Evidence map›Paper›PMID 28428887›Full record

ArticleJournal for immunotherapy of cancer2017

Differential intratumoral distributions of CD8 and CD163 immune cells as prognostic biomarkers in breast cancer.

Sotirios P Fortis, Michael Sofopoulos, Nectaria N Sotiriadou, Christoforos Haritos, Christoforos K Vaxevanis, Eleftheria A Anastasopoulou, Nicole Janssen, Niki Arnogiannaki, Alexandros Ardavanis, Graham Pawelec and 2 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

64 citing papers in PubMed, 93 citations in OpenAlex.

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  11. CD103Clinical and translational medicine · 2025
    Article
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  17. CD163Breast cancer research : BCR · 2024
    Article
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4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 2 countries.

Sotirios P Fortis *Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, Athens, Greece.
Michael Sofopoulos *Pathology Department, Saint Savas Cancer Hospital, Athens, Greece.
Nectaria N SotiriadouPathology Department, Saint Savas Cancer Hospital, Athens, Greece.
Christoforos HaritosCancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, Athens, Greece.
Christoforos K VaxevanisCancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, Athens, Greece.
Eleftheria A AnastasopoulouCancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, Athens, Greece.
Nicole JanssenCenter for Medical Research, Eberhard-Karls Universität, Tübingen, Germany.
Niki ArnogiannakiPathology Department, Saint Savas Cancer Hospital, Athens, Greece.
Alexandros ArdavanisFirst Medical Oncology Clinic, Saint Savas Cancer Hospital, Athens, Greece.
Graham PawelecCenter for Medical Research, Eberhard-Karls Universität, Tübingen, Germany.
Sonia A Perez *Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, Athens, Greece.
Constantin N Baxevanis *Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, Athens, Greece.
St Savas Hospital · GRCenter for Clinical Research (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor immune cell infiltrates are essential in hindering cancer progression and may complement the TNM classification. CD8+ and CD163+ cells have prognostic impact in breast cancer but their spatial heterogeneity has not been extensively explored in this type of cancer. Here, their potential as prognostic biomarkers was evaluated, depending on their combined densities in the tumor center (TC) and the tumor invasive margin (IM).

methodsCD8+ and CD163+ cells were quantified by immunohistochemistry of formalin-fixed, paraffin-embedded (FFPE) tumor tissue samples from a cohort totaling 162 patients with histologically-confirmed primary invasive non-metastatic ductal breast cancer diagnosed between 2000 and 2015. Clinical follow-up (median 6.9 years) was available for 97 of these patients.

resultsDifferential densities of CD8+ and CD163+ cells in the combined TC and IM compartments (i.e., high(H)/low(L), respectively for CD8+ cells and the reverse L/H combination for CD163+ cells) were found to have significant prognostic value for survival, and allowed better patient stratification than TNM stage, tumor size, lymph node invasion and histological grade. The combined evaluation of CD8+ and CD163+ cell densities jointly in TC and IM further improves prediction of clinical outcomes based on disease-free and overall survival. Patients having the favorable immune signatures had favorable clinical outcomes despite poor clinicopathological parameters.

conclusionsGiven the important roles of CD8+ and CD163+ cells in regulating opposing immune circuits, adding an assessment of their differential densities to the prognostic biomarker armamentarium in breast cancer would be valuable. Larger validation studies are necessary to confirm these findings. TRIAL REGISTRATIONS: Study code: IRB-ID 6079/448/10-6-13 Date of approval: 10/06/2013 Retrospective study (2000-2010) First patient prospectively enrolled 14/2/2014.

Indexed as

AdultAgedAntigens, CDAntigens, Differentiation, MyelomonocyticBiomarkers, TumorBreast NeoplasmsCD163 AntigenCD8-Positive T-LymphocytesFemaleHumansMiddle AgedPrognosisReceptors, Cell SurfaceAntigens, CDAntigens, Differentiation, MyelomonocyticBiomarkers, TumorCD163 AntigenReceptors, Cell SurfaceBreast cancerCD163CD8ImmunoscoringPrognostic signatureTumor infiltration

Identifiers

PMID28428887
PMCPMC5395775
OpenAlexW2605865590

What OpenQuestion holds

Textmetadata
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.