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An ATXN2-linked stress granule transcript program marks proliferative and CD8-low states in colorectal cancer.
Immune checkpoint blockade benefits only a minority of colorectal cancer patients, and many tumors show immune-cold phenotypes at the transcript level, especially in microsatellite-stable (MSS) disease. Stress granules are conserved ribonucleoprotein assemblies that form under metabolic and proteotoxic stress and include the RNA-binding protein ataxin-2 (ATXN2). However, it remains unclear whether stress-granule-related tumor programs consistently track immune-cold colorectal cancer (CRC) states across independent cohorts. Here, we tested whether a compact stress-granule-related transcript program anchored on ATXN2 (CS_ATXN2) is associated with reduced CD8 cytotoxic transcript signal in bulk CRC beyond proliferation, hypoxia, and tumor purity. We analyzed three independent bulk CRC cohorts (total n = 1220) using multivariable models adjusting for proliferation, hypoxia, and tumor purity, pooled by random-effects meta-analysis. Program-level robustness and relative specificity were assessed using a P_BODY control, leave-one-gene-out testing, and expression-matched random gene sets. Four orthogonal immune deconvolution frameworks were applied, and patient-level pseudobulk analysis was performed in a CRC single-cell atlas. CS_ATXN2 was consistently associated with lower CD8 cytotoxic transcript signal across all three cohorts (pooled standardized beta = -0.159, 95% CI -0.215 to -0.103, p < 0.001, I² = 21.2%), surviving stromal adjustment and not reproduced by a P_BODY control. Immune deconvolution analyses provided convergent but not uniform support for reduced inferred lymphocyte signals in CS_ATXN2-high tumors. Patient-level single-cell analysis identified CXCL8 and LIF as candidate extracellular transcripts elevated in CS_ATXN2-high malignant cells (FDR < 0.05). In summary, CS_ATXN2 is a reproducible transcriptomic marker of proliferative and CD8-low CRC states.
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A TP63 mutation identified in a Han Chinese family with ectodermal dysplasia.
OBJECTIVE: The purpose of this study was to identify a pathogenic mutation located in TP63 in a nuclear Han Chinese family. DESIGN: Whole-exome sequencing and Sanger sequencing were performed to identify candidate variants. The AlphaFold and PyMOL predicted the three-dimensional structure of the protein. Single-cell RNA-sequencing data and spatiotemporal transcriptomic atlas were used to generate the dissection of candidate gene expression at single-cell resolution. Significant genes (Pearson's coefficient ≥0.8 and P < 0.05) were identified for Gene Ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathways analysis. RESULTS: A heterozygous missense variant at TP63 exon 8 (c.1010 G>A:p.Arg337Gln) was identified in the proband. This variant was predicted deleterious and likely to impair the local stability of the protein. In addition, single-cell RNA-sequencing indicated that TP63 was highly expressed in skin tissues. Furthermore, spatial transcriptome data of mice embryos showed TP63 was mainly enriched in the mucosal epithelium, thymus, epidermis, mesenchyme, and surface ectoderm. GO and KEGG pathway annotation analysis revealed that TP63 played a positive role in the process of ectoderm via the TGF-beta signaling pathway. CONCLUSIONS: The missense variant of TP63 (c.1010 G>A:p.Arg337Gln) was associated with ectodermal dysplasia.
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Disulfidptosis-related gene SLC7A11 predicts prognosis and indicates tumor immune infiltration in lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) is closely associated with factors such as smoking and metabolic disorders. A unique form of cell death known as disulfidptosis, which is regulated by genes like SLC7A11, has emerged as an area of interest; however, its effect on the immune microenvironment in the context of cancer remains largely unexplored. The aim of this study was to analyze the immunoregulatory role of disulfidptosis-related genes in LUAD to unveil and underscore their significance in the process of immune regulation. METHODS: This study examined the role of disulfidptosis-related genes in LUAD using data from The Cancer Genome Atlas (TCGA) with a particular focus on immune infiltration and the function of SLC7A11. The research employed a clustering analysis, survival analysis, and immune function assessment, integrating both bulk and single-cell RNA sequencing data, to gain a comprehensive understanding of disulfidptosis in LUAD. RESULTS: The analysis revealed three distinct LUAD clusters, each characterized by different survival rates and patterns of immune cell infiltration. Notably, high expression levels of SLC7A11 were associated with a poor prognosis and mechanisms of immune evasion. High SLC7A11 expression is correlated with a poor prognosis and immune evasion in LUAD. These results underscore the significant role of SLC7A11 in the progression of disulfidptosis and LUAD. CONCLUSIONS: This study sheds new light on the role of disulfidptosis in LUAD, particularly highlighting the immunoregulatory effects of SLC7A11. The findings suggest that targeting SLC7A11 could lead to the development of novel therapeutic strategies aimed at enhancing the response to immunotherapy in LUAD patients. To substantiate these results, further experimental validation is needed.
