Identification of suitable reference genes for gene expression studies using quantitative polymerase chain reaction in lung cancer in vitro

Abstract

The present study aimed to examine 10 housekeeping genes (HKGs), including 18s ribosomal RNA (18S), glyceraldehyde‑3‑phosphate dehydrogenase (GAPDH), ribosomal protein large P0 (RPLP0), β‑actin (ACTB), peptidylprolyl isomerase A (PPIA), phosphoglycerate kinase‑1 (PGK1), β‑2‑microglobulin (B2M), ribosomal protein LI3a (RPL13A), hypoxanthine phosphoribosyl transferase‑1 (HPRT1) and TATA box binding protein (TBP) in order to identify the most stable and suitable reference genes for use in expression studies in non‑small cell lung cancer. The mRNA expression encoding the panel of the 10 HKGs was determined using reverse transcription‑quantitative PCR (RT‑qPCR) in human lung cancer cell lines. Three software programs, BestKeeper, NormFinder and geNorm, were used to ascertain the most suitable reference genes to normalize the RNA input. The present study examined three lung cancer cell lines (A549, NCI‑H446 and NCI‑H460). The analysis of the experimental data using BestKeeper software revealed that all 10 HKGs were stable, with GADPH, followed by 18S being the most stable genes and PPIA and HPRT1 being the least stable genes. The NormFinder software results demonstrated that PPIA followed by ACTB were the most stable and B2M and RPLP0 were the least stable. The geNorm software results revealed that ACTB and PGK1, followed by PPIA were the most stable genes and B2M and RPLP0 were identified as the least stable genes. Due to discrepancies in the ranking orders of the reference genes obtained by different analyzing software programs, it was not possible to determine a single universal reference gene. The suitability of selected reference genes requires unconditional validation prior to each study. Based on the three analyzing programs, ACTB, PPIA and PGK1 were the most stable reference genes in lung cancer cell lines.

Serum availability affects expression of common house-keeping genes in colon adenocarcinoma cell lines: implications for quantitative real-time PCR studies

“…RPLP0 has been claimed a suitable reference for human intestinal epithelial cells (Dydensborg et al 2006). In turn, PPIA has been repeatedly found a suitable normalizer in a number of human studies (Andrusiewicz et al 2016; Ali et al 2015; Lemma et al 2016), also these concerning CRC patients (Sørby et al 2010; Kheirelseid et al 2010), but affected by cell stimulation in others (Kaszubowska et al 2015). IPO8 and GUSB were yet another HKG recommended for CRC studies (Sørby et al 2010; Blanquicett et al 2002) and highly ranked in our in vitro study as well.…”

Determination of qPCR Reference Genes Suitable for Normalizing Gene Expression in a Canine Model of Duchenne Muscular Dystrophy

“…The accuracy of this technique is criticallydependent on good normalization: even with identical starting material, slight differences in the efficiency of RNA isolation or cDNA synthesis can significantly affect subsequent quantitation. Effective normalization requires appropriate reference genes, and indeed efforts to identify, validate and publicize such genes are becoming more common in a variety of disease states [20][21][22][23][24] and model organisms [25][26][27][28][29][30]. A review of the literature specifically within the DMD field however reveals a considerable number of candidates: selected examples in dystrophic dogs include GAPDH [31][32][33], RPS18 [34], HPRT1 [35,36], 18S [37]; in humans, TBP and GUSB [13]; and in mice GAPDH [33,38], ActB [39], 18S [40].…”

Validation of internal reference genes for relative quantitation studies of gene expression in human laryngeal cancer

“…In general, internal reference genes, such as 18S rRNA, GAPDH, and ACTB, are chosen for relative quantification analysis between clinical samples. However, increasing evidence has suggested that the expression levels of these commonly used internal reference genes are variable in distinct tissues, cell lines, between treatments of the same cell line (Ali et al, 2015; Ma et al, 2015; Yang et al, 2014; Yu et al, 2015), as well as across cell types (He et al, 2015; Li et al, 2015a; Li et al, 2015b). Thus, with the advancement of precise medicine, it is of high importance to evaluate and validate internal reference genes for the target gene expression profile studies among different cell types and tissues.…”