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SLC12A7 serves as a prognostic and immunotherapeutic biomarker identified by multi-omics analysis.
BACKGROUND: Solute carrier family 12 member 7 (SLC12A7) is a membrane transporter implicated in ion homeostasis. Recent studies have suggested its aberrant expression in various malignancies; however, its functional roles and clinical relevance across cancers remain poorly defined. Given the limited understanding of SLC12A7 in oncogenesis and the urgent need for novel biomarkers, particularly in hepatocellular carcinoma (HCC), we conducted a comprehensive pan-cancer analysis to elucidate its potential oncogenic roles. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), cBioPortal, TIMER 2.0, and Gene Expression Omnibus (GEO) were integrated to investigate the expression patterns, prognostic significance, genetic alterations, and immune correlations of SLC12A7. Single-cell RNA sequencing data were analyzed to examine its heterogeneity within the tumor microenvironment. Functional enrichment analyses were performed to identify associated signaling pathways. In vitro experiments were conducted to validate the effects of SLC12A7 on proliferation, migration, and invasion in HCC cell lines. RESULTS: SLC12A7 was significantly upregulated in multiple cancer types and correlated with unfavorable clinical outcomes. Single-cell analysis revealed its enrichment in malignant cell populations and its involvement in the regulation of the tumor microenvironment. SLC12A7 expression was associated with immune cell infiltration and immune checkpoint gene expression. Functional assays confirmed that SLC12A7 enhances HCC cell proliferation, migration, and invasion. CONCLUSIONS: These findings identify SLC12A7 as a potential prognostic biomarker and immunotherapeutic target across cancers. Its oncogenic role in HCC suggests clinical utility in guiding prognosis and treatment strategies.
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CD44-Mediated Poor Prognosis in Glioma Is Associated With M2-Polarization of Tumor-Associated Macrophages and Immunosuppression.
BACKGROUND: Glioma is the most common primary brain tumor with a poor prognosis. Key genes that are negatively related to prognosis may provide the therapy targets to cure glioma. To clarify the role of CD44 in glioma, we explored its function at bulk-transcriptome, spatial and single-cell transcriptome levels. METHODS: In total, expression profiles with survival data of whole-grade glioma from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), RNA-seq data with anatomic information of glioblastoma (GBM) from the Ivy Glioblastoma Atlas Project, RNA-sequencing (RNA-seq) data from recurrent GBM receiving adjuvant anti-PD-1 immunotherapy accessed through GSE121810, and single-cell RNA-seq data of GBM under accession GSE103224 were enrolled in this study. CD44-specific findings were further analyzed by R language. RESULTS: CD44 is positively correlated with WHO grade of malignancy and is negatively related to prognosis in glioma. Meanwhile, CD44 predominantly expresses in GBM mesenchymal subtype, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses reveal that CD44 positively coexpressed genes are closely related to glioma immunity. Moreover, CD44+ cells mainly distribute in perinecrotic region with high expression of immune factors. At single-cell resolution, only malignant tumor cells, tumor-associated macrophages (TAMs), and T cells express CD44 in GBM. CD44+ malignant tumor cells are in mesenchymal-1-like (MES1-like) cellular state, and CD44+ TAMs are in M2 phenotype. CD44+ T cells have high expression of both PD-1 and PD-L1. CD44 and its directly interacted inhibitory immunomodulators are upregulated in patients with nonresponder recurrent GBM treated with PD-1 blockade therapy. CONCLUSION: Our work demonstrates that CD44, a new M2 TAM biomarker, is involved in immune suppressor and promote glioma progression in glioma microenvironment. These results expand our understanding of CD44-specific clinical and immune features in glioma.
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The lysosome-related characteristics affects the prognosis and tumor microenvironment of lung adenocarcinoma.
BACKGROUND: The lysosome plays a vitally crucial role in tumor development and is a major participant in the cell death process, involving aberrant functional and structural changes. However, there are few studies on lysosome-associated genes (LAGs) in lung adenocarcinoma (LUAD). METHODS: Bulk RNA-seq of LUAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The lysosome risk signature was constructed after univariate and least absolute shrinkage and selection operator (Lasso) cox regression analysis of the TCGA training set, and its capability was validated by additional validation sets from GEO. Single cell sequencing (scRNA) was obtained from GEO to analyze the differences of lysosome risk signature at the single-cell level and the differences in the function and pathway. In vitro experiments have validated the function of CTSH in LUAD. RESULTS: The risk signature contained seven key LAGs, and patients were categorized into high- and low-risk groups based on a specific calculation formula. The LAG risk signature, which accurately predicted the prognostic status of LUAD patients, was still regarded as an independent prognostic indicator in multifactorial cox regression analysis. Subsequently, the combination of the signature and key clinical information was used to construct a column-line diagram for clinical assessment, which had a high discriminatory power. Immune infiltration analysis from bulk RNA-seq and scRNA-seq indicated that the low-risk group was immune-activated and had a better benefit in the prediction of immunotherapy. Finally, we validated its role in inhibiting tumor proliferation and metastasis in LUAD cells by knockdown of CTSH. CONCLUSION: We defined a new biomarker that provided unique insights for individualized survival prediction and immunotherapy recommendations for LUAD patients.
