RESUMEN
Triple negative breast cancer (TNBC) is a subtype of breast cancer of heterogeneous nature that is negative for estrogen receptor (ER), progesterone receptor (PR) and growth factor human epidermal 2 (HER2) following immunohistochemical analysis. TNBC is frequently characterized by relapse and reduced survival. To date, there is no targeted therapy for this type of cancer. Chemotherapy, radiotherapy, and surgery remain as the standard treatments options. The lack of a target therapy and the heterogeneity of TNBC highlight the need to seek new therapeutic options. In this study, fresh tissue samples of TNBC were analyzed with a panel of 48 driver genes (212 amplicons) that are likely to be therapeutic targets. We found intron variants, missense, stop gained and splicing variants in TP53, PIK3CA and FLT3 genes. Interestingly, all the analyzed samples had at least two variants in the TP53 gene, one being a drug response variant, rs1042522, found in 94% of our samples. We also found seven additional variants not previously reported in the TP53 gene, to the best of our knowledge, with probable deleterious characteristics of the tumor suppressor gene. We found four genetic variants in the PIK3CA gene, including two missense variants. The rs2491231 variant in the FLT3 gene was identified in 84% (16/19) of the samples, which not yet reported for TNBC, to the best of our knowledge. In conclusion, genetic variants in TP53 were found in all TNBC tumors, with rs1042522 being the most frequent (94% of TNBC biopsies), which had not been previously reported in TNBC. Also, we found two missense variants in the PIK3CA gene. These results justify the validation of these genetic variants in a large cohort, as well as the extensive study of their impact on the prognosis and therapy management of TBNC.
RESUMEN
Prebiotics are selectively fermentable dietary compounds that result in changes in the composition and/or activity of the intestinal microbiota, thus conferring benefits upon host health. In veterinary medicine, commercially available products containing prebiotics have not been well studied with regard to the changes they trigger on the composition of the gut microbiota. This study evaluated the effect of a commercially available nutraceutical containing fructo-oligosaccharides (FOS) and inulin on the fecal microbiota of healthy cats and dogs when administered for 16 days. Fecal samples were collected at two time points before and at two time points during prebiotic administration. Total genomic DNA was obtained from fecal samples and 454-pyrosequencing was used for 16S rRNA gene bacterial profiling. The linear discriminant analysis (LDA) effect size (LEfSe) method was used for detecting bacterial taxa that may respond (i.e., increase or decrease in its relative abundance) to prebiotic administration. Prebiotic administration was associated with a good acceptance and no side effects (e.g., diarrhea) were reported by the owners. A low dose of prebiotics (50 mL total regardless of body weight with the end product containing 0.45% of prebiotics) revealed a lower abundance of Gammaproteobacteria and a higher abundance of Veillonellaceae during prebiotic administration in cats, while Staphylococcaceae showed a higher abundance during prebiotic administration in dogs. These differences were not sufficient to separate bacterial communities as shown by analysis of weighted UniFrac distance metrics. A predictive approach of the fecal bacterial metagenome using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) also did not reveal differences between the period before and during prebiotic administration. A second trial using a higher dose of prebiotics (3.2 mL/kg body weight with the end product containing 3.1% of prebiotics) was tested in dogs and revealed a lower abundance of Dorea (family Clostridiaceae) and a higher abundance of Megamonas and other (unknown) members of Veillonellaceae during prebiotic administration. Again, these changes were not sufficient to separate bacterial communities or predicted metabolic profiles according to treatment. A closer analysis of bacterial communities at all time-points revealed highly individualized patterns of variation. This study shows a high interindividual variation of fecal bacterial communities from pet cats and dogs, that these communities are relatively stable over time, and that some of this variation can be attributable to prebiotic administration, a phenomenon that may be affected by the amount of the prebiotic administered in the formulation. This study also provides insights into the response of gut bacterial communities in pet cats and dogs during administration of commercially available products containing prebiotics. More studies are needed to explore potentially beneficial effects on host health beyond changes in bacterial communities.
RESUMEN
The 16S rRNA gene (16S rDNA) codes for RNA that plays a fundamental role during translation in the ribosome and is used extensively as a marker gene to establish relationships among bacteria. However, the complementary non-coding 16S rDNA (nc16S rDNA) has been ignored. An idea emerged in the course of analyzing bacterial 16S rDNA sequences in search for nucleotide composition and substitution patterns: Does the nc16S rDNA code? If so, what does it code for? More importantly: Does 16S rDNA evolution reflect its own evolution or the evolution of its counterpart nc16S rDNA? The objective of this minireview is to discuss these thoughts. nc strands often encode small RNAs (sRNAs), ancient components of gene regulation. nc16S rDNA sequences from different bacterial groups were used to search for possible matches in the Bacterial Small Regulatory RNA Database. Intriguingly, the sequence of one published sRNA obtained from Legionella pneumophila (GenBank: AE0173541) showed high non-random similarity with nc16S rDNA corresponding in part to the V5 region especially from Legionella and relatives. While the target(s) of this sRNA is unclear at the moment, its mere existence might open up a new chapter in the use of the 16S rDNA to study relationships among bacteria.
