Santa Cruz Xena Research Articles

Prognostic value and anti-tumor immunity role of TMED9 in pan-cancer: a bioinformatics study.

Transmembrane p24 trafficking protein 9 (TMED9) belongs to the TMED family, and its overexpression frequently induces cancer. Studies have demonstrated the association between the overexpression of TMED9 and cancer development and proliferative migration in cancers such as ovarian cancer, hepatocellular carcinoma, and breast cancer. However, there has been no study investigating the clinical value, biological function, and anti-tumor immune effects of TMED9 from a pan-cancer perspective. The aim of this study is to evaluate the prognostic value and anti-tumor immunity role of TMED9 across pan-cancers. We utilized R language along with The Cancer Genome Atlas (TCGA), UCSC Xena (University of California, Santa Cruz Xena Browser), Human Protein Atlas (HPA), and other datasets to investigate TMED9 expression in various tumors. The association between high TMED9 expression and clinical prognosis and patient survival was examined using the Kaplan-Meier method, log-rank test, as well as univariate and multivariate Cox regression analyses. Tumor Immune Estimation Resource 2.0 (TIMER2.0) and various algorithms were employed to explore the relationship between TMED9 and the tumor microenvironment (TME). Additionally, the biological function of TMED9 in cancer was investigated through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) analyses. TMED9 was over-expressed in the majority of cancers. Patients exhibiting elevated TMED9 expression typically experienced diminished survival rates and unfavorable clinical outcomes. TMED9 played a role as a mediator in the aggressive phenotype of numerous tumors, actively engaging in various biological and signaling pathways linked to cancer development. TMED9 demonstrated the capacity to modulate the anti-tumor immune response in pan-cancer patients, exerting its influence on the infiltration levels of immune cells and cancer-associated fibroblasts (CAFs). TMED9 serves as a novel "cancer indicator" and "clinical prognostic marker", capable of reshaping the TME, impacting the immunotherapeutic response, and guiding precise treatments for cancers to a certain extent.

CD276 as a promising diagnostic and prognostic biomarker for bladder cancer through bioinformatics and clinical research.

To assess CD276 expression and explore its relationship with the clinicopathological characteristics and prognosis of patients with bladder cancer. In total, RNA-sequencing data and clinical profiles of 436 bladder cancer cases from The Cancer Genome Atlas (TCGA) were assessed using the University of California Santa Cruz Xena (UCSC) platform. We compared the CD276 levels in cancerous and adjacent normal tissues and used the R software for statistical association with the clinical stage, grade, and survival (the overall survival, disease-specific survival, and progression-free survival). A single-gene GSEA analysis on TCGA-BLCA data was performed to explore potential pathways through which CD276 might influence bladder cancer. Additionally, CD276 expression was analyzed by comparing data from 9 cancerous tissues and 3 adjacent normal tissues in the GEO dataset GSE7476. Furthermore, we analyzed 133 cancerous bladder and adjacent tissue samples from the Soochow University Hospital, collected between January 1, 2016, and September 30, 2022, to assess the CD276 protein expression using immunohistochemistry. We examined the relationship between tumor CD276 levels and clinical outcomes and prognosis of bladder cancer. Bioinformatic analysis revealed elevated CD276 expression in tumors compared to that in adjacent tissues (p<0.05), correlating with poor survival. GSEA revealed that CD276 was significantly involved in extracellular matrix-related pathways. Immunohistochemistry confirmed CD276 overexpression in tumor tissues, with higher levels linked to advanced pathological grades and worse prognosis. CD276 is markedly upregulated in bladder cancer and associated with severe pathological features, advanced disease, potential for metastasis, and diminished survival rates. It may promote bladder cancer development and progression by influencing extracellular matrix-related-related pathways, making it a viable diagnostic and prognostic biomarker for bladder cancer.

Xenoestrogen and Its Interaction with Human Genes and Cellular Proteins: An In-Silico Study.

