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Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer.

ABSTRACT: Epithelial ovarian cancer is by far the most lethal gynecological malignancy. The exploration of promising immunomarkers to predict prognosis in ovarian cancer patients remains challenging. In our research, we carried out an integrated bioinformatic analysis of genome expressions and their immune characteristics in the ovarian cancer microenvironment with validation in different experiments. We filtrated 332 differentially expressed genes with 10 upregulated hub genes from the Gene Expression Omnibus database. These genes were closely related to ovarian tumorigenesis. Subsequently, the survival and immune infiltration analysis demonstrated that the upregulation of five candidate genes, ITGB2, VEGFA, CLDN4, OCLN, and SPP1, were correlated with an unfavorable clinical outcome and increased immune cell infiltration in ovarian cancer. Of these genes, ITGB2 tended to be the gene most correlated with various immune cell infiltrations and had a strong correlation with significant M2 macrophages infiltration (r = 0.707, p = 4.71 × 10^-39), while it had a moderate correlation with CD4+/CD8+ T cells and B cells. This characteristic explains why the high expression of ITGB2 was accompanied by immune activation but did not reverse carcinogenesis. Additionally, we confirmed that ITGB2 was over-expressed in ovarian cancer tissues and was mainly located in cytoplasm, detected by Western blotting and the immunohistochemical method. In summary, ITGB2 may serve as a prognostic immunomarker for ovarian cancer patients.

SUBMITTER: Li C

PROVIDER: S-EPMC10047357 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer.

Li Chanyuan C Deng Ting T Cao Junya J Zhou Yun Y Luo Xiaolin X Feng Yanling Y Huang He H Liu Jihong J

Diagnostics (Basel, Switzerland) 20230318 6

Epithelial ovarian cancer is by far the most lethal gynecological malignancy. The exploration of promising immunomarkers to predict prognosis in ovarian cancer patients remains challenging. In our research, we carried out an integrated bioinformatic analysis of genome expressions and their immune characteristics in the ovarian cancer microenvironment with validation in different experiments. We filtrated 332 differentially expressed genes with 10 upregulated hub genes from the Gene Expression Om ...[more]

PMID: 36980477

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Project description:BackgroundOvarian cancer (OvCa) is a malignant disease of the female reproductive system with a high mortality rate. LncRNA has been confirmed to play a crucial role in the development and progression of various cancer types. Novel lncRNA ZFHX4-AS1 has been reported in several cancers, albeit its functional mechanisms in OvCa remain unclear.MethodsWith reference to the public databases and based on integrating bioinformatics analyses, we explored the expression of ZFHX4-AS1 and its roles in the prognosis of OvCa. We employed the Kaplan-Meier curves to investigate the outcome of patients with different ZFHX4-AS1 expressions. Furthermore, its biological function and the related hallmark pathways were assessed through Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, and Gene-set enrichment analysis (GSEA). We explored the correlation between lncRNA ZFHX4-AS1 and tumor-infiltrating immune cells through CIBERSORT. The immune checkpoints associated with lncRNA ZFHX4-AS1 and its related genes were investigated. The effect of lncRNA ZFHX4-AS1 on proliferation, invasion and migration of OvCa cells was verified through Cell Counting Kit (CCK)-8, colony formation, wound healing and transwell assays.ResultsThe expression of lncRNA ZFHX4-AS1 was upregulated in OvCa relative to that in normal tissues. Increased lncRNA ZFHX4-AS1 expression was associated with poor overall survival and progression-free survival in OvCa. The GO and KEGG pathway analyses revealed the role of lncRNA ZFHX4-AS1 in cell metabolism, protein synthesis, cell proliferation, and cell cycle. GSEA indicated the hallmark gene sets that were significantly enriched in the high and low expression groups. The CIBERSORT database revealed M2 macrophages, memory B-cells, naïve B cells, and activated NK cells were affected by lncRNA ZFHX4-AS1 expression (all P < 0.05). The expression of lncRNA ZFHX4-AS1 and its related differential genes MRPS11, NSA2, and MRPL13 were significantly correlated with the immune checkpoints. Knockdown of lncRNA ZFHX4-AS1 could inhibit the proliferation, invasion and migration of OvCa cells.ConclusionsThe results suggested that lncRNA ZFHX4-AS1 is a novel prognostic biomarker associated with cell proliferation, metabolism, infiltration, and distribution of tumor-infiltrating immune cells in OvCa, indicating that lncRNA ZFHX4-AS1 can be used as a potential therapeutic target for OvCa in the future.

