Kaplan-Meier Plotter Database Research Articles

Increased Expression of the RBPMS Splice Variants Inhibits Cell Proliferation in Ovarian Cancer Cells.

RNA-Binding Protein with Multiple Splicing (RBPMS) is a member of family proteins that bind to nascent RNA transcripts and regulate their splicing, localization, and stability. Evidence indicates that RBPMS controls the activity of transcription factors associated with cell growth and proliferation, including AP-1 and Smads. Three major RBPMS protein splice variants (RBPMSA, RBPMSB, and RBPMSC) have been described in the literature. We previously reported that reduced RBPMS levels decreased the sensitivity of ovarian cancer cells to cisplatin treatment. However, little is known about the biological role of the RBPMS splice variants in ovarian cancer cells. We performed RT-PCR and Western blots and observed that both RBPMSA and RBPMSC are reduced at the mRNA and protein levels in cisplatin resistant as compared with cisplatin sensitive ovarian cancer cells. The mRNA and protein levels of RBPMSB were not detectable in any of the ovarian cancer cells tested. To better understand the biological role of each RBPMSA and RBPMSC, we transfected these two splice variants in the A2780CP20 and OVCAR3CIS cisplatin resistant ovarian cancer cells and performed cell proliferation, cell migration, and invasion assays. Compared with control clones, a significant reduction in the number of colonies, colony size, cell migration, and invasion was observed with RBPMSA and RBPMSC overexpressed cells. Moreover, A2780CP20-RBPMSA and A2780CP20-RBPMSC clones showed reduced senescence-associated β-galactosidase (β-Gal)-levels when compared with control clones. A2780CP20-RBPMSA clones were more sensitive to cisplatin treatment as compared with A2780CP20-RBPMSC clones. The A2780CP20-RBPMSA and A2780CP20-RBPMSC clones subcutaneously injected into athymic nude mice formed smaller tumors as compared with A2780CP20-EV control group. Additionally, immunohistochemical analysis showed lower proliferation (Ki67) and angiogenesis (CD31) staining in tissue sections of A2780CP20-RBPMSA and A2780CP20-RBPMSC tumors compared with controls. RNAseq studies revealed many common RNA transcripts altered in A2780CP20-RBPMSA and A2780CP20-RBPMSC clones. Unique RNA transcripts deregulated by each RBPMS variant were also observed. Kaplan-Meier (KM) plotter database information identified clinically relevant RBPMSA and RBPMSC downstream effectors. These studies suggest that increased levels of RBPMSA and RBPMSC reduce cell proliferation in ovarian cancer cells. However, only RBPMSA expression levels were associated with the sensitivity of ovarian cancer cells to cisplatin treatment.

CEP55 predicts the poor prognosis and promotes tumorigenesis in endometrial cancer by regulating the Foxo1 signaling.

Endometrial cancer is a common gynecologic cancer, which is relevant to many differentially expressed genes. Centrosomal protein 55 (CEP55) was proved to be aberrantly expressed in several cancers. However, the function of CEP55 in endometrial cancer remains largely uncertain. The differentially expressed genes in endometrial cancer were analyzed by GEO datasets. CEP55 expression and its correlation to aggressive behaviors and diagnosis were analyzed by TCGA and the Human Protein Atlas databases. The association between CEP55 expression and 5-year overall survival in endometrial cancer was predicted using Kaplan-Meier Plotter database. Cell proliferation and apoptosis were determined by western blotting, EdU staining, TUNEL staining, and LDH release. CEP55-related targets were predicted by LinkedOmics and analyzed by KEGG pathway analysis using KOBAS. Foxo1 level was detected by western blotting. CEP55 expression was increased in endometrial cancer. The upregulated CEP55 was associated with tumor invasion, histologic grade, histological type and poor prognosis in endometrial cancer. CEP55 knockdown decreased PCNA and CDK2 levels and inhibited cell proliferation. Moreover, CEP55 downregulation promoted cell apoptosis, LDH release and increased cl-caspase-3/caspase-3 level. CEP55-related targets were enriched in Foxo1 signaling. CEP55 silencing increased the transcription activity of Foxo1. Inhibition of Foxo1 activity reversed the effect of CEP55 knockdown on cell proliferation and apoptosis. In conclusion, CEP55 knockdown repressed cell proliferation and facilitated apoptosis by regulating the Foxo1 signaling in endometrial cancer.

HSPA8 Is a New Biomarker of Triple Negative Breast Cancer Related to Prognosis and Immune Infiltration.

