ArticleProteomics2017
Quantitative proteomics of breast tumors: Tissue quality assessment to clinical biomarkers.
Article in Proteomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Mass spectrometry-based proteomics of FFPE tissues: progress, limitations, and clinical translation barriers.Clinical proteomics · 2025Review
- An integrated modelling approach for targeted degradation: insights on optimization, data requirements and PKPD predictions from semi- or fully-mechanistic models and exact steady state solutions.Journal of pharmacokinetics and pharmacodynamics · 2023Article
- Deciphering Phenotypes from Protein Biomarkers for Translational Research with PIPER.Journal of proteome research · 2023Article
- Proteomics for cancer drug design.Expert review of proteomics · 2019Article
- Proteomic Technology "Lens" for Epithelial-Mesenchymal Transition Process Identification in Oncology.Analytical cellular pathology (Amsterdam) · 2019Review
- Development of parallel reaction monitoring (PRM)-based quantitative proteomics applied to HER2-Positive breast cancer.Oncotarget · 2018Article
- Quantification of Breast Cancer Protein Biomarkers at Different Expression Levels in Human Tumors.Methods in molecular biology (Clifton, N.J.) · 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
7 authors at 4 institutions in 2 countries.
Funding
Abstract
Liquid chromatography-selected reaction monitoring mass spectrometry (LC-SRM) is not only a proven tool for clinical chemistry, but also a versatile method to enhance the capability to quantify biomarkers for tumor biology research. As the treatment of cancer continues to evolve, the ability to assess multiple biomarkers to assign cancer phenotypes based on the genetic background and the signaling of the individual tumor becomes paramount to our ability to treat the patient. In breast cancer, the American Society of Clinical Oncology has defined biomarkers for patient assessment to guide selection of therapy: estrogen receptor, progesterone receptor, and the HER2/Neu receptor tyrosine kinase; therefore, these proteins were selected for LC-SRM assay development. Detailed molecular characterization of these proteins is necessary for patient treatment, so expression and phosphorylation assays have been developed and applied. In addition, other LC-SRM assays were developed to further evaluate tumor biology (e.g. Ki-67 for proliferation and vimentin for tumor aggressiveness related to the epithelial-to-mesenchymal transition). These measurements combined with biomarkers for tissue quality and histological content are implemented in a three-tier multiplexed assay platform, which is translated from cell line models into frozen tumor tissues banked from breast cancer patients.
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.