Comprehensive analysis and establishment of a prediction model of alternative splicing events reveal the prognostic predictor and immune microenvironment signatures in triple negative breast cancer

In silico identification of a novel Cdc2-like kinase 2 (CLK2) inhibitor in triple negative breast cancer

Dysregulation of RNA splicing processes is intricately linked to tumorigenesis in various cancers, especially breast cancer. Cdc2-like kinase 2 (CLK2), an oncogenic RNA-splicing kinase pivotal in breast cancer, plays a significant role, particularly in the context of triple-negative breast cancer (TNBC), a subtype marked by substantial medical challenges due to its low survival rates. In this study, we employed a structure-based virtual screening (SBVS) method to identify potential CLK2 inhibitors with novel chemical structures for treating TNBC. Compound 670551 emerged as a novel CLK2 inhibitor with a 50% inhibitory concentration (IC50) value of 619.7 nM. Importantly, Compound 670551 exhibited high selectivity for CLK2 over other protein kinases. Functionally, this compound significantly reduced the survival and proliferation of TNBC cells. Results from a cell-based assay demonstrated that this inhibitor led to a decrease in RNA splicing proteins, such as SRSF4 and SRSF6, resulting in cell apoptosis. In summary, we identified a novel CLK2 inhibitor as a promising potential treatment for TNBC therapy.

Alternative splicing and related RNA binding proteins in human health and disease

Alternative splicing (AS) serves as a pivotal mechanism in transcriptional regulation, engendering transcript diversity, and modifications in protein structure and functionality. Across varying tissues, developmental stages, or under specific conditions, AS gives rise to distinct splice isoforms. This implies that these isoforms possess unique temporal and spatial roles, thereby associating AS with standard biological activities and diseases. Among these, AS-related RNA-binding proteins (RBPs) play an instrumental role in regulating alternative splicing events. Under physiological conditions, the diversity of proteins mediated by AS influences the structure, function, interaction, and localization of proteins, thereby participating in the differentiation and development of an array of tissues and organs. Under pathological conditions, alterations in AS are linked with various diseases, particularly cancer. These changes can lead to modifications in gene splicing patterns, culminating in changes or loss of protein functionality. For instance, in cancer, abnormalities in AS and RBPs may result in aberrant expression of cancer-associated genes, thereby promoting the onset and progression of tumors. AS and RBPs are also associated with numerous neurodegenerative diseases and autoimmune diseases. Consequently, the study of AS across different tissues holds significant value. This review provides a detailed account of the recent advancements in the study of alternative splicing and AS-related RNA-binding proteins in tissue development and diseases, which aids in deepening the understanding of gene expression complexity and offers new insights and methodologies for precision medicine.

Alternative splicing event associated with immunological features in bladder cancer

Bladder cancer (BLCA) is the most prevalent urinary tumor with few treatments. Alternative splicing (AS) is closely related to tumor development and tumor immune microenvironment. However, the comprehensive analysis of AS and prognosis and immunological features in BLCA is still lacking. In this study, we downloaded RNA-Seq data and clinical information from The Cancer Genome Atlas (TCGA) database, and AS events were acquired from the TCGA Splice-seq. A total of eight prognostic AS events (C19orf57|47943|ES, ANK3|11845|AP, AK9|77203|AT, GRIK2|77096|AT, DYM|45472|ES, PTGER3|3415|AT, ACTG1|44120|RI, and TRMU|62711|AA) were identified by univariate analysis and least absolute shrinkage and selection operator (LASSO) regression analysis to construct a risk score model. The Kaplan-Meier analysis revealed that the high-risk group had a worse prognosis compared with the low-risk group. The area under the receiver operating characteristic (ROC) curves (AUCs) for this risk score model in 1, 3, and 5 years were 0.698, 0.742, and 0.772, respectively. One of the prognostic AS event-related genes, TRMU, was differentially expressed between tumor and normal tissues in BLCA. The single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithm showed that both the risk score model and TRMU were significantly associated with tumor immune microenvironment and immune status (immune cells, immune-related pathway, and immune checkpoint) in BLCA patients. The TIMER database confirmed the relationship between the expression of TRMU and immune cells and checkpoint genes. Furthermore, Cytoscape software 3.8.0 was used to construct the regulatory network between AS and splicing factors (SFs). Our study demonstrated that AS events were powerful biomarkers to predict the prognosis and immune status in BLCA, which may be potential therapeutic targets in BLCA.

