The Cancer Genome Atlas Database Research Articles

EZH2 as a prognostic-related biomarker in lung adenocarcinoma correlating with cell cycle and immune infiltrates

BackgroundsIt has been observed that high levels of enhancer of zeste homolog 2 (EZH2) expression are associated with unsatisfactory prognoses and can be found in a wide range of malignancies. However, the effects of EZH2 on Lung Adenocarcinoma (LUAD) remain elusive. Through the integration of bioinformatic analyses, the present paper sought to ascertain the effects of EZH2 in LUAD.MethodsThe TIMER and UALCAN databases were applied to analyze mRNA and protein expression data for EZH2 in LUAD. The result of immunohistochemistry was obtained from the HPA database, and the survival curve was drawn according to the library provided by the HPA database. The LinkedOmics database was utilized to investigate the co-expressed genes and signal transduction pathways with EZH2. Up- and down-regulated genes from The Linked Omics database were introduced to the CMap database to predict potential drug targets for LUAD using the CMap database. The association between EZH2 and cancer-infiltrating immunocytes was studied through TIMER and TISIDB. In addition, this paper explores the relationship between EZH2 mRNA expression and NSCLC OS using the Kaplan–Meier plotter database to further validate and complement the research. Furthermore, the correlation between EZH2 expression and EGFR genes, KRAS genes, BRAF genes, and smoking from the Cancer Genome Atlas (TCGA) database is analyzed.ResultsIn contrast to paracancer specimens, the mRNA and protein levels of EZH2 were higher in LUAD tissues. Significantly, high levels of EZH2 were associated with unsatisfactory prognoses in LUAD patients. Additionally, the coexpressed genes of EZH2 were predominantly associated with numerous cell growth-associated pathways, including the cell cycle, DNA replication, RNA transport, and the p53 signaling pathway, according to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The results of TCGA database revealed that the expression of EZH2 was lower in normal tissues than in lung cancer tissues (p < 0.05). Smoking was associated with elevated EZH2 expression (p < 0.001). EZH2 was highly expressed in lung cancers with positive KRAS expression, and the correlation was significant in lung adenocarcinoma (r = 0.3129, p < 0.001). CMap was applied to determine the top 15 positively correlated drugs/molecules and the top 15 negatively correlated drugs/molecules. MK-1775, MK-5108, fenbendazole, albendazole, BAY-K8644, evodiamine, purvalanol-a, mycophenolic-acid, PHA-793887, and cyclopamine are potential drugs for patients with lung adenocarcinoma and high EZH2 expression.ConclusionsHighly expressed EZH2 is a predictor of a suboptimal prognosis in LUAD and may serve as a prognostic marker and target gene for LUAD. The underlying cause may be associated with the synergistic effect of KRAS, immune cell infiltration, and metabolic processes.

Prognostic value of an eighteen-genes panel in acute myeloid leukemia by analyzing TARGET and TCGA databases.

Acute myeloid leukemia (AML) has a poor prognosis, and the current 5-year survival rate is less than 30%. The present study was designed to identify the significant genes closely related to AML prognosis and predict the prognostic value by constructing a risk model based on their expression. Using bioinformatics (Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, univariate and multivariate Cox regression analysis, Kaplan-Meier survival analysis, and receiver operating characteristic (ROC) analysis) to identify a prognostic gene signature for AML. Finally, The Cancer Genome Atlas (TCGA) database was used to validate this prognostic signature. Based on univariate and multivariate Cox regression analysis, eighteen prognostic genes were identified, and the gene signature and risk score model were constructed. Multivariate Cox analysis showed that the risk score was an independent prognostic factor [hazard ratio (HR) = 1.122, 95% confidence interval (CI) = 1.067-1.180, P< 0.001]. ROC analysis showed a high predictive value of the risk model with an area under the curve (AUC) of 0.705. This study evaluated a potential prognostic signature with eighteen genes and constructed a risk model significantly related to the prognosis of AML patients.

A nine-gene signature as prognostic biomarker in gastric cancer by bioinformatics analysis.

The prognosis of advanced gastric cancer (GC) remains poor. It is urgent and necessary to find suitable prognostic markers. miR-619-5p is highly expressed in GC. However, the value of miR-619-5p and its target genes as prognostic biomarkers of GC is unclear. RT-PCR was performed to verify the expression of miR-619-5p in GC cell lines and their exosomes. Western blotting and transmission electron microscope were used to identify exosomes. The target genes of miR-619-5p were predicted by RNA22 and TargetScan. The differentially expressed genes (DEGs) and prognosis-related genes (PRGs) were obtained using The Cancer Genome Atlas (TCGA) database. The DAVID database was used to analyse pathway enrichment and functional annotation of common target genes. The STRING database and Cytoscape software were used to screen key genes and visualize their functional modules. The survival analysis was conducted using TCGA and Kaplan-Meier Plotter (KMP) databases. Finally, a prognostic model was constructed on the foundation of the key genes to assess the reliability of the screening process. The expression of miR-619-5p in GC cells and their exosomes was proved to be significantly higher than that in normal cell lines. There are 129 common target genes involved in 3 pathways and 28 functional annotations. Finally, nine key target genes of GC (BRCA1, RAD51, KIF11, ERCC6L, BRIP1, TIMELESS, CDC25A, CLSPN and NCAPG2) were identified, and a prognostic model was successfully constructed with a good predictive ability. The model of 9-gene signature could effectively predict the prognosis of GC, and have great potential to be novel prognostic factors and therapeutic targets for patients with GC.

