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:Development of Raman spectroscopy-based microbial desorption technology for high-speed separation of functional single cells and genome analysis (KAP220340)
Project description:Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design and personalized medicine approaches for COVID-19.
Project description:This QSP model explains how the mechanism of action connects to the clinical outcomes and, therefore, may serve as an important model-based platform to guide the development and personalized dosing of the CART therapy.
Project description:This project intends to make a study of personalized medicine evaluation system establishment for liver cancer, gastric cancer and nasopharynx cancer to provide strong support for the development of Precision Medicine and personalized medicine for the patients of high-incidence-rates cancer in China.
Project description:This SuperSeries is composed of the following subset Series: GSE29996: Deep sequencing of gastric carcinoma reveals somatic mutations relevant to personalized medicine [Affymetrix SNP array data] GSE29998: Deep sequencing of gastric carcinoma reveals somatic mutations relevant to personalized medicine [Illumina mRNA expression array data] Refer to individual Series
Project description:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes. RNA was extracted from fresh frozen archival patient PanNET samples and hybridized on Affymetrix GeneChip human Gene 1.0 ST arrays. The CEL files were processed using R based bioconductor and normalized values were obtained using RMA.
