Immune Infiltration Levels Research Articles

Exploring potential therapeutic targets for small cell lung cancer based on transcriptomics combined with Mendelian randomization analysis

ObjectiveThe main objective of this study was to explore and identify new genetic targets in small-cell lung cancer (SCLC) through transcriptomics analysis and Mendelian randomization (MR) analysis, which will help in the subsequent development of new therapeutic interventions.MethodsIn this study, we extracted the SCLC dataset from the Gene Expression Omnibus (GEO) database, processed the data, and screened out differentially expressed genes (DEGs) using R software. Based on expression quantitative trait loci data and the genome-wide association study data of SCLC, MR analysis was used to screen the genes closely related to SCLC disease, which intersect with DEGs to obtain co-expressed genes (CEGs), and the biological functions and pathways of CEGs were further explored by enrichment analysis. In addition, the CIBERSORT algorithm was applied to assess the level of immune cell infiltration in SCLC and to analyze the correlation between CEGs and immune cells. Meanwhile, we performed a survival analysis on these five CEGs using an independent cohort of SCLC patients. Finally, the results for the target genes were validated.ResultsIn this study, 857 DEGs were identified, including 443 up-regulated and 414 down-regulated genes, and 5 CEGs (PSAT1, PSRC1, COLEC12, PLLP, HP) that were significantly associated with SCLC were identified through further intersecting. The results of enrichment analyses indicated that CEGs play important roles in several key functions and pathways. Immune-cell-related analysis revealed the unique distribution of immune cell infiltration in SCLC and the mechanism of immune cell regulation by CEGs. Survival analysis results indicated that PSRC1 was significantly correlated with the overall survival of SCLC, and the survival rate of the high-expression group was markedly lower than that of the low-expression group. Finally, the consistency of the results between the validation group analyses and MR analysis confirmed that the results of this study is reliable.ConclusionThe CEGs and their associated functions and pathways screened in this study may be potential targets of therapeutic intervention in SCLC by targeting specific molecular pathways.

Identification and validation of CDK1 as a promising therapeutic target for Eriocitrin in colorectal cancer: a combined bioinformatics and experimental approach

BackgroundColorectal cancer (CRC) is a prevalent malignancy worldwide, associated with significant morbidity and mortality. Cyclin-dependent kinase 1 (CDK1) plays a crucial role in cell cycle regulation and has been implicated in various cancers. This study aimed to evaluate the prognostic value of CDK1 in CRC and to identify traditional Chinese medicines (TCM) that can target CDK1 as potential treatments for CRC.MethodsThe expression and prognostic value of CDK1 were analyzed through TCGA, GEO, GEPIA, UALCAN and HPA databases. An ESTIMATE analysis was applied to estimate the proportions of stromal and immune cells in tumor samples. GO and KEGG enrichment analyses were performed to clarify the functional roles of CDK1-related genes. CCK-8, colony formation, cell migration, cell invasion, and wound healing assays were employed to explore tumor-promoting role of CDK1. Molecular docking, cellular thermal shift, and isothermal dose-response assays were employed to identify potential inhibitors of CDK1.ResultsCDK1 was highly expressed in CRC and associated with a poorer prognosis. The expression of CDK1 was also correlated with the levels of immune cells infiltration. CDK1-related genes were primarily involved in the cell cycle and the P53 signaling pathway. Knockdown of CDK1 inhibited the proliferation, migration, and invasion of CRC cells in vitro. Furthermore, Eriocitrin emerged as a potential inhibitor, exerting its anti-tumor effects by targeting and inhibiting CDK1 activity.ConclusionCDK1 plays a critical role in CRC prognosis. Eriocitrin, a potential CDK1 inhibitor derived from TCM, highlights a promising new therapeutic strategy for CRC treatment.

Upregulated PCAT-1 predicts poor prognosis and reduced immune cell infiltration in head and neck squamous cell carcinoma through the miR-145-5p / FSCN-1 axis.

