Evidence map›Paper›PMID 28650989›Full record

ArticlePloS one2017

Tumor tissue protein signatures reflect histological grade of breast cancer.

Petter Skoog, Mattias Ohlsson, Mårten Fernö, Lisa Rydén, Carl A K Borrebaeck, Christer Wingren

Abstract readValidation Study
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Protein Signatures and Tissue Diagnosis of Pancreatic Cancer.Journal of the American College of Surgeons · 2020
    Article
  4. Article
  5. Review
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

6 authors.

Petter SkoogDept. of Immunotechnology, Lund University, Medicon Village, Lund, Sweden.
Mattias OhlssonComputational Biology & Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
Mårten FernöDepartment of Oncology and Pathology, Clinical Sciences, Lund University, Lund, Sweden.
Lisa RydénDepartment of Surgery, Clinical Sciences, Lund University, Lund, Sweden.
Carl A K BorrebaeckDept. of Immunotechnology, Lund University, Medicon Village, Lund, Sweden.
Christer WingrenDept. of Immunotechnology, Lund University, Medicon Village, Lund, Sweden.ORCID http://orcid.org/0000-0002-8729-9273

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histological grade is one of the most commonly used prognostic factors for patients diagnosed with breast cancer. However, conventional grading has proven technically challenging, and up to 60% of the tumors are classified as histological grade 2, which represents a heterogeneous cohort less informative for clinical decision making. In an attempt to study and extend the molecular puzzle of histologically graded breast cancer, we have in this pilot project searched for additional protein biomarkers in a new space of the proteome. To this end, we have for the first time performed protein expression profiling of breast cancer tumor tissue, using recombinant antibody microarrays, targeting mainly immunoregulatory proteins. Thus, we have explored the immune system as a disease-specific sensor (clinical immunoproteomics). Uniquely, the results showed that several biologically relevant proteins reflecting histological grade could be delineated. In more detail, the tentative biomarker panels could be used to i) build a candidate model classifying grade 1 vs. grade 3 tumors, ii) demonstrate the molecular heterogeneity among grade 2 tumors, and iii) potentially re-classify several of the grade 2 tumors to more like grade 1 or grade 3 tumors. This could, in the long-term run, lead to improved prognosis, by which the patients could benefit from improved tailored care.

Indexed as

AdultAgedBiomarkers, TumorBreast NeoplasmsFemaleHumansMiddle AgedNeoplasm GradingNeoplasm ProteinsPilot ProjectsPrognosisProtein Array AnalysisSingle-Chain AntibodiesBiomarkers, TumorNeoplasm ProteinsSingle-Chain Antibodies

Identifiers

PMID28650989
PMCPMC5484475

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Registered trials

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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.