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It remains unclear to what extent tumor heterogeneity impacts on protein biomarker discovery. Here, we quantified proteome intra-tissue heterogeneity (ITH) based on a multi-region analysis of prostate tissues using pressure cycling technology and Sequential Windowed Acquisition of all THeoretical fragment ion mass spectrometry. We quantified 6,873 proteins and analyzed the ITH of 3,700 proteins. The level of ITH varied depending on proteins and tissue types. Benign tissues exhibited more complex ITH patterns than malignant tissues. Spatial variability of 10 prostate biomarkers was validated by immunohistochemistry in an independent cohort (n = 83) using tissue microarrays. Prostate-specific antigen was preferentially variable in benign prostatic hyperplasia, whereas growth/differentiation factor 15 substantially varied in prostate adenocarcinomas. Furthermore, we found that DNA repair pathways exhibited a high degree of variability in tumorous tissues, which may contribute to the genetic heterogeneity of tumors. This study conceptually adds a new perspective to protein biomarker discovery: it suggests that recent technological progress should be exploited to quantify and account for spatial proteome variation to complement biomarker identification and utilization.
SWATH, tumors, 610 Medicine & health, 1301 Biochemistry, Genetics and Molecular Biology (miscellaneous), Resources, ITH, genetic heterogeneity, 10062 Urological Clinic, 10049 Institute of Pathology and Molecular Pathology, 1110 Plant Science, 2307 Health, Toxicology and Mutagenesis, biomarker, 2303 Ecology
SWATH, tumors, 610 Medicine & health, 1301 Biochemistry, Genetics and Molecular Biology (miscellaneous), Resources, ITH, genetic heterogeneity, 10062 Urological Clinic, 10049 Institute of Pathology and Molecular Pathology, 1110 Plant Science, 2307 Health, Toxicology and Mutagenesis, biomarker, 2303 Ecology
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 49 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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