LncRNA PCAT-1 is known to promote cancer proliferation, invasion, and metastasis. However, its significance in HNSCC is not fully understood. This research investigates how the PCAT-1 / miR-145-5p / FSCN-1 axis promote HNSCC. We analyzed the gene expression patterns on 238 fresh-frozen samples, comparing tumors with their normal adjacent tissues (NATs). HNSCC samples showed higher PCAT-1 and FSCN-1 expression compared to NATs (p < 0.001 and p < 0.001, respectively). In contrast, miR-145-5p expression was markedly downregulated compared to NATs (p < 0.001). Notably, ROC curve analysis revealed exceptional diagnostic power, with an AUC of 0.83 for PCAT-1, 0.95 for miR-145-5p, and 0.91 for FSCN-1. Pearson correlation analysis unveiled a significant positive correlation between PCAT-1 and FSCN-1 expression levels (r = 0.084, p < 0.001) and negative correlations between FSCN-1 and miR-145-5p (r = -0.710, p < 0.001) as well as between PCAT-1 and miR-145-5p (r = -0.759, p < 0.001). Distinct molecular profiles were observed in the levels of PCAT-1, miR-145-5p, and FSCN-1 between HPV (-) and HPV ( +) 16 and 18 genotypes (p = 0.007, p = 0.027, and p = 0.002). MiR-145-5p expression showed significant differences between HPV (-) and HPV ( +) other genotypes (p = 0.035). FSCN-1 expression showed notable distinctions between HPV ( +) 18 & 16 and HPV ( +) other genotypes (p = 0.031). Elevated levels of lncRNA PCAT-1 promote HNSCC through the miR-145-5p/FSCN-1 axis and are associated with poor prognosis and reduced immune cell infiltration levels.

Euglena gracilis-derived β-glucan ameliorates particulate matter (PM2.5)-induced airway inflammation by modulating nuclear factor kappa B, mitogen-activated protein kinase, and nuclear factor erythroid 2-related factor 2 signaling pathways in A549 cells and BALB/c mice.

This study aimed to investigate the effects of β-glucan derived from Euglena gracilis (EGB), an edible microalga, on particulate matter (PM2.5)-induced airway inflammation in A549 cells and BALB/c mice. EGB effectively suppressed the mRNA and protein levels of inflammatory cytokines (IL-6, IL-1β, TNF-α, IL-8) and mediators (iNOS, COX-2), while inhibiting the NF-κB and MAPK signaling pathways triggered by PM2.5 exposure and reducing nuclear NF-κB levels. Additionally, EGB decreased PM2.5-induced ROS production and increased the protein levels of NRF2 and HO-1, along with genes encoding antioxidant enzymes (catalase, GPx, SOD1), associated with elevated nuclear NRF2 levels. EGB reduced immune cell infiltration and inflammatory cytokine levels in BALF and serum, both of which increased by PM2.5 exposure. EGB also significantly increased alveolar numbers while decreasing the gene expression of MMP1/9/13. Furthermore, EGB suppressed PM2.5-induced bronchial thickening and collagen-1 deposition by downregulating TGF-β1 expression, and alleviated goblet cell hyperplasia and mucin production in lung tissues. These results suggest that EGB effectively reduces PM2.5-induced airway inflammation by suppressing NF-κB and MAPK signaling pathways, lowering pro-inflammatory cytokines, and activating the NRF2-HO-1 signaling pathway to enhance antioxidant enzyme expression. This study highlights the potential of EGB as an edible functional agent for controlling PM-related airway inflammation.

Identification of a novel disulfidptosis-related gene signature in osteoarthritis using bioinformatics analysis and experimental validation

Osteoarthritis (OA) is a degenerative bone disease characterized by the destruction of joint cartilage and synovial inflammation, involving intricate immune regulation processes. Disulfidptosis, a novel form of programmed cell death, has recently been identified; however, the effects and roles of disulfidptosis-related genes (DR-DEGs) in OA remain unclear. We obtained six OA datasets from the GEO database, using four as training sets and two as validation sets. Differential expression analysis was employed to identify DR-DEGs, and unique molecular subtypes of OA were constructed based on these DR-DEGs. Subsequently, the immune microenvironment of OA patients was comprehensively analyzed using the “CIBERSORT” algorithm for immune infiltration. Various machine learning algorithms were utilized to screen characteristic DR-DEGs, and nomogram models and ROC curves were built based on these genes. The scRNA dataset (GSE169454) was used to classify chondrocytes in OA samples into distinct cell types, further exploring the gene distribution and correlation of characteristic DR-DEGs with specific cell subpopulations. Moreover, the expression levels of four characteristic DR-DEGs were validated through OA cell models and rat models. In our study, we identified 10 DR-DEGs with significant differences in expression within OA samples. Based on these DR-DEGs, two distinct molecular subtypes were recognized (cluster 1 and 2). ZNF484 and NDUFS1 were found to be significantly overexpressed in subtype 1, while the infiltration abundance of activated mast cells was markedly elevated in subtype 2. Moreover, significant differences were observed in the infiltration proportions of 11 immune cell types between OA and control samples, with 9 DR-DEGs demonstrating substantial correlations with immune cell infiltration levels. Further analysis of the scRNA dataset revealed that SLC3A2 and NDUFC1 were predominantly expressed in the preHTC subpopulation. All 10 DR-DEGs exhibited notably higher expression in the EC subpopulation across various cell types. The proportion of EC subgroups with high SLC3A2 expression increased, mainly enriching pathways related to inflammation, such as the IL-17 signaling pathway and TGF-beta signaling pathway. Using machine learning, we identified four characteristic DR-DEGs, which, in combination with the nomogram and ROC models, demonstrated promising performance in the diagnosis of OA. Additionally, in vivo validation confirmed a significant elevation of PPM1F expression in OA models. This study identified DR-DEGs as potential biomarkers for the diagnosis and classification of OA and provided a preliminary understanding of their role in the immune microenvironment. However, further experimental and clinical studies are required to validate their diagnostic value and therapeutic potential.

