in SLE patients as compared to healthy subjects, as well as a notable sex dissimilarity in intron retention events. Sexually differential spliced genes specific to SLE patients were enriched for dynamic cellular processes including chromatin remodeling, stress and inflammatory responses. Remarkably, the extent of sexual differences in AS in the SLE patients and healthy individuals exceeded those in gene expression. Overall, this study reveals an unprecedent variation in sex-dependent splicing events in SLE and the healthy state, with potential implications for understanding the molecular basis of sexual dimorphism in autoimmunity.

A Regulatory Axis between Epithelial Splicing Regulatory Proteins and Estrogen Receptor α Modulates the Alternative Transcriptome of Luminal Breast Cancer

Epithelial splicing regulatory proteins 1 and 2 (ESRP1/2) control the splicing pattern during epithelial to mesenchymal transition (EMT) in a physiological context and in cancer, including breast cancer (BC). Here, we report that ESRP1, but not ESRP2, is overexpressed in luminal BCs of patients with poor prognosis and correlates with estrogen receptor α (ERα) levels. Analysis of ERα genome-binding profiles in cell lines and primary breast tumors showed its binding in the proximity of ESRP1 and ESRP2 genes, whose expression is strongly decreased by ERα silencing in hormone-deprived conditions. The combined knock-down of ESRP1/2 in MCF-7 cells followed by RNA-Seq, revealed the dysregulation of 754 genes, with a widespread alteration of alternative splicing events (ASEs) of genes involved in cell signaling, metabolism, cell growth, and EMT. Functional network analysis of ASEs correlated with ESRP1/2 expression in ERα+ BCs showed RAC1 as the hub node in the protein-protein interactions altered by ESRP1/2 silencing. The comparison of ERα- and ESRP-modulated ASEs revealed 63 commonly regulated events, including 27 detected in primary BCs and endocrine-resistant cell lines. Our data support a functional implication of the ERα-ESRP1/2 axis in the onset and progression of BC by controlling the splicing patterns of related genes.

Functional Interaction Between the Oncogenic Kinase NEK2 and Sam68 Promotes a Splicing Program Involved in Migration and Invasion in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype. Poor prognosis in TNBC is partly due to lack of efficacious targeted therapy and high propensity to metastasize. Dysregulation of alternative splicing has recently emerged as a trait of TNBC, suggesting that unveiling the molecular mechanisms underlying its regulation could uncover new druggable cancer vulnerabilities. The oncogenic kinase NEK2 is significantly upregulated in TNBC and contributes to shaping their unique splicing profile. Herein, we found that NEK2 interacts with the RNA binding protein Sam68 in TNBC cells and that NEK2-mediated phosphorylation of Sam68 enhances its splicing activity. Genome-wide transcriptome analyses identified the splicing targets of Sam68 in TNBC cells and revealed a common set of exons that are co-regulated by NEK2. Functional annotation of splicing-regulated genes highlighted cell migration and spreading as biological processes regulated by Sam68. Accordingly, Sam68 depletion reduces TNBC cell migration and invasion, and these effects are potentiated by the concomitant inhibition of NEK2 activity. Our findings indicate that Sam68 and NEK2 functionally cooperate in the regulation of a splicing program that sustains the pro-metastatic features of TNBC cells.

The Identification of Prognostic and Metastatic Alternative Splicing in Skin Cutaneous Melanoma

Skin cutaneous melanoma (SKCM) is a type of highly invasive cancer originated from melanocytes. It is reported that aberrant alternative splicing (AS) plays an important role in the neoplasia and metastasis of many types of cancer. Therefore, we investigated whether ASEs of pre-RNA have such an influence on the prognosis of SKCM and the related mechanism of ASEs in SKCM. The RNA-seq data and ASEs data for SKCM patients were obtained from the TCGA and TCGASpliceSeq database. The univariate Cox regression revealed 1265 overall survival-related splicing events (OS-SEs). Screened by Lasso regression, 4 OS-SEs were identified and used to construct an effective prediction model (AUC: .904), whose risk score was proved to be an independent prognostic factor. Furthermore, Kruskal-Wallis test and Mann-Whitney-Wilcoxon test showed that an aberrant splicing type of aminoacyl tRNA synthetase complex-interacting multifunctional protein 2 (AIMP2) regulated by CDC-like kinase 1 (CLK1) was associated with the metastasis and stage of SKCM. Besides, the overlapped signal pathway for AIMP2 was galactose metabolism identified by the co-expression analysis. External database validation also confirmed that AIMP2, CLK1, and the galactose metabolism were associated with the metastasis and stage of SKCM patients. ChIP-seq and ATAC-seq methods further confirmed the transcription regulation of CLK1, AIMP2, and other key genes, whose cellular expression was detected by Single Cell Sequencing. In conclusion, we proposed that CLK1-regulated AIMP2-78704-ES might play a critical role in the tumorigenesis and metastasis of SKCM via galactose metabolism. Besides, we established an effective model with MTMR14-63114-ES, URI1-48867-ES, BATF2-16724-AP, and MED22-88025-AP to predict the metastasis and prognosis of SKCM patients.

