Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Department of Computer Science and Engineering, Islamic University, Kushtia, Bangladesh.
Int J Biol Markers. 2024 Jun;39(2):118-129. doi: 10.1177/03936155241230968. Epub 2024 Feb 26.
Ultraviolet radiation causes skin cancer, but the exact mechanism by which it occurs and the most effective methods of intervention to prevent it are yet unknown. For this purpose, our study will use bioinformatics and systems biology approaches to discover potential biomarkers of skin cancer for early diagnosis and prevention of disease with applicable clinical treatments.
This study compared gene expression and protein levels in ultraviolet-mediated cultured keratinocytes and adjacent normal skin tissue using RNA sequencing data from the National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) database. Then, pathway analysis was employed with a selection of hub genes from the protein-protein interaction (PPI) network and the survival and expression profiles. Finally, potential clinical biomarkers were validated by receiver operating characteristic (ROC) curve analysis.
We identified 32 shared differentially expressed genes (DEGs) by analyzing three different subsets of the GSE85443 dataset. Skin cancer development is related to the control of several DEGs through cyclin-dependent protein serine/threonine kinase activity, cell cycle regulation, and activation of the NIMA kinase pathways. The cytoHubba plugin in Cytoscape identified 12 hub genes from PPI; among these 3 DEGs, namely, , and were significantly associated with survival ( < 0.05) and highly expressed in skin cancer tissues. For validation purposes, ROC curve analysis indicated two biomarkers: (area under the curve (AUC) value = 0.8) and (AUC value = 0.7), which were in an acceptable range.
Further translational research, including clinical experiments, teratogenicity tests, and in-vitro or in-vivo studies, will be performed to evaluate the expression of these identified biomarkers regarding the prognosis of skin cancer patients.
紫外线会导致皮肤癌，但它的具体发生机制以及预防它的最有效干预方法尚不清楚。为此，我们的研究将使用生物信息学和系统生物学方法来发现皮肤癌的潜在生物标志物，以便进行早期诊断和预防疾病，并提供适用的临床治疗。
本研究通过比较国家生物技术信息中心-基因表达综合数据库（NCBI-GEO）数据库中 RNA 测序数据，比较了紫外线介导的培养角质形成细胞和相邻正常皮肤组织的基因表达和蛋白质水平。然后，利用蛋白质-蛋白质相互作用（PPI）网络和生存及表达谱选择枢纽基因进行通路分析。最后，通过接收者操作特征（ROC）曲线分析验证潜在的临床生物标志物。
通过分析 GSE85443 数据集的三个不同子集，我们鉴定了 32 个共享的差异表达基因（DEGs）。皮肤癌的发展与通过细胞周期蛋白依赖性蛋白丝氨酸/苏氨酸激酶活性、细胞周期调控和 NIMA 激酶途径激活来控制几个 DEGs 有关。Cytoscape 中的 cytoHubba 插件从 PPI 中鉴定了 12 个枢纽基因；在这 3 个 DEGs 中，和与生存显著相关（<0.05），并且在皮肤癌组织中高度表达。为了验证目的，ROC 曲线分析表明有两个生物标志物：（曲线下面积（AUC）值=0.8）和（AUC 值=0.7），这在可接受的范围内。
将进行进一步的转化研究，包括临床实验、致畸性测试以及体外或体内研究，以评估这些鉴定的生物标志物在皮肤癌患者预后方面的表达。