Triple negative breast cancer (TNBC) is a kind of cancer that endangers the lives of women all over the world in the 21st century. Heat shock protein member 8 (HSPA8) is the chaperone gene of the heat shock protein family. It is involved in many cellular functions. For example, it promotes the circulation between ATP and ADP, participates in protein folding, and can change the vitality of the cell and inhibit its growth. However, the abnormal expression of HSPA8 gene in TNBC and its diagnostic and prognostic significance still need to be further studied. First, we used related databases (such as TCGA, GEO, GTEx, ONCOMINE, TIMER2.0, UALCAN, HPA, STRING, CCLE, and Kaplan-Meier plotter databases) to analyze the relationship between HSPA8 and TNBC by bioinformatics. Then, the analysis using only a small part of the experimental work is used to explain our findings. For example, HSPA8 protein expression was evaluated by immunohistochemical method in TNBC tissues. Western blotting experiments were carried out to verify the results. Then, the clinicopathological characteristics of patients with TNBC were analyzed by R software and Cox regression analysis. On the basis, a nomogram is constructed to estimate the 1-, 3-, and 5-year overall survival (OS). The prognostic nomogram performance was calibrated and evaluated by the calibration curve and receiver operating characteristic (ROC) curve. In the study, we analyzed the three GEO databases (including GSE86945, GSE106977, and GSE102088) and found that HSPA8 is one of the central genes of TNBC. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) researches indicated that HSPA8 was mainly involved in partner-mediated autophagy, mRNA catabolism, neutrophil activation, immune response, protein targeting, RNA splicing, RNA catabolism, and other biological processes. Next, we used bioinformatics technology to find that the expression level of HSPA8 in breast cancer (BC) and TNBC samples was significantly higher than that in normal breast tissues, which was determined by analyzing hospital patient samples and related experiments. In addition, the expression level of HSPA8 in BC and TNBC samples was significantly correlated with clinical indexes such as TNM stage. The Cox analysis revealed that the expression of HSPA8 in TNBC had significant clinical prognostic value. The results of nomogram and ROC test show that HSPA8 has significant predictive ability in TNBC. The results of immune infiltration of HSPA8 through the TIMER2.0 database showed that there was a significant correlation between HSPA8 and immune cell subsets. Our results show that the expression of HSPA8 in TNBC has important clinical diagnostic significance and clarify the potential molecular mechanism that promotes the evolution of TNBC. The high expression of HSPA8 may be related with the poor clinical outcome of TNBC. This helps to provide us with a new direction of TNBC targeted therapy.

Identification of a novel oxidative stress-related prognostic model in lung adenocarcinoma.

Background: Oxidative stress (OxS) participates in a variety of biological processes, and is considered to be related to the occurrence and progression of many tumors; however, the potential diagnostic value of OxS in lung cancer remains unclear. Methods: The clinicopathological and transcriptome data for lung adenocarcinoma (LUAD) were collected from TCGA and GEO database. LASSO regression was used to construct a prognostic risk model. The prognostic significance of the OxS-related genes was explored using a Kaplan-Meier plotter database. The prediction performance of the risk model was shown in both the TCGA and GSE68465 cohorts. The qRT-PCR was performed to explore the expression of genes. CCK-8, Edu and transwell assays were conducted to analyze the role of CAT on cell proliferation migration and invasion in lung cancer. Immune infiltration was evaluated by CIBERSORT and mutational landscape was displayed in the TCGA database. Moreover, the relationship between risk score with drug sensitivity was investigated by pRRophetic. Results: We identified a prognosis related risk model based on a four OxS gene signature in LUAD, including CYP2D6, FM O 3, CAT, and GAPDH. The survival analysis and ROC curve indicated good predictive power of the model in both the TCGA and GEO cohorts. LUAD patients in the high-risk group had a shorter OS compared to the low-risk group. QRT-PCR result showed that the expression of four genes was consistent with previous analysis in cell lines. Moreover, overexpression of CAT could decrease the proliferation, invasion and migration of lung cancer cells. The Cox regression analysis showed that the risk score could be used as an independent prognostic factor for OS. LUAD patients in the high-risk score group exhibited a higher tumor mutation burden and risk score were closely related to tumor associated immune cell infiltration, as well as the expression of immune checkpoint molecules. Both the high- and low-risk groups have significant differences in sensitivity to some common chemotherapy drugs, such as Paclitaxel, Docetaxel, and Vinblastine, which may contribute to clinical treatment decisions. Conclusion: We established a robust OxS-related prognostic model, which may contribute to individualized immunotherapeutic strategies in LUAD.

