Glioma progression is shaped by molecular heterogeneity, therapy resistance, and an immunosuppressive tumor microenvironment. Lysosomal remodeling has emerged as a hallmark of glioma adaptation; however, the regulation of individual lysosomal enzymes to malignant progression remains poorly understood. Lysosomal acid phosphatase 2 (ACP2) has been implicated in developmental and metabolic disorders, but its role in glioma has not been systematically investigated. In this study, we conducted an integrative multi-omics analysis to define the transcriptional, clinical, functional, and cellular correlates of ACP2 in glioma. Bulk RNA-seq datasets from TCGA and CGGA were used to analyze gene expressions, survival modeling, and machine-learning-based prognostic classification to evaluate the predictive contribution of ACP2 across glioma grades. Immune infiltration was quantified using TIMER2.0. Functional pathways were assessed using MetaCore, KEGG, GO, and Hallmark GSEA. Single-cell RNA-seq and single-nucleus RNA-seq analyses provided cell-type and subtype-specific validation. Protein-protein interactions were examined using STRING and GeneMANIA. Further pharmacogenomic associations were examined using GDSC/CTRP, and molecular docking was performed to simulate the drug ability of ACP2. Findings of this study indicated that ACP2 was significantly overexpressed in glioma relative to normal tissues and demonstrated the strongest prognostic impact among ACP family members. Elevated ACP2 expression correlated with reduced overall survival across multiple independent cohorts and was associated with increased infiltration of macrophages, neutrophils, and dendritic cells. Enrichment analyses revealed consistent activation of PI3K/AKT, KRAS, E2F and extracellular matrix remodeling pathways. MetaCore identified APP processing and cytoskeletal remodeling as top ACP2-associated modules. Single-cell and single-nucleus analyses localized ACP2 expression mainly to malignant glioma and myeloid populations, with higher expression in recurrent and advanced malignant states. This multi-omics framework identified ACP2 as a lysosomal regulator of glioma aggressiveness and immune remodeling. ACP2 functions as a robust biomarker of malignancy and may represent a candidate target for therapeutic exploration in glioma.

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide. Although the transcription-export (TREX) complex plays a central role in RNA maturation and nuclear export, the clinical and biological relevance of individual THO Complex Subunit (including THOC1, THOC2, THOC3, THOC5, THOC6, and THOC7) in LUAD is not well defined. We performed integrative analyses combining bulk transcriptomics from TCGA/GTEx and independent GEO cohorts, survival modeling, DNA methylation profiling, protein-level annotation from public resources, protein-protein interaction network analysis, immune infiltration estimation (TIMER), and single-cell RNA sequencing (scRNA-seq) to evaluate the relevance of THOC3 and THOC7 in LUAD. Across TCGA and external GEO validation datasets, THOC3 and THOC7 were consistently upregulated in LUAD and associated with poorer overall and disease-free survival, whereas other THO complex members showed weaker or inconsistent associations. Given these comparatively consistent and reproducible signals, we therefore prioritized THOC3 and THOC7 for downstream multi-layer analyses. Epigenetic profiling and interaction network analyses placed both genes within conserved RNA processing and export programs linked to genome maintenance pathways. Single-cell transcriptomic analysis provided additional resolution, demonstrating predominant enrichment of THOC3 and THOC7 in malignant epithelial clusters, with THOC3 aligning with transcriptional programs associated with DNA replication and repair, and THOC7 with proliferative and checkpoint-related states. Notably, expression of both genes was also detectable in myeloid and neutrophil subsets, and THOC7 expression remained elevated in recurrent LUAD samples, indicating association with aggressive and treatment-resistant disease states. Collectively, by integrating bulk, single-cell, epigenetic, and immune profiling across multiple independent cohorts, this study identifies THOC3 and THOC7 as reproducible molecular correlates of aggressive LUAD phenotypes. These highlight dysregulated RNA export programs as potential biomarkers of poor prognosis and motivate future functional studies to assess RNA export dependencies in LUAD.

