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Multiomics identifies tumor-intrinsic SREBP1 driving immune exclusion in hepatocellular carcinoma.
Immune checkpoint inhibitors (ICI) have improved patient outcomes in hepatocellular carcinoma (HCC); however, most patients do not experience durable benefit. The non-T cell-inflamed tumor microenvironment, characterized by limited CD8+ T-cell infiltration, reduced dendritic cell function, and low interferon-γ-associated gene expression, is associated with a lower likelihood of response to ICI. To nominate new therapeutic targets for overcoming ICI resistance in HCC, we conducted a large-scale multiomic analysis on 900+human specimens (RNA sequencing (RNA-seq), proteomics) and 31 tumor single-cell (sc) RNA-seq samples, with tissue validation through imaging mass cytometry (IMC) and spatial lipidomics by matrix-assisted laser desorption/ionization (MALDI), with experimental investigation by in vitro CD8+ T-cell recruitment and macrophage polarization functional assays using three-dimensional (3D) co-culture models. We discovered 32 oncogenic pathways associated with immune exclusion, with sterol regulatory element binding protein 1 (SREBP1, encoded by SREBF1) as a hub regulator. scRNA-seq analysis showed that SREBP1 signaling is associated with enriched lipid biogenesis pathways in tumor cells, elevated immunosuppressive markers in macrophages, and diminished CD8+ T-cell infiltration. Integration of IMC and MALDI images revealed distinct lipid species differentially abundant in tumor regions with low versus high CD8+ T cell infiltration. Functional studies in a 3D in vitro tumor-immune co-culture system demonstrated that CRISPR-mediated SREBF1 knockout (KO) in HepG2 cells reduced monocyte recruitment, decreased expression of the protumorigenic CD206 marker in macrophages, and enhanced CD8+ T-cell migration compared with wild-type (WT) (p<0.0001). RNA-seq of SREBF1 KO versus WT tumor cells confirmed suppression of lipid biosynthesis genes.Our findings nominate an atlas of tumor-intrinsic drivers of immune exclusion, particularly SREBP1 via pro-tumorigenic macrophage (M2-like) reprogramming. These pathways may represent novel therapeutic targets to enhance antitumor immunity and deserve further study as targeted therapy candidates to enhance ICI in HCC.
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Single-cell transcriptomics analysis reveals that the tumor-infiltrating B cells determine the indolent fate of papillary thyroid carcinoma.
OBJECTIVE: Active surveillance (AS) offers a viable alternative to surgical intervention for the management of indolent papillary thyroid carcinoma (PTC), helping to minimize the incidence of unnecessary treatment. However, the broader adoption of AS is hindered by the need for more reliable diagnostic markers. This study aimed to identify the differences between indolent and progressive PTC and find new targets for biomarker development and therapeutic strategies. METHODS: We used single-cell RNA sequencing (scRNA-seq) to analyze cellular differences in 10 early-stage PTC tumors. Findings were validated in an additional 25 tumors using cell co-culture, migration assays, immunofluorescence staining, flow cytometry, and analysis of data from The Cancer Genome Atlas (TCGA). RESULTS: Tumor-infiltrating B cells (TIL-B), particularly germinal center B cells (GC-B), were more abundant in indolent PTC. These cells suppressed thyroid cell proliferation in both indolent and progressive cases, though indolent PTC had a higher capacity to recruit peripheral B cells. In indolent cases, TIL-B cells showed increased proliferation and formed clusters within tertiary lymphoid structures (TLS). PTPRC-CD22 interactions were identified as potential drivers of TIL-B cell proliferation. Markers linked to GC-B cells, such as LMO2, were highlighted as potential diagnostic and prognostic indicators for indolent PTC. CONCLUSION: This study provides insights into the cellular landscape of early-stage PTC, revealing distinct tumor and immune microenvironment features in indolent and progressive cases. These findings advance the understanding of indolent PTC biology and support the development of reliable diagnostic and prognostic biomarkers.
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Single-cell transcriptomic atlas of the human endometrium during the menstrual cycle.