Exploring the Significance of the Exon 4-Skipping Isoform of the ZNF217 Oncogene in Breast Cancer

Oncogene alternative splicing events can create distinct functional transcripts that offer new candidate prognostic biomarkers for breast cancer. ZNF217 is a well-established oncogene but its exon 4-skipping isoform (ZNF217-ΔE4) has never been investigated in terms of clinical or biological relevance. Using in silico RNA-seq and RT-qPCR analyses, we demonstrated for the first time the existence of ZNF217-ΔE4 transcripts in primary breast tumors, and a positive correlation between ZNF217-ΔE4 mRNA levels and those of the wild-type oncogene (ZNF217-WT). A pilot retrospective analysis revealed that, in the Luminal subclass, the combination of the two ZNF217 variants (the ZNF217-ΔE4-WT gene-expression signature) provided more information than the mRNA expression levels of each isoform alone. Ectopic overexpression of ZNF217-ΔE4 in breast cancer cells promoted an aggressive phenotype and an increase in ZNF217-WT expression levels that was inversely correlated with DNA methylation of the ZNF217 gene. This study provides new insights into the possible role of the ZNF217-ΔE4 splice variant in breast cancer and suggests a close interplay between the ZNF217-WT and ZNF217-ΔE4 isoforms. Our data suggest that a dual signature combining the expression levels of these two isoforms may serve as a novel prognostic biomarker allowing better stratification of breast cancers with good prognosis and aiding clinicians in therapeutic decisions.

A Transcriptome-Wide Isoform Landscape of Melanocytic Nevi and Primary Melanomas Identifies Gene Isoforms Associated with Malignancy

Genetic splice variants have become of central interest in recent years, as they play an important role in different cancers. Little is known about splice variants in melanoma. Here, we analyzed a genome-wide transcriptomic dataset of benign melanocytic nevi and primary melanomas (n = 80) for the expression of specific splice variants. Using kallisto, a map for differentially expressed splice variants in melanoma vs. benign melanocytic nevi was generated. Among the top genes with differentially expressed splice variants were Ras-related in brain 6B (RAB6B), a member of the RAS family of GTPases, Macrophage Scavenger Receptor 1 (MSR1), Collagen Type XI Alpha 2 Chain (COLL11A2), and LY6/PLAUR Domain Containing 1 (LYPD1). The Gene Ontology terms of differentially expressed splice variants showed no enrichment for functional gene sets of melanoma vs. nevus lesions, but between type 1 (pigmentation type) and type 2 (immune response type) melanocytic lesions. A number of genes such as Checkpoint Kinase 1 (CHEK1) showed an association of mutational patterns and occurrence of splice variants in melanoma. Moreover, mutations in genes of the splicing machinery were common in both benign nevi and melanomas, suggesting a common mechanism starting early in melanoma development. Mutations in some of these genes of the splicing machinery, such as Serine and Arginine Rich Splicing Factor A3 and B3 (SF3A3, SF3B3), were significantly enriched in melanomas as compared to benign nevi. Taken together, a map of splice variants in melanoma is presented that shows a multitude of differentially expressed splice genes between benign nevi and primary melanomas. The underlying mechanisms may involve mutations in genes of the splicing machinery.

An AIB1 Isoform Alters Enhancer Access and Enables Progression of Early-Stage Triple-Negative Breast Cancer

AIB1Δ4 is an N-terminally truncated isoform of the oncogene amplified in breast cancer 1 (AIB1) with increased expression in high-grade human ductal carcinoma in situ (DCIS). However, the role of AIB1Δ4 in DCIS malignant progression has not been defined. Here we CRISPR-engineered RNA splice junctions to produce normal and early-stage DCIS breast epithelial cells that expressed only AIB1Δ4. These cells showed enhanced motility and invasion in 3D cell culture. In zebrafish, AIB1Δ4-expressing cells enabled invasion of parental cells when present in a mixed population. In mouse xenografts, a subpopulation of AIB1Δ4 cells mixed with parental cells enhanced tumor growth, recurrence, and lung metastasis. AIB1Δ4 chromatin immunoprecipitation sequencing revealed enhanced binding to regions including peroxisome proliferator-activated receptor (PPAR) and glucocorticoid receptor (GR) genomic recognition sites. H3K27ac and H3K4me1 genomic engagement patterns revealed selective activation of breast cancer-specific enhancer sites by AIB1Δ4. AIB1Δ4 cells displayed upregulated inflammatory response genes and downregulated PPAR signaling gene expression patterns. In the presence of AIB1Δ4 enabler cells, parental cells increased NF-κB and WNT signaling. Cellular cross-talk was inhibited by the PPARγ agonist efatutazone but was enhanced by treatment with the GR agonist dexamethasone. In conclusion, expression of the AIB1Δ4-selective cistrome in a small subpopulation of cells triggers an "enabler" phenotype hallmarked by an invasive transcriptional program and collective malignant progression in a heterogeneous tumor population. SIGNIFICANCE: A minor subset of early-stage breast cancer cells expressing AIB1Δ4 enables bulk tumor cells to become invasive, suggesting that selective eradication of this population could impair breast cancer metastasis.