Oral squamous cell carcinoma (OSCC) ranks 16th worldwide as the most common type of malignancy in head and neck cancer globally, and addressing it has been an ongoing but difficult pursuit, as treatment resistance is commonly reported. Hence, employing multiple cell death pathways is an emerging strategy in overcoming treatment resistance in OSCC. We investigate here the effect of heteronemin, a marine sesterterpenoid isolated from sponges, for its anti-cancer potential, hypothesizing that it can induce non-apoptotic cell death pathways to overcome apoptosis-resistant cells and elucidate the underlying mechanisms involved. Our results show that heteronemin significantly kills cancer cells via the induction of the intrinsic apoptotic pathway. It also triggers ferroptosis, down-regulating glutathione peroxidase 4 (GPX4) and upregulating markers of lipid peroxidation such as 4-hydroxynonenal and malondialdehyde. We demonstrate that increasing reactive oxygen species generation plays a central role in triggering these pathways. ensuring the death of the cancer cells despite a compensation attempt via inducing autophagy and modulating Nrf2. Our study is the first to demonstrate the complex but interesting role of heteronemin in killing OSCC cells: inducing apoptosis and switching to ferroptosis as the cells attempt to survive. It also inhibits protective autophagy, leaving OSCC cells incapable of protecting themselves from imminent death. This complex mechanism adds to the existing knowledge on the mechanism of heteronemin as a strong therapeutic compound to treat OSCC cells.

Hexavalent chromium (Cr(VI)) is a well-established environmental and occupational carcinogen, but its time-dependent molecular effects remain poorly characterized. This study aims to elucidate the transcriptional responses triggered by acute versus chronic Cr(VI) exposure through an integrated analysis of two publicly available transcriptomic datasets: GSE16349 (short-term exposure, 16 hours) and GSE24025 (long-term exposure, 4 weeks). We identified 250 differentially expressed genes across both exposure models. MetaCore pathway enrichment analysis revealed shared activation of apoptosis, survival signaling, DNA damage response and repair, and cell cycle progression. Notably, short-term exposure primarily activated acute stress responses, whereas long-term exposure induced reprograms transcription toward fibrosis, EMT, and oncogenic signaling. Protein-protein interaction (PPI) network analysis identified potential key hub genes, with potential as biomarkers for Cr(VI) exposure monitoring. Our findings highlight distinct molecular trajectories in response to Cr(VI) over time, providing valuable insights into the progression from early toxic stress to chronic carcinogenic transformation. These results advance our understanding of Cr(VI)-induced carcinogenesis and suggest these potential targets for preventive and therapeutic interventions in exposed populations.

Ovarian cancer is characterized by extensive molecular heterogeneity and poor clinical outcomes, highlighting the need to identify biologically relevant therapeutic targets. NCCRP1 remains poorly characterized in ovarian cancer, and its molecular and therapeutic significance is largely unknown. In this study, we applied an integrative multiomics framework incorporating transcriptomic profiling, survival analysis, immune microenvironment characterization, pathway and network analyses, pharmacogenomic assessment, structural modeling, and single-cell RNA sequencing to investigate the role of NCCRP1 in ovarian cancer. Family-wide screening of the TCGA-OV cohort identified NCCRP1 as the only member significantly associated with overall survival. Elevated NCCRP1 expression was enriched in tumor tissues and associated with adverse clinical outcomes. Functional analyses demonstrated that NCCRP1-high tumors exhibit activation of epithelial-mesenchymal transition, cytoskeletal remodeling, adhesion signaling, and hypoxia-associated pathways, suggesting involvement in tumor plasticity and progression. Network-based analyses further positioned NCCRP1 within regulatory programs linked to structural reorganization and aggressive tumor phenotypes. Single-cell RNA sequencing confirmed that NCCRP1 expression is predominantly localized to malignant epithelial populations, supporting a tumor-intrinsic role. Pharmacogenomic analyses identified NCCRP1-associated transcriptional states linked to distinct drug sensitivity patterns, while structural modeling suggested the presence of a surface-accessible cavity capable of accommodating small molecules. Although these findings require experimental validation, they provide preliminary evidence supporting the potential druggability of NCCRP1. Our findings provide a comprehensive molecular characterization of NCCRP1 and support its prioritization as a candidate therapeutic target in ovarian cancer. This study demonstrates the utility of integrating multiomics, pharmacogenomic, structural, and single-cell approaches for therapeutic target discovery and prioritization in cancer.