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Transcriptomics and Spatial Proteomics for Discovery and Validation of Missing Proteins in the Human Ovary.
Efforts to understand the complexities of human biology encompass multidimensional aspects, with proteins emerging as crucial components. However, studying the human ovary introduces unique challenges due to its complex dynamics and changes over a lifetime, varied cellular composition, and limited sample access. Here, four new RNA-seq samples of ovarian cortex spanning ages of 7 to 32 were sequenced and added to the existing data in the Human Protein Atlas (HPA) database www.proteinatlas.org, opening the doors to unique possibilities for exploration of oocyte-specific proteins. Based on transcriptomics analysis of the four new tissue samples representing both prepubertal girls and women of fertile age, we selected 20 protein candidates that lacked previous evidence at the protein level, so-called "missing proteins" (MPs). The proteins were validated using high-resolution antibody-based profiling and single-cell transcriptomics. Fourteen proteins exhibited consistent single-cell expression patterns in oocytes and granulosa cells, confirming their presence in the ovary and suggesting that these proteins play important roles in ovarian function, thus proposing that these 14 proteins should no longer be classified as MPs. This research significantly advances the understanding of MPs, unearthing fresh avenues for prospective exploration. By integrating innovative methodologies and leveraging the wealth of data in the HPA database, these insights contribute to refining our understanding of protein roles within the human ovary and opening the doors for further investigations into missing proteins and human reproduction.
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Single-cell RNA-seq reveals fate determination control of an individual fibre cell initiation in cotton (Gossypium hirsutum).
Cotton fibre is a unicellular seed trichome, and lint fibre initials per seed as a factor determines fibre yield. However, the mechanisms controlling fibre initiation from ovule epidermis are not understood well enough. Here, with single-cell RNA sequencing (scRNA-seq), a total of 14 535 cells were identified from cotton ovule outer integument of Xu142_LF line at four developmental stages (1.5, 1, 0.5 days before anthesis and the day of anthesis). Three major cell types, fibre, non-fibre epidermis and outer pigment layer were identified and then verified by RNA in situ hybridization. A comparative analysis on scRNA-seq data between Xu142 and its fibreless mutant Xu142 fl further confirmed fibre cluster definition. The developmental trajectory of fibre cell was reconstructed, and fibre cell was identified differentiated at 1 day before anthesis. Gene regulatory networks at four stages revealed the spatiotemporal pattern of core transcription factors, and MYB25-like and HOX3 were demonstrated played key roles as commanders in fibre differentiation and tip-biased diffuse growth respectively. A model for early development of a single fibre cell was proposed here, which sheds light on further deciphering mechanism of plant trichome and the improvement of cotton fibre yield.
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High expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa.
It has been reported that ACE2 is the main host cell receptor of 2019-nCoV and plays a crucial role in the entry of virus into the cell to cause the final infection. To investigate the potential route of 2019-nCov infection on the mucosa of oral cavity, bulk RNA-seq profiles from two public databases including The Cancer Genome Atlas (TCGA) and Functional Annotation of The Mammalian Genome Cap Analysis of Gene Expression (FANTOM5 CAGE) dataset were collected. RNA-seq profiling data of 13 organ types with para-carcinoma normal tissues from TCGA and 14 organ types with normal tissues from FANTOM5 CAGE were analyzed in order to explore and validate the expression of ACE2 on the mucosa of oral cavity. Further, single-cell transcriptomes from an independent data generated in-house were used to identify and confirm the ACE2-expressing cell composition and proportion in oral cavity. The results demonstrated that the ACE2 expressed on the mucosa of oral cavity. Interestingly, this receptor was highly enriched in epithelial cells of tongue. Preliminarily, those findings have explained the basic mechanism that the oral cavity is a potentially high risk for 2019-nCoV infectious susceptibility and provided a piece of evidence for the future prevention strategy in dental clinical practice as well as daily life.
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GAHIB: graph attention VAE with a hyperbolic information bottleneck for biologically structured single-cell representations.
Current single-cell RNA-sequencing (scRNA-seq) variational autoencoders (VAEs) usually emphasise local cell graph structure, hyperbolic latent geometry, or bottleneck compression separately, yet these biases are rarely evaluated together in one evidence-gated representation model. We present GAHIB (graph attention VAE with a hyperbolic information bottleneck), which combines a graph-attention encoder, a 2D information bottleneck, and a Lorentz-hyperbolic geometry loss. Because the main clustering benchmark uses Leiden-derived proxy labels rather than definitive biological ground truth, we evaluate the model in two tiers: a broad 53-dataset proxy-label benchmark for method characterisation, and curated-label and marker analyses on annotated systems for biological interpretation. Across the proxy benchmark, GAHIB shows a balanced aggregate profile across clustering, projection-quality, and latent-structure metrics, while important comparisons remain mixed: scVI is statistically close to NMI/ARI, and scDHMap remains competitive on DRE-UMAP. On curated-label systems, the biological signal remains context-dependent; muscle atlas analyses support lineage-aligned structure with marker enrichment, whereas the fine T-cell immune-subtype task favors scVI. Sensitivity, seed-stability, a bounded count-dropout pilot, and cost analyses indicate practical runtime under the tested settings; however, the dropout evidence is limited to named pilot systems, and complete manually curated provenance remains an explicit limitation. Together, the results position GAHIB as a complementary, geometrically aware, single-cell representation rather than a drop-in clustering replacement.
