Genotype-Tissue Expression Database Research Articles

Comparative Analysis of Transcription Factors TWIST2, GATA3, and HES5 in Glioblastoma Multiforme : Evaluating Biomarker Potential and Therapeutic Targets Using In Silico Methods.

Glioblastoma multiforme (GBM) is characterized by substantial heterogeneity and limited therapeutic options. As molecular approaches to central nervous system (CNS) tumors have gained prominence, this study examined the roles of three genes, TWIST2, GATA3, and HES5, known to be involved in oncogenesis, developmental processes, and maintenance of cancer stem cell properties, which have not yet been extensively studied in GBM. This study is the first to present gene expression data for TWIST2, GATA3, and HES5 specifically within the context of GBM patient survival. Gene expression data for TWIST2, GATA3, and HES5 were collected from GBM and normal brain tissues using datasets from The Cancer Genome Atlas (TCGA) via the Genomic Data Commons (GDC) portal and the Genotype-Tissue Expression (GTEx) database. These data were rigorously analyzed using in silico methods. All three genes were significantly more expressed in GBM tissues than in normal tissues. TWIST2 and GATA3 were linked to lower survival rates in GBM patients. Interestingly, higher HES5 levels were associated with better survival rates, suggesting a complex role that needs more investigation. This study shows that TWIST2, GATA3, and HES5 could help predict outcomes in GBM patients. Our multigene model offers a better understanding of GBM and points to new treatment options, bringing hope for improved therapies and patient outcomes. This research advances our knowledge of GBM and highlights the potential of molecular diagnostics in oncology.

The prognostic and immune significance of Rab11A in pan-cancer and its function and mechanism underlying estrogen receptor targeting in breast cancer.

Rab11A is an important molecule for recycling endosomes and is closely related to the proliferation, invasion, and metastasis of tumors. This study investigated the prognostic and immune significance of Rab11A and validated its potential function and mechanism in breast cancer (BRCA). RNA sequencing data for 33 tumors were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression databases. Correlation analysis was used to evaluate the relationship between Rab11A expression and immune characteristics. Potential pathways were identified using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis. Immunohistochemical analysis, colony formation assay, bromodeoxyuridine incorporation assay, immunofluorescence, and Western blot were used to explore potential function and mechanism. Analysis of the TCGA database showed significant upregulation of Rab11A expression in a variety of cancers. Rab11A was up-regulated in 82.4% of BRCA. High Rab11A expression is associated with poor survival in cancer patients and is a predictor of poor prognosis. CIBERSORT analysis showed that Rab11A was negatively associated with almost all immune cycle activity scores pan-cancer. The results of the TCGA-BRCA cohort were further confirmed by using pathological samples from clinical BRCA patients. The results showed that Rab11A expression was correlated with estrogen receptor (ER) and progesterone receptor expression in BRCA (p<0.05). Knockdown and overexpression of Rab11A affected the proliferation of BRCA cells. Further mechanistic studies revealed that down-regulation of ER alpha (ERα) and up-regulation of ER beta (ERβ) mediated Rab11A-induced inhibition of BRCA cell proliferation. Rab11A expression in pan-cancer is associated with poor prognosis and immune profile. In particular, in BRCA, Rab11A expression regulates cell proliferation by targeting ERα and ERβ. High Rab11A expression is tightly associated with immune characteristics, tumor microenvironment, and genetic mutations. These results provide a reference for exploring the role of Rab11A in pan-cancer and provide a new perspective for revealing potential therapeutic targets in BRCA.

Investigating PPT2’s role in ovarian cancer prognosis and immunotherapy outcomes

Ovarian cancer (OC) remains the primary cause of mortality among gynecological malignancies, and the identification of reliable molecular biomarkers to prognosticate OC outcomes is yet to be achieved. The gene palmitoyl protein thioesterase 2 (PPT2), which has been sparsely studied in OC, was closely associated with metabolism. This study aimed to determine the association between PPT2 expression, prognosis, immune infiltration, and potential molecular mechanisms in OC. We obtained the RNA-seq and clinical data from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases, then Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, nomogram, and calibration were conducted to assess and verify the role of PPT2. Gene set enrichment analysis (GSEA) was used to figure out the closely correlated pathways with PPT2. Overexpression experiment was performed to explore the function of PPT2. Our findings showed that PPT2 mRNA expression was apparent down-regulation in OC tissue compared to normal ovarian tissues in TCGA, GTEx datasets, and GEO datasets. This differential expression was also confirmed in our in-house datasets at both the mRNA and protein levels. Decreased PPT2 expression correlated with lower survival rates in TCGA, several GEO datasets, and our in-house datasets. Multivariate analysis revealed that PPT2 was an independent factor in predicting better outcomes for OC patients in TCGA and GEO. A negative correlation was revealed between immune infiltration and PPT2 expression through Single-sample GSEA (ssGSEA). Additionally, PPT2 was negatively correlated with an up-regulated immune score, stromal score, and estimate score, suggesting that patients with low PPT2 expression might benefit more from immunotherapy. Numerous chemical agents showed lower IC50 in patients with high PPT2 expression. In single-cell RNA sequencing (scRNA-seq) analysis of several OC datasets, we found PPT2 was mainly expressed in endothelial cells. Furthermore, we found that PPT2 inhibited OC cell proliferation in vitro. Our results demonstrated that PPT2 was considered a favorable prognostic biomarker for OC and may be vital in predicting response to immunotherapy and chemotherapy. Further research was needed to fully understand the relationship between PPT2 and immunotherapy efficacy in OC patients.