Exostosin glycosyltransferase 1 (EXT1) and exostosin glycosyltransferase 2 (EXT2) catalyze heparan sulfate chain elongation and are increasingly implicated in cancer biology, but their roles in gliomas remain incompletely defined. Here, we performed an integrative multi-omics analysis to dissect the transcriptional, epigenetic, and microenvironmental landscape of EXT1 and EXT2 across gliomas. Bulk transcriptomic data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) revealed that both EXT1 and EXT2 are upregulated in high-grade gliomas and associate with adverse survival, with EXT1 showing the strongest and most consistent prognostic impact. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) indicated that EXT1-high tumors are enriched for DNA damage and replication stress programs, cell cycle progression, inflammatory response, and stromal activation pathways, whereas EXT2 expression is preferentially linked to extracellular matrix remodeling, cytoskeletal organization and angiogenesis-related signaling. Single-cell RNA sequencing and Immune deconvolution using Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) showed that EXT1 correlates with increased stromal and immune scores, and reduced cytotoxic T cell signatures, consistent with an immunosuppressive tumor microenvironment. EXT2 expression is enriched in gliomas with pronounced vascular and mesenchymal features, supporting a complementary role in invasive growth and tissue remodeling. Immunohistochemistry on a glioma tissue microarray validated the upregulation of EXT1 protein in high-grade tumors. The study findings identified EXT1 as a central glycosylation-linked regulator of replication stress tolerance and immune remodeling in gliomas, and suggest that EXT2 contributes to extracellular matrix and cytoskeletal reprogramming. The exostosin axis represents a promising source of prognostic biomarkers and potential therapeutic targets in glioma.

Pancreatic adenocarcinoma (PDAC) remains one of the most lethal malignancies, characterized by aggressive progression, pronounced stromal desmoplasia, and a limited response to targeted therapies. Although epidermal growth factor receptor (EGFR) inhibitors have shown promise in preclinical studies, their clinical efficacy has been modest, suggesting the existence of compensatory signaling networks. An integrated analytical framework was employed, combining bulk transcriptomic analyses of TCGA-PDAC and GTEx datasets, DNA methylation profiling, protein–protein interaction (PPI) network analysis, immune infiltration estimation, and single-cell RNA sequencing. Expression patterns and clinical associations of integrin αvβ3 were evaluated using TCGA, GEPIA, UALCAN, and the Human Protein Atlas. Functional validation was performed using in vitro assays in pancreatic cancer cell lines to assess the effects of DL-N2, a tetrac-conjugated nanoparticle targeting integrin αvβ3, alone or in combination with gefitinib. Integrin αvβ3 (ITGAV/ITGB3) was upregulated in PDAC tissues compared with normal pancreatic tissue and was associated with poor prognosis. Single-cell transcriptomic profiling localized αvβ3 expression to malignant ductal cells and stromal fibroblasts. Computational analyses predicted strong associations of αvβ3 with EGFR, MMP2, and MMP9, implicating it in epithelial–mesenchymal transition (EMT), extracellular matrix (ECM) remodeling, and immune regulation. In vitro, experiments showed that DL-N2 suppressed basal and EGF-induced proliferation, decreased the expression of EGFR, PCNA, and CCND1, and reduced angiogenic and invasive mediators, including VEGF-α, bFGF2, and MMP9. Notably, DL-N2 inhibited PD-L1 expression, linking αvβ3 signaling to immune evasion. In addition, both DL-N2 and gefitinib inhibited cell migration, and their combined treatment exerted an additive effect on the suppression of pancreatic cancer cell migration. Our findings establish integrin αvβ3 as a multifunctional regulator of pancreatic cancer progression, integrating growth-associated signaling, extracellular matrix regulation, and immune-associated pathways. Targeting αvβ3 with DL-N2 remodels both tumor-intrinsic and microenvironmental pathways, potentially enhancing EGFR inhibition and restoring chemosensitivity. Dual blockade of αvβ3 and EGFR represents a rational therapeutic strategy to overcome drug resistance and improve outcomes in PDAC.