The alternatively spliced RECK transcript variant 3 is a predictor of poor survival for melanoma patients being upregulated in aggressive cell lines and modulating MMP gene expression in vitro

The reversion-inducing cysteine-rich protein with kazal motifs (RECK) gene was described as a tumor suppressor gene two decades ago. Recently, novel alternatively spliced products of this gene have been identified. Of these, the transcript variant 3 (RECKVar3) was shown to display tumor-facilitating effects in astrocytoma cells in vitro, with a higher RECKVar3/canonical RECK expression ratio being correlated with lower survival rates of patients. However, the regulatory mechanisms through which the cell controls the production and maintenance of these alternative transcripts, as well as their expression in other tumor types, remain elusive. Thus, the aim of this study is to investigate the role of the alternatively spliced transcripts from the RECK gene in melanoma progression as well as their regulation mechanism. To this end, we analyzed data from the Cancer Genome Atlas network and experimental data obtained from a panel of cell lines to show that high levels of RECKVar3 are predictive of poor survival. We also show that the MAPK and PI3K signaling pathways clearly play a role in determining the alternative-to-canonical ratio in vitro. Finally, we show that overexpression of the RECKVar3 protein upregulates matrix metalloproteinases (MMP)-9 and MMP-14 mRNA, while downregulating their inhibitor, tissue inhibitor of metalloproteinase (TIMP)3, and that RECKVar3-specific knockdown in the 1205Lu melanoma cell line hampered upregulation of the MMP9 mRNA promoted by the MEK1/2 inhibitor U0126. Taken together, our data complement the evidence that the RECK gene has a dual role in cancer, contributing to better understanding of the signaling cues, which dictate the melanoma invasive potential.

Differential expression of protein disulfide-isomerase A3 isoforms, PDIA3 and PDIA3N, in human prostate cancer cell lines representing different stages of prostate cancer

Prostate cancer (PCa) is a highly heterogeneous and unpredictable progressive disease. Sensitivity of PCa cells to androgens play a central role in tumor aggressiveness but biomarkers with high sensitivity and specificity that follow the progression of the disease has not yet been verified. The vitamin D endocrine system and its receptors, the Vitamin D Receptor (VDR) and the Protein Disulfide-Isomerase A3 (PDIA3), are related to anti-tumoral effects as well as carcinogenesis and have therefore been suggested as potential candidates for the prevention and therapy of several cancer forms, including PCa. In this study, we evaluated the mRNA expression of VDR and PDIA3 involved in vitamin D signaling in cell lines representing different stages of PCa (PNT2, P4E6, LNCaP, DU145 and PC3). This study further aimed to evaluate vitamin D receptors and their isoforms as potential markers for clinical diagnosis of PCa. A novel transcript isoform of PDIA3 (PDIA3N) was identified and found to be expressed in all PCa cell lines analyzed. Androgen-independent cell lines showed a higher mRNA expression ratio between PDIA3N/PDIA3 contrary to androgen-dependent cell lines that showed a lower mRNA expression ratio between PDIA3N/PDIA3. The structure of PDIA3N differed from PDIA3. PDIA3N was found to be a N-truncated isoform of PDIA3 and differences in protein structure suggests an altered protein function i.e. cell location, thioredoxin activity and affinity for 1,25(OH)₂D₃. Collectively, PDIA3 transcript isoforms, the ratio between PDIA3N/PDIA3 and especially PDIA3N, are proposed as candidate markers for future studies with different stages of PCa progression.

Differential alternative RNA splicing and transcription events between tumors from African American and White patients in The Cancer Genome Atlas

Individuals of African ancestry suffer disproportionally from higher incidence, aggressiveness, and mortality for particular cancers. This disparity likely results from an interplay among differences in multiple determinants of health, including differences in tumor biology. We used The Cancer Genome Atlas (TCGA) SpliceSeq and TCGA aggregate expression datasets and identified differential alternative RNA splicing and transcription events (ARS/T) in cancers between self-identified African American (AA) and White (W) patients. We found that retained intron events were enriched among race-related ARS/T. In addition, on average, 12% of the most highly ranked race-related ARS/T overlapped between any two analyzed cancers. Moreover, the genes undergoing race-related ARS/T functioned in cancer-promoting pathways, and a number of race-related ARS/T were associated with patient survival. We built a web-application, CanSplice, to mine genomic datasets by self-identified race. The race-related targets have the potential to aid in the development of new biomarkers and therapeutics to mitigate cancer disparity.

Overexpressed P75CUX1 promotes EMT in glioma infiltration by activating β-catenin

The homeobox protein cut-like 1 (CUX1) comprises three isoforms and has been shown to be involved in the development of various types of malignancies. However, the expression and role of the CUX1 isoforms in glioma remain unclear. Herein, we first identified that P75CUX1 isoform exhibited consistent expression among three isoforms in glioma with specifically designed antibodies to identify all CUX1 isoforms. Moreover, a significantly higher expression of P75CUX1 was found in glioma compared with non-tumor brain (NB) tissues, analyzed with western blot and immunohistochemistry, and the expression level of P75CUX1 was positively associated with tumor grade. In addition, Kaplan-Meier survival analysis indicated that P75CUX1 could serve as an independent prognostic indicator to identify glioma patients with poor overall survival. Furthermore, CUX1 knockdown suppressed migration and invasion of glioma cells both in vitro and in vivo. Mechanistically, this study found that P75CUX1 regulated epithelial-mesenchymal transition (EMT) process mediated via β-catenin, and CUX1/β-catenin/EMT is a novel signaling cascade mediating the infiltration of glioma. Besides, CUX1 was verified to promote the progression of glioma via multiple other signaling pathways, such as Hippo and PI3K/AKT. In conclusion, we suggested that P75CUX1 could serve as a potential prognostic indicator as well as a novel treatment target in malignant glioma.

