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H3K27me3 loss and METTL3-m6A converge to upregulate SOX11/SMARCA4 and drive H3K27-altered spinal cord glioma stemness and proliferation.
BACKGROUND: H3 K27-altered diffuse midline gliomas (H3-DMGs) are driven by stem-like and proliferative tumor cells resulting from global H3K27me3 loss. Here, we aimed to identify key molecular mechanisms involved in the interplay between epigenetic and epitranscriptomic regulation underlying this process. METHODS: Patient-derived spinal cord H3-DMG stem-like spheres and serum-induced differentiated cells were used to model tumor plasticity. Multi-omics approaches, including single-cell RNA sequencing, spatial transcriptomics, RNA m6A profiling, CUT&Tag, ATAC-seq, and in vitro and in vivo assays were performed to dissect epigenetic and epitranscriptomic regulation of stemness. RESULTS: Differentiation reduced stemness markers, proliferation, H3K27M expression, and global m6A levels, while increasing H3K27me3. METTL3 was significantly downregulated during differentiation and positively correlated with stemness and proliferation in patient tumors. METTL3 promoted tumor stemness and growth by stabilizing SOX11 mRNA through YTHDC2-dependent m6A recognition. In parallel, H3K27me3 loss relieved transcriptional repression at both METTL3 and SOX11 loci, leading to SOX11 overexpression. Functionally, SOX11 interacted with SMARCA4, the core ATPase of the SWI/SNF complex, to enhance chromatin accessibility and activate stemness-associated transcriptional programs marked by H3K27ac and H3K4me3 enrichment. Clinically, METTL3 and SOX11 were upregulated in H3K27M-mutant tumors, and high SOX11 expression correlated with increased proliferation, poor prognosis, and enhanced sensitivity to the SMARCA4 inhibitor BRM014. CONCLUSIONS: H3K27M-driven epigenetic dysregulation promotes SOX11 overexpression through combined H3K27me3 loss and METTL3-mediated m6A modification. SOX11 sustains tumor stemness and proliferation by recruiting SMARCA4 to remodel chromatin and serves as both a prognostic biomarker and a predictor of response to SMARCA4-targeted therapy in spinal cord H3-DMG.
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Cell death-related biomarker SLC2A1 has a significant role in prognosis prediction and immunotherapy efficacy evaluation in pan-cancer.
Introduction: SLC2A1, a member of the SLC transporter family, is involved in a variety of cell death modalities and has been found to be associated with the prognosis and immune microenvironment of a variety of tumors. However, there is a lack of systematic and comprehensive studies on the role of SLC2A1 in pan-cancer. Methods: The mRNA, promoter methylation, and protein expression levels of SLC2A1 in pan-cancer were comprehensively evaluated using GEPIA2.0, TIMER2.0, and UALCAN databases. UCSCXenaShiny based on the cancer genomic atlas pan-cancer data and GEPIA2.0 database were used to assess the prognostic significance of SLC2A1 in pan-cancer. Genetic alterations in SLC2A1 were also evaluated using cBioPortal. The relevance of SLC2A1 to immune infiltrating cells in pan-cancer was evaluated using the XCELL algorithm in combination with the TIMER2.0 database. The correlation of SLC2A1 with the efficacy of immune checkpoint blocker (ICB) therapy was evaluated using the tumor immune dysfunction and exclusion (TIDE) score. The correlation of SLC2A1 with numerous immune-related markers was also evaluated using the TISIDB database. The correlation of SLC2A1 with tumor biological function was evaluated at the single-cell level using the CancerSEA database. Finally, the biological function of SLC2A1 was comprehensively evaluated using gene set enrichment analysis (GSEA) and protein interaction networks. Results: SLC2A1 expression is aberrant in a variety of tumors and is strongly associated with the prognosis of several cancers. SLC2A1 is significantly associated with a variety of immune infiltrating cells including CD8+ T cells, myeloid-derived suppressor cells and macrophages in a variety of tumors. Meanwhile, the expression of SLC2A1 significantly correlated with multiple immune-related markers. In addition, SLC2A1 can also predict the effect of immune checkpoint blocker therapy in some tumors. In a functional analysis, SLC2A1 was significantly associated with hypoxia, epithelial-mesenchymal transition, mTORC1 signaling, and multiple metabolic pathways in pan-cancer. Conclusion: Our study systematically and comprehensively summarizes the prognostic significance and immune-related role of SLC2A1 in pan-cancer and reveals the potential mechanism of SLC2A1 in regulating the tumor microenvironment and tumor behavior, providing a new effective pan-applicable biomarker for prognostic prediction and the evaluation of immunotherapeutic strategies for tumors.