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Diverse infections transcriptionally reprogram the intestinal epithelium and epithelial-immune cell interactions.
The distal small intestine plays vital roles in host physiology by regulating nutrient and fluid homeostasis. Despite being impacted in Crohn's disease and a major target for a range of infections, we know relatively little about the complexity of cellular responses and cell-cell communication in the ileum during infection. Single cell and spatial transcriptomics have emerged as powerful technologies to study tissue heterogeneity in the gut, but these tools have focused on the large intestine, in part due to the accessibility of this tissue for biopsies and its importance in cancer. Here we present GutPath, an atlas of over 500,000 single cells with RNA and protein expression profiles for 91 cell states in the ileum across diverse infectious archetypes. We show that GutPath accurately captures established immune responses to infection while revealing pathogen-specific responses in enterocytes. To highlight the discovery potential of this atlas, we identify a novel enterocyte cell state present during Yersinia pseudotuberculosis infection that is spatially linked to bacterial load and tissue pathology. GutPath establishes a much-needed resource for the immunology community that will accelerate the study of the transcriptional diversity of cellular landscapes in the small intestine.
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A single-cell transcriptomic atlas of the pigtail macaque placenta in late gestation.
The placenta is a complex organ with multiple immune and non-immune cell types that promote fetal tolerance and facilitate the transfer of nutrients and oxygen. The nonhuman primate (NHP) is a key experimental model for studying human pregnancy complications, in part due to similarities in placental structure, which makes it essential to understand how single-cell populations compare across the human and NHP maternal-fetal interface. We constructed a single-cell RNA-Seq (scRNA-Seq) atlas of the placenta from the pigtail macaque ( Macaca nemestrina ) in the third trimester, comprising three different tissues at the maternal-fetal interface: the chorionic villi (placental disc), chorioamniotic membranes, and the maternal decidua. Each tissue was separately dissociated into single cells and processed through the 10X Genomics and Seurat pipeline, followed by aggregation, unsupervised clustering, and cluster annotation. Next, we determined the maternal-fetal origins of cell populations and analyzed single-cell RNA trajectory, Gene Ontology enrichment, and cell-cell communication. Single-cell populations in the pigtail macaque were strikingly similar in their identity and frequency to those found in the human placenta, including cells from trophoblast, stromal cell, immune, and macrophage lineages. An advantage of our approach was the deep sequencing of three tissues at the maternal-fetal interface, which yielded a rich diversity of common and rare single-cell populations. The third-trimester pigtail macaque single-cell atlas enables the identification of cellular subclusters analogous to those in humans and provides a powerful resource for understanding experimental perturbations on the NHP placenta.
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Integrative genomics elucidates the evolutionary, temporal, and developmental origins of a hydrocephalus risk gene.
INTRODUCTION: A prior integrative, multi-omics human genetics and functional genomics study identified maelstrom (MAEL), a gene involved in regulation of DNA transposon activity and genome structure, as a transcriptome-wide predictor of hydrocephalus (HC) in the brain cortex. However, the developmental timing, cell-type specificity, evolutionary conservation, and direct measurement of MAEL expression in human HC cortex remain unknown. OBJECTIVE: To characterize the evolutionary origin and developmental, cell-type specificity, and temporal expression patterns of MAEL in the developing human brain and to measure MAEL expression in primary human HC cortical tissue. METHODS: Ensembl was used to delineate the evolution and taxonomy of MAEL across species. Analysis of single-nucleus RNA sequencing (snRNA-seq) of 49 brain regions across pre- and post-natal timescales from the Developing Human Brain Atlas (Allen Institute) identified temporal and spatial MAEL expression patterns. We quantified MAEL expression in primary cortical brain tissue obtained during the surgical treatment of HC via snRNA-seq. RESULTS: We performed taxonomic gene-mapping to define the evolutionary origin of MAEL to assess suitability for mechanistic characterization in vitro and in vivo across species. We find that MAEL is among the top 0.01% human-specific genes and < 50% sequence homology among commonly used model organisms with highly divergent functions, necessitating mechanistic validation in human tissue. snRNA-seq of the non-disease prenatal human brain identified MAEL expression enriched in cortical excitatory neurons, which was recapitulated in primary HC brain tissue obtained during HC surgery. Finally, using snRNA-seq of primary HC brain tissue, we functionally validated reduced MAEL expression, consistent with a prior human TWAS analysis. CONCLUSIONS: Our findings extend prior genetic association data by defining the developmental and cellular context of MAEL expression in the human brain and by providing direct evidence of reduced MAEL expression in the human HC cortex. While these data support a plausible role of MAEL in HC pathobiology, further mechanistic studies are needed to prove causality.