ZNF503 combined with GATA3 is a prognostic factor in triple-negative breast cancer

Purpose Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor prognosis. Therefore, there is an urgent need to identify prognostic markers to improve current treatment and therapeutic strategies. The transcriptional factor ZNF503 has been reported to promote aggressive breast cancer development through the down-regulation of GATA3 expression and has been identified as a candidate predictive marker. In this study, we explored whether ZNF503 and GATA3 could serve as prognostic markers independently or in combination. Material and methods We performed a survival analysis of 989 breast cancer patients from The Cancer Genome Atlas (TCGA), and validated the findings in 202 breast cancer patients from tissue microarray (TMA). Results In TCGA database, the mRNA expression of GATA3 and ZNF503 could not predict TNBC prognosis alone, though the ratio index, ZNF503/GATA3 could be a novel prognostic biomarker in TNBC patients. In TMA database, we detected the protein expression of ZNF503 and GATA3 and found that the combination of the two genes, ZNF503-GATA3, significantly improved the predictive ability of clinical outcomes. Conclusions The results indicated that the binding index of ZNF503 and GATA3 could be used as a prognostic biomarker in TNBC.

Abstract 4266: Genomic landscape of prostate cancer: Bioinformatic analysis of TCGA PanCancer data by race and identification of key pathways and genes in PTEN mutation

Abstract Issue: Prostate cancer (Pca) is still among the most frequently diagnosed cancers in adults. The most often mutated gene in PCa is PTEN (Phosphatase and Tensin Homolog), making it a possible biomarker for prospective customized therapy. The root causes of health inequalities in PCa have not received much attention. Numerous online databases, like The Cancer Genome Atlas (TCGA), provide gene expression data and other data, allowing researchers to further investigate new processes or therapy options. However, there hasn't been much study on tailored therapy up to this point since there may have been difficulties with access to genomic information and bioinformatic tools. Methods: The PCa data in cBioPortal comprises 494 samples. We selected 154 samples comprising 7 Blacks and 147 Whites. We used the TCGA database to obtain the PCa gene expression and DNA methylation data for study. In order to examine the data by race/ethnicity, gene expression, DNA methylation, and genomic changes, we evaluated at the differentially expressed and methylated genes using online tools (cBioPortal). To evaluate gene methylation, expression, and alterations, log ratios of means in Blacks to means in Whites were computed across the data. Additionally, Kaplan-Meier survival analysis, protein interaction analysis, and multivariable data analysis were carried out. Results: PCa data in the TCGA database showed PTEN mutation in 20% patients. The median age of participants was 63 years (range: 42-78). For every category of data assessed, there were significant differences by race/ethnicity (q &amp;lt; 0.05). In the survival analysis, SLC2A1, NUDT12, CUTALP, and other genes were associated with survival. Conclusion: Genetic alteration, expression, and DNA methylation are each significantly different by the two race groups compared. According to our research, PTEN mutation in PCa may influence several genes and biological processes. Citation Format: Olumide Arigbede, Sarah G. Buxbaum, Sara Falzarano, Suhn K. Rhie. Genomic landscape of prostate cancer: Bioinformatic analysis of TCGA PanCancer data by race and identification of key pathways and genes in PTEN mutation. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4266.

Abstract 6555: Integrated bioinformatics analysis identified ASNS and DDIT3 as the therapeutic target in castration resistance prostate cancer

Abstract Background: Many studies have demonstrated the mechanisms of progression to castration-resistant prostate cancer (CRPC) and novel strategies for the treatment of CRPC. Despite these advances, the molecular mechanism underlying the progression to CRPC remain unclear, and no effective treatments for CRPC are currently available. Here, we characterized the pathways and key genes involved in the progression to CRPC to gain insight into the mechanisms and potential therapeutic targets of CRPC. Methods: Bicalutamide-resistant prostate cancer cells derived from LNCaP was generated and named Bical R. RNA sequencing was used to identify differentially expressed genes (DEGs) between LNCaP and Bical R. DAVID and Clue GO were used to perform functional enrichment analysis, and the Cytohubba plug-in Cytoscape was used to identify hub genes associated with progression to CRPC. To validate the expression of hub genes, we performed qRT-PCR and western blot analyses. Further validation was performed using GEO microarray (GSE 32269 and GSE28403). To elucidate the clinical usefulness of these genes, we assessed the disease-free survival of patients with prostate cancer from The Cancer Genome Atlas (TCGA) database. Results: In total, 631 DEGs (302 upregulated genes and 329 downregulated genes) were identified, and Kyoto Encyclopedia of Genes and Genomes pathways were analyzed based on DAVID and Clue GO. We found that the PI3K-Akt and MAPK signaling pathways are of great significance for investigating the mechanism of CRPC progression. Hub genes from protein-protein interaction network of upregulated DEGs (AGT, ASNS, ATF3, ATF4, DDIT3, EFNA5, and VEGFA) were identified. Among the hub genes, ASNS and DDIT3 were markedly up-regulated in CRPC cell lines and CRPC tissues, respectively. Additionally, patients with high expression of ASNS and DDIT3 showed worse disease-free survival in TCGA database. Conclusion: Our study revealed that the PI3K-Akt and MAPK signaling pathways may be important in the mechanism of CRPC progression, and ASNS and DDIT3 may be associated with progression to CRPC. These results may contribute to the development of potential therapeutic targets and mechanisms underlying the progression to CRPC to improve clinical efficacy for CRPC treatment. Acknowledgements: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2022R1A2C2003513). Citation Format: Ae Ryang Jung, Sun Shin, U-Syn Ha, Mee Young Kim, Sung-Hoo Hong, Ji Youl Lee, Sae Woong Kim, Yeun-Jun Chung, Yong Hyun Park. Integrated bioinformatics analysis identified ASNS and DDIT3 as the therapeutic target in castration resistance prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6555.