Clusterization in acute myeloid leukemia based on prognostic alternative splicing signature to reveal the clinical characteristics in the bone marrow microenvironment

Background

Alternative splicing (AS), a crucial post-transcriptional regulatory mechanism in expanding the coding capacities of genomes and increasing the diversity of proteins, still faces various challenges in the splicing regulation mechanism of acute myeloid leukemia (AML) and microenvironmental changes.

Results

A total of 27,833 AS events were detected in 8337 genes in 178 AML patients, with exon skip being the predominant type. Approximately 11% of the AS events were significantly related to prognosis, and the prediction models based on various events demonstrated high classification efficiencies. Splicing factors correlation networks further altered the diversity of AS events through epigenetic regulation and clarified the potential mechanism of the splicing pathway. Unsupervised cluster analysis revealed significant correlations between AS and immune features, molecular mutations, immune checkpoints and clinical outcome. The results suggested that AS clusters could be used to identify patient subgroups with different survival outcomes in AML, among which C1 was both associated with good outcome in overall survival. Interestingly, C1 was associated with lower immune scores compared with C2 and C3, and favorable-risk cytogenetics was rarely distributed in C2, but much more common in C1.

Conclusions

This study revealed a comprehensive landscape of AS events, and provides new insight into molecular targeted therapy and immunotherapy strategy for AML.

Modeling circRNA expression pattern with integrated sequence and epigenetic features demonstrates the potential involvement of H3K79me2 in circRNA expression

MOTIVATION

CircRNAs are an abundant class of non-coding RNAs with widespread, cell-/tissue-specific patterns. Previous work suggested that epigenetic features might be related to circRNA expression. However, the contribution of epigenetic changes to circRNA expression has not been investigated systematically. Here, we built a machine learning framework named CIRCScan, to predict circRNA expression in various cell lines based on the sequence and epigenetic features.

RESULTS

The predicted accuracy of the expression status models was high with area under the curve of receiver operating characteristic (ROC) values of 0.89-0.92 and the false-positive rates of 0.17-0.25. Predicted expressed circRNAs were further validated by RNA-seq data. The performance of expression-level prediction models was also good with normalized root-mean-square errors of 0.28-0.30 and Pearson's correlation coefficient r over 0.4 in all cell lines, along with Spearman's correlation coefficient ρ of 0.33-0.46. Noteworthy, H3K79me2 was highly ranked in modeling both circRNA expression status and levels across different cells. Further analysis in additional nine cell lines demonstrated a significant enrichment of H3K79me2 in circRNA flanking intron regions, supporting the potential involvement of H3K79me2 in circRNA expression regulation.

AVAILABILITY AND IMPLEMENTATION

The CIRCScan assembler is freely available online for academic use at https://github.com/johnlcd/CIRCScan.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Abnormal PTBP1 Expression Sustains the Disease Progression of Multiple Myeloma

Multiple myeloma (MM) is a hematopoietic malignancy characterized by heterogeneity, which corresponds to alternative splicing (AS) profiles and disadjust gene expression. Bioinformatics analysis of AS factors possibly related to MM progression identified the polypyrimidine tract binding protein (PTBP1) as candidate. The purpose of this study was to confirm the incidence and prognostic value of PTBP1 in MM patients. Several cohorts of 2971 patients presenting newly diagnosed and relapsed MM were enrolled. Correlations between PTBP1 expression and clinicopathological characteristics, proliferative activity, and response to therapy of myeloma cells were analyzed. Moreover, the effect of PTBP1 on the AS pattern of specific aerobic glycolysis-related genes was explored in MM patients. Clinically, PTBP1 expression was present at all stages; it increased with disease progression and poor prognosis, which was even stronger elevated in patients with high tumor burden and drug resistance. Mechanistically, PTBP1 modulated AS of PKM2 and aerobic glycolysis-related genes in MM patients, which play synergistic or additive effects in clinical outcome. PTBP1 may be a novel marker for prognostic prediction and a promising therapeutic target for the development of anti-MM treatments.

Reference genome and annotation updates lead to contradictory prognostic predictions in gene expression signatures: a case study of resected stage I lung adenocarcinoma

RNA-sequencing enables accurate and low-cost transcriptome-wide detection. However, expression estimates vary as reference genomes and gene annotations are updated, confounding existing expression-based prognostic signatures. Herein, prognostic 9-gene pair signature (GPS) was applied to 197 patients with stage I lung adenocarcinoma derived from previous and latest data from The Cancer Genome Atlas (TCGA) processed with different reference genomes and annotations. For 9-GPS, 6.6% of patients exhibited discordant risk classifications between the two TCGA versions. Similar results were observed for other prognostic signatures, including IRGPI, 15-gene and ORACLE. We found that conflicting annotations for gene length and overlap were the major cause of their discordant risk classification. Therefore, we constructed a prognostic 40-GPS based on stable genes across GENCODE v20-v30 and validated it using public data of 471 stage I samples (log-rank P < 0.0010). Risk classification was still stable in RNA-sequencing data processed with the newest GENCODE v32 versus GENCODE v20-v30. Specifically, 40-GPS could predict survival for 30 stage I samples with formalin-fixed paraffin-embedded tissues (log-rank P = 0.0177). In conclusion, this method overcomes the vulnerability of existing prognostic signatures due to reference genome and annotation updates. 40-GPS may offer individualized clinical applications due to its prognostic accuracy and classification stability.

