Comprehensive Characterization of Alternative mRNA Splicing Events in Glioblastoma: Implications for Prognosis, Molecular Subtypes, and Immune Microenvironment Remodeling

A Single-Cell Atlas of RNA Alternative Splicing in the Glioma-Immune Ecosystem

Single-cell analysis has refined our understanding of cellular heterogeneity in glioma, yet RNA alternative splicing (AS)-a critical layer of transcriptome regulation-remains underexplored at single-cell resolution. Here, we present a pan-glioma single-cell AS analysis in both tumor and immune cells through integrating seven SMART-seq2 datasets of human gliomas. Our analysis reveals lineage-specific AS across glioma cellular states, with the most divergent AS landscapes between mesenchymal- and neuronal-like glioma cells, exemplified by AS in TCF12 and PTBP2. Comparison between core and peripheral glioma cells highlights AS-redox co-regulation of cytoskeleton organization. Further analysis of glioma-infiltrating immune cells reveals potential isoform-level regulation of protein glycosylation in regulatory T cells and a link between MS4A7 AS in macrophages and clinical response to anti-PD-1 therapy. This study emphasizes the role of AS in glioma cellular heterogeneity, highlighting the importance of an isoform-centric approach to better understand the complex biological processes driving tumorigenesis.

Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme

Aberrant alternative splicing and abnormal alternative splicing events (ASEs) in glioblastoma multiforme (GBM) remain largely elusive. The prognostic-associated ASEs in GBM were identified and summarized into 123 genes using GBM and LGG datasets from ASCancer Atlas and TCGA. The eleven genes (C2, COL3A1, CTSL, EIF3L, FKBP9, FN1, HPCAL1, HSPB1, IGFBP4, MANBA, PRKAR1B) were screened to develop an alternative splicing prognostic risk score (ASRS) model through machine learning algorithms. The model was trained on the TCGA-GBM cohort and validated with four external datasets from CGGA and GEO, achieving AUC values of 0.808, 0.814, 0.763, 0.859, and 0.836 for 3-year survival rates, respectively. ASRS could be an independent prognostic factor for GBM patients (HR > 1.8 across three datasets) through multivariate Cox regression analysis. The high-risk group demonstrated poorer prognosis, elevated immune scores, increased levels of immune cell infiltration, and greater differences in drug sensitivity. We found that FN1, used for model construction, contained 4 abnormal ASEs resulting in high expression of non-canonical transcripts and the presence of premature termination codon. These abnormal ASEs may be regulated by tumour-related splicing factors according to the PPI network. Furthermore, both mRNA and protein levels of FN1 were highly expressed in GBM compared to LGG, correlating with poor prognosis in GBM. In conclusion, our findings highlight the role of ASEs in affecting the progression of GBM, and the model showed a potential application for prognostic risk of patients. FN1 may serve as a promising splicing biomarker for GBM, and mechanisms of processes of aberrant splicing need to be revealed in the future.

RNA splicing analysis deciphers developmental hierarchies and reveals therapeutic targets in adult glioma

Widespread alterations in RNA alternative splicing (AS) have been identified in adult gliomas. However, their regulatory mechanism, biological significance, and therapeutic potential remain largely elusive. Here, using a computational approach with both bulk and single-cell RNA-Seq, we uncover a prognostic AS signature linked with neural developmental hierarchies. Using advanced iPSC glioma models driven by glioma driver mutations, we show that this AS signature could be enhanced by EGFRvIII and inhibited by in situ IDH1 mutation. Functional validations of 2 isoform switching events in CERS5 and MPZL1 show regulations of sphingolipid metabolism and SHP2 signaling, respectively. Analysis of upstream RNA binding proteins reveals PTBP1 as a key regulator of the AS signature where targeting of PTBP1 suppresses tumor growth and promotes the expression of a neuron marker TUJ1 in glioma stem-like cells. Overall, our data highlights the role of AS in affecting glioma malignancy and heterogeneity and its potential as a therapeutic vulnerability for treating adult gliomas.

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.

Interaction of a Novel Alternatively Spliced Variant of HSD11B1L with Parkin Enhances the Carcinogenesis Potential of Glioblastoma: Peiminine Interferes with This Interaction

