AS-CMC: a pan-cancer database of alternative splicing for molecular classification of cancer

Subtype-specific alternative splicing events in breast cancer identified by large-scale data analysis

Genome analysis in cancer has focused mainly on elucidating the function and regulatory mechanisms of genes that exhibit differential expression or mutation in cancer samples compared to normal samples. Recently, transcriptome analysis revealed that abnormal splicing events in cancer samples could contribute to cancer pathogenesis. Moreover, splicing variants in cancer reportedly generate diverse cancer antigens. Although abnormal splicing events are expected to be potential targets in cancer immunotherapy, the exploration of such targets and their biological significance in cancer have not been fully understood. In this study, to explore subtype-specific alternative splicing events, we conducted a comprehensive analysis of splicing events for each breast cancer subtype using large-scale splicing data derived from The Cancer Genome Atlas and found subtype-specific alternative splicing patterns. Analyses indicated that genes that produce subtype-specific alternative splicing events are potential novel targets for immunotherapy against breast cancer. The subtype-specific alternative splicing events identified in this study, which were not identified by mutation or differential expression analysis, bring new significance to previously overlooked splicing events.

RPS24 alternative splicing is a marker of cancer progression and epithelial-mesenchymal transition

Although alternative splicing (AS) is a major mechanism that adds diversity to gene expression patterns, its precise role in generating variability in ribosomal proteins, known as ribosomal heterogeneity, remains unclear. The ribosomal protein S24 (RPS24) gene, encoding a ribosomal component, undergoes AS; however, in-depth studies have been challenging because of three microexons between exons 4 and 6. We conducted a detailed analysis of RPS24 AS isoforms using a direct approach to investigate the splicing junctions related to these microexons, focusing on four AS isoforms. Each of these isoforms showed tissue specificity and relative differences in expression among cancer types. Significant differences in the proportions of these RPS24 AS isoforms between cancerous and normal tissues across diverse cancer types were also observed. Our study highlighted a significant correlation between the expression levels of a specific RPS24 AS isoform and the epithelial-mesenchymal transition process in lung and breast cancers. Our research contributes to a better understanding of the intricate regulatory mechanisms governing AS of ribosomal protein genes and highlights the biological implications of RPS24 AS isoforms in tissue development and tumorigenesis.

ACTL6A: unraveling its prognostic impact and paving the way for targeted therapeutics in carcinogenesis

Introduction: Increased Actin-like 6A (ACTL6A) expression is associated with various cancers, but its comprehensive investigation across different malignancies is lacking. We aimed to analyze ACTL6A as a potential oncogene and therapeutic target using bioinformatics tools. Methods: We comprehensively analyzed ACTL6A expression profiles across human malignancies, focusing on correlations with tumor grade, stage, metastasis, and patient survival. Genetic alterations were examined, and the epigenetic landscape of ACTL6A was assessed using rigorous methods. The impact of ACTL6A on immune cell infiltration in the tumor microenvironment was evaluated, along with molecular docking studies and machine learning models. Results: Our analysis revealed elevated ACTL6A expression in various tumors, correlating with poor prognostic indicators such as tumor grade, stage, metastasis, and patient survival. Genetic mutations and epigenetic modifications were identified, along with associations with immune cell infiltration and key cellular pathways. Machine learning models demonstrated ACTL6A's potential for cancer detection. Discussion: ACTL6A emerges as a promising diagnostic and therapeutic target in cancer, with implications for prognosis and therapy. Our study provides comprehensive insights into its carcinogenic actions, highlighting its potential as both a prognostic indicator and a target for anti-cancer therapy. This integrative approach enhances our understanding of ACTL6A's role in cancer pathogenesis and treatment.

Zaki M, Soltan MA, Noreldin AE. Oncogenic Potential of Replication Factor C Subunit 4: Correlations with Tumor Progression and Assessment of Potential Inhibitors

Replication Factor C Subunit 4 (RFC4), an oncogene implicated in many human cancers, has yet to be extensively studied in many cancer types to determine its expression patterns and tumor tissue function. Various bioinformatics tools were used to analyze RFC4 as a potential oncogene and therapeutic target across many cancers. We first examined RFC4 expression levels in several human tumor types to determine relationships with tumor grade, stage, metastasis, and patient survival. We also examined RFC4's genetic changes, epigenetic methylation, and effect on tumor microenvironment (TME) immune cell infiltration. We also analyzed RFC4's connections with immunological checkpoints to identify potential molecular pathways involved in carcinogenesis. Our findings show that RFC4 is upregulated in several tumor types and associated with poor prognoses in many human cancers. This study shows that RFC4 significantly affects the tumor immunological microenvironment, specifically immune cell populations. Finally, we screened for RFC4-inhibiting pharmacological compounds with anti-cancer potential. This study fully elucidates RFC4's carcinogenic activities, emphasizing its potential as a prognostic biomarker and a target for anti-cancer therapy.

