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Identification of mitophagy-related biomarkers with immune cell infiltration in psoriasis.

BACKGROUND: Psoriasis is an inflammatory disorder characterized by scaly erythematous plaques and significant comorbidities. Recent studies have suggested that impaired mitophagy, the cellular mechanism for removing dysfunctional mitochondria, may contribute to the pathogenesis of psoriasis. METHODS: In this study, we analyzed bulk RNA sequencing data from 167 healthy individuals and 177 patients with psoriasis obtained from the Gene Expression Omnibus database (GSE30999 and GSE54456). Mitophagy-related genes were isolated using weighted gene co-expression network analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed and protein-protein interaction networks were constructed for the functional enrichment of genes associated with mitophagy. The correlations between genes associated with mitophagy, signaling pathways, and immune cell infiltration were analyzed. The potential diagnostic value of genes associated with mitophagy was evaluated using receiver operating characteristic (ROC) curves, which were validated in imiquimod-induced psoriatic skin lesions in mice. RESULTS: We identified 3,839 differentially expressed genes between healthy individuals and patients with psoriasis, and 23 genes were selected as hub genes showing a high correlation with mitophagy in psoriasis. GO and KEGG analyses revealed that hub and associated genes were significantly correlated with skin functions, such as epidermal development and keratinocyte differentiation. In addition, mitophagy-related genes were negatively associated with pro-inflammatory and pro-proliferation pathways in psoriasis. Among the immune cells, CD4+ T cells were most significantly affected by mitophagy-related genes. ROC analysis demonstrated that mitophagy-related genes, especially ACER1, C1ORF68, CST6, FLG2, GJB3, GJB5, GPRIN2, KRT2, and SPRR4 were potential biomarkers of psoriasis for use in diagnosis or treatment. CONCLUSIONS: Mitophagy-related genes play crucial roles in psoriasis and have potential use as biomarkers, providing insights into disease mechanisms and therapeutic targets. Further research may lead to the development of new strategies for psoriasis management.

Psoriasis

Effect of Tertiary Lymphoid Structures on Immune Cell Infiltration in the Tumor Microenvironment and Prognosis in Lung Adenocarcinoma.

Tertiary lymphoid structures (TLSs) modulate immune responses in various solid tumors, but their comprehensive role in lung adenocarcinoma (LUAD) remains unclear. In this study, we analyzed RNA-seq data from 539 LUAD patients in The Cancer Genome Atlas (TCGA) and microarray data from 223 samples from the Gene Expression Omnibus (GEO, GSE13213, and GSE37745). TLS signatures were evaluated via unsupervised consensus clustering based on 12 chemokine transcriptome signatures. The relationships between TLS and clinical characteristics, tumor microenvironment (TME) cell infiltration, and prognosis were assessed using ESTIMATE and CIBERSORT. A prognostic model was established using LASSO regression and validated with external datasets. Additionally, H&E and IHC analyses were performed to explore associations between intratumoral TLS density, immune-related molecular expression, and patient prognosis in LUAD. Consensus clustering of the TCGA cohort revealed two distinct LUAD patient clusters according to TLS abundance. Cluster 1 exhibited greater immune cell infiltration, more favorable prognosis, and increased expression of immune checkpoint molecules. We developed a prognostic model comprising eight survival-associated genes that act as independent prognostic factors for patient survival. H&E/IHC analyses revealed that TLS density-regardless of pathological stage-was associated with better prognosis; higher intratumoral TLS density/proportion was also related to more favorable outcomes. IHC confirmed that survival-associated genes (CD5, HLA-DMB, and P2RY13) are independent prognostic indicators in LUAD. Our study demonstrated the close relationship between TLS signatures and an active immune microenvironment, highlighting their potential as independent prognostic indicators in LUAD.

Humans

MS4A3 as a potential prognostic biomarker for colon cancer: integrated analysis of expression patterns and immune cell infiltration.

BACKGROUND: Membrane Spanning 4-Domains A3 (MS4A3) has been confirmed to possess significant tumor-suppressive potential in various malignancies. However, its expression characteristics and clinical prognostic value in colon cancer (CC) still lack systematic and in-depth investigation. This study aimed to systematically investigate the expression pattern, prognostic value, immune microenvironment association, and biological function of MS4A3 in CC through integrated bioinformatics analyses and experimental validation. METHODS: This study utilized The Cancer Genome Atlas-Colon Adenocarcinoma (TCGA-COAD) cohort to screen for genes significantly associated with CC and combined multiple independent Gene Expression Omnibus (GEO) datasets to validate the expression patterns and prognostic significance of MS4A3. Key biological pathways were identified through gene set enrichment analysis (GSEA), and tumor immune infiltration characteristics were evaluated using the CIBERSORT algorithm. Additionally, the expression of MS4A3 and its impacts on cellular functions were validated at the cellular level through quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, Cell Counting Kit-8 (CCK-8), EdU, Transwell, and TUNEL assays. RESULTS: Analysis of public datasets revealed that MS4A3 is significantly downregulated in CC tissues, and its low expression is an independent risk factor for shortened overall survival (OS). GSEA indicated that MS4A3 downregulation is closely associated with the aberrant activation of the pentose phosphate pathway. Immune infiltration analysis showed that low MS4A3 expression is closely linked to the enrichment of M2 macrophages and neutrophils, as well as the upregulation of multiple immune checkpoint genes. In vitro experiments further confirmed that MS4A3 was lowly expressed in CC cell lines. Its overexpression significantly inhibited CC cell viability, proliferation, migration, and invasion, while simultaneously promoting cell apoptosis. CONCLUSIONS: MS4A3 expression is significantly decreased in CC tissues and is significantly correlated with poor prognosis, suggesting that this gene may serve as a potential prognostic biomarker.

