Dataset Information

Prognostic value and co-expression patterns of metabolic pathways in cancers.

ABSTRACT:

Background

Abnormal metabolic pathways have been considered as one of the hallmarks of cancer. While numerous metabolic pathways have been studied in various cancers, the direct link between metabolic pathway gene expression and cancer prognosis has not been established.

Results

Using two recently developed bioinformatics analysis methods, we evaluated the prognosis potential of metabolic pathway expression and tumor-vs-normal dysregulations for up to 29 metabolic pathways in 33 cancer types. Results show that increased metabolic gene expression within tumors corresponds to poor cancer prognosis. Meta differential co-expression analysis identified four metabolic pathways with significant global co-expression network disturbance between tumor and normal samples. Differential expression analysis of metabolic pathways also demonstrated strong gene expression disturbance between paired tumor and normal samples.

Conclusion

Taken together, these results strongly suggested that metabolic pathway gene expressions are disturbed after tumorigenesis. Within tumors, many metabolic pathways are upregulated for tumor cells to activate corresponding metabolisms to sustain the required energy for cell division.

SUBMITTER: Zhang D

PROVIDER: S-EPMC7771089 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Prognostic value and co-expression patterns of metabolic pathways in cancers.

Zhang Dan D Guo Yan Y Xie Ni N

BMC genomics 20201229 Suppl 11

<h4>Background</h4>Abnormal metabolic pathways have been considered as one of the hallmarks of cancer. While numerous metabolic pathways have been studied in various cancers, the direct link between metabolic pathway gene expression and cancer prognosis has not been established.<h4>Results</h4>Using two recently developed bioinformatics analysis methods, we evaluated the prognosis potential of metabolic pathway expression and tumor-vs-normal dysregulations for up to 29 metabolic pathways in 33 c ...[more]

PMID: 33372594

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Project description:Breast cancer is the most common cause of cancer death among women worldwide. Localized breast cancer can be cured by surgery and adjuvant therapy, but mortality remains high for tumors that metastasize early. Type IV collagen is a basement membrane protein, and breach of this extracellular matrix structure is the first step of cancer invasion. Type IV collagen is found in the stroma of many cancers, but its role in tumor biology is unclear. Here, expression of type IV collagen in the stroma of small breast cancers was analyzed, correlated to clinically used prognostic biomarkers and patient survival. The findings were further validated in an independent gene expression data cohort. Tissue samples from 1,379 women with in situ and small invasive breast cancers (≤15 mm) diagnosed in 1986-2004 were included. Primary tumor tissue was collected into tissue microarrays. Type IV collagen expression in tissues was visualized using immunohistochemistry. Gene expression data was extracted from the Cancer Genome Atlas database. Out of 1,379 women, 856 had an invasive breast cancer and type IV collagen staining was available for 714 patients. In Kaplan-Meier analysis high type IV collagen expression was significantly associated (p = 0.026) with poorer breast cancer specific survival. There was no correlation of type IV collagen expression to clinically used prognostic biomarkers. High type IV collagen expression was clearly associated to distant metastasis (p = 0.002). In an external validation cohort (n = 1,104), high type IV collagen mRNA expression was significantly (p = 0.041) associated with poorer overall survival, with overexpression of type IV collagen mRNA in metastatic tissue. Stromal type IV collagen expression in the primary tumor correlates to poor breast cancer specific survival most likely due to a higher risk of developing distant metastasis. This ECM protein may function as biomarker to predict the risk of future metastatic disease in patients with breast cancers.

Project description:BackgroundThe Dickkopf1 (DKK1) gene encodes a protein that belongs to the Dickkopf family. The protein can inhibit the Wnt signaling pathway which plays a key role in the carcinogenesis and progression of various types of cancers. Based on this, we hypothesized that the differential expression of DKK1 may figure significantly in cancers by regulating Wnt signaling pathway transduction. In this study, we conducted bioinformatics analysis to evaluate the prognostic and therapeutic value of DKK1 expression level in human cancers.MethodsThe expression level was analyzed by using the Oncomine database and Gene Expression Profiling Interactive Analysis tool. The analysis of prognosis was conducted by using the UALCAN, Gene Expression Profiling Interactive Analysis (GEPIA), and DriverDBv3 databases. We also investigated using DKK1 promoter methylation to define cancer types through the UALCAN database. Meanwhile, the related functional networks of DKK1 were analyzed by using the GeneMANIA interactive tool and Cytoscape software. Furthermore, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis was conducted using the Metascape online website, and we used the cBioPotartal database to explored DKK1 expression, aberrant information, and the co-expression genes in the subgroups of lung cancer. Finally, we performed the overall survival (OS) meta-analysis of the DKK1 expression in lung squamous cell carcinoma (LUSC) via the Lung Cancer Explorer (LCE).ResultsDKK1 was differentially expressed in different types of human cancers. DKK1 was overexpressed in human cancers including head and neck squamous cell carcinoma (HNSC), LUSC, and pancreatic adenocarcinoma (PAAD). Overexpression of DKK1 indicated adverse OS in bladder urothelial carcinoma (BLCA), HNSC, and PADD, but no difference in OS was found between the LUSC and healthy groups. The high expression of DKK1 was also associated with shorter disease-free survival (DFS) in HNSC, LUSC, and PAAD. Gene regulation network analysis indicated that DKK1 was mainly involved in Wnt signaling pathways and several other signaling pathways.ConclusionsOur findings showed that DKK1 is significantly expressed in various cancers and could be a biomarker for targeted therapy and a predictor for prognosis of these specific cancers. The bioinformatics analysis revealed a significant overexpression of DKK1 in HNSC, LUSC, and PAAD, with DKK1 overexpression being associated with adverse outcome in these patients, but how DKK1 expression levels relate to hematological malignancies and prognosis is still unclear. These new insights into the function of DKK1 may provide a basis for new targeted drug therapy and an avenue for further investigation into the mechanisms underlying carcinogenesis of DKK1 in different cancer types.

Dataset Information

Prognostic value and co-expression patterns of metabolic pathways in cancers.

Background

Results

Conclusion

Publications

Prognostic value and co-expression patterns of metabolic pathways in cancers.

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