Abstract 1412: Co-existence of TP53 mutation confers endocrine resistance in PIK3CA-mutated ER+HER2- breast cancer

Abstract Background: PIK3CA mutation is commonly found in estrogen receptor (ER)+ human epidermal growth factor receptor-2 (HER2)- breast cancer (BC) and can be therapeutically targeted by alpelisib, an alpha-specific PIK3CA inhibitor. While previous studies presented conflicting results on the prognostic influence of PIK3CA mutation among ER+HER2- breast cancer, few have been able to address causes of the prognostic discrepancy on a clinical level. In this study, we investigated clinical and genomic features according to a coexistence of TP53 mutation in PIK3CA mutated ER+HER2- breast cancer. Methods: Tumor tissue based next generation sequencing (NGS) was analyzed for 224 HR+ HER2- BC patients from April 2017 to August 2021 in Gangnam Severance Hospital, Seoul, South Korea. Matching clinical records with patient information were reviewed retrospectively. Clinicopathologic features including age, tumor size, histologic grade (HG), TNM stage, estrogen receptor (ER) expression, progesterone (PgR) expression, Ki-67, and Oncotype Dx Recurrence Score (RS) were analyzed. Further analysis was carried out using The Cancer Genome Atlas (TCGA) to explore the relationship of mutation status with intrinsic subtype and risk of recurrence (ROR) score. Results: We identified PIK3CA mutation (PIK3CA m) in 105 (46.9%) of 224 patients, and of these, TP53 co-mutation was found in 25 (23.8%). None of clinicopathologic features were different according to PIK3CA mutation. When PIK3CA m cohort was analyzed according to TP53 mutation (TP53 m) status, tumors with TP53 m presented unfavorable features such as higher HG (p&amp;lt;0.001), lower PgR expression (TP53 wt: Median 7 versus TP53 m: Median 5, p=0.027), and higher N stage (p=0.008). It also displayed a significantly higher proliferative profiles with Ki-67 (TP53 wt: Median 15 versus TP53 m: Median 20, p&amp;lt;0.001) and Oncotype Dx RS (TP53 wt: Median 15 versus TP53 m: Median 26.5, p=0.002). In the 539 ER+HER2- breast cancer from the TCGA database, PIK3CA and TP53 co-mutation was found in 33 (6.1%). Distribution of intrinsic subtypes revealed a higher rate of Luminal B in PIK3CA and TP53 co-mutant tumors (51.5%) than in PIK3CA m and TP53 wt tumors (14.3%, p&amp;lt;0.001). The ROR score was found to be higher in the PIK3CA-TP53 co-mutation compared to PIK3CA m alone (p&amp;lt;0.001). Conclusion: Unlike PIK3CA mutation, PIK3CA and TP53 co-mutation clearly divided multiple clinicopathologic features of HR+ HER2- BC including with. Poorer prognosis of co-mutation was also corroborated by TCGA analysis of intrinsic subtype and ROR score. These findings indirectly suggest that co-mutation of TP53 gene may be associated with less sensitivity to PIK3CA targeted therapy in PIK3CA m ER+HER2- breast cancers. Further research is warranted to improve an efficacy of PIK3CA targeted therapy for PIK3CA m ER+ breast cancer with endocrine-resistant factors. Citation Format: Yoonwon Kook, Kyungsoo Kim, Ji Soo Jang, Seung Ho Baek, Soong June BAe, Joon Jeong, Sung Gwe Ahn. Co-existence of TP53 mutation confers endocrine resistance in PIK3CA-mutated ER+HER2- breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1412.

Abstract 1424: Selective blockade of neuropeptide Y receptor 1 induces cell cycle arrest and promotes apoptosis in colon cancer cells

