Opportunities and methods for studying alternative splicing in cancer with RNA-Seq

Research and application of omics and artificial intelligence in cancer

Cancer has a high incidence and lethality rate, which is a significant threat to human health. With the development of high-throughput technologies, different types of cancer genomics data have been accumulated, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. A comprehensive analysis of various omics data is needed to understand the underlying mechanisms of tumor development. However, integrating such a massive amount of data is one of the main challenges today. Artificial intelligence (AI) techniques such as machine learning are now becoming practical tools for analyzing and understanding multi-omics data on diseases. Enabling great optimization of existing research paradigms for cancer screening, diagnosis, and treatment. In addition, intelligent healthcare has received widespread attention with the development of healthcare informatization. As an essential part of innovative healthcare, practical, intelligent prognosis analysis and personalized treatment for cancer patients are also necessary. This paper introduces the advanced multi-omics data analysis technology in recent years, presents the cases and advantages of the combination of both omics data and AI applied to cancer diseases, and finally briefly describes the challenges faced by multi-omics analysis and AI at the current stage, aiming to provide new perspectives for oncology research and the possibility of personalized cancer treatment.

Translatome analysis in acute ischemic stroke: Astrocytes and microglia exhibit differences in poststroke alternative splicing of expressed transcripts

Astrocytes and microglia undergo dynamic and complex morphological and functional changes following ischemic stroke, which are instrumental in both inflammatory responses and neural repair. While gene expression alterations poststroke have been extensively studied, investigations into posttranscriptional regulatory mechanisms, specifically alternative splicing (AS), remain limited. Utilizing previously reported Ribo-Tag-seq data, this study analyzed AS alterations in poststroke astrocytes and microglia from young adult male and female mice. Our findings reveal that in astrocytes, compared to the sham group, 109 differential alternative splicing (DAS) events were observed at 4 h poststroke, which increased to 320 at day 3. In microglia, these numbers were 316 and 266, respectively. Interestingly, the disparity between DAS genes and differentially expressed genes is substantial, with fewer than 10 genes shared at both poststroke time points in astrocytes and microglia. Gene ontology enrichment analysis revealed the involvement of these DAS genes in diverse functions, encompassing immune response (Adam8, Ccr1), metabolism (Acsl6, Pcyt2, Myo5a), and developmental cell growth (App), among others. Selective DAS events were further validated by semiquantitative RT-PCR. Overall, this study comprehensively describes the AS alterations in astrocytes and microglia during the hyperacute and acute phases of ischemic stroke and underscores the significance of certain hub DAS events in neuroinflammatory processes.

Glioblastoma vaccines: past, present, and opportunities

Glioblastoma (GBM) is one of the most lethal central nervous systems (CNS) tumours in adults. As supplements to standard of care (SOC), various immunotherapies improve the therapeutic effect in other cancers. Among them, tumour vaccines can serve as complementary monotherapy or boost the clinical efficacy with other immunotherapies, such as immune checkpoint blockade (ICB) and chimeric antigen receptor T cells (CAR-T) therapy. Previous studies in GBM therapeutic vaccines have suggested that few neoantigens could be targeted in GBM due to low mutation burden, and single-peptide therapeutic vaccination had limited efficacy in tumour control as monotherapy. Combining diverse antigens, including neoantigens, tumour-associated antigens (TAAs), and pathogen-derived antigens, and optimizing vaccine design or vaccination strategy may help with clinical efficacy improvement. In this review, we discussed current GBM therapeutic vaccine platforms, evaluated and potential antigenic targets, current challenges, and perspective opportunities for efficacy improvement.

Alternative Splicing Landscape of Head and Neck Squamous Cell Carcinoma

Head and neck malignancies are a significant global health concern, with head and neck squamous cell carcinoma (HNSCC) being the sixth most common cancer worldwide accounting for > 90% of cases. In recent years, there has been growing recognition of the potential role of alternative splicing (AS) in the etiology of cancer. Increasing evidence suggests that AS is associated with various aspects of cancer progression, including tumor occurrence, invasion, metastasis, and drug resistance. Additionally, AS is involved in shaping the tumor microenvironment, which plays a crucial role in tumor development and response to therapy. AS can influence the expression of factors involved in angiogenesis, immune response, and extracellular matrix remodeling, all of which contribute to the formation of a supportive microenvironment for tumor growth. Exploring the mechanism of AS events in HNSCC could provide insights into the development and progression of this cancer, as well as its interaction with the tumor microenvironment. Understanding how AS contributes to the molecular changes in HNSCC cells and influences the tumor microenvironment could lead to the identification of new therapeutic targets. Targeted chemotherapy and immunotherapy strategies tailored to the specific AS patterns in HNSCC could potentially improve treatment outcomes and reduce side effects. This review explores the concept, types, processes, and technological advancements of AS, focusing on its role in the initiation, progression, treatment, and prognosis of HNSCC.

Long-read sequencing reveals the landscape of aberrant alternative splicing and novel therapeutic target in colorectal cancer

BACKGROUND

Alternative splicing complexity plays a vital role in carcinogenesis and cancer progression. Improved understanding of novel splicing events and the underlying regulatory mechanisms may contribute new insights into developing new therapeutic strategies for colorectal cancer (CRC).

METHODS

Here, we combined long-read sequencing technology with short-read RNA-seq methods to investigate the transcriptome complexity in CRC. By using experiment assays, we explored the function of newly identified splicing isoform TIMP1 Δ4-5. Moreover, a CRISPR/dCasRx-based strategy to induce the TIMP1 exon 4-5 exclusion was introduced to inhibit neoplasm growth.

RESULTS

A total of 90,703 transcripts were identified, of which > 62% were novel compared with current transcriptome annotations. These novel transcripts were more likely to be sample specific, expressed at relatively lower levels with more exons, and oncogenes displayed a characteristic to generate more transcripts in CRC. Clinical outcome data analysis showed that 1472 differentially expressed alternative splicing events (DEAS) were tightly associated with CRC patients' prognosis, and many novel isoforms were likely to be important determinants for patient survival. Among these, newly identified splicing isoform TIMP1 Δ4-5 was significantly downregulated in CRC. Further in vitro and in vivo assays demonstrated that ectopic expression of TIMP1 Δ4-5 significantly suppresses tumor cell growth and metastasis. Serine/arginine-rich splicing factor 1 (SRSF1) acts as a onco-splicing regulator through sustaining the inclusion of TIMP1 exon 4-5. Furthermore, CRISPR/dCasRx-based strategies designed to induce TIMP1 exon 4-5 exclusion have the potential to restrain the CRC growth.

CONCLUSIONS

This data provides a rich resource for deeper studies of gastrointestinal malignancies. Newly identified splicing isoform TIMP1 Δ4-5 plays an important role in mediating CRC progression and may be a potential therapy target in CRC.

Coexpression of Tail Fiber and Tail Protein Genes of the Cyanophage PP Using a Synthetic Genomics Approach Enhances the Salt Tolerance of Synechocystis PCC 6803

Cyanophages are viruses that specifically infect cyanobacteria and are capable of regulating the population densities and seasonal distributions of cyanobacteria. However, few studies have investigated the interactions between cyanophages and heterologous hosts, owing to the inability of cyanophages to infect heterologous cyanobacterial hosts. Here, a truncated artificial cyanophage genome, Syn-P4-8, was designed and assembled that contained 18 genes for viral coat assembly proteins but not genes related to host infection or DNA replication. Syn-P4-8 was transferred into the heterologous host Synechocystis sp. PCC 6803 by conjugation. The growth of strain CS-02 carrying Syn-P4-8 was significantly better than that of the control strain when grown in medium containing 5% NaCl. Only two cyanophage genes, encoding the tail protein (open reading frame 25 [ORF25]) and the tail fiber protein (ORF26), were transcribed in Synechocystis PCC 6803 grown in BG11 medium supplemented with 5% NaCl. However, expression of either ORF25 or ORF26 alone could not recover this phenotype. In addition, transcriptomic analysis revealed the presence of 334 differentially expressed genes in CS-02 compared to the control strain, corresponding to 151 downregulated and 183 upregulated genes that may affect cyanobacterial salt tolerances. In this study, synthetic biology methods were used to strengthen our understanding of the interactions between cyanophage genes and heterologous hosts. IMPORTANCE We synthesized and assembled a truncated cyanophage genome called Syn-P4-8, containing 18 genes for viral coat assembly proteins, and transferred it into a nonhost strain, Synechocystis sp. PCC 6803, to investigate interactions between Syn-P4-8 and Synechocystis PCC 6803. We found that coexpression of tail fiber and tail protein genes enhanced the salt tolerance of Synechocystis PCC 6803.

