ArticleClinical colorectal cancer2016
A Plasma-Based Protein Marker Panel for Colorectal Cancer Detection Identified by Multiplex Targeted Mass Spectrometry.
Article in Clinical colorectal cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Lower Gastrointestinal Cancers: A Systematic Review and Meta-Analysis.Advances in therapy · 2021Pooled it
- Novel plasma protein signatures for early diagnosis and prognostic stratification in colorectal cancer.iScience · 2026Article
- Multiplexed Quantification of First-Trimester Serum Biomarkers in Healthy Pregnancy.International journal of molecular sciences · 2025Article
- Absolute Quantitative Targeted Monitoring of Potential Plasma Protein Biomarkers: A Pilot Study on Healthy Individuals.Biomedicines · 2024Article
- Mass spectrometry-based proteomics as an emerging tool in clinical laboratories.Clinical proteomics · 2023Review
- Tidyproteomics: an open-source R package and data object for quantitative proteomics post analysis and visualization.BMC bioinformatics · 2023Article
- Blood-derived molecular signatures as biomarker panels for the early detection of colorectal cancer.Molecular biology reports · 2020Review
- Cell-Free DNA Blood Collection Tubes Are Appropriate for Clinical Proteomics: A Demonstration in Colorectal Cancer.Proteomics. Clinical applications · 2018Article
- Quantitative mass spectrometry analysis reveals a panel of nine proteins as diagnostic markers for colon adenocarcinomas.Oncotarget · 2018Article
- Noninvasive Biomarkers of Colorectal Cancer: Role in Diagnosis and Personalised Treatment Perspectives.Gastroenterology research and practice · 2018Review
- Blood-Based Protein Signatures for Early Detection of Colorectal Cancer: A Systematic Review.Clinical and translational gastroenterology · 2017Article
- International scientific communications in the field of colorectal tumour markers.World journal of gastrointestinal surgery · 2017Article
- Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects.Clinical proteomics · 2017Article
- In Silico Prediction of Gamma-Aminobutyric Acid Type-A Receptors Using Novel Machine-Learning-Based SVM and GBDT Approaches.BioMed research international · 2016Article
Corrections and comments
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Authors and funding
20 authors at 3 institutions in 1 country.
Funding
Abstract
introductionColorectal cancer (CRC) testing programs reduce mortality; however, approximately 40% of the recommended population who should undergo CRC testing does not. Early colon cancer detection in patient populations ineligible for testing, such as the elderly or those with significant comorbidities, could have clinical benefit. Despite many attempts to identify individual protein markers of this disease, little progress has been made. Targeted mass spectrometry, using multiple reaction monitoring (MRM) technology, enables the simultaneous assessment of groups of candidates for improved detection performance. MATERIALS AND
methodsA multiplex assay was developed for 187 candidate marker proteins, using 337 peptides monitored through 674 simultaneously measured MRM transitions in a 30-minute liquid chromatography-mass spectrometry analysis of immunodepleted blood plasma. To evaluate the combined candidate marker performance, the present study used 274 individual patient blood plasma samples, 137 with biopsy-confirmed colorectal cancer and 137 age- and gender-matched controls. Using 2 well-matched platforms running 5 days each week, all 274 samples were analyzed in 52 days.
resultsUsing one half of the data as a discovery set (69 disease cases and 69 control cases), the elastic net feature selection and random forest classifier assembly were used in cross-validation to identify a 15-transition classifier. The mean training receiver operating characteristic area under the curve was 0.82. After final classifier assembly using the entire discovery set, the 136-sample (68 disease cases and 68 control cases) validation set was evaluated. The validation area under the curve was 0.91. At the point of maximum accuracy (84%), the sensitivity was 87% and the specificity was 81%.
conclusionThese results have demonstrated the ability of simultaneous assessment of candidate marker proteins using high-multiplex, targeted-mass spectrometry to identify a subset group of CRC markers with significant and meaningful performance.
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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.