Construction of the prognostic signature of alternative splicing revealed the prognostic predictor and immune microenvironment in head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinoma (HNSC) is a prevalent and heterogeneous malignancy with poor prognosis and high mortality rates. There is significant evidence of alternative splicing (AS) contributing to tumor development, suggesting its potential in predicting prognosis and therapeutic efficacy. This study aims to establish an AS-based prognostic signature in HNSC patients.

Methods: The expression profiles and clinical information of 486 HNSC patients were downloaded from the TCGA database, and the AS data were downloaded from the TCGA SpliceSeq database. The survival-associated AS events were identified by conducting a Cox regression analysis and utilized to develop a prognostic signature by fitting into a LASSO-regularized Cox regression model. Survival analysis, univariate and multivariate Cox regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to evaluate the signature and an independent cohort was used for validation. The immune cell function and infiltration were analyzed by CIBERSORT and the ssGSEA algorithm.

Results: Univariate Cox regression analysis identified 2726 survival-associated AS events from 1714 genes. The correlation network reported DDX39B, PRPF39, and ARGLU1 as key splicing factors (SF) regulating these AS events. Eight survival-associated AS events were selected and validated by LASSO regression to develop a prognostic signature. It was confirmed that this signature could predict HNSC outcomes independent of other variables via multivariate Cox regression analysis. The risk score AUC was more than 0.75 for 3 years, highlighting the signature’s prediction capability. Immune infiltration analysis reported different immune cell distributions between the two risk groups. The immune cell content was higher in the high-risk group than in the low-risk group. The correlation analysis revealed a significant correlation between risk score, immune cell subsets, and immune checkpoint expression.

Conclusion: The prognostic signature developed from survival-associated AS events could predict the prognosis of HNSC patients and their clinical response to immunotherapy. However, this signature requires further research and validation in larger cohort studies.

Prognostic Relevance of Nuclear Receptors in Relation to Peritumoral Inflammation and Tumor Infiltration by Lymphocytes in Breast Cancer

The prognostic impact of tumor-infiltrating lymphocytes (TILs) is intensively investigated in breast cancer (BC). It is already known that triple-negative breast cancer (TNBC), the most aggressive type of BC, has the highest percentage of TILs. In addition, there is an influence of steroid hormone receptor expression (type I nuclear receptors) on TIL subpopulations in breast cancer tissue. The link between type II nuclear receptors and the level of TILs is unclear. Therefore, the aim of this study was to quantify TILs in a panel of 264 sporadic breast cancers and investigate the correlation of TIL levels with type I and II nuclear receptors expression. TIL levels were significantly increased in the subgroup of TNBC. By contrast, they decreased in estrogen (ER)- or progesterone receptor (PR)-positive cases. Moreover, TIL levels were correlated with type II nuclear receptors, including PPARγ, with a significant inverse correlation of the nuclear form (r = −0.727, p < 0.001) and a weak positive correlation of the cytoplasmic form (r = 0.202, p < 0.002). Surprisingly, BC cases with a TIL Salgado score of >15% showed a significantly decreased overall survival. In addition, peritumoral inflammation was also quantified in BC tissue samples. In our cohort, although the level of peritumoral inflammation was not correlated with OS, it determined the prognostic value of ER, PR, and PPARγ in BC. Altogether, the present study provides a differentiated overview of the relations between nuclear receptor expression, TIL levels, peritumoral inflammation, and prognosis in BC.

