Identification of necroptosis-associated miRNA signature for predicting prognosis and immune landscape in stomach adenocarcinoma.

PURPOSE: This study aims to identify the potential necroptosis related genes (NRGs)-associated miRNAs signature and explore the impact on the prognosis of stomach adenocarcinoma (STAD). METHODS: Employing rigorous methodologies, we utilized univariate Cox, Lasso and multivariate Cox regression analyses to develop a prognostic signature. Kaplan-Meier (K-M) and ROC curves were applied to assess the prognostic value of signature in a training group and an independent test group. Furthermore, we conducted Gene Set Enrichment Analysis (GSEA) for enrichment of tumor-related pathways. The risk score was calculated for each patient based on the expression of miRNAs which were enrolled in the signature. Patients were stratified into high- and low-risk groups. The immune cell infiltration and immunotherapy were compared between the two groups. Finally, the diagnostic potential of the miRNA was explored by RT-qPCR. RESULTS: We constructed a prognostic model based on 6 NRGs-associated miRNAs. K-M plots underscored superior survival outcomes in the low-risk group. GSEA results revealed the enrichment of several tumor-related pathways in the high-risk group. Notably, CD8+ T cells, Tregs and activated memory CD4+ T cells exhibited negative correlations with the risk score. Additionally, a few immune checkpoint genes, such as CTLA4, PD1 and PD-L1, were significantly upregulated in the low-risk group. Furthermore, the serum expression levels of all these 6 miRNAs were significantly elevated in STAD patients. CONCLUSIONS: Our study identified a robust risk score derived from a signature of 6 NRGs-associated miRNAs, demonstrating high efficacy for prognosis of STAD. These results not only contributed to our understanding of STAD pathogenesis, but also held promise for potential clinical applications, particularly in the realm of personalized immunotherapy for STAD patients.

A 15-Inflammation-Related Gene Signature Predicts the Prognosis of Patients With Pancreatic Ductal Adenocarcinoma.

Chronic inflammation promotes the development of pancreatic ductal adenocarcinoma (PDAC) and PDAC-related inflammatory tumor microenvironment facilitates tumor growth and metastasis. Thus, we aimed to study the association between inflammatory response and prognosis in patients with PDAC. We conducted the whole transcriptomic sequencing using tissue samples collected from patients diagnosed with PDAC (n = 106) recruited from Shandong Cancer Hospital. We first constructed a prognostic signature using 15 inflammation-related genes in The Cancer Genome Atlas (TCGA) cohort (n = 177) and further validated it in an independent International Cancer Genome Consortium (ICGC) cohort (n = 90) and our in-house cohort. PDAC patients with a higher risk score had poorer overall survival (OS) (P < 0.001; HR, 3.02; 95% CI, 1.94-4.70). The association between the prognostic signature and OS remained significant in the multivariable Cox regression adjusting for age, sex, alcohol exposure, diabetes, and stage (P < 0.001; HR, 2.91; 95% CI, 1.73-4.89). This gene signature also robustly predicted prognosis in the ICGC cohort (P = 0.01; HR, 1.94; 95% CI, 1.14-3.30) and our cohort (P < 0.001; HR, 2.40; 95% CI, 1.45-3.97). Immune subtype C3 (inflammatory) was enriched and CD8+ T cells were higher in patients with a lower risk score (P < 0.05). Furthermore, PDAC patients with higher risk scores were more sensitive to chemotherapy, immunotherapy, and PARP inhibitors (P < 0.05). In sum, we identified a novel gene signature that was associated with inflammatory response for risk stratification, prognosis prediction, and therapy guidance in PDAC patients. Future studies are warranted to validate the clinical utility of the signature.