Comparative RNA-Seq Analysis Revealed Tissue-Specific Splicing Variations during the Generation of the PDX Model

Tissue-specific gene expression generates fundamental differences in the function of each tissue and affects the characteristics of the tumors that are created as a result. However, it is unclear how much the tissue specificity is conserved during grafting of the primary tumor into an immune-compromised mouse model. Here, we performed a comparative RNA-seq analysis of four different primary-patient derived xenograft (PDX) tumors. The analysis revealed a conserved RNA biotype distribution of primary-PDX pairs, as revealed by previous works. Interestingly, we detected significant changes in the splicing pattern of PDX, which was mainly comprised of skipped exons. This was confirmed by splicing variant-specific RT-PCR analysis. On the other hand, the correlation analysis for the tissue-specific genes indicated overall strong positive correlations between the primary and PDX tumor pairs, with the exception of gastric cancer cases, which showed an inverse correlation. These data propose a tissue-specific change in splicing events during PDX formation as a variable factor that affects primary-PDX integrity.

SpliceWiz: interactive analysis and visualization of alternative splicing in R

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

Cyclin Dependent Kinase Inhibitor 2A Genetic and Epigenetic Alterations Interfere with Several Immune Components and Predict Poor Clinical Outcome

Cyclin dependent kinase inhibitor 2A (CDKN2A) is a well-known tumor suppressor gene as it functions as a cell cycle regulator. While several reports correlate the malfunction of CDKN2A with the initiation and progression of several types of human tumors, there is a lack of a comprehensive study that analyzes the potential effect of CDKN2A genetic alterations on the human immune components and the consequences of that effect on tumor progression and patient survival in a pan-cancer model. The first stage of the current study was the analysis of CDKN2A differential expression in tumor tissues and the corresponding normal ones and correlating that with tumor stage, grade, metastasis, and clinical outcome. Next, a detailed profile of CDKN2A genetic alteration under tumor conditions was described and assessed for its effect on the status of different human immune components. CDKN2A was found to be upregulated in cancerous tissues versus normal ones and that predicted the progression of tumor stage, grade, and metastasis in addition to poor prognosis under different forms of tumors. Additionally, CDKN2A experienced different forms of genetic alteration under tumor conditions, a characteristic that influenced the infiltration and the status of CD8, the chemokine CCL4, and the chemokine receptor CCR6. Collectively, the current study demonstrates the potential employment of CDKN2A genetic alteration as a prognostic and immunological biomarker under several types of human cancers.

Alternative splicing: a new breakthrough for understanding tumorigenesis and potential clinical applications

BACKGROUND

Alternative splicing (AS) is a post-transcriptional process that produces transcript variants, thus leading to transcriptome complexity. Recently, the scope of AS studies has been greatly expanded toward clinical applications owing to the abundance of RNA sequencing data.

OBJECTIVE

This review consists of two parts. We first summarize bioinformatic resources that are useful for large-scale cancer-related AS studies. We then highlight the research efforts to utilize AS events for predicting clinical outcomes and planning therapeutic strategies.

RESULTS

Computational approaches to interrogate AS events have been reviewed under three categories: (1) databases to provide functional and clinical annotation of AS events, (2) analytical tools to identify cancer-associated AS event, and (3) methods to identify splicing-related DNA variants and splicing-derived neoantigens. We also present the recent progress in exploring the clinical utility of AS under four categories: (1) identification of AS events for cancer prognosis, (2) utilization of AS events in molecular classification of various cancers, (3) regulatory mechanisms of AS underlying drug resistance, and (4) potential use of AS in cancer therapy.

CONCLUSION

This review will be helpful for understanding the biological implications of AS in cancer and facilitate the development of AS markers for cancer prognosis and treatment. We anticipate that future studies will lead to the application of genome-wide AS profiles in cancer precision medicine.