Alternative splicing acts as an independent prognosticator in ovarian carcinoma

The Many Roads from Alternative Splicing to Cancer: Molecular Mechanisms Involving Driver Genes

Cancer driver genes are either oncogenes or tumour suppressor genes that are classically activated or inactivated, respectively, by driver mutations. Alternative splicing-which produces various mature mRNAs and, eventually, protein variants from a single gene-may also result in driving neoplastic transformation because of the different and often opposed functions of the variants of driver genes. The present review analyses the different alternative splicing events that result in driving neoplastic transformation, with an emphasis on their molecular mechanisms. To do this, we collected a list of 568 gene drivers of cancer and revised the literature to select those involved in the alternative splicing of other genes as well as those in which its pre-mRNA is subject to alternative splicing, with the result, in both cases, of producing an oncogenic isoform. Thirty-one genes fall into the first category, which includes splicing factors and components of the spliceosome and splicing regulators. In the second category, namely that comprising driver genes in which alternative splicing produces the oncogenic isoform, 168 genes were found. Then, we grouped them according to the molecular mechanisms responsible for alternative splicing yielding oncogenic isoforms, namely, mutations in cis splicing-determining elements, other causes involving non-mutated cis elements, changes in splicing factors, and epigenetic and chromatin-related changes. The data given in the present review substantiate the idea that aberrant splicing may regulate the activation of proto-oncogenes or inactivation of tumour suppressor genes and details on the mechanisms involved are given for more than 40 driver genes.

Advancements in protein glycosylation biomarkers for ovarian cancer through mass spectrometry-based approaches

INTRODUCTION

Ovarian cancer, characterized by metastasis and reduced 5-year survival rates, stands as a substantial factor in the mortality of gynecological malignancies worldwide. The challenge of delayed diagnosis originates from vague early symptoms and the absence of efficient screening and diagnostic biomarkers for early cancer detection. Recent studies have explored the intricate interplay between ovarian cancer and protein glycosylation, unveiling the potential significance of glycosylation-oriented biomarkers.

AREAS COVERED

This review examines the progress in glycosylation biomarker research, with particular emphasis on advances driven by mass spectrometry-based technologies. We document milestones achieved, discuss encountered limitations, and also highlight potential areas for future research and development of protein glycosylation biomarkers for ovarian cancer.

EXPERT OPINION

The association of glycosylation in ovarian cancer is well known, but current research lacks desired sensitivity and specificity for early detection. Notably, investigations into protein-specific and site-specific glycoproteomics have the potential to significantly enhance our understanding of ovarian cancer and facilitate the identification of glycosylation-based biomarkers. Furthermore, the integration of advanced mass spectrometry techniques with AI-driven analysis and glycome databases holds the promise for revolutionizing biomarker discovery for ovarian cancer, ultimately transforming diagnosis and improving patient outcomes.

Transcriptome Responses to Different Salinity Conditions in Litoditis marina, Revealed by Long-Read Sequencing

The marine nematode Litoditis marina is widely distributed in intertidal zones around the globe, yet the mechanisms underlying its broad adaptation to salinity remain elusive. In this study, we applied ONT long-read sequencing technology to unravel the transcriptome responses to different salinity conditions in L. marina. Through ONT sequencing under 3‱, 30‱ and 60‱ salinity environments, we obtained 131.78 G clean data and 26,647 non-redundant long-read transcripts, including 6464 novel transcripts. The DEGs obtained from the current ONT lrRNA-seq were highly correlated with those identified in our previously reported Illumina short-read RNA sequencing data. When we compared the 30‱ to the 3‱ salinity condition, we found that GO terms such as oxidoreductase activity, cation transmembrane transport and ion transmembrane transport were shared between the ONT lrRNA-seq and Illumina data. Similarly, GO terms including extracellular space, structural constituents of cuticle, substrate-specific channel activity, ion transport and substrate-specific transmembrane transporter activity were shared between the ONT and Illumina data under 60‱ compared to 30‱ salinity. In addition, we found that 79 genes significantly increased, while 119 genes significantly decreased, as the salinity increased. Furthermore, through the GO enrichment analysis of 214 genes containing DAS, in 30‱ compared to 3‱ salinity, we found that GO terms such as cellular component assembly and coenzyme biosynthetic process were enriched. Additionally, we observed that GO terms such as cellular component assembly and coenzyme biosynthetic process were also enriched in 60‱ compared to 30‱ salinity. Moreover, we found that 86, 125, and 81 genes that contained DAS were also DEGs, in comparisons between 30‱ and 3‱, 60‱ and 30‱, and 60‱ and 3‱ salinity, respectively. In addition, we demonstrated the landscape of alternative polyadenylation in marine nematode under different salinity conditions This report provides several novel insights for the further study of the mechanisms by which euryhalinity formed and evolved, and it might also contribute to the investigation of salinity dynamics induced by global climate change.

