| Literature DB >> 31216637 |
Alexandra Iulia Irimie1, Cornelia Braicu2, Sergiu Pasca3, Lorand Magdo4, Diana Gulei5, Roxana Cojocneanu6, Cristina Ciocan7, Andrei Olariu8, Ovidiu Coza9,10, Ioana Berindan-Neagoe11,12,13.
Abstract
Regarding cancer as a genetic multi-factorial disease, a number of aspects need to be investigated and analyzed in terms of cancer's predisposition, development and prognosis. One of these multi-dimensional factors, which has gained increased attention in the oncological field due to its unelucidated role in risk assessment for cancer, is diet. Moreover, as studies advance, a clearer connection between diet and the molecular alteration of patients is becoming identifiable and quantifiable, thereby replacing the old general view associating specific phenotypical changes with the differential intake of nutrients. Respectively, there are two major fields concentrated on the interrelation between genome and diet: nutrigenetics and nutrigenomics. Nutrigenetics studies the effects of nutrition at the gene level, whereas nutrigenomics studies the effect of nutrients on genome and transcriptome patterns. By precisely evaluating the interaction between the genomic profile of patients and their nutrient intake, it is possible to envision a concept of personalized medicine encompassing nutrition and health care. The list of nutrients that could have an inhibitory effect on cancer development is quite extensive, with evidence in the scientific literature. The administration of these nutrients showed significant results in vitro and in vivo regarding cancer inhibition, although more studies regarding administration in effective doses in actual patients need to be done.Entities:
Keywords: cancer; chemoprevention; nutrigenetics; nutrigenomics
Mesh:
Substances:
Year: 2019 PMID: 31216637 PMCID: PMC6630934 DOI: 10.3390/medicina55060283
Source DB: PubMed Journal: Medicina (Kaunas) ISSN: 1010-660X Impact factor: 2.430
List of techniques presently utilized at each “omics” level (DNA, RNA, protein, metabolite) that could determine the impact of nutrients on human health, with emphasis on the practical application.
| Nutrigenetics | Nutrigenomics | Practical Application | Ref. | |
|---|---|---|---|---|
|
| Next generation sequencing (NGS), pyrosequencing, nanostring, polymerase chain reaction (PCR)-based methods | Microarray, NGS, nanostring | Methods assessing DNA are more prone to be applied in nutrigenetics, with emphasis on particular mutations or single nucleotide polymorphisms (SNPs) that affect the response to a particular diet. This entails prediction of genotype/mutation patterns caused by the indirect interaction of genes with certain nutrients. | [ |
|
| Next generation sequencing, pyrosequencing, PCR-based methods | Microarray, NGS, nanostring | Methods assessing RNA are more prone to be applied in nutrigenomics, to evaluate the effect on the alteration of coding and non-coding genes of a particular nutrient. This means determining RNA levels from different tissues to observe the effects of nutrients on transcriptomic profile in terms of impact on physiological or pathological status. | [ |
|
| Mass spectrometry (MS), high performance liquid chromatography (HPLC), high performance liquid chromatography–tandem mass spectrometry (HPLC/MS), ultra-high performance liquid chromatography–tandem mass spectrometry (UHPLC/MS) | HPLC/MS, UHPLC/MS | Proteomics is also more prone to be found in nutrigenomic studies. Being an extension of transcriptomics, it allows for validating mRNA expression protein levels. | [ |
|
| Nuclear magnetic resonance, HPLC/MS, UHPLC/MS | Nuclear magnetic resonance, HPLC/MS, ultra-high performance liquid chromatography (UHPLC) | Giving a complete picture, metabolites are able to be more accurate in predicting the effect of nutrients. Furthermore, they could be used for validation of the other “omics.” | [ |
List of experimentally investigated nutrients with a potential impact on cancer therapy, determined by cancer type, expected outcomes and genes effected.