The mutated in colorectal cancer (MCC) gene can serve as a potential biomarker of glioblastoma.

The mutated in colorectal cancer (MCC) gene was initially identified as a candidate tumor suppressor gene in colorectal cancer, acting as a negative regulator of cell cycle progression. However, its functional roles in brain tumors, particularly glioblastoma, remain largely unexplored. This study reveals a significant association between MCC status and glioblastoma. We explored MCC expression in the glioblastoma database, patient samples, and cell lines. We investigated the proliferation and migration of the cell lines in MCC gene knockdown using small interfering RNA. In vitro analyses revealed elevated protein and mRNA levels of MCC in several glioblastoma cell lines (U118MG and T98G). Silencing MCC expression via siRNA-mediated knockdown resulted in increased proliferation and migration of these cell lines. Supporting these findings, analyses of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases confirmed higher MCC expression in glioblastoma tumors than in normal brain tissue. Importantly, we observed that high MCC expression was associated with poor prognosis in glioblastoma patients, highlighting its potential role in disease progression. Additionally, this study identifies a nuclear localization of MCC in the glioblastoma cell line. These findings indicate that MCC expression is significantly upregulated in glioblastoma and may play a role in its pathophysiology, warranting further investigation.

Actin-related protein 2/3 complex subunit 1B promotes ovarian cancer progression by regulating the AKT/PI3K/mTOR signaling pathway.

Actin-related protein 2/3 complex subunit 1B (ARPC1B) is an essential subunit of the actin-related protein 2/3 (Arp2/3) complex. While there have been numerous research reports on Arp2/3 in relation to tumors, there needs to be more research on ARPC1B and its role in tumors, particularly at the pan-cancer level. Utilizing data from the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx) databases, we analyzed ARPC1B expression differences in normal, tumor, and adjacent tissues, investigating its correlation with prognosis and clinical stages in various cancers. We conducted gene enrichment analysis and explored ARPC1B's connection to the tumor immune microenvironment and its impact on anti-tumor drug resistance. In addition, in vivo and in vitro experiments have also been carried out to find the mechanism of ARPC1B on ovarian cancer (OV) proliferation and invasion. ARPC1B was highly expressed in 33 tumor types, suggesting its role as a tumor-promoting factor. Its expression correlated with poor prognosis and served as a clinical staging marker in over 10 tumor types. ARPC1B is implicated in various biological processes and signaling pathways, uniquely associated with tumor immunity, indicating immunosuppressive conditions in high-expression cases. High ARPC1B expression was linked to resistance to six anti-tumor drugs. Further experiments showed that ARPC1B can affect the proliferation, apoptosis, migration, and invasion of OV cells through the AKT/PI3K/mTOR pathway. ARPC1B is a biomarker for immune suppression, prognosis, clinical staging, and drug resistance, providing new insights for cancer therapeutics.

Comprehensive analysis of NOTCH pathway with tumor environment in pancreatic adenocarcinoma

Abstract Objectives Pancreatic adenocarcinoma (PAAD) ranks among the most prevalent malignant neoplasms, and multiple pathways are involved in its pathogenesis, including the NOTCH pathway. However, the variable biological functions of the pathway in PAAD are controversial. Methods RNA-seq data for PAAD was analyzed using data from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Utilizing Kaplan-Meier survival curves and Cox regression analyses, we examined the prognostic significance. The tumor microenvironment and immunotherapy responses were investigated using ssGSEA, ESTIMATE, and TIDE models. Functional enrichment analysis was used to explore gene functions. Results We identified NOTCH2, JAG1, NOTCH4, and DLL3 as high-priority members of the NOTCH pathway that modulates PAAD. Elevated NOTCH2 and JAG1 levels were markedly linked to reduced overall survival (OS), while increased NOTCH4 and DLL3 levels were significantly related to extended OS. Immune analyses showed that NOTCH-based scores were closely related to the immune microenvironment. NOTCH scores were not only closely correlated with tumor-infiltrating immune cells, but also with immunologically activated and immune checkpoint gene expression. The high NOTCH score group had a higher proportion of tumor-infiltrating immune cells and had better responses to immune checkpoint inhibitor therapy. Conclusions These data indicate that NOTCH2, JAG1, NOTCH4, and DLL3 could function as efficient prognostic biomarkers and therapeutic targets in PAAD, and patients with a high NOTCH score may have a significant response to immune checkpoint inhibitor treatment.