Autosurv: interpretable deep learning framework for cancer survival analysis incorporating clinical and multi-omics data

Accurate prognosis for cancer patients can provide critical information for optimizing treatment plans and improving life quality. Combining omics data and demographic/clinical information can offer a more comprehensive view of cancer prognosis than using omics or clinical data alone and can also reveal the underlying disease mechanisms at the molecular level. In this study, we developed and validated a deep learning framework to extract information from high-dimensional gene expression and miRNA expression data and conduct prognosis prediction for breast cancer and ovarian-cancer patients using multiple independent multi-omics datasets. Our model achieved significantly better prognosis prediction than the current machine learning and deep learning approaches in various settings. Moreover, an interpretation method was applied to tackle the "black-box" nature of deep neural networks and we identified features (i.e., genes, miRNA, demographic/clinical variables) that were important to distinguish predicted high- and low-risk patients. The significance of the identified features was partially supported by previous studies.

Pharmacological depletion of RNA splicing factor RBM39 by indisulam synergizes with PARP inhibitors in high-grade serous ovarian carcinoma

Ovarian high-grade serous carcinoma (HGSC) is the most common subtype of ovarian cancer with limited therapeutic options and a poor prognosis. In recent years, poly-ADP ribose polymerase (PARP) inhibitors have demonstrated significant clinical benefits, especially in patients with BRCA1/2 mutations. However, acquired drug resistance and relapse is a major challenge. Indisulam (E7070) has been identified as a molecular glue that brings together splicing factor RBM39 and DCAF15 E3 ubiquitin ligase resulting in polyubiquitination, degradation, and subsequent RNA splicing defects. In this work, we demonstrate that the loss of RBM39 induces splicing defects in key DNA damage repair genes in ovarian cancer, leading to increased sensitivity to cisplatin and various PARP inhibitors. The addition of indisulam also improved olaparib response in mice bearing PARP inhibitor-resistant tumors. These findings demonstrate that combining RBM39 degraders and PARP inhibitors is a promising therapeutic approach to improve PARP inhibitor response in ovarian HGSC.

AUTOSURV: INTERPRETABLE DEEP LEARNING FRAMEWORK FOR CANCER SURVIVAL ANALYSIS INCORPORATING CLINICAL AND MULTI-OMICS DATA

Accurate prognosis for cancer patients can provide critical information for optimizing treatment plans and improving life quality. Combining omics data and demographic/clinical information can offer a more comprehensive view of cancer prognosis than using omics or clinical data alone and can reveal the underlying disease mechanisms at the molecular level. In this study, we developed a novel deep learning framework to extract information from high-dimensional gene expression and miRNA expression data and conduct prognosis prediction for breast cancer and ovarian cancer patients. Our model achieved significantly better prognosis prediction than the conventional Cox Proportional Hazard model and other competitive deep learning approaches in various settings. Moreover, an interpretation approach was applied to tackle the "black-box" nature of deep neural networks and we identified features (i.e., genes, miRNA, demographic/clinical variables) that made important contributions to distinguishing predicted high- and low-risk patients. The identified associations were partially supported by previous studies.