The Role of Alternative Splicing Factors, DDB2-Related Ageing and DNA Damage Repair in the Progression and Prognosis of Stomach Adenocarcinoma Patients

DNA damage response is a key signal transduction pathway in triggering ageing and tumor progression. Abnormal alternative splicing (AS) is associated with tumors and ageing. However, the role of AS factors associated with DNA damage repair and ageing in stomach adenocarcinoma (STAD) remains unclear. We downloaded the percentage of splicing (PSI) values for AS in STAD from the TCGA SpliceSeq database. The PSI values of DNA repair gene AS events were integrated with STAD patient survival data for Cox regression analysis. The prediction model for the overall survival (OS) was constructed by the clinical traits. The tumor immune microenvironment was analyzed by CIBERSORT and ESTIMATE. We detected 824 AS events originating from 166 DNA repair genes. Cox regression analysis provided 21 prognostic AS events connected with OS statistically, and a prognostic prediction model was constructed. The expression of these AS factors was higher in STAD tumors. DDB2 high senescence levels were associated with active immune responses and better survival in STAD patients. We built a novel prognostic model founded on DNA repair genes with AS events and identified that DDB2 may be a potential biomarker to apply in clinics.

Circulating cell-free messenger RNA enables non-invasive pan-tumour monitoring of melanoma therapy independent of the mutational genotype

BACKGROUND

Plasma-derived tumour-specific cell-free nucleic acids are increasingly utilized as a minimally invasive, real-time biomarker approach in many solid tumours. Circulating tumour DNA of melanoma-specific mutations is currently the best studied liquid biopsy biomarker for melanoma. However, the combination of hotspot genetic alterations covers only around 80% of all melanoma patients. Therefore, alternative approaches are needed to enable the follow-up of all genotypes, including wild-type.

METHODS

We identified KPNA2, DTL, BACE2 and DTYMK messenger RNA (mRNA) upregulated in melanoma versus nevi tissues by unsupervised data mining (N = 175 melanoma, N = 20 normal skin, N = 6 benign nevi) and experimentally confirmed differential mRNA expression in vitro (N = 18 melanoma, N = 8 benign nevi). Circulating cell-free RNA (cfRNA) was analysed in 361 plasma samples (collected before and during therapy) from 100 melanoma patients and 18 healthy donors. Absolute cfRNA copies were quantified on droplet digital PCR.

RESULTS

KPNA2, DTL, BACE2 and DTYMK cfRNA demonstrated high diagnostic accuracy between melanoma patients' and healthy donors' plasma (AUC > 86%, p < .0001). cfRNA copies increased proportionally with increasing tumour burden independently of demographic variables and even remained elevated in individuals with radiological absence of disease. Re-analysis of single-cell transcriptomes revealed a pan-tumour origin of cfRNA, including endothelial, cancer-associated fibroblasts, macrophages and B cells beyond melanoma cells as cellular sources. Low baseline cfRNA levels were associated with significantly longer progression-free survival (PFS) (KPNA2 HR = .54, p = .0362; DTL HR = .60, p = .0349) and overall survival (KPNA2 HR = .52, p = .0237; BACE2 HR = .55, p = .0419; DTYMK HR = .43, p = .0393). Lastly, we found that cfRNA copies significantly increased during therapy in non-responders compared to responders regardless of therapy and mutational subtypes and that the increase of KPNA2 (HR = 1.73, p = .0441) and DTYMK (HR = 1.82, p = .018) cfRNA during therapy was predictive of shorter PFS.

CONCLUSIONS

In sum, we identified a new panel of cfRNAs for a pan-tumour liquid biopsy approach and demonstrated its utility as a prognostic, therapy-monitoring tool independent of the melanoma mutational genotype.

New bladder cancer non-invasive surveillance method based on voltammetric electronic tongue measurement of urine

Bladder cancer (BC) is the sixth leading cause of death by cancer. Depending on the invasiveness of tumors, patients with BC will undergo surgery and surveillance lifelong, owing the high rate of recurrence and progression. In this context, the development of strategies to support non-invasive BC diagnosis is focusing attention. Voltammetric electronic tongue (VET) has been demonstrated to be of use in the analysis of biofluids. Here, we present the implementation of a VET to study 207 urines to discriminate BC and non-BC for diagnosis and surveillance to detect recurrences. Special attention has been paid to the experimental setup to improve reproducibility in the measurements. PLSDA analysis together with variable selection provided a model with high sensitivity, specificity, and area under the ROC curve AUC (0.844, 0.882, and 0.917, respectively). These results pave the way for the development of non-invasive low-cost and easy-to-use strategies to support BC diagnosis and follow-up.

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Bladder cancer (BC) and control urines were studied by voltammetric electronic tongue

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A PLSDA model was obtained with high sensitivity, specificity, and accuracy (84/88/86)

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103/122 BC urines and 7⅝5 control urines were predicted correctly

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The electronic tongue has the potential for non-invasive BC diagnostics and follow-up

Alternative splicing patterns reveal prognostic indicator in muscle-invasive bladder cancer

Background

Bladder cancer is one of the most lethal malignancy in urological system, and 20–25% of bladder cancer patients are muscle invasive with unfavorable prognosis. However, the role of alternative splicing (AS) in muscle-invasive bladder cancer (MIBC) remains to be elucidated.

Methods

Percent spliced in (PSI) data obtained from the Cancer Genome Atlas (TCGA) SpliceSeq database (n = 394) were utilized to evaluate the AS events in MIBC. Prognosis-associated AS events were screened out by univariate Cox regression. LASSO Cox regression was used to identify reliable prognostic patterns in a training set and further validated in a test set. Splicing regulatory networks were constructed by correlations between PSI of AS events and RNA expression of splicing factors.

Results

As a result, a total of 2589 prognosis-related AS events in MIBC were identified. Pathways of spliceosomal complex (FDR = 0.017), DNA-directed RNA polymerase II, core complex (FDR = 0.032), and base excision repair (FDR = 0.038) were observed to be significantly enriched. Additionally, we noticed that most of the prognosis-related AS events were favorable factors. According to the LASSO and multivariate Cox regression analyses, 15-AS-based signature was established with the area under curve (AUC) of 0.709, 0.823, and 0.857 at 1-, 3-, and 5- years, respectively. The MIBC patients were further divided into high- and low-risk groups based on median risk sores. Interestingly, we observed that the prevalence of FGFR3 with mutations and focal amplification was significantly higher in low-risk group. Functional and immune infiltration analysis suggested potential signaling pathways and distinct immune states between these two groups. Moreover, splicing correlation network displayed a regulatory mode of prognostic splicing factors (SF) in MIBC patients.

Conclusions

This study not only provided novel insights into deciphering the possible mechanism of tumorgenesis and pathogenesis but also help refine risk stratification systems and potential treatment of decision-making for MIBC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02685-0.

Landscape of Alternative Splicing Events Related to Prognosis and Immune Infiltration in Glioma: A Data Analysis and Basic Verification

Background

Glioma is a prevalent primary brain cancer with high invasiveness and typical local diffuse infiltration. Alternative splicing (AS), as a pervasive transcriptional regulatory mechanism, amplifies the coding capacity of the genome and promotes the progression of malignancies. This study was aimed at identifying AS events and novel biomarkers associated with survival for glioma.

Methods

RNA splicing patterns were collected from The Cancer Genome Atlas SpliceSeq database, followed by calculating the percentage of splicing index. Expression profiles and related clinical information of glioma were integrated based on the UCSC Xena database. The AS events in glioma were further analyzed, and glioma prognosis-related splicing factors were identified with the use of bioinformatics analysis and laboratory techniques. Further immune infiltration analysis was performed.

Results

Altogether, 9028 AS events were discovered. Upon univariate Cox analysis, 425 AS events were found to be related to the survival of patients with glioma, and 42 AS events were further screened to construct the final prognostic model (area under the curve = 0.974). Additionally, decreased expression of the splicing factors including Neuro-Oncological Ventral Antigen 1 (NOVA1), heterogeneous nuclear ribonucleoprotein C (HNRNPC), heterogeneous nuclear ribonucleoprotein L-like protein (HNRNPLL), and RNA-Binding Motif Protein 4 (RBM4) contributed to the poor survival in glioma. The immune infiltration analysis demonstrated that AS events were related to the proportion of immune cells infiltrating in glioma.