MS4A3

Analysis and validation of abnormal signaling pathways and immune cell infiltration characteristics in digestive system cancers based on peroxisome-related genes.

BACKGROUND: Although emerging evidence suggests a role for peroxisomes in tumorigenesis, their functions in digestive cancers remain unclear. This study aims to investigate the association between peroxisomes and digestive tract tumors. METHODS: To systematically investigate peroxisomal functions in digestive cancers, we first constructed and validated tumor-specific prognostic signatures based on peroxisome-related genes (PRGs) through univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. We then characterized the tumor immune microenvironment (TIME) with CIBERSORT, X-CELL, and EPIC algorithms, and identified tumor-specific and common signalings via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Focusing on hepatocellular carcinoma (HCC), we experimentally validated peroxisome-related therapeutic responses by profiling signature genes in radioresistant cells and an orthotopic transarterial chemoembolization (TACE) rat model. PEX13 knockdown further assessed peroxisomal role in radiosensitivity and targeted therapy response. Clinical relevance of PEX13 was evaluated in HCC cohort. Single-cell RNA sequencing dataset and lipidomics further revealed peroxisomal mechanisms in HCC progression. Finally, peroxisomal function in colorectal cancer (CRC) was validated in vitro. RESULTS: Novel peroxisome-related prognostic signatures demonstrated strong predictive power in HCC, colon adenocarcinoma, rectal adenocarcinoma, pancreatic adenocarcinoma, gastric adenocarcinoma, esophageal adenocarcinoma, esophageal squamous cell carcinoma, and cholangiocarcinoma. High-risk patients displayed an immunosuppressive microenvironment, characterized by increased infiltration of regulatory T cells, M2 macrophages, Th2 cells, or cancer-associated fibroblasts, or Th1 cells' reduction. Peroxisomes engaged in several distinct yet convergent pathways, most notably "positive regulation of response to stimuli". HCC prognostic genes were dynamically regulated in response to therapeutic stimuli, including radiotherapy, targeted therapy, and TACE. Clinically, the expression of PEX13 was markedly upregulated in tumor tissues from therapy-resistant HCC patients. Mechanistically, peroxisomal dysfunction induced by silencing PEX13 in HCC or UBE2D2 in CRC may overcome therapeutic resistance (radiotherapy/ lenvatinib resistance in HCC, radioresistance in CRC) through reprogramming lipid metabolism. CONCLUSIONS: Peroxisomes act as pivotal regulators of digestive cancer progression by modulating signaling pathways, the TIME, therapeutic resistance, and lipid metabolism. Targeting peroxisomal function, particularly in high-risk subgroups of HCC and CRC, warrants further exploration as a promising therapeutic strategy.

Peroxisomes

High-Frequency Irreversible Electroporation Alters Proteomic Profiles and Tropism of Small Tumor-Derived Extracellular Vesicles to Promote Immune Cell Infiltration.

High-frequency irreversible electroporation (H-FIRE) is a nonthermal tumor ablation technique that disrupts the blood-brain barrier (BBB) in a focal and reversible manner. However, the mechanisms underlying this disruption remain poorly understood, particularly the role of small tumor-derived extracellular vesicles (sTDEVs) released from ablated tumor cells. In this study, we investigate the proteomic and functional alterations of sTDEVs released from F98 glioma and LL/2 Lewis lung carcinoma cells following H-FIRE ablation. Mass spectrometry analysis revealed 108 unique proteins in sTDEVs derived from ablative doses of H-FIRE, which are capable of disrupting the BBB in an in vitro model. Proteomic analysis of TDEVs highlights key changes in pathways related to integrin signaling, Platelet-derived growth factor receptor (PDGFR) signaling, and ubiquitination, which may underline their interactions with brain endothelial cells. These "disruptive" sTDEVs exhibit enhanced tropism for cerebral endothelial cells both in vitro and in vivo, where they persist in the brain longer than sTDEVs released after non-ablative H-FIRE doses. Notably, when introduced into a healthy Fischer rat model, disruptive sTDEVs are associated with increased recruitment of Iba1+ immune cells, suggesting a potential role in modulating post-ablation immune responses. However, despite their altered protein composition, these vesicles do not directly increase BBB permeability in vivo. This study is the first to demonstrate that electroporation-based tumor ablation significantly alters the composition and functionality of tumor-derived extracellular vesicles, potentially influencing the tumor microenvironment post-ablation. These findings have important implications for developing multimodal treatment strategies that combine H-FIRE with systemic therapies to enhance efficacy while managing the peritumoral microenvironment.