Breast cancer represents one of the leading causes of death worldwide. Apart from genetic factors, the sex hormone estrogen plays a pivotal role in breast cancer development. We are exposed to a plethora of estrogen mimics on a daily basis via various routes. Nevertheless, how xenoestrogens, the exogenous estrogen mimics, modulate cancer-associated signaling pathways and interact with specific genes is still underexplored. Hence, this study aims to explore the direct or indirect binding partners of xenoestrogens and their expression upon exposure to these estrogenic compounds. The collection of genes linked to the xenoestrogens Octylphenol, Nonylphenol, Bisphenol-A, and 2,2-bis(4-hydroxyphenyl)-1,1,1-trichloroethane were gathered from the Comparative Toxicogenomics Database. Venny 2.1 was utilized to pinpoint the genes shared by these xenoestrogens. Subsequently, the shared genes underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis using the Database for Annotation, Visualization, and Integrated Discovery bioinformatics resource. A xenoestrogen-protein interaction network was constructed using Search Tool for Interactions of Chemicals. The expressions of common genes were studied with the microarray dataset GSE5200 from the Gene Expression Omnibus database. Also, the expression of a common gene set within different breast cancer subtypes was identified using the University of California, Santa Cruz Xena. The genes linked to xenoestrogens were identified, and 13 genes were found to interact with all four xenoestrogens. Through DAVID analysis, the genes chosen are found to be enriched for various functions and pathways, including pathways in cancer, chemical carcinogenesis-receptor activation, and estrogen signaling pathways. The results of the Comparative Toxicogenomics Database and the chemical-protein interaction network derived from STITCH were similar. Microarray data analysis showed significantly high expression of all 13 genes in another study, with Bisphenol-A and Nonylphenol treated MCF-7 cells, most of the genes are expressed in luminal A or basal breast cancer subtype. In summary, the genes associated with the four xenoestrogens were mostly linked to pathways related to tumorigenesis, and the expression of these genes was found to be higher in breast cancer.

NDC80 Kinetochore Complex Serves as a Potential Prognostic Predictor and Correlates with Immune Infiltrates in Epithelial OvarianCancer Patients.

This study focuses on evaluating the prognostic value of the NDC80 kinetochore complex in ovarian cancer (OC) using the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database and reveals the relationship between the NDC80 complex and immune infiltrates in OC. We collected data on NDC80 complex expression levels in both OC tissues and non-OC ovarian tissues from the University of California Santa Cruz Xena and GEO databases. The clinicopathological characteristics correlated with overall survival were analyzed using Cox regression and the Kaplan-Meier method. Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis and CIBERSORT were performed using data from TCGA database. Immunohistochemical staining was used to verify the higher expression level of NUF2 protein in OC in vitro. Meanwhile, we utilized the Tumor Immune Estimation Resource to analyze the correlation between the NDC80 complex and immunocyte infiltration. The NDC80 complex expression level was prominently higher in OC tissues than in non-OC ovarian tissues and correlated with advanced histologic grade characteristics. Gene expression profiling interactive analysis and the Kaplan-Meier survival curve uncovered a close relationship between high expression of the NDC80 complex and poor overall survival in OC patients. The univariate Cox regression hazard model produced age, pathologic stage, tumor status, primary therapy outcome, SPC24 expression level, and Karnofsky performance score as prognostic factors for OC patients. NDC80 complex expression levels were highly associated with immune cell infiltration, showing NK CD56 bright cells and NK cells with a negative correlation and T helper 2 cells with a positive correlation (P<0.05). These findings provide evidence that an increased expression level of the NDC80 complex is closely associated with the progression of OC and could also serve as a novel target of immunotherapy in OC.

Identification of m6A-associated genes as prognostic and immune-associated biomarkers in Wilms tumor

ObjectivesWilms tumor (WT) is a common renal malignant tumor in children. We aimed to investigate the potential prognostic value of m6A-related genes and their relationship to the immune microenvironment in WT.MethodsRNA-seq data and clinical information from 121 WT and 6 normal samples were obtained from the University of California Santa Cruz Xena database. We used various bioinformatics analysis tools to analyze these data and verify the expression level of m6A-related genes by experiments.ResultsFour m6A-related genes were successfully screened, including ADGRG2, CPD, CTHRC1, and LRTM2. Kaplan–Meier survival curves showed that the four genes were closely related to the prognosis of WT, which was also confirmed by receiver operator characteristic curves. Subsequently, in the immune microenvironment of WT, we discovered that Th1_cells were positively correlated with ADGRG2, CCR was negatively correlated with CPD, CCR was positively correlated with CTHRC1, APC_co_stimulation, CCR, Macrophages, inflammation-promoting cells, Treg, and Type_II_IFN_Reponse were negatively correlated with LRTM2. Finally, qRT-PCR showed that expression levels of the four genes were upregulated in the nephroblastoma cell lines (G-401, SK-NEP-1, and WT-CLS1) compared with the human embryonic kidney cell lines (293T).ConclusionsTaken together, our study first time screened the m6A-related genes and revealed that ADGRG2, CPD, CTHRC1, and LRTM2 are the prognostic and immune-associated biomarkers in WT.

Utility of G protein-coupled oestrogen receptor 1 as a biomarker for pan-cancer diagnosis, prognosis and immune infiltration: a comprehensive bioinformatics analysis.