Prognostic Alternative mRNA Splicing Signature and a Novel Biomarker in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a high-risk subtype of breast cancer defined by negative expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Accumulating evidence indicates that alternative splicing (AS) events are correlated with the prognosis of cancer. RNA sequencing data and AS event data were manually curated from The Cancer Genome Atlas (TCGA) dataset and TCGA Splice Seq, respectively. Univariate and multivariate Cox regression analyses were applied to screen AS events associated with TNBC survival and to establish a prognostic model. A receiver operating characteristic (ROC) curve was used to evaluate the performance of the prognostic model. Differentially expressed gene analysis and functional enrichment analysis were harnessed to reveal the functional role of gene sets and to screen novel biomarkers. By integrated bioinformatics analysis of AS events and gene expression in TNBC, our study is the first to generate specific AS event profiles, prognostic AS event interaction networks, and splice factor-AS interaction networks for TNBC. Surprisingly, we found that the performance of the AS-based prognostic model was encouraging with a mean area under the ROC curve of 0.957 at 2-10 years. We also found that chemokine (C-C motif) ligand 16 (CCL16) expression was correlated with TNBC grade and could be a potential novel biomarker. In conclusion, this study provided a systematic analysis of prognostic AS event profiles and gene expression in TNBC. A novel prognostic model based on AS events may establish a foundation for future research investigating the diagnosis and treatment of TNBC.

Poison-Exon Inclusion in DHX9 Reduces Its Expression and Sensitizes Ewing Sarcoma Cells to Chemotherapeutic Treatment

Alternative splicing is a combinatorial mechanism by which exons are joined to produce multiple mRNA variants, thus expanding the coding potential and plasticity of eukaryotic genomes. Defects in alternative splicing regulation are associated with several human diseases, including cancer. Ewing sarcoma is an aggressive tumor of bone and soft tissue, mainly affecting adolescents and young adults. DHX9 is a key player in Ewing sarcoma malignancy, and its expression correlates with worse prognosis in patients. In this study, by screening a library of siRNAs, we have identified splicing factors that regulate the alternative inclusion of a poison exon in DHX9 mRNA, leading to its downregulation. In particular, we found that hnRNPM and SRSF3 bind in vivo to this poison exon and suppress its inclusion. Notably, DHX9 expression correlates with that of SRSF3 and hnRNPM in Ewing sarcoma patients. Furthermore, downregulation of SRSF3 or hnRNPM inhibited DHX9 expression and Ewing sarcoma cell proliferation, while sensitizing cells to chemotherapeutic treatment. Hence, our study suggests that inhibition of hnRNPM and SRSF3 expression or activity could be exploited as a therapeutic tool to enhance the efficacy of chemotherapy in Ewing sarcoma.

Gene Expression Profiles Controlled by the Alternative Splicing Factor Nova2 in Endothelial Cells

Alternative splicing (AS) plays an important role in expanding the complexity of the human genome through the production of specialized proteins regulating organ development and physiological functions, as well as contributing to several pathological conditions. How AS programs impact on the signaling pathways controlling endothelial cell (EC) functions and vascular development is largely unknown. Here we identified, through RNA-seq, changes in mRNA steady-state levels in ECs caused by the neuro-oncological ventral antigen 2 (Nova2), a key AS regulator of the vascular morphogenesis. Bioinformatics analyses identified significant enrichment for genes regulated by peroxisome proliferator-activated receptor-gamma (Ppar-γ) and E2F1 transcription factors. We also showed that Nova2 in ECs controlled the AS profiles of Ppar-γ and E2F dimerization partner 2 (Tfdp2), thus generating different protein isoforms with distinct function (Ppar-γ) or subcellular localization (Tfdp2). Collectively, our results supported a mechanism whereby Nova2 integrated splicing decisions in order to regulate Ppar-γ and E2F1 activities. Our data added a layer to the sequential series of events controlled by Nova2 in ECs to orchestrate vascular biology.

Expression frequency of c-kit isoforms and its prognostic potential in canine mammary tumours