TMPRSS4 is a novel biomarker and correlated with immune infiltration in thyroid carcinoma

Transmembrane protease serine 4 (TMPRSS4) is a cancer-associated protease associated with prognosis in various types of cancer. Mechanistically, TMPRSS4 mainly regulates malignant phenotypes, such as tumor invasion and metastasis, by either the epithelial to mesenchymal transition (EMT) program or promoting the proliferation of cancer cells. To date, TMPRSS4 and immune infiltration in thyroid carcinoma (TC) are largely unknown. Thus, this paper evaluated the expression of TMPRSS4 in tumor tissue through the Tumor Immune Estimation Resource (TIMER) database, and Oncomine, and its correlation with clinical parameters by UALCAN databases. Furthermore, we analyzed its prognostic value from Kaplan-Meier Plotter database, and the relationship between TMPRSS4 and the abundance of tumor-infiltrating lymphocytes (TILs) in TC in TISIDB, screening potential immune targets to explore novel mechanisms for the clinical management of TC. Finally, we assessed the correlation between TMPRSS4 and some immune markers to uncover a potential immune-related biomarker in TC patients by TIMER2.0. The results revealed that TMPRSS4 was highly expressed in TC and was also associated with lymphatic metastasis, advanced stage, histological subtype, and favorable clinical outcome. The stratified analysis based on immune cell content showed that decreased TMPRSS4 had worse prognosis in CD8+ T cell-enriched TC patients. TMPRSS4 was positively correlated with tumor immune infiltration and the expression of gene markers of immune cells. Notably, its expression was lower in the lymphocyte-depleted subtype than in other immunosubtypes in TC. Moreover, TMPRSS4 was closely related to chemokines as well as their receptors and the immunosuppressive checkpoints CTLA-4, PD-1, and HLA-G. In conclusion, TMPRSS4 may act as a novel biomarker predicting prognosis and immune infiltration in TC.

Diagnostic, prognostic, and immunological roles of CD177 in cervical cancer.

CD177, an indicator of prognosis in diverse cancers, is involved in the physiological processes of various tumor cells, and acts as an immune molecule with novel functions in cancer pathogenesis. However, the diagnostic, prognostic, and immunological role of CD177 in cervical cancer remains unclear. Utilizing publicly available databases and integrating several bioinformatics analysis methods, we evaluated the expression level of CD177 in cervical cancer by GENT2, HPA, and GEO databases. And the experiments of western blot and immunohistochemical staining were used to testthehypothesis. The Kaplan-Meier Plotter database, Xena Shiny, and the constructed nomogram were clearly demonstrated its prognostic value for patients. Gene set enrichment analysis explored the relationship between CD177 and cervical cancer immune responses and immune cells infiltration level. In addition, we investigated the association between CD177 expression and stromal score, immune score, immune checkpoint, and drug sensitivity by TCGA RNA-seq data. CD177 was apparently expressed at low levels in cervical cancer and predicted a poor survival rate for patients. CD177 significantly activated immune-related signaling pathways and had a positive relationship with immune cell infiltration level. The high CD177 expression group possessed the high stromal score and immune score. CD177 had potential interactions with CTLA4, CD27, BLTA, CD200R1, CD80, NRP1, TNFRSF25, TIGIT, ICOS, and TNFSF9 checkpoint markers. And CD177 expression was positively relevant with drug sensitivity for Lapatinib, Belinostat, ATRA, Gefitinib, Navitoclax, and Tamoxifen. These findings may shed light on the vital role of CD177 in cervical cancer diagnosis, prognosis, and immunological functions, and it may be a promising predictor and potential factor for cervical cancer patients.

Comprehensive Analysis of the Expression and Prognosis for Lipid Metabolism-Related Genes in Hepatocellular Carcinoma.

Hao DingBackground This study aimed to screen potential key genes associated with lipid metabolism and to evaluate their expressions and prognosis values in hepatocellular carcinoma (HCC). Methods Data sets GSE6764, GSE14520, and GSE112790 were used to identify the common differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was constructed by STRING database. Hub genes in PPI network were identified and subjected to functional enrichment analysis to screen lipid metabolism-related genes. The expressions of selected genes and their associations with prognosis were analyzed using UALCAN, The Human Protein Atlas, and Kaplan-Meier plotter databases. The transcriptional factor (TF)-gene regulatory network was constructed using NetworkAnalyst. Results A total of 331 common DEGs including 106 upregulated and 225 downregulated genes were identified. PPI network analysis showed that 76 genes with high degrees were identified as hub genes, among which 14 genes were lipid metabolism-related genes. PON1, CYP2C9, and SPP1 were found to be the independent prognostic markers. Key TFs with close interactions with these prognostic genes, including HINFP, SRF, YY1, and NR3C1, were identified from the TF-gene regulatory network. Conclusion This study presented evidence for the prognostic capabilities of lipid metabolism-related genes in HCC, and newly identified HINFP and NR3C1 as potential biomarkers for HCC.

High HOXA9 gene expression predicts response to chemotherapy and prognosis of high-grade serous ovarian cancer patients.

