Evidence map›Paper›PMID 31289117›Full record

ArticleMolecular & cellular proteomics : MCP2019

A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer.

Ruth Hüttenhain, Meena Choi, Laura Martin de la Fuente, Kathrin Oehl, Ching-Yun Chang, Anne-Kathrin Zimmermann, Susanne Malander, Håkan Olsson, Silvia Surinova, Timothy Clough and 6 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.5field-weighted citation impact, top 6% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 109 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 9 institutions in 4 countries.

Ruth Hüttenhain‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland. Electronic address: ruth.huttenhain@ucsf.edu.
Meena Choi§Khoury College of Computer Sciences, Northeastern University, Boston, MA.
Laura Martin de la Fuente¶Department of Surgery and Oncology, Clinical Sciences, Lund University, Lund, Sweden.
Kathrin Oehl‖Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
Ching-Yun Chang**Department of Statistics, Purdue University, West Lafayette, IN.
Anne-Kathrin Zimmermann‖Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
Susanne Malander¶Department of Surgery and Oncology, Clinical Sciences, Lund University, Lund, Sweden.
Håkan Olsson¶Department of Surgery and Oncology, Clinical Sciences, Lund University, Lund, Sweden.
Silvia Surinova‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
Timothy Clough**Department of Statistics, Purdue University, West Lafayette, IN.
Viola Heinzelmann-Schwarz‡‡Gynecological Cancer Center, University Hospital Basel, University of Basel, Basel, Switzerland; §§Ovarian Cancer Research, Department of Biomedicine, University of Basel, Basel, Switzerland.
Peter J Wild¶¶Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Daniela M Dinulescu‖‖Department of Pathology, Division of Women's and Perinatal Pathology Brigham and Women's Hospital Harvard Medical School, Boston, MA.
Emma Niméus¶Department of Surgery and Oncology, Clinical Sciences, Lund University, Lund, Sweden; ‡‡‡Department of Surgery, Skånes University hospital, Lund, Sweden.
Olga Vitek§Khoury College of Computer Sciences, Northeastern University, Boston, MA; **Department of Statistics, Purdue University, West Lafayette, IN.
Ruedi Aebersold‡Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland; §§§Faculty of Science, University of Zurich, 8057 Zurich, Switzerland.
Lund University · SEETH Zurich · CHNortheastern University · USPurdue University West Lafayette · USUniversity Hospital of Zurich · CHBrigham and Women's Hospital · USGoethe University Frankfurt · DEUniversity of Basel · CHUniversity of Zurich · CH

Funding

Wellcome Trust
6 · The paper itself

Abstract

Protein biomarkers for epithelial ovarian cancer are critical for the early detection of the cancer to improve patient prognosis and for the clinical management of the disease to monitor treatment response and to detect recurrences. Unfortunately, the discovery of protein biomarkers is hampered by the limited availability of reliable and sensitive assays needed for the reproducible quantification of proteins in complex biological matrices such as blood plasma. In recent years, targeted mass spectrometry, exemplified by selected reaction monitoring (SRM) has emerged as a method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing plasma-based protein biomarkers for epithelial ovarian cancer and illustrate how the SRM platform, when combined with rigorous experimental design and statistical analysis, can result in detection of predictive analytes.Our biomarker development strategy first involved a discovery-driven proteomic effort to derive potential

Indexed as

AnimalsAntigens, NeoplasmBiomarkers, TumorBlood ProteinsCA-125 AntigenCarcinoma, Ovarian EpithelialCase-Control StudiesCohort StudiesDesmoglein 2Extracellular Matrix ProteinsFemaleHeavy Chain DiseaseHumansImmunoglobulin mu-ChainsMass SpectrometryMembrane ProteinsAntigens, NeoplasmBiomarkers, TumorBlood ProteinsCA-125 AntigenDesmoglein 2DSG2 protein, humanExtracellular Matrix ProteinsIGHM protein, humanImmunoglobulin mu-ChainsL1CAM protein, humanLGALS3BP protein, humanMembrane ProteinsMUC16 protein, humanNeural Cell Adhesion Molecule L1Thrombospondin 1thrombospondin-1, humanCancer biomarker(s)ovarian cancerplasma or serum analysisquantificationselected reaction monitoringstatisticstargeted mass spectrometry

Identifiers

PMID31289117
PMCPMC6731088
OpenAlexW2957410556

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.