Abstract Introduction: Colorectal cancer (CRC) is a leading cause of cancer related deaths worldwide. The balance between cancer cell proliferation and apoptosis, which maintains intestinal epithelial cell homeostasis, is disturbed in CRC. Furthermore, deregulation of the apoptotic pathway contributes to therapeutic resistance. Therefore, determination of the mechanisms employed by CRC cells to evade apoptosis is important for development of new therapeutic strategies. Our group has recently reported that neuropeptide Y (NPY), which is a 36-amino acid neuropeptide, is associated with increased angiogenic response in colon cancer. However, the regulatory role of NPY in cellular homeostasis in CRC is largely unknown. NPY is secreted by colon cancer cells that express Y1 receptors (Y1R). The aim of the present study was to investigate the role of NPY in regulation of cell growth and survival in CRC and to determine the apoptosis inducing effects of Y1R antagonist, BIBO 3304 trifluoroacetate (BIBO), in CT26 colon carcinoma cells. Methods: Correlation between NPY expression and cell cycle and apoptosis-related genes were analyzed in cBioPortal for cancer genomics with a sample number of 594 CRC patients from the cancer genome atlas database (TCGA). Based on the TCGA database, 16 apoptosis-related genes (11 proapoptotic and 5 antiapoptotic) were checked. The effect of Y1R blocker (BIBO, Bio-Techne, MN) on CT26 (ATCC) cell proliferation, apoptosis and cell cycle progression was determined by performing in vitro cell proliferation assay and flow cytometry. Results and Conclusion: NPY expression in CRC shows a positive correlation with pro-survival/anti-apoptotic genes (BCL2, BCL2L1, BCL2L2, BCL2A1, MCL1) and negative correlation with key genes associated with the induction of cellular apoptosis (GZMB, TRIB3, TPX2, BAX, BAK1, BAD, BID, BIK, BOK, HRK) in CRC. Decreased cell proliferation and increased apoptosis was observed in CT26 mouse CRC cells upon inhibition of Y1R. An increased number of CT26 cells in early and mid-apoptotic phase was observed upon treatment with Y1R antagonist, BIBO, compared to untreated cells. In addition, cell cycle analysis indicated an increase in cell numbers in the G1/S cell cycle transition phase in the BIBO treated group. Our findings therefore indicate that treatment of CT26 CRC cells with Y1R blocker results in cell cycle arrest, which provides an opportunity for the cells to either undergo repair mechanisms or follow the apoptotic pathway. Blocking the actions of NPY by Y1R blockers thus may be a promising therapeutic approach in CRC patients. Citation Format: Sooraj Kakkat, Steven McClellan, Debanjan Chakroborty, Chandrani Sarkar. Selective blockade of neuropeptide Y receptor 1 induces cell cycle arrest and promotes apoptosis in colon cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1424.

Abstract 1477: TICRR is a prognosis biomarker associated with RNA epigenetic modification, DDR pathway, and RNA metabolism of lung adenocarcinoma

Abstract Background: TOPBP1 interacting checkpoint and replication regulator (TICRR), a hub gene of the Cdk2-mediated initiation step of DNA replication, has been identified as a prognostic biomarker in papillary renal cell carcinoma (PRCC). Nevertheless, there are few studies on the comprehensive analysis between mRNA expression of TICRR and lung adenocarcinoma (LUAD). Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database of LUAD were acquired to analyze the mRNA expression between tumor and normal tissues, survival prognosis, and clinicopathology characters. The GO, KEGG, and gene set enrichment analysis (GSEA) were performed using the R package. The correlation of TICRR with immune cell infiltration, RNA epigenetic modification, DDR pathway, and RNA metabolism of LUAD were further explored using TCGA and GEO database. Results: TICRR was confirmed significantly upregulated in several cancers, like LUAD, Lung squamous cell carcinoma (LUSC), Uterine Corpus Endometrial Carcinoma (UCEC), except for Prostate adenocarcinoma (PRAD), Thyroid carcinoma (THCA), which was downregulated in tumor tissues. Cox analysis indicated the overexpression of TICRR was related to poor survival in several cancers. The KEGG enrichment showed TICRR expression positively related to cell cycle, homologous recombination, mismatch repair, DNA replication, and cysteine metabolism in LUAD. Pathway enrichment showed a close relationship with spliceosome, oxidative phosphorylation, and ubiquitin-mediated proteolysis. Immune infiltration analysis revealed TICRR expression was negatively correlated with B cell expression, immune score, stromal score, and immunostimulators like IL2 (P&amp;lt;0.001), and positively correlated with neutrophil cell expression, immune inhibitors like PD-L1 and CTLA4. Interestingly, high mRNA expression of TICRR correlates with DDR pathway signature (37 genes), 37 m6A/m5C regulated genes, and some metabolism-regulated genes. Single-cell analysis of six LUAD samples showed that TICRR was significantly enriched in macrophage and T cells. Conclusions: TICRR has been identified to be a prognosis biomarker in LUAD, which is involved in immune activation, pathway transportation, RNA modification, and tumor energy metabolism. TICRR can be used as a promising therapeutic target and prognosis indicator for LUAD. Citation Format: Xunbo Zheng, Jun Guan, Chenteng Chen, Li Han, Hanxing Huang. TICRR is a prognosis biomarker associated with RNA epigenetic modification, DDR pathway, and RNA metabolism of lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1477.