Obstructive sleep apnea (OSA) is characterized by recurrent intermittent hypoxia (IH) and has been increasingly associated with lung cancer incidence and mortality. However, how IH-related biological programs relate to immune remodeling, stemness-associated phenotypes, and therapeutic resistance in lung cancer remains incompletely understood. We integrated single-cell RNA sequencing data from IH-exposed murine lung tissues (GSE301350) with bulk transcriptomic datasets from TCGA-LUAD and GSE31210 to examine hypoxia-associated cellular and transcriptional patterns. Stemness was quantified using CytoTRACE and transcriptome-based stemness scoring, and its associations with immune infiltration, immune checkpoint expression, TIDE scores, predicted drug sensitivity, and immunotherapy response were evaluated. A stemness-based prognostic model was constructed using LASSO Cox regression and validated in independent cohorts. Single-cell analysis revealed marked immune remodeling under intermittent hypoxia (IH), including expansion of effector T cells, and monocytes/macrophages, populations alongside reduced B cells and dendritic cells. In human LUAD cohorts, stemness-high tumors were associated with mitochondrial and metabolic stress-related transcriptional programs, and increased expression of immune checkpoint genes (PD-1, PD-L1, CTLA4, LAG3). Elevated stemness scores correlated with higher TIDE scores, poorer overall survival, and reduced predicted responsiveness to immunotherapy. LASSO modeling identified a six-gene stemness signature (EIF5A, MELTF, SEMA3C, CPS1, TCN1, SELENOK), that consistently stratified patients into high- and low-risk groups across TCGA and GSE31210 cohorts. Multivariate Cox regression confirmed the risk score as an independent prognostic factor. Drug sensitivity analyses further suggested that stemness-high tumors may exhibit increased susceptibility to selected kinase inhibitors (Dasatinib, A-770041) and metabolic modulators (Phenformin, Salubrinal). OSA-associated IH is linked to stemness-associated transcriptional plasticity, immune suppression, and adverse clinical outcomes in lung cancer. The identified stemness-based gene signature provides a robust prognostic biomarker and highlights potential therapeutic vulnerabilities, supporting integrative strategies that combine stemness and immune -targeted approaches with immunotherapy in OSA-associated lung cancer.

Multifactorial inherited disorders (MIDs) arise from complex interactions between polygenic risk and environmental exposures, presenting major challenges for mechanistic discovery, patient stratification, and targeted therapy development. While traditional approaches like genome-wide association studies (GWAS) and bulk omics profiling have identified broad associations, they often struggle to resolve the cellular context in which these interactions drive pathogenesis.Emergingsingle-cell technologies now offer unprecedented resolution to dissect tissue heterogeneity, define rare or transient disease-relevant cell states, and map dynamic trajectories across tissues and disease stages. This reviewprovides a comprehensive synthesis ofcurrent single-cell methodologies including transcriptomic, epigenomic, proteomic, and spatial techniques and their application to MID research. We explore how these toolsare revealingcell-type-specific regulatory circuits,contextualizingthe functional impact of inherited risk variants, andelucidatingcellular responses to environmental perturbations.We propose thatintegrating single-cell multi-omics data is critical for illuminating the mechanistic basis of complex traits and for advancing biomarker discovery. However, significant challenges remain, including technical variability, limited cohort scalability, difficulties in multi-modal data integration, and a lack of standardized analytical workflows for polygenic diseases. Overcoming these barriers will require harmonized study designs, robust computational frameworks, and the incorporation of longitudinal and environmental exposure data.Ultimately, we conclude thatsingle-cell analysis is poised to transform MID research, offering a powerful new paradigm for mechanistic insight, therapeutic innovation, and the realization of precision medicine.

