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Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma.

ABSTRACT: Aim:Anaplastic thyroid carcinoma (ATC) is the most lethal thyroid malignancy. Identification of novel drug targets is urgently needed. Materials & Methods:We re-analyzed several GEO datasets by systematic retrieval and data merging. Differentially expressed genes (DEGs) were filtered out. We also performed pathway enrichment analysis to interpret the data. We predicted key genes based on protein-protein interaction networks, weighted gene co-expression network analysis and genes' cancer/testis expression pattern. We also further characterized these genes using data from the Cancer Genome Atlas (TCGA) project and gene ontology annotation. Results:Cell cycle-related pathways were significantly enriched in upregulated genes in ATC. We identified TRIP13, DLGAP5, HJURP, CDKN3, NEK2, KIF15, TTK, KIF2C, AURKA and TPX2 as cell cycle-related key genes with cancer/testis expression pattern. We further uncovered that most of these putative key genes were critical components during chromosome segregation. Conclusion:We predicted several key genes harboring potential therapeutic value in ATC. Cell cycle-related processes, especially chromosome segregation, may be the key to tumorigenesis and treatment of ATC.

SUBMITTER: Liu M

PROVIDER: S-EPMC6203939 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma.

Liu Mu M Qiu Yu-Lu YL Jin Tong T Zhou Yin Y Mao Zhi-Yuan ZY Zhang Yong-Jie YJ

PeerJ 20181024

<h4>Aim</h4>Anaplastic thyroid carcinoma (ATC) is the most lethal thyroid malignancy. Identification of novel drug targets is urgently needed.<h4>Materials & methods</h4>We re-analyzed several GEO datasets by systematic retrieval and data merging. Differentially expressed genes (DEGs) were filtered out. We also performed pathway enrichment analysis to interpret the data. We predicted key genes based on protein-protein interaction networks, weighted gene co-expression network analysis and genes' ...[more]

PMID: 30386706

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Project description:The current outbreak of coronavirus disease (COVID-19) has been affecting millions of people and has caused devastating mortality worldwide. Moreover, it is to be noted that cytokine storm has become an important cause for the rising mortality. However, the efforts for the development of drugs, vaccines and treatment has also been intervened due to poor understanding of host's defense mechanism and also due to the development of cytokine storm against this viral infection. Thus, a deeper understanding of the mechanism behind the immune dysregulation and cytokine storm development might give us clues for the clinical management of the severe cases. Hence, we have implemented differential gene expression analysis together with protein-protein interaction and Gene Ontology (GO) studies with the help of Severe Acute respiratory syndrome coronavirus (SARS-CoV) data sets such as GSE1739 and GSE33267 to give us more knowledge on the host immune response for the pathogenic coronavirus which in turn reduces the mortality. A total of 79 differentially-expressed genes (DEGs) were identified in our data set using the filters such as P-value and log2 fold change values of less than 0.05 and 1.5 respectively. Further, network analysis and GO studies showed that differential expression of two hub genes namely ELANE and LTF which could induce higher levels of pro-inflammatory cytokines in the lungs. We are certain that differential expression of ELANE and LTF results in an excessive inflammatory reaction known as the cytokine storm and ultimately leading to death. Therefore, targeting these key drivers of cytokine storm genes appears to be the potential therapeutic targets for combating the Severe Acute respiratory syndrome coronavirus - 2 (SARS-CoV-2) infection ultimately resulting in reduced mortality. Indeed, this predictive view may open new insights for designing an immune intervention for COVID-19 in the near future resulting in the mitigation of mortality rate.

Project description:Anaplastic thyroid cancer (ATC) is one of the deadliest human cancers and it is less than 2% of thyroid carcinomas (TCs). The standard treatment of ATC includes surgical debulking, accelerated hyperfractionated external beam radiation therapy (EBRT), and chemotherapy, in particular with cisplatin or doxorubicin, achieving about 10 months of median survival. Since ATC is a rare and aggressive tumor, it is still challenging to predict the patient clinical therapy responsiveness. Several genetic mutations have been described in ATC, involved in different molecular pathways linked to tumor progression, and novel therapies acting on these molecular pathways have been investigated, to improve the quality of life in these patients. Here we review the new targeted therapy of ATC. We report interesting results obtained with molecules targeting different pathways: angiogenesis (vandetanib, combretastatin, sorafenib, lenvatinib, sunitinib, CLM94, CLM3, etc.); EGFR (gefitinib, docetaxel); BRAF (dabrafenib/trametinib, vemurafenib); PPARγ agonists (rosiglitazone, pioglitazone, efatutazone); PD-1 and PD-L1 (pembrolizumab); TERT. To escape resistance to monotherapies, the evaluation of combination strategies with radiotherapy, chemotherapy, or targeted drugs is ongoing. The results of clinical trials with dabrafenib and trametinib led to the approval from FDA of this combination for patients with BRAF V600E mutated ATC with locally advanced, unresectable, or metastatic ATC. The anti-PD-L1 antibody immunotherapy, alone or combined with a BRAF inhibitor, has been shown also promising in the treatment of ATC. Furthermore, to increase the therapeutic success and not to use ineffective or even harmful treatments, a real tailored therapy should be pursued, and this can be achieved thanks to the new available genomic analysis methods and to the possibility to test in vitro novel treatments directly in primary cells from each ATC patient. Exploring new treatment strategies is mandatory to improve the survival of these patients, guaranteeing a good quality of life.

Dataset Information

Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma.

Publications

Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma.

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