Animals

Targeting RECQL4 in hepatocellular carcinoma: from prognosis to therapeutic potential.

OBJECTIVE: The aim of this study is to assess the clinical utility of RecQ Like Helicase 4 (RECQL4) as a prognostic marker in hepatocellular carcinoma (HCC) and investigate its associations with various biological processes, angiogenesis-related factors, immune cell infiltration, immune checkpoints, and drug sensitivity. METHODS: RECQL4 expression was analyzed across a range of cancer types utilizing data from the TCGA database. Disparities in RECQL4 expression levels between normal and malignant tissues were evaluated, alongside an analysis of progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) curves. Exploration of pertinent pathways, immune cell infiltration, single-cell RNA-seq data, and drug sensitivity was conducted employing The Cancer Genome Atlas (TCGA) and Tumor Immune Single-Cell Hub (TISCH) databases. Furthermore, validation of in-silico results was validated through qPCR, Western blotting, CCK-8 assay, EdU assay, clonogenic assay, wound-healing assay, and transwell assay. RESULTS: In HCC, RECQL4 was highly expressed and associated with poorer prognosis (p&#x2009;<&#x2009;0.05). It positively correlated with pathways related to MYC targets, DNA replication, PI3K/AKT/mTOR signaling, DNA repair mechanisms, and the G2/M checkpoint (R&#x2009;>&#x2009;0.24, p&#x2009;<&#x2009;0.001). RECQL4 also showed significant correlations with angiogenesis-related genes, including PTK2 (R&#x2009;>&#x2009;0.4, p&#x2009;<&#x2009;0.05), suggesting a potential role in angiogenesis regulation. Immune analysis indicated that RECQL4 was associated with immune cell types such as T helper 2 cells, NK CD56bright cells, and follicular helper T cells, suggesting a positive relationship with their infiltration. High RECQL4 expression was also linked to increased sensitivity to drugs including Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Cellular experiments showed that RECQL4 expression at the mRNA and protein levels were significantly higher in HCC cell lines Hep3B and Huh7 compared to the normal liver cell line MHA. Moreover, RECQL4 knockdown resulted in reduced proliferation and migration in HCC cell lines (p&#x2009;<&#x2009;0.05). CONCLUSIONS: RECQL4 shows promise as a biomarker for predicting recurrence and survival in HCC and may affect angiogenesis regulation. Its expression also appears to impact sensitivity to drugs such as Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Furthermore, silencing RECQL4 significantly inhibits HCC cell line proliferation and migration.

Humans

A machine learning-derived intratumoral heterogeneity-related signature predicts the prognosis for and therapeutic response in patients with skin cutaneous melanoma.

BACKGROUND: Reliable biomarkers for predicting prognosis and therapeutic response in skin cutaneous melanoma (SKCM) remain limited. This study aimed to develop an intratumoral heterogeneity (ITH)-related prognostic signature for SKCM using integrative machine learning. METHODS: RNA sequencing (RNA-seq) data from 472 SKCM patients in The Cancer Genome Atlas (TCGA) and 214 patients in the GSE65904 cohort were analyzed. ITH scores were calculated using the DEPTH2 algorithm. Differentially expressed genes (DEGs) were identified between high- and low-ITH groups [|log2fold change (FC)| &#x2265;1, false discovery rate (FDR) <0.05]. Based on 38 prognostic DEGs identified by univariate Cox regression, we employed an integrative framework of 101 machine learning algorithm combinations to construct prognostic models in the TCGA training cohort. The model with the highest average concordance index (C-index) was validated in the GSE65904 cohort and selected as the prognostic ITH-related signature (PIRS). Associations of the PIRS risk score with tumor mutational burden (TMB), immune cell infiltration, immune checkpoint gene expression, and drug sensitivity were systematically evaluated. Model performance was assessed using receiver operating characteristic (ROC) curves and Cox regression analyses. RESULTS: A 38-gene PIRS was constructed using the plsRcox algorithm. Patients with high PIRS risk scores exhibited significantly poorer overall survival (OS) in both the TCGA and Gene Expression Omnibus (GEO) cohorts. The PIRS was identified as an independent prognostic factor, with area under the curve (AUC) values of 0.779, 0.734, and 0.756 for 1-, 3-, and 5-year survival, respectively. High-risk samples displayed significantly lower TMB (P<0.05), reduced immune and stromal cell infiltration (P<0.001), downregulated immune function, and decreased expression of immune checkpoint genes. Additionally, high- and low-PIRS risk score groups exhibited distinct sensitivity patterns to different classes of targeted agents. CONCLUSIONS: The machine learning-derived PIRS robustly predicts prognosis in SKCM patients. Its clinical application is promising for optimizing patient risk stratification and treatment decisions, though further prospective validation is warranted.

