Integrative single-cell and multi-omics analysis of ZBTB21-mediated serine metabolism in colorectal cancer: from metabolic reprogramming to immune microenvironment modulation.

Integrative single-cell and bulk transcriptomics uncovers a lipid metabolism-related lncRNA signature alongside the ELFN1-AS1/LYPLA1 axis driving osteosarcoma progression

Osteosarcoma is the most prevalent primary malignant bone tumor in adolescents, featuring prominent intratumoral heterogeneity, early pulmonary metastasis and stagnant survival improvement for metastatic/chemoresistant patients. Altered lipid metabolism represents as a core adaptive hallmark of malignancy, whereas the prognostic implication and molecular regulatory functions of lipid metabolism-related long non-coding RNAs (LMRLs) remain poorly elucidated in osteosarcoma. Single-cell RNA-seq data from GSE152048 and bulk transcriptomic and clinical data from TARGET-OS were integrated. Lipid metabolic activity, malignant cell-state transitions, and intercellular communication were evaluated using AUCell, Monocle, and CellChat, respectively. Lipid metabolism-related genes were identified by integrating single-cell differential expression analysis with WGCNA. A prognostic lncRNA signature was constructed using Pearson correlation, Cox regression, and LASSO analyses. Immune infiltration, tumor mutational burden, immune checkpoint expression, and drug sensitivity were further assessed. scTenifoldKnk-based virtual knockout screening was performed to predict downstream target genes of ELFN1-AS1, followed by comprehensive in vitro and in vivo functional validation of the ELFN1-AS1/LYPLA1 regulatory axis. Single-cell analysis revealed marked lipid-metabolic heterogeneity across osteosarcoma cell populations, with dynamic remodeling along malignant cell-state transitions and enhanced communication between high-lipid-metabolism osteosarcoma cells and stromal or vascular compartments. By integrating single-cell and bulk transcriptomic evidence, 22 lipid metabolism-related candidate genes were identified, from which a five-LMRL signature comprising AL133410.1, AL596247.1, ELFN1-AS1, IL10RB-DT, and NECTIN3-AS1 was developed. This signature effectively stratified patients into prognostically distinct risk groups and remained an independent predictor of overall survival. Exploratory computational analyses indicated risk subgroups exhibited divergent immune landscapes, mutational profiles and predicted drug responsiveness. Virtual knockout screening prioritized LYPLA1 as the key downstream effector of ELFN1-AS1. Among the signature lncRNAs, ELFN1-AS1 was prominently upregulated in osteosarcoma tissues and cells and was associated with poor prognosis. Mechanistically, ELFN1-AS1 drives osteosarcoma progression by triggering LYPLA1-dependent lipid accumulation-associated phenotype. Pharmacological blockade of de-novo lipogenesis using orlistat (selective FASN inhibitor) attenuated ELFN1-AS1-driven oncogenic phenotypes. This study establishes an LMRL-based for osteosarcoma prognostic stratification that reflects immune, genomic and therapeutic heterogeneity. Combining virtual knockout screening and experimental validation, we characterize the oncogenic ELFN1-AS1/LYPLA1 regulatory cascade as a potential biomarker and therapeutic target for precision management of osteosarcoma.

Multimodal integration of pathomics and single-cell transcriptomics reveals CDC20 as a link between prostate cancer recurrence and benzo[a]pyrene-responsive phenotypes

