AUTHOR=Wen Xiaoxia , Yang Guishu , Dong Yongcheng , Luo Liping , Cao Bangrong , Mengesha Birga Anteneh , Zu Ruiling , Liao Yulin , Liu Chang , Li Shi , Deng Yao , Zhang Kaijiong , Ma Xin , Huang Jian , Wang Dongsheng , Zhao Keyan , Leng Ping , Luo Huaichao 

TITLE=Selection and Validation of Reference Genes for Pan-Cancer in Platelets Based on RNA-Sequence Data

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.913886

DOI=10.3389/fgene.2022.913886

ISSN=1664-8021

ABSTRACT=Studies have proved that platelets are involved in the pathophysiology of pan-cancer by interacting with tumor cells in the tumor microenvironment. This function changes the RNA expression profile of platelets, called tumor-educated platelets (TEPs). Some messenger RNA (mRNA) in TEPs had been attainable biomarkers for the diagnosis of pan-cancer. Quantitative real-time PCR (RT-qPCR) is often used to analyze gene expression, relying on accurate data normalization. Reference genes are generally utilized to normalize RT-qPCR data. However, the use of reference genes in current studies based on platelets and pan-cancer was not uniform and has not been validated. Given that expression of some commonly used reference genes is altered in certain conditions. Therefore, selecting and verifying the most suitable reference gene for pan-cancer in platelet is necessary. We performed bioinformatics and functional analysis from RNA-seq of the TEPs dataset (GSE68086). 95 candidate reference genes were generated after the primary bioinformatics step. Seven reference genes (YWHAZ, GNAS, GAPDH, OAZ1, PTMA, B2M, and ACTB) were screened out among the 95 candidate reference genes from the dataset of the platelets’ transcriptome of the pan-cancer and 73 commonly known reference genes. They were verified by another platelet expression dataset (GSE89843). Then we used RT-qPCR to confirm the expression levels of these 7 genes in 50 subject samples (pan-cancer patients and healthy individuals) and analyzed these results using the internal stability analysis software programs (The comparative delta-Ct method, geNorm, NormFinder, and BestKeeper) to rank the candidate genes in order of decreasing stability. In contrast, the GAPDH gene was stably and constitutively expressed at high levels in all the samples tested. Therefore, GAPDH was recommended as the most suitable reference gene for platelet transcript analysis. In conclusion, our result may play an essential part in establishing the molecular diagnostic platform based on the platelet to distinguish tumor patients from healthy individuals.