In a human menstrual cycle the endometrium undergoes remodeling, shedding and regeneration, all of which are driven by substantial gene expression changes in the underlying cellular hierarchy. Despite its importance in human fertility and regenerative biology, our understanding of this unique type of tissue homeostasis remains rudimentary. We characterized the transcriptomic transformation of human endometrium at single-cell resolution across the menstrual cycle, resolving cellular heterogeneity in multiple dimensions. We profiled the behavior of seven endometrial cell types, including a previously uncharacterized ciliated cell type, during four major phases of endometrial transformation, and found characteristic signatures for each cell type and phase. We discovered that the human window of implantation opens with an abrupt and discontinuous transcriptomic activation in the epithelia, accompanied with a widespread decidualization feature in the stromal fibroblasts. Our study provides a high-resolution molecular and cellular characterization of human endometrial transformation across the menstrual cycle, providing insights into this essential physiological process.
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Integrative analysis confirms TPX2 as a novel biomarker for clinical implication, tumor microenvironment, and immunotherapy response across human solid tumors.
Targeting Protein for Xenopus Kinesin Like Protein 2 (TPX2) serves as a microtubule associated protein for the regulation of spindle assembly and tumorigenesis. We aim to investigate the prognostic and immunological role of TPX2 in pan-cancer. TCGA database, Tumor Immune Single-cell Hub (TISCH), and Human Protein Atlas (HPA) were retrieved to evaluate the expression pattern of TPX2 as well as its diagnostic and prognostic value in solid tumors. Genomic alterations of TPX2 were assessed with cBioPortal database. In vitro experiments in lung adenocarcinoma (LUAD) were performed to confirm the potential role of TPX2. Overexpression of TPX2 was found in 22 types of cancers, and was positively related with copy number variations (CNV) and negative with methylation. Up-regulated TPX2 could predict worse outcomes in the majority of cancers. Single-cell analysis revealed that TPX2 was mainly distributed in malignant cells (especially in glioma) and proliferating T cells. Genomic alteration of TPX2 was common in different types of tumors, while with prognostic value in two types of cancers. Additionally, significant correlations were found between TPX2 expression and tumor microenvironment (including stromal cells and immune cells) as well as immune related genes across cancer types. Drug sensitivity analysis revealed that TPX2 could predict response to chemotherapy and immunotherapy. Functional analyses demonstrated close relationship of TPX2 with immune function and malignant phenotypes. Finally, it was confirmed that knockdown of TPX2 could reduce proliferation and migration ability of LUAD cells. In summary, TPX2 could serve as a diagnostic and prognostic biomarker and a potential immunotherapy marker.
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Spatial transcriptomics and the kidney.
PURPOSE OF REVIEW: The application of spatial transcriptomics technologies to the interrogation of kidney tissue is a burgeoning effort. These technologies share a common purpose in mapping both the expression of individual molecules and entire transcriptomic signatures of kidney cell types and structures. Such information is often superimposed upon a histologic image. The resulting datasets are readily merged with other imaging and transcriptomic techniques to establish a spatially anchored atlas of the kidney. This review provides an overview of the various spatial transcriptomic technologies and recent studies in kidney disease. Potential applications gleaned from the interrogation of other organ systems, but relative to the kidney, are also discussed. RECENT FINDINGS: Spatial transcriptomic technologies have enabled localization of whole transcriptome mRNA expression, correlation of mRNA to histology, measurement of in situ changes in expression across time, and even subcellular localization of transcripts within the kidney. These innovations continue to aid in the development of human cellular atlases of the kidney, the reclassification of disease, and the identification of important therapeutic targets. SUMMARY: Spatial localization of gene expression will complement our current understanding of disease derived from single cell RNA sequencing, histopathology, protein immunofluorescence, and electron microscopy. Although spatial technologies continue to evolve rapidly, their importance in the localization of disease signatures is already apparent. Further efforts are required to integrate whole transcriptome and subcellular expression signatures into the individualized assessment of human kidney disease.
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Single cell atlas of Xenoturbella bocki highlights limited cell-type complexity.