Dysregulation of splicing variants and spliceosome components in breast cancer

The dysregulation of the splicing process has emerged as a novel hallmark of metabolic and tumor pathologies. In breast cancer (BCa), which represents the most diagnosed cancer type among women worldwide, the generation and/or dysregulation of several oncogenic splicing variants have been described. This is the case of the splicing variants of HER2, ER, BRCA1, or the recently identified by our group, In1-ghrelin and SST5TMD4, which exhibit oncogenic roles, increasing the malignancy, poor prognosis, and resistance to treatment of BCa. This altered expression of oncogenic splicing variants has been closely linked with the dysregulation of the elements belonging to the macromolecular machinery that controls the splicing process (spliceosome components and the associated splicing factors). In this review, we compile the current knowledge demonstrating the altered expression of splicing variants and spliceosomal components in BCa, showing the existence of a growing body of evidence supporting the close implication of the alteration in the splicing process in mammary tumorigenesis.

Prognostic alternative splicing events related splicing factors define the tumor microenvironment and pharmacogenomic landscape in lung adenocarcinoma

Background: Recent studies identified correlations between splicing factors (SFs) and tumor progression and therapy. However, the potential roles of SFs in immune regulation and the tumor microenvironment (TME) remain unknown.

Methods: We used UpSet plots to screen for prognostic-related alternative splicing (AS) events. We evaluated SF patterns in specific immune landscapes. Single sample gene set enrichment analysis (ssGSEA) algorithms were used to quantify relative infiltration levels in immune cell subsets. Principal component analysis (PCA) algorithm-based SFscore were used to evaluate SF patterns in individual tumors with an immune response.

Results: From prognosis-related AS events, 16 prognosis-related SFs were selected to construct three SF patterns. Further TME analyses showed these patterns were highly consistent with immune-inflamed, immune-excluded, and immune-desert landscapes. Based on SFscore constructed using differentially expressed genes (DEGs) between SF patterns, patients were classified into two immune-subtypes associated with differential pharmacogenomic landscapes and cell features. A low SFscore was associated with high immune cell infiltration, high tumor mutation burden (TMB), and elevated expression of immune check points (ICPs), indicating a better immune response.

Conclusions: SFs are significantly associated with TME remodeling. Evaluating different SF patterns enhances our understanding of the TME and improves effective immunotherapy strategies.

The Role of Alternative Splicing in Cancer: Regulatory Mechanism, Therapeutic Strategy, and Bioinformatics Application

[Formula: see text] Alternative splicing (AS) can generate distinct transcripts and subsequent isoforms that play differential functions from the same pre-mRNA. Recently, increasing numbers of studies have emerged, unmasking the association between AS and cancer. In this review, we arranged AS events that are closely related to cancer progression and presented promising treatments based on AS for cancer therapy. Obtaining proliferative capacity, acquiring invasive properties, gaining angiogenic features, shifting metabolic ability, and getting immune escape inclination are all splicing events involved in biological processes. Spliceosome-targeted and antisense oligonucleotide technologies are two novel strategies that are hopeful in tumor therapy. In addition, bioinformatics applications based on AS were summarized for better prediction and elucidation of regulatory routines mingled in. Together, we aimed to provide a better understanding of complicated AS events associated with cancer biology and reveal AS a promising target of cancer treatment in the future.

CD68 and CD83 immune populations in non-metastatic axillary lymph nodes are of prognostic value for the survival and relapse of breast cancer patients

BACKGROUND

The foremost cause of death of breast cancer (BC) patients is metastasis, and the first site to which BC predominantly metastasizes is the axillary lymph node (ALN). Thus, ALN status is a key prognostic indicator at diagnosis. The immune system has an essential role in cancer progression and dissemination, so its evaluation in ALNs could have significant applications. In the present study we aimed to investigate the association of clinical-pathological and immune variables in the primary tumour and non-metastatic ALNs (ALNs^-) of a cohort of luminal A and triple-negative BC (TNBC) patients with cancer-specific survival (CSS) and time to progression (TTP).