KIT is a tyrosine kinase receptor involved in carcinogenesis. Two alternatively spliced transcripts, differed from presence of four amino acids (GNSK) at exon 9 of c-kit, were identified in various human tumours and canine hemangiosarcoma (HSA). The biological function and clinical implications of these isoforms have not yet been elucidated in canine tumours. The current study aimed to validate the expression profile and ultimately to evaluate the correlation of c-kit isoform levels with clinicopathological factors of canine mammary tumours (CMTs). In total, the expression profiles of c-kit isoforms in 196 samples obtained from normal mammary glands (NMGs) of healthy controls and dogs with CMTs, benign and malignant CMTs, and HSAs were determined by polymerase chain reaction (PCR) and quantified via real-time PCR. Overall, the expression levels of the two isoforms were equivalent in NMGs, whereas the GNSK^- /GNSK⁺ ratio sharply increased to 7.44- and 8.33-fold, indicating abundant GNSK^- isoforms in benign and malignant CMTs, respectively. However, a significant decrease in GNSK^- expression was detected in dogs with high-grade malignant CMTs (mCMTs) and with metastatic CMTs compared with expression in those with a lower grade and non-metastatic CMTs. In addition, the median survival time was shorter in mCMT canines with a lower GNSK^- /GNSK⁺ ratio than that in mCMT canines with a higher ratio (899 days vs 1534 days). In conclusion, two c-kit isoforms are ubiquitously expressed with great variability in HSAs and CMTs with both benign and malignant status. The GNSK^- /GNSK⁺ ratio could serve as a prognostic indicator for dogs with mCMTs.

Construction of a model to predict the prognosis of patients with cholangiocarcinoma using alternative splicing events

Cholangiocarcinoma (CCA) is a type of malignant tumor that originates in the mucosal epithelial cells of the biliary system. It is a highly aggressive cancer that progresses rapidly, has low surgical resection rates and a high recurrence. At present, no prognostic molecular biomarker for CCA has been identified. However, CCA progression is affected by mRNA precursors that modify gene expression levels and protein structures through alternative splicing (AS) events, which create molecular indicators that may potentially be used to predict CCA outcomes. The present study aimed to construct a model to predict CCA prognosis based on AS events. Using prognostic data available from The Cancer Genome Atlas, including the percent spliced index of AS events obtained from TCGASpliceSeq in 32 CCA cases, univariate and multivariate Cox regression analyses were performed to assess the associations between AS events and the overall survival (OS) rates of patients with CCA. Additional multivariate Cox regression analyses were used to identify AS events that were significantly associated with prognosis, which were used to construct a prediction model with a prognostic index (PI). A receiver operating characteristic (ROC) curve was used to determine the predictive value of the PI, and Pearson's correlation analysis was used to determine the association between OS-related AS events and splicing factors. A total of 38,804 AS events were identified in 9,673 CCA genes, among which univariate Cox regression analysis identified 1,639 AS events associated with OS (P<0.05); multivariate Cox regression analysis narrowed this list to 23 CCA AS events (P<0.001). The final PI model was constructed to predict the survival of patients with CCA; the ROC curve demonstrated that it had a high predictive power for CCA prognosis, with a highest area under the curve of 0.986. Correlations between 23 OS-related AS events and splicing factors were also noted, and may thus, these AS events may be used to improve predictions of OS. In conclusion, AS events exhibited potential for predicting the prognosis of patients with CCA, and thus, the effects of AS events in CCA required further examination.

Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data

Alternative splicing in tumor cells may be used as a molecular marker for the differential diagnosis of certain tumor types and assessment of prognosis. The aim of the present study was to investigate the associations among alternative splicing events, splicing factors, and the survival of patients with hepatocellular carcinoma (HCC). The alternative splicing event profiles of 371 patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq data, and the percent-splice-in value for each splicing event was calculated. The association between alternative splicing events and overall survival was evaluated. The most significant prognosis-related splicing events were used to build up a prognostic index (PI). A total of 3,082 survival-associated alternative splicing events were detected in HCC. The final PI based on all of the most significant candidate alternative splicing events exhibited better performance in distinguishing good or poor survival in patients compared to the PI based on a single type of splicing event. Receiver operating characteristic curves confirmed the high efficiency of the PI in predicting the survival of HCC patients, with an area under the curve of 0.914. The overexpression of 32 prognosis-related splicing factor genes could also predict poor prognosis in patients with HCC. In conclusion, the constructed computational prognostic model based on HCC-specific alternative splicing events may be used as a molecular marker for the prognosis of HCC.

Alternative splicing-derived intersectin1-L and intersectin1-S exert opposite function in glioma progression

Intersectin1 (ITSN1) contains two isoforms: ITSN1-S and ITSN1-L, which is highly regulated by alternative splicing. However, the alteration of alternative splicing and its importance in cancer is still unknown. In this study, our transcriptome analysis by using a large glioma cohort indicated the two isoforms exerted opposite function in glioma progression. Our previous results had shown ITSN1-S could promote glioma development; however, the function of ITSN1-L remained unknown. In this study, we first confirmed that ITSN1-L exerted an inhibitory role in glioma progression both in vivo and in vitro, which was contrary to the function of ITSN1-S. In additional, we also elucidated the mechanisms of ITSN1-L in inhibiting tumor progression. First, we revealed ITSN1-L could interact with α-tubulin to promote HDAC6-dependent deacetylation of ac-tubulin leading to decreased cell motility. Second, ITSN1-L could attenuate cell-substrate adhesion through FAK/integrin β3 pathway. Third, ITSN1-L was able to strengthen cell-cell adhesion by upregulating N-cadherin expression and its re-localization to membrane by ANXA2 and TUBB3/TUBB4. In conclusion, we found for the first time that two isoforms produced by alternative splicing exerted opposite functions in glioma development. Therefore, upregulation of ITSN1-L expression as well as downregulation of ITSN1-S expression probably was a better strategy in glioma treatment. Our present study laid a foundation for the importance of alternative splicing in glioma progression and raised the possibility of controlling glioma development completely at an alternative splicing level to be a more effective strategy.