Skin cutaneous melanoma (SKCM)

Integrated transcriptomic and immunogenomic analysis unravels the immunological functions and prognostic landscape of WD repeat domain 76.

BackgroundWD Repeat Domain 76 (WDR76) plays a potential role in cellular regulation; however, its comprehensive landscape across human malignancies and its specific biological function in hepatocellular carcinoma (HCC) remain largely unexplored.MethodsWe conducted a systematic pan-cancer analysis utilizing multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) atabases to evaluate WDR76 expression, subcellular localization, and its correlation with clinicopathologic features, genomic instability, and immune infiltration. Diagnostic and prognostic values were assessed via Receiver operating characteristic (ROC) and Kaplan-Meier analyses. Furthermore, the functional role of WDR76 in HCC was validated in vitro using Hep-3B and Huh7 cell lines through siRNA-mediated knockdown, followed by CCK-8, wound-healing, and transwell assays.ResultsWDR76 was significantly upregulated in the majority of tumor types, including LIHC, LUAD, and COAD, while exhibiting nuclear localization. Elevated WDR76 expression correlated with advanced tumor staging, metastasis, and poor clinical outcomes across multiple cohorts, particularly in ACC, KIRP, and LIHC. ROC analysis highlighted its exceptional diagnostic precision in cancers such as GBM and LIHC. Immunologically, WDR76 expression was intricately linked to immune cell infiltration, immune checkpoint markers, and genomic instability parameters, suggesting a role in shaping the tumor microenvironment. Drug sensitivity profiling revealed that high WDR76 levels correlate with resistance to specific chemotherapeutic agents. Experimentally, silencing WDR76 in HCC cells significantly suppressed cell proliferation, migration, and invasion capabilities.ConclusionOur study establishes WDR76 as a robust pan-cancer prognostic biomarker and a potential immunotherapeutic target. Specifically, we provide experimental evidence that WDR76 functions as an oncogenic driver in liver cancer, promoting malignant phenotypes and offering a novel avenue for targeted therapeutic intervention.

Humans

Lactate dehydrogenase a is a crucial biomarker that affects the prognosis, chemotherapy effect, and immune infiltration of breast cancer.

PURPOSE: Lactate dehydrogenase A (LDHA) is a key node in tumor growth, metabolism, and invasion and is upregulated across multiple cancers. However, the molecular mechanisms by which LDHA influences breast cancer (BC) remain unclear. We analyzed public datasets and an institutional cohort to clarify the relationship between LDHA and BC, with the aim of informing future therapeutic strategies. PATIENTS AND METHODS: Using The Cancer Genome Atlas (TCGA), we assessed LDHA expression in BC and examined its associations with tumor mutational burden (TMB), immune cell infiltration, immune checkpoint molecules, and drug sensitivity. We integrated multiple databases and used Kaplan-Meier analyses to evaluate prognostic value. To explore biological functions of LDHA, we performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). We then analyzed BC patients receiving neoadjuvant chemotherapy (NAC) at Harbin Medical University Cancer Hospital to test the relationship between serum lactate dehydrogenase (LDH) and pathological complete response (pCR). Finally, we used National Health and Nutrition Examination Survey (NHANES) data to examine the association between serum LDH and mortality. RESULTS: LDHA was upregulated in BC tissues, and higher expression was significantly associated with worse overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS). Functional analyses indicated enrichment of metabolic pathways, such as glycolysis. LDHA expression correlated with multiple immune cell populations, suggesting involvement in the tumor immune microenvironment. Lower LDHA expression was associated with greater sensitivity to several chemotherapeutic agents. In our institutional cohort, patients with lower serum LDH were more likely to achieve pCR, and LDH was an independent predictor of pCR. In NHANES, elevated serum LDH was linked to increased mortality risk. CONCLUSION: Our findings suggest that LDHA expression and serum LDH levels are promising prognostic biomarkers for survival and may predict chemotherapy response in BC patients. These results highlight the clinical relevance of LDHA-mediated metabolic pathways. However, as a correlational study, our findings warrant further validation through functional experiments to confirm LDHA's role as a potential therapeutic target.

Humans

Notch pathway defines an aggressive and immune-suppressive phenotype associated with checkpoint inhibitor resistance in pan-gastrointestinal adenocarcinomas.