The regulation of NFKB1 on CD200R1 expression and their potential roles in Parkinson’s disease

BackgroundOveractivated microglia are a key contributor to Parkinson’s disease (PD) by inducing neuroinflammation. CD200R1, a membrane glycoprotein mainly found on microglia, is crucial for maintaining quiescence with its dysregulation linked to microglia’s abnormal activation. We and other groups have reported a decline in CD200R1 levels in several neurological disorders including PD. However, the mechanism regulating CD200R1 expression and the specific reasons for its reduction in PD remain largely unexplored. Given the pivotal role of transcription factors in gene expression, this study aimed to elucidate the transcriptional regulation of CD200R1 and its implications in PD.MethodsThe CD200R1 promoter core region was identified via luciferase assays. Potential transcription factors were predicted using the UCSC ChIP-seq database and JASPAR. NFKB1 binding to the CD200R1 core promoter was substantiated through electrophoretic mobility shift and chromatin immunoprecipitation assays. Knocking-down or overexpressing NFKB1 validated its regulatory effect on CD200R1. Correlation between decreased CD200R1 and deficient NFKB1 was studied using Genotype-Tissue Expression database. The clinical samples of the peripheral blood mononuclear cells were acquired from 44 PD patients (mean age 64.13 ± 9.78, 43.2% male, median Hoehn-Yahr stage 1.77) and 45 controls (mean age 64.70 ± 9.41, 52.1% male). NFKB1 knockout mice were utilized to study the impact of NFKB1 on CD200R1 expression and to assess their roles in PD pathophysiology.ResultsThe study identified the CD200R1 core promoter region, located 482 to 146 bp upstream of its translation initiation site, was directly regulated by NFKB1. Significant correlation between NFKB1 and CD200R1 expression was observed in human PMBCs. Both NFKB1 and CD200R1 were significantly decreased in PD patient samples. Furthermore, NFKB1-/- mice exhibited exacerbated microglia activation and dopaminergic neuron loss after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatment.ConclusionOur study identified that NFKB1 served as a direct regulator of CD200R1. Reduced NFKB1 played a critical role in CD200R1 dysregulation and subsequent microglia overactivation in PD. These findings provide evidence that targeting the NFKB1-CD200R1 axis would be a novel therapeutic strategy for PD.

Screening of potential targets and small-molecule drugs related to lipid metabolism in ovarian cancer based on bioinformatics

Backgroundabout 70 % of ovarian cancer (OC) patients with postoperative chemotherapy relapse within 2–3 years due to drug resistance and metastasis, and the 5-year survival rate is only about 30 %. Lipid metabolism plays an important role in OC. We try to explore the potential targets and drugs related to lipid metabolism to provide clues for the treatment of OC. Methodsthe gene expression profiles of OC and normal ovarian tissue samples were obtained from the cancer genome atlas (TCGA) and genotype-tissue expression databases (GTEx). The differentially expressed genes (DEGs) were analyzed. Lipid metabolism related genes (LMRGs) were downloaded from MSigDB database. The DEGs related to lipid metabolism in OC was obtained by intersection. And gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses were performed. The protein-protein interaction (PPI) network of lipid metabolism related DEGs was constructed, and seven algorithms were used to screen core potential target genes. Its expression in OC and prognostic ability were analyzed by Univariate Cox. Cmap database mining OC lipid metabolism related potential small-molecular drugs and docking. CCK8, scratch assay, transwell test and free fatty acid (FFA) assay, fluorescence detection of cellular fatty acid uptake, and the reactivity assay of CPT1A were used to detect the biological effects of drugs on OC cell.Rreverse transcription PCR(RT-qPCR) and WesternBlot were performed to measure the expression of core targets. Results437 DEGs related to lipid metabolism of OC were screened. GO and KEGG analysis showed that these DEGs were lipid metabolism, fatty acid metabolism, sphingolipid metabolism, PPAR signal pathway and so on. The PPI network based on lipid metabolism DEGs consists of 301 nodes and 1107 interaction pairs, and 6 core target genes were screened. ROC curve analysis showed that all of the 6 genes could predict the prognosis of OC. Three small molecular drugs Cephaeline, AZD8055 and GSK-1059615 were found by cmap and molecular docking showed that they all had good binding ability to target gene. Cephaeline has the strongest inhibitory effect on SKOV3 cells of OC, and could significantly inhibit cell migration and invasion regulate the mRNA and protein expression of some targets, and inhibit lipid metabolism process in ovarian cancer cells. Conclusionsix OC potential genes related to lipid metabolism were identified and verified, which can be used as potential biomarkers and therapeutic targets to evaluate the prognostic risk of OC patients. In addition, three small-molecular drugs that may be effective in the treatment of OC were unearthed, among which Cephaeline has the most potential. We speculate that Cephaeline may target six genes to inhibit progression of OC by affecting lipid metabolism.