The G protein-coupled oestrogen receptor (GPER) 1 mediates non-genomic oestrogen-related signalling and plays an important role in the regulation of cell growth and programmed cell death through multiple downstream pathways. Despite the increasing interest in the role of GPER1 in cancer development, no pan-cancer analysis has been available for GPER1. In this study we performed a comprehensive analysis of the role of GPER1 in pan-cancer via Human Protein Atlas (HPA), The Cancer Genome Atlas (TCGA), University of California, Santa Cruz Xena (UCSC XENA), Genotype-Tissue Expression (GTEx), MethSurv, The University of Alabama at Birmingham CANcer data analysis Portal (UALCAN), cBioPortal, STRING and TISIDB detabases, followed by enrichment analysis using R software. GPER1 was widely expressed in tissues and organs and differed in expression from normal tissue in a variety of cancers. In diagnostic assessment, it's Area Under the Curve (AUC) surpassed 0.9 in nine cancer types. Survival analysis showed that GPER1 was correlated with the prognosis of 11 cancer types. Moreover, GPER1 expression was associated with immune infiltration in multiple cancers. In summary, GPER1 has good diagnostic or prognostic value across various malignancies. Together with its extensive correlation with immune components, the aforementioned results suggests that GPER1 shows promise in tumour diagnosis and prognosis, providing new ideas for precise and personalised anti-tumour strategies.

F-Box and Leucine-Rich Repeat Protein 7 Is a Prognostic Biomarker and Is Correlated with the Immunosuppressive Microenvironment in Colorectal Cancer.

Background: Colorectal cancer (CRC) is a common malignancy of the digestive system, but its specific mechanisms of occurrence and development remain incompletely understood. F-Box and leucine-rich repeat protein 7 (FBXL7) is a subunit of the Skp-cullin-F-box ubiquitin ligase, involved in cell cycle regulation, endothelial cell damage, and inflammatory immunological responses. However, the role of FBXL7 in CRC remains unknown. In this study, we investigated the clinical significance and potential mechanism of FBXL7 expression in CRC progression. Methods: We utilized data from The Cancer Genome Atlas (TCGA) and the University of California Santa Cruz Xena (UCSC Xena) database for bioinformatic analyses. Clinical CRC samples were used to confirm FBXL7 expression. Gene set enrichment analysis (GSEA) and various databases, such as TCGA, UCSC Xena, cBioPortal, University of ALabama at Birmingham CANcer data analysis portal, MethSurv, Tumor Immune Estimation Resource (TIMER), TIMER2.0, Tumor-Immune System Interaction Database, and Tumor Immune Dysfunction and Exclusion Database (TIDB), were used to investigate the role of FBXL7 in CRC. Statistical analysis was performed using R (v.3.6.3) or GraphPad Prism 8.0. Results: Our findings revealed the predictive significance of FBXL7 in CRC patients. FBXL7 expression was associated with tumor stage, lymph node stage, pathological stage, perineural invasion, and lymphatic invasion. GSEA analysis identified associations between FBXL7 and extracellular matrix organization, as well as immune-related pathways. Immunological analysis revealed a correlation between high FBXL7 expression and the development of an immunosuppressive microenvironment. Conclusion: Identifying FBXL7 as a novel biomarker for CRC could shed light on the promotion of CRC development by the immune environment.

Decreased Expression of GLYATL1 Predicts Poor Prognosis in Patients with Clear Cell Renal Cell Carcinoma.

GLYATL1 is a member of the glycine-N-acyltransferase family, which catalyses acyl group transfer. The role of GLYATL1 in cancer is largely unknown; therefore, the potential value of GLYATL1 in clear cell renal cell carcinoma (ccRCC) was explored. The ccRCC gene expression profiles and clinical data were obtained from the University of California Santa Cruz Xena platform. Differential expression and survival analysis were performed using R software. Samples from the TIMER public database and real-world were used for validation. The potential molecular mechanism of GLYATL1 in ccRCC was explored using gene set enrichment analysis (GSEA). GLYATL1 was downregulated, indicating a poor prognosis in ccRCC. Low expression of GLYATL1 was significantly associated with advanced stage and higher histological grade ccRCC. The differential expression of GLYATL1 was validated at the protein level using clinical samples and tissue microarray. The results of GSEA showed that multiple crucial signalling pathways including fatty acid metabolism, adipogenesis, oxidative phosphorylation and epithelial-mesenchymal transition were enriched. This study demonstrated that GLYATL1 downregulation has an unfavourable impact on the survival of patients with ccRCC. The resulting data indicated that GLYATL1 could be a potential new target for ccRCC therapy, which may be helpful for the personalized treatment of such individuals.