Identification and Validation of the Diagnostic Markers for Inflammatory Bowel Disease by Bioinformatics Analysis and Machine Learning.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract which is mediated by the inappropriate immune responses. This study was aimed to identify novel diagnostic biomarkers for diagnosis of IBD and explore the relationship between the diagnostic biomarkers and infiltrated immune cells. GSE38713, GSE53306, and GSE75214 downloaded from the Gene Expression Omnibus (GEO) database were split into training and testing sets. Differentially expressed genes (DEGs) were screened using the "limma" package. Gene Ontology (GO) and KEGG pathway enrichment analysis of DEGs were performed by clusterProfiler package. The LASSO regression and support vector machine recursive feature elimination (SVM-RFE) algorithms were conducted to identify novel diagnostic biomarkers. The receiver operating characteristic (ROC) curve was applied to evaluate the diagnostic value of the candidate biomarkers. The relationship of the candidate biomarkers and infiltrating immune cells in IBD were evaluated by CIBERSOTR. Quantitative Real-Time PCR (qRT-PCR) was applied to measure the expression level of the biomarkers in IBD. A total of 289 dysregulated genes were identified as DEGs in IBD. These DEGs were significantly enriched in chemokine signaling pathway and cytokine-cytokine receptor interaction. RHOU was identified as a critical diagnostic gene in IBD, which was confirmed using ROC curve and qRT-PCR assays. Immune cell infiltration analysis showed that RHOU was correlated with macrophages M2, dendritic cells resting, mast cells resting, T cells CD4 memory resting, macrophages M0, and mast cells activated. Our results imply that RHOU may be a potential diagnostic biomarker for IBD.

Inherent Capability of Self-Assembling Nanostructures in Specific Proteasome Activation for Cancer Cell Pyroptosis.

Understanding the direct interaction of nanostructures per se with biological systems is important for biomedical applications. However, whether nanostructures regulate biological systems by targeting specific cellular proteins remains largely unknown. In the present work, self-assembling nanomicelles are constructed using small-molecule oleanolic acid (OA) as a molecular template. Unexpectedly, without modifications by functional ligands, OA nanomicelles significantly activate cellular proteasome function by directly binding to 20S proteasome subunit alpha 6 (PSMA6). Mechanism study reveals that OA nanomicelles interact with PSMA6 to dynamically modulate its N-terminal domain conformation change, thereby controlling the entry of proteins into 20S proteasome. Subsequently, OA nanomicelles accelerate the degradation of several crucial proteins, thus potently driving cancer cell pyroptosis. For translational medicine, OA nanomicelles exhibit a significant anticancer potential in tumor-bearing mouse models and stimulate immune cell infiltration. Collectively, this proof-of-concept study advances the mechanical understanding of nanostructure-guided biological effects via their inherent capacity to activate proteasome.

Constructing a novel mitochondrial-related gene signature for evaluating the tumor immune microenvironment and predicting survival in stomach adenocarcinoma.

BACKGROUND: The incidence and mortality of gastric cancer ranks fifth and fourth worldwide among all malignancies, respectively. Accumulating evidences have revealed the close relationship between mitochondrial dysfunction and the initiation and progression of stomach cancer. However, rare prognostic models for mitochondrial-related gene risk have been built up in stomach cancer. METHODS: In current study, the expression and prognostic value of mitochondrial-related genes in stomach adenocarcinoma (STAD) patients were systematically analyzed to establish a mitochondrial-related risk model based on available TCGA and GEO databases. The tumor microenvironment (TME), immune cell infiltration, tumor mutation burden, and drug sensitivity of gastric adenocarcinoma patients were also investigated using R language, GraphPad Prism 8 and online databases. RESULTS: We established a mitochondrial-related risk prognostic model including NOX4, ALDH3A2, FKBP10 and MAOA and validated its predictive power. This risk model indicated that the immune cell infiltration in high-risk group was significantly different from that in the low-risk group. Besides, the risk score was closely related to TME signature genes and immune checkpoint molecules, suggesting that the immunosuppressive tumor microenvironment might lead to poor prognosis in high-risk groups. Moreover, TIDE analysis demonstrated that combined analysis of risk score and immune score, or stromal score, or microsatellite status could more effectively predict the benefit of immunotherapy in STAD patients with different stratifications. Finally, rapamycin, PD-0325901 and dasatinib were found to be more effective for patients in the high-risk group, whereas AZD7762, CEP-701 and methotrexate were predicted to be more effective for patients in the low-risk group. CONCLUSIONS: Our results suggest that the mitochondrial-related risk model could be a reliable prognostic biomarker for personalized treatment of STAD patients.

Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration.

