ArticleJournal of proteome research2016
Optimized Protocol for Quantitative Multiple Reaction Monitoring-Based Proteomic Analysis of Formalin-Fixed, Paraffin-Embedded Tissues.
Article in Journal of proteome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03765450 (Pharmacokinetics of Infliximab and Tumor Necrosis Factor Concentrations in Serum, Stool, and Colonic Mucosa in Acute Severe Ulcerative Colitis), which is not on this map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Pharmacokinetics of Infliximab and Tumor Necrosis Factor Concentrations in Serum, Stool, and Colonic Mucosa in Acute Severe Ulcerative Colitis
Who cites it
24 citing papers in PubMed.
- Mass spectrometry-based proteomics of FFPE tissues: progress, limitations, and clinical translation barriers.Clinical proteomics · 2025Review
- Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer.Scientific reports · 2025Article
- Article
- A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Clinical Proteomics for Solid Organ Tissues.Molecular & cellular proteomics : MCP · 2023Article
- Article
- Cellular Therapy for Children with Central Nervous System Tumors: Mining and Mapping the Correlative Data.Current oncology reports · 2023Review
- ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues.Analytical chemistry · 2023Article
- Intraventricular B7-H3 CAR T Cells for Diffuse Intrinsic Pontine Glioma: Preliminary First-in-Human Bioactivity and Safety.Cancer discovery · 2023Article
- Quantification of Human Epidermal Growth Factor Receptor 2 by Immunopeptide Enrichment and Targeted Mass Spectrometry in Formalin-Fixed Paraffin-Embedded and Frozen Breast Cancer Tissues.Clinical chemistry · 2021Article
- Comparative evaluation of two methods for LC-MS/MS proteomic analysis of formalin fixed and paraffin embedded tissues.Journal of proteomics · 2021Review
- Targeted Mass Spectrometry Enables Multiplexed Quantification of Immunomodulatory Proteins in Clinical Biospecimens.Frontiers in immunology · 2021Article
- A Novel Nanoproteomic Approach for the Identification of Molecular Targets Associated with Thyroid Tumors.Nanomaterials (Basel, Switzerland) · 2020Article
- Accelerated instability testing reveals quantitative mass spectrometry overcomes specimen storage limitations associated with PD-L1 immunohistochemistry.Laboratory investigation; a journal of technical methods and pathology · 2020Article
- Quantitative Profiling of the Human Substantia Nigra Proteome from Laser-capture Microdissected FFPE Tissue.Molecular & cellular proteomics : MCP · 2020Article
- High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification.Molecular oncology · 2019Article
- Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper.Clinical pharmacology and therapeutics · 2019Article
- Fibrinogen alpha amyloidosis: insights from proteomics.Expert review of proteomics · 2019Review
- Clinical potential of mass spectrometry-based proteogenomics.Nature reviews. Clinical oncology · 2019Review
- Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers.Expert review of proteomics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Despite a clinical, economic, and regulatory imperative to develop companion diagnostics, precious few new biomarkers have been successfully translated into clinical use, due in part to inadequate protein assay technologies to support large-scale testing of hundreds of candidate biomarkers in formalin-fixed paraffin-embedded (FFPE) tissues. Although the feasibility of using targeted, multiple reaction monitoring mass spectrometry (MRM-MS) for quantitative analyses of FFPE tissues has been demonstrated, protocols have not been systematically optimized for robust quantification across a large number of analytes, nor has the performance of peptide immuno-MRM been evaluated. To address this gap, we used a test battery approach coupled to MRM-MS with the addition of stable isotope-labeled standard peptides (targeting 512 analytes) to quantitatively evaluate the performance of three extraction protocols in combination with three trypsin digestion protocols (i.e., nine processes). A process based on RapiGest buffer extraction and urea-based digestion was identified to enable similar quantitation results from FFPE and frozen tissues. Using the optimized protocols for MRM-based analysis of FFPE tissues, median precision was 11.4% (across 249 analytes). There was excellent correlation between measurements made on matched FFPE and frozen tissues, both for direct MRM analysis (R(2) = 0.94) and immuno-MRM (R(2) = 0.89). The optimized process enables highly reproducible, multiplex, standardizable, quantitative MRM in archival tissue specimens.
Indexed as
Identifiers
What OpenQuestion holds
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.