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CD93 Correlates With Immune Infiltration and Impacts Patient Immunotherapy Efficacy: A Pan-Cancer Analysis.
Background: The clinical implementation of immune-checkpoint inhibitors (ICIs) targeting CTLA4, PD-1, and PD-L1 has revolutionized the treatment of cancer. However, the majority of patients do not derive clinical benefit. Further development is needed to optimize the approach of ICI therapy. Immunotherapy combined with other forms of treatment is a rising strategy for boosting antitumor responses. CD93 was found to sensitize tumors to immune-checkpoint blocker therapy after the blockade of its pathway. However, its role in immune and ICB therapy across pan-cancer has remained unexplored. Methods: In this study, we provide a comprehensive investigation of CD93 expression in a pan-cancer manner involving 33 cancer types. We evaluated the association of CD93 expression with prognosis, mismatch repair, tumor mutation burden, and microsatellite instability, immune checkpoints, tumor microenvironment, and immune using multiple online datasets, including The Cancer Genome Atlas, Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, Tumor Immune Estimation Resource database, and Tumor Immune Single-cell Hub. Results: CD93 expression varied strongly among cancer types, and increased CD93 gene expression was associated with poor prognosis as well as higher immune factors in most cancer types. Additionally, the level of CD93 was significantly correlated with MMR, TMB, MSI, immune checkpoints, TME, and immune cell infiltration. Noticeably, our results mediated a strong positive contact between CD93 and CAFs, endothelial cells, myeloid dendritic cells, hematopoietic stem cells, mononuclear/macrophage subsets, and neutrophils while a negative correlation with Th1, MDSC, NK, and T-cell follicular helper in almost all cancers. Function analysis on CD93 revealed a link between itself and promoting cancers, inflammation, and angiogenesis. Conclusion: CD93 can function as a prognostic marker in various malignant tumors and is integral in TME and immune infiltration. Inhibition of the CD93 pathway may be a novel and promising strategy for immunotherapy in human cancer. Further explorations of the mechanisms of CD93 in the immune system may help improve cancer therapy methods.
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Plac1 Remodels the Tumor Immune Evasion Microenvironment and Predicts Therapeutic Response in Head and Neck Squamous Cell Carcinoma.
Head and neck squamous cell carcinoma (HNSCC or HNSC) is the sixth most common cancer worldwide. Placenta-specific 1 (Plac1) belongs to the cancer testis antigen family and is highly expressed in malignant cells in HNSC. However, the biological function and prognostic value of plac1 in HNSC are still unclear. In the current research, we performed a comprehensive analysis of plac1 using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) bulk RNA sequencing databases as well as a single-cell sequencing dataset. We constructed a 15-gene prognostic signature through screening plac1-related immunomodulators and validated its efficiency and accuracy in immunotherapy cohorts and a pancancer database. We found that plac1 expression level is a prognostic predictor of poor overall survival in patients with HNSC. Plac1 is associated with epithelial-mesenchymal transition and tumor invasion. Plac1 has a "dual immunosuppressive function" on tumor microenvironment. On one hand, plac1-positive cells promote extracellular matrix formation and suppress immune cell infiltration. On the other hand, plac1-positive cells enhance the interaction between dendritic cells and macrophages, which further suppresses antitumor immunity. Finally, we constructed a 15-gene prognostic signature, the efficiency and accuracy of which were validated in immunotherapy cohorts and a pancancer database. In conclusion, plac1 is a promising candidate biomarker for prognosis, a potential target for immunotherapy, and a novel point for studying the immunosuppressive mechanisms of the tumor microenvironment in HNSC.
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Integrating network toxicology, machine learning, and single-cell sequencing to reveal the FASN-mediated role of phenolic endocrine disruptors in water in promoting prostate cancer.