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The single-cell landscape of the human vein after arteriovenous fistula creation and implications for maturation failure.
INTRODUCTION: The biological mechanisms underlying arteriovenous fistula (AVF) maturation in patients receiving hemodialysis remain poorly understood despite decades of research. METHODS: To address this gap, we first investigated the cellular changes in the venous wall after fistula creation in histological biopsies of longitudinal veins and AVF samples (23 patients). Using single-cell RNA sequencing of 70,281 cells from independent pre-access veins, early resections, mature, and failed AVFs (20 patients), we then created a complementary transcriptomic atlas of the human vein before and after anastomosis. RESULTS: AVFs had increased wall area and cell number but reduced cell density in histological sections, suggesting that postoperative wall thickening occurs predominantly through extracellular matrix (ECM) deposition. The early remodeling of the AVF was characterized by a loss of smooth muscle cells, increased monocyte infiltration, and the reprograming of myofibroblasts and fibroblasts toward reparative phenotypes. In contrast, later stages of remodeling were dominated by ECM-producing myofibroblasts and fibroblasts, occurring in the context of low cell proliferation. Failed AVFs displayed persistent inflammation and exaggerated healing responses as defining features. Specifically, these AVFs contained abundant proinflammatory and adhesive macrophages with upregulation of the Myddosome signaling complex, proinflammatory vasa vasorum endothelial cells, and hyperactivated fibroblasts and myofibroblasts. Macrophage-derived osteopontin emerged as a key paracrine signal driving vascular cell activation in failed AVFs. Additional signals derived from fibroblasts, myofibroblasts, and endothelial cells, including chemokines, semaphorins, fibroblast growth factors, angiopoietin-like proteins, periostin, and transforming growth factor-β, were also enriched within the inflammatory microenvironment sustaining AVF failure. CONCLUSIONS: Our findings uncover previously unrecognized cellular and molecular patterns in human veins following AVF creation, providing novel insights and potential therapeutic targets to improve AVF maturation outcomes.
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Ubiquitin-conjugating enzyme E2S serves as a prognostic marker for skin cutaneous melanoma.
BACKGROUND: This study investigates the expression of ubiquitin-conjugating enzyme E2S (UBE2S) as a significant prognostic marker for skin cutaneous melanoma (SKCM) and its association with the tumor microenvironment (TME). The research aimed to advance precision oncology by identifying novel therapeutic targets for SKCM. METHODS: UBE2S expression in normal skin and SKCM tissues was analyzed using Sangerbox, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and DiSignAtlas databases. Its relationship with SKCM prognosis was examined through GEPIA2, Sangerbox, Ualcan, and TISIDB. The Human Protein Atlas (HPA) database assessed UBE2S protein expression and localization in cancerous and adjacent tissues, normal skin single-cell subgroups, and various cell lines. The CellTracer database explored UBE2S expression and cell differentiation in SKCM single-cell subgroups. CancerSEA and CellTracer databases were utilized to explore UBE2S's role in SKCM single-cell analysis, while TISIDB examined its correlation with the TME. RESULTS: Data from various databases showed significantly higher UBE2S messenger RNA (mRNA) and protein levels in cancer tissues compared to normal tissues. UBE2S, mainly found on the cell membrane, is linked to poor patient prognosis (P<0.05). UBE2S was highly expressed in normal skin, SKCM immune cells, and non-immune cell subpopulations, with a strong correlation to immune-related indicators in the SKCM TME (P<0.001). The A-431 and SK-MEL-30 cell lines ranked 7th and 12th in UBE2S expression among all cell lines. UBE2S expression was also positively linked to proliferation, invasion, metastasis, cell cycle, and quiescence (P<0.05). CONCLUSIONS: UBE2S has the potential to serve as a prognostic biomarker for SKCM, demonstrating a strong correlation with cellular infiltration within the SKCM TME and the functional status of individual cells.
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RPS6KA1 Remodels Fatty Acid Metabolism and Suppresses Malignant Progression in Colorectal Cancer.
