Identification and performance evaluation of housekeeping genes for microRNA expression normalization by reverse transcription‑quantitative PCR using liquid‑based cervical cytology samples

Screening for cervical cancer by cytology has been effective in reducing the worldwide incidence and mortality rates of this disease. However, a number of studies have demonstrated that the sensitivity of conventional cervical cytology may be too low for detection of cervical intraepithelial neoplasias (CIN). Therefore, it is important to incorporate more sensitive molecular diagnostic tests that could substantially improve the detection rates and accuracy for identifying CIN lesions. MicroRNAs (miRNAs) are a class of small non-coding RNAs with the potential to provide robust non-invasive cancer biomarkers for detecting CIN lesions in liquid-based cervical cytology (LBC) samples. At present, there is no consensus on which are the best housekeeping genes for miRNA normalization in LBC. The present study aimed to identify housekeeping genes with consistent and reproducible performance for normalization of reverse transcription-quantitative PCR (RT-qPCR) expression analysis of miRNA using LBC samples. The present study firstly selected six potential candidate housekeeping genes based on a systematic literature evaluation. Subsequently, the expression levels of microRNAs U6, RNU-44, RNU-47, RNU-48, RNU-49 and hsa-miR-16 were measured in 40 LBC samples using RT-qPCR. The stability of each potential housekeeping gene was assessed using the NormFinder algorithm. The results revealed that U6 and RNU-49 were the most stable genes among all candidates requiring fewer amplification cycles and smaller variation across the sample set. However, RNU-44, RNU-47, RNU-48 and hsa-miR-16 stability exceeded the recommended housekeeping value suitable for normalization. The findings revealed that U6 may be a reliable housekeeping gene for normalization of miRNA RT-qPCR expression analysis using LBC samples. Key words: cervical cancer, miRNA expression, liquid-based cytology, housekeeping genes, reverse transcription-quantitative PCR