Deciphering Nucleic Acid Binding Proteome of Mouse Immune Organs Reveals Hub Proteins for Aging

Profiling the nucleic acid-binding proteins (NABPs) during aging process is critical to elucidate its roles in biological systems as well as transcriptional and translational regulation. Here, we developed a comprehensive strategy to survey the NABPs of mouse immune organs by using single cell preparation and selective capture technology-based proteomics. Our approach provided a global view of tissue NABPs from different organs under normal physiological conditions with extraction specificity of 70 to 90%. Through quantitative proteomics analysis of mouse spleen and thymus at 1, 4, 12, 24, 48, and 72 weeks, we investigated the molecular features of aging-related NABPs. A total of 2674 proteins were quantified in all six stages, demonstrating distinct and time-specific expression pattern of NABPs. Thymus and spleen exhibited unique aging signatures, and differential proteins and pathways were enriched across the mouse lifespan. Three core modules and 16 hub proteins associated with aging were revealed through weighted gene correlation network analysis. Significant candidates were screened for immunoassay verification, and six hub proteins were confirmed. The integrated strategy pertains the capability to decipher the dynamic functions of NABPs in aging physiology and benefit further mechanism research.

Alternative splicing of HSPA12A pre-RNA by SRSF11 contributes to metastasis potential of colorectal cancer

BACKGROUND

Dysregulation of alternative splicing (AS) induced by serine/arginine-rich proteins has recently been linked to cancer metastasis. Nonetheless, as a member of the serine/arginine-rich protein family, the involvement of SRSF11 in colorectal cancer (CRC) is unknown.

METHODS

The TCGA dataset and clinical samples were used to assess SRSF11 expression levels in CRC. For SRSF11, functional experiments were conducted both in vitro and in vivo. RNA-seq technology was used to analyze and screen SRSF11-triggered AS events, which were then confirmed by in vivo UV crosslinking and immunoprecipitation (CLIP) and mini-gene reporter assays. Jalview software was used to determine the preferential binding motif with relation to exon skipping (ES) events. Furthermore, coimmunoprecipitation (Co-IP) and Phospho-tag SDS-PAGE experiments were used to investigate PAK5-mediated phosphorylation regulation on SRSF11, and in vitro kinase experiments validated the interaction.

RESULTS

In CRC, SRSF11 was discovered to be overexpressed and associated with a poor prognosis. And SRSF11 played a pro-metastatic role in vitro and in vivo. By screening SRSF11-regulated AS events, we identified the binding motif of SRSF11-triggered splicing-switching of HSPA12A AS, which specifically regulated HSPA12A AS by directly binding to a motif in exon 2. Mechanistically, the HSPA12A transcript with exon 2 retention increased N-cadherin expression by promoting RNA stability. Furthermore, the oncogenic kinase PAK5 phosphorylated SRSF11 at serine 287, protecting it from ubiquitination degradation.

CONCLUSIONS

SRSF11 exerts pro-metastatic effects in CRC by inhibiting the AS of HSPA12A pre-RNA. Our findings point to SRSF11-regulated HSPA12A splicing as a novel relationship between SRSF11-regulated splicing and CRC metastasis and suggest a PAK5/SRSF11/HSPA12A axis as a potential therapeutic target and prognostic biomarker in CRC.

Transcriptome Analyses Reveal Essential Roles of Alternative Splicing Regulation in Heat-Stressed Holstein Cows