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FKBP10 may affect the malignant phenotype of oral squamous cell carcinoma cells through the ECM/WNT signaling pathway.
Oral squamous cell carcinoma (OSCC) is a common malignant tumor in the oral and maxillofacial region with a poor prognosis, and its pathophysiology has not been fully elucidated. Although FKBP10 is overexpressed in multiple malignancies, its function and regulatory mechanism in OSCC remain largely unknown. Methods: OSCC and paired adjacent normal tissue samples were collected, and public datasets including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were integrated. Bioinformatics approaches including Weighted Gene Co-Expression Network Analysis (WGCNA), limma differential expression analysis and machine learning were applied to screen candidate target genes. Single-cell and spatial transcriptome analyses were performed to delineate the main expression domain of FKBP10 and its distribution in macrophages. Cell Counting Kit-8 (CCK-8), colony formation, Transwell, wound healing and flow cytometry assays were conducted to examine the effects of FKBP10 knockdown on the biological behaviors of SCC-9 cells. Western blot and Gene Set Enrichment Analysis (GSEA) were adopted to explore the potential molecular mechanism. Result: Bioinformatics research identified FKBP10 as a significant target gene for OSCC. FKBP10 is predominantly enriched in fibroblasts and significantly upregulated in OSCC tissues. It has a strong positive correlation with M2-type macrophage infiltration and is linked to a negative outcome for patients. FKBP10 knockdown can cause cell apoptosis, stop the cell cycle at the G0/G1 phase, and prevent SCC-9 cells from proliferating, migrating, and invading. Meanwhile, knockdown of FKBP10 downregulated the protein levels of Periostin (POSTN), Integrin Subunit Beta 5 (ITGB5) and key WNT signaling molecules. Conclusion༚FKBP10 may influence the recruitment of M2-type macrophages by regulating the ECM/integrin adhesion signal and the WNT pathway, thereby changing the tumor immune milieu and encouraging the occurrence and progression of OSCC. It is projected to become a promising biomarker and target for prognostic evaluation and targeted therapy of OSCC.
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Identification of PPIA, DPP4, and ITK as Potential Targets of Pterostilbene in Abdominal Aortic Aneurysm: A Network Pharmacology and Molecular Docking Study.
BACKGROUND: Pterostilbene is a polyphenolic compound with antioxidant and anti-inflammatory properties. This study aims to explore its potential therapeutic effects on Abdominal Aortic Aneurysm (AAA). METHODS: The Gene Expression Omnibus (GEO) database was accessed to obtain single- cell sequencing data and transcriptome datasets to identify Differentially Expressed Genes (DEGs) in AAA. The DEGs were further intersected with predicted targets of pterostilbene to identify common genes, which were considered core genes for functional enrichment analysis and Gene Set Enrichment Analysis (GSEA). Molecular docking and 100 ns Molecular Dynamics (MD) simulations were then performed to evaluate binding affinity and stability. RESULTS: PPIA, DPP4, and ITK were identified as overlapping genes associated with both pterostilbene and AAA. A single-cell atlas revealed their specific expression patterns across different cell types. The three genes were also correlated with IL6/JAK/STAT3, inflammatory response, and immune-related pathways. Molecular docking showed binding affinities ranging from -5.66 to -7.11 kcal/mol, and 100 ns MD simulations revealed stable binding conformations for all three targets. DISCUSSION: The present multi-omics analysis suggests that pterostilbene may exert therapeutic effects on AAA by modulating inflammation- and immune-related pathways, providing a hypothesis-generating basis for further investigation. CONCLUSION: This hypothesis-generating study proposes that pterostilbene may exert therapeutic effects on AAA by targeting PPIA, DPP4, and ITK and modulating inflammation- and immune-related pathways. However, these computational findings require further experimental validation.