High-grade serous ovarian cancer (HGSOC) is a deadly malignancy. Homeobox protein A9 (HOXA9) is linked with serous papillary histotype differentiation, and inappropriate HOXA9 expression is a step in ovarian cancer that induces aberrant differentiation. This study aimed to reveal the significance of HOXA9 in HGSOC. HOXA9 mRNA and protein expression were examined by quantitative PCR and immunohistochemistry, respectively. The chi-square test was used to evaluate associations between HOXA9 expression and clinical characteristics. The prognostic value of HOXA9 was calculated by the Kaplan-Meier method. The Kaplan-Meier Plotter database was used to assess the prognostic value of HOXA9. The mRNA and protein expression of HOXA9 were significantly upregulated in chemotherapy-resistant HGSOC compared with chemotherapy-sensitive HGSOC. The chi-square test showed that high HOXA9 expression was significantly related with grade, clinical stage, and residual disease. High HOXA9 expression was significantly associated with poor prognosis. The Kaplan-Meier Plotter database further confirmed these results. Cox hazard regression showed that high HOXA9 expression was an independent prognostic factor for survival in HGSOC patients. This study showed that HOXA9 expression was associated with chemotherapy resistance and poor outcomes in HGSOC patients. High HOXA9 expression might be a prognostic indicator for HGSOC.

The roles of BTG1 mRNA expression in cancers: A bioinformatics analysis.

BTG1 (B-cell translocation gene 1) may inhibit proliferation and cell cycle progression, induce differentiation, apoptosis, and anti-inflammatory activity. The goal of this study was to clarify the clinicopathological and prognostic significances of BTG1 mRNA expression and related signal pathways in cancers. Using the Oncomine, TCGA (the cancer genome atlas), xiantao, UALCAN (The University of ALabama at Birmingham Cancer data analysis Portal), and Kaplan-Meier plotter databases, we undertook a bioinformatics study of BTG1 mRNA expression in cancers. BTG1 expression was lower in gastric, lung, breast and ovarian cancer than normal tissue due to its promoter methylation, which was the opposite to BTG1 expression. BTG1 expression was positively correlated with dedifferentiation and histological grading of gastric cancer (p < 0.05), with squamous subtype and young age of lung cancer (p < 0.05), with infrequent lymph node metastasis, low TNM staging, young age, white race, infiltrative lobular subtype, Her2 negativity, favorable molecular subtyping, and no postmenopause status of breast cancer (p < 0.05), and with elder age, venous invasion, lymphatic invasion, and clinicopathological staging of ovarian cancer (p < 0.05). BTG1 expression was negatively correlated with favorable prognosis of gastric, lung or ovarian cancer patients, but the converse was true for breast cancer (p < 0.05). KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis showed that the top signal pathways included cytokine-cytokine receptor interaction, cell adhesion molecules, chemokine, immune cell receptor and NF (nuclear factor)-κB signal pathways in gastric and breast cancer. The top hub genes mainly contained CD (cluster of differentiation) antigens in gastric cancer, FGF (fibroblast growth factor)-FGFR (FGF receptor) in lung cancer, NADH (nicotinamide adenine dinucleotide): ubiquinone oxidoreductase in breast cancer, and ribosomal proteins in ovarian cancer. BTG1 expression might be employed as a potential marker to indicate carcinogenesis and subsequent progression, even prognosis.

Tumor microenvironment-related gene selenium-binding protein 1 (SELENBP1) is associated with immunotherapy efficacy and survival in colorectal cancer

BackgroundSelenium-binding protein 1 (SELENBP1), a member of the selenium-containing protein family, plays an important role in malignant tumorigenesis and progression. However, it is currently lacking research about relationship between SELENBP1 and immunotherapy in colorectal cancer (CRC).MethodsWe first analyzed the expression levels of SELENBP1 based on the Cancer Genome Atlas (TCGA), Oncomine andUALCAN. Chisq.test, Fisher.test, Wilcoxon-Mann-Whitney test and logistic regression were used to analyze the relationship of clinical characteristics with SELENBP1 expression. Then Gene ontology/ Kyoto encyclopedia of genes and genomes (GO/KEGG), Gene set enrichment analysis (GSEA) enrichment analysis to clarify bio-processes and signaling pathways. The cBioPortal was used to perform analysis of mutation sites, types, etc. of SELENBP1. In addition, the correlation of SELENBP1 gene with tumor immune infiltration and prognosis was analyzed using ssGSEA, ESTIMATE, tumor immune dysfunction and rejection (TIDE) algorithm and Kaplan-Meier (KM) Plotter database. Quantitative real-time PCR (qRT-PCR) and western blotting (WB) were used to validate the expression of SELENBP1 in CRC samples and matched normal tissues. Immunohistochemistry (IHC) was further performed to detect the expression of SELENBP1 in CRC samples and matched normal tissues.ResultsWe found that SELENBP1 expression was lower in CRC compared to normal colorectal tissue and was associated with poor prognosis. The aggressiveness of CRC increased with decreased SELENBP1 expression. Enrichment analysis showed that the SELENBP1 gene was significantly enriched in several pathways, such as programmed death 1 (PD-1) signaling, signaling by interleukins, TCR signaling, collagen degradation, costimulation by the CD28 family. Decreased expression of SELENBP1 was associated with DNA methylation and mutation. Immune infiltration analysis identified that SELENBP1 expression was closely related to various immune cells and immune chemokines/receptors. With increasing SELENBP1 expression, immune and stromal components in the tumor microenvironment were significantly decreased. SELENBP1 expression in CRC patients affects patient prognosis by influencing tumor immune infiltration. Beside this, SELENBP1 expression is closely related to the sensitivity of chemotherapy and immunotherapy.ConclusionsSurvival analysis as well as enrichment and immunoassay results suggest that SELENBP1 can be considered as a promising prognostic biomarker for CRC. SELENBP1 expression is closely associated with immune infiltration and immunotherapy. Collectively, our study provided useful information on the oncogenic role of SELENBP1, contributing to further exploring the underlying mechanisms.