Cytokines are central regulators of inflammation and immune responses within the tumor microenvironment and have been implicated in cancer progression and prognosis. However, the prognostic value of coordinated cytokine-related transcriptional programs across cancer types has not been systematically explored. Pan-cancer transcriptomic and clinical data were analyzed to construct a cytokine-related prognostic signature using least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were stratified into high-risk and low-risk groups based on the derived risk score. Prognostic performance was evaluated in training and test cohorts, and biological relevance was assessed through survival analyses and pathway-level investigations. A 16-gene cytokine-related signature was established that consistently stratified patients into distinct prognostic groups across multiple cancer types. High cytokine-related risk scores were significantly associated with unfavorable survival outcomes and were linked to enhanced cell cycle activity, epithelial-mesenchymal transition, and extracellular matrix remodeling. Integration of the risk score with clinical variables improved individualized survival prediction. Immunohistochemical analyses further confirmed increased protein expression of representative risk-associated genes, including pannexin 1 (PANX1) and FERM domain containing 8 (FRMD8), in multiple tumor tissues compared with corresponding normal tissues. The cytokine-related prognostic signature captures key inflammatory and immune-related programs underlying tumor aggressiveness and provides a robust tool for pan-cancer risk stratification with potential clinical utility.

Glioblastoma multiforme (GBM), the most aggressive primary brain tumor, is characterized by high recurrence, metabolic plasticity, and complex tumor microenvironmental interactions. The human chitinase and chitinase-like protein family includes five members (CHI3L1, CHI3L2, CHIA, CHID1, and CHIT1) that share conserved chitinase-related domains but exhibit diverse biological functions in immune regulation and tissue remodeling. While chitinase-like proteins are recognized as mesenchymal-associated markers, however, the role of CHID1 in GBM remains largely unexplored. An integrative multi-omics strategy combining TCGA-GBM and CGGA transcriptomic datasets, single-cell RNA sequencing, and enrichment analyses (GSEA, GO, KEGG, and MetaCore) were used to investigate CHID1 expression patterns and associated transcriptional programs. Pharmacogenomic correlations and molecular docking were used to explore potential drug-response associations. CHID1 showed higher expression in GBM compared to the normal brain and was associated with poor overall survival. A single-cell analysis showed tumor-associated expression patterns of CHID1 across malignant samples. Pathway enrichment analyses identified transcriptional programs related to oxidative phosphorylation, redox-related processes, DNA repair, and cell cycle pathways. Collectively, this study provides a comprehensive multi-cohort and multi-modal characterization of CHID1 expression in GBM, integrating bulk transcriptomics, single-cell RNA sequencing, and tissue-level validation. The findings establish CHID1 as a GBM-associated transcriptional marker linked to metabolic and redox-related programs and provide a systematic resource for future investigations into chitinase family-related biology in GBM.

Lung cancer remains the leading cause of cancer mortality. The AP-1 adaptor complex, including AP1AR, AP1S1, AP1S2, AP1S3, AP1M1, AP1M2, AP1B1, and AP1G1, functions as a conserved hub of vesicular trafficking, selecting cargo and coordinating clathrin-mediated transport. By shaping receptor recycling, membrane composition, and signal duration, AP-1 influences core cancer phenotypes such as proliferation, migration, and therapy response. However, the family-level role of AP-1 adaptors in lung cancer is incompletely defined. We systematically profiled all eight AP-1 adaptor genes using multi-omics datasets, survival resources, pharmacogenomic panels, Human Protein Atlas data, pathway enrichment, and single-cell RNA sequencing with cell-cell communication modeling. AP1AR was consistently upregulated in lung adenocarcinoma and independently associated with poorer overall survival. It was linked to cell-cycle progression, DNA replication checkpoints, hypoxia, and epithelial-to-mesenchymal transition (EMT). At single cell resolution, AP1AR also regulate malignant epithelial and fibroblast cell types. Pseudotime analyses revealed progressive activation along proliferative and EMT axes, and CellChat modeling indicated enhanced stromal and epithelial signaling. AP1S3 and AP1S1 showed complementary roles, associated with oncogenic/inflammatory signaling and immune-metabolic programs, respectively. These findings identify AP1AR as a clinically relevant biomarker and highlight AP-1 adaptor biology as an underexplored contributor to lung adenocarcinoma progression and therapeutic stratification.

