Reference gene evaluation for normalization of gene expression studies with lymph tissue and node‑derived stromal cells of patients with oral squamous cell carcinoma

Profiling studies using reverse transcription quantitative PCR (RT-qPCR) require reliable normalization to reference genes to accurately interpret the results. A stable reference gene panel was established to profile metastatic and non-metastatic lymph nodes in patients with oral squamous cell carcinoma. The stability of 18S ribosomal RNA (<i>18SrRNA</i>), ribosomal Protein Lateral Stalk Subunit P0 (<i>RPLP0</i>), ribosomal Protein L27 (<i>RPL27</i>), TATA-box binding protein (<i>TBP</i>), hypoxanthine phosphoribosyl-transferase 1 (<i>HPRT1</i>), beta-actin (<i>ACTB</i>), glyceraldehyde-3-Phosphate Dehydrogenase (<i>GAPDH</i>) and vimentin (<i>VIM</i>) was evaluated, as reference genes for profiling patient-derived lymph node stromal cells (LNSCs; N=8; N0:6, N+:2) and lymph node tissues (Patients:14, Nodes=20; N0:7; N+:13). The genes were initially assessed based on their expression levels, specificity, and stability rankings to identify the best combination of reference genes. <i>VIM</i> was excluded from the final analysis because of its low expression (high quantification cycle >32) and multiple peaks in the melting curve. The stability analysis was performed using Reffinder, which utilizes four tools; geNorm, NormFinder, BestKeeper and Comparative ∆Ct methods, thereby enabling the computing of a comprehensive ranking. Evaluation of the gene profiles indicated that while <i>RPLP0</i> and <i>18SrRNA</i> were stable in both lymph node tissues and LNSCs, <i>HPRT1, RPL27</i> were uniquely stable in these tissues whereas <i>ACTB</i> and <i>TBP</i> were most stable in LNSCs. The present study identified the most stable reference gene panel for the RT-qPCR profiling of lymph node tissues and patient-derived LNSCs. The observation that the gene panel differed between the two model systems further emphasized the need to evaluate the reference gene subset based on the disease and cellular context.