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Tracing the evolution of single-cell 3D genomes in Kras-driven cancers.
Although three-dimensional (3D) genome structures are altered in cancer, it remains unclear how these changes evolve and diversify during cancer progression. Leveraging genome-wide chromatin tracing to visualize 3D genome folding directly in tissues, we generated 3D genome cancer atlases of oncogenic Kras-driven mouse lung adenocarcinoma (LUAD) and pancreatic ductal adenocarcinoma. Here we define nonmonotonic, stage-specific alterations in 3D genome compaction, heterogeneity and compartmentalization as cancers progress from normal to preinvasive and ultimately to invasive tumors, discovering a potential structural bottleneck in early tumor progression. Remarkably, 3D genome architectures distinguish morphologic cancer states in single cells, despite considerable cell-to-cell heterogeneity. Analyses of genome compartmentalization changes not only showed that compartment-associated genes are more homogeneously regulated but also elucidated prognostic and dependency genes in LUAD, as well as an unexpected role for Rnf2 in 3D genome regulation. Our results highlight the power of single-cell 3D genome mapping to identify diagnostic, prognostic and therapeutic biomarkers in cancer.
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Construction of a prognostic model for triple-negative breast cancer based on immune-related genes, and associations between the tumor immune microenvironment and immunological therapy.
BACKGROUND: Triple-negative breast cancer (TNBC) is the subtype of breast cancer with the worst prognosis, and it is highly heterogeneous. There is growing evidence that the tumor immune microenvironment (TIME) plays a crucial role in tumor development, maintenance, and treatment responses. Notably however, the full effects of the TIME on prognosis, TIME characteristics, and immunotherapy responses in TNBC patients have not been fully elucidated. METHODS: Gene Expression Omnibus and The Cancer Genome Atlas data were used to data analysis. Single-cell sequencing and tissue microarray analysis were used to investigate gene expression. The concentrations and distributions of immune cell types were determined and analyzed using the CIBERSORT strategy. Tumor immune dysfunction and exclusion score and the IMvigor210 cohort were used to estimate the sensitivity of TNBC patients with different prognostic statuses to immune checkpoint treatment. RESULTS: Five immune-related genes associated with TNBC prognosis (IL6ST, NR2F1, CKLF, TCF7L2, and HSPA2) was identified and a prognostic evaluation model was constructed based on those genes. The respective areas under the curve of the prognostic nomogram model at 3 and 5 years were 0.791 and 0.859. The group with a lower nomogram score, with a better prognosis survival status and clinical treatment benefit rate. CONCLUSION: A prognostic model for TNBC that was closely related to the immune landscape and therapeutic responses was constructed. This model may help clinicians to make more precise and personalized treatment decisions pertaining to TNBC patients.
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Unveiling the Role of SLC6A17 in Lung Adenocarcinoma: Prognosis, Pathways, and Therapeutic Implications.