BACKGROUND: Current research on autophagy is mainly focused on intervertebral disc tissues and cells, while there is few on human peripheral blood sample. therefore, this study constructed a diagnostic model to identify autophagy-related markers of intervertebral disc degeneration (IVDD). METHODS: GSE150408 and GSE124272 datasets were acquired from the Gene Expression Omnibus database, and differential expression analysis was performed. The IVDD-autophagy genes were obtained using Weighted Gene Coexpression Network Analysis, and a diagnostic model was constructed and validated, followed by Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA). Meanwhile, miRNA-gene and transcription factor-gene interaction networks were constructed. In addition, drug-gene interactions and target genes of methylprednisolone and glucosamine were analyzed. RESULTS: A total of 1,776 differentially expressed genes were identified between IVDD and control samples, and the composition of the four immune cell types was significantly different between the IVDD and control samples. The Meturquoise and Mebrown modules were significantly related to immune cells, with significant differences between the control and IVDD samples. A diagnostic model was constructed using five key IVDD-autophagy genes. The area under the curve values of the model in the training and validation datasets were 0.907 and 0.984, respectively. The enrichment scores of the two pathways were significantly different between the IVDD and healthy groups. Eight pathways in the IVDD and healthy groups had significant differences. A total of 16 miRNAs and 3 transcription factors were predicted to be of great value. In total, 84 significantly related drugs were screened for five key IVDD-autophagy genes in the diagnostic model, and three common autophagy-related target genes of methylprednisolone and glucosamine were predicted. CONCLUSION: This study constructs a reliable autophagy-related diagnostic model that is strongly related to the immune microenvironment of IVD. Autophagy-related genes, including PHF23, RAB24, STAT3, TOMM5, and DNAJB9, may participate in IVDD pathogenesis. In addition, methylprednisolone and glucosamine may exert therapeutic effects on IVDD by targeting CTSD, VEGFA, and BAX genes through apoptosis, as well as the sphingolipid and AGE-RAGE signaling pathways in diabetic complications.

LRRK2 correlates with macrophage infiltration in pan-cancer.

Leucine-rich repeat kinase2 (LRRK2) influences the host immune responses and correlates with the pathogenesis of inflammation, cancer as well as Parkinson' Disease. Herein, we explored the oncogenic role of LRRK2 at pan-cancer level and validated the analysis by single cell RNA-sequencing and in-vitro experiments. As a result, LRRK2 significantly correlated with the survival events. Specifically, LRRK2 increased the risk of Low-Grade Glioma whereas improved the survival probability of patients with Skin Cutaneous Melanoma. Gene set enrichment analysis demonstrated the involvement of LRRK2 in the host immune responses. Within the tumor microenvironment, LRRK2 was positively associated with the recruitment of macrophages. Furthermore, scRNA-seq and co-culture experiments demonstrated that LRRK2 deficiency impaired macrophage functions, and influenced the neoplastic progression in a cancer type-specific manner. Therefore, the present study provided a therapeutic strategy for LGG based on the interference with LRRK2 expression and activity to prevent macrophage recruitment and promote tumor eradication.

Rcl1 suppresses tumor progression of hepatocellular carcinoma: a comprehensive analysis of bioinformatics and in vitro experiments.

BACKGROUND: RNA 3'-terminal phosphate cyclase-like protein (Rcl1) is involved in pre-rRNA processing, but its implication in cancers remains unclear. METHODS: RCL1 expressions in 21 malignancies was examinated through GEPIA website portal. Clinical implication data related to RCL1 level in Hepatocellular Carcinoma (HCC) samples were downloaded through TCGA, ICGC, GEO databases. Survival analysis and gene function enrichment analyses were performed through R software. The correlation between RCL1 expression and tumor immune infiltration was assessed via the TIMER2.0 database. The effects of Rcl1 overexpression or knockdown on cell growth and metastasis was evaluated by CCK8, transwell, and cell cycle assays. RESULTS: RCL1 expression is commonly down-regulated in HCC. The lower expression of RCL1 is associated with higher tumor stage, higher AFP level, vascular invasion, and poor prognosis. RCL1 expression has a significant correlation with immune cells infiltration in HCC, especially myeloid-derived suppressor cell (MDSC). Moreover, it was further identified that Rcl1 expression was reduced in HCC cell lines and negatively correlated with invasion of HCC cell lines. Immunofluorescence (IF) analysis revealed that the level of Rcl1 expression in the cytoplasm of HCC cells is significantly lower than that in the cytoplasm of L-02 cell. Moreover, both gain- and loss-of-function studies demonstrated that Rcl1 inhibited the growth and metastasis of HCC cells and regulated cell cycle progression in vitro. CONCLUSIONS: Rcl1 may serve as a novel tumor suppressor in HCC, and its biological effect needs further study.

