Removal of introns from messenger RNA precursors (pre-mRNA splicing) is an essential step for the expression of most eukaryotic genes. Alternative splicing enables the regulated generation of multiple mRNA and protein products from a single gene. Cancer cells have general as well as cancer type-specific and subtype-specific alterations in the splicing process that can have prognostic value and contribute to every hallmark of cancer progression, including cancer immune responses. These splicing alterations are often linked to the occurrence of cancer driver mutations in genes encoding either core components or regulators of the splicing machinery. Of therapeutic relevance, the transcriptomic landscape of cancer cells makes them particularly vulnerable to pharmacological inhibition of splicing. Small-molecule splicing modulators are currently in clinical trials and, in addition to splice site-switching antisense oligonucleotides, offer the promise of novel and personalized approaches to cancer treatment.

Roles and mechanisms of alternative splicing in cancer - implications for care.

Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancer cases, with more than 850,000 new diagnoses per year globally. Recent trends in the United States have shown that liver cancer mortality has continued to increase in both men and women, while 5-year survival remains less than 20%. Understanding key mechanisms that drive chronic liver disease progression to HCC can show new therapeutic targets and biomarkers for early detection of HCC. In that regard, many studies have underscored the importance of alternative splicing as a source of novel HCC prognostic markers and disease targets. Alternative splicing of RNA provides functional diversity to the genome, and endows cells with the ability to rapidly remodel the proteome. Genes that control fundamental processes, such as metabolism, cell proliferation, and apoptosis, are altered globally in HCC by alternative splicing. This review highlights the major splicing factors, RNA binding proteins, transcriptional targets, and signaling pathways that are of key relevance to HCC. We highlight primary research from the past 3-5 years involving functional interrogation of alternative splicing in rodent and human liver, using both large-scale transcriptomic and focused mechanistic approaches. Because this is a rapidly advancing field, we anticipate that it will be transformative for the future of basic liver biology, as well as HCC diagnosis and management.

Alternative Splicing in Hepatocellular Carcinoma.

Most genes are alternatively spliced and increasing number of evidences show that alternative splicing (AS) is modified and related to tumor progression. Systematic profiles of AS signature in hepatocellular carcinoma (HCC) is absent and urgently needed. Here, differentially spliced AS transcripts between HCC and non-HCC tissues were compared, prognosis-associated AS events by using univariate Cox regression analysis were selected. Our gene functional enrichment analysis demonstrated the potential pathways enriched by survival-associated AS. Prognostic AS signatures were then constructed for HCC prognosis prediction by Lasso regression model. We also analyzed splicing factors (SFs) regulating underlying mechanisms by Pearson correlation and then built corresponding regulatory networks. In addition, we explored the performance of AS signature in the mutated HCC samples. Genome-wide AS events in 377 HCC patients from TCGA were profiled. Among 34 163 AS events in 8985 genes, 3950 AS events in 2403 genes associated with overall survival (OS) significantly for HCC were detected. In addition, computational algorithm results showed that metabolic and ribosome pathways may be the potential molecular mechanisms regulating the poor prognosis. More importantly, survival-associated AS signatures revealed high performance in predicting HCC prognosis. The area under curve for AS signature was 0.806 in all HCC and 0.944 in TP53 mutated HCC samples at 2000 days of OS. We submitted prognostic SFs to build the AS regulatory network, from which we found prognostic AS events were significantly enriched in metabolism-related pathways. A robust AS signature for HCC patients and revealed the regulatory splicing networks contributing to the potential significantly enriched metabolism-related pathways.

Prognostic alternative mRNA splicing signature in hepatocellular carcinoma: a study based on large-scale sequencing data

Alternative splicing events (ASEs) play a role in cancer development and progression We investigated whether ASEs are prognostic for overall survival (OS) in hepatocellular carcinoma (HCC) RNA sequencing data was obtained for 343 patients included in The Cancer Genome Atlas Matched splicing event data for these patients was then obtained from the TCGASpliceSeq database, which includes data for seven types of ASEs Univariate and multivariate Cox regression analysis demonstrated that 3,814 OS-associated splicing events (OS-SEs) were correlated with OS Prognostic indices were developed based on the most significant OS-SEs The prognostic index based on all seven types of ASEs (PI-ALL) demonstrated superior efficacy in predicting OS of HCC patients at 2,000 days compared to those based on single ASE types Patients were stratified into two risk groups (high and low) based on the median prognostic index Kaplan-Meier survival analysis demonstrated that PI-ALL had the greatest capacity to distinguish between patients with favorable vs poor outcomes Finally, univariate Cox regression analysis demonstrated that the expression of 23 splicing factors was correlated with OS-SEs in the HCC cohort Our data indicate that a prognostic index based on ASEs is prognostic for OS in HCC

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Alternative splicing events are prognostic in hepatocellular carcinoma.