BACKGROUND: Phenolic endocrine-disrupting chemicals (EDCs) like nonylphenol (NP) and octylphenol (OP) are widespread water pollutants. Their estrogen-like properties are suspected contributors to prostate cancer, but their precise molecular mechanisms remain unclear. METHODS: We employed a multidimensional framework to investigate this link. Potential NP/OP targets were predicted using SwissTargetPrediction, SEA, and CTD databases and cross-referenced with prostate cancer-associated genes from GeneCards and OMIM. Differential expression analysis of the GSE46602 dataset (36 tumor vs. 14 benign samples) identified candidate genes, which were refined to core genes using Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Their diagnostic power was evaluated via an Artificial Neural Network (ANN) model and validated in The Cancer Genome Atlas (TCGA) cohort. Single-cell RNA sequencing data from six prostate cancer samples (GSE137829) were analyzed to reveal cell-type-specific expression patterns. Molecular docking and molecular dynamics (MD) simulations assessed binding stability between pollutants and target proteins. RESULTS: We identified 143 overlapping genes between NP/OP targets and prostate cancer-associated genes, significantly enriched in lipid metabolism and prostate cancer pathways (adjusted P < 0.05). Dual-algorithm screening identified four core genes (ENPP2, FASN, PTGS2, and CHRM1). Among them, Fatty Acid Synthase (FASN) exhibited the best diagnostic performance in the TCGA validation cohort (AUC = 0.800), outperforming PTGS2 (0.783), ENPP2 (0.621), and CHRM1 (0.605), and was significantly overexpressed in prostate cancer tissues (|log2FC| > 1, adjusted P < 0.05). Single-cell analysis across seven annotated cell types revealed specific FASN overexpression in epithelial cells, with expression progressively upregulated along pseudotime disease trajectories. Gene Set Variation Analysis (GSVA) demonstrated significant activation of oncogenic pathways - including PI3K-AKT-mTOR, androgen response, and early estrogen response - in FASN-high epithelial cells. Molecular docking confirmed favorable binding of NP and OP to FASN (binding affinities of -6.0 and -6.1 kcal/mol, respectively), and MD simulations showed that both complexes reached stable equilibrium with RMSD fluctuations below 0.3 nm. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculations further yielded binding free energies of -19.70 kcal/mol (NP-FASN) and -17.24 kcal/mol (OP-FASN). CONCLUSION: This study computationally identifies FASN as a potential molecular hub that may link phenolic EDC exposure to prostate cancer. Our bioinformatic analyses suggest a hypothetical mechanism involving pollutant-driven disruption of lipid metabolic reprogramming via FASN, potentially activating a pro-oncogenic network, which warrants future experimental validation.
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Spatial immune atlas of breast cancer brain metastasis reveals CD163+ macrophage reprogramming associated with immune escape.
BACKGROUND: Brain metastases (BrM) remain a major cause of mortality in breast cancer (BC), yet the spatial organization and molecular circuitry of the metastatic immune microenvironment are poorly defined. METHODS: To address this gap, we integrated high-plex imaging mass cytometry (IMC) performed on human primary breast tumors (n=20 regions of interests (ROIs)) and human brain-metastasis tissues (n=40 ROIs) with publicly available datasets, including single-cell RNA sequencing (scRNA-seq) from BC (n=10) and BrM (n=12) and spatial transcriptomic (ST) data from BC (n=7) and BrM (n=1), enabling single-cell resolution of tissue architecture, functional states, and intercellular signaling. RESULTS: IMC resolved nine major cell classes and diverse epithelial, myeloid, and T-cell subtypes, and revealed a striking shift in macrophage polarization: CD163-CD11b- macrophages were markedly depleted in brain metastases, whereas CD163+ subsets persisted. Spatial analysis demonstrated the loss of the immune-permissive CN1 neighborhood in brain metastases, which is enriched in memory T cells, B cells, and dendritic cells, and the expansion of the immunosuppressive CN9 niche in brain metastases, containing CD163+ macrophages, invasion-like epithelial cells, and exhausted T cells. ScRNA-seq integration corroborated these findings by refining the annotation of major immune and stromal lineages and confirming CD163 expression patterns across macrophage subsets. ST deconvolution further reproduced these CN1-like and CN9-like domains in situ, validating their anatomical organization across BC and BrM. Ligand-receptor inference highlighted specific inhibitory pathways-including programmed cell death protein 1/programmed death-ligand 1, growth arrest-specific 6-Tyro3, Axl, and Mer receptor tyrosine kinase family, nectin cell adhesion molecule 2 (NECTIN2)-T-cell immunoreceptor with Ig and ITIM domains, and prostaglandin E2 (PGE2)-prostaglandin E2 receptor 4-that are associated with immune evasion and metastatic growth. Functional validation in an in vivo brain metastasis model further supported the therapeutic relevance of targeting these immunoregulatory pathways. CONCLUSIONS: Together, these findings show a shift from permissive to suppressive immune niches, accompanied by pronounced macrophage reprogramming, as central features of BC adaptation to the brain. This spatially resolved framework provides mechanistic insight into the poor responsiveness of brain metastases to current immunotherapies and identifies defined inhibitory ligand-receptor axes as actionable targets for combination immunotherapy.