Sirtuin 7 Deficiency Reduces Inflammation and Tubular Damage Induced by an Episode of Acute Kidney Injury.

Acute kidney injury (AKI) is a public health problem worldwide. Sirtuins are a family of seven NAD+-dependent deacylases, Overexpression of Sirtuin 1, 3, and 5 protect against AKI. However, the role of Sirtuin 7 (Sirt7) in AKI is not known. Here, we analyzed how Sirt7 deficient mice (KO-Sirt7) were affected by AKI. As expected, wild-type and Sirt7 heterozygotes mice that underwent renal ischemia/reperfusion (IR) exhibited the characteristic hallmarks of AKI: renal dysfunction, tubular damage, albuminuria, increased oxidative stress, and renal inflammation. In contrast, the KO-Sirt7+IR mice were protected from AKI, exhibiting lesser albuminuria and reduction in urinary biomarkers of tubular damage, despite similar renal dysfunction. The renoprotection in the Sirt7-KO+IR group was associated with reduced kidney weight, minor expression of inflammatory cytokines and less renal infiltration of inflammatory cells. This anti-inflammatory effect was related to diminished p65 expression and in its active phosphorylation, as well as by a reduction in p65 nuclear translocation. Sirt7 deficient mice are protected from AKI, suggesting that this histone deacetylase promotes tubular damage and renal inflammation. Therefore, our findings indicate that Sirt7 inhibitors may be an attractive therapeutic target to reduce NFκB signaling.

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most prevalent and inflammation-associated cancers. The tumor microenvironment (TME) plays an essential role in HCC development and metastasis, leading to poor prognosis. The overall TME immune cells infiltration characterizations mediated by immune-related genes (IRGs) remain unclear. In this study, we aimed to investigate whether immune-related genes could be indicators for the prognosis of HCC patients and TME cell infiltration characterization as well as responses to immunotherapy. METHODS: We obtained differentially expressed immune-related genes (DE IRGs) between normal liver tissues and liver cancer tissues from The Cancer Genome Atlas (TCGA) database. To identify the prognostic genes and establish an immune risk signature, we performed univariable Cox regression survival analysis and the Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the DE IRGs by robust rank aggregation method. Cox regression analysis was used to identify independent prognostic factors in HCC. We estimated the immune cell infiltration in TME via CIBERSORT and immunotherapy response through TIDE algorithm. RESULTS: We constructed an immune signature and validated its predictive capability. The immune signature included 7 differentially expressed IRGs: BIRC5, CACYBP, NR0B1, RAET1E, S100A8, SPINK5, and SPP1. The univariate and multivariate cox analysis showed that the 7-IRGs signature was a robust independent prognostic factor in the overall survival of HCC patients. The 7-IRG signature was associated with some clinical features, including gender, vascular invasion, histological grade, clinical stage, T stage. We also found that the 7-IRG signature could reflect the infiltration characterization of different immunocytes in the tumor microenvironment (TME) and had a good correlation with immune checkpoint molecules, revealing that the poor prognosis might be partly due to immunosuppressive TME. The Tumour Immune Dysfunction and Exclusion (TIDE) analysis data showed that the 7-IRG signature had great potential for indicating the immunotherapy response in HCC patients. The mutation analysis demonstrated a significant difference in the tumor mutation burden (TMB) between the high- and low-risk groups, partially explaining this signature's predictive value. CONCLUSION: In a word, we constructed and validated a novel, immune-related prognostic signature for HCC patients. This signature could effectively indicate HCC patients' survival and immunotherapy response. And it might act as potential immunotherapeutic targets for HCC patients.

Low dose radiation primed iNOS + M1macrophages modulate angiogenic programming of tumor derived endothelium.