Prognostic significance of LRRC1 in hepatocellular carcinoma and construction of relevant prognostic model.

This study aimed to elucidate the prognostic value of the leucine rich repeat containing 1 (LRRC1) gene in hepatocellular carcinoma (HCC) and to determine the effects of high and low LRRC1 expression on mutation and immune cell infiltration. We downloaded HCC mRNA-seq expression and clinical data from University of California Santa Cruz Xena. The expression of LRRC1 was compared between HCC tumor and normal samples. Tumor samples were divided according to high and low LRRC1 expression. Differentially expressed genes between the 2 groups were identified, and function, mutation, and immune cell infiltration were analyzed. Genes associated with immune cells were identified using weighted gene co-expression network analysis, and transcription factors of these genes were predicted. Moreover, a prognostic model was developed and its performance was evaluated. The expression of LRRC1 was upregulated in HCC tissues, and this indicated a poor prognosis for patients with HCC. Differentially expressed genes between high and low LRRC1 expression were significantly enriched in pathways associated with cancer, amino acid metabolism, carbohydrate metabolism, and the immune system. We identified 15 differentially infiltrated immune cells between tumors with high and low LRRC1 expression and 14 of them correlated with LRRC1 gene expression. Weighted gene co-expression network analysis identified 83 immune cell-related genes, 27 of which had prognostic value. Cyclic AMP-response element binding protein regulated annexin A5, matrix metallopeptidase 9, and LRRC1 in the transcription factor regulatory network. Finally, a prognostic model composed of 7 genes were generated, which could accurately predict the prognosis of HCC patients. The LRRC1 gene might serve as a potential immune-associated prognostic biomarker for HCC.

Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

BackgroundBoth N6-methyladenosine (m6A) and ferroptosis-related genes are associated with the prognosis of lung adenocarcinoma. However, the predictive value of m6A-related ferroptosis genes remains unclear. Here, we aimed to identify the prognostic value of m6A-related ferroptosis genes in lung adenocarcinoma.MethodsLung adenocarcinoma sample data were downloaded from the University of California Santa Cruz Xena and Gene Expression Omnibus databases. Spearman’s correlation analysis was used to screen for m6A-related ferroptosis genes. Univariate Cox regression, Kaplan–Meier, and Lasso analyses were conducted to identify prognostic m6A-related ferroptosis genes, and stepwise regression was used to construct a prognostic gene signature. The predictive value of the gene signature was assessed using a multivariate Cox analysis. In the validation cohort, survival analysis was performed to verify gene signature stability. The training cohort was divided into high- and low-risk groups according to the median risk score to assess differences between the two groups in terms of gene set variation analysis, somatic mutations, and tumor immune infiltration cells.ResultsSix m6A-related ferroptosis genes were used to construct a gene signature in the training cohort and a multivariate Cox analysis was conducted to determine the independent prognostic value of these genes in lung adenocarcinoma. In the validation cohort, Kaplan–Meier and receiver operating characteristic analyses confirmed the strong predictive power of this signature for the prognosis of lung adenocarcinoma. Gene set variation analysis showed that the low-risk group was mainly related to immunity, and the high-risk group was mainly related to DNA replication. Somatic mutation analysis revealed that the TP53 gene had the highest mutation rate in the high-risk group. Tumor immune infiltration cell analysis showed that the low-risk group had higher levels of resting CD4 memory T cells and lower levels of M0 macrophages.ConclusionOur study identified a novel m6A-related ferroptosis-associated six-gene signature (comprising SLC2A1, HERPUD1, EIF2S1, ACSL3, NCOA4, and CISD1) for predicting lung adenocarcinoma prognosis, yielding a useful prognostic biomarker and potential therapeutic target.

Aquaporin-4 as a New Potential Molecular Biomarker for Prognosis of Low-Grade Glioma: Comprehensive Analysis Based on Online Platforms

Aquaporin-4 (AQP4) is a significant factor in transcellular and transepithelial water movement, and abnormal expression of AQP4 has been detected in many types of tumors. The purpose of this study was to explore its role in low-grade gliomas (LGG) using freely available online bioinformatics tools. OncoLnc database was used to analyze Cox coefficients and compare AQP4 expression between various types of tumors; Tumor Immune Estimation Resource database and Gene Expression Profiling Interactive Analysis were used to compare gene expression between LGG and normal tissues; University of California Santa Cruz Xena browser generated Kaplan-Meier survival curves in the LGG cohort in The Cancer Genome Atlas and subgroups; LinkedOmics database screened the most relevant genes based on Pearson correlation coefficient; Gene Ontology Biological Process and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed through gene set enrichment analysis to explore possible molecular mechanisms. LGG had higher AQP4 expression compared with normal tissues and ranked first among 21 different types of cancer (P < 0.05). The oligodendroglioma group had the lowest AQP4 expression and the longest overall survival (OS) (P < 0.05). LGG with astrocytoma, isocitrate dehydrogenase mutation, or 1p/19q codeletion had lower AQP4 expression and longer OS (P < 0.001). LGG with lower AQP4 expression, without 1p/19q codeletion, without chemotherapy, and with or without radiation therapy had longer OS (P < 0.05). AQP4 and coexpressed genes were involved in complex biological processes in LGG, including regulation of neurotransmitter level, peroxisome proliferator-activated receptor signaling pathway, cell adhesion molecules, and others. AQP4 is a prognostic marker in LGG and its subgroups. Patients with lower AQP4 expression may have longer OS.