Alternative splicing, RNA-seq and drug discovery

Alternative splicing, hereafter referred to as AS, is an essential component of gene expression regulation that contributes to the diversity of proteomes. Recent developments in RNA sequencing (RNA-seq) technologies, combined with the advent of computational tools, have enabled transcriptome-wide studies of AS at an unprecedented scale and resolution. RNA mis-splicing can cause human disease, and to target alternative splicing has led to the development of novel therapeutics. Splice variants diversify the repertoire of biomarkers and functionally contribute to drug resistance. Our expanding knowledge of AS variation in human populations holds great promise for improving disease diagnoses and ultimately patient care in the era of sequencing and precision medicine.

Netrin Family: Role for Protein Isoforms in Cancer

Netrins form a family of secreted and membrane-associated proteins. Netrins are involved in processes for axonal guidance, morphogenesis, and angiogenesis by regulating cell migration and survival. These processes are of special interest in tumor biology. From the netrin genes various isoforms are translated and regulated by alternative splicing. We review here the diversity of isoforms of the netrin family members and their known and potential roles in cancer.

Network-based approach to identify principal isoforms among four cancer types

Protein isoforms are structurally similar proteins produced by alternative splicing of a single gene or genes from the same family. Isoforms of a protein can perform the same, similar, or even opposite biological functions. A previous study identified principal isoforms of proteins based on the extent of interactions per isoform in a functional relationship network, focusing on data from normal tissues. Additionally, the expression levels of specific isoforms of various genes associated with tumorigenesis and prognosis are frequently altered in tumors compared with those in normal tissues. In this study, we aimed to identify higher degree isoforms (HDIs) of multi-isoform genes (MIGs) in cancer by applying a meta-analytical framework to calculate co-expression between each pair of isoforms in two large datasets of RNA-seq profiles from breast cancer, lung cancer, leukemia, and colon cancer cell lines. Then, we compared HDIs with isoforms identified by proteomic data and prognostic and predictive evidence in various cancers. In addition, we separately analyzed the associations between HDIs and non-HDIs (nHDIs) of the same genes according to transcript expression and drug responses in various cancer type cell lines. Collectively, these results indicated the complex properties of HDIs per gene identified by cancer type-based isoform-isoform co-expression networks and showed the potential of HDIs as novel therapeutic targets for cancer treatment.

Biological classification with RNA-seq data: Can alternatively spliced transcript expression enhance machine learning classifiers?

RNA sequencing (RNA-seq) is becoming a prevalent approach to quantify gene expression and is expected to gain better insights into a number of biological and biomedical questions compared to DNA microarrays. Most importantly, RNA-seq allows us to quantify expression at the gene or transcript levels. However, leveraging the RNA-seq data requires development of new data mining and analytics methods. Supervised learning methods are commonly used approaches for biological data analysis that have recently gained attention for their applications to RNA-seq data. Here, we assess the utility of supervised learning methods trained on RNA-seq data for a diverse range of biological classification tasks. We hypothesize that the transcript-level expression data are more informative for biological classification tasks than the gene-level expression data. Our large-scale assessment utilizes multiple data sets, organisms, lab groups, and RNA-seq analysis pipelines. Overall, we performed and assessed 61 biological classification problems that leverage three independent RNA-seq data sets and include over 2000 samples that come from multiple organisms, lab groups, and RNA-seq analyses. These 61 problems include predictions of the tissue type, sex, or age of the sample, healthy or cancerous phenotypes, and pathological tumor stages for the samples from the cancerous tissue. For each problem, the performance of three normalization techniques and six machine learning classifiers was explored. We find that for every single classification problem, the transcript-based classifiers outperform or are comparable with gene expression-based methods. The top-performing techniques reached a near perfect classification accuracy, demonstrating the utility of supervised learning for RNA-seq based data analysis.

The Splicing Factor PTBP1 Promotes Expression of Oncogenic Splice Variants and Predicts Poor Prognosis in Patients with Non-muscle-Invasive Bladder Cancer

Purpose: Non-muscle-invasive bladder cancer (NMIBC) is a malignant disease characterized by high heterogeneity, which corresponds to dysregulated gene expression and alternative splicing (AS) profiles. Bioinformatics analyses of splicing factors potentially linked to bladder cancer progression identified the heterogeneous nuclear ribonucleoprotein I (i.e., PTBP1) as candidate. This study aimed at investigating whether PTBP1 expression associates with clinical outcome in patients with NMIBC.Experimental Design: A cohort of 152 patients presenting with primary NMIBC (pTa-pT1) was enrolled. Primary NMIBCs were assessed for PTBP1 expression by IHC, and the results were correlated with clinical data using Kaplan-Meier curves and Cox regression analyses. Cell proliferation and survival assays were performed to assess the function of PTBP1. Furthermore, the impact of PTBP1 on the AS pattern of specific bladder cancer-related genes was investigated in cancer cell lines and in patients' specimens.Results: Public datasets querying highlighted a positive correlation between PTBP1 expression and NMIBC progression, which was then confirmed by IHC analysis. High PTBP1 expression was associated with worse clinical outcome in terms of incidence of tumor relapse and survival in patients with NMIBC. Interestingly, downregulation of PTBP1 in bladder cancer cell lines affected prosurvival features. Accordingly, PTBP1 modulated AS of bladder cancer-related genes in cell lines and patient's specimens.Conclusions: PTBP1 expression correlates with disease progression, poor prognosis, and worse survival in patients with NMIBC. Downregulation of PTBP1 expression affects prosurvival features of bladder cancer cells and modulates AS of genes with relevance for bladder cancer, suggesting its role as an outcome-predictor in this disease. Clin Cancer Res; 24(21); 5422-32. ©2018 AACR.