Conclusions

It is of great value for comprehensive consideration of AS events, splicing networks, and related molecular subtype clusters in revealing the underlying mechanism and immune microenvironment remodeling for glioma, which provides clues for the further verification of related therapeutic targets.

Identification and characterization of alternative splicing variants of buffalo LXRα expressed in mammary gland

Liver X receptor α (LXRα) is a ligand-dependent transcription factor and plays an important role in the regulation of cholesterol homeostasis, fatty acid biosynthesis and glucose metabolism. In this study, transcripts of LXRα gene were cloned and characterized from buffalo mammary gland, and three alternative splicing transcripts of buffalo LXRα gene were identified, named LXRα1, LXRα2 and LXRα3. The structure of the LXRα transcripts of buffalo and cattle was highly similar. Bioinformatics analysis showed that LXRα1 contains two complete functional domains of LXRα, one is the DNA-binding domain (NR_DBD_LXR) and the other is the ligand-binding domain (NR_LBD_LXR). The reading frame of LXRα2 is altered due to the skipping of exon 9, which truncates its encoding protein prematurely at the 400th amino acid residue, making it contain a complete DNA-binding domain and part of a ligand-binding domain. Due to the deletion of exon 4, the protein encoded by LXRα3 lacks 89 amino acid residues and contains only a complete ligand-binding domain, which makes it lose its transcriptional regulation function. In addition, motifs and conserved domains of three LXRα variants of buffalo were highly consistent with those of corresponding transcripts from other mammal species. Subcellular localization analysis showed that LXRα1 plays a functional role in the nucleus of buffalo mammary epithelial cells, while LXRα2 and LXRα3 are distributed in the nucleus and cytoplasm. Compared with non-lactating period, the mRNA abundance of the three LXRα transcripts in the mammary gland tissue of buffalo increased during lactating period, revealing that they play a key role in the synthesis of buffalo milk fat. Among the three LXRα transcripts, LXRα1 has the highest expression in the mammary gland, indicating that it is the major transcript in the mammary gland and has important regulatory functions, while LXRα2 and LXRα3 may have regulatory effects on the function of LXRα1. This study highlights the key role of LXRα alternative splicing in the post-transcriptional regulation of buffalo lactation.

Systematic Genome-Wide Profiles Reveal Alternative Splicing Landscape and Implications of Splicing Regulator DExD-Box Helicase 21 in Aggressive Progression of Adrenocortical Carcinoma

Alternative splicing (AS) in the tumor biological process has provided a novel perspective on carcinogenesis. However, the clinical significance of individual AS patterns of adrenocortical carcinoma (ACC) has been underestimated, and in-depth investigations are lacking. We selected 76 ACC samples from the Cancer Genome Atlas (TCGA) SpliceSeq and SpliceAid2 databases, and 39 ACC samples from Fudan University Shanghai Cancer Center (FUSCC). Prognosis-related AS events (PASEs) and survival analysis were evaluated based on prediction models constructed by machine-learning algorithm. In total, 23,984 AS events and 3,614 PASEs were detected in the patients with ACC. The predicted risk score of each patient suggested that eight PASEs groups were significantly correlated with the clinical outcomes of these patients (p < 0.001). Prognostic models produced AUC values of 0.907 in all PASEs' groups. Eight splicing factors (SFs), including BAG2, CXorf56, DExD-Box Helicase 21 (DDX21), HSPB1, MBNL3, MSI1, RBMXL2, and SEC31B, were identified in regulatory networks of ACC. DDX21 was identified and validated as a novel clinical promoter and therapeutic target in 115 patients with ACC from TCGA and FUSCC cohorts. In conclusion, the strict standards used in this study ensured the systematic discovery of profiles of AS events using genome-wide cohorts. Our findings contribute to a comprehensive understanding of the landscape and underlying mechanism of AS, providing valuable insights into the potential usages of DDX21 for predicting prognosis for patients with ACC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-021-00026-x.

Analysis of Genome-Wide Alternative Splicing Profiling and Development of Potential Drugs in Lung Adenocarcinoma

Alternative splicing (AS) is significantly related to tumor development as well as a patient’s clinical characteristics. This study was designed to systematically analyze the survival-associated AS signatures in Lung adenocarcinoma (LUAD). Among 30,735 AS events in 9,635 genes, we found that there were 1,429 AS in 1,125 genes which were conspicuously related to the overall survival of LUAD patients. Then, according to the seven types of AS events, we established AS signatures and constructed a new combined prognostic model. The Kaplan-Meier curve results showed that seven types of AS signatures and the combined prognostic model could divide patients into distinct prognoses. The ROC curve shows that all eight AS signatures had powerful predictive properties with different AUCs ranging from 0.708 to 0.849. Additionally, the elevated risk scores were positively related to higher TNM stage and metastasis. Interestingly, AS events and splicing factors (SFs) network shed light on a meaningful connection between prognostic AS genes and corresponding SFs. Moreover, we found that the combined prognostic model signature has a higher predictive ability than the mRNA signature. Furthermore, tumors at high risk might evade immune recognition by decreasing the expression of antigen presentation genes. Finally, we predicted the three most significant small molecule drugs to inhibit LUAD. Among them, NVP-AUY922 had the lowest IC50 value and might become a potential drug to prolong a patient’s survival. In conclusion, our study established a potential prognostic signature for LUAD patients, revealed a splicing network between AS and SFs and possible immune escape mechanism, and provided several small-molecule drugs to inhibit tumorigenesis.

Analysis of Prognostic Alternative Splicing Reveals the Landscape of Immune Microenvironment in Thyroid Cancer

Background

The incidence of thyroid cancer (THCA) continues to increase in recent decades. Accumulating evidence showed that the unbalanced alternative splicing (AS) promotes the occurrence of cancers and leads to poor prognosis of patients. However, the research on alternative splicing events in THCA is lacking, and its underlying mechanism is not fully understood. This study identifies a novel prognostic signature based on AS events to reveal the relationship of AS with tumor immune microenvironment.

Methods

Based on the AS data, transcriptional data, and clinical information, the differentially expressed alternative splicings (DEASs) were screened out. Least absolute shrinkage and selection operator (LASSO) regression and multi-Cox regression analyses were employed to identify prognostic results related to AS events and establish a prognostic signature. The predictive ability of the signature was assessed by Kaplan-Meier (K-M) survival curve, risk plots, and receiver operating characteristic (ROC) curves. Furthermore, correlations between tumor-infiltrating immune cells, immune checkpoints, immune score and prognostic signature were analyzed.

Results

According to the LASSO regression analysis, a total of five AS events were selected to construct the signature. K-M survival curve showed that the higher the risk score, the worse the OS of the patients. Risk plots further confirmed this result. ROC curves indicated the high predictive efficiency of the prognostic signature. As for tumor immune microenvironment, patients in the high-risk group had a higher proportion of immune cells, including plasma cell, CD8+ T cell, macrophages (M0 and M2), and activated dendritic cell. Immune checkpoint proteins, such as PDCD1LG2, HAVCR2, CD274, etc., were significantly higher in the high-risk group. We also found that the ESTIMATE score, stromal score, and immune score were lower in the high-risk group, while the result of tumor purity was the opposite.

Conclusions

Collectively, a prognostic signature consisting of five AS events in THCA was established. Furthermore, there was an inextricable correlation between immune cell infiltration, immune checkpoint proteins, and AS events. This study will provide a basis for THCA immunotherapy in the future.

Discovery and Verification of Key Liver Cancer Genes and Alternative Splicing Events Based on Second-Generation Sequencing Data Analysis

Hepatocellular carcinoma (HCC) is the most common malignant liver disease in the world. Existing screening and early diagnosis methods are not highly sensitive for HCC, and patients are likely to develop the disease to the middle and advanced stages before being diagnosed. Therefore, finding new and efficient diagnosis and treatment methods has become an urgent problem. We aimed at finding and verifying new liver cancer markers by combining informatics analysis with experimental exploration to provide new ideas and methods for the diagnosis and treatment of clinical liver cancer. We used two different bioinformatic pipelines to analyze sequencing data of clinical liver cancer samples and identify differentially expressed genes and key variants after combining them with The Cancer Genome Atlas sequencing data. Then, we explored the functions and mechanisms of the key variants to identify potential liver cancer markers. Through bioinformatic analysis of sequencing data, 139 differentially expressed genes were found, including 53 upregulated genes and 86 downregulated genes. Through enrichment and alternative splicing event analysis of sequencing data, we found nine key variants with exon skipping events. Metallothionein 1E (MT1E)-203 was found to be a key variant that influenced cell proliferation through the p53 cell cycle pathway through cell viability and proliferation assays, and MT1E-203 lost the ability to bind two zinc ions due to exon skipping according to the structure prediction of MT1E-203. MT1E-203 is a potential biomarker for HCC and may play an important role in the diagnosis and treatment of HCC.