METHODS

We analysed the differences in the variables between patients with different outcomes, created univariate and multivariate Cox regression models, validated them by bootstrapping and multiple imputation of missing data techniques, and used Kaplan-Meier survival curves for a 10-years follow-up.

RESULTS

We found some clinical-pathological variables at diagnosis (tumour diameter, TNBC molecular profile and presence of ALN metastasis), and the levels of several immune markers in the two studied sites, to be associated with worse CSS and TTP. Nevertheless, only CD68 and CD83 in ALNs^- were confirmed as independent prognostic factors for TTP.

CONCLUSIONS

The study identified the importance of macrophage and dendritic cell markers as prognostic factors of relapse for BC. We highlight the importance of studying the immune response in ALNs^-, which could be relevant to the prediction of BC patients' outcome.

Prognostic Signatures of Alternative Splicing Events in Esophageal Carcinoma Based on TCGA Splice-Seq Data

An alternative splicing (AS) event is a highly complex process that plays an essential role in post-transcriptional gene expression. Several studies have suggested that abnormal AS events were the primary element in the pathological process of cancer. However, few works are dedicated to the study of AS events in esophageal carcinoma (EC). In the present study, clinical information and RNA-seq data of EC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The percent spliced in (PSI) values of AS events were acquired from the TCGA Splice-seq. A total of 183 EC patients were enrolled in this study, and 2,212 AS events were found significantly associated with the overall survival of these patients by univariate Cox regression analysis. The prognostic signatures based on AS events were built by multivariate Cox analysis. Receiver operating characteristic (ROC) curves displayed that the area under the curve (AUC) of the following prognostic signatures, including exon skip (ES), alternate terminator (AT), alternate acceptor site (AA), alternate promoter (AP), alternate donor site (AD), retained intron (RI), and total events, was greater than 0.8, suggesting that these seven signatures had valuable prognosis prediction capacity. Finally, the risk score of prognostic signatures was indicated as an independent risk factor of survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the function of splicing factors (SFs) that were associated with AS events. Also, the interactive network between AS events and SFs identified several hub genes and AS events which need further study. This was a comprehensive study that explored prognosis-related AS events and established valuable prognosis signatures in EC patients. The network of interactions between AS events and SFs might offer novel insights into the fundamental mechanisms of tumorigenesis and progression of EC.

Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer

Recent evidence suggests that splicing factors (SFs) and alternative splicing (AS) play important roles in cancer progression. We constructed four SF-risk-models using 12 survival-related SFs. In Luminal-A, Luminal-B, Her-2, and Basal-Like BRCA, SF-risk-models for three genes (PAXBP1, NKAP, and NCBP2), four genes (RBM15B, PNN, ACIN1, and SRSF8), three genes (LSM3, SNRNP200, and SNU13), and three genes (SRPK3, PUF60, and PNN) were constructed. These models have a promising prognosis-predicting power. The co-expression and protein-protein interaction analysis suggest that the 12 SFs are highly functional-connected. Pathway analysis and gene set enrichment analysis suggests that the functional role of the selected 12 SFs is highly context-dependent among different BRCA subtypes. We further constructed four AS-risk-models with good prognosis predicting ability in four BRCA subtypes by integrating the four SF-risk-models and 21 survival-related AS-events. This study proposed that SFs and ASs were potential multidimensional biomarkers for the diagnosis, prognosis, and treatment of BRCA.

Systemic characterization of alternative splicing related to prognosis and immune infiltration in malignant mesothelioma

BACKGROUND

Malignant mesothelioma (MM) is a relatively rare and highly lethal tumor with few treatment options. Thus, it is important to identify prognostic markers that can help clinicians diagnose mesothelioma earlier and assess disease activity more accurately. Alternative splicing (AS) events have been recognized as critical signatures for tumor diagnosis and treatment in multiple cancers, including MM.