Downregulation of Crystallin Lambda 1 is a New Independent Prognostic Marker in Clear Cell Renal Cell Carcinoma.

BackgroundClear cell renal cell carcinoma (ccRCC), the most prevalent kidney cancer subtype, has a high mortality rate. Crystallin lambda 1 (CRYL1) encodes an enzyme that catalyzes the dehydrogenation of L-gulonate into dehydro-L-gulonate in uronate cycle. CRYL1 dysregulation has been linked to the progression of several cancers. This research aimed to evaluate the prognostic significance of CRYL1 expression in ccRCC prognosis.MethodsClinical data and gene expression profiles on ccRCC were retrieved from the University of California Santa Cruz Xena platform. Differences (variations) in the expression profiles of CRYL1 in ccRCC and healthy tissues were found using RNA-sequencing data, and these findings were validated using qPCR with real-world samples. CRYL1 expression levels were also linked to clinicopathological characteristics, survival, and immune microenvironments. The potential pathway via which CRYL1 expression levels impact the prognosis of patients with ccRCC was investigated using gene set enrichment analysis (GSEA).ResultsIn ccRCC tissues, CRYL1 expression levels were lower compared to healthy renal tissues in TCGA cohort (n = 535, P < 0.001), which was validated in another real-world cohort (n = 14, P < 0.001). Lower CRYL1 expression levels were linked to unfavorable clinicopathological characteristics and prognoses (P < 0.001). According to multivariate Cox regression analysis (P < 0.001), CRYL1 expression levels in patients with ccRCC could serve as an independent prognostic indicator. Furthermore, a strong link between CRYL1 expression levels and immune microenvironment was observed (P < 0.001). Finally, GSEA revealed that CRYL1 expression levels (P < 0.001) were associated with fatty acid metabolism, G2M checkpoint delays, and epithelial-mesenchymal transitions in ccRCC.ConclusionOur study found that lower levels of CRYL1 expression were linked to unfavorable clinicopathological characteristics and worse prognoses, and CRYL1 could serve as a new target for the treatment of ccRCC, which is useful for personalized medicine.

Clinical significance and oncogenic function of NR1H4 in clear cell renal cell carcinoma

BackgroundNuclear receptor subfamily 1 group H member 4 (NR1H4) have been reported in various cancer types, however, little is known about the clinical values and biological function in clear cell Renal cell carcinoma (ccRCC).MethodsThe expression pattens of NR1H4 in ccRCC were investigated in clinical specimens, cell lines and publicly‑available databases. Cell Counting Kit-8 (CCK-8), colony formation, 5-ethynyl-2' -deoxyuridine (EdU), transwell and cell wound healing assays were performed to assess the biological functions of NR1H4 in 786-O ccRCC cells. Gene set enrichment analysis (GSEA), Flow Cytometry, quantitative real‐time PCR (qRT-PCR), western blot and immunofluorescence were performed to explore the molecular mechanism of NR1H4 in ccRCC. We explored the early diagnostic value, prognostic value, genetic mutation and DNA methylation of NR1H4 by a comprehensive bioinformatics analysis based on the data published in the following databases: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Kaplan‐Meier Plotter, Gene Expression Profiling Interactive Analysis (GEPIA), UNIVERSITY OF CALIFORNIA SANTA CRUZ Xena (UCSC Xena), cBio Cancer Genomics Portal, MethSurv, SurvivalMeth and The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN). Its correlation with tumor-infiltrating immune cells in ccRCC was analyzed by Tumor Immune Estimation Resource 2.0 (TIMER2.0) and Tumor Immune System Interactions Database (TISIDB).ResultsIn this study, NR1H4 was found to be highly expressed in ccRCC tissues and ccRCC cell lines. Knockdown of NR1H4 significantly suppressed cancer cell proliferation, migration and invasion. Mechanistically, tumor‐associated signaling pathways were enriched in the NR1H4 overexpression group and si-NR1H4 could induce the downregulation of Cyclin E2 (CCNE2). By bioinformatics analysis, NR1H4 was identified as highly expressed in stage I ccRCC with a high diagnostic accuracy (area under the receiver operating characteristic curve > 0.8). Genetic alteration and DNA methylation of NR1H4 were significantly associated with prognosis in ccRCC patients. Moreover, NR1H4 expression associated with immune cell infiltration levels in ccRCC, which provides a new idea for immunotherapy.ConclusionsOur study indicated that NR1H4 might be a potential tumor biomarker and therapeutic target for ccRCC which could promote cancer cell proliferation, migration and invasion via regulating CCNE2.