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.

Correlations Between the Characteristics of Alternative Splicing Events, Prognosis, and the Immune Microenvironment in Breast Cancer

Objective

Alternative splicing (AS) is the mechanism by which a few genes encode numerous proteins, and it redefines the concept of gene expression regulation. Recent studies showed that dysregulation of AS was an important cause of tumorigenesis and microenvironment formation. Therefore, we performed a systematic analysis to examine the role of AS in breast cancer (Breast Cancer, BrCa) progression.

Methods

The present study included 993 BrCa patients from The Cancer Genome Atlas (TCGA) database in the genome-wide analysis of AS events. We used differential and prognostic analyses and found differentially expressed alternative splicing (DEAS) events and independent prognostic factors related to patients' overall survival (OS) and disease-free survival (DFS). We divided the patients into two groups based on these AS events and analyzed their clinical features, molecular subtyping and immune characteristics. We also constructed a splicing factor (SF) regulation network for key AS events and verified the existence of AS events in tissue samples using real-time quantitative PCR.

Results

A total of 678 AS events were identified as differentially expressed, of which 13 and 10 AS events were independent prognostic factors of patients' OS and DFS, respectively. Unsupervised clustering analysis based on these prognostic factors indicated that the Cluster 1 group had a better prognosis and more immune cell infiltration. SFs were significantly related to the expression of AS events, and AA-RPS21 was significantly upregulated in tumors.

Conclusion

Alternative splicing expands the mechanism of breast cancer progression from a new perspective. Notably, alternative splicing may affect the patient's prognosis by affecting the infiltration of immune cells. Our research provides important guidance for subsequent studies of AS in breast cancer.

Liquid biomarkers for the management of paediatric neuroblastoma: an approach to personalised and targeted cancer therapy

Background:

Neuroblastoma is the most common extracranial solid tumour of infancy and accounts for about 6–10% of paediatric cancers. It has a biologically and clinically heterogeneous behaviour that ranges from spontaneous regression to cases of highly aggressive metastatic disease that could be unresponsive to standard therapy. In recent years, there have been several investigations into the development of various diagnostic, predictive and prognostic biomarkers towards personalised and targeted management of the disease.

Materials and Methods:

This paper reports on the review of current clinical and emerging biomarkers used in risk assessment, screening for early detection and diagnosis, prognostication and monitoring of the response of treatment of neuroblastoma in paediatric patients.

Conclusions:

Tumour markers can significantly improve diagnosis; however, the invasive, unpleasant and inconvenient nature of current tissue biopsies limits their applications, especially in paediatric patients. Therefore, the development of a non-invasive, reliable high accurate and personalised diagnostic tool capable of early detection and rapid response is the most promising step towards advanced cancer management from tumour diagnosis, therapy to patient monitoring and represents an important step towards the promise of precision, personalised and targeted medicine. Liquid biopsy assay with wide ranges of clinical applications is emerging to hold incredible potential for advancing cancer treatment and has greater promise for diagnostic purposes, identification and tracking of tumour-specific alterations during the course of the disease and to guide therapeutic decisions.

Transcriptome Analysis of the Japanese Pine Sawyer Beetle, Monochamus alternatus, Infected with the Entomopathogenic Fungus Metarhizium anisopliae JEF-197

The Japanese pine sawyer (JPS) beetle, Monochamus alternatus Hope (Coleoptera: Cerambycidae), damages pine trees and transmits the pine wilt nematode, Bursaphelenchus xylophilus Nickle. Chemical agents have been used to control JPS beetle, but due to various issues, efforts are being made to replace these chemical agents with entomopathogenic fungi. We investigated the expression of immune-related genes in JPS beetle in response to infection with JEF-197, a Metarhizium anisopliae isolate, using RNA-seq. RNA samples were obtained from JEF-197, JPS adults treated with JEF-197, and non-treated JPS adults on the 8th day after fungal treatment, and RNA-seq was performed using Illumina sequencing. JPS beetle transcriptome was assembled de novo and differentially expressed gene (DEG) analysis was performed. There were 719 and 1953 up- and downregulated unigenes upon JEF-197 infection, respectively. Upregulated contigs included genes involved in RNA transport, ribosome biogenesis in eukaryotes, spliceosome-related genes, and genes involved in immune-related signaling pathways such as the Toll and Imd pathways. Forty-two fungal DEGs related to energy and protein metabolism were upregulated, and genes involved in the stress response were also upregulated in the infected JPS beetles. Together, our results indicate that infection of JPS beetles by JEF-197 induces the expression of immune-related genes.

Urinary microRNA and mRNA in Tumors

Liquid biopsy is gaining importance in the context of analysis of circulating subcellular components, such as exosomes and nucleic acids, and the investigation of biological fluids is increasing because they express features common to the tissue of origin. Particularly, urine has become one of the most attractive biofluids in clinical practice due to its easy collection approach, its availability of large quantities, and its noninvasiveness. Furthermore, a peculiarity is that, compared to serum or plasma, urine is characterized by a simpler composition that improves isolation and identification of biomarkers. Recent studies have been associated with the investigation of mRNAs and microRNAs as potential noninvasive cancer biomarkers in urine, and to date, several approaches for isolating and measuring urinary nucleic acids have been established, despite still developing. This chapter aims at giving some main published evidences on urinary microRNAs and mRNAs, with the intent to consider their potential translational use in clinical practice.

Profiles of alternative splicing events in the diagnosis and prognosis of Gastric Cancer

Background: Gastric cancer (GC) is a heterogeneous disease, and alternative splicing (AS) is a powerful universal transcriptional regulatory mechanism that contributes to the occurrence and development of cancer. However, the systematic analysis of AS events in GC is lacking; therefore, further studies are needed. Methods: Genome-wide analysis of AS events was performed using RNA-Seq data to evaluate the difference between GC and adjacent tissues at the AS level. Prognostic signatures based on differentially expressed alternative splicing (DEAS) events and a correlation network between DEAS and genes were built. Results: We identified 48,141 AS events, of which 2325 showed differential expression patterns. The parental genes before DEAS events play an essential role in regulating GC-related processes such as ribosome (FDR < 0.0001) and thermogenesis (FDR = 0.0002). There were 76 survival-associated DEAS cases. Stratifying patients according to the percent spliced in index value of six types of splicing patterns formed significant Kaplan-Meier curves in the overall survival analysis. A prognostic feature based on DEAS performed well for stratification in patients with GC. Conclusion: The present study will enrich our understanding regarding the distinction of GC and provide a generous amount of biomarkers and potential targets for the treatment of GC.

Development and validation of an individual alternative splicing prognostic signature in gastric cancer

Gastric cancer (GC) is a heterogeneous disease with different clinical manifestations and prognoses. Alternative splicing (AS) is a determinant of gene expression and contributes to protein diversity from a rather limited gene transcript in metazoans. AS events are associated with different aspects of cancer biology, including cell proliferation, apoptosis, invasion, etc. Here, we present a comprehensive analysis of the prognostic AS profile in GC. GC-specific AS (GCAS) events were analyzed, and overall survival-associated GCAS (OS-GCAS) events were verified among the genome-wide AS events identified in The Cancer Genome Atlas (TCGA) database. In total, 1,287 GCAS events of 837 genes and 173 OS-GCAS events of 130 genes were identified. The parental genes of OS-GCAS events were significantly enriched in the development of GC. Protein-protein interaction (PPI) and OS-GCAS-associated splicing factor (SF) interaction networks were constructed. Multivariate Cox regression analysis with least absolute shrinkage and selection operator (LASSO) penalty was performed to establish a prognostic risk formula, representing 23 OS-GCAS events. The low-risk group had better OS than the high-risk group and lower immune and stromal scores. Cox proportional hazard regression was applied to generate an AS-clinical integrated prognostic model with a considerable area under the curve (AUC) value in both the training and validation datasets. Our study provides a profile of OS-GCAS events and an AS-clinical nomogram to predict the prognosis of GC.