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ANTIPODE Provides a Global View of Cell Type Homology and Transcriptomic Divergence in the Developing Mammalian Brain.
Diverse neurons and glia are generated in conserved spatial and temporal sequences during mammalian brain development. Divergence in gene regulatory networks can alter brain composition, scaling, timing, and function. However, resolving the identity, extent, and principles of gene regulatory divergence requires cellular-resolution surveys spanning brain regions and species and improved methods for defining cell type homologies. Here, we present ANTIPODE, a deep-learning variational inference framework that simultaneously integrates single-cell datasets, identifies homologous cell types, and parcellates differential expression across cell types, modules, and covariance. Applying ANTIPODE to a census of the whole developing macaque brain and a meta-atlas of human, macaque, and mouse brain development, we find broad conservation of initial neuron classes but widespread regulatory divergence within homologous types, shaped by genomic context, cell lineage, and developmental timing. Together, ANTIPODE provides a formalized and interpretable framework for cross-species single-cell analysis and reveals principles of gene regulatory divergence in mammalian brain evolution.
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A Gold Standard-Derived Modular Barcoding Approach to Cancer Transcriptomics.
A challenge with studying cancer transcriptomes is in distilling the wealth of information down into manageable portions of information. In this resource, we develop an approach that creates and assembles cancer type-specific gene expression modules into flexible barcodes, allowing for adaptation to a wide variety of uses. Specifically, we propose that modules derived organically from high-quality gold standards such as The Cancer Genome Atlas (TCGA) can accurately capture and describe functionally related genes that are relevant to specific cancer types. We show that such modules can: (1) uncover novel gene relationships and nominate new functional memberships, (2) improve and speed up analysis of smaller or lower-resolution datasets, (3) re-create and expand known cancer subtyping schemes, (4) act as a "decoder" to bridge seemingly disparate established gene signatures, and (5) efficiently apply single-cell RNA sequencing information to other datasets. Moreover, such modules can be used in conjunction with native spreadsheet program commands to create a powerful and rapid approach to hypothesis generation and testing that is readily accessible to non-bioinformaticians. Finally, we provide tools for users to create and interpret their own modules. Overall, the flexible modular nature of the proposed barcoding provides a user-friendly approach to rapidly decoding transcriptome-wide data for research or, potentially, clinical uses.
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Comprehensive analyses of PDHA1 that serves as a predictive biomarker for immunotherapy response in cancer.
Recent studies have proposed that pyruvate dehydrogenase E1 component subunit alpha (PDHA1), a cuproptosis-key gene, is crucial to the glucose metabolism reprogram of tumor cells. However, the functional roles and regulated mechanisms of PDHA1 in multiple cancers are largely unknown. The Cancer Genome Atlas (TCGA), GEPIA2, and cBioPortal databases were utilized to elucidate the function of PDHA1 in 33 tumor types. We found that PDHA1 was aberrantly expressed in most cancer types. Lung adenocarcinoma (LUAD) patients with high PDHA1 levels were significantly correlated with poor prognosis of overall survival (OS) and first progression (FP). Kidney renal clear cell carcinoma (KIRC) patients with low PDHA1 levels displayed poor OS and disease-free survival (DFS). However, for stomach adenocarcinoma (STAD), the downregulated PDHA1 expression predicted a good prognosis in patients. Moreover, we evaluated the mutation diversity of PDHA1 in cancers and their association with prognosis. We also analyzed the protein phosphorylation and DNA methylation of PDHA1 in various tumors. The PDHA1 expression was negatively correlated with tumor-infiltrating immune cells, such as myeloid dendritic cells (DCs), B cells, and T cells in pan-cancers. Mechanically, we used single-cell sequencing to discover that the PDHA1 expression had a close link with several cancer-associated signaling pathways, such as DNA damage, cell invasion, and angiogenesis. At last, we conducted a co-expressed enrichment analysis and showed that aberrantly expressed PDHA1 participated in the regulation of mitochondrial signaling pathways, including oxidative phosphorylation, cellular respiration, and electron transfer activity. In summary, PDHA1 could be a prognostic and immune-associated biomarker in multiple cancers.
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Gene expression and immune cell heterogeneity in inbred Amur tiger.