TCF4 as a potential prognostic biomarker and an anticancer target in gastric cancer.

Lymphoid enhancer-binding factor 1 (LEF1)/T cell factor (TCF) family members are key transcription factors in malignant tumors. In this study, the role of T cell factor 4 (TCF4) in the progression of gastric cancer (GC) cell migration and invasion was investigated. Fifty-five pairs of GC tissues and adjacent non-tumor tissues were collected for evaluating the expression of LEF1/TCF family members, which were also evaluated by the Gene Expression Profiling Interactive Analysis (GEPIA) database, an online analysis platform based on The Cancer Genome Atlas and Genotype-Tissue Expression databases. Through GEPIA online analysis and our experimental specimens, we found that TCF4 messenger RNA (mRNA) expression was significantly upregulated in GC tissues compared with normal non-tumor tissues. The findings from protein-protein interaction (PPI) analysis suggested that myocyte enhancer factor 2C (MEF2C) may function as a regulatory gene for TCF4 and play a role in the progression of GC. A significant increase in TCF4 mRNA expression was observed in the GC cell lines. Silencing of TCF4 led to significant inhibition of the proliferation, migration, and invasion of the MGC-803 and SGC-7901 cells. TdT-mediated dUTP nick end labeling (TUNEL)-positive staining cells were significantly increased after transfection with TCF4 small interfering (si)-RNA into GC cells. In addition, patients with GC with high TCF4 expression were associated with poor T stage, pathologic stages, histologic grade, overall survival, and recurrence-free survival, indicating that TCF4 may be a potential prognostic marker of GC. TCF4 potentially exerts a carcinogenic role in the progression of GC. TCF4 may serve as a prognostic indicator and therapeutic target for GC.

Ferroptosis-Related Gene Signature for Prognosis Prediction in Acute Myeloid Leukemia and Potential Therapeutic Options.

Limited data were available to understand the significance of ferroptosis in leukemia prognosis, regardless of the genomic background. RNA-seq data from 151 AML patients were analyzed from The Cancer Genome Atlas (TCGA) database, along with 70 healthy samples from the Genotype-Tissue Expression (GTEx) database. Ferroptosis-related genes (FRGs) features were constructed by multivariate COX regression analysis and risk scores were calculated for each sample and a novel prediction model was identified. The validation was carried out using data from 35 AML patients and 13 healthy controls in our cohort. Drug sensitivity analysis was conducted on various chemotherapeutic drugs. A signature of 10 FRGs was identified, as prognostic predictors for AML, and the risk scores were calculated to constructed the prognostic features of FRGs. Significantly lower overall survival was observed in the high-risk group. The predictive ability of these features for AML prognosis was confirmed using Cox regression analysis, ROC curves, and DCA. The prediction model performed well in our clinical practices, and had its potential superiority when comparing to classical NCCN risk stratification. Multiple chemotherapy drugs, including paclitaxel, dactinomycin, cisplatin, etc. had a lower IC50 in FRGs high-risk group than low-risk group. The AML prognosis model based on FRGs accurately predicts AML prognosis and drug sensitivity, and the drugs identified worthy further investigation.

FN1, a reliable prognostic biomarker for thyroid cancer, is associated with tumor immunity and an unfavorable prognosis.

Thyroid cancer (THCA) is a malignant tumor that affects the endocrine system. At present, an effective treatment for THCA remains elusive, particularly for medullary carcinoma and undifferentiated carcinoma, due to the lack of suitable medications and prognostic markers. Patient RNA-sequencing and clinical data were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Protein-protein interaction analyses were performed for differentially expressed genes related to THCA. Moreover, the associations between fibronectin 1 (FN1), clinical data, immune checkpoint genes and immune cell infiltration was assessed. The potential functional role of the FN1 gene was evaluated through gene set enrichment analysis. Immunohistochemistry was used to assess FN1 expression in 103 cases of THCA, comprising 32 with papillary carcinoma, 30 with follicular carcinoma, 35 with medullary carcinoma and 6 with undifferentiated carcinoma. Finally, 11 co-expression modules were constructed and the expression of five identified hub genes (FN1, mucin-1, keratin 19, intracellular adhesion molecule 1 and neural cell adhesion molecule) were evaluated. The results demonstrated that higher FN1 gene expression levels were strongly associated with a higher pathologic stage and tumor stage, and were significantly associated with immune cell infiltration in THCA. Significant increases in FN1 protein expression levels were noted among patients diagnosed with four types of THCA, comprising papillary carcinoma, follicular carcinoma, medullary carcinoma and undifferentiated carcinoma. Patients diagnosed with medullary carcinoma and undifferentiated carcinoma, and with low FN1 expression levels, exhibited a significant survival advantage compared with those with high FN1 expression levels. In conclusion, the present study identified five hub genes involved in the onset and progression of THCA. Furthermore, FN1 could serve as a candidate biomarker and a therapeutic target for THCA and may be a key gene mediating THCA immune infiltration.

