Identification and validation of alternative splicing isoforms as novel biomarker candidates in hepatocellular carcinoma

Decoding the role of aberrant RNA alternative splicing in hepatocellular carcinoma: a comprehensive review

During eukaryotic gene expression, alternative splicing of messenger RNA precursors is critical in increasing protein diversity and regulatory complexity. Multiple transcript isoforms could be produced by alternative splicing from a single gene; they could eventually be translated into protein isoforms with deleted, added, or altered domains or produce transcripts containing premature termination codons that could be targeted by nonsense-mediated mRNA decay. Alternative splicing can generate proteins with similar, different, or even opposite functions. Increasingly strong evidence indicates that abnormal RNA splicing is a prevalent and crucial occurrence in cellular differentiation, tissue advancement, and the development and progression of cancer. Aberrant alternative splicing could affect cancer cell activities such as growth, apoptosis, invasiveness, drug resistance, angiogenesis, and metabolism. This systematic review provides a comprehensive overview of the impact of abnormal RNA alternative splicing on the development and progression of hepatocellular carcinoma.

Vacuolar protein sorting 35 (VPS35) acts as a tumor promoter via facilitating cell cycle progression in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is insidious and highly malignant with extremely poor prognosis and drug resistance to current chemotherapies. Therefore, there is a critical need to investigate the molecular mechanism underlying PDAC progression to develop promising diagnostic and therapeutic interventions. In parallel, vacuolar protein sorting (VPS) proteins, involved in the sorting, transportation, and localization of membrane proteins, have gradually attracted the attention of researchers in the development of cancers. Although VPS35 has been reported to promote carcinoma progression, the specific molecular mechanism is still unclear. Here, we determined the impact of VPS35 on the tumorigenesis of PDAC and explored the underlying molecular mechanism. We performed a pan-cancer analysis of 46 VPS genes using RNAseq data from GTEx (control) and TCGA (tumor) and predicted potential functions of VPS35 in PDAC by enrichment analysis. Furthermore, cell cloning experiments, gene knockout, cell cycle analysis, immunohistochemistry, and other molecular and biochemical experiments were used to validate the function of VPS35. Consequently, VPS35 was found overexpressed in multiple cancers and correlated with the poor prognosis of PDAC. Meanwhile, we verified that VPS35 could modulate the cell cycle and promote tumor cell growth in PDAC. Collectively, we provide solid evidence that VPS35 facilitates the cell cycle progression as a critical novel target in PDAC clinical therapy.

Drug repurposing-an emerging strategy in cancer therapeutics

Cancer is a complex disease affecting millions of people around the world. Despite advances in surgical and radiation therapy, chemotherapy continues to be an important therapeutic option for the treatment of cancer. The current treatment is expensive and has several side effects. Also, over time, cancer cells develop resistance to chemotherapy, due to which there is a demand for new drugs. Drug repurposing is a novel approach that focuses on finding new applications for the old clinically approved drugs. Current advances in the high-dimensional multiomics landscape, especially proteomics, genomics, and computational omics-data analysis, have facilitated drug repurposing. The drug repurposing approach provides cheaper, effective, and safe drugs with fewer side effects and fastens the process of drug development. The review further delineates each repurposed drug's original indication and mechanism of action in cancer. Along with this, the article also provides insight upon artificial intelligence and its application in drug repurposing. Clinical trials are vital for determining medication safety and effectiveness, and hence the clinical studies for each repurposed medicine in cancer, including their stages, status, and National Clinical Trial (NCT) identification, are reported in this review article. Various emerging evidences imply that repurposing drugs is critical for the faster and more affordable discovery of anti-cancerous drugs, and the advent of artificial intelligence-based computational tools can accelerate the translational cancer-targeting pipeline.

Identification and Characterization of Alternatively Spliced Transcript Isoforms of IRX4 in Prostate Cancer

Alternative splicing (AS) is tightly regulated to maintain genomic stability in humans. However, tumor growth, metastasis and therapy resistance benefit from aberrant RNA splicing. Iroquois-class homeodomain protein 4 (IRX4) is a TALE homeobox transcription factor which has been implicated in prostate cancer (PCa) as a tumor suppressor through genome-wide association studies (GWAS) and functional follow-up studies. In the current study, we characterized 12 IRX4 transcripts in PCa cell lines, including seven novel transcripts by RT-PCR and sequencing. They demonstrate unique expression profiles between androgen-responsive and nonresponsive cell lines. These transcripts were significantly overexpressed in PCa cell lines and the cancer genome atlas program (TCGA) PCa clinical specimens, suggesting their probable involvement in PCa progression. Moreover, a PCa risk-associated SNP rs12653946 genotype GG was corelated with lower IRX4 transcript levels. Using mass spectrometry analysis, we identified two IRX4 protein isoforms (54.4 kDa, 57 kDa) comprising all the functional domains and two novel isoforms (40 kDa, 8.7 kDa) lacking functional domains. These IRX4 isoforms might induce distinct functional programming that could contribute to PCa hallmarks, thus providing novel insights into diagnostic, prognostic and therapeutic significance in PCa management.

Profiles of prognostic alternative splicing signature in hepatocellular carcinoma

Previous studies have demonstrated the role of abnormal alternative splicing (AS) in tumor progression. This study examines the prognostic index (PI) of alternative splices (ASs) in patients with hepatocellular carcinoma (HCC). The clinical features and splicing events of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed AS (DEAS) were compared between HCC and adjacent normal samples. Univariate Cox regression analysis was used to determine changes in DEAS associated with overall survival (OS). A PI was generated from OS‐associated DEASs using Kaplan‐Meier curves, receiver operating characteristic (ROC) curves, multivariate Cox regression, and cluster analysis. Then, the correlation between DEASs and splicing factors was assessed, followed by functional and pathway enrichment analysis. We identified 34 163 ASs of 8985 genes in HCC, and 153 OS‐ASs were identified using univariate Cox regression analysis. Low‐ and high‐PI groups were determined based on the median “PI‐ALL” value according to significantly different survival (P = 2.2e − 16). The ROC curve of all PI (PI‐ALL) had an area under the curve (AUC) of 0.993 for survival status in patients with HCC. A potential regulatory network associated with prognosis of patients with HCC was established. Enrichment analysis also resulted in the identification of several pathways potentially associated with carcinogenesis and progression of HCC. Four clusters were identified that were associated with clinical features and prognosis. Our study generated comprehensive profiles of ASs in HCC. The interaction network and functional connections were used to elucidate the underlying mechanisms of AS in HCC.

Alternative splicing events are prognostic in hepatocellular carcinoma

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.