Inbreeding leads to a reduction in genetic diversity and an elevated likelihood of expressing recessive defective genes, which adversely affect the development of the immune system and render individuals and populations more susceptible to carcinogenic factors, consequently heightening the risk of cancer. Through investigating the function and extent of immune cell interaction in peripheral blood mononuclear cells (PBMCs) of inbred individual, a comprehensive understanding can be gained regarding the impact of inbreeding on various aspects of the immune system, including diversity, self-tolerance, immune responsiveness, susceptibility to diseases, and other related areas. Currently, the wild Amur tiger population in China exhibits a moderate degree of inbreeding, with a probability exceeding 90% that it will be deemed extinct within the forthcoming century. However, the impact of inbreeding on the immune system remains ambiguous, presenting numerous challenges for the development and implementation of conservation strategies. Here, for the first time, a detailed single-cell sequencing atlas of peripheral blood samples obtained from Amur tigers is presented, delineating eight distinct cell types. Our study demonstrates that the inbred tiger exhibits a relatively lower proportion of lymphocytes and cDC2 cells, along with reduced intercellular interactions. We also observed elevated activity in several signaling pathways (e.g., TGFb, APRIL, BAG, GRN, VISFATIN) that have been linked to inflammation and cancer in other species. The WGCNA analysis analysis further suggested a candidate regulatory network in inbred tiger, with the cancer-associated gene YTHDC2 emerging as a hub gene. Together, our exploratory study offers preliminary insights into the immune heterogeneity in inbred Amur tigers and can potentially guide future studies aimed at enabling timely health interventions for this endangered species.
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Single-nucleus profiling highlights the all-brain echinoderm nervous system.
Metazoans comprise diverse tissues and cell types, each essential for the organismal survival. Most of these types are established early in embryogenesis and persist into adulthood. In indirectly developing sea urchins, however, the continuity between embryonic and adult stages is interrupted by a planktonic larval stage that undergoes complete metamorphosis. While gene regulatory networks controlling embryonic and larval lineages are well studied, the molecular and morphological identities of postmetamorphic cell types remain poorly understood. Here, we reconstructed the cell atlas of postmetamorphic Paracentrotus lividus juveniles using single-nucleus transcriptomics, revealing conservation of regulatory mechanisms. We identified signatures of eight distinct cell type groups and analyzed 29 neuronal families, including 15 unique photoreceptor types. By combining transcriptomics, spatial analysis, and ultrastructure, we identified vertebrate neuronal and opsin homologs expressed across the juvenile. These findings show that the echinoderm body plan is predominantly head-like and exhibits an "all-brain" organization.
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Spinster homolog 2 reduces malignancies of glioblastoma via PTEN/PI3K/AKT pathway.
The molecular mechanisms of glioblastoma (GBM) are unclear, and the prognosis is poor. Spinster homolog 2 (SPNS2) is reportedly involved in pathological processes such as immune response, vascular development, and cancer. However, the biological function and molecular role of SPNS2 in GBM are unclear. SPNS2 is aberrantly low expressed in glioma. Survival curves, risk scores, prognostic nomograms, and univariate and multifactorial Cox regression analyses showed that SPNS2 is an independent prognostic indicator significantly associated with glioma progression and prognosis. Cell function assays and in vivo xenograft transplantation were performed that downregulation of SPNS2 promoted GBM cell growth, migration, invasion, epithelial-mesenchymal transition (EMT), anti-apoptosis, drug resistance, and stemness, while overexpression of SPNS2 had the opposite effect. Meanwhile, the functional enrichment and signaling pathways of SPNS2 in the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and RNA sequencing were analyzed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene set enrichment analysis (GSEA). The above results were related to the inhibition of the PTEN/PI3K/AKT pathway by SPNS2. In addition, we predicted that SPNS2 is closely associated with immune infiltration in the tumor microenvironment by four immune algorithms, ESTIMATE, TIMER, CIBERSORT, and QUANTISEQ. In particular, SPNS2 was negatively correlated with the infiltration of most immune cells, immunomodulators, and chemokines. Finally, single-cell sequencing analysis also revealed that SPNS2 was remarkably correlated with macrophages, and downregulation of SPNS2 promotes the expression of M2-like macrophages. This study provides new evidence that SPNS2 inhibits malignant progression, stemness, and immune infiltration of GBM cells through PTEN/PI3K/AKT pathway. SPNS2 may become a new diagnostic indicator and potential immunotherapeutic target for glioma.