Identification and analysis of dysregulated fatty acid metabolism genes in breast cancer subtypes.

Breast cancer is one of the most aggressive and lethal types of transformation among women. An anomaly of normal fatty acid metabolism is acknowledged as a critical trigger for malignant transformations including breast cancer, but the prospect of targeting fatty acid metabolism for the treatment of malignancy has remained unrecognized so far. It has been observed that specific fatty acid metabolism genes are involved in the commencement and development of breast cancer. These specific genes have also been observed to be related to different isotypes/molecular subtypes of breast cancer. The main purpose of this study was to scrutinize the prognostic significance, functional role, and expression pattern of fatty acid metabolism genes. In-Silico tools like TCGA BrCA, Gepia2, Ualcan Analysis, UCSC Xena, Kaplan-Meier plotter, Bc-gene EXminer, String, gene ontology, and KEGG databases, were used to assess the expression pattern of the fatty acid metabolism genes in breast cancer patients and also among the different molecular sub-types of breast cancer. Differential gene expression analysis revealed dysregulation of FABP4, FABP5, PLIN1,PLIN2, PLIN4, PLIN5, LPIN1, MGLL, PNPLA2, PNPLA7, ACSL1, and ACOX2 showing a fold change > ± 1.5. Also, most of these genes show downregulation in Ualcan analysis of different isotypes/molecular subtypes of breast cancer. The study reveals that the screened genes i.e., FABP4, FABP5, PLIN1,PLIN2, PLIN4, PLIN5, LPIN1, MGLL, PNPLA2, PNPLA7, ACSL1, and ACOX2 can be used as biomarkers that reveal poor prognosis and may serve as therapeutic targets for the treatment of breast cancer.

Prognostic Signature GXYLT2 Is Correlated with Immune Infiltration in Bladder Cancer.

Background GXYLT2 (glucoside xylosyltransferase 2) was known as an important gene that regulates classical Notch signaling and is involved in progression in human tumors. However, the correlation between GXYLT2 expression and bladder cancer remains unclear. Methods GXYLT2 expression was analyzed by ONCOMINE database, GEPIA database, and TIMER database. The Cancer Genome Atlas (TCGA) was utilized to confirm relationships between GXYLT2 and molecular subtypes of BLCA (bladder cancer). We discovered prognostic value of GXYLT2 in BLCA using GEPIA, LinkedOmics database, and Kaplan-Meier Plotter database. Subsequently, correlations between GXYLT2 and tumor immune infiltration were investigated through TIMER and TISIDB website. We then downloaded data of patients with BLCA from TCGA website, to conduct functional annotations and to construct protein-protein interaction network through STRING and Enrich web servers. Results Significant differences were observed between GXYLT2 expression of bladder cancer and normal tissues. GXYLT2 was a poor prognostic biomarker in BLCA with impact on diverse clinical characteristics. We found that GXYLT2 was closely related to tumor immune infiltrated cells and immune genes. Functional annotations indicated that GXYLT2 was linked to immune-related pathways. Conclusions The results suggested that GXYLT2 was associated with a poor prognosis and tumor immune cell infiltration of BLCA. GXYLT2 could be a promising therapeutic target in bladder cancer.

Application of genomic selection and experimental techniques to predict cell death and immunotherapeutic efficacy of ferroptosis-related CXCL2 in hepatocellular carcinoma.