The landscape of alternative splicing reveals novel events associated with tumorigenesis and the immune microenvironment in gastric cancer

Alternative splicing (AS), contributing to vast protein diversity from a rather limited number of genes in eukaryotic transcripts, has emerged as an important signature for tumor initiation and progression. However, a systematic understanding of its functional impact and relevance to gastric cancer (GC) tumorigenesis is lacking. Differentially expressed AS (DEAS) was verified among GC-associated AS events based on RNA-seq profiles from the TCGA database. Functional enrichment analysis, unsupervised clustering analysis and prognostic models were used to infer the potential roles of DEAS events and their molecular, clinical and immune features. In total, 12,225 AS events were detected from 5,199 genes, among which 314 AS events were identified as DEAS events in GC. The parental genes of the DEAS events were significantly enriched in the regulation of GC-related processes. The splicing correlation network suggested a significant relationship between DEAS events and splicing factors (SFs). Three clusters of DEAS events were identified to be different in prognosis, cancer-specific signatures and immune features between distinct clusters. Univariate and multivariate analyses regarded 3 DEAS events as independent prognostic indicators. Profiling of the AS landscape in GC elucidated the functional roles of the splicing network in GC and might serve as a novel prognostic indicator and therapeutic target.

Profiles of alternative splicing landscape in breast cancer and their clinical significance: an integrative analysis based on large-sequencing data

Background

Alternative splicing (AS) is closely correlated with the initiation and progression of carcinoma. The systematic analysis of its biological and clinical significance in breast cancer (BRCA) is, however, lacking.

Methods

Clinical data and RNA-seq were obtained from the TCGA dataset and differentially expressed AS (DEAS) events between tumor and paired normal BRCA tissues were identified. Enrichment analysis was then used to reveal the potential biological functions of DEAS events. We performed protein-protein interaction (PPI) analysis of DEAS events by using STRING and the correlation network between splicing factors (SFs) and AS events was constructed. The LASSO Cox model, Kaplan-Meier and log-rank tests were used to construct and evaluate DEAS-related risk signature, and the association between DEAS events and clinicopathological features were then analyzed.

Results

After strict filtering, 35,367 AS events and 973 DEAS events were detected. DEAS corresponding genes were significantly enriched in pivotal pathways including cell adhesion, cytoskeleton organization, and extracellular matrix organization. A total of 103 DEAS events were correlated with disease free survival. The DEAS-related risk signature stratified BRCA patients into two groups and the area under curve (AUC) was 0.754. Moreover, patients in the high-risk group had enriched basel-like subtype, advanced clinical stages, proliferation, and metastasis potency.

Conclusions

Collectively, the profile of DEAS landscape in BRCA revealed the potential biological function and prognostic value of DEAS events.

ROP18-Mediated Transcriptional Reprogramming of HEK293T Cell Reveals New Roles of ROP18 in the Interplay Between Toxoplasma gondii and the Host Cell

Toxoplasma gondii secretes a number of virulence-related effector proteins, such as the rhoptry protein 18 (ROP18). To further broaden our understanding of the molecular functions of ROP18, we examined the transcriptional response of human embryonic kidney cells (HEK293T) to ROP18 of type I T. gondii RH strain. Using RNA-sequencing, we compared the transcriptome of ROP18-expressing HEK293T cells to control HEK293T cells. Our analysis revealed that ROP18 altered the expression of 750 genes (467 upregulated genes and 283 downregulated genes) in HEK293T cells. Gene ontology (GO) and pathway enrichment analyses showed that differentially expressed genes (DEGs) were significantly enriched in extracellular matrix– and immune–related GO terms and pathways. KEGG pathway enrichment analysis revealed that DEGs were involved in several disease-related pathways, such as nervous system diseases and eye disease. ROP18 significantly increased the alternative splicing pattern “retained intron” and altered the expression of 144 transcription factors (TFs). These results provide new insight into how ROP18 may influence biological processes in the host cells via altering the expression of genes, TFs, and pathways. More in vitro and in vivo studies are required to substantiate these findings.

Revised Exon Structure of l-DOPA Decarboxylase (DDC) Reveals Novel Splice Variants Associated with Colorectal Cancer Progression

Colorectal cancer (CRC) is a highly heterogenous malignancy with an increased mortality rate. Aberrant splicing is a typical characteristic of CRC, and several studies support the prognostic value of particular transcripts in this malignancy. l-DOPA decarboxylase (DDC) and its derivative neurotransmitters play a multifaceted role in physiological and pathological states. Our recent data support the existence of 6 DDC novel exons. In this study, we investigated the existence of additional DDC novel exons and transcripts, and their potential value as biomarkers in CRC. Next-generation sequencing (NGS) in 55 human cell lines coupled with Sanger sequencing uncovered 3 additional DDC novel exons and 20 splice variants, 7 of which likely encode new protein isoforms. Eight of these transcripts were detected in CRC. An in-house qPCR assay was developed and performed in TNM II and III CRC samples for the quantification of transcripts bearing novel exons. Extensive biostatistical analysis uncovered the prognostic value of specific DDC novel exons for patients’ disease-free and overall survival. The revised DDC exon structure, the putative protein isoforms with distinct functions, and the prognostic value of novel exons highlight the pivotal role of DDC in CRC progression, indicating its potential utility as a molecular biomarker in CRC.

An alternative splicing signature model for predicting hepatocellular carcinoma-specific survival

BACKGROUND

Alternative splicing (AS) is a transcriptional regulation mechanism, which can expand the coding ability of genome and contribute to the occurrence and development of cancer. A systematic analysis of AS in hepatocellular carcinoma (HCC) is lacking and urgently needed.

METHODS

Univariate and multivariate Cox regression analyses were used to distinguish survival-related AS events and to calculate the risk score. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the AS events' clinical significance to build a risk model in HCC.

RESULTS

Data of AS events was obtained from the Splice-Seq database. The corresponding clinical information of HCC was downloaded from The Cancer Genome Atlas (TCGA) data portal. We analyzed 78,878 AS events from 13,045 genes in HCC patients. A total of 2,440 and 2,888 AS events were significantly related to HCC patients' disease-free survival (DFS) and overall survival (OS). The two prognostic models (DFS and OS) were constructed based on a total of seven AS types from survival-related AS events above. The area under the curve (AUC) of the ROC curves was 0.769 in the DFS cohort and 0.886 in the OS cohort.

CONCLUSIONS

The prognostic model constructed by AS events can be used to predict the prognosis of HCC patients and provide potential therapeutic targets for further validation.

Integrative bioinformatics analysis of prognostic alternative splicing signatures in gastric cancer

Background

The potential prognostic value of alternative splicing (AS) variants and regulatory splicing factors in gastric carcinogenesis is unclear. We aimed to exploit the aberrant AS signatures and splicing factors involved in gastric cancer (GC) and to determine their prognostic predictive values.

Methods

We performed detailed data acquisition using the Cancer Genome Atlas project and profiled genome-wide AS signatures in a cohort of 190 patients with stomach adenocarcinoma (STAD). Prognostic prediction models and splicing correlation networks were assessed using an integrative bioinformatics analysis approach.

Results

We detected 1,308 overall survival (OS)-related AS signatures in 993 genes, most of which were favorable prognostic factors. Six splicing factors have been suggested to be dysregulated in GC, i.e., DHX15, PPP4R2, PRPF38B, RBM9, RBM15, and ILF3. Another notable finding was that most favorable prognosis AS events were positively correlated with expression of splicing factors, while a majority of poor survival prognostic AS genes were negatively associated with the expression of splicing factors.

Conclusions

To our knowledge, the current study provided the first comprehensive profiling of global modifications in the RNA splicing to identify survival associated AS signatures of GC specific genes. Our findings contribute to a better understanding of aberrant AS signatures and splicing factors in STAD, which can potentially be used as prognostic biomarkers and therapeutic targets for GC.

Prognostic alternative splicing signature reveals the landscape of immune infiltration in Pancreatic Cancer

Background: Pancreatic cancer (PC) is an aggressive cancer with worse survival in the world. Emerging evidence suggested that the imbalance of alternative splicing (AS) is a hallmark of cancer and indicated poor prognosis of patients. Genes-derived splicing events can produce neoepitopes for immunotherapy. However, the profound study of splicing profiling in PC is still elusive. We aimed to identification of novel prognostic signature across a comprehensive splicing landscape and reveal their relationship with tumor-infiltrating immune cells in pancreatic cancer microenvironment.

Methods: Based on integrated analysis of splicing profiling and clinical data, differentially splicing events were filtered out. Then, stepwise Cox regression analysis was applied to identify survival-related splicing events and construct prognostic signature. Functional enrichment analysis was performed to explore biology function. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were performed to validate the predictive effect of predictive signature. We also verified the clinical value of prognostic signature under the influence of different clinical parameters. For deeper analysis, we evaluated the correlation between prognostic signature and infiltrating immune cells by CIBERSORT.