Solid tumors are covered by stroma, which is hypoxic in nature and composed of various non-malignant components such as endothelial cells, fibroblasts, and pericytes that support tumor growth. Tumor stroma represents a mechanical barrier for tumor infiltration of CD8+ effector T cells in particular. In this context, our previous studies have demonstrated the therapeutic impact of Low-Dose Radiation (LDR)-primed and M1-retuned (iNOS+) peritumoral macrophages that produce inducible nitric oxide, have immunological roles on tumor infiltration of effector T cells, cancer-related inflammation, and subsequent tumor immune rejection in a mouse model of pancreatic cancer. These findings suggested a possible modification of tumor endothelium by LDR-primed macrophages. In line with these observations, here we demonstrate the influence of LDR in down-modulating HIF-1 in irradiated tumors in the course of polarization of irradiated tumor-associated macrophages toward an M1 phenotype. Furthermore, we demonstrate that M1 macrophages which are primed by LDR can directly influence angiogenic responses in eNOS+ endothelial cells which produce nitric oxide having both vascular and physiological roles. Furthermore, we demonstrate that naïve macrophages, upon differentiating to an M1 phenotype either by Th1 stimuli or LDR, potentially modify sphingosine-1-phosphate/VEGF-induced angiogenic signaling in tumor-derived endothelial cells with tumorigenic potential, thus indicating the significance of iNOS+ macrophages in modulating signaling in eNOS+ tumor-derived endothelium. Our study suggests that iNOS+ macrophages can activate tumor endothelium which may contribute to cancer-directed immunotherapy in particular.

The Analysis of ceRNA Networks and Tumor Microenvironment in Endometrial Cancer.

Background: Endometrial carcinoma is a life-threatening and aggressive tumor that affects women worldwide. ceRNAs and carcinoma-infiltrating immunocytes can be associated with tumor formation and progression. Therefore, investigating the unique mechanisms underlying endometrial carcinoma is crucial. Methods: Prognostic nomograms were constructed based on the differentially expressed genes between normal and tumor tissues. Twenty types of tumor immune infiltrating cells in uterine corpus endometrial carcinoma (UCEC) were examined using CIBERSORT. To identify the potential signaling pathways, the associations among essential ceRNA network genes and important immunocytes were investigated using the co-expression assay. Results: Differential analysis identified 3636 mRNAs, 249 miRNAs, and 252 lncRNAs unique to UCEC. The ceRNA network was constructed using the interplays between 19 lncRNA-miRNA pairs and 434 miRNA-mRNA pairs. Furthermore, CIBERSORT and ceRNA integration analysis revealed that immune cells, including dendritic cells and natural killer cells, and associated ceRNAs such as LRP8, HDGF, PPARGC1B, and TEAD1 can appropriately predict prognosis. A receiver operating characteristic curve was constructed to predict patient outcomes. Conclusions: Using a nomogram, we predicted the outcomes of patients with UCEC Furthermore, we revealed its significance in improving clinical management.

Unveiling Immune Infiltration Characterizing Genes in Hypertrophic Cardiomyopathy Through Transcriptomics and Bioinformatics.

Background: Hypertrophic cardiomyopathy (HCM) is a dominantly inherited disease associated with sudden immune cell associations that remain unclear. The aim of this study was to comprehensively screen candidate markers associated with HCM and immune cells and explore potential pathogenic pathways. Methods: First, download the GSE32453 dataset to identify differentially expressed genes (DEGs) and perform Gene Ontology and pathway enrichment analysis using DAVID and GSEA. Next, construct protein-protein interaction (PPI) networks using String and Cytoscape to identify hub genes. Afterward, use CIBERSORT to determine the proportion of immune cells attributed to key genes in HCM and conduct ROC analysis based on the external dataset GSE36961 to evaluate their diagnostic value. Finally, validate the expression of key genes in the hypertrophic cardiomyocyte model through qRT-PCR using data from the HPA database. Results: Comprehensive analysis revealed that there were 254 upregulated genes and 181 downregulated genes in HCM. The enrichment study underscored pathways of inflammatory signaling, including MAPK and PI3K-Akt pathways. Pathways abundant in genes associated with HCM encompassed myocardial contraction and NADH dehydrogenase activity. Additionally, the analysis of immune infiltration revealed a notable increase in macrophages, NK cells, and monocytes in the HCM group, showing statistically significant variances in CD4 memory resting T cell infiltration when compared to the healthy control group. Within the validation dataset GSE36961, the Area Under the Curve (AUC) scores for eight crucial genes (FOS, CD86, CD68, BDNF, PIK3R1, PLEK, RAC2, CCL2) each exceeded 0.8. The HPA database revealed the positioning traits and paths of these eight crucial genes in smooth muscle cells, myocardial cells, and fibroblasts. The outcomes of the qRT-PCR were aligned with the sequencing findings. Conclusion: Bioinformatics analysis unveiled pivotal genes, pathways, and immune involvement, illuminating the molecular underpinnings of HCM. These findings suggest promising therapeutic targets for clinical applications.

