Abstract
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 SWATH 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 ten prostate biomarkers was validated by immunohistochemistry in an independent cohort (n=83) using tissue microarrays. PSA was preferentially variable in benign prostatic hyperplasia, while GDF15 substantially varied in prostate adenocarcinomas. Further, 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.
Highlights
During the last decade, numerous new cancer treatment options have been developed
We further investigated the biological variation of selected proteins from the pressure cycling technology (PCT)-SWATH analysis using a complementary technology in an independent, larger cohort
We constructed a tissue microarray (TMA) using benign and malignant (ADCA) prostate tissues from 83 additional patients and established IHC assays to measure the expression of 10 representative proteins in the various intra-tissue heterogeneity (ITH) groups identified from the PCT-SWATH results, including actin related protein 1 homolog B (ACTR1B), DES, prostate-specific antigen (PSA), and growth/differentiation factor 15 (GDF15) as shown in Fig 5, as well as ACPP, ABCF1, NUP93, CUTA, CRAT, and FSTL1 (Fig S5)
Summary
Numerous new cancer treatment options have been developed Their optimal application, requires better molecular characterization of the tumors with the aim of developing biomarkers matching the specific tumor to the best available therapy. Some cancer types, such as prostate cancer, still suffer from an “over-treatment problem,” i.e., radical therapy such as removal of the organ in unnecessary cases because of uncertain diagnosis. These problems persist despite the recent progress in genomic, transcriptomic, and proteomic profiling of tumors. It remains a challenge to optimize clinical decisions based on single biopsies (Boutros et al, 2015)
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