Results: According to systematic analyzing, a final six splicing events were identified and validated the good prognostic capability in entire TCGA dataset, validation set 1 and validation set 2 by Kaplan-Meier curves (P < 0.0001). The area under the curve (AUC) of ROC curves were also confirmed the high predictive efficiency of the prognostic signature in these three cohorts (AUC = 0.857, 0.895 and 0.788). In order to validate whether prognostic signature highlights a correlation between AS and immune contexture, CIBERSORT was performed to analyze the proportion of tumor-infiltrating immune cells in PC. Based on prognostic signature, we identified survival-related immune cells including CD8 T cells (P = 0.0111), activated CD4 memory T cells (P = 0.0329) and resting mast cells (P = 0.0352).

Conclusion: In conclusion, our study contribute to provide a promising prognostic signature based on six splicing events and revealed prognosis-related immune cells which indeed represented novel tumor drivers and provide potential targets for personalized therapeutic.

Genome-Wide Transcriptional Analysis Reveals Alternative Splicing Event Profiles in Hepatocellular Carcinoma and Their Prognostic Significance

Accumulating evidence indicates an unexpected role of aberrant splicing in hepatocellular carcinoma (HCC) that has been seriously neglected in previous studies. There is a need for a detailed analysis of alternative splicing (AS) and its underlying biological and clinical relevance in HCC. In this study, clinical information and corresponding RNA sequencing data of HCC patients were obtained from The Cancer Genome Atlas. Percent spliced in (PSI) values and transcriptional splicing patterns of genes were determined from the original RNA sequencing data using SpliceSeq. Then, based on the PSI values of AS events in different patients, a series of bioinformatics methods was used to identify differentially expressed AS events (DEAS), determine potential regulatory relationships, and investigate the correlation between DEAS and the patients' clinicopathological features. Finally, 25,934 AS events originating from 8,795 genes were screened with high reliability; 263 of these AS events were identified as DEAS. The parent genes of these DEAS formed an intricate network with roles in the regulation of cancer-related pathway and liver metabolism. In HCC, 36 splicing factors were involved in the dysregulation of part DEAS, 100 DEAS events were correlated with overall survival, and 71 DEAS events were correlated with disease-free survival. Stratifying HCC patients according to DEAS resulted in four clusters with different survival patterns. Significant variations in AS occurred during HCC initiation and maintenance; these are likely to be vital both for biological processes and in prognosis. The HCC-related AS events identified here and the splicing networks constructed will be valuable in deciphering the underlying role of AS in HCC.

Identification of Prognostic Signatures of Alternative Splicing in Glioma

Alternative splicing (AS) is a ubiquitous mechanism in which pre-mRNA can be spliced into divergent variants and involved in carcinogenesis and progression in several cancers. In the present study, we systematically profiled prognostic AS signatures involving both low grade glioma (LGG) and glioblastoma (GBM) and investigated the association of AS signatures with tumor grade and IDH1 status in glioma. Percent spliced in (PSI) values and corresponding clinical data were obtained from TCGA SpliceSeq and TCGA data portal, respectively. Prognostic AS signatures were identified using univariate and stepwise multivariate Cox regression. Heatmap analysis was performed based on prognostic AS signatures. A prognostic signature was established with 69 and 88 AS events, including specific splicing events of MUTYH, STEAP3, and CTNNB1, in LGG and GBM cohorts, respectively. The area under the curve (AUC) of the prediction model was 0.968 at 2000 days of overall survival (OS) in the LGG cohort and 0.966 at 450 days of OS in the GBM cohort. In addition, these prognostic AS signatures could complement current molecular classification, such as IDH1 mutation, 1p/19q codeletion, and ATRX loss, of glioma and further identify potential subgroups of glioma with the same molecular features. In conclusion, our study systematically profiled prognostic AS events involving both low grade glioma and glioblastoma for the first time, which also shed light on the crosstalk between AS signatures and molecular features of glioma.

Liquid biopsy and tumor heterogeneity in metastatic solid tumors: the potentiality of blood samples

In a large number of cancer types, treatment selection depends on the presence of specific tumor biomarkers. Due to the dynamic nature of cancer, very often these predictive biomarkers are not uniformly present in all cancer cells. Tumor heterogeneity represents indeed one of the main causes of therapeutic failure, and its decoding remains a major ongoing challenge in the field.

Liquid biopsy is the sampling and analysis of non-solid biological tissue often through rapid and non-invasive methods, which allows the assessment in real-time of the evolving landscape of cancer. Samples can be obtained from blood and most other bodily fluids. A blood-based liquid biopsy can capture circulating tumor cells and leukocytes, as well as circulating tumor-derived nucleic acids.

In this review, we discuss the current and possibly future applications of blood-based liquid biopsy in oncology, its advantages and its limitations in clinical practice. We specifically focused on its role as a tool to capture tumor heterogeneity in metastatic cancer patients.

Aberrant expression of CPSF1 promotes head and neck squamous cell carcinoma via regulating alternative splicing

Alternative mRNA splicing increases protein diversity, and alternative splicing events (ASEs) drive oncogenesis in multiple tumor types. However, the driving alterations that underlie the broad dysregulation of ASEs are incompletely defined. Using head and neck squamous cell carcinoma (HNSCC) as a model, we hypothesized that the genomic alteration of genes associated with the spliceosome may broadly induce ASEs across a broad range of target genes, driving an oncogenic phenotype. We identified 319 spliceosome genes and employed a discovery pipeline to identify 13 candidate spliceosome genes altered in HNSCC using The Cancer Genome Atlas (TCGA) HNSCC data. Phenotypic screens identified amplified and overexpressed CPSF1 as a target gene alteration that was validated in proliferation, colony formation, and apoptosis assays in cell line and xenograft systems as well as in primary HNSCC. We employed knockdown and overexpression assays followed by identification of ASEs regulated by CPSF1 overexpression to identify changes in ASEs, and the expression of these ASEs was validated using RNA from cell line models. Alterations in expression of spliceosome genes, including CPSF1, may contribute to HNSCC by mediating aberrant ASE expression.

Systematic evaluation of differential splicing tools for RNA-seq studies

Differential splicing (DS) is a post-transcriptional biological process with critical, wide-ranging effects on a plethora of cellular activities and disease processes. To date, a number of computational approaches have been developed to identify and quantify differentially spliced genes from RNA-seq data, but a comprehensive intercomparison and appraisal of these approaches is currently lacking. In this study, we systematically evaluated 10 DS analysis tools for consistency and reproducibility, precision, recall and false discovery rate, agreement upon reported differentially spliced genes and functional enrichment. The tools were selected to represent the three different methodological categories: exon-based (DEXSeq, edgeR, JunctionSeq, limma), isoform-based (cuffdiff2, DiffSplice) and event-based methods (dSpliceType, MAJIQ, rMATS, SUPPA). Overall, all the exon-based methods and two event-based methods (MAJIQ and rMATS) scored well on the selected measures. Of the 10 tools tested, the exon-based methods performed generally better than the isoform-based and event-based methods. However, overall, the different data analysis tools performed strikingly differently across different data sets or numbers of samples.

Comprehensive characterization of the alternative splicing landscape in head and neck squamous cell carcinoma reveals novel events associated with tumorigenesis and the immune microenvironment

Alternative splicing (AS) has emerged as a key event in tumor development and microenvironment formation. However, comprehensive analysis of AS and its clinical significance in head and neck squamous cell carcinoma (HNSC) is urgently required. Methods: Genome-wide profiling of AS events using RNA-Seq data from The Cancer Genome Atlas (TCGA) program was performed in a cohort of 464 patients with HNSC. Cancer-associated AS events (CASEs) were identified between paired HNSC and adjacent normal tissues and evaluated in functional enrichment analysis. Splicing networks and prognostic models were constructed using bioinformatics tools. Unsupervised clustering of the CASEs identified was conducted and associations with clinical, molecular and immune features were analyzed. Results: We detected a total of 32,309 AS events and identified 473 CASEs in HNSC; among these, 91 were validated in an independent cohort (n = 15). Functional protein domains were frequently altered, especially by CASEs affecting cancer drivers, such as PCSK5. CASE parent genes were significantly enriched in pathways related to HNSC and the tumor immune microenvironment, such as the viral carcinogenesis (FDR < 0.001), Human Papillomavirus infection (FDR < 0.001), chemokine (FDR < 0.001) and T cell receptor (FDR < 0.001) signaling pathways. CASEs enriched in immune-related pathways were closely associated with immune cell infiltration and cytolytic activity. AS regulatory networks suggested a significant association between splicing factor (SF) expression and CASEs and might be regulated by SF methylation. Eighteen CASEs were identified as independent prognostic factors for overall and disease-free survival. Unsupervised clustering analysis revealed distinct correlations between AS-based clusters and prognosis, molecular characteristics and immune features. Immunogenic features and immune subgroups cooperatively depict the immune features of AS-based clusters. Conclusion: This comprehensive genome-wide analysis of the AS landscape in HNSC revealed novel AS events related to carcinogenesis and immune microenvironment, with implications for prognosis and therapeutic responses.