| Nutrient | Cancer type | Expected Outcomes | Genes effected | Comment | Ref. |
|---|---|---|---|---|---|
|
| Glioma, lung, colorectal cancer | Pro/anti-oxidant action, cell differentiation and immune response | Expression level and polymorphism of RARs, RXRs, and PPARβ/δ, Akt, Erk, JNK, p38 | Epidemiological data are not consistent | [ |
|
| Solid tumors and hematological malignancies | Selective activation of apoptosis and autophagy. Interferes with redox-sensitive transcription factors and associated target molecules. Selective metabolic and genotoxic stress on tumor cells. | Expression level and polymorphism of GLUT, GST, MnSOD, SVCT, Hp | Low toxicity to normal tissues, but with controversial data due to its dual effect as a pro/antioxidant. The molecular mechanism(s) of selective toxicity on tumor cells remains to be deciphered | [ |
|
| Colorectal, breast, prostate or pancreatic cancer | Correlated with lower risks of specific cancers. | Expression level and polymorphism of VDR target genes like p21WAF1/CIP
| The results of these studies have been inconsistent, possibly because of the challenges in carrying out such studies. | [ |
|
| Prostate, breast colorectal cancer | Reduces unwanted side effect of cytotoxicity by targeting oxidative stress and inflammatory markers | Polymorphism of | This might also have a pro-oxidant effect. | [ |
|
| Gastric colorectal, breast, pancreatic cancer | Carcinogenesis and embryonic development. At low doses, it decreases cancer risk but overdoses might increase cancer risk | Methylation of | Dual role: protection early in carcinogenesis and at high doses in late stages of cancer | [ |
|
| Prostate, breast, lung, oropharyngeal, colorectal, bladder, skin, leukemias, uterine, ovarian cancers | Antioxidant, reduces cancer risk; restores epigenetic altered events; genomic stability | Expression and polymorphism of GPxsang, TrxRs | Still highly controversial, being tumor specific and dose specific (pro/antioxidant effect) | [ |
| Polyunsaturated fatty acids ( | Breast, colorectal cancer | Regulate cytokine production; stimulate the immune response and enhances apoptosis in cancer cells; regulate cell proliferation and angiogenesis | Transcription factors: PPARs or NFκβ; immune response: TNFα, IL-1β, IL-6; angiogenesis mechanisms: VEGF, PDGF, MMP-2; cell proliferation: cyclins, p53, PTEN | Involved in tumor biology and cancer patients’ prognosis; epidemiologic data furnish inconsistent picture | [ |
|
| Colorectal, breast, pancreatic, ovarian or stomach cancer | Increased intestinal transit blocking the absorption of external or internal toxic factors | Expression level and polymorphism of CAZymes family | Highly controversial epidemiological data, due to the different types of soluble or insoluble fibers used in studies | [ |
|
| Colorectal cancer | Cell-mediated immune responses; increase the activity of antioxidant enzymes | Expression level and polymorphism of CAZymes family | Presently there is no direct evidence in epidemiological data | [ |
Figure 1Nutrients’ molecular targets and their intermediaries associated with the hallmarks of cancer. The major impact of nutrients is through their action on reactive oxygen species (ROS) production, which has a critical role in tumor-promoting inflammation. Aside from this effect, nutrients have been shown to effect multiple hallmarks of cancer: for example, fatty acids act on tumor-promoting inflammation, the induction of angiogenesis, the activation of invasion and metastasis and the sustenance of proliferative signaling. Other effects can be observed, significantly impacting on a person’s cancer susceptibility and prognosis, aspects of which can be modulated by patient diet in a directed manner, leading to the development of personalized nutrition.
Figure 2Pathways or interactions representative of the metabolism of nutrients. The majority of the nutrients function either as electron transporters in redox systems or as ligands for transcription factors involved in gene regulation. These effects can be intertwined, as in the case of folate metabolism. Folate metabolism has a dual effect in that it facilitates protein methylation by providing 1-carbon source influencing gene regulation, and it acts in the redox system of oxidative stress by influencing the levels of homocysteine. GPx = glutathione peroxidase; GSH = reduced glutathione; GSSG = oxidized glutathione; GR = gluthatione reductase; NADP = nicotinamide dinucleotide phosphate; RAR = retinoic acid receptor; RXR = retinoid X receptor; RARE = retinoic acid response element; VDR = vitamin D receptor; VDRE = vitamin D response element; dUMP = deoxy uridine monophosphate; dTMP = deoxythymidine monophosphate; TYMS = thymidilatesynthetase; DHF = dihydrofolate; T/HF = tetrahydrofolate; MTHFR = methylene tetrahydrofolate reductase; MTHFD = methylene tetrahydrofolate dehydrogenase; MS = methionine synthetase; SAM = S-adenosyl methionine; SAH = S-adenosine homocysteine; MAT = methionine adenosine transferase; SAHH = S-adenylhomocisteine hydrolase.