TOX: a potential new immune checkpoint in cancers by pancancer analysis

BackgroundThymocyte selection-associated HMG-BOX (TOX) belongs to a family of transcription factors containing a highly conserved region of the high mobility group box (HMG-Box). A growing body of research has shown that TOX is involved in the occurrence and development of tumors and promotes T-cell exhaustion. We assessed the role of TOX with The Cancer Genome Atlas (TCGA) Pancancer Data.MethodsTOX expression was examined with RNA-seq data from the TCGA and Genotype-Tissue Expression (GTEx) databases. The genetic alteration status and protein level of TOX were analyzed using databases, including the Human Protein Atlas (HPA), GeneCards, and STRING. The prognostic significance was estimated with survival data from the TCGA. Moreover, R software was used for enrichment analysis of TOX. The relationship between TOX and immune cell infiltration was assessed with the Tumor Immune Estimation Resource (TIMER) 2.0 database and the “CIBERSORT” method. The correlation between TOX and immune checkpoints was further explored. Immunohistochemical analysis was used to further verify the difference in TOX expression between cancerous and paracancerous tissues, and cell viability was evaluated using a CCK-8 assay.ResultsIn most cancer types in the TCGA cohort, differential TOX expression was observed. The genetic alteration status and protein level of TOX were examined, and the prognosis of cancers was associated with TOX expression. Moreover, TOX levels were closely related to different immune-related pathways, immune cell infiltration and immune checkpoints. Additionally, significant differences in TOX expression between several cancerous and paracancerous tissues were validated. Furthermore, TOX clearly impacted the viability of cancer cells.ConclusionsTOX, a potential biomarker for cancer, may be involved in the regulation of the immune microenvironment and can be used for new targeted drugs.

Pan-cancer analysis of the role of MPP7 in human tumors

MAGUK p55 subfamily member 7, a part of the membrane palmitoylated protein subfamily, is an essential adapter that promotes epithelial cell polarity and has increasing significance in multiple cancers, including esophageal cancer, clear cell renal cell carcinoma, breast cancer, and pancreatic ductal adenocarcinoma. This paper aims to determine the effect of the MAGUK p55 subfamily member 7 in various tumor types using The Cancer Genome Atlas and Genotype-Tissue Expression database. A variety of software and web platforms, such as cBioPortal, GEPIA2, TIMER2, UALCAN, R, STRING, and DAVID, were used to obtain and analyze data. Notably, low expression of MAGUK p55 subfamily member 7 was observed in most cancers. In addition, low expression of MAGUK p55 subfamily member 7 predicted poor prognoses in cancer patients. Mutation was the most frequent genetic alteration type in MAGUK p55 subfamily member 7, with the phosphorylation sites identified as S412 and S490 in various cancers. Furthermore, expression of MAGUK p55 subfamily member 7 was associated with cancer-related fibroblasts and CD8+ T cells. Gene enrichment analysis indicated that MAGUK p55 subfamily member 7 influences cancer through the Rap1 signaling pathway. This paper elucidates the biological significance of MAGUK p55 subfamily member 7 in human pan-cancer prognosis and immune response.

Pan-cancer analysis of SERPINE1 with a concentration on immune therapeutic and prognostic in gastric cancer.

The serine protease inhibitor clade E member 1 (SERPINE1) is a key modulator of the plasminogen/plasminase system and has been demonstrated to promote tumor progression and metastasis in various tumours. However, although much literature has explored the cancer-promoting mechanism of SERPINE1, the pan-cancer analyses of its predictive value and immune response remain unexplored. The differential expression, and survival analysis of SERPINE1 expression in multiple cancers were analysed using The Cancer Genome Atlasand Genotype-Tissue Expression database. Kaplan-Meier (K-M) plotter and survival data analysis were used to analyze the prognostic value of SERPINE1 expression, including overall survival (OS), disease-specific survival, disease-free interval and progression-free interval and investigated the relationship of SERPINE1 expression with microsatellite instability. We further analysed the correlation between the expression of SERPINE1 and immune infiltration. The Kyoto Encyclopaedia of Genes and Genomes pathway was used for enrichment analysis, and the Gene Set Enrichment Analysis (GSEA) database was used to perform pathway analysis. Finally, invitro experiments demonstrated that knockdown or overexpression of SERPINE1 could alter the proliferation and migration of gastric cancer (GC) cells. The results indicated that SERPINE1 expression levels different significantly between cancer and normal tissues, meanwhile, it was highly expressed in various cancers. By analysing online data, it has been observed that the gene SERPINE1 exhibits heightened expression levels across a variety of human cancers, significantly impacting patient survival rates. Notably, the presence of SERPINE1 was strongly associated with decrease OS and disease-free survival in individuals diagnosed with GC. Furthermore, an observed link indicates that higher levels of SERPINE expression are associated with increased infiltration of immune cells in GC. Finally, invitro experiments showed that knockdown or overexpression of SERPINE1 inhibited the growth, and migration, of GC cells. SERPINE1expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in GC. This study shows that SERPINE1 is an oncogene that participates in regulating the immune infiltration and affecting the prognosis of patients in multiple cancers, especially in GC. These findings underscore the importance of further investigating the role of SERPINE1 in cancer progression and offer a promising direction for the development of new therapeutic strategies.