Prostate cancer recurrence reflects molecular and histological heterogeneity, yet the cellular states harboring recurrence-associated signals and their potential environmental modifiers remain incompletely understood. We integrated single-cell RNA sequencing, bulk transcriptomes with recurrence annotation, quantitative histopathology, cross-cohort survival modeling, reverse network toxicology, molecular simulation, and cellular perturbation experiments. Analysis of 36,025 cells from GSE141445 identified 14,464 malignant luminal epithelial cells. Scissor identified a recurrence-associated transcriptional state enriched for adhesion, migration, angiogenesis, and proliferation programs. H&E-derived features from 304 paired TCGA-PRAD cases captured variation in this transcriptional program and supported internal recurrence risk stratification. Cross-cohort modeling prioritized CDC20, ENSA, and PTTG1. Reverse toxicology further prioritized benzo[a]pyrene (BaP), and CDC20 showed the most favorable predicted BaP docking score. In PC-3 and DU145 cells, 10 nM BaP increased CDC20 expression, whereas CDC20 silencing attenuated BaP-associated proliferation, colony formation, wound closure, and migration. These findings identify CDC20 as a recurrence-associated molecular node involved in BaP-responsive malignant biological phenotypes and provide a phenotype-anchored framework linking recurrence biology with environmental exposure-related tumor behavior.

Multi-omics and single-cell analysis link the pan-cancer TOP2A-immune exclusion paradox to a non-cell-autonomous dilution effect

TOP2A is universally upregulated in human cancers, yet its negative correlation with immune infiltration in bulk transcriptomes remains mechanistically unresolved at single-cell resolution. We integrated multi-omics data across 34 cancer types with external prognostic validation in 59 independent datasets. Single-cell deconvolution resolved cell-type-specific expression, and confounder-adjusted analyses distinguished proliferation-dependent from TOP2A -specific phenotypes. Pharmacogenomic profiling employed bidirectional Connectivity Map screening with cross-validation across four drug sensitivity databases. TOP2A was broadly upregulated at mRNA and protein levels across cancers, with high expression associated with shorter survival in most malignancies yet a protective effect in THYM and READ. Copy-number amplification, rather than somatic mutation, emerged as the predominant genomic correlate of TOP2A overexpression. TOP2A expression correlated positively with tumor mutation burden, homologous recombination deficiency, aneuploidy, and loss of heterozygosity, indicating widespread genomic instability. Single-cell analysis revealed that TOP2A expression is stringently restricted to malignant epithelial cells and proliferating immune subsets. Tumor purity and proliferation-adjusted analyses demonstrated that the bulk-level immune exclusion signature reflects stoichiometric dilution driven by malignant cell expansion rather than direct immunosuppression, whereas associations with genomic instability were largely proliferation-independent. Pharmacogenomic cross-validation revealed enhanced sensitivity of TOP2A -high tumors to topoisomerase, Aurora kinase, and microtubule inhibitors, but intrinsic resistance to MEK and EGFR inhibitors. CMap screening prioritized the HDAC inhibitor MS-275 as a candidate with pan-cancer reversal potential across 22 cancer types. This study clarifies that TOP2A functions as a pan‑cancer barometer of proliferative burden and genomic instability rather than a direct immune suppressor. Resolving the bulk-level immune paradox as a non-cell-autonomous dilution effect through single-cell deconvolution and confounder-adjusted analyses, and identifying putative therapeutic vulnerabilities, we provide a framework for deploying TOP2A as a prognostic biomarker and a hypothesis-generating therapeutic target.

Ketone body metabolism is associated with macrophage heterogeneity and a protumor phenotype in gastric cancer through single cell and bulk transcriptomic analysis