Immunomodulatory insights of monoterpene glycosides in endometriosis: immune infiltration and target pathways analysis

Endometriosis is a complex gynecological condition characterized by abnormal immune responses. This study aims to explore the immunomodulatory effects of monoterpene glycosides from Paeonia lactiflora on endometriosis. Using the ssGSEA algorithm, we assessed immune cell infiltration levels between normal and endometriosis groups. Key targets were identified through differential expression analysis of the GSE51981 dataset. Potential immunomodulatory targets of Paeonia lactiflora compounds were identified through Venn diagram analysis, followed by enrichment and machine learning analyses. A nomogram was developed for predicting endometriosis, while molecular docking explored compound-target interactions. Significant differences in immune cell infiltration were observed, with increased CD8 T cells, cytotoxic cells, and others in endometriosis. Differential expression analysis identified 43 potential targets. Enrichment analysis highlighted pathways involved in immune and inflammatory responses. Machine learning identified SSTR5, CASP3, FABP2, and SYK as critical targets, contributing to a nomogram that demonstrated good predictive performance for endometriosis risk. Molecular docking revealed strong interactions between Paeoniflorigenone and CASP3. Our findings suggest that monoterpene glycosides have therapeutic effects on endometriosis by modulating key immune-related targets and pathways, providing a basis for further investigation into Paeonia lactiflora’s potential as a treatment for this condition.

Construction of an Oxidative Stress Risk Model to Analyze the Correlation Between Liver Cancer and Tumor Immunity.

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally. Despite advancements in immunotherapy, the prognosis for patients with HCC continues to be poor. As oxidative stress plays a significant role in the onset and progression of various diseases, including metabolism-related HCC, comprehending its mechanism in HCC is critical for effective diagnosis and treatment. This study utilized the TCGA dataset and a collection of oxidative stress genes to determine the expression of oxidative stress-related genes in HCC and their association with overall survival using diverse bioinformatics methods. A novel prognostic risk model was developed, and the TCGA cohort was divided into high-risk and low-risk groups based on each tumor sample's risk score. Levels of immune cell infiltration and the expression of immune checkpoint-related genes in different risk subgroups were analyzed to investigate the potential link between tumor immunity and oxidative stress-related features. The expression of model genes in actual samples was validated through immunohistochemistry, and their mRNA and protein expression levels were measured in cell cultures. Four oxidative stress-related genes (EZH2, ANKZF1, G6PD, and HMOX1) were identified and utilized to create a predictive risk model for HCC patient overall survival, which was subsequently validated in an independent cohort. A significant correlation was found between the expression of these prognostic genes and the infiltration of tumor immune cells. Elevated expression of EZH2, ANKZF1, G6PD, and HMOX1 was observed in both HCC tissues and cell lines. The combined assessment of EZH2, ANKZF1, G6PD, and HMOX1 gene expression can serve as a model to evaluate the risk of oxidative stress in HCC. Furthermore, there is a notable correlation between the expression of these risk model genes and tumor immunity.

Analyzing the potential targets and mechanisms of chronic kidney disease induced by common synthetic Endocrine Disrupting Compounds (EDCs) in Chinese surface water environment using network toxicology and molecular docking techniques.