The Notch pathway regulates the homeostasis and tumorigenesis of gastrointestinal epithelium. Given its roles in cancer stem cell capacity and cancer immunity, we hypothesized that Notch activation can predict poor prognosis and resistance to immune checkpoint inhibitors (ICIs) in gastrointestinal adenocarcinoma (GIAC). The mRNA expression and genomic alterations of Notch pathway were characterized in esophagus (ESAD), stomach (STAD), colon (COAD), or rectum (READ) adenocarcinomas from The Cancer Genome Atlas (TCGA) dataset. The prognostic model (mRNA-score) was constructed using the TCGA dataset (the training set) and was validated in 3 independent sets (GSE19417 [ESAD], GSE84437 [STAD], and GSE40967 [COAD]). The associations of the mRNA-score with drug sensitivity, immune cell infiltration, and immunotherapy efficacy were, respectively, analyzed using the Genomics of Drug Sensitivity in Cancer (GDSC) database, the TCGA dataset, and multiple clinical cohorts including GSE165252, PRJEB25780, IMvigor210, and CheckMate-009/010/025. Notch pathway genes exhibited conserved genomic/transcriptomic features across four GIAC subtypes. Three pan-GIAC clusters were determined by unsupervised clustering, and the cluster with higher expression of the Notch pathway genes had shorter overall survival (OS), immunosuppressive microenvironment, and higher scores of the signatures concerning angiogenesis, cell cycle, PI3K-AKT-mTOR, TGF-&#x3b2;, glycolysis, etc. A prognostic algorithm (mRNA-score) was constructed, which was correlated with poor OS in the training set (TCGA, P&#x2009;<&#x2009;0.001) and three validation sets (GSE19417, P&#x2009;=&#x2009;0.025; GSE84437, P&#x2009;=&#x2009;0.001, GSE40967, P&#x2009;=&#x2009;0.007). A high mRNA-score was linked with more "resting"/ "anti-inflammatory" rather than "activated"/ "pro-inflammatory" tumor-infiltrating immune cells and ICI resistance in GIACs (GSE165252, P&#x2009;=&#x2009;0.047; PRJEB25780, P&#x2009;=&#x2009;0.047) and other solid tumors such as urothelial carcinoma and clear cell renal cell carcinoma. Our findings demonstrate the utility of the Notch pathway in predicting prognosis and ICI resistance. Further studies are warranted to explore the efficacy of Notch inhibitors as immunotherapeutic adjuvants to overcome ICI resistance.

Humans

Immune landscape and novel therapeutic targets of epidermal growth factor receptor and anaplastic lymphoma kinase wild type never-smoker lung adenocarcinoma.

BACKGROUND: Never-smoker lung adenocarcinoma (NSLA) exhibits distinct immunosuppressive profiles and a lower tumor mutation burden compared with lung adenocarcinoma in smokers. These correlate with poor responses to immune checkpoint inhibitors. In this study, we aimed to elucidate the tumor-immune microenvironment of NSLA without epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) alterations and identify novel therapeutic targets. METHODS: We analyzed genome, transcriptome, and proteomic data from 102 NSLA tumor samples and 16 normal adjacent tissues. We classified tumors into distinct immune clusters (IC) based on gene signatures by profiling the tumor-infiltrating immune cells. RESULTS: The tumors were stratified into three ICs: hot, intermediate, and cold. Notably, only 21 (20.6%) patients exhibited hot IC enriched in cytotoxic T cells, natural killer cells, and B-cell signatures, which correlated with improved recurrence-free survival. Cold ICs (37.3%) exhibited higher myeloid-derived suppressor cell (MDSC) levels and M2 macrophage signatures, with poor immune cell infiltration and relatively low stimulatory cytokines and chemokines expression. CEACAM1, and NECTIN2 were upregulated in intermediate and cold ICs and correlated with MDSC and M2 macrophage infiltration. High expression of these genes was associated with poor survival outcomes. Protein-protein network analysis of 20 upregulated molecules associated with cancer- and driver-related proteins in cold IC identified XPO 1 as a key component. CONCLUSION: Our proteogenomic analysis highlighted the immunosuppressive properties of NSLA without EGFR and ALK alterations and identified novel therapeutic targets. These findings may provide novel treatment strategies that could improve the clinical outcomes of patients with NSLA.

Humans

KLHL17 as a Prognostic Indicator and Therapeutic Target in Cervical Cancer: A Comprehensive Analysis.