Galectin-3 (LGALS3), a β-galactoside-binding lectin, plays a pivotal role in regulating physiological and pathological processes in hepatocellular carcinoma (HCC). This study integrates multi-omics analytics and structure-based drug screening to evaluate Galectin-3 inhibitors for HCC treatment. Transcriptomic data and immunohistochemistry confirmed elevated Galectin-3 expression in HCC tissues, with Kaplan-Meier analysis showing its association with poor survival. Single-cell RNA sequencing revealed Galectin-3’s role in immune regulation, cancer stemness, and epithelial-mesenchymal transition. Structure-based screening identified 68 compounds with significant interactions with key Galectin-3 binding sites. Molecular dynamics simulations confirmed stable complex formation between Galectin-3 and inhibitors GB1107 and Pimasertib. In vitro assays demonstrated both compounds significantly inhibited HCC cell viability, colony formation, and migration dose-dependently. GB1107 exhibited stronger cytotoxicity at lower doses, while Pimasertib induced greater apoptosis at higher concentrations. Both compounds effectively downregulated stemness and epithelial-mesenchymal transition markers. These findings suggest Galectin-3 inhibition by GB1107 and Pimasertib disrupts oncogenic pathways, reducing tumor growth and metastatic potential, and offering promising therapeutic strategies for HCC management.

Purpose COVID-19 infection has been associated with cardiovascular complications, including new-onset atrial fibrillation/flutter (NOAF). However, the potential protective effect of COVID-19 vaccination against long-term NOAF risk following COVID-19 infection remains unclear. Methods This retrospective cohort study used the TriNetX Research Network to identify adults diagnosed with COVID-19. Patients were divided into a vaccine group and control group (unvaccinated). After propensity score matching (238,750 patients per group), we assessed the primary outcome of 24-month NOAF incidence, with secondary outcomes at 1, 6 and 12 months. Subgroup analyses examined effects across patient characteristics and comorbidities. Sensitivity analysis was performed by excluding patients with severe COVID-19 illness. Results The 24-month NOAF incidence was significantly lower in the vaccine group compared to the control group (1.91% vs 2.18%; HR: 0.82, 95% CI: 0.78-0.85). This protective effect was also observed at 1 month (HR: 0.73, p < 0.001), 6 months (HR: 0.71, p < 0.001), and 12 months (HR: 0.77, p < 0.001). Sensitivity analysis confirmed these findings (HR: 0.79 at 24 months). Subgroup analyses demonstrated that COVID-19 vaccination provided significant protection against NOAF across all examined subgroups, with younger patients (18-60 years) showing greater risk reduction compared to older individuals. Conclusion COVID-19 vaccination was associated with a significantly reduced 24-month risk of NOAF after COVID-19 infection. These findings suggest vaccination may mitigate long-term cardiovascular sequelae of COVID-19. Future research should elucidate underlying protective mechanisms and optimize vaccination strategies for cardiovascular protection, particularly in high-risk populations.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer with a poor prognosis, thus emphasizing the need for early and accurate diagnostic tools. In this study, we propose a comparative study approach to understand how machine learning (ML) modeling using urinary biomarkers combined with demographic data can predict PDAC. The study also utilized a single-cell RNA sequencing (scRNA-seq) analysis to assess and understand gene expressions of included biomarkers. With inclusion of available biomarkers and incorporation of demographic information, we employed different approaches for preprocessing techniques, normalization approaches, ML techniques, and deep learning (DL) approaches to provide a comprehensive prediction model. The scRNA-seq approach also highlighted the significance of the urinary biomarkers from the pancreatic single-cell sample. Based on this analysis, the marker was identified as one of the top three most highly expressed genes in PDAC tissues. The predictive modeling approach was conducted for both binary and multiclass classification using both ML and DL approaches. The comparative analysis using all included parameter combinations produced modeling settings, and among these parameters, the DL modeling approach using binary classification outperformed the other approaches by achieving 91% accuracy. This framework provided insights that highlighted the critical role of demographic data and potential approaches to include such features in the model without impacting the predictive accuracy. Future work will focus on examining the framework using different datasets, integrating additional omics data, and exploring advanced DL architectures to further improve predictive performances.