Since most hepatocellular carcinoma (HCC) patients are diagnosed at advanced stages, there is no effective treatment to improve patient survival. Ferroptosis, a regulated cell death driven by iron accumulation and lipid peroxidation, has been reported to play an important role in tumorigenesis. However, the detailed mechanism and biological function of ferroptosis are still incompletely understood in HCC patients. In this study, we analyzed genomic profiles of three HCC datasets, GSE6764, GSE14520, and GSE14323. Venn diagrams were implemented to visualize the overlapping genes between differentially expressed genes and ferroptosis-related gene set. Then, one up-regulated gene, ACSL4, and five down-regulated genes, STEAP3, MT1G, GCH1, HAMP, and CXCL2, were screened. Based on the survival analysis performed by Kaplan-Meier plotter database, ferroptosis-related gene CXCL2 was demonstrated positively-correlated with the patients’ prognosis. Moreover, CXCL2 overexpression significantly inhibited cell growth and improved cellular ROS, Fe2+ and MDA levels in HCC cells Huh7 and MHCC97H, suggesting the roles of CXCL2 in inducing ferroptotic cell death. In addition, aberrantly expressed CXCL2 was negatively associated with malignancy clinical features, such as nodal metastasis and higher grades. The ssGSEA enrichment analysis revealed that CXCL2 co-expressed molecules were mainly involved in inflammation and immune-related pathways, such as acute inflammatory response, humoral immune response, adaptive immune response. TISIDB algorithm indicated the positive correlation between CXCL2 expression and tumor-infiltrating immune cells, including neutrophils and macrophages. Additionally, we also found that CXCL2 was positively correlated with immune infiltration score, and HCC patients with higher score harbored better prognosis. Together, these findings suggested that CXCL2 may enhance ferroptosis sensitivity and regulate immune microenvironment in HCC, and serve as a promising prognosis biomarker for HCC patients.

SLC17A2 Expression Correlates with Prognosis and Immune Infiltrates in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a dismal prognosis, according to updated statistics. The solute carrier family 17 member 2 (SLC17A2) has not been studied in liver cancer. Therefore, we evaluated the role of SLC17A2 in HCC by bioinformatics analysis. The objective of the study was to explore the value of SLC17A2 in the prognosis and diagnosis of hepatocellular carcinoma. The expression level of SLC17A2 in HCC and the clinicopathological data were analyzed based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and validated by immunohistochemical staining. In addition, the Kaplan-Meier plotter database and receiver operating characteristic (ROC) curve analysis were used to explore the prognostic and diagnostic significance. Some online databases were used to analyze the relationship between immune cell infiltration and analyze the relationship between immune cell infiltration and SLC17A2 in HCC. Multivariate Cox regression analysis showed that SLC17A2 expression was low in HCC (P < 0.05) and closely related to the clinical stage of HCC. In addition, SLC17A2 had a certain diagnostic value in HCC according to ROC curve analysis. Further biological analyses showed that SLC17A2 can regulate fatty acid metabolism, amino acid metabolism and cytochrome P450- related metabolism. Notably, we found that SLC17A2 expression was closely correlated with the infiltration of most immune cells in HCC. SLC17A2 expression is low in HCC and correlates with immune infiltration, so it may serve as an independent prognostic factor for HCC.

GRAP2 is a prognostic biomarker and correlated with immune infiltration in lung adenocarcinoma.

GRAP2 is an adaptor protein involved in leukocyte signal activation; however, the prognostic value of GRAP2 and its correlation with immune infiltration in lung adenocarcinoma (LUAD) are unclear. Original data were downloaded from the TCGA database and Gene Expression Omnibus (GEO) database. GRAP2 expression was analyzed with the TCGA and TIMER databases. We evaluated the influence of GRAP2 on clinical prognosis using the Kaplan-Meier plotter, GEO, and GEPIA database. The TIMER and TISIDB databases were used to investigate correlations between GRAP2 expression and cancer immune characteristics. Finally, we confirmed the expression of GRAP2 in LUAD by immunohistochemistry staining. The transcription levels of GRAP2 were significantly lower in several human cancer types, including LUAD, than in adjacent normal tissues. Immunohistochemistry staining confirmed that LUAD tumor tissues had lower GRAP2 protein expression levels than adjacent normal tissues. GRAP2 downregulation was associated with poorer overall survival, pathologic stage, T stage, N stage, and primary therapy outcome in LUAD. Mechanistically, we found a hub gene set that included a total of 91 genes coexpressed with GRAP2, which were closely related to the immune response in LUAD. The expression levels of GRAP2 were positively correlated with the infiltration levels of multiple immune cells and the cumulative survival time of a few immune cells. GRAP2 expression was found to be positively correlated with that of multiple immune markers, chemokines, chemokine receptors, and MHC molecules in LUAD. GRAP2 can be used as a biomarker for assessing prognosis and immune infiltration levels in LUAD.

REV1: A novel biomarker and potential therapeutic target for various cancers.