Signature based on RNA-binding protein-related genes for predicting prognosis and guiding therapy in non-small cell lung cancer.

Background: Studies have reported that RNA-binding proteins (RBPs) are dysregulated in multiple cancers and are correlated with the progression and prognosis of disease. However, the functions of RBPs in non-small cell lung cancer (NSCLC) remain unclear. The present study aimed to explore the function of RBPs in NSCLC and their prognostic and therapeutic value. Methods: The mRNA expression profiles, DNA methylation data, gene mutation data, copy number variation data, and corresponding clinical information on NSCLC were downloaded from The Cancer Genome Atlas, Gene Expression Omnibus, and the University of California Santa Cruz Xena databases. The differentially expressed RBPs were identified between tumor and control tissues, and the expression and prognostic value of these RBPs were systemically investigated by bioinformatics analysis. A quantitative polymerase chain reaction (qPCR) was performed to validate the dysregulated genes in the prognostic signature. Results: A prognostic RBP-related signature was successfully constructed based on eight RBPs represented as a risk score using least absolute shrinkage and selection operator (LASSO) regression analysis. The high-risk group had a worse overall survival (OS) probability than the low-risk group (p < 0.001) with 1-, 3-, and 5-year area under the receiver operator characteristic curve values of 0.671, 0.638, and 0.637, respectively. The risk score was associated with the stage of disease (p < 0.05) and was an independent prognostic factor for NSCLC when adjusted for age and UICC stage (p < 0.001, hazard ratio (HR): 1.888). The constructed nomogram showed a good predictive value. The P53, focal adhesion, and NOD-like receptor signaling pathways were the primary pathways in the high-risk group (adjusted p value <0.05). The high-risk group was correlated with increased immune infiltration (p < 0.05), upregulated relative expression levels of programmed cell death 1 (PD1) (p = 0.015), cytotoxic T-lymphocyte-associated protein 4 (CTLA4) (p = 0.042), higher gene mutation frequency, higher tumor mutational burden (p = 0.034), and better chemotherapy response (p < 0.001). The signature was successfully validated using the GSE26939, GSE31210, GSE30219, and GSE157009 datasets. Dysregulation of these genes in patients with NSCLC was confirmed using the qPCR in an independent cohort (p < 0.05). Conclusion: An RBP-related signature was successfully constructed to predict prognosis in NSCLC, functioning as a reference for individualized therapy, including immunotherapy and chemotherapy.

Comprehensive Analysis of the Relationship between m6A Methylation Patterns and Immune Microenvironment in Lung Adenocarcinoma

背景与目的m6A RNA甲基化修饰在肺癌的发生与进展中起着重要作用，可以调节肿瘤免疫进而影响疾病预后。目前很多集中在某些特定的m6A效应器的差异表达及对肿瘤免疫细胞浸润的影响，但单个效应器表达的变化远远不足以反映m6A修饰特征的全貌，且关于m6A修饰对肺腺癌免疫微环境影响的研究仍较少。本研究拟探讨不同m6A修饰模式对肺腺癌中免疫微环境的影响。方法从癌症基因组图谱数据库（The Cancer Genome Atlas, TCGA）、加州大学圣克鲁兹分校泛癌全基因数据分析工具数据库（University of California Santa Cruz Xena, UCSC Xena）、基因表达综合数据库（Gene Expression Omnibus, GEO）获取肺腺癌相关数据信息。使用Maftools R分析肺腺癌队列中24个m6A效应器的基因突变，比较肺腺癌组织和正常组织中m6A效应器的表达差异，并通过Cox回归分析进行生存分析。通过Consensus Cluster Plus R非监督聚类的方法构建m6A修饰模式，进行m6A聚类生存分析、GSVA通路富集分析、免疫评分及免疫细胞浸润分析。在68例肺腺癌组织中，通过免疫组化分析LRPPRC蛋白表达水平与CD8、CD68的表达水平，验证LRPPRC与CD8+细胞毒性T细胞及巨噬细胞浸润的关系。结果在567例肺腺癌样本中有150例发生了m6A效应器突变，频率为26.46%。与正常组织相比，肺腺癌组织中共有6个读取器和3个写入器的表达明显上调。IGF2BP1和HNRNPC是影响肺腺癌患者预后的独立危险因素，且各效应器之间也存在大量的相互作用。构建了3种具有不同免疫细胞浸润特征和临床预后的m6A修饰模式。发现LRPPRC的表达与包括杀伤性T细胞和巨噬细胞在内的多种免疫细胞的浸润呈负相关，并在68例肺腺癌组织中得到验证。结论m6A修饰对肺腺癌免疫微环境的调节起着重要作用，LRPPRC有可能作为预测抗PD1免疫治疗效果的潜在生物标记物。

