MATERIALS AND METHODS: We evaluated simple statistics and published model-based approaches. Multiplex-qPCR was conducted to determine the expression of 24 candidate RG in AMLs (N=9). Singleplex-qPCR was carried out on selected RG (SRP14, B2M and ATP5B) and genes of interest in AML (N=15) and healthy controls, HC (N=12).
RESULTS: RG expression levels in AML samples were highly variable and coefficient of variance (CV) ranged from 0.37% to 10.17%. Analysis using GeNorm and Normfinder listed different orders of most stable genes but the top seven (ACTB, UBE2D2, B2M, NF45, RPL37A, GK, QARS) were the same. In singleplex-qPCR, SRP14 maintained the lowest CV in AML samples. B2M, one of most stable reference genes in AML, was expressed near significantly different in AML and HC. GeNorm selected ATP5B+SRP14 while Normfinder chose SRP14+B2M as the best two RG in combination. The median expressions of combined RG genes in AML compared to HC were less significantly different than individually implying smaller expression variation after combination. Genes of interest normalised with RG in combination or individually, displayed significantly different expression patterns.
CONCLUSIONS: The selection of best reference gene in qPCR must consider all sample sets. Model-based approaches are important in large candidate gene analysis. This study showed combination of RG SRP14+B2M was the most suitable normalisation factor for qPCR analysis of AML and healthy individuals.
OBJECTIVES: The current study investigated the gene expression profile of hepatocellular carcinoma, HepG2, cells after treatment with Limonene.
METHODS: The concentration that killed 50% of HepG2 cells was used to elucidate the genetic mechanisms of limonene anticancer activity. The apoptotic induction was detected by flow cytometry and confocal fluorescence microscope. Two of the pro-apoptotic events, caspase-3 activation and phosphatidylserine translocation were manifested by confocal fluorescence microscopy. Highthroughput real-time PCR was used to profile 1023 cancer-related genes in 16 different gene families related to the cancer development.
RESULTS: In comparison to untreated cells, limonene increased the percentage of apoptotic cells up to 89.61%, by flow cytometry, and 48.2% by fluorescence microscopy. There was a significant limonene- driven differential gene expression of HepG2 cells in 15 different gene families. Limonene was shown to significantly (>2log) up-regulate and down-regulate 14 and 59 genes, respectively. The affected gene families, from the most to the least affected, were apoptosis induction, signal transduction, cancer genes augmentation, alteration in kinases expression, inflammation, DNA damage repair, and cell cycle proteins.
CONCLUSION: The current study reveals that limonene could be a promising, cheap, and effective anticancer compound. The broad spectrum of limonene anticancer activity is interesting for anticancer drug development. Further research is needed to confirm the current findings and to examine the anticancer potential of limonene along with underlying mechanisms on different cell lines.