Deciphering the Leading-Edge Spatiotemporal Microenvironment of Hepatocellular Carcinoma for Targeted Drug Discovery Using SpaPred

Exploring the mechanism by which triphenyl phosphate promotes malignant phenotypes in bladder and kidney cancer through MMP9 based on bioinformatics analysis and experimental validation.

Background Bladder and kidney cancer burden rises globally, with environmental toxicants driving their progression. Methods We integrated global epidemiological analysis, single-cell transcriptomics, cell-cell communication analysis, epithelial subclustering, pseudotime inference, toxicological target prediction, survival modeling, cross-cohort validation, single-cell virtual knockout, spatial transcriptomic deconvolution, molecular docking/dynamics, CETSA, and in vitro assays to define a shared molecular interface linking triphenyl phosphate (TPP) to bladder and kidney cancer. Results Both malignancies exhibited age- and SDI-associated burden patterns. Single-cell profiling identified conserved epithelial, stromal, and immune ecosystems, with tumor epithelial cells occupying central positions in intercellular communication networks. Epithelial subclustering revealed a reproducible EMT-high subcluster 4 in both cancers, which localized to a terminal-like pseudotime state and was associated with poor survival. Predicted TPP targets intersected with subcluster 4 signatures and converged on extracellular matrix organization, adhesion, and leukocyte transendothelial migration pathways. Integrative survival modeling and multi-cohort validation identified MMP9 as a robust prognostic candidate associated with tumor progression. Importantly, single-cell virtual knockout of MMP9 revealed convergent remodeling of proliferative, inflammatory, hypoxia-related, and stress-response programs across bladder and renal cancer epithelial cells, highlighting conserved regulatory circuitry. Spatial transcriptomics further localized MMP9 to macrophage- and fibroblast-enriched niches in both tumor types. Structural modeling and CETSA supported an interaction between TPP and MMP9. Experimentally, TPP upregulated MMP9 at both mRNA and protein levels in T24 and 786-O cells; higher concentrations reduced viability, whereas lower concentrations enhanced migration and clonogenic growth. Conclusions TPP promotes the malignant phenotypes of bladder and kidney cancer via MMP9, which is validated by virtual knockout and in vitro experiments.

Integrative single-cell and spatial transcriptomic approaches to decipher the tumor microenvironment and therapeutic resistance in pancreatic cancer

ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) is among the most aggressive human malignancies and has an extremely poor prognosis. Its progression is largely driven by a highly complex and immunosuppressive tumor microenvironment (TME), highlighting the urgent need for a deeper understanding of its molecular mechanisms. Recent advances in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have provided unprecedented opportunities to dissect cellular heterogeneity, spatial organization, and gene expression dynamics within the TME. In this review, we summarize the major scRNA-seq and ST technologies and their unique strengths in cancer research and highlight their integrated applications in revealing PDAC heterogeneity, stromal–immune interactions, and mechanisms of therapeutic resistance. We further discuss how these approaches can inform biomarker discovery and guide the development of novel therapeutic strategies. Together, these findings suggest that integrated single-cell and spatial transcriptomics offers transformative potential to advance precision oncology and improve outcomes for patients with pancreatic cancer.

Integrative multi-omics reveals a prognostic and therapeutic landscape of synthetic lethality-associated signatures in lung adenocarcinoma

Summary Lung adenocarcinoma (LUAD) exhibits considerable heterogeneity and therapeutic resistance. Here, we integrated single-cell RNA sequencing, spatial transcriptomics, and machine learning to characterize synthetic lethality (SL)-associated transcriptional activity in LUAD. We quantified SL activity across malignant epithelial cells and stratified them into high-, dominant-, and low-SL groups. High-SL cells were enriched in advanced-stage and metastatic samples and showed reduced differentiation potential. Through multiple machine learning algorithms, we identified 13 high-SL signature genes, with IFRD2 (interferon-related developmental regulator 2) among the top contributors. Experimental validation confirmed IFRD2 upregulation in high-malignancy cell lines, and IFRD2 knockdown modulated sensitivity to the PARP inhibitor niraparib. The predicted compound prostaglandin A1 exhibited selective cytotoxicity against LUAD cells and induced DNA damage, consistent with an SL-related mechanism. Our findings establish a framework for identifying SL-associated vulnerabilities and provide a resource of candidate genes and compounds for further mechanistic investigation in LUAD precision therapy.