BACKGROUND: The role of solute carrier family 6 member 17 (SLC6A17) in lung adenocarcinoma (LUAD) is unclear. OBJECTIVES: To address this gap in knowledge, we employed bioinformatics analysis and experimental validation. METHODS: This research aimed to scrutinize the expression patterns of the SLC6A17 gene across a spectrum of cancers and specifically within LUAD, utilizing data extracted from The Cancer Genome Atlas (TCGA). The correlation between SLC6A17 expression and LUAD prognosis was investigated to assess its diagnostic relevance. The study delved into the possible regulatory mechanisms of SLC6A17, focusing on its links to immune cell infiltration and drug response in LUAD. The examination of SLC6A17 expression was extended to single-cell sequencing data in LUAD, alongside an evaluation of the gene's genomic alterations and clinical implications within this disease context. Validation of SLC6A17 expression levels was conducted using datasets from GSE87340 and various cell lines, employing quantitative real-time polymerase chain reaction (qRTPCR) techniques. RESULTS: SLC6A17 exhibited aberrant expression in both pan-cancer and LUAD. Increased expression of SLC6A17 in LUAD patients was significantly associated with poorer overall survival (p = 0.008), progress-free survival (p = 0.019), and disease specific survival (p = 0.030). In LUAD patients, the levels of SLC6A17 expression were found to be a significant standalone indicator of prognosis, with a p-value of 0.031. SLC6A17 exhibited associations with various pathways, including focal adhesion, ECM receptor interaction, cell cycle, linoleic acid metabolism, pathways in cancer, and more. SLC6A17 expression demonstrated correlations with immune infiltration in LUAD. SLC6A17 expression revealed a notably inverse relationship with several substances, including AR-42, T0901317, tubastatin A, SB52334, and amuvatinib, within the context of LUAD. SLC6A17 was found to be significantly positively regulated in LUAD cell lines. CONCLUSION: These findings suggest that SLC6A17 indicates the potential of a potential prognostic biomarker and immunotherapeutic target for patients with LUAD.
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Integrative analysis of adiponectin-related genes reveals immune subtypes and prognostic significance in melanoma.
AIMS: This study aimed to explore the prognostic and immune-related associations of adiponectin-related genes in melanoma. METHODS: Single nucleotide polymorphism (SNP) and transcriptomic data from the Integrative Epidemiology Unit Open Genome-Wide Association Study database (IEU openGWAS) and The Cancer Genome Atlas Skin Cutaneous Melanoma cohort (TCGA-SKCM) were integrated to identify adiponectin-related genes. Consensus clustering defined molecular subtypes. Differentially expressed genes (DEGs) were analyzed using functional enrichment, protein-protein interaction (PPI), and immune infiltration (CIBERSORT). In vitro assays assessed transcriptional changes following endogenous albumin (ALB) modulation in melanoma cells. RESULTS: Five adiponectin-associated SNPs were linked to melanoma prognosis. Four molecular subtypes with distinct survival outcomes were identified, with ALB-high Cluster 3 showing the poorest prognosis. A total of 702 DEGs were enriched in immune-related pathways, including IL-17 signaling and antigen presentation. ALB was identified as a PPI hub and positively correlated with memory B cells (R = 0.34, P = 0.012). In vitro, ALB overexpression was associated with increased mRNA levels of IL-6, TNF-α, TGF-β, IL-17A, and RORγt. CONCLUSION: Tumor-associated ALB expression is associated with adverse prognosis and immune-related transcriptional features in melanoma, suggesting its potential as a prognostic biomarker and marker of transcriptomic heterogeneity.
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Suppressing glutamine metabolism in the pancreatic cancer microenvironment can enhance the anti-tumor effect of CD8 T cells and promote the efficacy of immunotherapy.
OBJECTIVE: This study aims to investigate the relationship between tumor cell glutamine metabolism and CD8 T cells, with the goal of providing new insights to improve immunotherapy for pancreatic cancer. METHODS: Using the The Cancer Genome Atlas - Pancreatic Adenocarcinoma (TCGA-PAAD) cohort, we computed gene expression scores related to glutamine metabolism and stratified patients into high- and low-score groups. Prognosis and differences in immune cell anti-tumor activity were compared between these groups. We further utilized single-cell RNA sequencing data to quantitatively assess the expression of glutamine metabolism-related pathways in tumor cells. Based on tumor-specific glutamine metabolism gene expression, patients were again classified into high- and low-score groups. The immune remodeling effects exerted by tumor cell glutamine metabolism on CD8 T cells were subsequently investigated. To examine the impact of perturbing glutamine metabolism within the tumor microenvironment on CD8 T cell phenotype and the efficacy of PD-1 inhibitors, we conducted in vivo animal experiments. RESULTS: we analyzed the pancreatic cancer dataset in the cancer gene atlas database. We found that tumor glutamine metabolism was negatively correlated with patient prognosis and anti-tumor activity. Next, we defined two types of CD8 effector T cells in single-cell RNA sequencing data, namely, effector memory T cells (CD8-Tem) and terminally differentiated effector memory T cells (CD8-Temra). Under the pressure of high glutamine metabolism in tumor cells, the cytotoxicity of the CD8-Tem subset was reduced, and its immaturity score increased, while the exhaustion score of the CD8-Temra subset increased. Pseudotime analysis showed that CD8-Tn in the low-scoring group mainly developed into CD8-Tem subset, and its immune activation pathway was significantly upregulated. In addition, we found that the glutamine metabolism inhibitor JHU083 promoted the infiltration of CD4 and CD8 T cells and T lymphocyte differentiation, and increased the efficacy of PD-1 inhibitors. Glutamine inhibitors can inhibit the apoptosis of immune cells in the tumor microenvironment, while promoting CD8 T cells activation and cytotoxicity increase. CONCLUSION: Inhibition of glutamine metabolism within the pancreatic cancer microenvironment results in reduced apoptosis of immune cells, heightened activation and cytotoxicity of CD8 T cells, and a substantial enhancement in the therapeutic efficacy of immunotherapy.