Long-term exposure to NP and OP, as common synthetic endocrine-disrupting chemicals (EDCs) in surface water environments in China, is closely associated with the development of chronic kidney disease (CKD). However, their potential targets and toxicological mechanisms for inducing CKD remain unknown. This study utilizes network toxicology and molecular docking techniques to explore the potential toxic targets and molecular mechanisms of CKD induction by NP and OP. We identify 49 core targets of NP and OP action in CKD using the Comparative Toxicogenomics Database (CTD) and GeneCards databases. Using the STRING database and Cytoscape software, we identify five hub genes: MAPK3, TNF, BCL2, ESR1, and FOS. We construct a nomogram model based on the CKD dataset GSE66494, utilizing these five hub genes. Calibration and ROC curves demonstrate that the model has good diagnostic value for CKD, and the DCA curve indicates that the model has high clinical utility. Single-gene GSEA enrichment analysis identifies five hub genes that influence the development of CKD through multiple biological pathways, revealing that several immune-regulatory signaling pathways are activated. The CIBERSORT algorithm identifies eight types of immune cell infiltration levels that change significantly during CKD development, and correlation analyses suggest that the five hub genes are strongly associated with multiple immune cell infiltrations. The molecular docking results suggested that ESR1, MAPK3, and TNF had the lowest binding energies and high binding affinities with NP and OP. The results of molecular dynamics simulations similarly confirmed the stability of the interactions between ESR1, MAPK3 and TNF proteins with NP and OP. The results of this study provide a theoretical basis for understanding the potential toxicity targets and mechanisms of NP- and OP-induced CKD and promote the application of network toxicology and molecular docking techniques in the study of environmental pollutants.

Functional Analysis and Experimental Validation of the Prognostic and Immune Effects of the Oncogenic Protein CDC45 in Breast Cancer.

Cell division cycle protein 45 (CDC45) plays a crucial role in DNA replication. This study investigates its role in breast cancer (BC) and its impact on tumor progression. We utilized the GEO database to screen differentially expressed genes (DEGs) and conducted enrichment analysis on these genes. We established a Nomogram model based on CDC45 and other clinical indicators. Additionally, we performed protein-protein interaction (PPI) network construction, drug sensitivity analysis, and immune correlation analysis of CDC45. The function of CDC45 was further verified through cell and animal experiments. CDC45 is highly expressed in most tumors, including BC. The expression level of CDC45 was significantly associated with age, sex, race, cancer stage, and molecular subtypes (all p < 0.05). CDC45 was incorporated into a Nomogram model, which showed moderate accuracy in predicting patient prognosis. We also analyzed the co-expression genes of CDC45, including TOPBP1, GINS2, MCM5, GINS1, GINS4, POLE2, MCM2, MCM6, MCM4, and MCM7. Furthermore, CDC45 expression was closely linked to immune infiltration levels, immune checkpoint inhibitors, and the therapeutic response to small molecule drugs. Finally, both in vitro and in vivo experiments confirmed the cancer-promoting effect of CDC45 in BC. The expression level of CDC45 is linked to the prognosis, immune infiltration, and drug sensitivity of BC. In vitro and in vivo experiments have confirmed that CDC45 acts as a cancer-promoting protein in breast cancer.

A novel N7-Methylguanine-related gene signature for predicting prognosis in acute myeloid leukemia: bioinformatic analysis and experimental verification

ABSTRACT Background: The involvement of N7-Methylguanine (m7G) RNA methylation regulators in the progression of different types of solid cancers in humans has been established. However, the specific impact of m7G-related genes on Acute myeloid leukemia (AML) remains uncertain. Our research aims to build a novel signature of M7Gs that could enhance our understanding of the molecular heterogeneity in leukemia. Methods: The RNA-seq and clinical data of patients with AML were acquired from the UCSC XENA website. Prognostic-related genes were selected using LASSO to construct a risk-scoring model. External datasets were utilized to validate the effectiveness of the model, and the mRNA expressions of candidate genes were measured using RT-qPCR. Results: A prognostic model was developed using a risk-scoring approach based on three candidate genes (IFIT5, EIF4E2, and LARP1) and their respective risk coefficients. Multivariate Cox regression analysis revealed a significant association between the risk score and overall survival (p<0.001). In both the experimental and validation cohorts, individuals classified as high risk exhibited a poorer prognosis. The 5-year area under the curve (AUC) was calculated as 0.715 for the TCGA-LAML cohort and 0.646 for GSE37642. Additionally, analysis using ssGSEA demonstrated that the high-risk group exhibited higher levels of immune cell infiltration compared to low-risk group. RT-qPCR results indicated that the expression levels of LARP1, EIF4E2 and IFIT5 were consistent with the results of the bioinformatic analysis. Conclusions: In summary, the m7G-related genes are potential prognostic biomarkers for patients with AML.