Background: REV1 is a member of the translesion synthesis DNA polymerase Y family. It is an essential player in a variety of DNA replication activities, and perform major roles in the production of both spontaneous and DNA damage-induced mutations. This study aimed to explore the role of REV1 as a prognostic biomarker and its potential function regulating the sensitivity of anti-tumor drugs in various cancers. Methods: We analyzed the impact of REV1 gene alterations on patient prognosis and the impact of different REV1 single nucleotide polymorphisms (SNP) on protein structure and function using multiple online prediction servers. REV1 expression was assessed using data from Oncomine, TCGA, and TIMER database. The correlation between REV1 expression and patient prognosis was performed using the PrognoScan and Kaplan-Meier plotter databases. The IC50 values of anti-cancer drugs were downloaded from the Genomics of Drug Sensitivity in Cancer database and the correlation analyses between REV1 expression and each drug pathway’s IC50 value in different tumor types were conducted. Results: Progression free survival was longer in REV1 gene altered group comparing to unaltered group [Median progression free survival (PFS), 107.80 vs. 60.89 months, p value = 7.062e-3]. REV1 SNP rs183737771 (F427L) was predicted to be deleterious SNP. REV1 expression differs in different tumour types. Low REV1 expression is associated with better prognosis in colorectal disease specific survival (DSS), disease-free survival (DFS), gastric overall survival (OS), post progression survival (PPS) and ovarian (OS, PPS) cancer while high REV1 expression is associated with better prognosis in lung [OS, relapse free survival (RFS), first progession (FP), PPS] and breast (DSS, RFS) cancer. In colon adenocarcinoma and rectum adenocarcinoma and lung adenocarcinoma, low expression of REV1 may suggest resistance to drugs in certain pathways. Conversely, high expression of REV1 in acute myeloid leukemia, brain lower grade glioma, small cell lung cancer and thyroid carcinoma may indicate resistance to drugs in certain pathways. Conclusion: REV1 plays different roles in different tumor types, drug susceptibility, and related biological events. REV1 expression is significantly correlated with different prognosis in colorectal, ovarian, lung, breast, and gastric cancer. REV1 expression can be used as predictive marker for various drugs of various pathways in different tumors.

Survival-based bioinformatics analysis to identify hub long non-coding RNAs along with lncRNA-miRNA-mRNA network for potential diagnosis/prognosis of thyroid cancer.

Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA-seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan-Meier plotter database to create a survival associated with the ceRNA network (survival-related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival-related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non-tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer-related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival-related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs.

PHD3 as a Prognosis Marker and its Relationship with Immune Infiltration in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is a highly heterogeneous malignant tumor. Therefore, it is necessary to find predictive biomarkers related to the prognosis and immune infiltration of lung adenocarcinoma, which may provide an effective theoretical basis for its clinical treatment. This study aimed to evaluate whether the expression level of PHD3 in lung adenocarcinoma (LUAD) is related to immunity. PHD3 expression was analyzed by the ONCOMINE, TIMER, UALCAN, and GEPIA databases. The correlations between clinical information and PHD3 expression were analyzed by the LinkedOmics database. Then, we evaluated the influence of PHD3 on the survival of LUAD patients using Kaplan-Meier Plotter and HPA database. We explored the correlation between PHD3 and tumor immunity using TIMER and the correlation module of TISDIB. Finally, we used the cBioportal database to analyze PHD3 mutations in LUAD. Comprehensive analysis displayed PHD3 expression to be clearly higher in LUAD compared to adjacent normal tissues. PHD3 expression was identified to be positively associated with tumor purity, histological type, and later pathological stage. Survival curve results revealed the high expression of PHD3 in LUAD patients to be accompanied by a poor prognosis. Further study indicated PHD3 to be significantly related to a variety of tumor immune cells and molecules. Moreover, among the LUAD cases with gene alteration of PHD3, amplification was the most common of all alteration types. PHD3 may be used as a biomarker for survival and immunotherapy of LUAD.

Prognostic Value of UBE2T and Its Correlation with Immune Infiltrates in Lung Adenocarcinoma.

