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Comertpay et al. J Transl Genet Genom 2022;6:84-94  https://dx.doi.org/10.20517/jtgg.2021.44  Page 88











































                Figure 1. Co-expression network of the differentially expressed genes. Mutual differentially expressed genes (DEGs) that were
                significantly correlated are depicted as nodes, and statistically significant correlations between DEGs are represented as edges. Blue and
                red color edges represent positive and negative correlations, respectively.

               ABAT, alcohol dehydrogenase 1B (Class I), ADH1B, AGTR1, CCND1, FMO2, GRIA2, GYG2, IL6ST,
               MMP12, MMP9, PRKAR2B, S100A2, SCUBE2, TFPI, and TGFBR3.

               The first neighbor enriched PPI network was constructed by using DEGs [Figure 2]. Hub proteins with
               degree score ≥ 2 were determined as CCND1, PRKAR2B, IL6ST, PLN, GRIA2, S100A2, DUSP4, KRT6B,
               MMP9, AGTR1, and GYG2. Seed genes were also identified as common DEGs among co-expressed genes
               and hub genes of the PPI network [Figure 3A]. AGTR1, CCND1, GRIA2, GYG2, IL6ST, and PRKAR2B
               were downregulated while S100A2 and MMP9 were upregulated seed genes [Figure 3B]. The biological
               importance of the seed genes was described according to GeneCard  in Table 1. The protein product of
                                                                          [28]
               AGTR1 is a vasopressor hormone that affects the narrowing of blood arteries. CCND1 functions as a
               regulator of CDK kinases. Another seed gene, IL6ST, is a signal transducer and part of the cytokine receptor
               complex. GRIA2 and S100A2 are related to physiological processes, while GYG2 and PRKAR2B are
               metabolism-related genes. It has been reported that MMP9 is a metastasis-associated gene.

               To identify important signaling pathways to the obesity-related carcinogenesis mechanism, pathway
               enrichment analysis was performed via KEGG and Reactome databases [Table 2]. Especially tumor-
               associated signaling pathways were obtained. RAF-independent MAPK1/3 activation, collagen degradation,
               bladder cancer, drug metabolism-cytochrome P450, and signaling by Hedgehog pathways in cancer were
               determined as significant pathways (P value < 0.01).
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