Pan‑cancer analysis on the role of KMT2C expression in tumor progression and immunotherapy.

Histone lysine N-methyltransferase 2C (KMT2C) is involved in transcriptional regulation and DNA damage repair. Mutations in KMT2C have been implicated in the progression, metastasis, and drug resistance of multiple cancer types. However, the roles of KMT2C in the regulation of tumor prognosis, immune cell infiltration and the immune microenvironment in these multiple cancer types remain unclear. Therefore, in the present study, data from The Cancer Genome Atlas and Genotype-Tissue Expression databases were used for KMT2C expression analyses. Kaplan-Meier and univariate Cox regression analyses were also performed to investigate the prognostic role of KMT2C. In addition, Gene Set Enrichment Analysis (GSEA) was conducted to study the KMT2C-related signaling pathways. Tumor immune estimation resource 2 and single-sample GSEA were conducted to investigate the correlation between KMT2C expression and immune cell infiltrations, and Spearman's analysis was conducted to study the correlations among KMT2C, tumor mutational burden, microsatellite instability, immune regulators, chemokines and immune receptors. Immunohistochemistry of patient kidney tumor samples was performed to verify the correlation between KMT2C and programmed death-ligand 1 (PD-L1) expression. Finally, RNA interference, wound healing and colony formation assays were conducted to evaluate the effects of KMT2C expression on cell proliferation and metastasis. The results of the present study demonstrated that KMT2C was highly expressed in multiple cancer types, was a protective factor in kidney renal clear cell carcinoma and ovarian serous cystadenocarcinoma, and a risk factor for lung squamous cell carcinoma and uveal melanoma. In addition, KMT2C levels were negatively correlated with immune-activated pathways and the infiltration of immune cells, and positively correlated with inhibitory immune factors and tumor angiogenesis. Patients with low KMT2C expression had higher objective response rates to immunotherapy, and drug sensitivity analysis indicated that topoisomerase, histone deacetylase, DOT1-like histone H3K79 methyltransferase and G9A nuclear histone lysine methyltransferase inhibitors could potentially be used to treat tumors with high KMT2C expression levels. Finally, the KMT2C and PD-L1 expression levels were shown to be positively correlated, and KMT2C knockdown markedly promoted the proliferation and invasion capacities of A549 cells. In conclusion, the present study revealed that low KMT2C expression may be a promising biomarker for predicting the response of patients with cancer to immunotherapy. Conversely, high KMT2C expression was shown to promote tumor angiogenesis, which may contribute to the formation of the immunosuppressive tumor microenvironment.

Comprehensive analysis of PSMG3 in pan-cancer and validation of its role in hepatocellular carcinoma.

Proteasome assembly chaperone 3 (PSMG3), a subunit of proteasome, has been found to be associated with lung cancer. However, the role of PSMG3 in other cancers has not been elucidated. The objective of this study was to explore the immune role of PSMG3 in pan-cancer and confirm the oncogenic significance in liver hepatocellular carcinoma (LIHC). We examined the differential expression of PSMG3 across various cancer types using data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. We investigated the prognostic value of PSMG3 and examined its relationship with tumor mutation burden (TMB), microsatellite instability (MSI), and immune infiltration. The functional enrichment analysis was performed to explore the potential molecular mechanism of PSMG3. To elucidate the biological function of PSMG3, we conducted in vitro experiments using liver cancer cell lines. PSMG3 was highly expressed in most cancers. The high PSMG3 expression value of PSMG3 was closely related to poor prognosis. We observed correlations between PSMG3 and TMB, and MSI immune infiltration. PSMG3 may be involved in metabolic reprogramming, cell cycle, and PPAR pathways. The over-expression of PSMG3 promoted the proliferation, migration, and invasion capabilities of liver cancer cells. Our study demonstrated that PSMG3 was a pivotal oncogene in multiple cancers. PSMG3 contributed to the progression and immune infiltration in pan-cancer, especially in LIHC.