Non-small cell lung cancer has a subtype with a high morbidity and mortality rate called lung adenocarcinoma (LUAD). It is critical to locate reliable prognostic biomarkers for LUAD at this time. Ubiquitin-conjugating enzyme E2T (UBE2T) has been found in numerous malignancies; however, its expression level and potential functions in LUAD are not completely understood at this time. A differentially expressed gene (DEG) screening method was used to identify genes that were expressed differently in 516 samples from LUAD and 59 samples from TCGA datasets. Clinicopathological markers were correlated with UBE2T expression. Using the Kaplan–Meier plotter database, UBE2T was evaluated for its prognostic value in the context of LUAD. In order to examine the importance of independent prognostic factors, both univariable and multivariable Cox regression models were applied. TIMER and CIBERSORT were utilized in order to investigate the connection that exists between UBE2T expression and tumor-infiltrating immune cells. This study collected 578 DEGs in total, as follows: 171 genes were significantly increased, while 408 genes were significantly decreased. We identified 9 survival-related DEGs in LUAD, including ASF1B, CA9, CCNB2, CCNE1, RRM2, SAPCD2, TCN1, TPX2, and UBE2T. Our attention focused on UBE2T, which was highly expressed in LUAD. A correlation was also found between high UBE2T expression and gender, age, advanced clinical stage, and decreased overall survival. In addition, multivariate analysis demonstrated UBE2T expression to be a significant independent diagnostic factor for patients suffering from LUAD. UBE2T was positively correlated with resting T cell CD4+ memory, myeloid dendritic cell resting, mast cell activated, macrophage M2, and B cell plasma, whereas it was negatively correlated with resting T cell CD4+ memory, MDC resting, MDC activated, macrophage M2, and B cell plasma. Overall, high expression levels of UBE2T correlated with poor overall survival in patients with LUAD, and UBE2T was an independent predictor involved in immune infiltration of LUAD. These findings offer fresh perspectives that contribute to our comprehension of the evolution of LUAD.

Systems Network Pharmacology-Based Prediction and Analysis of Potential Targets and Pharmacological Mechanism of Actinidia chinensis Planch. Root Extract for Application in Hepatocellular Carcinoma.

Purpose Traditional Chinese medicine (TCM) sometimes plays a crucial role in advanced cancer treatment. Despite the significant therapeutic efficacy in hepatocellular carcinoma (HCC) that Actinidia chinensis Planch root extract (acRoots) has proven, its complex composition and underlying mechanism have not been fully elucidated. Therefore, this study analyzed the multiple chemical compounds in acRoots and their targets via network pharmacology and bioinformatics analysis, with the overarching goal of revealing the potential mechanisms of the anti-HCC effect. Methods The main ingredients contained in acRoots were initially screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the candidate bioactive ingredient targets were identified using DrugBank and the UniProt public databases. Second, the biological processes of the targets of active molecules filtered from the ingredients of acRoots were evaluated using gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Third, weighted gene coexpression network analysis (WGCNA) was performed to identify gene coexpression modules associated with HCC. The hub genes of acRoots in HCC were defined via contrasting the above module eigengenes with candidate target genes of acRoots. Furthermore, the target-pathway network was analyzed to explore the mechanism for anti-HCC effect of hub genes. Kaplan–Meier plotter database analysis was performed to validate the hub genes of acRoots correlation with prognostic values in HCC. In order to verify the results of the network pharmacological analysis, we performed a molecular docking approach on the active ingredients and key targets using the Discovery Studio software. The viability of SMMC-7721 and HL-7702 cells was determined by Cell counting kit-8 (CCK-8) after being treated with different concentrations of (+)-catechin (0, 50, 100, 150, 200, and 250 g/ml) for 24, 48, and 72 hours, respectively. Finally, qRT-PCR and Western blot involving human hepatocarcinoma cells were utilized to verify the impact of (+)-catechin on the hub genes associated with prognosis. Results 6 out of 26 active ingredients extracted from TCMSP were deemed as the core ingredients of acRoots. 175 bioactive-ingredient targets of acRoots were obtained and a bioactive-ingredient targets network was established correspondingly. The biological processes (BP) of target genes mainly involved processes, such as toxic substance and wounding. The results of KEGG pathways indicated that the target genes were mainly enriched in pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, and other pathways. Also, the two hub genes (i.e., ESR1 and CAT) were closely associated with the prognosis of HCC patients. As a consequence, we predicated a series of signaling pathways, including estrogen signaling pathway and longevity regulation pathway, through which acRoots could facilitate the treatment for HCC. The molecular docking experiment ascertained that ESR1 and CAT had an effective binding force with (+)-catechin, one of the core ingredients of acRoots. Furthermore, (+)-catechin inhibited SMMC-7721 cell growth in a dose-dependent manner and a time-dependent manner. Finally, we suggest that the expression level of ESR1 and CAT is positively related to the (+)-catechin concentrations in in-vitro experiments. Conclusion The bioactive ingredients of acRoots, including quercetin, (+)-catechin, beta-sitosterol, and aloe-emodin, have synergistic interactions in reinforcing the anticancer effect in HCC. Evidently, acRoots took effect by regulating multitargets and multipathways through its active ingredients. Further, (+)-catechin, the possible paramount anti-HCC active ingredient in acRoots, helped improve the prognosis of HCC patients by increasing the expression of ESR1 and CAT. Additionally, the findings yielded provide a conceptual guidance for the clinical treatment of HCC and the methods adopted are potentially applicable in the future comprehensive analysis of the underlying mechanisms of TCMs.