Combining immunogenic cell death and cuproptosis to construct a prognostic signature and predict the immune status and treatment efficacy for hepatocellular carcinoma

Abstract Background Immunogenic cell death (ICD) is defined as cell death sufficient to activate an adaptive immune response in an immunocompetent host. Cuproptosis is induced by increased intracellular toxicity due to copper ion accumulation. ICD and cuproptosis have great potential in regulating the growth and proliferation of cancer cells. Methods We used transcriptome data from TCGA database to identify two subtypes based on consensus clustering and explored the differences between the two groups. We further combined ICD- and cuproptosis-related genes to develop a signature and predict OS, immune status, and treatment responses in HCC patients. An ICGC cohort was used for external validation. Results Patients in the groups with high expression of ICD- and cuproptosis-related genes had higher levels of immune cell infiltration and a better immunotherapeutic response. Eight related genes (BAX, HSP90AA1, IFNB1, LY96, NT5E, LIPT1, DLAT, and CDKN2A) were screened for the prognostic signature. The survival analysis revealed that patients in the low-risk group were less likely to die at an early stage than were those in the high-risk group. The signature also showed better results in predicting immune cell infiltration and the treatment response. Conclusions Our study revealed that the prognostic signature constructed by combining ICD- and cuproptosis-related genes performs well in predicting the survival of patients with HCC and is closely associated with immune cell infiltration and immunotherapy.

Exploration of the shared pathways and common biomarkers in cervical and ovarian cancer using integrated bioinformatics analysis.

Searching for potential biomarkers and therapeutic targets for early diagnosis of gynecological tumors to improve patient survival. Microarray datasets of cervical cancer (CC) and ovarian cancer (OC) were downloaded from the Gene Expression Omnibus (GEO) database, then, differential gene expression between cancerous and normal tissues in the datasets was analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to screen for co-expression modules associated with CC and OC. The screened shared genes were then further analyzed for functional pathway enrichment. Next, the least absolute shrinkage and selection operator (LASSO) with tenfold cross validation is used to further screened for common diagnostic biomarkers for the two diseases, and further validation is performed using two independent GEO datasets. Finally, the CIBERSORT algorithm was used to estimate the immune infiltration levels of CC and OC, and the correlation between immune cell infiltration and common biomarkers was explored. After crossing the common DEGs detected by "Limma" R package with the common module genes identified by WGCNA, 44 shared genes were obtained. Functional enrichment indicates that these shared genes are mainly related to DNA synthesis pathways. Lasso regression analysis revealed that EFNA1, TYMS, and WISP2 were co-diagnostic markers for CC and OC, and then based on their expression levels and diagnostic efficacy, EFNA1 was selected as the best co-marker for CC and OC. Immune infiltration analysis shows that the immune environment has a significant impact on the occurrence and development of CC and OC, and the expression of EFNA1 is related to changes in immune cells. Gene-drug interaction analyses identified 27 common drug compounds that interact with candidate genes. This study adopted bioinformatics methods to investigate the common pathways and identify diagnostic markers between CC and OC, suggesting that DNA synthesis and immune environment are closely related to the occurrence and development of CC and OC. EFNA1 may be a potential diagnostic indicator and therapeutic target for patients with CC and OC.

Genes Associated with the Immune System Affected by Ionizing Radiation and Estrogen in an Experimental Breast Cancer Model.

Breast cancer is a global health issue that, when in the metastasis stage, is characterized by the lack of estrogen receptor-α, the progesterone receptor, and human epidermal growth receptor expressions. The present study analyzed the differential gene expression related to the immune system affected by ionizing radiation and estrogen in cell lines derived from an experimental breast cancer model that was previously developed; where the immortalized human breast epithelial cell line MCF-10F, a triple-negative breast cancer cell line, was exposed to low doses of high linear energy transfer α particle radiation (150 keV/μm), it subsequently grew in the presence or absence of 17β-estradiol. Results indicated that interferon-related developmental regulator 1 gene expression was affected in the estrogen-treated cell line; this interferon, as well as the Interferon-Induced Transmembrane protein 2, and the TNF alpha-induced Protein 6 gene expression levels were higher than the control in the Alpha3 cell line. Furthermore, the interferon-related developmental regulator 1, the Interferon-Induced Transmembrane protein 2, the TNF alpha-induced Protein 6, the Nuclear Factor Interleukin 3-regulated, and the Interferon-Gamma Receptor 1 showed high expression levels in the Alpha5 cell line, and the Interferon Regulatory Factor 6 was high in the Tumor2 cell line. Additionally, to further strengthen these data, publicly available datasets were analyzed. This analysis was conducted to assess the correlation between estrogen receptor alpha expression and the genes mentioned above in breast cancer patients, the differential gene expression between tumor and normal tissues, the immune infiltration level, the ER status, and the survival outcome adjusted by the clinical stage factor. It can be concluded that the genes of the interferon family and Tumor Necrosis factors can be potential therapeutic targets for breast cancer, since they are active before tumor formation as a defense of the body under radiation or estrogen effects.

