Project description:Whole genome sequencing of 10 HCLc tumor and matched-germline T cells. Genomic DNA from highly purified HCLc tumor and T cell populations were utilized for library preparation using NEBNext Ultra DNA library prep kit. Sequencing was performed as 150 bp paired end sequencing using four lanes of an Illumina HiSeq4000 to an average depth of 12X. Reads from each library were aligned to the human reference genome GRCh37 using BWA-MEM (v0.7.12). The analysis of somatic genetic alterations in WGS data from tumor-germline pair HCLc samples was divided based on the nature of the mutation, as follow: single-nucleotide variants (SNVs), indels, CNAs and SVs. Moreover, COSMIC mutational signatures and subclonal architecture was inferred for each tumor.
Project description:The next generation of personalized medical treatment according to the type of personal genetic information are evolving rapidly. The genome analysis needs systematic infra and database based on personal genetic information. Therefore, a big data of genome-clinical information is important.
To determine the feasibility of the use of tumor’s molecular profiling and targeted therapies in the treatment of advanced cancer and to determine the clinical outcome(Response rate,PFS, duration of response and overall survival )of patients with advanced cancer, the investigators are going to take a tumor tissue of patients and process molecular profiling and receive molecular profile directed treatments.
Project description:Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Understanding of the intratumoral heterogeneity of HCC is instructive for developing personalized therapy and molecular biomarkers. We applied whole exome sequencing to a total of 63 samples from 11 patients to resolve the genetic architecture and subclonal diversification. Notably, spatial genomic diversity was found in all 11 HCC cases, with 33% of the driver mutations being heterogeneous. Temporal dissection of mutational signatures suggested that exogenous and endogenous factors have different contributions in shaping the mutational spectrum during the development of HCC. Moreover, we observed extensive intratumoral epigenetic heterogeneity in HCC, and showed that integrative analysis of both genetic and epigenetic phylogenies could generate more robust resolution of clonal architecture than single profiling approach. Our results also demonstrated prominent epigenetic subclonal diversification even in a stable HCC genome. Together, these findings highlight the widespread intratumoral heterogeneity at both genomic and epigenomic levels in HCC, and provide important molecular foundation for better understanding of the biology and pathogenesis of this malignancy.
Project description:Genotyping studies suggest that there is genetic variability among P. gingivalis strains, however the extent of variability remains unclear, and the regions of variability have only partially been identified. We previously used heteroduplex analysis of the ribosomal operon intergenic spacer region (ISR) to type P. gingivalis strains in several diverse populations, identifying 6 predominant heteroduplex types and many minor ones. In addition we used ISR sequence analysis to determine the relatedness of P. gingivalis strains to one another, and demonstrated a link between ISR sequence phylogeny and the disease-associated phenotype of P. gingivalis strains. The availability of whole genome microarrays based on the genomic sequence of strain W83 has allowed a more comprehensive analysis of P. gingivalis strain variability, using the entire genome. The objectives of this study were to define the phylogeny of P. gingivalis strains using the entire genome, to compare the phylogeny based on genome content to the phylogeny based on a single locus (ISR), and to identify genes that are associated with the strongly disease-associated strain W83 that could be important for virulence. Keywords: Comparative genomic hybridization
Project description:Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.
Project description:Expansion microscopy is a recently introduced imaging technique that achieves super-resolution through physically expanding the specimen by ~4×, after embedding into a swellable gel. The resolution attained is, correspondingly, approximately fourfold better than the diffraction limit, or ~70 nm. This is a major improvement over conventional microscopy, but still lags behind modern STED or STORM setups, whose resolution can reach 20-30 nm. We addressed this issue here by introducing an improved gel recipe that enables an expansion factor of ~10× in each dimension, which corresponds to an expansion of the sample volume by more than 1,000-fold. Our protocol, which we termed X10 microscopy, achieves a resolution of 25-30 nm on conventional epifluorescence microscopes. X10 provides multi-color images similar or even superior to those produced with more challenging methods, such as STED, STORM, and iterative expansion microscopy (iExM). X10 is therefore the cheapest and easiest option for high-quality super-resolution imaging currently available. X10 should be usable in any laboratory, irrespective of the machinery owned or of the technical knowledge.