INTRODUCTION: This study aims to clarify the role of kelch like family member 17 (KLHL17) in cervical cancer (CESC) is unclear. OBJECTIVE: To clarify this uncertainty, our research employed bioinformatics analysis coupled with experimental corroboration. METHODS: We utilized the Cancer Genome Atlas (TCGA) database to assess the expression of KLHL17 in various cancers, specifically CESC, and to explore its association with clinical characteristics, diagnostic utility, and prognostic significance in CESC. The current investigation delved into the potential regulatory pathways related to KLHL17, examining its connection with the infiltration of immune cells, the expression of immune checkpoint genes, the status of microsatellite instability (MSI), and the efficacy of diverse therapeutic agents in CESC. The research analyzed KLHL17 expression patterns using single-cell sequencing data from CESC samples and investigated the genetic variations of KLHL17 within this context. KLHL17 expression was validated using GSE145372. The presence and levels of KLHL17 in different cell lines were validated through quantitative real-time PCR (qRT-PCR) assays. RESULTS: KLHL17 exhibited irregular expression profiles across various cancer types, including CESC. Furthermore, increased KLHL17 levels in CESC patients were significantly associated with a lower progression-free survival (PFS) rate (hazard ratio: 1.62; 95% confidence interval: 1.01-2.60, p = 0.044). Moreover, KLHL17 expression emerged as a distinct prognostic indicator for CESC patients (p = 0.031). It has been associated with various biological pathways, such as cytokine-cytokine receptor interaction, primary immunodeficiency, cell adhesion molecules (CAMs), chemokine signaling pathway, steroid hormone biosynthesis, and others. The expression levels of KLHL17 were found to correlate with the presence of immune cells, the expression of immune checkpoint genes, and the status of MSI within CESC. Furthermore, KLHL17 expression exhibited a significant and inverse correlation with XMD15-27, rTRAIL, Paclitaxel, tp4ek, and tp4ek-k6. Furthermore, KLHL17 was found to be significantly positively regulated in CESC cell lines. DISCUSSION: The findings suggest that KLHL17 is involved in the progression of CESC and may serve as a potential prognostic marker and therapeutic target. KLHL17's association with immune cell infiltration and immune checkpoint genes indicates a role in immuneevasion. Future research should focus on validating these findings through independent datasets and experimental studies to elucidate the molecular mechanisms underlying KLHL17's role in CESC progression and immune regulation. CONCLUSION: KLHL17 is a promising prognostic marker and potential therapeutic target in CESC.

Humans

Integrated pan-cancer profiling highlights OSR2 as a prognostic indicator and immune-associated biomarker.

BACKGROUND: Odd-skipped-related 2 (OSR2), encoded by the OSR2 gene, has been reported to function as a checkpoint associated with CD8&#x207a; T-cell exhaustion in the tumor microenvironment of solid malignancies, suggesting its potential as a therapeutic target to improve immunotherapeutic responses. Nevertheless, the molecular and clinical significance of OSR2 across diverse cancer types has not yet been systematically investigated, and its pan-cancer expression profile, prognostic implications, and associations with tumor immunity remain to be fully elucidated. METHODS: In this study, we integrated datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) portal, and the Human Protein Atlas to construct a systematic pan-cancer profile of OSR2. The prognostic value of OSR2 was comprehensively assessed using univariate Cox regression, survival analysis, and receiver operating characteristic (ROC) curve analysis. In addition, we performed an in-depth analysis of the relationships between OSR2 and multiple molecular and immunological features, including copy number variation (CNV), DNA methylation, tumor mutational burden (TMB), microsatellite instability (MSI), immune-related gene expression, immune cell infiltration, and drug sensitivity, with the aim of exploring its potential immunological associations with the tumor microenvironment. RESULTS: OSR2 expression was significantly upregulated or downregulated in the majority of tumor tissues relative to normal counterparts and exhibited distinct cancer-type-specific patterns across clinical stages. CNV alterations and aberrant DNA methylation were closely associated with abnormal OSR2 mRNA expression in multiple cancers. Prognostic analyses indicated that OSR2 expression was significantly associated with overall survival, disease-specific survival, disease-free interval, and progression-free interval across multiple cancer types, showing either risk-associated or protective associations in a tumor-context-dependent manner. Furthermore, OSR2 expression showed strong associations with immune cell infiltration, particularly T-cell subsets, and was significantly correlated with the expression of multiple immune checkpoint-related genes across diverse malignancies. OSR2 expression was also closely associated with TMB, MSI, and sensitivity to multiple anticancer agents. CONCLUSION: Taken together, these findings suggest that OSR2 is associated with prognosis and immune-related features across multiple cancer types. OSR2 may be linked to features of the tumor immune microenvironment through its relationships with immune cell infiltration, immune checkpoint gene expression, and genomic instability, and thus may serve as a candidate biomarker for further investigation in cancer immunotherapy.

CD8&#x207a; T-cell

ZEB family is a prognostic biomarker and correlates with anoikis and immune infiltration in kidney renal clear cell carcinoma.