Heat stress (HS) severely impacts the productivity and welfare of dairy cows. Investigating the biological mechanisms underlying HS response is crucial for developing effective mitigation and breeding strategies. Therefore, we evaluated the changes in milk yield, physiological indicators, blood biochemical parameters, and alternative splicing (AS) patterns of lactating Holstein cows during thermoneutral (TN, N = 19) and heat-stress (HS, N = 17) conditions. There was a significant (p < 0.05) decline in milk yield as physiological indicators increased after exposure to natural HS conditions. The levels of eight out of 13 biochemical parameters of HS were also significantly altered in the presence of HS (p < 0.05). These results demonstrate that HS negatively influences various biological processes of Holstein cows. Furthermore, we investigated AS events based on the RNA-seq data from blood samples. With HS, five common types of AS events were generally increased by 6.7−38.9%. A total of 3470 AS events corresponding to 3143 unique genes were differentially alternatively spliced (DSGs) (p-adjusted < 0.05) between TN and HS groups. The functional annotation results show that the majority of DSGs are involved in mRNA splicing and spliceosomal complex, followed by enrichment in immune and metabolic processes. Eighty-seven out of 645 differentially expressed genes (DEGs) (fold change ≥ 1.5 and false discovery rate < 0.05) overlapped with DSGs. Further analyses showed that 20 of these genes were significantly enriched for the RNA splicing, RNA binding, and RNA transport. Among them, two genes (RBM25 and LUC7L3) had strong interrelation and co-expression pattern with other genes and were identified as candidate genes potentially associated with HS responses in dairy cows. In summary, AS plays a crucial role in changing the transcriptome diversity of heat-stress-related genes in multiple biological pathways and provides a different regulation mechanism from DEGs.

Screening and Identification of Survival-Associated Splicing Factors in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LUSC) is a disease with high morbidity and mortality. Many studies have shown that aberrant alternative splicing (AS) can lead to tumorigenesis, and splicing factors (SFs) serve as an important function during AS. In this research, we propose an analysis method based on synergy to screen key factors that regulate the initiation and progression of LUSC. We first screened alternative splicing events (ASEs) associated with survival in LUSC patients by bivariate Cox regression analysis. Then an association network consisting of OS-ASEs, SFs, and their targeting relationship was constructed to identify key SFs. Finally, 10 key SFs were selected in terms of degree centrality. The validation on TCGA and cross-platform GEO datasets showed that some SFs were significantly differentially expressed in cancer and paracancer tissues, and some of them were associated with prognosis, indicating that our method is valid and accurate. It is expected that our method would be applied to a wide range of research fields and provide new insights in the future.

Comprehensive characterization of 11 prognostic alternative splicing events in ovarian cancer interacted with the immune microenvironment

Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. Transcriptome data and Percent Spliced In (PSI) values of ovarian cancer patients were downloaded from TCGA database and TCGA SpliceSeq. Totally we identified 1472 AS events that were associated with survival of ovarian serous cystadenocarcinoma (OC) and exon skipping (ES) was the most important type. Univariate and multivariate Cox regression analysis were performed to identify survival-associated AS events and developed the prognostic model based on 11-AS events. The immune cells and different response to cytotoxic T lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) blockers in low-risk and high-risk group of OC patients were analyzed. Ten kinds of immune cells were found up-regulated in low-risk group. Activated B cell, natural killer T cell, natural killer cell and regulatory T cell were associated with survival of OC. The patients in low-risk group had good response to CTLA-4 and PD-1 blockers treatment. Moreover, a regulatory network was established according to the correlation between AS events and splicing factors (SFs). The present study provided valuable insights into the underlying mechanisms of OC. AS events that were correlated with the immune system might be potential therapeutic targets.

Temporal Modulation of Differential Alternative Splicing in HaCaT Human Keratinocyte Cell Line Chronically Exposed to Arsenic for up to 28 Wk

BACKGROUND

Chronic arsenic exposure via drinking water is associated with an increased risk of developing cancer and noncancer chronic diseases. Pre-mRNAs are often subject to alternative splicing, generating mRNA isoforms encoding functionally distinct protein isoforms. The resulting imbalance in isoform species can result in pathogenic changes in critical signaling pathways. Alternative splicing as a mechanism of arsenic-induced toxicity and carcinogenicity is understudied.

OBJECTIVE

This study aimed to accurately profile differential alternative splicing events in human keratinocytes induced by chronic arsenic exposure that might play a role in carcinogenesis.

