ArticleProteomics. Clinical applications2014
Identification of plasma protein profiles associated with risk groups of prostate cancer patients.
Article in Proteomics. Clinical applications, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Article
- Bead-based microfluidic platforms for multiplex and ultrasensitive immunoassays in clinical diagnosis and treatment.Mechanobiology in medicine · 2024Review
- Review
- The Value of a New Diagnostic Test for Prostate Cancer: A Cost-Utility Analysis in Early Stage of Development.PharmacoEconomics - open · 2021Article
- Current applications of antibody microarrays.Clinical proteomics · 2018Review
- Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.Nature reviews. Cancer · 2017Review
- Multiplexed protein profiling by sequential affinity capture.Proteomics · 2016Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 3 countries.
Funding
Abstract
purposeEarly detection of prostate cancer (PC) using prostate-specific antigen (PSA) in blood reduces PC-death among unscreened men. However, due to modest specificity of PSA at commonly used cut-offs, there are urgent needs for additional biomarkers contributing enhanced risk classification among men with modestly elevated PSA. EXPERIMENTAL
designRecombinant antibody microarrays were applied for protein expression profiling of 80 plasma samples from routine PSA-measurements, a priori divided into four risk groups, based on levels of total and %free PSA.
resultsThe results demonstrated that plasma protein profiles could be identified that pin-pointed PC (a malignant biomarker signature) and most importantly that showed moderate to high correlation with biochemically defined PC risk groups. Notably, the data also implied that the risk group with midrange PSA and low %free PSA, a priori known to be heterogeneous, could be further stratified into two subgroups, more resembling the lowest and highest risk groups, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: In this pilot study, we have shown that plasma protein biomarker signatures, associated with risk groups of PC, could be identified from crude plasma samples using affinity proteomics. This approach could in the longer perspective provide novel opportunities for improved risk classification of PC patients.
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Registered trials
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