Glioblastoma (GBM) is a primary brain tumor of unknown etiology. It is extremely aggressive, incurable and has a short average survival time for patients. Therefore, understanding the precise molecular mechanisms of this diseases is essential to establish effective treatments. In this study, we cloned and sequenced a splice variant of the hydroxysteroid 11-β dehydrogenase 1 like gene (HSD11B1L) and named it HSD11B1L-181. HSD11 B1L-181 was specifically expressed only in GBM cells. Overexpression of this variant can significantly promote the proliferation, migration and invasion of GBM cells. Knockdown of HSD11B1L-181 expression inhibited the oncogenic potential of GBM cells. Furthermore, we identified the direct interaction of parkin with HSD11B1L-181 by screening the GBM cDNA expression library via yeast two-hybrid. Parkin is an RBR E3 ubiquitin ligase whose mutations are associated with tumorigenesis. Small interfering RNA treatment of parkin enhanced the proliferative, migratory and invasive abilities of GBM. Finally, we found that the alkaloid peiminine from the bulbs of Fritillaria thunbergii Miq blocks the interaction between HSD11B1L-181 and parkin, thereby lessening carcinogenesis of GBM. We further confirmed the potential of peiminine to prevent GBM in cellular, ectopic and orthotopic xenograft mouse models. Taken together, these findings not only provide insight into GBM, but also present an opportunity for future GBM treatment.

Genome-wide identification of alternative splicing and splicing regulated in immune infiltration in osteosarcoma patients

Background: Osteosarcoma typically occurs in adolescents, and the survival rate of patients with metastatic and recurrent osteosarcoma remains low. Abnormal regulation of alternative splicing is associated with the development of osteosarcoma. However, there is no genome-wide analysis of the function and regulatory mechanisms of aberrant alternative splicing associated with osteosarcoma. Methods: Published transcriptome data on osteosarcoma (GSE126209) derived from osteosarcoma patient tissue were downloaded. Gene expression profiling by high-throughput sequencing was performed on 9 normal samples and 10 tumor samples for genome-wide identification of osteosarcoma-related alternative splicing events. The potential function of osteosarcoma-associated alternative splicing events was examined by immune infiltration and correlation analysis. Regulation of aberrantly expressed RNA-binding proteins (RBPs) related to alternative splicing in osteosarcoma was clarified by co-expression analysis. Results: A total of 63 alternative splicing events, which are highly credible and dominant, were identified. GO enrichment analysis indicated that alternative splicing may be closely related to the immune response process. Immune infiltration analysis showed significant changes in the percentages of CD8 T cells, resting memory CD4 T cells, activated memory CD4 T cells, monocytes, resting dendritic cells, and activated mast cells in tumors compared to normal tissues, indicating the involvement of these immune cell types in the occurrence of osteosarcoma. Moreover, the analysis identified alternative splicing events that were co-altered with resting memory CD4 T cells, resting dendritic cells, and activated mast cells, events that may be associated with regulation of the osteosarcoma immune microenvironment. In addition, a co-regulatory network (RBP-RAS-immune) of osteosarcoma-associated RBPs with aberrant alternative splicing and altered immune cells was established. These RBPs include NOP58, FAM120C, DYNC1H1, TRAP1, and LMNA, which may serve as molecular targets for osteosarcoma immune regulation. Conclusion: These findings allow us to further understand the causes of osteosarcoma development and provide a new research direction for osteosarcoma immunotherapy or targeted therapy.

A new molecular subclassification and in silico predictions for diagnosis and prognosis of papillary thyroid cancer by alternative splicing profile

Introduction: Papillary thyroid cancer (PTC) is the most common endocrine malignancy. However, different PTC variants reveal high heterogeneity at histological, cytological, molecular and clinicopathological levels, which complicates the precise diagnosis and management of PTC. Alternative splicing (AS) has been reported to be potential cancer biomarkers and therapeutic targets. Method: Here, we aim to find a more sophisticated molecular subclassification and characterization for PTC by integrating AS profiling. Based on six differentially expressed alternative splicing (DEAS) events, a new molecular subclassification was proposed to reclassify PTC into three new groups named as Cluster0, Cluster1 and Cluster2 respectively. Results: An in silico prediction was performed for accurate recognition of new groups with the average accuracy of 91.2%. Moreover, series of analyses were implemented to explore the differences of clinicopathology, molecular and immune characteristics across them. It suggests that there are remarkable differences among them, but Cluster2 was characterized by poor prognosis, higher immune heterogeneity and more sensitive to anti-PD1 therapy. The splicing correlation networks proved the complicated regulation relationships between AS events and splicing factors (SFs). An independent prognostic indicator for PTC overall survival (OS) was established. Finally, three compounds (orantinib, tyrphostin-AG-1295 and AG-370) were discovered to be the potential therapeutic agents. Discussion: Overall, the six DEAS events are not only potential biomarkers for precise diagnosis of PTC, but also the probable prognostic predictors. This research would be expected to highlight the effect of AS events on PTC characterization and also provide new insights into refining precise subclassification and improving medical therapy for PTC patients.