Crosstalk between CD180-overexpression macrophages and glioma cells worsens patient survival through malignant phenotype promotion and immunosuppressive regulation

BackgroundUnderstanding the molecular mechanisms in immunosuppressive regulation is crucial for improving immunotherapeutic strategies. Macrophages, the major immune cells in tumor microenvironment (TME), play a dual role in tumor progression. CD180, primarily expressed in macrophages, remains unclear and requires further investigation.MethodsRNA-seq data were obtained to analyze CD180 expression in gliomas and assess its prognostic value. The comprehensive immune infiltration analysis was performed. Single-cell RNA-seq (scRNA-seq) data were used to examine CD180 expression distribution at the cellular level. CD180-overexpression macrophages were co-cultured with three glioma cell lines. The effects on glioma cell behavior were evaluated through qRT-PCR, Western blot, CCK-8 assay, EdU assay, Transwell assay, TUNEL assay, and flow cytometry. Differentially expressed genes (DEGs) and their potential biological functions were analyzed between different CD180 expression groups. Consensus clustering was used to identify CD180-related glioma subtypes.ResultsCD180 was significantly upregulated in glioma samples and associated with poor prognosis. High CD180 expression was correlated with increased immune cell infiltration, particularly macrophages, and elevated levels of immune checkpoints. Analysis of scRNA-seq data revealed the predominant expression of CD180 in macrophages within the glioma TME. In vitro experiments demonstrated that CD180-overexpression macrophages promoted glioma cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), while decreasing apoptosis. Mutations in TP53 and PTEN were significantly more prevalent in the high CD180 expression group. We identified nine chemotherapeutic agents that were more effective in glioma patients with high CD180 expression. Additionally, two CD180-related glioma subtypes with distinct prognosis were identified.ConclusionsThis study confirmed the prognostic role of CD180 in glioma and its involvement in immunosuppressive regulation and malignant phenotype promotion. Therefore, CD180 was considered as a promising target for immunotherapeutic strategies in glioma treatment.

Continuous prediction for tumor mutation burden based on transcriptional data in gastrointestinal cancers

BackgroundTumor mutation burden (TMB) has been considered a biomarker for utilization of immune checkpoint inhibitors(ICIs), but whole exome sequencing(WES) and cancer gene panel(CGP) based on next generation sequencing for TMB detection are costly. Here, we use transcriptome data of TCGA to construct a model for TMB prediction in gastrointestinal tumors.MethodsTranscriptome data, somatic mutation data and clinical data of four gastrointestinal tumors from TCGA, including esophageal cancer (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ). Using R, we performed visual analysis of somatic mutation data, differentially expressed genes (DEGs) function enrichment analysis, gene set enrichment analysis (GSEA), and estimated TMB value in clinic. Finally, a deep neural network (DNN) model was constructed for TMB prediction.ResultsVisualization of somatic mutation data summarized the classification of mutation, frequency of each mutation type, and top-mutated genes. GSEA showed the enrichment of CD4+/CD8+ T cells in the high TMB group and the activation of tumor suppressing pathways. Single-sample GSEA (ssGSEA) manifested that the high-TMB group had higher level of multiple immune cells infiltration. In addition, distribution of TMB was related to clinical parameters.Like age, M stage, N stage, AJCC stage, and overall survival(OS). After model optimization using genetic algorithm, in the training set, validation set, and testing set, the Pearson relevance coefficient r between predicted values and actual values reaches 0.98, 0.82, and 0.92, respectively; the coefficient of determination R2 is 0.95, 0.82, and 0.7, respectively.ConclusionTMB correlates with clinicopathological parameters in gastrointestinal carcinoma, and patients with high TMB have higher levels of immune infiltration. In addition, the DNN model based on 31 genes predicts TMB of gastrointestinal tumors in a high accuracy.

