Candidate Genes and Pathways in Cervical Cancer: A Systematic Review and Integrated Bioinformatic Analysis

• Published in: Cancers Vol. 15; no. 3; p. 853
• Main Authors: Elias, Marjanu Hikmah, Das, Srijit, Abdul Hamid, Nazefah
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 30.01.2023; MDPI
• Subjects: Biopsy; Cancer; Care and treatment; Cell cycle; Cell differentiation; Cell signaling; Cervical cancer; Cervix; Consortia; Data collection; Developing countries; Development and progression; Diagnosis; DNA microarrays; Gene expression; Genes; Genetic aspects; Genomics; Health aspects; Keywords; LDCs; Molecular modelling; Oncology, Experimental; Ontology; Pathogenesis; Proteins; Sample size; Software; Systematic Review; Tumors; Malaysia; United States > US; molecular pathway; gene ontology; differentially expressed gene; cervical cancer
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers15030853

Cervical cancer is the leading cause of cancer-related death among women in developing countries. However, no comprehensive molecular mechanism for cervical cancer has been established, as many studies were small-cohort studies conducted with small sample sizes. A thorough literature search was performed using the PubMed, Scopus, EBSCOhost, and Science Direct databases. Medical Subject Heading (MeSH) terms such as “Uterine Cervical Neoplasms” and “gene expression” were used as the keywords in all fields. A total of 4027 studies were retrieved, and only clinical studies, which used the microarray method to identify differentially expressed genes (DEGs) in the cervical tissue of cervical cancer patients, were selected. Following the screening, 6 studies were selected and 1128 DEGs were extracted from the data. Sixty-two differentially expressed genes from at least two studies were selected for further analysis by DAVID, STRING, and Cytoscape software. In cervical cancer pathogenesis, three significant clusters with high intermolecular interactions from the Protein–Protein Interaction (PPI) network complex revealed three major molecular mechanisms, including cell signaling, cell cycle, and cell differentiation. Subsequently, eight genes were chosen as the candidate genes based on their involvement in the relevant gene ontology (GO) and their interaction with other genes in the PPI network through undirected first neighbor nodes. The present systematic review improves our understanding of the molecular mechanism of cervical cancer and the proposed genes that can be used to expand the biomarker panel in the screening for cervical cancer. The targeted genes may be beneficial for the development of better treatment strategies.