BACKGROUND: Zinc finger E-box binding homEeobox 1 (ZEB1) and ZEB2 are two anoikis-related transcription factors. The mRNA expressions of these two genes are significantly increased in kidney renal clear cell carcinoma (KIRC), which are associated with poor survival. Meanwhile, the mechanisms and clinical significance of ZEB1 and ZEB2 upregulation in KIRC remain unknown. METHODS: Through the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, expression profiles, prognostic value and receiver operating characteristic curves (ROCs) of ZEB1 and ZEB2 were evaluated. The correlations of ZEB1 and ZEB2 with anoikis were further assessed in TCGA-KIRC database. Next, miRTarBase, miRDB, and TargetScan were used to predict microRNAs targeting ZEB1 and ZEB2, and TCGA-KIRC database was utilized to discern differences in microRNAs and establish the association between microRNAs and ZEBs. TCGA, TIMER, TISIDB, and TISCH were used to analyze tumor immune infiltration. RESULTS: It was found that ZEB1 and ZEB2 expression were related with histologic grade in KIRC patient. Kaplan-Meier survival analyses showed that KIRC patients with low ZEB1 or ZEB2 levels had a significantly lower survival rate. Meanwhile, ZEB1 and ZEB2 are closely related to anoikis and are regulated by microRNAs. We constructed a risk model using univariate Cox and LASSO regression analyses to identify two microRNAs (hsa-miR-130b-3p and hsa-miR-138-5p). Furthermore, ZEB1 and ZEB2 regulate immune cell invasion in KIRC tumor microenvironments. CONCLUSIONS: Anoikis, cytotoxic immune cell infiltration, and patient survival outcomes were correlated with ZEB1 and ZEB2 mRNA upregulation in KIRC. ZEB1 and ZEB2 are regulated by microRNAs.

Humans

Immune subtyping of colorectal adenoma identifies a subtype with activated adaptive immunity ahead of progressing to cancer.

BACKGROUND: Colorectal adenomas (CRA) represent precursor lesions with varying risks of malignant transformation. However, molecular subtyping, particularly immune-related classification, remains underexplored in adenomas. This study aims to characterize the immune landscape of CRA through immune subtyping and evaluate its association with cancer progression, gene expression signatures, and functional pathways. METHODS: We conducted a retrospective analysis of transcriptomic data from multiple cohorts of CRA samples. Immune subtypes were identified using non-negative matrix factorization (NMF) based on immune-related genes. Diverse deconvolution algorithms were used to estimate immune cell infiltration. The immune status alteration in premalignant lesion was further consolidated by single-cell transcriptome data. Differential gene expression analysis was performed between subtypes, followed by functional enrichment analyses (Gene Ontology [GO] and Kyoto Encyclopedia of Genes and Genomes [KEGG]). RESULTS: Two distinct immune subtypes were identified: an immune-enriched subtype characterized by high lymphocyte infiltration and elevated expression of immune-related genes, and an immune-deficient subtype with suppressed immune activity. Differential expression analysis revealed significant upregulation of immune response genes (e.g., CD4, CD86, HLA-DRA) in the immune-enriched subtype. GO and KEGG analyses highlighted enrichments in leukocyte transendothelial migration, chemokine signaling, and antigen processing and presentation pathways. Single-cell result revealed an early occurrence of TIGIT activation and exhausted CD8 T cell features in adenoma when compared to normal tissue. CONCLUSION: This study delineates distinct immune subtypes within CRAs. The immune-enriched subtype demonstrates activated adaptive immunity and may reflect a higher potential for immune surveillance, while the immune-deficient subtype exhibits stromal features suggestive of progressive transformation. These findings provide insights into early immune microenvironment alterations and may inform strategies for risk stratification and immunoprevention in colorectal carcinogenesis.

Colorectal adenoma

Pan-cancer Bioinformatics Analysis Combined with Colon Cancer Experimental Validation: A Study on TMED3 as a Diagnostic and Prognostic Biomarker.

Transmembrane Emp24 Protein Transport Domain 3 (TMED3), a member of the p24 protein family, has been implicated in tumor proliferation, invasion, and migration. This study aimed to evaluate the expression patterns, prognostic significance, immune associations, and potential biological functions of TMED3 across multiple cancer types using pan-cancer bioinformatics analysis combined with immunohistochemical (IHC) validation in colon cancer. Multiomics datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, Human Protein Atlas, and cBioPortal databases were analyzed to investigate TMED3 expression and genetic alterations in pan-cancer. Immunohistochemistry was performed to evaluate TMED3 protein expression in colon cancer tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the prognostic value of TMED3. Spearman correlation analysis was conducted to evaluate the associations of TMED3 with tumor mutational burden, microsatellite instability (MSI), immune cell infiltration, and immune checkpoints. Gene Set Enrichment Analysis was performed to investigate potential biological pathways associated with TMED3 in colon cancer. TMED3 expression was elevated in most tumor types and was associated with unfavorable overall survival and disease-specific survival in adrenocortical carcinoma, colon adenocarcinoma, and uveal melanoma. The greatest frequency of TMED3 genetic alterations was identified in mesothelioma, with amplification representing the predominant alteration type. In addition, TMED3 expression showed significant correlations with tumor mutational burden and microsatellite instability in kidney renal clear cell carcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. TMED3 expression was also associated with immune infiltration and immune checkpoint expression in several tumors. IHC analysis demonstrated increased TMED3 expression in colon cancer tissues compared with normal colon tissues and showed an association with T stage. Functional enrichment analysis identified pathways related to ribosome, antigen processing and presentation, oxidative phosphorylation, and pentose phosphate. These findings indicate that TMED3 may represent a promising biomarker for the diagnosis and prognostic evaluation of colon cancer as well as other tumor types.

