Evidence map›Paper›PMID 31921107›Full record

ArticleFrontiers in immunology2019

A Transcriptomic Immunologic Signature Predicts Favorable Outcome in Neoadjuvant Chemotherapy Treated Triple Negative Breast Tumors.

Javier Pérez-Pena, Janos Tibor Fekete, Raquel Páez, Mariona Baliu-Piqué, José Ángel García-Saenz, Vanesa García-Barberán, Aránzazu Manzano, Pedro Pérez-Segura, Azucena Esparis-Ogando, Atanasio Pandiella and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
1.6field-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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. 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

12 authors at 6 institutions in 2 countries.

Javier Pérez-PenaExperimental Therapeutics Unit, Medical Oncology Department, Hospital Clínico San Carlos (HCSC), Instituto de Investigación Sanitaria (IdISSC) and CIBERONC, Madrid, Spain.
Janos Tibor FeketeDepartment of Bioinformatics, Semmelweis University, Budapest, Hungary.
Raquel PáezTranslational Research Unit, Translational Oncology Laboratory, Albacete University Hospital, Albacete, Spain.
Mariona Baliu-PiquéExperimental Therapeutics Unit, Medical Oncology Department, Hospital Clínico San Carlos (HCSC), Instituto de Investigación Sanitaria (IdISSC) and CIBERONC, Madrid, Spain.
José Ángel García-SaenzExperimental Therapeutics Unit, Medical Oncology Department, Hospital Clínico San Carlos (HCSC), Instituto de Investigación Sanitaria (IdISSC) and CIBERONC, Madrid, Spain.
Vanesa García-BarberánExperimental Therapeutics Unit, Medical Oncology Department, Hospital Clínico San Carlos (HCSC), Instituto de Investigación Sanitaria (IdISSC) and CIBERONC, Madrid, Spain.
Aránzazu ManzanoExperimental Therapeutics Unit, Medical Oncology Department, Hospital Clínico San Carlos (HCSC), Instituto de Investigación Sanitaria (IdISSC) and CIBERONC, Madrid, Spain.
Pedro Pérez-SeguraExperimental Therapeutics Unit, Medical Oncology Department, Hospital Clínico San Carlos (HCSC), Instituto de Investigación Sanitaria (IdISSC) and CIBERONC, Madrid, Spain.
Azucena Esparis-OgandoInstituto de Biología Molecular y Celular del Cáncer and CIBERONC, CSIC-Universidad de Salamanca, Salamanca, Spain.
Atanasio PandiellaInstituto de Biología Molecular y Celular del Cáncer and CIBERONC, CSIC-Universidad de Salamanca, Salamanca, Spain.
Balázs GyorffyDepartment of Bioinformatics, Semmelweis University, Budapest, Hungary.
Alberto OcanaExperimental Therapeutics Unit, Medical Oncology Department, Hospital Clínico San Carlos (HCSC), Instituto de Investigación Sanitaria (IdISSC) and CIBERONC, Madrid, Spain.
Centro de Investigación Biomédica en Red de Cáncer · ESInstituto de Investigación Sanitaria del Hospital Clínico San Carlos · ESHungarian Academy of Sciences · HUInstitute of Molecular Life Sciences · HUUniversidad de Salamanca · ESUniversity of Castilla-La Mancha · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Limited therapeutic options exist for the treatment of patients with triple negative breast cancer (TNBC). Neoadjuvant chemotherapy is currently the standard of care treatment in the early stages of the disease, although reliable biomarkers of response have been scarcely described. In our study we explored whether immunologic signatures associated with inflamed tumors or hot tumors could predict the outcome to neoadjuvant chemotherapy. Publicly available transcriptomic data of more than 2,000 patients were evaluated. ROC plots were generated to assess the response to therapy. Cox proportional hazards regression was computed. Kaplan-Meier plots were drawn to visualize the survival differences. Higher expression of IDO1, CXCL9, CXCL10, HLA-DRA, HLA-E, STAT1, and GZMB were associated with a higher proportion without relapse in the first 5 y after chemotherapy in TNBC. The expression of these genes was associated with a high presence of CD8 T cells in responder patients using the EPIC bioinformatic tool. The strongest effect was observed for STAT1 (

Indexed as

ImmunityTranscriptomeAntineoplastic Combined Chemotherapy ProtocolsArea Under CurveGene Expression ProfilingHumansNeoadjuvant TherapyPrognosisROC CurveTreatment OutcomeTriple Negative Breast Neoplasmschemotherapy treated patientsimmunotherapyoutcometranscriptomic signaturetriple negative breast cancer

Identifiers

PMID31921107
PMCPMC6930158
OpenAlexW2994697502

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.