Format

Send to

Choose Destination
Gene. 2017 May 20;613:14-19. doi: 10.1016/j.gene.2017.02.034. Epub 2017 Mar 1.

The herbal medicine Melissa officinalis extract effects on gene expression of p53, Bcl-2, Her2, VEGF-A and hTERT in human lung, breast and prostate cancer cell lines.

Author information

1
Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran; Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
2
Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran; Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
3
Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
4
Department of Clinical Biochemistry and Laboratory Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran; Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
5
Cellular and Molecular Biology Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran.
6
Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Department of Clinical Biochemistry and Laboratory Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran; Molecular Targeting Therapy Research Group, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran. Electronic address: yousefib@tbzmed.ac.ir.

Abstract

INTRODUCTION:

Earlier, we verified that Melissa officinalis extract (MOE) elicits potent antiproliferative effects on different human cancer cells. To gain insights into the molecular mechanisms accounting for the cytotoxic effects of MOE, we assessed the expression patterns of several prominent molecules with therapeutic potential in cancer by Quantitative PCR (Q-PCR).

METHODS:

A549, MCF-7 and PC3 cancer cells were grown in complete RPMI 1640 and seeded in 24 well micro plates. After incubation for 72h, 100μg/ml of MOE was added and the cells were further incubated for 72h. Afterwards, the cells were subjected to RNA extraction for the means of Q-PCR.

RESULTS:

Our results indicated that in PC3 cancer cells, MOE resulted in a significant downregulation of VEGF-A (0.0004 fold), Bcl-2 (0.001 fold), Her2 (0.02 fold), and hTERT (0.023 fold) compared to the untreated control. In addition, VEGF-A and hTERT mRNA were significantly downregulated in MCF-7 and A549 cancer cells, as well. Notably, high anti-angiogenic activity was closely associated with a high anti-telomerase activity of MOE in studying cancer cells. The decrease in VEGF-A expression was significantly superior than that of hTERT downregulation, as PC3 cancer cells with the highest hTERT down regulation (0.023) presented the highest anti VEGF activity (0.0004 fold), whereas MCF-7 cells with the lowest hTERT inhibition (0.213) showed the lowest VEGF inhibition(0.0435) among the three studied cancer cells. We noticed that the modulation of VEGF-A and hTERT gene expression can be considered as a common target, accounting for the therapeutic potential of MOE on human breast, lung and prostate cancer cells.

CONCLUSION:

Altogether, it is suggested that the potent antiproliferative activity of the hydroalcoholic extract of Melissa officinalis is somehow explainable by its high potency to inhibit expression of the prominent oncogenes Bcl2, Her2, VEGF-A and hTERT in prostate cancer. In tumors with functional p53, including MCF-7 and A549 cancer cells, the role of p53, Bcl2 and Her2 is less significant. It appears that MOE exerts its antiproliferative effects in these cancer cells partly via concurrent downregulation of VEGF-A and hTERT. Additional studies are needed to clarify the role of other active molecules in cancer cells harboring functional p53.

KEYWORDS:

Bcl-2; Cancer; Her2; Melissa Officinalis; VEGF-A; hTERT; p53

PMID:
28259690
DOI:
10.1016/j.gene.2017.02.034
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center