Dataset Information

Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology.

ABSTRACT:

Aim

Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology.

Background

Colon cancer is one of lethal cancer in men and women. Treatment in advanced colon cancer is difficult and survival rate is low.

Methods

Gene expression profiles of children patients with non-preforated appendicitis in comparison with the samples with non- appendicitis abdominal pain are analysis via protein - protein interaction PPI and the critical compounds are introduced by STITCH.

Results

Six critical genes including MAPK3, AKT1, SRC, TP53, GAPDH, and ALB were identified as a possible biomarker panel related to colon cancer grade II to III transition. Among these critical genes roles of MAPK3, AKT1, SRC, TP53 are highlighted.

Conclusion

It was concluded that target therapy to regulate SRC and TP53 may be the effective therapeutic way to treatment of colon cancer and more researches in necessary to design drugs for these purposes.

SUBMITTER: Rostami-Nejad M

PROVIDER: S-EPMC6441480 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology.

Rostami-Nejad Mohammad M Rezaei Tavirani Sina S Mansouri Vahid V Jahani-Sherafat Somayeh S Moravvej Farshi Hamideh H

Gastroenterology and hepatology from bed to bench 20190101 1

<h4>Aim</h4>Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology.<h4>Background</h4>Colon cancer is one of lethal cancer in men and women. Treatment in advanced colon cancer is difficult and survival rate is low.<h4>Methods</h4>Gene expression profiles of children patients with non-preforated appendicitis in comparison with the samples with non- appendicitis abdominal pain are analysis via protein - protein interaction PPI and the critical c ...[more]

PMID: 30949321

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Project description:Due to the extremely intrinsic heterogeneity among glioma patients, the outcomes of these patients are tremendously different. Therefore, the exploitation of novel biomarker classification of glioma is vitally important for deep insight into the essence and predicting the prognosis of glioma. We aim to analyze the correlation between TP73 mRNA expression, DNA methylated alteration and the prognosis of WHO grade II/III glioma, utilizing bioinformatics to evaluate its significance as a risk-factor in predicting the prognosis of these glioma patients. The analysis found that TP73 expression was positively correlated with the grade of glioma, and showed a strong correlation with glioma molecular classification, which revealed significantly higher TP73 expression in IDH-wildtype than in IDH-mutant subtype of WHO grade II/III glioma. Cox regression analysis indicated that high expression of TP73 shared an independent high-risk factor impacting the prognosis of WHO grade II/III glioma. We discovered 8 DNA promoter methylation sites with prognostic significance, which were negatively associated with TP73 expression, and positively associated with beneficial overall survival (OS) and progression-free survival (PFS). Integrating with four independent glioma datasets, subsequent Meta-analysis verified that low expression of TP73 was closely related to favorable OS, especially in IDH-mutant subtype. Moreover, we found that 1p/19qCodel /TP73low subgroup shared the most favorable OS, 1p/19qNon-codel /TP73high subgroup suffered the worst OS. Meanwhile, the enrichment analysis of TP73-related differential mRNAs demonstrated that TP73 aberration in WHO grade II/III glioma might be closely related to cell cycle and P53 signaling pathways. Finally, TP73 expression of 53 glioma specimens was measured by qRT-PCR, which was consistent with the previous analytical result, and TP73 high-expression subgroup suffered worse PFS than TP73 low-expression subgroup. In summary, our funding supports that TP73 gene can perform as a reliable biomarker to evaluate the survival outcome of patients diagnosed with WHO grade II/III glioma.

Project description:Grade II and III gliomas are heterogeneous and aggressive diseases. More efficient prognosis models and treatment methods are needed. This study aims to construct a new risk model and propose a new strategy for grade II and III gliomas. The data were downloaded from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), gene set enrichment analysis (GSEA), and the EMTome website for analysis. The Human Cell Landscape website and the Genomics of Drug Sensitivity in Cancer website were used for single-cell analysis and drug susceptibility analysis. Gene set enrichment analysis, gene function enrichment analysis, univariate and multivariate Cox regression analyses, Pearson's correlation analysis, log-rank test, Kaplan-Meier survival analysis, and ROC analysis were performed. We constructed an immune-related prognostic model associated with the isocitrate dehydrogenase 1 (IDH1) mutation status. By analyzing the immune microenvironment of patients with different risk scores, we found that high-risk patients were more likely to have an inflammatory immune microenvironment and a higher programmed death ligand-1 (PD-L1) expression level. Epithelial-mesenchymal transition (EMT)-related gene sets were significantly enriched in the high-risk group, and the epithelial-mesenchymal transition phenotype was associated with a decrease in CD8+ T cells and an increase in M2 macrophages. Transforming growth factor-β (TGF-β) signaling was the most important signaling in inducing epithelial-mesenchymal transition, and TGFB1/TGFBR1 was correlated with an increase in CD8+ T cytopenia and M2 macrophages. Survival analysis showed that simultaneous low expression of TGFBR1 and PD-L1 had better survival results. Through single-cell analysis, we found that TGFB1 is closely related to microglia and macrophages, especially M2 macrophages. Finally, we discussed the sensitivity of TGFB1 inhibitors in gliomas using cell line susceptibility data. These results demonstrated a potential immunotherapy strategy in combination with the TGFB1/TGFBR1 inhibitor and PD-1/PD-L1 inhibitor for grade II and III gliomas.

Dataset Information

Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology.

Aim

Background

Methods

Results

Conclusion

Publications

Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology.

Similar Datasets

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