Integrative analysis reveals functional and regulatory roles of H3K79me2 in mediating alternative splicing

Background

Accumulating evidence suggests alternative splicing (AS) is a co-transcriptional splicing process not only controlled by RNA-binding splicing factors, but also mediated by epigenetic regulators, such as chromatin structure, nucleosome density, and histone modification. Aberrant AS plays an important role in regulating various diseases, including cancers.

Methods

In this study, we integrated AS events derived from RNA-seq with H3K79me2 ChIP-seq data across 34 different normal and cancer cell types and found the higher enrichment of H3K79me2 in two AS types, skipping exon (SE) and alternative 3′ splice site (A3SS).

Results

Interestingly, by applying self-organizing map (SOM) clustering, we unveiled two clusters mainly comprised of blood cancer cell types with a strong correlation between H3K79me2 and SE. Remarkably, the expression of transcripts associated with SE was not significantly different from that of those not associated with SE, indicating the involvement of H3K79me2 in splicing has little impact on full mRNA transcription. We further showed that the deletion of DOT1L1, the sole H3K79 methyltransferase, impeded leukemia cell proliferation as well as switched exon skipping to the inclusion isoform in two MLL-rearranged acute myeloid leukemia cell lines. Our data demonstrate H3K79me2 was involved in mediating SE processing, which might in turn influence transformation and disease progression in leukemias.

Conclusions

Collectively, our work for the first time reveals that H3K79me2 plays functional and regulatory roles through a co-transcriptional splicing mechanism.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0538-1) contains supplementary material, which is available to authorized users.

The Expanding Landscape of Alternative Splicing Variation in Human Populations

Alternative splicing is a tightly regulated biological process by which the number of gene products for any given gene can be greatly expanded. Genomic variants in splicing regulatory sequences can disrupt splicing and cause disease. Recent developments in sequencing technologies and computational biology have allowed researchers to investigate alternative splicing at an unprecedented scale and resolution. Population-scale transcriptome studies have revealed many naturally occurring genetic variants that modulate alternative splicing and consequently influence phenotypic variability and disease susceptibility in human populations. Innovations in experimental and computational tools such as massively parallel reporter assays and deep learning have enabled the rapid screening of genomic variants for their causal impacts on splicing. In this review, we describe technological advances that have greatly increased the speed and scale at which discoveries are made about the genetic variation of alternative splicing. We summarize major findings from population transcriptomic studies of alternative splicing and discuss the implications of these findings for human genetics and medicine.

The effects of alternative splicing on miRNA binding sites in bladder cancer

Eukaryotic organisms have developed a variety of mechanisms to regulate translation post-transcriptionally, including but not limited to the use of miRNA silencing in many species. One method of post-transcriptional regulation is through miRNAs that bind to the 3′ UTRs to regulate mRNA abundance and influence protein expression. Therefore, the diversity of mRNA 3′ UTRs mediating miRNA binding sites influence miRNA-mediated regulation. Alternative polyadenylation, by shortening mRNA isoforms, increases the diversity of 3′ UTRs; moreover, short mRNA isoforms elude miRNA-medicated repression. Because no current prediction methods for putative miRNA target sites consider whether or not 1) splicing-informed miRNA binding sites and/or 2) the use of 3′ UTRs provide higher resolution or functionality, we sought to identify not only the genome-wide impact of using exons in mRNA 3′ UTRs but also their functional connection to miRNA regulation and clinical outcomes in cancer. With a genome-wide expression of mRNA and miRNA quantified by 395 bladder cancer cases from The Cancer Genome Atlas (TCGA), we 1) demonstrate the diversity of 3′ UTRs affecting miRNA efficiency and 2) identify a set of genes clinically associated with mRNA expression in bladder cancer. Knowledge of 3′ UTR diversity will not only be a useful addition to current miRNA target prediction algorithms but also enhance the clinical utility of mRNA isoforms in the expression of mRNA in cancer. Thus, variability among cancer patient’s variability in molecular signatures based on these exon usage events in 3′ UTR along with miRNAs in bladder cancer may lead to better prognostic/treatment strategies for improved precision medicine.

The role of alternative splicing in cancer

The functional capacity of cells is defined by the transcriptome. Many recent studies have identified variations in the transcriptome of tumors due to alternative splicing changes, as well as mutations in splicing factors and regulatory signals in most tumor types. Some of these alterations have been linked to tumor progression, metastasis, therapy resistance, and other oncogenic processes. Here, we describe the different mechanisms that drive splicing changes in tumors and their impact in cancer. Motivated by the current evidence, we propose a model whereby a subset of the splicing patterns contributes to the definition of specific tumor phenotypes, and may hold potential for the development of novel clinical biomarkers and therapeutic approaches.