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INTRODUCTION: Gliomas, a type of brain neoplasm, are prevalent and often fatal. Molecular diagnostics have improved understanding, but treatment options are limited. This study investigates the role of INTS9 in processing small nuclear RNA (snRNA), which is crucial to generating mature messenger RNA (mRNA). We aim to employ advanced bioinformatics analyses with large-scale databases and conduct functional experiments to elucidate its potential role in glioma therapeutics. MATERIALS AND METHODS: We collected genomic, proteomic, and Whole-Exon-Sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) for bioinformatic analyses. Then, we validated INTS9 protein expression through immunohistochemistry and assessed its correlation with P53 and KI67 protein expression. Gene Set Enrichment Analysis (GSEA) was performed to identify altered signaling pathways, and functional experiments were conducted on three cell lines treated with siINTS9. Then, we also investigate the impacts of tumor heterogeneity on INTS9 expression by integrating single-cell sequencing, 12-cell state prediction, and CIBERSORT analyses. Finally, we also observed longitudinal changes in INTS9 using the Glioma Longitudinal Analysis (GLASS) dataset. RESULTS: Our findings showed increased INTS9 levels in tumor tissue compared to non-neoplastic components, correlating with high tumor grading and proliferation index. TP53 mutation was the most notable factor associated with upregulated INTS9, along with other potential contributors, such as combined chromosome 7 gain/10 loss, TERT promoter mutation, and increased Tumor Mutational Burden (TMB). In GSEA analyses, we also linked INTS9 with enhanced cell proliferation and inflammation signaling. Downregulating INTS9 impacted cellular proliferation and cell cycle regulation during the function validation. In the context of the 12 cell states, INTS9 correlated with tumor-stem and tumor-proliferative-stem cells. CIBERSORT analyses revealed increased INTS9 associated with increased macrophage M0 and M2 but depletion of monocytes. Longitudinally, we also noticed that the INTS9 expression declined during recurrence in IDH wildtype. CONCLUSION: This study assessed the role of INTS9 protein in glioma development and its potential as a therapeutic target. Results indicated elevated INTS9 levels were linked to increased proliferation capacity, higher tumor grading, and poorer prognosis, potentially resulting from TP53 mutations. This research highlights the potential of INTS9 as a promising target for glioma treatment.
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Finding the 3D structure of large, multi-subunit complexes is difficult, despite recent advances in cryo-EM technology, due to remaining challenges to expressing and purifying subunits. Computational approaches that predict protein-protein interactions, including Direct Coupling Analysis (DCA), represent an attractive alternative for dissecting interactions within protein complexes. However, they are readily applicable only to small proteins due to high computational complexity and a high number of false positives. To solve this problem, we proposed a modified DCA approach, a powerful tool to predict the most likely interfaces of protein complexes. Since our modified approach cannot provide structural and mechanistic details of interacting peptides, we combine it with Molecular Dynamics (MD) simulations. To illustrate this novel approach, we predict interacting domains and structural details of interactions of two Integrator complex subunits, INTS9 and INTS11. Our predictions of interacting residues of INTS9/INTS11 are highly consistent with crystallographic structure. We then expand our procedure to two complexes whose structures are not well-studied: 1) The heterodimer formed by the Cleavage and Polyadenylation Specificity Factor 100-kD (CPSF100) and 73-kD (CPSF73); 2) The heterotrimer formed by INTS4/INTS9/INTS11. Experimental data supports our predictions of interactions within these two complexes, demonstrating that combining DCA and MD simulations is a powerful approach to revealing structural insights of large protein complexes.