Development and Validation of Diagnostic Models for Transcriptomic Signature Genes for Multiple Tissues in Osteoarthritis.

Background: Progress in research on expression profiles in osteoarthritis (OA) has been limited to individual tissues within the joint, such as the synovium, cartilage, or meniscus. This study aimed to comprehensively analyze the common gene expression characteristics of various structures in OA and construct a diagnostic model. Methods: Three datasets were selected: synovium, meniscus, and knee joint cartilage. Modular clustering and differential analysis of genes were used for further functional analyses and the construction of protein networks. Signature genes with the highest diagnostic potential were identified and verified using external gene datasets. The expression of these genes was validated in clinical samples by Real-time (RT)-qPCR and immunohistochemistry (IHC) staining. This study investigated the status of immune cells in OA by examining their infiltration. Results: The merged OA dataset included 438 DEGs clustered into seven modules using WGCNA. The intersection of these DEGs with WGCNA modules identified 190 genes. Using Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest algorithms, nine signature genes were identified (CDADC1, PPFIBP1, ENO2, NOM1, SLC25A14, METTL2A, LINC01089, L3HYPDH, NPHP3), each demonstrating substantial diagnostic potential (areas under the curve from 0.701 to 0.925). Furthermore, dysregulation of various immune cells has also been observed. Conclusion: CDADC1, PPFIBP1, ENO2, NOM1, SLC25A14, METTL2A, LINC01089, L3HYPDH, NPHP3 demonstrated significant diagnostic efficacy in OA and are involved in immune cell infiltration.

Development of a Novel Lipid Metabolism-related Gene Prognostic Signature for Patients with Colorectal Cancer.

BACKGROUND: The purpose of this study was to explore the expression profiles of lipid metabolism-related genes in patients with Colorectal Cancer (CRC). METHODS: The lipid metabolism statuses of CRC patients from The Cancer Genome Atlas (TCGA) were analyzed. Risk characteristics were constructed by univariate Cox regression and minimum Absolute contraction and Selection Operator (LASSO) Cox regression. A histogram was constructed based on factors such as age, sex, TNM stage, T stage, N stage, and risk score to provide a visual tool for clinicians to predict the probability of 1-year, 3-year, and 5-year OS for CRC patients. By determining Area Under Curve (AUC) values, the time-dependent Receiver Operating characteristic Curve (ROC) was used to evaluate the efficiency of our model in predicting prognosis. RESULTS: A novel risk signal based on lipid metabolism-related genes was constructed to predict the survival of CRC patients. Risk characteristics were shown to be an independent prognostic factor in CRC patients (p <0.001). There were significant differences in the abundance and immune characteristics of tumor-filtering immune cells between high-risk and low-risk groups. The nomogram had a high potential for clinical application and the ROC AUC value was 0.827. Moreover, ROC analysis demonstrated that the nomogram model was more accurate to predict the survival of CRC patients than age, gender, stage and risk score. CONCLUSION: In this study, we demonstrated a lipid metabolism-related genes prognosis biomarker associated with the tumor immune micro-environment in patients with CRC.

Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies.

BACKGROUND: Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications. METHODS: Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes. Subsequently, a protein-protein interaction (PPI) network was established using the STRING database. The created network was visually inspected through Cytoscape, and HGs were identified using the CytoHubba plugin tool. Furthermore, enrichment analysis, expression pattern analysis, clinicopathological correlation, survival analysis, immune cell infiltration analysis, and examination of chemical compounds were carried out using Enrichr, GEPIA2, ULCAN, Kaplan Meier plotter, TIMER2.0, and CTD web platforms, respectively. The diagnostic and prognostic significance of HGs was evaluated through the ROC curve analysis. RESULTS: Ten genes associated with ECM functions were identified as HGs among 131 DEGs obtained from microarray datasets. Notably, the expression of these HGs exhibited significantly (p < 0.05) higher in PC, demonstrating a clear association with tumor advancement. Remarkably, higher expression levels of these HGs were inversely correlated with the likelihood of patient survival. Moreover, ROC curve analysis revealed that identified HGs are promising biomarkers for both diagnostic (AUC > 0.75) and prognostic (AUC > 0.64) purposes. Furthermore, we observed a positive correlation between immune cell infiltration and the expression of most HGs. Lastly, our study identified nine compounds with significant interaction profiles that could potentially act as effective chemical agents targeting the identified HGs. CONCLUSION: Taken together, our findings suggest that COL1A1, KRT19, MMP1, COL11A1, SDC1, ITGA2, COL1A2, POSTN, FN1, and COL5A1 hold promise as innovative biomarkers for both the diagnosis and prognosis of PC, and they present as prospective targets for therapeutic interventions aimed at impeding the progression PC.