Marburg virus (MARV) disease (MVD) is an uncommon yet serious viral hemorrhagic fever that impacts humans and non-human primates. In humans, infection by the MARV is marked by rapid onset, high transmissibility, and elevated mortality rates, presenting considerable obstacles to the development of vaccines and treatments. Bats, particularly Rousettus aegyptiacus, are suspected to be natural hosts of MARV. Previous research reported asymptomatic MARV infection in bats, in stark contrast to the severe responses observed in humans and other primates. Recent MARV outbreaks highlight significant public health concerns, underscoring the need for gene expression studies during MARV progression. To investigate this, we employed two models from the Gene Expression Omnibus, including kidney cells from Rousettus aegyptiacus and primary proximal tubular cells from Homo sapiens. These models were chosen to identify changes in gene expression profiles and to examine co-regulated genes and pathways involved in MARV disease progression. Our analysis of differentially expressed genes (DEGs) revealed that these genes are mainly associated with pathways related to the complement system, innate immune response via interferons (IFNs), Wnt/β-catenin signaling, and Hedgehog signaling, which played crucial roles in MARV infection across both models. Furthermore, we also identified several potential compounds that may be useful against MARV infection. These findings offer valuable insights into the mechanisms underlying MARV's pathophysiology and suggest potential strategies for preventing transmission, managing post-infection effects, and developing future vaccines.

Lung adenocarcinoma (LUAD) remains the most prevalent and lethal subtype of lung cancer, largely due to late diagnosis and therapeutic resistance. In this study, we conducted a comprehensive multi-omics analysis to characterize the pleckstrin homology domain-containing (PLEKHA) family gene in LUAD. Among the eight members, PLEKHA6 was uniquely overexpressed in LUAD tissues and significantly associated with poor prognosis. Integrated bulk RNA-Seq, single-cell RNA-Seq, DNA methylation, and pharmacogenomic analyses identified PLEKHA6 as a key modulator of oncogenic processes, including Wnt/β-catenin signaling, cadherin-mediated adhesion, and cytoskeletal remodeling. Functional assays in A549 LUAD cells revealed that PLEKHA6 knockdown suppressed β-catenin and VE-cadherin expression, leading to impaired proliferation, migration, and colony formation, along with enhanced apoptosis and cell cycle arrest. Single-cell RNA sequencing demonstrated a correlation between PLEKHA6 expression and tumor-associated macrophage (TAM) infiltration, implicating PLEKHA6 in immune remodeling within the tumor microenvironment (TME). Drug sensitivity analysis and molecular docking further identified potential therapeutic drugs targeting PLEKHA6-expressing LUAD cells. Collectively, our findings establish PLEKHA6 as a novel oncogenic driver and immune modulator in LUAD, supporting its potential as both a prognostic biomarker and a therapeutic target for precision oncology.

Lung adenocarcinoma (LUAD) remains to be one of the most prevalent and highly invasive forms of cancer. Mitochondrial outer membrane protein-2 or Metaxin-2 (MTX2), a key regulator of mitochondrial function, has been linked to cellular bioenergetics and stress response mechanisms. However, its roles in the progression and prognosis of LUAD remain largely unexplored. This study, employed a multi-omics approach, integrating transcriptomic and clinical patient data from public databases, to evaluate the expression and prognostic relevance of MTX2 in LUAD. Single-cell RNA sequencing was utilized to further explore MTX2's role in immune infiltration and interactions within the tumor microenvironment. Additionally, we validated these findings through a series of molecular biology and functional assays. Our results demonstrated that MTX2 expression was higher in LUAD tissues compared to normal lung tissues. Elevated MTX2 levels were significantly associated with poorer overall survival in LUAD patients. Functional analyses revealed that MTX2 regulates mitochondrial bioenergetics and facilitates tumor cell proliferation. Additionally, MTX2 expression was associated with increased immune cell infiltration. A pathway analysis identified cell metabolic and tumor growth pathways regulated by MTX2, supporting its role in tumor progression. Our research identifies MTX2 as a promising prognostic biomarker and therapeutic target for LUAD. Increased expression of MTX2 promotes tumor growth by altering metabolic pathways and modulating the immune response, underscoring its potential as a new target for LUAD treatment.

