Mitochondria are highly organized multicomponent systems of endogenous fluorescent molecules, which can be detected by fluorescence spectroscopy. They play a crucial role in energetic metabolism of cells. The dysfunction of mitochondria plays a central role in aging and the pathophysiology of a variety of diseases. Mitochondria have an important function also in oncogenesis and tumor progression, and thus provide promising targets for the development of novel anti-cancer agents as new therapeutic opportunities. This requires the need for further use of various biological samples in research to stimulate the entire field of mitochondrial medicine.
In our study, we investigated the effect of resveratrol (at a dose of 100 mg/kg of body weight on daily basis) and ethanol (10% ethanol administered orally on daily basis), on the chemically induced carcinogenesis process in Sprague-Dawley rats at mitochondrial level. Carcinoma formation was induced using N-nitroso-N-methylurea (NMU, 50 mg/kg of body weight on 43th and 50th postnatal days). Mitochondria were isolated from the breast cancer tissue. The changes between controls, NMU carcinogenesis group, resveratrol or ethanol treated groups were measured by the fluorescence spectroscopy method.
The most significant changes were observed in the protein domain (ex/em 280/350 nm), where a significant increase in the chemically induced carcinogenesis group was observed over the treated groups and control. We also monitored decreased autofluorescence (normalized spectra) in the region specific for NADH+H+ (ex/em 350/440 nm) and FAD (ex/em 440/520 nm) in the group where carcinogenesis was induced compared to other groups.
The results showed, that resveratrol lowered the amount of total proteins in breast cancer tissue, which could indicate decreased tumor volume or halting tumor progression and also redox state in resveratrol treated group is much more similar to control. However, it is important to further elucidate its mechanism of action on molecular level, which could be promising strategy against cancer cells.
Keywords: antioxidant, carcinogenesis, autofluorescence
Statistics
Hi, nice work, but you should add error bars to your graphs. Which statistical method did you use? What did you use as a control?
Re: Statistics
Hi, thank you for your comment, I used T test for statistical evaluation of differences between the groups. As a control we used health rats.
question
Hi, nice work.
I understend your work right? You gave NMU all experimental animals? One group was untreated, one was administered resveratrol and another ethanol. The last group was healthy. Then ethanol itself had positive effects on mitochondria. Is ethanol also a beneficial drug in breast cancer?
I miss a little in the experimental work the number of animals used in the experiment as well as statistical processing. Could you write a few words and results on it?
Thanks
Re: question
Hi, thank you for your comment. Yes, the treatment of groups were as you wrote, the last one were healthy rats. Ethanol consumption is very controversial when counting protective and harmful properties (of course depending on dose). We are probably still far from understanding exact mechanisms of action on carcinogenesis. More studies report rather damaging properties of ethanol than beneficial and often is ethanol mentioned as risk factor of few types of cancer. In this experiment it was used as resveratrol was diluted in ethanol. It is surprise, that resveratrol is less protective than ethanol itself. Number of animals was 3 in each group. For the comparison between groups we used T test (two-tailed, two sample with equal/unequal variance according to value of F test) with following results: there was not statistically significant difference between groups NMU vs Et, NMU vs Res, or Res vs NMU. There were also not statistical significant difference between controls and treated groups in protein domain, although there is evident trend (probably caused by big standard deviation values, here is needed to increase number of animals). Best results from statisticall point of view were when comparing normalised data. There are significant differences between control and all treated groups in NADH and also FAD fluorescence varying from p=0,004347 (Et vs control for FAD) up to p=0,0000433 (NMU vs control for NADH). I hope the answer has satisfied your questions. :)