Evidence map›Paper›PMID 31357969›Full record

ArticleBMC cancer2019

Multiplex plasma protein profiling identifies novel markers to discriminate patients with adenocarcinoma of the lung.

Dijana Djureinovic, Victor Pontén, Per Landelius, Sahar Al Sayegh, Kai Kappert, Masood Kamali-Moghaddam, Patrick Micke, Elisabeth Ståhle

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Biomarkers Suitable for Early Detection of Intrathoracic Cancers in Primary Care: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Pooled it
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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

8 authors at 2 institutions in 2 countries.

Dijana DjureinovicDepartment of Immunology, Genetics and Pathology, Uppsala University, 751 85, Uppsala, Sweden. dijana.djureinovic@igp.uu.se.ORCID http://orcid.org/0000-0002-1852-5409
Victor PonténDepartment of Immunology, Genetics and Pathology, Uppsala University, 751 85, Uppsala, Sweden.
Per LandeliusDepartment of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Sahar Al SayeghDepartment of Immunology, Genetics and Pathology, Uppsala University, 751 85, Uppsala, Sweden.
Kai KappertInstitute of Laboratory Medicine, Clinical Chemistry and Pathobiochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
Masood Kamali-MoghaddamDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Patrick MickeDepartment of Immunology, Genetics and Pathology, Uppsala University, 751 85, Uppsala, Sweden.
Elisabeth StåhleDepartment of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Uppsala University · SEHumboldt-Universität zu Berlin · DE

Funding

Cancerfonden 2012/738Lions Cancer Foundation Uppsala NA
6 · The paper itself

Abstract

backgroundThe overall prognosis of non-small cell lung cancer (NSCLC) is poor, and currently only patients with localized disease are potentially curable. Therefore, preferably non-invasively determined biomarkers that detect NSCLC patients at early stages of the disease are of high clinical relevance. The aim of this study was to identify and validate novel protein markers in plasma using the highly sensitive DNA-assisted multiplex proximity extension assay (PEA) to discriminate NSCLC from other lung diseases.

methodsPlasma samples were collected from a total of 343 patients who underwent surgical resection for different lung diseases, including 144 patients with lung adenocarcinoma (LAC), 68 patients with non-malignant lung disease, 83 patients with lung metastasis of colorectal cancers and 48 patients with typical carcinoid. One microliter of plasma was analyzed using PEA, allowing detection and quantification of 92 established cancer related proteins. The concentrations of the plasma proteins were compared between disease groups.

resultsThe comparison between LAC and benign samples revealed significantly different plasma levels for four proteins; CXCL17, CEACAM5, VEGFR2 and ERBB3 (adjusted p-value < 0.05). A multi-parameter classifier was developed to discriminate between samples from LAC patients and from patients with non-malignant lung conditions. With a bootstrap aggregated decision tree algorithm (TreeBagger), a sensitivity of 93% and specificity of 64% was achieved to detect LAC in this risk population.

conclusionsBy applying the highly sensitive PEA, reliable protein profiles could be determined in microliter amounts of plasma. We further identified proteins that demonstrated different plasma concentration in defined disease groups and developed a signature that holds potential to be included in a screening assay for early lung cancer detection.

Indexed as

Adenocarcinoma of LungAgedBlood ProteinsCarcinoembryonic AntigenCarcinoma, Non-Small-Cell LungChemokines, CXCCohort StudiesData AccuracyEarly Detection of CancerFemaleGPI-Linked ProteinsHumansImmunoassayLung NeoplasmsMaleMass ScreeningBlood ProteinsCarcinoembryonic AntigenCEACAM5 protein, humanChemokines, CXCCXCL17 protein, humanERBB3 protein, humanGPI-Linked ProteinsKDR protein, humanReceptor, ErbB-3Vascular Endothelial Growth Factor Receptor-2BiomarkerBloodLung cancerPlasmaScreeningTumor markers

Identifiers

PMID31357969
PMCPMC6664554
OpenAlexW2802516363

What OpenQuestion holds

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LicenceCC BY
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.