Introduction: Glioblastoma multiforme (GBM) is the most common deadly brain malignancy and lacks effective therapies. Immunotherapy acts as a promising novel strategy, but not for all GBM patients. Therefore, classifying these patients into different prognostic groups is urgent for better personalized management. Materials and Methods: The Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to estimate the fraction of 22 types of immune-infiltrating cells, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune infiltration-related prognostic scoring system (IIRPSS). Additionally, a quantitative predicting survival nomogram was also established based on the immune risk score (IRS) derived from the IIRPSS. Moreover, we also preliminarily explored the differences in the immune microenvironment between different prognostic groups. Results: There was a total of 310 appropriate GBM samples (239 from TCGA and 71 from CGGA) included in further analyses after CIBERSORT filtering and data processing. The IIRPSS consisting of 17 types of immune cell fractions was constructed in TCGA cohort, the patients were successfully classified into different prognostic groups based on their immune risk score (p = 1e-10). What's more, the prognostic performance of the IIRPSS was validated in CGGA cohort (p = 0.005). The nomogram also showed a superior predicting value. (The predicting AUC for 1-, 2-, and 3-year were 0.754, 0.813, and 0.871, respectively). The immune microenvironment analyses reflected a significant immune response and a higher immune checkpoint expression in high-risk immune group. Conclusion: Our study constructed an IIRPSS, which maybe valuable to help clinicians select candidates most likely to benefit from immunological checkpoint inhibitors (ICIs) and laid the foundation for further improving personalized immunotherapy in patients with GBM.

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Development of an Immune Infiltration-Related Prognostic Scoring System Based on the Genomic Landscape Analysis of Glioblastoma Multiforme.

Background: Major treatments for small hepatocellular carcinoma (SHCC) include percutaneous ethanol injection (PEI), percutaneous acetic acid injection (PAI), radiofrequency ablation (RFA), or surg...

Comparative efficacy and safety between ablative therapies or surgery for small hepatocellular carcinoma: a network meta-analysis

There is a mutual hemodynamic and pathophysiological basis between the heart and brain. Glutamate (GLU) signaling plays an important role in the process of myocardial ischemia (MI) and ischemic stroke (IS). To further explore the common protective mechanism after cardiac and cerebral ischemic injuries, the relationship between GLU receptor-related genes and MI and IS were analyzed.A total of 25 crosstalk genes were identified, which were mainly enriched in the Toll-like receptor signaling pathway, Th17 cell differentiation, and other signaling pathways. Protein-protein interaction analysis suggested that the top six genes with the most interactions with shared genes were IL6, TLR4, IL1B, SRC, TLR2, and CCL2. Immune infiltration analysis suggested that immune cells such as myeloid-derived suppressor cells and monocytes were highly expressed in the MI and IS data. Memory B cells and Th17 cells were expressed at low levels in the MI and IS data; molecular interaction network construction suggested that genes such as JUN, FOS, and PPARA were shared genes and transcription factors; FCGR2A was a shared gene of MI and IS as well as an immune gene. Least absolute shrinkage and selection operator logistic regression analysis identified nine hub genes: IL1B, FOS, JUN, FCGR2A, IL6, AKT1, DRD4, GLUD2, and SRC. Receiver operating characteristic analysis revealed that the area under the curve of these hub genes was > 65% in MI and IS for all seven genes except IL6 and DRD4. Furthermore, clinical blood samples and cellular models showed that the expression of relevant hub genes was consistent with the bioinformatics analysis.In this study, we found that the GLU receptor-related genes IL1B, FOS, JUN, FCGR2A, and SRC were expressed in MI and IS with the same trend, which can be used to predict the occurrence of cardiac and cerebral ischemic diseases and provide reliable biomarkers to further explore the co-protective mechanism after cardiac and cerebral ischemic injury. 

https://bmcgenomics.biomedcentral.com/counter/pdf/10.1186/s12864-023-09408-z

Wei-Ting Liao

Papers

Prognostic alternative mRNA splicing signature in hepatocellular carcinoma: a study based on large-scale sequencing data

Comparative efficacy and safety between ablative therapies or surgery for small hepatocellular carcinoma: a network meta-analysis

Bioinformatics and experimental analyses of glutamate receptor and its targets genes in myocardial and cerebral ischemia