METHODS

Independent quadruplicate cultures of immortalized human keratinocytes (HaCaT) were maintained continuously for 28 wk with 0 or 100 nM sodium arsenite. RNA-sequencing (RNA-Seq) was performed with poly(A) RNA isolated from cells harvested at 7, 19, and 28 wk with subsequent replicate multivariate analysis of transcript splicing (rMATS) analysis to detect and quantify differential alternative splicing events. Reverse transcriptase-polymerase chain reaction (RT-PCR) for selected alternative splicing events was performed to validate RNA-Seq predictions. Functional enrichment was performed by gene ontology (GO) analysis of the differential alternative splicing event data set at each time point.

RESULTS

At least 600 differential alternative splicing events were detected at each time point tested, comprising all the five main types of alternative splicing and occurring in both open reading frames (ORFs) and untranslated regions (UTRs). Based on functional relevance ELK4, SHC1, and XRRA1 were selected for validation of predicted alternative splicing events at 7 wk by RT-PCR. Densitometric analysis of RT-PCR data corroborated the rMATS predicted alternative splicing for all three events. Protein expression validation of the selected alternative splicing events was challenging given that very few isoform-specific antibodies are available. GO analysis demonstrated that the enriched terms in differential alternatively spliced mRNAs changed dynamically with the time of exposure. Notably, RNA metabolism and splicing regulation pathways were enriched at the 7-wk time point, when the greatest number of differentially alternatively spliced mRNAs are detected. Our preliminary proteomic analysis demonstrated that the expression of the canonical isoforms of the splice regulators DDX42, RMB25, and SRRM2 were induced upon chronic arsenic exposure, corroborating the splicing predictions.

DISCUSSION

These results using cultures of HaCaT cells suggest that arsenic exposure disrupted an alternative splice factor network and induced time-dependent genome-wide differential alternative splicing that likely contributed to the changing proteomic landscape in arsenic-induced carcinogenesis. However, significant challenges remain in corroborating alternative splicing data at the proteomic level. https://doi.org/10.1289/EHP9676.

Hsp90-associated DNA replication checkpoint protein and proteasome-subunit components are involved in the age-related macular degeneration

Background:

Age-related macular degeneration (AMD) is the leading cause of vision loss worldwide. However, the mechanisms involved in the development and progression of AMD are poorly delineated. We aimed to explore the critical genes involved in the progression of AMD.

Methods:

The differentially expressed genes (DEGs) in AMD retinal pigment epithelial (RPE)/choroid tissues were identified using the microarray datasets GSE99248 and GSE125564, which were downloaded from the gene expression omnibus database. The overlapping DEGs from the two datasets were screened to identify DEG-related biological pathways using gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The hub genes were identified from these DEGs through protein-protein interaction network analyses. The expression levels of hub genes were evaluated by quantitative real-time polymerase chain reaction following the induction of senescence in ARPE-19 with FK866. Following the identification of AMD-related key genes, the potential small molecule compounds targeting the key genes were predicted by PharmacoDB. Finally, a microRNA-gene interaction network was constructed.

Results:

Microarray analyses identified 174 DEGs in the AMD RPE compared to the healthy RPE samples. These DEGs were primarily enriched in the pathways involved in the regulation of DNA replication, cell cycle, and proteasome-mediated protein polyubiquitination. Among the top ten hub genes, HSP90AA1, CHEK1, PSMA4, PSMD4, and PSMD8 were upregulated in the senescent ARPE-19 cells. Additionally, the drugs targeting HSP90AA1, CHEK1, and PSMA4 were identified. We hypothesize that Hsa-miR-16-5p might target four out of the five key DEGs in the AMD RPE.

Conclusions:

Based on our findings, HSP90AA1 is likely to be a central gene controlling the DNA replication and proteasome-mediated polyubiquitination during the RPE senescence observed in the progression of AMD. Targeting HSP90AA1, CHEK1, PSMA4, PSMD4, and/or PSMD8 genes through specific miRNAs or small molecules might potentially alleviate the progression of AMD through attenuating RPE senescence.