The tumor microenvironment (TME) in gastric cancer (GC) is characterized by significant heterogeneity, particularly among tumor-associated macrophages (TAMs). While metabolic reprogramming is a hallmark of cancer, the role of ketone body metabolism in shaping macrophage heterogeneity and its functional impact in GC remains largely unexplored. We analyzed the single-cell RNA-seq dataset GSE206785 (24 tumor and 24 paired normal tissues from treatment-naïve GC patients). After quality control, 110,187 cells were annotated using Seurat. Myeloid subsets were subclustered, and their functional states were assessed via GSVA, Monocle2 pseudotime trajectory analysis, and CellChat intercellular communication. The FOXM1_Mac subset was independently validated using an additional scRNA-seq cohort (GSE150290). Validation was performed using TCGA-STAD bulk RNA-seq data (n = 407). A ketone body metabolism-related prognostic signature was constructed using univariate Cox regression, LASSO Cox regression, and multivariate Cox regression, and was externally validated in the GSE66229 (ACRG) and GSE84437 cohorts. Multiplex immunofluorescence staining of 12 GC tissue samples was performed to validate the FOXM1_Mac subset and its metabolic association. Nine distinct macrophage/monocyte subsets were identified. The FOXM1_Mac showed the highest ketone body metabolism activity, with elevated expression of OXCT1, ACAT1, ACAT2, and HMGCL. Pseudotime analysis showed gradual upregulation of these enzymes along differentiation, peaking in the terminal FOXM1_Mac branch. Heatmap and spatial expression analyses revealed that inflammation/stress genes (e.g., FOS, JUN) were enriched in transitional segments, whereas ketone body metabolism genes were highly expressed in a separate terminal cluster. Cell–cell communication uncovered enhanced tumor-specific signaling (e.g., MIF-CD74/CXCR4, GAS6-AXL) targeting FOXM1_Mac and other subsets. These findings were reproducible in an independent scRNA-seq cohort (GSE150290). In TCGA-STAD, ketone body response pathways were significantly upregulated in tumors. Immune infiltration analysis indicated increased FOXM1_Mac abundance in tumor tissues. A prognostic model based on ketone body-related genes derived from LASSO and multivariate Cox regression effectively stratified patients into high- and low-risk groups with significantly different overall survival. The model achieved a 3-year AUC of 0.693 in the training cohort and demonstrated cross-platform and cross-population generalizability in two external validation cohorts (GSE66229 and GSE84437), suggesting potential clinical relevance. Immunofluorescence confirmed co-localization of FOXM1 and OXCT1 in CD11b⁺ myeloid cells, and a strong positive correlation between FOXM1 and OXCT1 expression was observed in 12 GC tissue samples. Our study identifies the heterogeneity of gastric cancer macrophages and suggests that ketone body metabolism is associated with the FOXM1_Mac, which exhibits a terminal, pro-tumor-like phenotype. The prognostic model indicates the potential clinical relevance of ketone body metabolism, providing correlative insights into GC pathogenesis and potential therapeutic targets. Experimental immunofluorescence data further support the association between FOXM1 expression and ketone body metabolism in GC CD11b⁺ myeloid cells (including macrophages).

Integrative Multi-Omics Analysis Reveals Host Regulatory and Immune Networks with Inferred Dysbiosis Relevance in Colorectal Cancer

Background: Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Increasing evidence suggests that intestinal microbial dysbiosis contributes to colorectal tumorigenesis by reshaping host molecular signaling and the tumor immune microenvironment. However, the molecular mechanisms linking microbiome-associated alterations to host regulatory networks and disease progression remain incompletely understood. Objective: This study aimed to identify the microbiome-associated molecular regulators and immune modulators involved in colorectal cancer through an integrative multi-omics systems biology approach. Methods: Publicly available transcriptomic datasets were analyzed to identify differentially expressed genes, followed by functional enrichment, protein-protein interaction network construction, hub gene prioritization, immune infiltration profiling, survival analysis, and multi-omics characterization. Results: The identified hub genes represent hypothesis-generating host candidates for further mechanistic and clinical validation. These genes occupied key positions within host regulatory networks and were significantly associated with adverse clinical outcomes and altered CD8+ T-cell infiltration, suggesting their involvement in immune remodeling within the tumor microenvironment. Multi-omics characterization demonstrated that PTEN and SMAD4 alterations were predominantly associated with genomic deletions, whereas SMAD2 dysregulation was associated with transcriptomic and gene-dosage variation. Although the overall mutational burden of the identified hub genes was not significantly associated with disease-free survival (p = 0.878), these molecular regulators showed associations with immune-cell infiltration and CRC-related pathways. Conclusions: Collectively, our findings provide a system-level framework describing the associations between dysbiosis-relevant host pathways, CRC-related regulatory networks, and immune responses.

From Environmental Lead Exposure to Colorectal Cancer: Integrated Transcriptomic and Genetic Analyses Identify HMOX1 as a Prioritized Candidate.