Project description:Extracellular, cancer-specific methylated DNA has been shown to be a prognostic marker when detected in serum or plasma. In this study we investigated the effect of treating cancer cells with differentially methylated CpG DNA. When breast cancer cell lines were treated with methylated CpG DNA, a consistent upregulation of CHAC1 mRNA expression was observed. CHAC1 was recently described to be a novel component of the unfolded protein response pathway. To elucidate the role of CHAC1 mRNA expression in cancer in more detail, we analyzed expression of this gene in breast (n=107) and ovarian cancer (n=107) and found a strong correlation with tumor differentiation. Poorly differentiated tumors exhibited higher CHAC1 expression levels (p=0.004 for breast and p=0.031 for ovarian cancer). Additionally, hormone receptor (HR)-negative breast cancers (p<0.001) and advanced stage disease ovarian cancers (p=0.026) also demonstrated high CHAC1 mRNA levels. mRNA expression analysis of the two known CHAC1 isoforms showed a strong association of expression above the median with poor outcome in breast cancer patients in a multivariate analysis (isoform a: relative risk (RR) of death 3.2 (95% CI 1.6-6.5; p<0.01); RR of relapse 3.9 (95% CI 1.6-9.8; p<0.01); isoform b: relative risk (RR) of death 3.5 (95% CI 1.6-7.3; p<0.01); RR of relapse 6.6 (95% CI 2.4-18.5; p<0.01)). Univariate analysis in ovarian cancer showed that CHAC1 mRNA expression above the median was associated with a poor relapse free survival (p=0.03). In younger ovarian cancer patients (age < median age), a high CHAC1 mRNA expression was associated with overall survival (p=0.007) and relapse free survival (p=0.015). Finally, we show that downregulation of CHAC1 by small interfering RNA suppressed breast cancer cell migration and proliferation, whereas overexpression resulted in an observed increase in these cellular behaviours. This is the first report demonstrating that a gene (CHAC1) whose expression is triggered by methylated, but not unmethylated DNA, is involved in tumour biology. Human breast cancer cell lines (BT-20, Hs578T) were treated with methylated and unmethylated DNA oligos, and differentially expressed genes were identified between treatments with methylated and un-methylated oligos.

Project description:BackgroundOvarian cancer (OC) is one of the most lethal gynecologic malignancies and a leading cause of death in the world. Thus, this necessitates identification of prognostic biomarkers which will be helpful in its treatment.MethodsThe gene expression profiles from The Cancer Genome Atlas (TCGA) and GSE31245 were selected as the training cohort and validation cohort, respectively. The Kaplan-Meier (KM) survival analysis was used to analyze the difference in overall survival (OS) between high and low RB transcriptional corepressor 1 (RB1) expression groups. To confirm whether RB1 was an independent risk factor for OC, we constructed a multivariate Cox regression model. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses were conducted to identify the functions of differentially expressed genes (DEGs). The associations of RB1 with immune infiltration and immune checkpoints were studied by the Tumor Immune Estimation Resource (TIMER 2.0) and the Gene Expression Profiling Interactive Analysis (GEPIA). The immunohistochemistry (IHC) was performed to compare the expression level of RB1 in normal tissues and tumor samples, and to predict the prognosis of OC.ResultsThe KM survival curve of the TCGA indicated that the OS in the high-risk group was lower than that in the low-risk group (HR = 1.61, 95% CI: 1.28-2.02, P = 3×10-5), which was validated in GSE31245 (HR = 4.08, 95% CI: 1.21-13.74, P = 0.01) and IHC. Multivariate Cox regression analysis revealed that RB1 was an independent prognostic biomarker (HR = 1.66, 95% CI: 1.31-2.10, P = 2.02×10-5). Enrichment analysis suggested that the DEGs were mainly involved in cell cycle, DNA replication, and mitochondrial transition. The infiltration levels of fibroblast, neutrophil, monocyte and macrophage were positively correlated with RB1. Furthermore, RB1 was associated with immune checkpoint molecules (CTLA4, LAG3, and CD274). The IHC staining revealed higher expression of RB1 in tumor tissues as compared to that in normal tissues (P = 0.019). Overexpression of RB1 was associated with poor prognosis of OC (P = 0.01).ConclusionThese findings suggest that RB1 was a novel and immune-related prognostic biomarker for OC, which may be a promising target for OC treatment.

Dataset Information

Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer.

Publications

Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer.

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