P-707 Discovery of novel serum biomarkers for premature ovarian insufficiency through machine-learning bioinformatic analysis

Abstract Study question Can we develop predictive, practical biomarkers for premature ovarian insufficiency (POI) from normal ovaries and human blood, tested and validated by machine-learning (ML) algorithm? Summary answer Applying random forest and XGBoost algorithms, we pinpointed 60 significant genes from ovarian tissues; transcriptome analysis identified RPM1 as the most significant biomarker. What is known already Accelerated ovarian aging has been suggested as one of the possible underlying mechanisms of POI; previous literature has focused on identifying its cause in genetic realm, commonly adopting first-generation sequencing (Sanger) and next-generation sequencing (NGS). However, such powerful tools are still limited in accurately depicting the complete transcript information of ovarian tissue. Moreover, theoretical value of such disease-predictive gene candidates needs to be validated using human tissues and blood, and finally, underlying mechanisms should be confirmed with ideal animal model and cell line. Study design, size, duration To overcome the existing limitations and maximize clinical relevance of disease-predictive gene analysis and theoretical biomarker exploration, the current study incorporated the transcriptome expression data from both young and old ovaries obtained from the Genotype-Tissue Expression (GTEx) database. Using supervised machine learning techniques, potential marker genes were identified, and a meaningful predictive index was subsequently developed using human plasma samples of control and POI women with and without pregnancy history. Participants/materials, setting, methods The performance evaluation of two ML models were achieved using the area under receiver operating characteristic curve (AUROC), accuracy, kappa, and F1 score, among various age groups. The expression profiles of final candidate marker genes were analyzed within the GTEx datasets, in relation to their correlation pattern with age. Finally, the potential transcriptome biomarkers were quantitatively evaluated using human blood samples from 92 controls and 108 POI women visiting a tertiary center in 2023. Main results and the role of chance We found 41 significant genes using the random forest algorithm and 19 significant genes using the XGboost algorithm. We then tested the ML-characterized 7 final candidate biomarkers in human blood samples (all p &amp;lt; 0.05). The AUROC and interventional predictive index results demonstrated the potential of RPM1 as a predictive marker with AUROC of 0.784, comparable to the AUROC of anti-mullerian hormone (AMH) as 0.659 and inhibin B (INHB) as 0.646. Limitations, reasons for caution To avoid potential biases, RPMs should be tested in a larger, multinational cohort with different genetic and geographic backgrounds, possibly incorporating Mendelian randomization method to estimate the causal effect of RPMs on POI. Finally, to ultimately confirm their therapeutic potential, preclinical studies should be considered using RPM recombinant proteins. Wider implications of the findings Our results proposed that predictive biomarkers for POI could be associated with premature, accelerated ovarian aging of the disease mechanism, and these biomarkers can be developed as evaluation metrics for the efficacy, progress, and prognosis of interventions and treatment modalities assigned to POI women seeking fertility. Trial registration number 202302240001

Systematic analysis of TREM2 and its carcinogenesis in pancreatic cancer.

Triggering receptor expressed on myeloid cells 2 (TREM2), a transmembrane immunoglobulin-superfamily receptor, is expressed primarily on cells such as macrophages and dendritic cells. TREM2 has been shown to be associated with diseases such as neurodegeneration, fatty liver, obesity, and atherosclerosis. Currently, it has become one of the hotspots in oncology research. However, the role of TREM2 in pan-cancer, especially pancreatic cancer, remains unclear. We used the Tumor-immune System Interactions Database (TISIDB) to explore TREM2 expression differences, Tumor Immune Single-cell Hub 2 (TISCH2) to explore TREM2 expression distribution, Tumor IMmune Estimation Resource 2.0 (TIMER 2.0) to explore immune infiltration, cBio Cancer Genomics Portal (cBioPortal) to explore genetic variation, Genomics of Drug Sensitivity in Cancer (GDSC) to explore drug resistance, and Kaplan-Meier plotter database to explore the relationship between TREM2 and prognosis in pancreatic cancer. In addition, we used The Cancer Genome Atlas-pancreatic adenocarcinoma (TCGA-PAAD) and normal pancreas samples from the Genotype-Tissue Expression (GTEx) databases to explore the relationship between TREM2 and lymph node metastasis. We verified the protein level of TREM2 in pancreatic cancer by Human Protein Atlas (HPA) and western blotting and detected the colocalization of TREM2 with malignant cell markers by multiplex immunohistochemistry (mIHC). Finally, we identified the tumor-promoting role of TREM2 in pancreatic cancer via in vitro experiments, such as cell cycle assays, colony formation assays, and transwell migration and invasion assays. Our results showed that TREM2 was differentially expressed in various tumors according to different molecular and immune subtypes of pan-cancer. It was found that TREM2 was mainly expressed in monocytes/macrophages. In addition, our study showed that TREM2 expression was closely associated with macrophages in the tumor microenvironment (TME) of pan-cancer. TREM2 was shown to be related to anti-inflammatory and immunosuppressive effects in most cancers. Furthermore, we found that amplification was the main somatic mutation of TREM2 in pan-cancer. Further correlational analysis revealed a significant negative association of TREM2 expression with sensitivity to AZD8186, which is a selective inhibitor of PI3K, but not gemcitabine and paclitaxel. Finally, through the knockdown and overexpression of TREM2, our findings verified that TREM2 on cancer cells promoted the progression of PAAD. In conclusion, our comprehensive analysis identified that TREM2 expression level was correlated with the TME and the immunosuppressive effects. In particular, our study indicated that TREM2 was involved in the progression of pancreatic cancer.