Background: Colorectal cancer (CRC), with high incidence but low rates of early diagnosis, poses significant challenges to public health worldwide. Lipid metabolic reprogramming has been closely associated with CRC occurrence and development. This study aimed to identify key fatty acid metabolism-related molecules involved in the development of CRC and to explore potential prognostic biomarkers and therapeutic targets. Methods: Based on The Cancer Genome Atlas (TCGA) data from colon adenocarcinoma (COAD) patients, we applied weighted gene co-expression network analysis (WGCNA), Cox regression, and least absolute shrinkage and selection operator (LASSO) to identify fatty acid metabolism-related signature genes in CRC. Expression validation and prognostic analysis were conducted. Summary-data-based Mendelian randomization (SMR) was used to infer causal relationships between target genes and CRC. Single-cell transcriptomics and immune infiltration analysis elucidated underlying pathogenic mechanisms. Cellular and animal experiments validated tumor-suppressive effects and lipid metabolic regulatory mechanisms. Results: RPS6KA1 and CHGA were identified as fatty acid metabolism-related signature genes in COAD. Only RPS6KA1 was significantly downregulated in COAD and negatively correlated with poor prognosis (p = 0.0069). SMR confirmed its tumor-suppressive role, potentially associated with enhanced antitumor functions of CD8+T cells and follicular helper T cells. In vitro and in vivo experiments demonstrated that RPS6KA1 inhibits malignant progression of colon cancer and modulates fatty acid metabolism. Conclusions: Integrated multi-dimensional bioinformatic and experimental analyses reveal that RPS6KA1 remodels fatty acid metabolism and suppresses malignant progression, indicating its value as a prognostic biomarker in CRC and providing new insights for therapeutic strategies.
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Potential biomarkers for the prognosis and treatment of HCC immunotherapy.
OBJECTIVE: The liver is a unique organ containing large populations of immune cells. Immunotherapy for liver cancer is a promising yet particularly challenging method. Therefore, it harbors great significance for the identification of immune-related subtypes and the potential therapeutic targets for hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Firstly, we classified the HCC samples downloaded from the dataset of Cancer Genome Atlas (TCGA) into two clusters based on the immune cell infiltration. Thereafter, we identified the significant module and regulatory factors using the weighted gene co-expression network analysis (WGCNA). The immune competence of the regulatory factors was delineated through the ESTIMATE algorithm, the analysis of the tumor microenvironment, and pan-cancer analysis. In the single-cell RNA sequencing analysis, we further explored the immune competence of regulatory factors. We also collected the potential drugs targeting the regulatory factors. In addition, we constructed lncRNA-miRNA-mRNA interaction regulatory networks. Finally, western blot and quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to verify the protein expression of regulatory genes in HCC cell lines and tissues. RESULTS: According to the immune cell infiltration, two immune-related subtypes-cluster 1 and cluster 2-were found. Patients in cluster 2 had a more significant immune infiltration than in cluster 1. Afterward, six significant regulatory genes were identified through WGCNA, and the expression in cluster 2 was high in cluster 1. We performed a comprehensive analysis to clarify the immune signature. The results showed that the six genes had significant immunological competence. Moreover, the expression of the six genes was similar to the subtypes' classification. In the analysis of the prognosis value, patients in cluster 2 had a better prognosis. In addition, the lncRNA in the lncRNA-miRNA-mRNA interaction regulatory networks was located in the nucleus and cytoplasm. In the single-cell RNA sequencing analysis, the six genes were related to the immune cell. We also identified potential drugs for CD6 and CLEC12A, which may provide potential therapeutic drugs. Finally, the regulatory genes were verified in the western blot and quantitative real-time polymerase chain reaction. CONCLUSIONS: The classification into two clusters based on the immune cell infiltration may provide a promising prospect for HCC through immunotherapy. The six regulatory genes may be potential therapeutic targets in the treatment of HCC.
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Identification of CD8+ T Cell Related Biomarkers in Ovarian Cancer.
Background: Immunotherapy is a promising strategy for ovarian cancer (OC), and this study aims to identify biomarkers related to CD8+ T cell infiltration to further discover the potential therapeutic target. Methods: Three datasets with OC transcriptomic data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Two immunotherapy treated cohorts were obtained from the Single Cell Portal and Mariathasan's study. The infiltration fraction of immune cells was quantified using three different algorithms, Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), and microenvironment cell populations counter (MCPcounter), and single-sample GSEA (ssGSEA). Weighted gene co-expression network analysis (WGCNA) was applied to identify the co-expression modules and related genes. The nonnegative matrix factorization (NMF) method was proposed for sample classification. The mutation analysis was conducted using the "maftools" R package. Key molecular markers with implications for prognosis were screened by univariate COX regression analysis and K-M survival analysis, which were further determined by the receiver operating characteristic (ROC) curve. Results: A total of 313 candidate CD8+ T cell-related genes were identified by taking the intersection from the TCGA-OV and GSE140082 cohorts. The NMF clustering analysis suggested that patients in the TCGA-OV cohort were divided into two clusters and the Cluster 1 group showed a worse prognosis. In contrast, Cluster 2 had higher amounts of immune cell infiltration, elevated ssGSEA scores in immunotherapy, and a higher mutation burden. CSMD3, MACF1, PDE4DIP, and OBSCN were more frequently mutated in Cluster 1, while SYNE2 was more frequently mutated in Cluster 2. CD38 and CXCL13 were identified by univariate COX regression analysis and K-M survival analysis in the TCGA-OV cohort, which were further externally validated in GSE140082 and GSE32062. Of note, patients with lower CXCL13 expression showed a worse prognosis and the CR/PR group had a higher expression of CXCL13 in two immunotherapy treated cohorts. Conclusion: OC patients with different CD8+ T cell infiltration had distinct clinical prognoses. CXCL13 might be a potential therapeutic target for the treatment of OC.
