The Exploration of Chemosensitivity Sites in Patients with Advanced Colorectal Cancer based on High-throughput Sequencing
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer
PROVIDER: 2692419 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Interventions: case series:Nil
Primary outcome(s): objective response rate
Study Design: Sequential
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Project description:Objective: The oral microbiota has been deeply studied by high-throughput sequencing techniques. However, although the interproximal regions have one of the highest caries rates in the oral cavity, information about the bacterial composition at those sites is scarce. Methods: In this study, we used 16S rRNA Illumina sequencing to describe the microbiota associated to interproximal regions at two time points. In addition, dental plaque samples at the vestibular and lingual surfaces from the same teeth were also analysed at the two time points. Results: Interproximal-associated microbiota was found to be similar to already described bacterial communities in other mouth niches. Streptoccocus, Veillonella, Rothia, Actinomyces, Neisseria, Haemophilus and Fusobacterium were the most abundant genera in this oral region. Statistical analyses showed that the microbiota from interproximal sites was more similar to that sampled from the vestibular surfaces than to the lingual surfaces. Interestingly, many potentially cariogenic bacteria such as Scardovia, Atopobium or Selenomonas were over-represented in the interproximal regions in comparison with vestibular and lingual sites. Conclusion: The microbiota at interproximal regions appears to be specific and stable through time. Potentially pathogenic bacteria may increase caries development risk and gingival inflammation at those sites.
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Project description:We report RNAseq data from tumors obtained from patients with triple negative breast cancer Eight patients with II-III stageTNBC diagnosis (only one patient with IV oligometastatic stage) were included in the study. All patients received neoadjuvant chemotherapy based on sequential anthracyclines and taxanes ± platinum salts plus radiation therapy. Seven patients were evaluable for response and pathological complete response (RCB=0) was reached in 71.4% of the patients (2 patients with RCB=2). No patients received adjuvant systemic therapy.Tumor biopsies were obtained for RNAseq studies.
2022-10-20 | GSE206998 | GEO
Project description:Interventions: Colorectal cancer group:None;Healthy control group:None
Primary outcome(s): Faecal flora
Study Design: Sequential
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Project description:ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint.
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Project description:Interventions: Study group:Total Neoadjuvant Therapy
Primary outcome(s): Pathological Complete Response;Objective Response Rate
Study Design: Single arm
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Project description:The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users' input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user's input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy's main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.
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Project description:Next-generation sequencing (NGS) allows faster acquisition of metagenomic data, but complete exploration of complex ecosystems is hindered by the extraordinary diversity of microorganisms. To reduce the environmental complexity, we created an innovative solution hybrid selection (SHS) method that is combined with NGS to characterize large DNA fragments harbouring biomarkers of interest. The quality of enrichment was evaluated after fragments containing the methyl coenzyme M reductase subunit A gene (mcrA), the biomarker of methanogenesis, were captured from a Methanosarcina strain and a metagenomic sample from a meromictic lake. The methanogen diversity was compared with direct metagenome and mcrA-based amplicon pyrosequencing strategies. The SHS approach resulted in the capture of DNA fragments up to 2.5 kb with an enrichment efficiency between 41 and 100%, depending on the sample complexity. Compared with direct metagenome and amplicons sequencing, SHS detected broader mcrA diversity, and it allowed efficient sampling of the rare biosphere and unknown sequences. In contrast to amplicon-based strategies, SHS is less biased and GC independent, and it recovered complete biomarker sequences in addition to conserved regions. Because this method can also isolate the regions flanking the target sequences, it could facilitate operon reconstructions.
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Project description:Transgenesis by random integration of a transgene into the genome of a zygote has become a reliable and powerful method for the creation of new mouse strains that express exogenous genes, including human disease genes, tissue specific reporter genes or genes that allow for tissue specific recombination. Nearly 6,500 transgenic alleles have been created by random integration in embryos over the last 30 years, but for the vast majority of these strains, the transgene insertion sites remain uncharacterized.To obtain a complete understanding of how insertion sites might contribute to phenotypic outcomes, to more cost effectively manage transgenic strains, and to fully understand mechanisms of instability in transgene expression, we've developed methodology and a scoring scheme for transgene insertion site discovery using high throughput sequencing data.Similar to other molecular approaches to transgene insertion site discovery, high-throughput sequencing of standard paired-end libraries is hindered by low signal to noise ratios. This problem is exacerbated when the transgene consists of sequences that are also present in the host genome. We've found that high throughput sequencing data from mate-pair libraries are more informative when compared to data from standard paired end libraries. We also show examples of the genomic regions that harbor transgenes, which have in common a preponderance of repetitive sequences.
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