FJ, Liu Z, Tang W. Systematic profiling of alternative splicing events and splicing factors in left- and right-sided colon cancer

Left- and right-sided colon cancer (LC and RC) differ substantially in their molecular characteristics and prognoses, and are thus treated using different strategies. We systematically analyzed alternative splicing (AS) events and splicing factors in LC and RC. RNA-seq data were used for genome-wide profiling of AS events that could distinguish LC from RC. The Exon Skip splicing pattern was more common in RC, while the Retained Intron pattern was more common in LC. The AS events that were upregulated in RC were enriched for genes in the axon guidance pathway, while those that were upregulated in LC were enriched for genes in immune-related pathways. Prognostic models based on differentially expressed AS events were built, and a prognostic signature based on these AS events performed well for risk stratification in colon cancer patients. A correlation network of differentially expressed AS events and differentially expressed splicing factors was constructed, and RBM25 was identified as the hub gene in the network. In conclusion, large differences in AS events may contribute to the phenotypic differences between LC and RC. The differentially expressed AS events reported herein could be used as biomarkers and treatment targets for colon cancer.

Determining the prognostic significance of alternative splicing events in soft tissue sarcoma using data from The Cancer Genome Atlas

BACKGROUND

Surgery, adjuvant chemotherapy, and radiotherapy are the primary treatment options for soft tissue sarcomas (STSs). However, identifying ways to improve the prognosis of patients with STS remains a considerable challenge. Evidence shows that the dysregulation of alternative splicing (AS) events is involved in tumor pathogenesis and progression. The present study objective was to identify survival-associated AS events that could serve as prognostic biomarkers and potentially serve as tumor-selective STS drug targets.

METHODS

STS-specific 'percent spliced in' (PSI) values for splicing events in 206 STS samples were downloaded from The Cancer Genome Atlas SpliceSeq^® database. Prognostic analyses were performed on seven types of AS events to determine their prognostic value in STS patients, for which prediction models were constructed with the risk score formula [Formula: see text]. Prediction models were also constructed to determine the prognostic value of AS events, and Spearman's rank correlation coefficients were calculated to determine the degree of correlation between splicing factor expression and the PSI values.

RESULTS

A total 10,439 events were found to significantly correlate with patient survival rates. The area under the time-dependent receiver operating characteristic curve for the prognostic predictor of STS overall survival was 0.826. Notably, the splicing events of certain STS key genes were significantly associated with STS 2-year overall survival in the present study, including exon skip (ES) events in MDM2 and EWSR1, alternate terminator events in CDKN2A and HMGA2 for dedifferentiated liposarcoma, ES in MDM2 and alternate promoter events in CDKN2A for leiomyosarcoma, and ES in EWSR1 for undifferentiated pleomorphic sarcoma. Moreover, splicing correlation networks between AS events and splicing factors revealed that almost all of the AS events showed negatively correlations with the expression of splicing factors.

CONCLUSION

An in-depth analysis of alternative RNA splicing could provide new insights into the mechanisms of STS oncogenesis and the potential for novel approaches to this type of cancer therapy.

Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer

Patients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of pre-neoplastic lesions and carcinomas in situ (CIS), invasiveness, and high costs. This work aims to identify a urinary metabolomic signature of recurrence by proton Nuclear Magnetic Resonance (¹H NMR) spectroscopy for the follow-up of NMIBC patients. To do this, changes in the urinary metabolome before and after transurethral resection (TUR) of tumors are analyzed and a Partial Least Square Discriminant Analysis (PLS-DA) model is developed. The usefulness of this discriminant model for the detection of tumor recurrences is assessed using a cohort of patients undergoing monitoring. The trajectories of the metabolomic profile in the follow-up period provide a negative predictive value of 92.7% in the sample classification. Pathway analyses show taurine, alanine, aspartate, glutamate, and phenylalanine perturbed metabolism associated with NMIBC. These results highlight the potential of ¹H NMR metabolomics to detect bladder cancer (BC) recurrences through a non-invasive approach.

Events of alternative splicing in head and neck cancer via RNA sequencing - an update

Background

Alternative splicing (AS) is a regulatory mechanism used to create many forms of mature messengers RNAs (mRNAs) from the same gene. Sequencing of RNA (RNA-Seq) is an advanced technology, which has been utilized by different studies to find AS mechanisms in head and neck cancer (HNC). Hitherto, there is no available review that could inform us of the major findings from these studies. Hence, we aim to perform a systematic literature search following PRISMA guidelines to study AS events in HNC identified through RNA-Seq studies.

Results

A total of five records were identified that utilized RNA-Seq data for identifying AS events in HNC. Five software was used in these records to identify AS events. Two genes influenced by AS i.e. MLL3 and RPS9 were found to be common in 4 out of 5 records. Likewise, 38 genes were identified to be similar in at least 3 records.

Conclusions

Alternative splicing in HNC is a multifaceted regulatory mechanism of gene expression. It can be studied via RNA-Seq using different bioinformatics tools. Genes MLL3, as well as RPS9, were repeatedly found to be associated with HNC, however needs further functional validation.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5794-y) contains supplementary material, which is available to authorized users.

Transcriptomics Signature from Next-Generation Sequencing Data Reveals New Transcriptomic Biomarkers Related to Prostate Cancer

Prostate cancer is one of the most common types of cancer among Canadian men. Next-generation sequencing using RNA-Seq provides large amounts of data that may reveal novel and informative biomarkers. We introduce a method that uses machine learning techniques to identify transcripts that correlate with prostate cancer development and progression. We have isolated transcripts that have the potential to serve as prognostic indicators and may have tremendous value in guiding treatment decisions. Analysis of normal versus malignant prostate cancer data sets indicates differential expression of the genes HEATR5B, DDC, and GABPB1-AS1 as potential prostate cancer biomarkers. Our study also supports PTGFR, NREP, SCARNA22, DOCK9, FLVCR2, IK2F3, USP13, and CLASP1 as potential biomarkers to predict prostate cancer progression, especially between stage II and subsequent stages of the disease.

Genome-Wide Profiling of Prognostic Alternative Splicing Signature in Colorectal Cancer

Background: This study was to explore differential RNA splicing patterns and elucidate the function of the splice variants served as prognostic biomarkers in colorectal cancer (CRC).

Methods: Genome-wide profiling of prognostic alternative splicing (AS) events using RNA-seq data from The Cancer Genome Atlas (TCGA) program was conducted to evaluate the roles of seven AS patterns in 330 colorectal cancer cohort. The prognostic predictors models were assessed by integrated Cox proportional hazards regression. Based on the correlations between survival associated AS events and splicing factors, splicing networks were built.

Results: A total of 2,158 survival associated AS events in CRC were identified. Interestingly, most of these top 20 survival associated AS events were adverse prognostic factors. The prognostic models were built by each type of splicing patterns, performing well for risk stratification in CRC patients. The area under curve (AUC) of receiver operating characteristic (ROC) for the combined prognostic predictors model could reach 0.963. Splicing network also suggested distinguished correlation between the expression of splicing factors and AS events in CRC patients.

Conclusion: The ideal prognostic predictors model for risk stratification in CRC patients was constructed by differential splicing patterns of 13 genes. Our findings enriched knowledge about differential RNA splicing patterns and the regulation of splicing, providing generous biomarker candidates and potential targets for the treatment of CRC.

Novel splice isoforms of pig myoneurin and their diverse mRNA expression patterns

OBJECTIVE

The aim of this study was to clone alternative splicing isoforms of pig myoneurin (MYNN), predict the structure and function of coding protein, and study temporal and spatial expression characteristics of each transcript.