MP04-03 EXOSOMAL LNCRNA BCYRN1 CAN BE A TARGET FOR DIAGNOSIS AND THERAPY IN RENAL CELL CARCINOMA

You have accessJournal of UrologyCME1 Apr 2023MP04-03 EXOSOMAL LNCRNA BCYRN1 CAN BE A TARGET FOR DIAGNOSIS AND THERAPY IN RENAL CELL CARCINOMA Hirofumi Yoshino, Shuichi Tatarano, and Hideki Enokida Hirofumi YoshinoHirofumi Yoshino More articles by this author , Shuichi TataranoShuichi Tatarano More articles by this author , and Hideki EnokidaHideki Enokida More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003215.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Exosomes are 40-100 nm nano-sized extracellular vesicles, released from many cell types into the extracellular space and transfer their component to recipient cells. We recently reported the method to collect exosomes from cell lysates and human serum by a spin column-based method in in a relatively short time, and the clinical significance that MYO15A was significantly upregulated in exosomes from renal cell carcinoma (RCC) patient’s sera compared with normal controls. In this study, we focused on one of long non-coding RNAs, BCYRN1, in RCCs. METHODS: Bioinformatic analysis was performed about clinical significance of BCYRN1 by using the database of The Cancer Genome Atlas (TCGA). Then, we performed RT-qPCR analysis of exosomes from clinical patients’ sera. Loss of function assays were performed in RCC cells (786-O, A498) on cell proliferation, cell migration and cell invasion in vitro and in vivo. RESULTS: The analyses with TCGA database indicated that high expression of BCYRN1 was significantly associated with a poorer outcome in RCC. RT-qPCR analysis of exosomes from clinical patients’ sera showed that BCYRN1 was significantly upregulated (p=0.0134) in RCC patients (n=35) compared to that in healthy controls (n=19). Moreover, BCYRN1 expression in patients with ≥T2a (n=9) was significantly higher (p=0.0404) than that in ≤T1b (n=25). Loss-of-function study by using si-RNAs of BCYRN1 suppressed proliferative, migratory, and invasive activities in RCC cells. In addition, BCYRN1 knockdown inhibited tumor growth in xenograft assay. CONCLUSIONS: It was suggested that exosomal BCYRN1 can be a novel diagnosis marker, and that BCYRN1 can be a new therapeutic target in RCCs. The identification of novel target for diagnosis and therapy may lead to a better understanding of RCC and the development of new therapeutic strategies to treat this disease. Source of Funding: none © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e34 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hirofumi Yoshino More articles by this author Shuichi Tatarano More articles by this author Hideki Enokida More articles by this author Expand All Advertisement PDF downloadLoading ...

MPP7 is a potential prognostic marker and is associated with cancer metabolism and immune infiltration in clear cell renal cell carcinoma: a bioinformatics analysis based on the TCGA database.

Metastasis is a major negative prognostic marker in clear cell renal cell carcinoma (ccRCC). Membrane palmitoylated proteins (MPPs) are a class of cell polarity-associated proteins that function in both cell-cell junction and adhesion. However, the relationship between MPP7 and the prognosis of ccRCC remains elusive. In this study, we aimed to investigate the associations between MPP7 expression with clinical prognosis of ccRCC using bioinformatics analyses. The messenger RNA (mRNA) and protein expression patterns of MPP7 in different cancer types were examined using The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases, with key clinical characteristics (TNM and pathological stages, pathological grade, survival status) included. A nomogram model using MPP7 expressions and other clinical factors was built to predict the survival probability. The Kaplan-Meier plotter and Cox regression were employed to investigate the clinical significance and prognostic value of MPP7 in ccRCC. MPP7 expression-associated signaling pathways with were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) tools. The Tumor Immune Estimation Resource (TIMER) database was used to investigate the correlation between MPP7 and the infiltration patterns of immune cells. By analyzing TCGA-kidney renal clear cell carcinoma (TCGA-KIRC) and HPA databases, we found that MPP7 was differentially expressed in tumor tissues and adjacent normal tissues (P<0.001). The MPP7 expression patterns were associated with pathological stage (P<0.001), histological grade (P<0.01), and survival status (P<0.001). Using nomogram model, Cox regression and survival analysis, it showed that MPP7 expressions combined with key clinical factors could accurately predict the clinical prognosis. The promoter methylation patterns of MPP7 were correlated with the clinical factors of ccRCC patients. Furthermore, the KEGG and GO analyses demonstrated that MPP7 is associated with mitochondrial oxidative metabolism. MPP7 expression was associated with multiple types of immune cells and correlated with the enrichment of these cells. MPP7 is a critical gene links with ccRCC prognosis and is associated with tumor immune status and metabolism. MPP7 could become a potential biomarker and important therapeutic target for ccRCC patients.

KIF11 is a potential prognostic biomarker and therapeutic target for adrenocortical carcinoma.

Adrenocortical carcinoma (ACC) is a rare endocrine neoplasia with poor prognosis. Emerging evidence suggests that kinesin family member 11 (KIF11) protein is overexpressed in several tumors and associated with the onset and progression of certain types of cancer; however, its biological functions and mechanisms in ACC progression have not been studied yet. Therefore, this study evaluated the clinical significance and therapeutic potential of the KIF11 protein in ACC. The Cancer Genome Atlas (TCGA) database (n=79) and Genotype Tissue Expression (GTEx) database (n=128) were utilized to explore the expression of KIF11 in ACC and normal adrenal tissues. The TCGA datasets were then data mined and statistically analyzed. R survival analysis and univariate and multivariate Cox regression analyses were used to evaluate the effect of KIF11 expression on the survival rates, and a nomogram was used to predict its impact on prognosis. The clinical data from 30 ACC patients' from Xiangya Hospital were also analyzed. The effects of KIF11 on the proliferation and invasion of ACC NCI-H295R were further validated in vitro. Analytical data from the TCGA and GTEx databases showed that KIF11 expression was upregulated in ACC tissues and associated with T (primary tumor), and M (metastasis) and stages of tumor progression. Increased KIF11 expression was significantly associated with shorter overall survival, disease-specific survival, and progression-free intervals. Clinical data from Xiangya Hospital illustrated that increased KIF11 had a significantly positive correlation with shorter overall survival, T and pathological stages, and tumor recurrence risk. Monastrol, a specific inhibitor of KIF11, was further confirmed to significantly inhibit the proliferation and invasion of ACC NCI-H295R cell in vitro. The nomogram demonstrated KIF11 was an excellent predictive biomarker in patients with ACC. The findings demonstrate that KIF11 could be a predictor of poor prognosis and thus possibly serve as a novel therapeutic target for ACC.