Elevated DLL3 in stomach cancer by tumor-associated macrophages enhances cancer-cell proliferation and cytokine secretion of macrophages.

BackgroundThe notch signal pathway is important in the development of both tumor-associated macrophages (TAMs) and stomach cancer, but how Notch signaling affects TAMs in stomach cancer is barely understood.MethodsThe expressions of Notch1, Notch2, Notch3, Notch4, hes family bHLH transcription factor 1 (Hes1), and delta-like canonical Notch ligand 3 (DLL3) were detected by Western blot and the expressions of interleukin (IL)-10, IL-12, and IL1-β were detected using enzyme-linked immunosorbent assay after the co-culture of macrophages and stomach-cancer cells. The proliferation and migration of cancer cells were detected using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay and scratch assay, respectively, and the cell cycle was detected using Annexin V/propidium iodide assay. The protein interactions with DLL3 were detected using co-immunoprecipitation and mass spectrometry.ResultsThe co-culture of macrophages and stomach-cancer cells MKN45 and BGC823 could enhance cell proliferation accompanied by the activation of Notch1/Notch2 signaling and upregulation of DLL3. Notch signaling gamma-secretase inhibitor (DAPT) blocked this process. The overexpression of DLL3 in stomach-cancer cells could promote the proliferation of cancer cells, enhance the activation of Notch1/Notch2 signaling, induce the expression of IL-33, lead to the degradation of galectin-3–binding protein (LG3BP) and heat shock cognate 71 kDa protein (HSPA8), and result in elevated IL-1β, IL-12, and IL-10 secretion by macrophages. Higher expression of DLL3 or IL-33 could lead to a lower survival rate based on University of California, Santa Cruz Xena Functional Genomics Explorer and The Cancer Genome Atlas data set.ConclusionsThis is evidence that DLL3 regulates macrophages in stomach cancer, suggesting that DLL3 may be a novel and potential target for stomach-cancer therapy.

New prognostic factors and scoring system for patients with acute myeloid leukemia

Acute myeloid leukemia (AML) is a malignant disease originating from myeloid hematopoietic stem or progenitor cells. It is important to identify molecules associated with the prognosis of AML and conduct an individual risk assessment for different patients. In the present study, the RNA expression profile of 132 patients with AML and 337 healthy individuals were downloaded from the University of California Santa Cruz Xena and the Genotype-Tissue Expression project databases. Differentially expressed mRNA (DEmRNA) transcripts between normal blood and AML blood were identified. Among these, prognosis-associated signature mRNA molecules were screened using univariate Cox and least absolute shrinkage and selection operator regression. A total of four genes, namely, family with sequence similarity 124 member B (FAM124B), 4-hydroxyphenylpyruvate dioxygenase-like protein (HPDL), myeloperoxidase (MPO) and purinergic receptor P2Y1 (P2RY1), were identified using multivariate Cox regression analysis and were used to construct a prognostic scoring system. Moreover, the expression levels of HPDL and MPO were higher in the samples with high immunity scores and estimate scores (sum of stromal score and immune score), compared with those with low scores. Reverse transcription-quantitative PCR and western blot analysis were used to confirm the upregulation of the four candidate genes in AML cell lines as well as in clinical AML samples. In summary, the present study identified a novel mRNA-based prognostic risk scoring system for patients with AML. The four genes used in this scoring system may also play an important role in AML.