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Polyamine-related 4-gene prognostic signature in hepatocellular carcinoma.
This study aimed to explore the biological and clinical roles of polyamine-related genes (PRGs) in hepatocellular carcinoma (HCC) and to construct a PRG-based prognostic signature for prognostic assessment and precision therapy guidance in HCC. Twenty-two PRGs were retrieved from the Molecular Signatures Database. Transcriptome, clinical, and somatic mutation data of HCC were integrated from The Cancer Genome Atlas, International Cancer Genome Collaboratory, National Omics Data Encyclopedia, and Gene Expression Omnibus. Consensus clustering identified PRG subtypes, and gene set variation analysis screened differentially-expressed genes. Univariate Cox, Least Absolute Shrinkage and Selection Operator, and multivariate Cox regression analyses were used to construct a prognostic signature, validated in internal and 4 external cohorts. Immune infiltration was analyzed via single-sample gene set enrichment analysis, CIBERSORT, and ESTIMATE. The signature's predictive value for chemotherapy, transcatheter arterial chemoembolization, and immunotherapy was assessed with GDSC, tumor immune dysfunction and exclusion and relevant therapy cohorts, and its performance was compared with 4 published HCC signatures. The expression of signature genes was verified at the mRNA, protein, and single-cell levels. Two PRG subtypes were identified in HCC. Cluster A correlated with poor prognosis, high immune infiltration, and low metabolic activity. A 4-gene signature (KIF20A, SPP1, PON1, and SERPINE1) was established, effectively stratifying HCC patients into high- and low-risk groups with significantly different overall survival. It was an independent prognostic factor with better predictive performance than published signatures, and the high-risk group had a higher TP53 mutation rate, distinct immune infiltration patterns, and was predicted to have poor therapy responses. The 4 signature genes showed abnormal expression in HCC tissues at multiple levels. This study identified 2 PRG subtypes and a robust 4-gene prognostic signature for HCC, which accurately predicts prognosis, reflects tumor immune microenvironment features, and guides precision therapy selection, highlighting PRGs' potential as HCC biomarkers and therapeutic targets.
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Evidence for altered immune-structural cell crosstalk in cystic fibrosis revealed by single cell transcriptomics.
BACKGROUND: Chronic pulmonary inflammation strongly contributes to respiratory failure and mortality in patients with cystic fibrosis (pwCF). Effective anti-microbial immunity and maintaining lung homeostasis require continuous structural-immune cell communication. Whether and how this crosstalk is altered in CF remains poorly understood, obscuring potential new angles for therapy development to restore airway homeostasis in pwCF. METHODS: We performed droplet-based single cell RNA-sequencing on bronchial biopsies from pwCF to investigate structural-immune cell crosstalk. Computational analyses were used to compare these data to samples obtained from healthy controls. RESULTS: CF airway wall biopsies showed lower proportions and altered transcriptomes of basal cells, submucosal gland cells and endothelial cells, and a higher abundance of ciliated cells, monocytes, macrophages and T cells. Both B and T lymphocytes displayed aberrantly activated phenotypes with transcriptional changes linked to hypoxia and vascular endothelial growth factor signaling, indicative of crosstalk with endothelial cells. The CF lung displayed unique changes in intercellular communication potential involving ionocytes, macrophages, endothelial cells and lymphocytes. This included interactions between HLA-E on structural cells and the druggable CD94/NKG2A immune checkpoint on CD8+T cells. CONCLUSIONS: We report the first single cell transcriptome atlas of the CF lung containing the full spectrum of structural and immune cells, providing a valuable resource for investigating changes to cellular composition, phenotypes and crosstalk linked to CF. Our analyses highlight dysregulated basal cell function and adaptive immunity in pwCF - despite favorable responses to CFTR modulator therapy. We identify novel aspects of CF pathophysiology and potential entry points for therapeutic strategies.