Glioblastoma multiforme (GBM) is characterized by rapid progression, therapeutic resistance, and a profoundly immunosuppressive tumor microenvironment. Emerging evidence suggests that endoplasmic reticulum (ER)-associated macromolecules play critical roles in tumor adaptation. In this study, we performed a multi-omics investigation of orosomucoid-like protein 2 (ORMDL2), a conserved ER membrane protein involved in sphingolipid biosynthesis and ER stress regulation, and uncovered its regulatory functions in GBM progression. Transcriptomic analyses across The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA) revealed elevated ORMDL2 expression in GBM tissues which causes poor prognosis. The MetaCore pathway and Gene Set Enrichment Analysis (GSEA) identified ORMDL2's involvement in antigen presentation via a major histocompatibility complex I (MHC class I), unfolded protein response (UPR), and mitochondrial apoptotic signaling. Single-cell RNA-sequencing data and the Human Protein Atlas showed ORMDL2 enrichment in tumor stromal cells. Pharmacogenomic correlation via the Genomics in Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) database suggested that ORMDL2 expression was associated with resistance to DNA damage response inhibitors such as etoposide, doxorubicin, talazoparib, and might interact with sphingolipid-targeting compounds. Collectively, our findings establish ORMDL2 as a multi-functional macromolecular regulator of immune suppression and therapeutic resistance in GBM, providing new mechanistic insights and potential targets for translational medicines.

BACKGROUND:Pancreatic ductal adenocarcinoma (PDAC) is the most common and aggressive type of pancreatic cancer, with a five-year survival rate below 8%. Its high mortality is largely due to late diagnosis, metastatic potential, and resistance to therapy. Epithelial-mesenchymal transition (EMT) plays a key role in metastasis, enabling cancer cells to become mobile. Partial EMT, where cells maintain both epithelial and mesenchymal traits, is more frequent in tumors than complete EMT and contributes to cancer progression. The long non-coding RNA MIR31 host gene (MIR31HG) has recently emerged as a critical factor in PDAC oncogenesis. This study aimed to investigate MIR31HG's role in partial EMT and its association with the basal-like PDAC subtype. METHODS:We analyzed the relationship between MIR31HG expression, partial EMT, and the basal-like subtype of PDAC by integrating data from public databases. We reanalyzed public data from PDAC patient-derived organoids to assess MIR31HG expression and gene signatures under hypoxic and normoxic conditions. RNA sequencing and bioinformatics analyses, including gene set enrichment analysis (GSEA), were used to investigate differentially expressed genes and pathway enrichments. EMT, partial EMT, and hypoxia scores were calculated based on the expression levels of specific gene sets. RESULTS:We observed that MIR31HG overexpression strongly correlates with higher partial EMT scores and the stabilization of the epithelial phenotype in PDAC. MIR31HG is highly expressed in the basal-like subtype of PDAC, which exhibits partial EMT traits. Hypoxia, a hallmark of basal-like PDAC, was shown to significantly induce MIR31HG expression, thereby promoting the basal-like phenotype and partial EMT. In patient-derived organoids, hypoxic conditions increased MIR31HG expression and enhanced basal-like and partial EMT gene signatures, while normoxia reduced these expressions. These findings suggest that hypoxia-induced MIR31HG expression plays a crucial role in driving the aggressive basal-like subtype of PDAC. CONCLUSIONS:Our results indicate that MIR31HG is crucial in regulating PDAC progression, particularly in the aggressive basal-like subtype associated with hypoxia and partial EMT. Targeting the MIR31HG-mediated network may offer a novel therapeutic approach to combat hypoxia-driven PDAC.