Glycophenotypic Alterations Induced by Pteridium aquilinum in Mice Gastric Mucosa: Synergistic Effect with Helicobacter pylori Infection

The bracken fern Pteridium aquilinum is a plant known to be carcinogenic to animals. Epidemiological studies have shown an association between bracken fern exposure and gastric cancer development in humans. The biological effects of exposure to this plant within the gastric carcinogenesis process are not fully understood. In the present work, effects in the gastric mucosa of mice treated with Pteridium aquilinum were evaluated, as well as molecular mechanisms underlying the synergistic role with Helicobacter pylori infection. Our results showed that exposure to Pteridium aquilinum induces histomorphological modifications including increased expression of acidic glycoconjugates in the gastric mucosa. The transcriptome analysis of gastric mucosa showed that upon exposure to Pteridium aquilinum several glycosyltransferase genes were differently expressed, including Galntl4, C1galt1 and St3gal2, that are mainly involved in the biosynthesis of simple mucin-type carbohydrate antigens. Concomitant treatment with Pteridium aquilinum and infection with Helicobacter pylori also resulted in differently expressed glycosyltransferase genes underlying the biosynthesis of terminal sialylated Lewis antigens, including Sialyl-Lewisx. These results disclose the molecular basis for the altered pattern of glycan structures observed in the mice gastric mucosa. The gene transcription alterations and the induced glycophenotypic changes observed in the gastric mucosa contribute for the understanding of the molecular mechanisms underlying the role of Pteridium aquilinum in the gastric carcinogenesis process

Response of high-risk of recurrence/progression bladder tumours expressing sialyl-Tn and sialyl-6-T to BCG immunotherapy

High risk of recurrence/progression bladder tumours is treated with Bacillus Calmette-Guérin (BCG) immunotherapy after complete resection of the tumour. Approximately 75% of these tumours express the uncommon carbohydrate antigen sialyl-Tn (Tn), a surrogate biomarker of tumour aggressiveness. Such changes in the glycosylation of cell-surface proteins influence tumour microenvironment and immune responses that may modulate treatment outcome and the course of disease. The aim of this work is to determine the efficiency of BCG immunotherapy against tumours expressing sTn and sTn-related antigen sialyl-6-T (s6T). METHODS: In a retrospective design, 94 tumours from patients treated with BCG were screened for sTn and s6T expression. In vitro studies were conducted to determine the interaction of BCG with high-grade bladder cancer cell line overexpressing sTn. RESULTS: From the 94 cases evaluated, 36 had recurrence after BCG treatment (38.3%). Treatment outcome was influenced by age over 65 years (HR=2.668; (1.344-5.254); P=0.005), maintenance schedule (HR=0.480; (0.246-0.936); P=0.031) and multifocality (HR=2.065; (1.033-4.126); P=0.040). sTn or s6T expression was associated with BCG response (P=0.024; P<0.0001) and with increased recurrence-free survival (P=0.001). Multivariate analyses showed that sTn and/or s6T were independent predictive markers of recurrence after BCG immunotherapy (HR=0.296; (0.148-0.594); P=0.001). In vitro studies demonstrated higher adhesion and internalisation of the bacillus to cells expressing sTn, promoting cell death. CONCLUSION: s6T is described for the first time in bladder tumours. Our data strongly suggest that BCG immunotherapy is efficient against sTn- and s6T-positive tumours. Furthermore, sTn and s6T expression are independent predictive markers of BCG treatment response and may be useful in the identification of patients who could benefit more from this immunotherapy

Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host