The prognostic significance and clinical relevance of stem cell characteristic in bladder cancer.

Background: Bladder cancer (BLCA) is a common malignant tumor of urinary system and prognostic biomarkers are needed for better clinical decision-making and patient management. Cancer stem cells (CSCs) are involved in carcinogenesis, development, metastasis and recurrence of BLCA. This study explored the prognostic and predictive value of CSCs-related genes and laid the groundwork for precision treatment development in BLCA. Methods: The mRNA data and corresponding clinical information obtained from TCGA-BLCA cohort was used to discover biomarkers and develop CSCs-related prognostic model, which was further validated in GSE32548 and GSE32894 datasets. In addition, the association between CSCs-related risk score and therapeutic efficacy was analyzed to explore the potential predictive value of the prognostic model. Results: We identified four CSCs-related subtypes and 900 differentially expressed genes (DEGs) among subtypes. Then the CSCs-related prognostic model was built based on 16 CSCs-related DEGs with the most significant prognostic value. Patients in the low-risk group had better overall survival than those in high-risk group (P < 0.001; HR, 0.42; 95 %CI, 0.31-0.57). Multivariable Cox analysis in training and test sets confirmed the independence of CSCs-related risk score as a prognostic factor (P < 0.05). The difference of survival between two risk groups were probably due to the significantly varied immune microenvironment based on the analysis of infiltrated immune cells. Additionally, the risk score was significantly associated with chemotherapy sensitivity and the response to anti-PD-L1 therapy (P < 0.05) which suggested a potential predictive value of CSCs-related risk model. Conclusion: We established a risk classifier based on 16 CSCs-related genes for predicting survival in patients with BLCA. The CSCs-related risk model has both prognostic value and potential predictive value for therapeutic efficacy, which brings us closer to understanding the important role of CSCs in BLCA and may provide guidance for clinical treatment decision-making and patient management. The clinical utility of the CSCs-related risk classifier warrants further studies.

Exploring the common mechanism of vascular dementia and inflammatory bowel disease: a bioinformatics-based study.

Objective: Emerging evidence has shown that gut diseases can regulate the development and function of the immune, metabolic, and nervous systems through dynamic bidirectional communication on the brain-gut axis. However, the specific mechanism of intestinal diseases and vascular dementia (VD) remains unclear. We designed this study especially, to further clarify the connection between VD and inflammatory bowel disease (IBD) from bioinformatics analyses. Methods: We downloaded Gene expression profiles for VD (GSE122063) and IBD (GSE47908, GSE179285) from the Gene Expression Omnibus (GEO) database. Then individual Gene Set Enrichment Analysis (GSEA) was used to confirm the connection between the two diseases respectively. The common differentially expressed genes (coDEGs) were identified, and the STRING database together with Cytoscape software were used to construct protein-protein interaction (PPI) network and core functional modules. We identified the hub genes by using the Cytohubba plugin. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied to identify pathways of coDEGs and hub genes. Subsequently, receiver operating characteristic (ROC) analysis was used to identify the diagnostic ability of these hub genes, and a training dataset was used to verify the expression levels of the hub genes. An alternative single-sample gene set enrichment (ssGSEA) algorithm was used to analyze immune cell infiltration between coDEGs and immune cells. Finally, the correlation between hub genes and immune cells was analyzed. Results: We screened 167 coDEGs. The main articles of coDEGs enrichment analysis focused on immune function. 8 shared hub genes were identified, including PTPRC, ITGB2, CYBB, IL1B, TLR2, CASP1, IL10RA, and BTK. The functional categories of hub genes enrichment analysis were mainly involved in the regulation of immune function and neuroinflammatory response. Compared to the healthy controls, abnormal infiltration of immune cells was found in VD and IBD. We also found the correlation between 8 shared hub genes and immune cells. Conclusions: This study suggests that IBD may be a new risk factor for VD. The 8 hub genes may predict the IBD complicated with VD. Immune-related coDEGS may be related to their association, which requires further research to prove.