CD4+ conventional T cells-related genes signature is a prognostic indicator for ovarian cancer.

It is believed that ovarian cancer (OC) is the most deadly form of gynecological cancer despite its infrequent occurrence, which makes it one of the most salient public health concerns. Clinical and preclinical studies have revealed that intratumoral CD4+ T cells possess cytotoxic capabilities and were capable of directly killing cancer cells. This study aimed to identify the CD4+ conventional T cells-related genes (CD4TGs) with respect to the prognosis in OC. We obtained the transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD4TGs were first identified from single-cell datasets, then univariate Cox regression was used to screen prognosis-related genes, LASSO was conducted to remove genes with coefficient zero, and multivariate Cox regression was used to calculate riskscore and to construct the CD4TGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), decision curve analysis (DCA), nomogram, and calibration were made to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. The role of riskscore has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy. A risk signature with 11 CD4TGs in OC was finally established in the TCGA database and furtherly validated in several GEO cohorts. High riskscore was significantly associated with a poorer prognosis and proven to be an independent prognostic biomarker by multivariate Cox regression. The 1-, 3-, and 5-year ROC values, DCA curve, nomogram, and calibration results confirmed the excellent prediction power of this model. Compared with the reported risk models, our model showed better performance. The patients were grouped into high-risk and low-risk subgroups according to the riskscore by the median value. The low-risk group patients tended to exhibit a higher immune infiltration, immune-related gene expression and were more sensitive to immunotherapy and chemotherapy. Collectively, our findings of the prognostic value of CD4TGs in prognosis and immune response, provided valuable insights into the molecular mechanisms and clinical management of OC.

Upregulation of the ferroptosis-related STEAP3 gene is a specific predictor of poor triple-negative breast cancer patient outcomes.

This study was designed to assess ferroptosis regulator gene (FRG) expression patterns in patients with TNBC based on data derived from The Cancer Genome Atlas (TCGA). Further, it was utilized to establish a TNBC FRG signature, after which the association between this signature and the tumor immune microenvironment (TIME) composition was assessed, and relevant prognostic factors were explored. The TCGA database was used to obtain RNA expression datasets and clinical information about 190 TNBC patients, after which a prognostic TNBC-related FRG signature was established using a least absolute shrinkage and selection operator (LASSO) Cox regression approach. These results were validated with separate data from the Gene Expression Omnibus (GEO). The TNBC-specific prognostic gene was identified via this method. The STEAP3 was then validated through Western immunoblotting, immunohistochemical staining, and quantitative real-time polymerase chain reaction (RT-qPCR) analyses of clinical tissue samples and TNBC cell lines. Chemotherapy interactions and predicted drug sensitivity studies were investigated to learn more about the potential clinical relevance of these observations. These data revealed that 87 FRGs were differentially expressed when comparing TNBC tumors and healthy tissue samples (87/259, 33.59%). Seven of these genes (CA9, CISD1, STEAP3, HMOX1, DUSP1, TAZ, HBA1) are significantly related to the overall survival of TNBC patients. Kaplan-Meier analyses and established FRG signatures and nomograms identified CISD1 and STEAP3 genes of prognostic relevance. Prognostic Risk Score values were positively correlated with the infiltration of CD4+ T cells (p = 0.001) and myeloid dendritic cells (p =0.004). Further evidence showed that STEAP3 was strongly and specifically associated with TNBC patient OS (P<0.05). The results above were confirmed by additional examinations of STEAP3 expression changes in TNBC patient samples and cell lines. High STEAP3 levels were negatively correlated with half-maximal inhibitory concentration (IC50) values for GSK1904529A (IGF1R inhibitor), AS601245 (JNK inhibitor), XMD8-85 (Erk5 inhibitor), Gefitinib, Sorafenib, and 5-Fluorouracil (P < 0.05) in patients with TNBC based on information derived from the TCGA-TNBC dataset. In the present study, a novel FRG model was developed and used to forecast the prognosis of TNBC patients accurately. Furthermore, it was discovered that STEAP3 was highly overexpressed in people with TNBC and associated with overall survival rates, laying the groundwork for the eventually targeted therapy of individuals with this form of cancer.

A novel lysosome-related gene signature coupled with gleason score for prognosis prediction in prostate cancer.

