Research On Large-Scale Proteomics Data From Non-and Minimally-Invasive Biopsies

With the completion of the human genome project,the post-genomic era has begun.Proteomics,as one of the most important research fields,has attracted extensive attention.Rapid progress within the proteomics field has opened up possibilities for direct intervention in the medical and clinical area where diseases,disease progression and cause of disease can be investigated at a molecular level.With the progression of the proteomics research projects,including Human Proteome Project(HPP),China Human Proteome Project(CNHPP),Clinical Proteomic Tumor Analysis Consortium(CPTAC),in this decade,proteomics has made a deep and wide exploration in the protein expression and changing rules under the physiological and pathological conditions in many model organisms.Recent developments in proteomics technology offer new opportunities for clinical applications in hospital or specialized laboratories including the identification of novel biomarkers,monitoring of disease,detecting adverse effects of drugs,and so on.However,the proteomes of human tissues and organs under physiological conditions have never been studied.In addition,human tissues are not completely uniform,more detailed studies on different regions,cells and structures of these tissues are still lacking.Moreover,before complex proteomic analysis can be introduced at a broader level into the clinic,definition of the real physiological condition including real healthy sample collection,sample preparation,sample storage,measurement,and bioinformatics analysis is another issue which has to be solved.It should also be mentioned that there is still a big problem to solve in proteomics research,that is,newly discovered biomarkers in proteomics always turn out to befailure.These results are mainly due to interpersonal differences.Therefore,how to solve these problems in big data has become a challenge for the development of proteomics.First,we present a global analysis of protein profiles of 82 apparently normal mucosa samples obtained from living individuals by endoscopic stomach biopsy.We identify6,258 high-confidence proteins and estimate the ranges of protein expression in the seven stomach regions,presenting a region-resolved proteome reference map of the near normal,human stomach.Furthermore,we measure mucosa protein profiles of tumor and tumor nearby tissues from 58 gastric cancer patients,enabling comparisons between tumor,TNT,and normal tissue.These datasets provide a rich resource for the gastrointestinal tract research community to investigate the molecular basis for region-specific functions in mucosa physiology and pathology including gastric cancer.Second,we evaluated variations in 497 urine proteomes from 167 healthy donors,establishing reference intervals(RIs)that covered urine protein variations.We demonstrated that RIs could be used to monitor physiological or pathological changes by detecting transient outlier proteins.Furthermore,we provided a RIs-based algorithm for biomarker discovery and validation to screen for diseases such as cancer.This study provided a proof-of-principle workflow for the use of urine proteome for health monitoring and disease screening.