Prognostic significance of NUAK1 and its association with immune infiltration in stomach adenocarcinoma

BackgroundStomach adenocarcinoma (STAD) represents a significant global health burden, accounting for a considerable proportion of cancer-related mortalities, and NUAK1, a protein kinase, plays a crucial role in cellular metabolism, cell cycle regulation, migration, and tumor progression. However, its relationship with prognosis and immune infiltration in STAD has not been thoroughly investigated.MethodsRNA sequencing data from the Cancer Genome Atlas (TCGA) and Genotypic Tissue Expression Project (GTEx) databases were employed to assess disparities in NUAK1 expression between STAD tumour and normal tissues. Additionally, we investigated the correlation between NUAK1 expression and patient prognosis, in addition to the level of immune cell infiltration. The potential functions were elucidated through an examination of the Gene Ontology (GO) Encyclopedia, the Kyoto Encyclopedia of Genes and Genomes (KEGG), and an enrichment analysis (GSEA). The GeneMANIA was used to validate the functions of nuak1-related genes.ResultsOur analysis demonstrated that NUAK1 expression in tumour tissues exhibited a notable disparity from that observed in normal tissues, with elevated levels detected in STAD tissues. We used the GeneMANIA database to identify functionally similar genes with significantly higher expression for some genes in the unpaired group samples. An elevated NUAK1 expression level was found to correlate with a poorer overall survival (OS), disease-specific survival (DSS), and progression-free intervals (PFI). Additionally, immune infiltration analysis indicated a significant positive correlation between NUAK1 expression and various tumor-infiltrating immune cells, while a negative correlation was observed with T helper cell 17(Th17) cells. Furthermore, enrichment analysis was conducted to identify relevant biological features and pathways.ConclusionThe expression levels of NUAK1 are significantly increased in STAD, and this heightened expression correlates with diminished OS, DSS, and PFI among affected patients. These observations indicate that NUAK1 has the potential to function as a prognostic biomarker for STAD and may represent a viable therapeutic target for intervention in its management.

FGL1 facilitates rather than suppresses anticancer immunity against microsatellite instable gastric cancer.

Microsatellite instability (MSI) is a phenotype characterized by changes in the sequence length of microsatellites in tumor cells and is closely linked to tumorigenesis and prognosis. Immune checkpoint inhibitors have shown good therapeutic effects in gastric cancer (GC) with MSI-high (MSI-H). However, the role of the novel immune checkpoint fibrinogen-like protein 1 (FGL1) in GC treatment has not been fully investigated. FGL1 expression in GC tissues and the difference in FGL1 immune infiltration between MSI/ microsatellite stability (MSS) patients were analyzed by bioinformatics and were verified in clinical samples. Xenograft models of MSS and MSI GC were constructed in human immune reconstitution mice, and FGL1 expression in tumors was detected. Immunofluorescence and immunohistochemistry were used to assay the infiltration of immune cells in the two types of mice. Cytotoxicity and chemotaxis tests were used to detect the toxicity and chemotaxis of CD8+T cells to GC cells, respectively. The cytokine content was detected by enzyme-linked immunosorbent assay. The therapeutic effects of FGL1 antibody on different types of GC were analyzed by xenograft mouse models. FGL1 exhibited significantly higher expression in GC, and its expression and immune cell infiltration levels were significantly higher in MSI GC than in MSS GC. CD8+T cells were significantly more effective in killing and chemotaxis of MSI GC cells than MSS GC cells. The FGL1 antibody was more effective in treating MSI GC.The novel immunosuppressor FGL1 antibody exerts a good therapeutic influence on MSI GC. These findings provide a basis for the development of drugs targeting FGL1 for MSI GC treatment.

SOX13 as a potential prognostic biomarker linked to immune infiltration and ferroptosis inhibits the proliferation, migration, and metastasis of thyroid cancer cells.

SOX13 is a transcription factor belonging to the SOX family. SOX proteins are critical regulators of multiple cancer progression, and some are known to control carcinogenesis. Nevertheless, the functional and clinical significance of SOX13 in human thyroid cancer (THCA) remain largely unelucidated. Data on SOX13 expression were obtained through The Cancer Genome Atlas together with Gene Expression Omnibus. Co-expression, differential expression, and functional analyses of genes were investigated by databases. Associations between SOX13 levels, immune infiltration, ferroptosis, and immune checkpoint gene levels were analyzed. Genetic changes in SOX13 were investigated using CBioPortal. Associations between SOX13 levels and THCA clinicopathological features were analyzed and nomogram modeling for diagnostic and prognostic prediction. The influence of SOX13 on proliferation, migration, and metastasis was determined in KTC-1 and TPC-1 cell lines. SOX13 was significantly lower in THCA tumors compared to controls. In addition, upregulated SOX13 gene mutation were evident in thyroid cancer. SOX13-associated genes exhibited differential expression in pathways associated with thyroid cancer development. Significant associations were found between SOX13 levels, immune infiltration, ferroptosis, and immune checkpoint genes in THCA tissue. SOX13 levels correlated with THCA stage, histologic grade, and primary neoplasm focus types, and independently predicted overall and progression-free intervals. SOX13 expression effectively distinguished between tumor and normal thyroid tissue. Spearman correlations highlighted a significant relationship between SOX13 and ferroptosis-associated genes. Overexpression of SOX13 enhances the inhibition of RSL3 (iron death activator) on the cell viability of TPC-1. Higher SOX13 levels in Thyroid cancer cells may lead to reduced proliferation, migration, and metastasis by regulating ferroptosis. Reduced SOX13 expression inversely impacts patient prognosis. In addition, SOX13 strongly regulates cancer immunity and Ferroptosis. Hence, SOX13 has great promise as a bioindicator for both thyroid cancer prognosis and immune cell invasion.