Background: Prostate cancer (PCa) is highly heterogeneous, which makes it difficult to precisely distinguish the clinical stages and histological grades of tumor lesions, thereby leading to large amounts of under- and over-treatment. Thus, we expect the development of novel prediction approaches for the prevention of inadequate therapies. The emerging evidence demonstrates the pivotal role of lysosome-related mechanisms in the prognosis of PCa. In this study, we aimed to identify a lysosome-related prognostic predictor in PCa for future therapies. Methods: The PCa samples involved in this study were gathered from The Cancer Genome Atlas database (TCGA) (n = 552) and cBioPortal database (n = 82). During screening, we categorized PCa patients into two immune groups based on median ssGSEA scores. Then, the Gleason score and lysosome-related genes were included and screened out by using a univariate Cox regression analysis and the least absolute shrinkage and selection operation (LASSO) analysis. Following further analysis, the probability of progression free interval (PFI) was modeled by using unadjusted Kaplan-Meier estimation curves and a multivariable Cox regression analysis. A receiver operating characteristic (ROC) curve, nomogram and calibration curve were used to examine the predictive value of this model in discriminating progression events from non-events. The model was trained and repeatedly validated by creating a training set (n = 400), an internal validation set (n = 100) and an external validation (n = 82) from the cohort. Results: Following grouping by ssGSEA score, the Gleason score and two LRGs-neutrophil cytosolic factor 1 (NCF1) and gamma-interferon-inducible lysosomal thiol reductase (IFI30)-were screened out to differentiate patients with or without progression (1-year AUC = 0.787; 3-year AUC = 0.798; 5-year AUC = 0.772; 10-year AUC = 0.832). Patients with a higher risk showed poorer outcomes (p < 0.0001) and a higher cumulative hazard (p < 0.0001). Besides this, our risk model combined LRGs with the Gleason score and presented a more accurate prediction of PCa prognosis than the Gleason score alone. In three validation sets, our model still achieved high prediction rates. Conclusion: In conclusion, this novel lysosome-related gene signature, coupled with the Gleason score, works well in PCa for prognosis prediction.

Over-expression of RRM2 predicts adverse prognosis correlated with immune infiltrates: A potential biomarker for hepatocellular carcinoma.

Ribonucleotide reductase regulatory subunit M2 (RRM2) has been reported to be an oncogene in some malignant tumors, such as lung adenocarcinoma, oral squamous cell carcinoma, glioblastoma, and breast cancer. However, the clinical significance of RRM2 in hepatocellular carcinoma has been less studied. The aim of this study was to assess the importance of RRM2 in hepatocellular carcinoma (HCC) based on the Cancer Genome Atlas (TCGA) database. The RRM2 expression levels and clinical features were downloaded from the TCGA database. Immunohistochemistry results between tumor tissues and normal tissues were downloaded from the Proteinatlas database. Meanwhile, the expression levels of RRM2 in tumor and paraneoplastic tissues were further verified by qRT-PCR and Western Blotting. Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein-interactions (PPI) network were constructed to analyze RRM2-related downstream molecules. In addition, RRM2 expression-related pathways performed by gene set enrichment analysis (GSEA). Association analysis of RRM2 gene expression and immune infiltration was performed by single-sample GSEA (ssGSEA). The RRM2 expression level in tumor tissues was higher than normal tissues (P <0.001). The elevated expression of RRM2 in HCC was significantly correlated with T stage (P <0.05), pathologic stage (P <0.05), tumor status (P <0.05), histologic grade (P<0.001), and AFP (P <0.001). HCC with higher RRM2 expression was positively associated with worse OS (overall survival), PFS (progression-free survival), and DSS (disease-specific survival). In the univariate analysis, the expression of RRM2, T stage, M stage, pathologic stage, and tumor status were negatively correlated with OS (P <0.05). Further analysis using multivariate Cox regression showed that tumor status (P<0.01) and RRM2 expression (P<0.05) were independent prognostic factors of OS in HCC. GO/KEGG analysis showed that the critical biological process (chromosome condensation and p53 signaling pathway) might be the possible function mechanism in promoting HCC. Moreover, GSEA showed that several pathways were enriched in RRM2 high-expression samples, including PD-1 signaling, cell cycle, P27 pathway, and T cell receptor signaling pathway. RRM2 was significantly correlated with the infiltration level of CD8 T cells, Cytotoxic cells, DCs, Neutrophils, NK cells, and T helper cells (P <0.05). Over-expression of RRM2 predict adverse prognosis and is correlated with immune infiltrates in HCC. RRM2 may be a significant molecular biomarker for HCC diagnosis and prognosis.

Establishment and validation of a cuproptosis-related lncRNA signature that predicts prognosis and potential targeted therapy in hepatocellular carcinoma

ABSTRACT Background: Cuproptosis is a recently identified form of programmed cell death and could be a new direction for tumour therapy, and it has important clinical implications. Long non-coding RNAs (lncRNAs) can intervene in diverse biological processes and have a decisive role in hepatocellular carcinoma (HCC). However, how cuproptosis-related lncRNAs (CRLs) participate in regulating HCC has yet to be recognised. This study aimed to establish and validate a prognostic signature of CRLs and to analyse their clinical value in HCC patients. Methods: To analyse the function of CRLs in the prognosis of HCC, RNA sequencing data, mutation data, and clinically relevant data were collected from the Cancer Genome Atlas Database (TCGA). Then, TCGA cohort was randomly divided into training and test sets. The training set was utilized to define prognostic signature of CRLs using bioinformatics methods. Subsequently, we verified the accuracy of this prognostic signature in the test set. Finally, we performed immune-related analysis, the half-maximal inhibitory concentration (IC50) prediction, gene set enrichment analysis, and tumour mutational burden (TMB) analysis. Results: We established a prognostic signature for the CRLs (SNHG4, AC026412.3, AL590705.3, and CDKN2A-DT). This signature-based risk group displayed an accurate predictive ability for the survival time of patients with HCC. We observed discrepancies in immune cells, immune function, the expression level of genes related to immune checkpoints, and TMB in high- and low-risk groups. Conclusion: This CRLs prognostic signature could predict clinical outcomes in patients with HCC as well as the efficacy of targeted and therapy immunotherapy.

