Richer gut microbiota with distinct metabolic profile in HIV infected Elite Controllers.

Gut microbiota dysbiosis features progressive HIV infection and is a potential target for intervention. Herein, we explored the microbiome of 16 elite controllers (EC), 32 antiretroviral therapy naive progressors and 16 HIV negative controls. We found that the number of observed genera and richness indices in fecal microbiota were significantly higher in EC versus naive. Genera Succinivibrio, Sutterella, Rhizobium, Delftia, Anaerofilum and Oscillospira were more abundant in EC, whereas Blautia and Anaerostipes were depleted. Additionally, carbohydrate metabolism and secondary bile acid synthesis pathway related genes were less represented in EC. Conversely, fatty acid metabolism, PPAR-signalling and lipid biosynthesis proteins pathways were enriched in EC vs naive. The kynurenine pathway of tryptophan metabolism was altered during progressive HIV infection, and inversely associated with microbiota richness. In conclusion, EC have richer gut microbiota than untreated HIV patients, with unique bacterial signatures and a distinct metabolic profile which may contribute to control of HIV.

A new PDAC mouse model originated from iPSCs-converted pancreatic cancer stem cells (CSCcm).

Pancreatic ductal adenocarcinoma (PDAC) is the most representative form of pancreatic cancers. PDAC solid tumours are constituted of heterogeneous populations of cells including cancer stem cells (CSCs), differentiated cancer cells, desmoplastic stroma and immune cells. The identification and consequent isolation of pancreatic CSCs facilitated the generation of genetically engineered murine models. Nonetheless, the current models may not be representative for the spontaneous tumour occurrence. In the present study, we show the generation of a novel pancreatic iPSC-converted cancer stem cell lines (CSCcm) as a cutting-edge model for the study of PDAC. The CSCcm lines were achieved only by the influence of pancreatic cancer cell lines conditioned medium and were not subjected to any genetic manipulation. The xenografts tumours from CSCcm lines displayed histopathological features of ADM, PanIN and PDAC lesions. Further molecular characterization from RNA-sequencing analysis highlighted primary culture cell lines (1st CSCcm) as potential candidates to represent the pancreatic CSCs and indicated the establishment of the pancreatic cancer molecular pattern in their subsequent progenies 2nd CSCcm and 3rd CSCcm. In addition, preliminary RNA-seq SNPs analysis showed that the distinct CSCcm lines did not harbour single point mutations for the oncogene Kras codon 12 or 13. Therefore, PDAC-CSCcm model may provide new insights about the actual occurrence of the pancreatic cancer leading to develop different approaches to target CSCs and abrogate the progression of this fatidic disease.

Risk prediction scores for recurrence and progression of non-muscle invasive bladder cancer: an international validation in primary tumours.

OBJECTIVE: We aimed to determine the validity of two risk scores for patients with non-muscle invasive bladder cancer in different European settings, in patients with primary tumours. METHODS: We included 1,892 patients with primary stage Ta or T1 non-muscle invasive bladder cancer who underwent a transurethral resection in Spain (n = 973), the Netherlands (n = 639), or Denmark (n = 280). We evaluated recurrence-free survival and progression-free survival according to the European Organisation for Research and Treatment of Cancer (EORTC) and the Spanish Urological Club for Oncological Treatment (CUETO) risk scores for each patient and used the concordance index (c-index) to indicate discriminative ability. RESULTS: The 3 cohorts were comparable according to age and sex, but patients from Denmark had a larger proportion of patients with the high stage and grade at diagnosis (p<0.01). At least one recurrence occurred in 839 (44%) patients and 258 (14%) patients had a progression during a median follow-up of 74 months. Patients from Denmark had the highest 10-year recurrence and progression rates (75% and 24%, respectively), whereas patients from Spain had the lowest rates (34% and 10%, respectively). The EORTC and CUETO risk scores both predicted progression better than recurrence with c-indices ranging from 0.72 to 0.82 while for recurrence, those ranged from 0.55 to 0.61. CONCLUSION: The EORTC and CUETO risk scores can reasonably predict progression, while prediction of recurrence is more difficult. New prognostic markers are needed to better predict recurrence of tumours in primary non-muscle invasive bladder cancer patients.

An efficient algorithm to perform multiple testing in epistasis screening.

BACKGROUND: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn's disease. RESULTS: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn's disease (CD) data. CONCLUSIONS: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn's disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.