Necrotic reshaping of the glioma microenvironment drives disease progression

Glioblastoma is the most common primary brain tumor and has a dismal prognosis. The development of central necrosis represents a tipping point in the evolution of these tumors that foreshadows aggressive expansion, swiftly leading to mortality. The onset of necrosis, severe hypoxia and associated radial glioma expansion correlates with dramatic tumor microenvironment (TME) alterations that accelerate tumor growth. In the past, most have concluded that hypoxia and necrosis must arise due to "cancer outgrowing its blood supply" when rapid tumor growth outpaces metabolic supply, leading to diffusion-limited hypoxia. However, growing evidence suggests that microscopic intravascular thrombosis driven by the neoplastic overexpression of pro-coagulants attenuates glioma blood supply (perfusion-limited hypoxia), leading to TME restructuring that includes breakdown of the blood-brain barrier, immunosuppressive immune cell accumulation, microvascular hyperproliferation, glioma stem cell enrichment and tumor cell migration outward. Cumulatively, these adaptations result in rapid tumor expansion, resistance to therapeutic interventions and clinical progression. To inform future translational investigations, the complex interplay among environmental cues and myriad cell types that contribute to this aggressive phenotype requires better understanding. This review focuses on contributions from intratumoral thrombosis, the effects of hypoxia and necrosis, the adaptive and innate immune responses, and the current state of targeted therapeutic interventions.

Systemic characterization of alternative splicing related to prognosis, immune infiltration, and drug sensitivity analysis in ovarian cancer

Background

Alternative splicing (AS) plays an essential role in tumorigenesis and progression. This study intended to construct an innovative prognostic model based on AS events to gain more precise survival prediction and search for potential therapeutic targets in ovarian cancer.

Methods

Seven types of AS events in ovarian serous cystadenocarcinoma (OV) patients with RNA-seq were obtained using The Cancer Genome Atlas (TCGA) SpliceSeq tool and database. Cox and Kaplan-Meier curve analyses were employed to establish the prognostic models. Relying on drug sensitivity data from the CellMiner database, Genomics of Drug Sensitivity (GDS) was adopted to estimate the platinum-sensitive analysis. Furthermore, a prognostic splicing factor (SF)-AS network was constructed using Cytoscape. Finally, in order to explore the influence of the tumor microenvironment on the prognosis of OV patients, we first combined a similar network fusion and consensus clustering (SNF-CC) algorithm to identify three OV subtypes based on survival-related AS events and then utilized single-sample Gene Set Enrichment Analysis (ssGSEA) method to perform immune cell infiltration analysis.

Results

A total of 48,049 AS events and 21,841 related genes were selected from 318 OV samples, and 2,206 AS events associated with disease-free survival (DFS) were identified. Multivariate Cox and Kaplan-Meier curve analyses were then employed to establish the prognostic models. Receiver operating characteristic (ROC) analysis from 0.59 to 0.75 showed that these models were highly efficient in distinguishing patient survival. GDS was adopted with the CellMiner database to provide some insights for platinum-sensitive analysis of OV. Furthermore, a prognostic SF-AS network, which discovered a significant connection between SFs and prognostic AS genes, was constructed using Cytoscape. The combined SNF-CC algorithm revealed three distinct OV subtypes based on the prognostic AS events, and the associations between this novel molecular classification and immune cell infiltration were further explored.

Conclusions

We developed a powerful prognostic AS signature for OV and provided a deeper understanding of SF-AS network regulatory mechanisms, as well as platinum-sensitive and cancer immune microenvironments. These results revealed various candidate biomarkers and potential targets for OV treatment strategies.

Systematic Profiling of mRNA Splicing Reveals the Prognostic Predictor and Potential Therapeutic Target for Glioblastoma Multiforme

Despite many changes in alternative splicing events (ASEs) are frequently involved in various cancers, prognosis-related ASEs and drug treatment targets in glioblastoma multiforme (GBM) have not been well explored. ASEs participate in many biological behaviors in the initiation and progression of tumors, the aberrant ASE has been considered another hallmark of cancer, and the systematic study of alternative splicing may provide potential biomarkers for malignancies. In this study, we carried out a systematic analysis to characterize the ASE signatures in GBM cohort. Through comparing GBM tissues and nontumor tissues, a total of 48,191 differently expressed ASEs from 10,727 genes were obtained, and these aberrant ASEs play an important role in the oncogenic process. Then, we identified 514 ASEs independently associated with patient survival in GBM by univariate and multivariate Cox regression, including exon skip in CD3D, alternate acceptor site in POLD2, and exon skip in DCN. Those prognostic models built on ASEs of each splice type can accurately predict the outcome of GBM patients, and values for the area under curve were 0.97 in the predictive model based on alternate acceptor site. In addition, the splicing-regulatory network revealed an interesting correlation between survival-associated splicing factors and prognostic ASE corresponding genes. Moreover, these three hub splicing factors in splicing regulation network are the potential targets of some drugs. In conclusion, a systematic analysis of ASE signatures in GBM could serve as an indicator for identifying novel prognostic biomarkers and guiding clinical treatment.