METHODS

Alternative splice isoforms of MYNN were identified using RNA sequencing (RNA-seq) and cloning techniques. Quantitative real-time polymerase chain reaction (qPCR) was employed to detect expression patterns in 11 tissues of Large White (LW) and Mashen (MS) pigs, and to study developmental expression patterns in cerebellum (CE), stomach (ST), and longissimus dorsi (LD).

RESULTS

The results showed that MYNN had two alternatively spliced isoforms, MYNN-1 (GenBank accession number: KY470829) and MYNN-2 (GenBank accession number: KY670835). MYNN-1 coding sequence (CDS) is composed of 1,830 bp encoding 609 AA, whereas MYNN-2 CDS is composed of 1,746 bp encoding 581 AA. MYNN-2 was 84 bp less than MYNN-1 and lacked the sixth exon. MYNN-2 was found to have one C2H2 type zinc finger protein domain less than MYNN-1. Two variants were ubiquitously expressed in all pig tissues, and there were significant differences in expression of different tissues (p<0.05; p<0.01). The expression of MYNN-1 was significantly higher than that of MYNN-2 in almost tissues (p<0.05; p<0.01), which testified that MYNN-1 is the main variant. The expression of two isoforms decreased gradually with increase of age in ST and CE of MS pig, whereas increased gradually in LW pig. In LD, the expression of two isoforms increased first and then decreased with increase of age in MS pig, and decreased gradually in LW pig.

CONCLUSION

Two transcripts of pig MYNN were successfully cloned and MYNN-1 was main variant. MYNN was highly expressed in ST, CE, and LD, and their expression was regular. We speculated that MYNN plays important roles in digestion/absorption and skeletal muscle growth, whereas the specific mechanisms require further elucidation.

Profiles of alternative splicing in colorectal cancer and their clinical significance: A study based on large-scale sequencing data

Background

Alternative splicing (AS), as a potent and pervasive mechanism of transcriptional regulatory, expands the genome's coding capacity and involves in the initiation and progression of cancer. Systematic analysis of alternative splicing in colorectal cancer (CRC) is lacking and greatly needed.

Methods

RNA-Seq data and corresponding clinical information of CRC cohort were downloaded from the TCGA data portal. Then, a java application, known as SpliceSeq, was used to evaluate the RNA splicing patterns and calculate the Percent Spliced In (PSI) value. Differently expressed AS events (DEAS) were identified based on PSI value between paired CRC and adjacent tissues. DEAS and its splicing networks were further analyzed by bioinformatics methods. Kaplan-Meier, Cox proportional regression and unsupervised clustering analysis were used to evaluate the association between DEAS and patients' clinical features.

Results

After strict filtering, a total of 34,334 AS events were identified, among which 421 AS events were found expressed differently. Parent genes of these DEAS play a important role in regulating CRC-related processes such as protein kinase activity (FDR<0.0001), PI3K-Akt signaling pathway (FDR = 0.0024) and p53 signaling pathway (FDR = 0.0143). 37 DEAS events were found to be associated with OS, and 68 DEAS events were found to be associated with DFS. Stratifying patients according to the PSI value of AT in CXCL12 and RI in CSTF3 formed significant Kaplan-Meier curves in both OS and DFS survival analysis. Unsupervised clustering analysis using DEAS revealed four clusters with distinct survival patterns, and associated with consensus molecular subtypes.

Conclusions

Large differences of AS events in CRC appear to exist, and these differences are likely to be important determinants of both prognosis and biological regulation. Our identified CRC-related AS events and uncovered splicing networks are valuable in deciphering the underlying mechanisms of AS in CRC, and provide clues of therapeutic targets to further validations.

Characterization of kinase gene expression and splicing profile in prostate cancer with RNA-Seq data

Background

Alternative splicing is a ubiquitous post-transcriptional regulation mechanism in most eukaryotic genes. Aberrant splicing isoforms and abnormal isoform ratios can contribute to cancer development. Kinase genes are key regulators of multiple cellular processes. Many kinases are found to be oncogenic and have been intensively investigated in the study of cancer and drugs. RNA-Seq provides a powerful technology for genome-wide study of alternative splicing in cancer besides the conventional gene expression profiling. But this potential has not been fully demonstrated yet.

Methods

We characterized the transcriptome profile of prostate cancer using RNA-Seq data from viewpoints of both differential expression and differential splicing, with an emphasis on kinase genes and their splicing variations. We built a pipeline to conduct differential expression and differential splicing analysis, followed by functional enrichment analysis. We performed kinase domain analysis to identify the functionally important candidate kinase gene in prostate cancer, and calculated the expression levels of isoforms to explore the function of isoform switching of kinase genes in prostate cancer.

Results

We identified distinct gene groups from differential expression and splicing analyses, which suggested that alternative splicing adds another level to gene expression regulation. Enriched GO terms of differentially expressed and spliced kinase genes were found to play different roles in regulation of cellular metabolism. Function analysis on differentially spliced kinase genes showed that differentially spliced exons of these genes are significantly enriched in protein kinase domains. Among them, we found that gene CDK5 has isoform switching between prostate cancer and benign tissues, which may affect cancer development by changing androgen receptor (AR) phosphorylation. The observation was validated in another RNA-Seq dataset of prostate cancer cell lines.

Conclusions

Our work characterized the expression and splicing profiles of kinase genes in prostate cancer and proposed a hypothetical model on isoform switching of CDK5 and AR phosphorylation in prostate cancer. These findings bring new understanding to the role of alternatively spliced kinases in prostate cancer and also demonstrate the use of RNA-Seq data in studying alternative splicing in cancer.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4925-1) contains supplementary material, which is available to authorized users.

Discovery and expression analysis of novel transcripts of the human SR-related CTD-associated factor 1 (SCAF1) gene in human cancer cells using Next-Generation Sequencing

The human SR-related CTD associated factor 1 (SCAF1) gene is a new member of the human SR (Ser/Arg-rich) superfamily of pre-mRNA splicing factors, which has been discovered and cloned by members of our lab. SCAF1 interacts with the CTD domain of the RNA polymerase II polypeptide A and is firmly involved in pre-mRNA splicing. Although it was found to be expressed widely in multiple human tissues, its mRNA levels vary a lot. The significant relation of SCAF1 with cancer has been confirmed by many studies, since SCAF1 mRNA transcript was found to be overexpressed in breast and ovarian tumors, confirming its significant prognostic value as a cancer biomarker in both these human malignancies. In this study, we describe the discovery and cloning of fifteen novel transcripts of the human SCAF1 gene (SCAF1 v.2 - v.16), using nested PCR and NGS technology. In detail, extensive bioinformatic analysis revealed that these novel SCAF1 splice variants comprise a total of nine novel alternative splicing events between the annotated exons of the gene, thus producing seven novel SCAF1 transcripts with open-reading frames, which are predicted to encode novel SCAF1 isoforms and eight novel SCAF1 transcripts with premature termination codons that are likely long non-coding RNAs. Additionally, a novel 3' UTR was discovered and cloned using nested 3' RACE and was validated with Sanger sequencing. In order to validate the NGS findings as well as to investigate the expression profile of each novel transcript, RT-PCR experiments were carried out with the use of variant-specific primers. Since SCAF1 is implicated in many human malignancies, qualifying as a potential biomarker, the quantification of the presented novel transcripts in human samples may have clinical applications in different types of cancer.

Characterization of viral RNA splicing using whole-transcriptome datasets from host species

RNA alternative splicing (AS) is an important post-transcriptional mechanism enabling single genes to produce multiple proteins. It has been well demonstrated that viruses deploy host AS machinery for viral protein productions. However, knowledge on viral AS is limited to a few disease-causing viruses in model species. Here we report a novel approach to characterizing viral AS using whole transcriptome dataset from host species. Two insect transcriptomes (Acheta domesticus and Planococcus citri) generated in the 1,000 Insect Transcriptome Evolution (1KITE) project were used as a proof of concept using the new pipeline. Two closely related densoviruses (Acheta domesticus densovirus, AdDNV, and Planococcus citri densovirus, PcDNV, Ambidensovirus, Densovirinae, Parvoviridae) were detected and analyzed for AS patterns. The results suggested that although the two viruses shared major AS features, dramatic AS divergences were observed. Detailed analysis of the splicing junctions showed clusters of AS events occurred in two regions of the virus genome, demonstrating that transcriptome analysis could gain valuable insights into viral splicing. When applied to large-scale transcriptomics projects with diverse taxonomic sampling, our new method is expected to rapidly expand our knowledge on RNA splicing mechanisms for a wide range of viruses.