Deciphering the Tumor Microenvironment: An Integrated Single-Cell RNA-Seq and AI Framework for Novel Biomarker and Therapeutic Target Discovery in Melanoma

Spatial multi omic profiling maps hypoxia-driven pro-fibrotic SPP1+ macrophages underpinning immune escape and TACE resistance in hepatocellular carcinoma

To elucidate the cellular and molecular mechanisms underlying therapeutic resistance (refractoriness) following transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) by comprehensively characterizing the post-treatment tumor microenvironment (TME). We employed an integrative spatial multi-omics strategy, combining bulk and single-cell RNA sequencing, subcellular-resolution spatial transcriptomics, and spatial proteomics on tissues from TACE-treated and treatment-naïve HCC patients. Public datasets were used for prognostic and predictive validation, and key findings were confirmed with multiplex immunofluorescence and in vitro experiments. TACE induced a profoundly hypoxic TME, which drove the selective enrichment of a pro-fibrotic tumor-associated macrophage (TAM) population characterized by high SPP1 expression (SPP1 + TAMs). Spatial mapping demonstrated that these SPP1 + TAMs localize to hypoxic tumor cores, where they remodel the extracellular matrix by producing fibronectin (FN1), establish fibrotic niches, and restrict T-cell activation, thereby orchestrating an immune-excluded microenvironment. The abundance of this macrophage subtype was a robust predictor of TACE resistance. TACE-induced hypoxia promotes a macrophage-driven fibrotic program that is a key determinant of immune evasion and treatment failure in HCC. Targeting this SPP1 + TAM-mediated fibrotic niche presents a potential therapeutic strategy to overcome TACE resistance and improve clinical outcomes.

SERPING1 facilitates colorectal liver metastasis by modulating epithelial-mesenchymal transition and tumor microenvironment remodeling.

BACKGROUND Colorectal liver metastasis (CRLM) remains the primary cause of mortality in patients with colorectal cancer (CRC). Despite its clinical significance, the complex molecular networks and microenvironmental dynamics driving CRLM remain incompletely understood. Identifying robust prognostic biomarkers and elucidating their underlying mechanisms are of critical importance for advancing targeted interventions. METHODS We integrated Weighted gene co-expression network analysis (WGCNA) with differential expression profiling to identify the CRLM-associated hub genes. The clinical relevance and spatial expression of the identified target, SERPING1, were validated in human CRC and CRLM tissue cohorts. In vitro functional assays (siRNA knockdown) and transcriptomic enrichment analyses were performed to evaluate the impact of SERPING1 on malignant epithelial phenotypes. Finally, Single-cell RNA sequencing (scRNA-seq) and immune infiltration algorithms were utilized to delineate its distribution within the tumor microenvironment (TME). RESULTS SERPING1 was identified as a critical prognostic hub gene, with its elevated expression significantly correlating with poor patient survival and exhibiting a stepwise upregulation along the primary-to-metastasis axis in clinical tissues. In vitro, silencing SERPING1 attenuated the proliferative, migratory, and invasive capacities of CRC cells. This was accompanied by a molecular shift away from the epithelial-mesenchymal transition (EMT) program, supported by the enrichment of classical pro-metastatic cascades. Crucially, scRNA-seq and microenvironmental analysis revealed that in vivo, SERPING1 is predominantly enriched within cancer-associated fibroblasts (CAFs), establishing a strong correlation with stromal infiltration. CONCLUSIONS These findings suggest that SERPING1 serves as a crucial molecular nexus in CRLM, potentially facilitating disease dissemination by supporting malignant EMT phenotypes and participating in stromal TME remodeling. Consequently, SERPING1 represents a promising biomarker and a potential therapeutic target for mitigating CRLM.