Evidence map›Paper›PMID 34189853›Full record

ArticleCancer medicine2021

Immunophenotype-associated gene signature in ductal breast tumors varies by receptor subtype, but the expression of individual signature genes remains consistent.

Michael Behring, Yuanfan Ye, Amr Elkholy, Prachi Bajpai, Sumit Agarwal, Hyung-Gyoon Kim, Akinyemi I Ojesina, Howard W Wiener, Upender Manne, Sadeep Shrestha and 1 more

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

Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 14% 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, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The biology of SCUBE.Journal of biomedical science · 2023
    Review
  6. Article
  7. Article
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

11 authors at 2 institutions in 1 country.

Michael BehringDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.ORCID 0000-0002-5162-322X
Yuanfan YeDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Amr ElkholyDepartment of Pathology and Surgery, University of Alabama at Birmingham, Birmingham, AL, USA.
Prachi BajpaiDepartment of Pathology and Surgery, University of Alabama at Birmingham, Birmingham, AL, USA.
Sumit AgarwalDepartment of Pathology and Surgery, University of Alabama at Birmingham, Birmingham, AL, USA.
Hyung-Gyoon KimDepartment of Pathology and Surgery, University of Alabama at Birmingham, Birmingham, AL, USA.
Akinyemi I OjesinaDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.ORCID 0000-0003-0755-3639
Howard W WienerDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Upender ManneDepartment of Pathology and Surgery, University of Alabama at Birmingham, Birmingham, AL, USA.ORCID 0000-0002-1545-3032
Sadeep ShresthaDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Ana I VazquezDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA.
University of Alabama at Birmingham · USQuantitative BioSciences · US

Funding

UAB Cancer Prevention and Control Training Program (T32)T32CA047888 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Ritu Aneja, Ellen Mary Lavoie Smith · 2018 to 2026
$3.2M
NCI NIH HHS T32 CA047888
6 · The paper itself

Abstract

backgroundIn silico deconvolution of invasive immune cell infiltration in bulk breast tumors helps characterize immunophenotype, expands treatment options, and influences survival endpoints. In this study, we identify the differential expression (DE) of the LM22 signature to classify immune-rich and -poor breast tumors and evaluate immune infiltration by receptor subtype and lymph node metastasis.

methodsUsing publicly available data, we applied the CIBERSORT algorithm to estimate immune cells infiltrating the tumor into immune-rich and immune-poor groups. We then tested the association of receptor subtype and nodal status with immune-rich/poor phenotype. We used DE to test individual signature genes and over-representation analysis for related pathways.

resultsCCL19 and CXCL9 expression differed between rich/poor signature groups regardless of subtype. Overexpression of CHI3L2 and FES was observed in triple negative breast cancers (TNBCs) relative to other subtypes in immune-rich tumors. Non-signature genes, LYZ, C1QB, CORO1A, EVI2B, GBP1, PSMB9, and CD52 were consistently overexpressed in immune-rich tumors, and SCUBE2 and GRIA2 were associated with immune-poor tumors. Immune-rich tumors had significant upregulation of genes/pathways while none were identified in immune-poor tumors.

conclusionsOverall, the proportion of immune-rich/poor tumors differed by subtype; however, a subset of 10 LM22 genes that marked immune-rich status remained the same across subtype. Non-LM22 genes differentially expressed between the phenotypes suggest that the biologic processes responsible for immune-poor phenotype are not yet well characterized.

Indexed as

Biomarkers, TumorBreast NeoplasmsCarcinoma, Ductal, BreastDatasets as TopicFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunophenotypingLymphocytes, Tumor-InfiltratingUp-RegulationBiomarkers, Tumorbreast cancermicroenvironmenttranscriptomicstumor-infiltrating immune cells

Identifiers

PMID34189853
PMCPMC8366080
OpenAlexW3176288306

What OpenQuestion holds

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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.