Humans

Research on identification of key genes and immune-metabolic mechanisms in atrial fibrillation through integrated multi-cohort transcriptomic analysis and machine learning.

This study aimed to integrate multiple datasets for the identification of atrial fibrillation (AF)-related differentially expressed genes (DEGs), analyze their underlying mechanisms through functional enrichment and machine learning, construct diagnostic models, and explore immune-metabolic interactions to provide novel biomarkers and theoretical foundations. Gene expression datasets were integrated and normalized, with batch effects removed using principal component analysis. Differential expression analysis, functional enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways), and machine learning-based feature gene selection and model construction were performed. Shapley additive explanations analysis was utilized to interpret the constructed models, while gene set enrichment analysis, gene set variation analysis, and immune cell infiltration analysis were conducted to investigate the associations between feature genes and immune infiltration. After integrating and normalizing gene expression data and eliminating batch effects via principal component analysis, 6 DEGs were identified, including 4 upregulated and 2 down-regulated ones. Functional enrichment analysis showed these DEGs were significantly enriched in neuro-related biological processes and pathways, indicating their key roles in AF pathogenesis. Five key feature genes were selected using LASSO, random forest, and support vector machine-recursive feature elimination algorithms. They had significant expression differences between the AF and control groups (P&#x2005;<&#x2005;.001) and were located on distinct chromosomes. The constructed random forest and support vector machine models performed excellently (area under the curve&#x2005;&#x2265;&#x2005;0.85). Shapley additive explanations analysis revealed TNNI1 contributed most to model prediction, with its expression significantly positively correlated with immune cell infiltration. Gene set enrichment analysis and gene set variation analysis analyses further showed feature genes participated in AF pathogenesis by regulating immune modulation, metabolic pathways, and autophagy. Immune cell infiltration analysis found altered proportions of T-cell subsets and M0 macrophages in the AF group, along with complex links between feature gene expression and immune cell function. This study systematically elucidated the unique gene expression patterns and key regulatory pathways associated with AF, clarifying the crucial roles of feature genes in immune regulation, metabolic imbalance, and cellular dysfunction. These findings provide a theoretical basis and potential therapeutic targets for understanding AF pathogenesis and developing targeted treatment strategies.

Atrial Fibrillation

COL5A1 in the tumor microenvironment predicts the prognosis of head and neck cancer.

ObjectivesThis study aims to investigate the significance of tumor microenvironment (TME)-related genes and signal transduction pathways in head and neck cancer (HNC).MethodsGene expression and clinical data of HNC patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened through a multi-step filtration approach to obtain candidate predictors. The biological role of COL5A1 in HNC was verified through rigorous bioinformatic analysis, experimental validation using quantitative real-time PCR (qRT-PCR), immunohistochemical (IHC) analysis from HNC samples, and IHC data from the Human Protein Atlas (HPA) database.ResultsCOL5A1 was significantly upregulated in HNC tissues and cell lines. High COL5A1 expression was significantly associated with advanced tumor grade (P&#x2009;<&#x2009;.05) and shorter survival (TCGA: P&#x2009;<&#x2009;.001; GSE42743: P&#x2009;=&#x2009;.004). COL5A1 was an independent prognostic indicator (univariate analysis: HR&#x2009;=&#x2009;1.324, P&#x2009;=&#x2009;.001; Multivariate analysis: HR&#x2009;=&#x2009;1.326, P&#x2009;=&#x2009;.005). It was enriched in pathways related to tumor invasion and immune responses, and its expression was associated with decreased levels of CD8+ T cells and increased levels of macrophages and neutrophils. Spatial distribution analysis revealed higher expression at the tumor's leading edge (vs. tumor core: P&#x2009;<&#x2009;.001). COL5A1 expression is associated with tumor stage, with more pronounced expression in advanced-stage tumors.ConclusionCOL5A1 represented a novel potential prognostic indicator and therapeutic target in an HNC database sample, as its expression is closely linked to tumor progression, immune cell infiltration, and adverse clinical outcomes. These findings, primarily derived from squamous cell carcinoma-dominated cohorts, warrant further functional validation.

Humans