An investigation on the role of differentially expressed genes in thyroid cancer under the influence of hypoxia

Thyroid cancer is a common endocrine malignancy with a significant increase in its incidence in the past three decades. Even though research has significantly aided the management of the disease, the progression towards advanced forms of cancers remains indeterminate. In order to investigate the current challenges in thyroid cancer studies, the present work employed systematic and interactive transcriptomic data to construct plausible protein-protein interaction networks to reveal the putative transcriptional control mechanisms in cancer. The data from 4 different datasets consisting of normal samples vs thyroid cancer samples were chosen. Hypoxia being a significant hallmark of cancer was predicted to have a functional role in the progression of cancer. Consequently, prognostic pathways involved in cancer in response to hypoxia were predicted in the present study. The genes from the datasets were intersected with the hypoxia hallmark gene set to detect the significantly differentially expressed genes which were deregulated under the influence of hypoxia. These genes were analyzed by bioinformatic tools and a high correlation was found between 12 significant genes (PLAUR, BGN, SDC2, DUSP1, FOS, EGFR, CP, PPARGC1A, CITED2, RORA, HSPA5 and ACKR3) indicating a significant association between them. Of all the genes PLAUR was found to be novel and it was significantly upregulated under the influence of hypoxia. The hub genes and their role as predicted biomarkers were also determined by ROC curve analysis. This may assist in further research towards understanding role of hypoxia in Thyroid cancer.