METHODS

We systematically examined the AS events and clinical information of 83 MM samples from TCGA database. Univariate Cox regression analysis was used to identify AS events associated with overall survival. LASSO analyses followed by multivariate Cox regression analyses were conducted to construct the prognostic signatures and assess the accuracy of these prognostic signatures by receiver operating characteristic (ROC) curve and Kaplan-Meier survival analyses. The ImmuCellAI and ssGSEA algorithms were used to assess the degrees of immune cell infiltration in MM samples. The survival-related splicing regulatory network was established based on the correlation between survival-related AS events and splicing factors (SFs).

RESULTS

A total of 3976 AS events associated with overall survival were identified by univariate Cox regression analysis, and ES events accounted for the greatest proportion. We constructed prognostic signatures based on survival-related AS events. The prognostic signatures proved to be an efficient predictor with an area under the curve (AUC) greater than 0.9. Additionally, the risk score based on 6 key AS events proved to be an independent prognostic factor, and a nomogram composed of 6 key AS events was established. We found that the risk score was significantly decreased in patients with the epithelioid subtype. In addition, unsupervised clustering clearly showed that the risk score was associated with immune cell infiltration. The abundances of cytotoxic T (Tc) cells, natural killer (NK) cells and T-helper 17 (Th17) cells were higher in the high-risk group, whereas the abundances of induced regulatory T (iTreg) cells were lower in the high-risk group. Finally, we identified 3 SFs (HSPB1, INTS1 and LUC7L2) that were significantly associated with MM patient survival and then constructed a regulatory network between the 3 SFs and survival-related AS to reveal potential regulatory mechanisms in MM.

CONCLUSION

Our study provided a prognostic signature based on 6 key events, representing a better effective tumor-specific diagnostic and prognostic marker than the TNM staging system. AS events that are correlated with the immune system may be potential therapeutic targets for MM.

Identification and Validation of a Prognostic Immune-Related Alternative Splicing Events Signature for Glioma

Background

Glioma is the most common malignant brain tumor in adults, with its tumor-promoting immune microenvironment always being intricate to handle with. Amounts of evidence has accumulated to suggest that alternative splicing (AS) is related to tumor immune microenvironment. However, comprehensive analysis of immune-related AS events and their clinical significance are still lacking in glioma.

Methods

AS events and transcriptome data of 653 glioma patients were downloaded online. ssGSEA was performed on transcriptome data of 653 patients to divided them into low, medium and high immune cell infiltration groups. Immune-related AS events were filtrated based on this grouping. Then lasso Cox regression analysis and multivariate Cox regression analysis were done to achieve an immune-related AS events prognostic signature for glioma. Kaplan-Meier analysis, ROC analyses, univariate Cox regression and multivariate Cox regression were performed to reveal the independent prognostic role of this signature. Meanwhile, a nomogram was constructed to achieved better prognostic value for glioma patients. Besides, functional enrichment analyses and correlation analyses with immune cells infiltration were used to validated the immune-related characteristic of this signature.

Results

36 immune-related AS events were achieved based on the grouping mentioned above. A nine-immune-related alternative splicing event signature was built for glioma patients. This signature showed an independent prognostic value and a nomogram containing gender, age, Karnofsky performance score, grade, IDH status, MGMT promoter status and risk score derived from the signature was constructed with a higher predictive ability for overall survival. Association with the infiltration of immune cell subtypes was validated and functional enrichment analysis found that the signature was mainly enriched in immune-related and pro-tumor functions.

Conclusion

Our research presented all immune-related AS events in glioma, identified an immune-related prognostic AS events risk model and a nomogram was constructed to predict the prognosis individually and more precisely. Tight connection was verified between this signature and clinical characteristics. Also, immune cells infiltration and immune checkpoints expression level were proved to link to risk scores, which enhanced the understanding of relationship between AS events and glioma immune microenvironment, firstly revealing the potential role of AS in immunotherapy of glioma.