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SPP1, LYZ, and MCM5: potential diagnostic biomarkers for rheumatoid arthritis and cervical cancer comorbidity.
BACKGROUND: The comorbidity of rheumatoid arthritis (RA), a chronic autoimmune disease, with cervical cancer has garnered a lot of attention. Cervical cancer is much more common in RA patients than in the general population, which may be caused by immunosuppressive therapy, chronic inflammation, and poor clearance of the Human Papillomavirus (HPV). The purpose of this study is to explore the molecular mechanism of comorbidity between RA and cervical cancer and identify potential biomarkers through transcriptomics and single cell transcriptomics analysis. METHODS: In this study, transcriptome expression profile data of RA and cervical cancer were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, and differential gene analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis were performed. Using multivariate Cox proportional hazard modeling and Lasso regression, independent differential genes linked to the prognosis of cervical cancer were screened. Molecular docking technology was used to predict the interaction between candidate gene encoded proteins and HPV 16 E6/E7. Intercellular communication and the expression patterns of potential genes in various cell groups were examined using single cell transcriptome data. Finally, the expression of candidate genes in cervical tissues of patients with RA combined with cervical cancer was verified by immunohistochemistry. RESULTS: The study found that those with RA had 493 up-regulated genes and 216 down-regulated genes, while individuals with cervical cancer had 2,600 up-regulated genes and 2,172 down-regulated genes. Cox regression analysis identified 35 genes independently associated with the prognosis of cervical cancer, of which SPP1, LYZ, and MCM5 were significantly regulated in both RA and cervical cancer. The HPV 16 E6/E7 specific binding sites of the proteins produced by these three genes were shown using molecular docking simulation. Especially, single cell transcriptomic analysis revealed that SPP1 was highly expressed in NK/T cells, Myeloid cells, and epithelial cells, and served as an important ligand receptor pair for communication between these cells. Immunohistochemistry results further verified the high expression of SPP1, LYZ, and MCM5 in patients with RA combined with cervical cancer. CONCLUSION: This study successfully identified SPP1, LYZ, and MCM5 as key hub genes for the comorbidity of RA and cervical cancer. By regulating processes like inflammation, immune evasion, and cell proliferation, these genes not only have a high diagnostic potential but may also contribute to the occurrence and development of cervical cancer.
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Construction of a neutrophil extracellular trap formation-related gene model for predicting the survival of lung adenocarcinoma patients and their response to immunotherapy.
BACKGROUND: Lung adenocarcinoma (LUAD) is associated with high morbidity and mortality rates. Increasing evidence indicates that neutrophil extracellular traps (NETs) play a critical role in tumor progression, metastasis and immunosuppression in the LUAD tumor microenvironment (TME). Nevertheless, the use of NET formation-related genes (NFRGs) to predict LUAD patient survival and response to immunotherapy has not been explored. Therefore, this study aimed to construct a NFRGs-based prognostic signature for stratifying LUAD patients and informing individualized management strategies. METHODS: The cell composition of the LUAD TME was investigated using the single-cell sequencing data in Single-Cell Lung Cancer Atlas (LuCA). NFRGs were identified to construct a prognostic signature based on The Cancer Genome Atlas (TCGA) cohort which was validated in the Gene Expression Omnibus (GEO) dataset. The univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox regression models, receiver operating characteristic (ROC) and Brier Score were applied to assess the prognostic model. A nomogram was established to facilitate the clinical application of the risk score. The Estimation of STromal and Immune cells in MAlignant Tumor tissues (ESTIMATE) and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were utilized to assess the TME and predict immunotherapy response. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was applied to quantify the expression levels of four NFRGs in LUAD paired tissue samples. RESULTS: Single‑cell RNA sequence analysis showed the importance of neutrophils in LUAD TME. We developed and validated a 4-NFRG (CAT, CTSG, ENO1, TLR2) prognostic signature based on TCGA and GEO cohorts, which stratified patients into high-risk and low-risk groups. Univariate and multivariate analyses showed that our risk model could independently predict the survival of LUAD patients. Patients in the low-risk group exhibited a more active immune microenvironment, lower TIDE scores, lower half-maximal inhibitory concentration (IC50) values and higher immune checkpoint molecule expression. Our risk signature could serve as a biomarker for predicting immunotherapeutic benefits. CONCLUSIONS: We developed a novel prognostic signature for LUAD patients based on NFRGs and emphasized the critical role of this signature in predicting LUAD patient survival and immunotherapy response.
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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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Comprehensive analysis of IGFL1 in colorectal cancer and its promotion of tumour progression via inhibition of lipophagy.
OBJECTIVE: Colorectal cancer (CRC) ranks among the most prevalent malignancies, with increasing incidence and mortality rates presenting a substantial public health challenge. While insulin growth factor like family member 1 (IGFL1) has been implicated in the regulation of various diseases, its functional role in colorectal cancer remains poorly characterised. This study therefore aims to elucidate the involvement of IGFL1 in CRC through an integrated approach combining bioinformatics analysis and experimental validation. METHODS: The expression of IGFL1 in CRC and its association with clinicopathological features, diagnostic relevance, and patient prognosis were evaluated using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Immunohistochemistry was performed to validate IGFL1 protein expression in CRC tissue samples. Immune cell infiltration levels and immune microenvironment scores related to IGFL1 expression were analysed using multiple computational algorithms, including CIBERSORT, ssGSEA, ESTIMATE, EPIC, MCP-counter, quanTIseq, TIMER, xCell, and CIBERSOR. Furthermore, IGFL1 expression patterns across distinct cellular subpopulations were examined using single-cell RNA sequencing datasets from the Tumor Immune Single-cell Hub (TISCH) database. The TIDE algorithm was applied to assess the potential clinical efficacy of immunotherapy in groups with high versus low IGFL1 expression, in addition to investigating correlations between IGFL1 expression and immune checkpoint markers. Genetic alterations of IGFL1 were analysed via cBioPortal, while the TIMER2.0 database was used to explore relationships between IGFL1 expression and key gene mutations in CRC. The CTRP and GDSC databases were employed to investigate associations between IGFL1 expression and sensitivity to conventional chemotherapy drugs. Finally, phenotypic validation and mechanistic studies were conducted using the CRC cell lines SW620 and HCT116. RESULTS: Our study demonstrates that IGFL1 expression is significantly up-regulated in CRC and possesses considerable diagnostic value. Elevated IGFL1 levels were consistently observed in clinical specimens, where high expression correlated with adverse clinicopathological features, poorer prognosis, and mutations in key oncogenes. Within the tumour microenvironment, IGFL1 appears to play a critical role in modulating the infiltration of diverse immune cell populations. Furthermore, IGFL1 expression influences both immunotherapy responsiveness and chemotherapy sensitivity in CRC patients. Genetic knockdown of IGFL1 markedly attenuated the malignant phenotype of CRC cells. RNA-sequencing analysis revealed that IGFL1 is closely linked to cholesterol metabolism, autophagy pathways, and ATP hydrolysis activity. Functionally, inhibition of IGFL1 enhanced lipophagy in CRC cells. Collectively, these findings indicate that IGFL1 promotes CRC pathogenesis and progression through the suppression of lipophagy. CONCLUSIONS: IGFL1 exhibits oncogenic properties in colorectal cancer and may represent a potential therapeutic target.
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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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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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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.