ArticleProceedings of the National Academy of Sciences of the United States of America2011
Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 2 of them syntheses that pooled it.
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Who cites it
93 citing papers in PubMed, 2 syntheses or guidelines pooled it, 192 citations in OpenAlex.
- Proclarix, A New Biomarker for the Diagnosis of Clinically Significant Prostate Cancer: A Systematic Review.Molecular diagnosis & therapy · 2022Pooled it
- Pooled it
- When less is more: Counterintuitive stoichiometries and cellular abundances are essential for ABC transporters' function.Science advances · 2025Article
- Proteomics of prostate cancer serum and plasma using low and high throughput approaches.Clinical proteomics · 2024Article
- Advances in multiparametric magnetic resonance imaging combined with biomarkers for the diagnosis of high-grade prostate cancer.Frontiers in surgery · 2024Review
- The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery.Biomedicines · 2023Review
- Development of a predictive model to distinguish prostate cancer from benign prostatic hyperplasia by integrating serum glycoproteomics and clinical variables.Clinical proteomics · 2023Article
- Resolving the Temporal Splenic Proteome during Fungal Infection for Discovery of Putative Dual Perspective Biomarker Signatures.Journal of the American Society for Mass Spectrometry · 2023Article
- Relationship between Proclarix and the Aggressiveness of Prostate Cancer.Molecular diagnosis & therapy · 2023Article
- Data-Independent Acquisition Mass Spectrometry of EPS-Urine Coupled to Machine Learning: A Predictive Model for Prostate Cancer.ACS omega · 2023Article
- A Novel Blood Proteomic Signature for Prostate Cancer.Cancers · 2023Article
- Intact glycopeptides identified by LC-MS/MS as biomarkers for response to chemotherapy of locally advanced cervical cancer.Frontiers in oncology · 2023Article
- Incubating Green Synthesized Iron Oxide Nanorods for Proteomics-Derived Motif Exploration: A Fusion to Deep Learning Oncogenesis.ACS omega · 2022Article
- Article
- Use of MS-GUIDE for identification of protein biomarkers for risk stratification of patients with prostate cancer.Clinical proteomics · 2022Article
- The Efficacy of Proclarix to Select Appropriate Candidates for Magnetic Resonance Imaging and Derived Prostate Biopsies in Men with Suspected Prostate Cancer.The world journal of men's health · 2022Article
- Development and validation of a multiparametric MRI-based radiomics signature for distinguishing between indolent and aggressive prostate cancer.The British journal of radiology · 2022Article
- Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry.Nature reviews. Urology · 2021Review
- Review
- Mass Spectrometry-Based Glycoproteomics and Prostate Cancer.International journal of molecular sciences · 2021Review
33 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A key barrier to the realization of personalized medicine for cancer is the identification of biomarkers. Here we describe a two-stage strategy for the discovery of serum biomarker signatures corresponding to specific cancer-causing mutations and its application to prostate cancer (PCa) in the context of the commonly occurring phosphatase and tensin homolog (PTEN) tumor-suppressor gene inactivation. In the first stage of our approach, we identified 775 N-linked glycoproteins from sera and prostate tissue of wild-type and Pten-null mice. Using label-free quantitative proteomics, we showed that Pten inactivation leads to measurable perturbations in the murine prostate and serum glycoproteome. Following bioinformatic prioritization, in a second stage we applied targeted proteomics to detect and quantify 39 human ortholog candidate biomarkers in the sera of PCa patients and control individuals. The resulting proteomic profiles were analyzed by machine learning to build predictive regression models for tissue PTEN status and diagnosis and grading of PCa. Our approach suggests a general path to rational cancer biomarker discovery and initial validation guided by cancer genetics and based on the integration of experimental mouse models, proteomics-based technologies, and computational modeling.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.