Heterogeneous pattern of gene expression driven by TTN mutation is involved in the construction of a prognosis model of lung squamous cell carcinoma.

To investigate the impact that TTN mutation had on the gene heterogeneity expression and prognosis in patients with lung adenocarcinoma. In this study, the Cancer Genome Atlas (TCGA) dataset was used to analyze the TTN mutations in lung adenocarcinoma. Lung adenocarcinoma data was collected from the TCGA database, clinical information of patients was analyzed, and bioinformatics statistical methods were applied for mutation analysis and prognosis survival analysis. The results were verified using the GEO dataset. The incidence of TTN mutations in lung adenocarcinoma was found to be 73%, and it was related to the prognosis of lung adenocarcinoma. Ten genes were screened with significant contributions to prognosis. A prognosis model was constructed and verified by LASSO COX analysis in the TCGA and GEO datasets based on these ten beneficial factors. The independent prognostic factor H2BC9 for TTN mutation-driven gene heterogeneity expression was screened through multi-factor COX regression analysis. Our data showed that the gene heterogeneity expression, which was driven by TTN mutations, prolonged the survival of lung adenocarcinoma patients and provided valuable clues for the prognosis of TTN gene mutations in lung adenocarcinoma.

Inhibition of HIST1H2AB suppresses the proliferation of lung adenocarcinoma.

Lung adenocarcinoma is one of the common causes of cancer-related deaths worldwide. Histone cluster 1 H2A family member b (HIST1H2AB) is a member of the histone H2A family. Bioinformatic analyses have revealed that HIST1H2AB is highly expressed in some cancers and might be an oncogene. However, information on the function of HIST1H2AB in lung adenocarcinoma is limited. The expression of HIST1H2AB was analyzed in normal lung, lung adenocarcinoma and paracancerous tissues from The Cancer Genome Atlas (TCGA) database and immunohistochemistry staining. It was further verified in the relative cell lines using real-time quantitative polymerase chain reaction (RT-qPCR). When the adenocarcinoma cells lines (A549 and H1299) were successfully transfected with shHIST1H2AB or an empty plasmid packaged into a lentivirus, cell proliferation was detected using Celigo fluorescence cell-counting, colony formation and annexin V-allophycocyanin assays. Twenty nude mice were subcutaneously injected with A549 cells transfected with shHIST1H2AB or empty plasmid; the tumor size was recorded on day 25 and then measured every 3 days thereafter. The final tumor weight was measured on day 37. Significantly differentially expressed genes were analyzed using a human gene expression array. Furthermore, the potentially relevant genes were verified using RT-qPCR and western blotting. HIST1H2AB was highly expressed in lung adenocarcinoma tissues from TCGA database and immunohistochemistry staining. Similar results were seen in the lung adenocarcinoma cells. When the cells were successfully transfected with shHIST1H2AB or an empty plasmid, downregulation of HIST1H2AB inhibited the growth and promoted the apoptosis of lung adenocarcinoma cells. The xenograft results suggested that HIST1H2AB downregulation delayed tumor growth and reduced tumor weight. Moreover, interferon signaling pathway and four genes (HMGB1, FOXM1, F2RL1 and SLC4A7) might be regulated by HIST1H2AB in the development of lung adenocarcinoma as indicated through gene expression array, RT-qPCR and western blotting analyses. HIST1H2AB acts as an oncogenic protein and HIST1H2AB inhibition suppresses the proliferation of lung adenocarcinoma cells. It may be a novel target for lung adenocarcinoma therapy.

GRAP2: A Novel Immune-Related Prognosis Biomarker in Cervical Cancer

Background: Immune infiltration of the tumor microenvironment offers unlimited possibilities for therapeutic strategies in cervical cancer, where GRAP2 is an adaptor protein engaged in diverse signal activations. However, uncertainty exists regarding GRAP2’s prognostic significance and its relationship to immune infiltration. Methods: The data on cervical cancer cases were downloaded from The Cancer Genome Atlas (TCGA) database. The ESTIMATE computational technique was utilized to calculate the amount of immunological and stromal components, which helped us to identify the differential expression genes (DEGs). Among them, GRAP2 was considered to be related to overall survival based on a protein-protein interaction network and a univariate Cox regression analysis. Thus, based on the Gene Expression Omnibus (GEO) and TCGA databases, we evaluated GRAP2’s influence on clinical prognosis. Furthermore, GRAP2 expression was analyzed by Gene Set Enrichment Analysis (GSEA). Finally, we used CIBERSORTx analysis to assess the proportion of tumor-infiltrating immune cells (TICs) and the connection between GRAP2 and the tumor immune microenvironment. Results: ESTIMATEScore was associated with cervical cancer patient’s prognosis. There are 791 DEGs and 11 potential key genes were identified including GRAP2. In survival analyses with clinical information, We found that the GRAP2 high expression group exhibited a significantly longer overall survival (OS) than the low expression group and that the gene expression gradually declined as the Federation of International of Gynecologists and Obstetricians (FIGO) stage and M classification increased. GRAP2 was strongly linked with immunity and metabolism, according to GSEA. Finally, we discovered that 11 different TIC types and GRAP2 expressions were linked. Conclusions: GRAP2 may be a novel immune-related prognosis biomarker in cervical cancer.