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Published on: March 11, 2014
Transcriptomic Network Analysis Using Exfoliative Cervical Cells Could Discriminate a Potential Risk of Progression
Nora Jee-Young Park1,2,3,4, Yeseul Choi5,6, Donghyeon Lee5,6
1Department of Pathology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea.
Background/Aim:
Cervical cancer is the fourth most common type of cancer in women worldwide and it is a major cause of cancer-related deaths in developing countries. Despite the marked reduction observed in the rates of the disease as a result of screening programs, it is necessary to develop robust biomarkers that can detect the neoplastic progression early in HPV-related cervical lesions.
Materials And Methods:
We performed comparative mRNA sequencing from exfoliative cervical cytology samples from nine Korean women using the Illumina NovaSeq6000 platform. Each pathological tissue was matched to the corresponding cytological sample. The pathologic diagnosis was scrutinized with ancillary immunohistochemistry and was considered a confirmative (endpoint) diagnosis. The pathological diagnoses consisted of three cases of chronic cervicitis, 2 high-grade squamous intraepithelial lesions (HSILs), 2 squamous cell carcinomas in situ (CIS), and 2 invasive squamous cell carcinomas (SQCCs), respectively. Using bioinformatic analyses, differentially expressed genes (DEGs; fold change ≥1.5; p<0.05) were applied for Gene Ontology (GO), Gene Set Enrichment Analysis (GSEA), and protein-protein interaction (PPI) networks.
Results:
From a total of 55,882 genes, 438 DEGs were pinpointed; 282 genes were up-regulated and 156 genes down-regulated. These transcriptomic profiles were clearly divided into neoplastic (HSIL, CIS, and SQCC; ≥HSILs) and non-neoplastic lesions. The up-regulated DEGs were HIF-1a, EDN1, PIK3R3, PPP1CA and AKR1C1. GO, GSEA, and PPI network analyses showed marked associations with metabolism, proteolysis, or proteoglycan process pathways in cervical carcinogenesis.
Conclusion:
The transcriptomic analysis using exfoliative cervical cells was more likely representative of its corresponding histopathological diagnosis, thus emphasizing its potential utility in clinical practice. This study provides comprehensive transcriptomic network analyses for robust biomarkers that might present a high potential risk of progression to cancer in the exfoliative cervical cytology; our findings support their clinical utility for improved cervical cancer screening.