Pan-cancer analysis of the prognostic and immunological role of RPL4

Ribosomal proteins (RPs) play an important role in the overall stability, function, and integrity of ribosomes. Ribosomal protein L4 (RPL4), which is encoded by RPL4, is assumed to play different roles in different cancers due to the strong correlation between them. However, research based on the underlying mechanisms of this correlations is limited. Therefore, this study investigated the biological role of RPL4 in various cancers. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to compare the differential expression of RPL4 in tumor and normal tissues. The Sangerbox database and Kaplan–Meier method were employed to assess RPL4's impact on the prognosis of pan-cancer. Analyses using the cBioPortal tool, Shiny Methylation Analysis Resource Tool (SMART), and MethSurv provided insights into the methylation and epigenetic alterations of RPL4. Gene enrichment analysis revealed that RPL4 is involved in ribosome biogenesis through multiple pathways, and its enrichment in signaling pathways directly or indirectly influence tumor development. Tumor Immune Single-cell Hub (TISCH) was used to analyze RPL4 expression levels and cellular functions in the tumor microenvironment. Tumor Immune Estimation Resource Database 2.0 (TIMER2.0) and Tumor-Immune System Interactions Database (TISIDB) tools revealed that RPL4 affected the immune infiltration potential of tumors. Furthermore, the application of the ROC mapper and CellMiner databases indicated an association between RPL4 and sensitivity to multiple antitumor drugs. Additionally, RPL4 was found to remodel the tumor immune microenvironment, leading to the development of chemoresistance. In conclusion, the findings suggest that RPL4 can be used as a potential tumor biomarker and may serve as a target for immunotherapy in various cancers. Genetic testing of RPL4 provides a foundation for the diagnosis, prognosis, and treatment of clinical tumors.

Development and validation of a glioma prognostic model based on telomere-related genes and immune infiltration analysis.

Gliomas are the most prevalent primary brain tumors, and patients typically exhibit poor prognoses. Increasing evidence suggests that telomere maintenance mechanisms play a crucial role in glioma development. However, the prognostic value of telomere-related genes in glioma remains uncertain. This study aimed to construct a prognostic model of telomere-related genes and further elucidate the potential association between the two. We acquired RNA-seq data for low-grade glioma (LGG) and glioblastoma (GBM), along with corresponding clinical information from The Cancer Genome Atlas (TCGA) database, and normal brain tissue data from the Genotype-Tissue Expression (GTEX) database for differential analysis. Telomere-related genes were obtained from TelNet. Initially, we conducted a differential analysis on TCGA and GTEX data to identify differentially expressed telomere-related genes, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on these genes. Subsequently, univariate Cox analysis and log-rank tests were employed to obtain prognosis-related genes. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis were sequentially utilized to construct prognostic models. The model's robustness was demonstrated using receiver operating characteristic (ROC) curve analysis, and multivariate Cox regression of risk scores for clinical characteristics and prognostic models were calculated to assess independent prognostic factors. The aforementioned results were validated using the Chinese Glioma Genome Atlas (CGGA) dataset. Finally, the CIBERSORT algorithm analyzed differences in immune cell infiltration levels between high- and low-risk groups, and candidate genes were validated in the Human Protein Atlas (HPA) database. Differential analysis yielded 496 differentially expressed telomere-related genes. GO and KEGG pathway analyses indicated that these genes were primarily involved in telomere-related biological processes and pathways. Subsequently, a prognostic model comprising ten telomere-related genes was constructed through univariate Cox regression analysis, log-rank test, LASSO regression analysis, and multivariate Cox regression analysis. Patients were stratified into high-risk and low-risk groups based on risk scores. Kaplan-Meier (K-M) survival analysis revealed worse outcomes in the high-risk group compared to the low-risk group, and establishing that this prognostic model was a significant independent prognostic factor for glioma patients. Lastly, immune infiltration analysis was conducted, uncovering notable differences in the proportion of multiple immune cell infiltrations between high- and low-risk groups, and eight candidate genes were verified in the HPA database. This study successfully constructed a prognostic model of telomere-related genes, which can more accurately predict glioma patient prognosis, offer potential targets and a theoretical basis for glioma treatment, and serve as a reference for immunotherapy through immune infiltration analysis.