Phylogenetic analyses over the last two decades have united a few small, and previously orphan clades, the nematodermatids, acoels and xenoturbelids, into the phylum Xenacoelomorpha. Some phylogenetic analyses support a sister relationship between Xenacoelomorpha and Ambulacraria (Xenambulacraria), while others suggest that Xenacoelomorpha may be sister to the rest of the Bilateria (Nephrozoa). An understanding of the cell type complements of Xenacoelomorphs is essential to assessing these alternatives as well as to our broader understanding of bilaterian cell type evolution. Employing whole organism single-cell RNA-seq in the marine xenacoelomorph worm Xenoturbella bocki, we show that Xenambulacrarian nerve nets share regulatory features and a peptidergic identity with those found in cnidarians and protostomes and more broadly share muscle and gland cell similarities with other metazoans. Taken together, these data are consistent with broad homologies of animal gland, muscle, and neurons as well as more specific affinities between Xenoturbella and acoel gut and epidermal tissues, consistent with the monophyly of Xenacoelomorpha.
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Integrative bioinformatics and immunohistochemical analysis unravel the prognostic significance and immunological implication of LIMCH1 in breast cancer: a retrospective study.
The current mortality rates for breast cancer underscore the need for better prognostic tools; moreover, LIM and calponin homology domain 1 (LIMCH1), which is a protein with dual roles in cancer, is a promising candidate for investigation. This study employed an integrative approach combining bioinformatics analysis of The Cancer Genome Atlas (TCGA) cohort and clinical immunohistochemistry (IHC) cohort data. We analysed LIMCH1 expression patterns, its associations with clinicopathological features and prognosis, and its impact on the tumour immune microenvironment (TIME). Functional annotations and single-cell RNA sequencing (scRNA-seq) data were used to explore the underlying molecular mechanisms. Our analysis revealed that high LIMCH1 expression in breast cancer patients was significantly associated with unfavourable clinical outcomes and served as an independent prognostic indicator. The functional annotations revealed pathways related to carcinogenesis and metabolic reconfiguration, thus suggesting the role of LIMCH1 in tumour progression. Additionally, LIMCH1 expression was correlated with an immunosuppressive TIME characterized by increased numbers of M2 macrophages and reduced numbers of CD8 + T cells and NK cells. Finally, we developed a nomogram incorporating LIMCH1 expression for predicting overall survival rates, thus providing a clinically applicable tool. Our research elucidates the diverse functions of LIMCH1 in the pathogenesis of breast cancer, thus highlighting its potential utility as both a prognostic indicator and a therapeutic intervention.
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Cross-scale modeling reveals a TFRC-driven immunosuppressive macrophage niche in cervical cancer.
BACKGROUND: The functional plasticity of tumor-associated macrophages (TAMs) is a critical determinant of the immunosuppressive microenvironment in cervical cancer, yet its integration into actionable prognostic frameworks remains limited. This study aimed to establish a TAM polarization-centered model and elucidate the mechanisms of underlying tumor-immune crosstalk. METHODS: Bulk transcriptomics from The Cancer Genome Atlas (TCGA) were integrated with single-cell RNA sequencing (scRNA-seq) data (GSE208653). By combining weighted gene co-expression network analysis (WGCNA) with a multi-algorithm machine learning framework, a prognostic signature was constructed and independently validated in the Gene Expression Omnibus (GEO) GSE52903 cohort. Single-cell analysis resolved the cellular origins of signature genes, prioritizing tumor-enriched genes for validation. Protein-level expression was verified via immunohistochemistry (IHC) in a paired clinical cohort (n=39). Functional validation of the core gene was performed in vitro using cervical cancer cell lines co-cultured with THP-1-derived macrophages. Polarization was assessed via reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blot (WB), enzyme-linked immunosorbent assay (ELISA), flow cytometry, and multiplex immunofluorescence (mIF). RESULTS: A robust five-gene prognostic signature (TP73, TFRC, SHC1, SCD, and PFKFB3) was developed, effectively stratifying patient survival. High risk scores correlated with a suppressed antitumor immune landscape and diminished predicted chemosensitivity to agents such as cisplatin. Single-cell analysis and IHC confirmed transferrin receptor (TFRC) as a tumor-intrinsic factor that is progressively upregulated during cervical carcinogenesis and enhances pro-M2 signaling. In vitro co-culture assays demonstrated that tumor-derived TFRC actively orchestrates an immunosuppressive M2-like macrophage niche, driving phenotypic shifts and pro-tumorigenic cytokine secretion, characterized by elevated interleukin-10 (IL-10) and reduced TNF-α. RT-qPCR analysis of 40 clinical specimens further confirmed a significant positive correlation between TFRC and the M2 marker Arg-1 at the mRNA level (r = 0.4961, P = 0.0011). CONCLUSIONS: This study establishes a cross-scale, biologically interpretable prognostic model linking macrophage plasticity to clinical outcomes. We identify TFRC as a pivotal metabolic-immune node through which tumor-intrinsic iron metabolism orchestrates an immunosuppressive niche, providing a foundation for novel therapeutic strategies in cervical cancer.