Screening of potential regulatory genes in carotid atherosclerosis vascular immune microenvironment.

Immune microenvironment is one of the essential characteristics of carotid atherosclerosis (CAS), which cannot be reversed by drug therapy alone. Thus, there is a pressing need to develop novel immunoregulatory strategies to delay this pathological process that drives cardiovascular-related diseases. This study aimed to detect changes in the immune microenvironment of vascular tissues at various stages of carotid atherosclerosis, as well as cluster and stratify vascular tissue samples based on the infiltration levels of immune cell subtypes to distinguish immune phenotypes and identify potential hub genes regulating the immune microenvironment of carotid atherosclerosis. RNA sequencing datasets for CAS vascular tissue and healthy vascular tissue (GSE43292 and GSE28829) were downloaded from the Gene Expression Omnibus (GEO) database. To begin, the immune cell subtype infiltration level of all samples in both GSE43292 and GSE28829 cohorts was assessed using the ssGSEA algorithm. Following this, consensus clustering was performed to stratify CAS samples into different clusters. Finally, hub genes were identified using the maximum neighborhood component algorithm based on the construction of interaction networks, and their diagnostic efficiency was evaluated. Compared to the controls, a higher number of immune cell subtypes were enriched in CAS samples with higher immune scores in the GSE43292 cohort. Advanced CAS was characterized by high immune cell infiltration, whereas early CAS was characterized by low immune cell infiltration in the GSE28829 cohort. Moreover, CAS progression may be related to the immune response pathway. Biological processes associated with muscle cell development may impede the progression of CAS. Finally, the hub genes PTPRC, ACTN2, ACTC1, LDB3, MYOZ2, and TPM2 had satisfactory efficacy in the diagnosis and prediction of high and low immune cell infiltration in CAS and distinguishing between early and advanced CAS samples. The enrichment of immune cells in vascular tissues is a primary factor driving pathological changes in CAS. Additionally, CAS progression may be related to the immune response pathway. Biological processes linked to muscle cell development may delay the progression of CAS. PTPRC, ACTN2, ACTC1, LDB3, MYOZ2, and TPM2 may regulate the immune microenvironment of CAS and participate in the occurrence and progression of the disease.

MiR-137 regulates autophagy and apoptosis in duodenal ulcer by targeting BNIP3L.

Duodenal ulcer (DU) represents a clinical manifestation and disease state that occurs when the mucosal surface of the duodenum is damaged. The processes of autophagy and apoptosis have been linked to the development of DU, yet the precise roles they play remain unclear. This study aimed to investigate the expression and mechanism of action of microRNAs (miRNA)-137 (miR-137) in DU. Dysregulated miRNAs and targeted genes were identified from the Gene Expression Omnibus database, and the immune cell infiltration levels were analyzed using CIBERSORT. To confirm the targeting of the miRNAs, we conducted dual luciferase reporter assays in vitro. The detection of cell apoptosis was conducted using flow cytometry. Moreover, quantitative reverse transcription polymerase chain reaction, cell counting kit-8, and Western blot were employed to ascertain the levels of autophagy- and apoptosis-related proteins. Bioinformatics analysis identified 5 miRNAs, with miR-137 showing the most pronounced dysregulation. Its target gene, BNIP3L, was subsequently identified. In vitro experiments confirmed that miR-137 targeted BNIP3L. The upregulation of miR-137 expression in HIEC-6 cells resulted in the inhibition of BNIP3L expression, a reduction in autophagy, and an increase in apoptosis. A reduction in the expression of miR-137 would have the opposite effect. miR-137 is upregulated in DU patients and contributes to ulcer progression by inhibiting BNIP3L, reducing autophagy, and promoting apoptosis. Targeting miR-137 could provide a novel therapeutic strategy for DU management.