Up-regulation expression and prognostic significance of Syntaxin4 in kidney renal clear cell carcinoma

BackgroundSyntaxin4 (STX4) gene encodes the protein STX4, a member of soluble N-ethylmaleimide-sensitive factor attachment protein receptors protein, playing a vital role in cell invadopodium formation and invasion, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of STX4 in kidney renal clear cell carcinoma (KIRC) remain to be investigated.MethodsIn this study, we collected the mRNA expression of STX4 in 535 KIRC patients from The Cancer Genome Atlasthrough the University of California Santa Cruz Xena database platform. Then we explored the expression of STX4 in KIRC, and the relationship with clinicopathological characteristics and prognostic value. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes function enrichment analyses were used to explore the potential mechanism of STX4 in KIRC. qRT-PCR analysis was performed toverify the above results with real world tissue specimens.ResultsThe results indicated that STX4 was up-expressed in KIRC, and were associated with higher histological grade, advanced stage, and poorer prognosis. Moreover, elevated STX4 expression is an independent risk factor for KIRC. qRT-PCR analysis showed that STX4 was significantly elevated in 10 paired of KIRC samples compared to normal samples. Functional enrichment analysis indicated that endo/exocytosis, autophagy, mTOR signaling pathway, and NOD-like receptor signaling pathway were enriched.ConclusionsIn summary, STX4 is constantly up-expressed in KIRC tissues, associated with a poor prognosis. We suggest that it can be an effective biomarker for the prognosis of KIRC and may be a novel therapeutic target in KIRC.

LEP as a potential biomarker in prognosis of breast cancer: Systemic review and meta analyses (PRISMA).

PurposeObesity strongly affects the prognosis of various malignancies, including breast cancer. Leptin (LEP) may be associated with obesity and breast cancer prognosis. The purpose of our study was to determine the prognostic value of LEP in breast cancer.MethodWe conducted a multi-omic analysis to determine the prognostic role of LEP. Different public bioinformatics platforms (Oncomine, Gene Expression Profiling Interactive Analysis, University of California Santa Cruz Xena, bc-GenExMiner, PrognoScan database, R2-Kaplan–Meier Scanner, UALCAN, Search Tool for the Retrieval of Interacting Genes/Proteins database , and The Database for Annotation, Visualization and Integrated Discovery) were used to evaluate the roles of LEP. Clinicopathological variables were evaluated.ResultsLEP was downregulated in breast cancer tissues compared to levels in normal tissues. By co-expressed gene analysis, a positive correlation between LEP and SLC19A3 was observed. Based on the clinicopathological analysis, low LEP expression was associated with older age, higher stage, lymph node status, human epidermal growth factor receptor 2 (HER2) status, estrogen receptor (ER+) positivity, and progesterone receptor (PR+) positivity. Kaplan–Meier survival analysis showed that low LEP expression indicated a poorer prognosis. LEP is hypermethylated in breast cancer tissues in PrognoScan and R2-Kaplan Meier Scanner, and low LEP expression was correlated with poor prognosis. LEP protein–protein interactions were analyzed using Search Tool for the Retrieval of Interacting Genes/Proteins database. Gene ontology analysis results showed that cellular component is mainly associated with the endosome lumen, cytosol, and secretory granules and is upregulated. For the biological process energy reserve, metabolic processes exhibited the greatest regulation compared to the others. In molecular function, it was mainly enriched in a variety of combinations, but hormone activity showed the highest regulation.ConclusionOur study provides evidence for the prognostic role of LEP in breast cancer and as a novel potential therapeutic target in such malignancies. Nevertheless, further validation is required.

Exploration of the Important Role of Microfibril-Associated Protein 4 Gene in Oral Squamous Cell Carcinoma.

BackgroundOral squamous cell carcinoma (OSCC) is a common tumor of the head and neck. Its treatment usually requires multiple modalities. Currently, there are no molecular biomarkers to guide these treatment strategies. Studies have shown that microfibril-associated protein 4 (MFAP4) is potentially useful for non-invasive assessment of various diseases; however, its biological function in tumors is still unknown. In this study, we propose that MFAP4 is a new prognostic target for OSCC.Material/MethodsFirst, we collected OSCC data (GSE25099 and GSE30784 datasets) from the Gene Expression Omnibus (GEO) database and compared the differential expression of MFAP4 gene between the patients (tumor) and normal (control) groups. The comparison was done with University of California Santa Cruz Xena (https://xenabrowser.net/Datapages/), and we calculated the difference in MFAP4 gene expression between normal and tumor tissues in a pan-cancer analysis. Then, we compared the 2 groups with high and low expression of MFAP4 gene in terms of tumor mutation burden (TMB), miRNA regulation, and immune cell infiltration.ResultsWe found that the expression of MFAP4 gene was significantly decreased in tumors. Our research also showed that high expression of MFAP4 was related to better prognosis of patients and may be related to tumor gene mutation, miRNA regulation, and infiltration of different immune cells.ConclusionsOur work provides evidence that expression of MFAP4 can be used as a prognostic biomarker for risk stratification of OSCC patients and elaborates on its relation with the regulation of TMB, miRNAs, and immune cell infiltration.