The shared circulating diagnostic biomarkers and molecular mechanisms of systemic lupus erythematosus and inflammatory bowel disease.

Background: Systemic lupus erythematosus (SLE) is a multi-organ chronic autoimmune disease. Inflammatory bowel disease (IBD) is a common chronic inflammatory disease of the gastrointestinal tract. Previous studies have shown that SLE and IBD share common pathogenic pathways and genetic susceptibility, but the specific pathogenic mechanisms remain unclear. Methods: The datasets of SLE and IBD were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified using the Limma package. Weighted gene coexpression network analysis (WGCNA) was used to determine co-expression modules related to SLE and IBD. Pathway enrichment was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis for co-driver genes. Using the Least AbsoluteShrinkage and Selection Operator (Lasso) regressionand Support Vector Machine-Recursive Feature Elimination (SVM-RFE), common diagnostic markers for both diseases were further evaluated. Then, we utilizedthe CIBERSORT method to assess the abundance of immune cell infiltration. Finally,we used the single-cell analysis to obtain the location of common diagnostic markers. Results: 71 common driver genes were identified in the SLE and IBD cohorts based on the DEGs and module genes. KEGG and GO enrichment results showed that these genes were closely associated with positive regulation of programmed cell death and inflammatory responses. By using LASSO regression and SVM, five hub genes (KLRF1, GZMK, KLRB1, CD40LG, and IL-7R) were ultimately determined as common diagnostic markers for SLE and IBD. ROC curve analysis also showed good diagnostic performance. The outcomes of immune cell infiltration demonstrated that SLE and IBD shared almost identical immune infiltration patterns. Furthermore, the majority of the hub genes were commonly expressed in NK cells by single-cell analysis. Conclusion: This study demonstrates that SLE and IBD share common diagnostic markers and pathogenic pathways. In addition, SLE and IBD show similar immune cellinfiltration microenvironments which provides newperspectives for future treatment.

Identification and validation of SLCO4C1 as a biological marker in hepatocellular carcinoma based on anoikis classification features.

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits a high degree of invasiveness and is closely associated with rapid disease progression. Multiple lines of evidence indicate a strong correlation between anoikis resistance and tumor progression, invasion, and metastasis. Nevertheless, the classification of anoikis in HCC and the investigation of novel biological target mechanisms in this context continue to pose challenges, requiring further exploration. METHODS: Combined with HCC samples from TCGA, GEO and ICGC databases, cluster analysis was conducted on anoikis genes, revealing novel patterns among different subtypes. Significant gene analysis of different gene subtypes was performed using WCGNA. The anoikis prognostic risk model was established by Lasso-Cox. Go, KEGG, and GSEA were applied to investigate pathway enrichment primarily observed in risk groups. We compared the disparities in immune infiltration, TMB, tumor microenvironment (TME), and drug sensitivity between the two risk groups. RT-qPCR and Western blotting were performed to validate the expression levels of SLCO4C1 in HCC. The biological functions of SLCO4C1 in HCC cells were assessed through various experiments, including CCK8 assay, colony formation assay, invasion migration assay, wound healing assay, and flow cytometry analysis. RESULTS: HCC was divided into 2 anoikis subtypes, and the subtypeB had a better prognosis. An anoikis prognostic model based on 12 (COPZ2, ACTG2, IFI27, SPP1, EPO, SLCO4C1, RAB26, STC2, RAC3, NQO1, MYCN, HSPA1B) risk genes is important for survival and prognosis. Significant differences were observed in immune cell infiltration, TME, and drug sensitivity analysis between the risk groups. SLCO4C1 was downregulated in HCC. SLCO4C1 downregulation promoted the proliferation, invasion, migration, and apoptosis of HCC cells. The tumor-suppressive role of SLCO4C1 in HCC has been confirmed. CONCLUSIONS: Our study presents a novel anoikis classification method for HCC that reveals the association between anoikis features and HCC. The anoikis feature is a critical biomarker bridging tumor cell death and tumor immunity. In this study, we provided the first evidence of SLCO4C1 functioning as a tumor suppressor in HCC.