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.

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

Background: Lung cancer remains one of the most diagnosed malignancies, being the second most diagnosed cancer, while still being the leading cause of cancer-related deaths. Late diagnosis remains a problem, alongside the high mutational burden encountered in lung cancer. Methods: We assessed the genetic profile of cancer genes in lung cancer using The Cancer Genome Atlas (TCGA) datasets for mutations and validated the results in a separate cohort of 32 lung cancer patients using tumor tissue and whole blood samples for next-generation sequencing (NGS) experiments. Another separate cohort of 32 patients was analyzed to validate some of the molecular alterations depicted in the NGS experiment. Results: In the TCGA analysis, we identified the most commonly mutated genes in each lung cancer dataset, with differences among the three histotypes analyzed. NGS analysis revealed TP53, CSF1R, PIK3CA, FLT3, ERBB4, and KDR as being the genes most frequently mutated. We validated the c.1621A>C mutation in KIT. The correlation analysis indicated negative correlation between adenocarcinoma and altered PIK3CA (r = −0.50918; p = 0.0029). TCGA survival analysis indicated that NRAS and IDH2 (LUAD), STK11 and TP53 (LUSC), and T53 (SCLC) alterations are correlated with the survival of patients. Conclusions: The study revealed differences in the mutational landscape of lung cancer histotypes.

In recent years, the role of microRNA (miRNA) in post-transcriptional gene regulation has advanced and supports strong evidence related to their important role in the regulation of a wide range of fundamental biological processes. Our study focuses on identifying specific alterations of miRNA patterns in periodontitis compared with healthy subjects. In the present study, we mapped the major miRNAs altered in patients with periodontitis (n = 3) compared with healthy subjects (n = 5), using microarray technology followed by a validation step by qRT-PCR and Ingenuity Pathways Analysis. Compared to healthy subjects, 159 differentially expressed miRNAs were identified among periodontitis patients, of which 89 were downregulated, and 70 were upregulated, considering a fold change of ±1.5 as the cut-off value and p ≤ 0.05. Key angiogenic miRNAs (miR-191-3p, miR-221-3p, miR-224-5p, miR-1228-3p) were further validated on a separate cohort of patients with periodontitis versus healthy controls by qRT-PCR, confirming the microarray data. Our findings indicate a periodontitis-specific miRNA expression pattern representing an essential issue for testing new potential diagnostic or prognostic biomarkers for periodontal disease. The identified miRNA profile in periodontal gingival tissue was linked to angiogenesis, with an important molecular mechanism that orchestrates cell fate.

Background: Non-small cell lung cancer (NSCLC) is still one of the types of cancer with the highest death rates. MicroRNAs (miRNAs) play essential roles in NSCLC development. This study evaluates miRNA expression patterns and specific mechanisms in male patients with NSCLC. Methods: We report an integrated microarray analysis of miRNAs for eight matched samples of males with NSCLC compared to the study of public datasets of males with NSCLC from TCGA, followed by qRT-PCR validation. Results: For the TCGA dataset, we identified 385 overexpressed and 75 underexpressed miRNAs. Our cohort identified 54 overexpressed and 77 underexpressed miRNAs, considering a fold-change (FC) of ±1.5 and p < 0.05 as the cutoff value. The common miRNA signature consisted of eight overexpressed and nine underexpressed miRNAs. Validation was performed using qRT-PCR on the tissue samples for miR-183-3p and miR-34c-5p and on plasma samples for miR-34c-5p. We also created mRNA-miRNA regulatory networks to identify critical molecules, revealing NSCLC signaling pathways related to underexpressed and overexpressed transcripts. The genes targeted by these transcripts were correlated with overall survival. Conclusions: miRNAs and some of their target genes could play essential roles in investigating the mechanisms involved in NSCLC evolution and provide opportunities to identify potential therapeutic targets.