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APOA2 mediates immune therapy tolerance in hepatocellular carcinoma by inhibiting the antigen-presenting function of dendritic cells through the PPAR signaling pathway.
BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, characterized by high heterogeneity and poor prognosis. Despite advances in systemic therapies, including immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), treatment efficacy remains limited. This study investigated the mechanisms underlying resistance to combined targeted therapy and immunotherapy in HCC. METHODS: We integrated spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) data from cabozantinib-nivolumab-treated patients, using the RCTD algorithm for cell-type deconvolution. High-dimensional weighted gene co-expression network analysis (hdWGCNA) identified resistance-associated modules, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and correlation analyses to characterize APOA2/SPINK1 roles in the tumor microenvironment (TME). Spatial niches were defined via the Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA) algorithm based on cell-type co-occurrence patterns, and multiscale co-localization was analyzed using the Multiview Intercellular SpaTial modeling framework (Misty). Ligand-receptor interactions were validated by CellChat, with results confirmed using The Cancer Genome Atlas (TCGA) bulk RNA-sequencing data. RESULTS: Thirty-nine resistance-associated genes were identified, with APOA2 and SPINK1 emerging as pivotal hub genes. APOA2 mediated immune resistance by impairing dendritic cell (DC) antigen presentation through the PPAR signaling pathway, contributing to a suppressive TME. SPINK1 was associated with tumor aggressiveness, enhancing invasion, metastasis, and therapy tolerance. Lipid metabolism pathways were enriched in the non-responder (NR) group, underscoring the role of metabolic reprogramming in immune evasion and treatment resistance. Correlation analyses revealed that APOA2 expression was negatively associated with major histocompatibility complex (MHC) molecule expression. CONCLUSIONS: This study highlights the critical roles of APOA2, SPINK1, and lipid metabolism in shaping an immunosuppressive TME and driving treatment resistance in HCC. These findings provide novel insights into the mechanisms of resistance and offer a foundation for developing therapeutic strategies for better clinical outcomes.
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A comparative brain atlas in the Mexican cavefish identifies widespread changes in cellular composition and gene expression.
Understanding how naturally occurring genetic variation shapes human health and disease is critical for improving diagnosis and treatment strategies. The Mexican cavefish, Astyanax mexicanus, represents a powerful system for evolutionary medicine, enabling investigation of naturally evolved mechanisms of resilience to disease-related traits including diabetes, obesity, insomnia, and eye loss. Larval A. mexicanus, like zebrafish, are transparent, allowing whole-brain imaging, circuit mapping, and the generation of computationally derived atlases that precisely quantify neuroanatomical differences between surface and cave populations. Developing a molecular map of brain cell types provides a foundation for identifying evolved differences in neural circuits and physiology. Here, we present a single-cell atlas of the larval cavefish brain that reveals widespread divergence in the abundance and molecular signatures of neurons and glia. Our cell type map validates known neuroanatomical differences, including a reduction of the optic tectum and expansion of the pineal gland in cavefish. We uncover substantial changes in multiple glial cell classes that are linked to neural regulation of behavior, including microglia. Analysis of differential gene expression between surface and cavefish microglia revealed enhanced genes associated with synaptic pruning and clearance of neural debris, suggesting cavefish increased microglia activity to shape brain development. We also analyzed cell types that did not classify as canonical neurons or glia and identified notable divergence in transcriptomes and cell composition, including reduced meningeal fibroblasts in cavefish and substantial transcriptional changes related to phototransduction in non-visual photoreceptors within the pineal gland. Together, these findings provide a comprehensive atlas of cell type-specific gene expression differences between A. mexicanus surface and cavefish, establishing a platform for dissecting the molecular and cellular basis of evolved disease resilience in cavefish.