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Construction of store-operated calcium entry-related gene signature for predicting prognosis and indicates immune microenvironment infiltration in stomach adenocarcinomas.
Gastric adenocarcinoma (STAD) is the most prevalent malignancy of the human digestive system and the fourth leading cause of cancer-related death. Calcium pools, especially Ca2+ entry (SOCE) for storage operations, play a crucial role in maintaining intracellular and extracellular calcium balance, influencing cell activity, and facilitating tumor progression. Nevertheless, the prognostic and immunological value of SOCE in STAD has not been systematically studied. The objective of this study was to develop a risk model for SOCE signature and to explore its correlation with clinical characteristics, prognosis, tumor microenvironment (TME), as well as response to immunotherapy, chemotherapy, and targeted drugs. We used the TCGA, GEO (GSE84437 and GSE159929), cBioPortal and TIMER databases to acquire mRNA expression data for STAD, along with patient clinical indicators, single-cell sequencing data, genomic variation information, and correlations of immune cell infiltration. An analysis of SOCE genes based on tumor vs. normal tissue comparisons, pan-cancer dimension, single-cell sequencing, DNA mutation, and copy number variation revealed that SOCE genes significantly impact the survival of STAD patients and are differentially involved in the immune response. SOCE co-expressed genes were identified by Pearson analysis, and subsequently protein-protein interaction (PPI) and gene function enrichment analysis indicated that coexpressed genes were associated with multicellular pathways. Based on TCGA and GSE84437 datasets, a multifactor Cox proportional hazard regression analysis was conducted to identify SOCE co-expressed genes associated with overall survival in STAD patients. Several mRNA prognostic genes, including PTPRJ, GPR146, LTBP3, FBLN1, EFEMP2, ADAMTS7 and LBH, were identified, which could be used as effective prognostic predictors for STAD patients. In both training and test datasets, receiver operating characteristic (ROC) curves were utilized to evaluate and illustrate the predictive capability of this characteristic in forecasting overall survival of STAD patients. The qPCR and human protein atlas (HPA) were employed to assess mRNA expression and protein levels. Furthermore, the ESTIMATE, TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, xCell and EPIC algorithms were utilized to perform immune score and analyze immune cell infiltration. It effectively revealed the difference in prognosis and immune cell infiltration in TME between high-risk and low-risk groups based on the risk signature associated with SOCE. Notably, significant differences in tumor immune dysfunction and rejection (TIDE) scores between the two groups, suggesting that patients in the low-risk group may exhibit a more favorable response to ICIS treatment. The GDSC database and R packages for predictive analysis were utilized to analyze responses to chemotherapy and targeted drugs in high-risk and low-risk groups. In summary, the 7-gene signature associated with SOCE serves as a significant biomarker for evaluating the TME and predicting the prognosis of STAD patients. In addition, it may provide valuable insights for developing effective immunotherapy and chemotherapy regiments for patients with STAD.