Evidence map›Paper›PMID 32196521›Full record

ArticlePloS one2020

A 3-gene biomarker signature to predict response to taxane-based neoadjuvant chemotherapy in breast cancer.

Jim Kallarackal, Florian Burger, Stefano Bianco, Alessandro Romualdi, Martina Schad

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. The biology of SCUBE.Journal of biomedical science · 2023
    Review
  3. EMT Molecular Signatures of Pancreatic Neuroendocrine Neoplasms.International journal of molecular sciences · 2022
    Article
  4. Review
  5. Translocon-associated Protein Subunit SSR3 Determines and Predicts Susceptibility to Paclitaxel in Breast Cancer and Glioblastoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022
    Article
  6. 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

5 authors.

Jim KallarackalOakLabs GmbH, Hennigsdorf, Germany.ORCID 0000-0002-4949-0800
Florian BurgerOakLabs GmbH, Hennigsdorf, Germany.
Stefano BiancoOakLabs GmbH, Hennigsdorf, Germany.
Alessandro RomualdiOakLabs GmbH, Hennigsdorf, Germany.
Martina SchadOakLabs GmbH, Hennigsdorf, Germany.ORCID 0000-0002-1747-0493

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the most common cancer in women worldwide, affecting one in eight women in their lifetime. Taxane-based chemotherapy is routinely used in the treatment of breast cancer. The purpose of this study was to develop and validate a predictive biomarker to improve the benefit/risk ratio for that cytotoxic chemotherapy. We explicitly strived for a biomarker that enables secure translation into clinical practice. We used genome-wide gene expression data of the Hatzis et al. discovery cohort of 310 patients for biomarker development and three independent cohorts with a total of 567 breast cancer patients for validation. We were able to develop a biomarker signature that consists of just the three gene products ELF5, SCUBE2 and NFIB, measured on RNA level. Compared to Hatzis et al., we achieved a significant improvement in predicting responders and non-responders in the Hatzis et al. validation cohort with an area under the receiver operating characteristics curve of 0.73 [95% CI, 69%-77%]. Moreover, we could confirm the performance of our biomarker on two further independent validation cohorts. The overall performance on all three validation cohorts expressed as area under the receiver operating characteristics curve was 0.75 [95% CI, 70%-80%]. At the clinically relevant classifier's operation point to optimize the exclusion of non-responders, the biomarker correctly predicts three out of four patients not responding to neoadjuvant taxane-based chemotherapy, independent of the breast cancer subtype. At the same time, the response rate in the group of predicted responders increased to 42% compared to 23% response rate in all patients of the validation cohorts.

Indexed as

TranscriptomeAdaptor Proteins, Signal TransducingAntineoplastic AgentsBiomarkers, TumorBreast NeoplasmsCalcium-Binding ProteinsDNA-Binding ProteinsFemaleHumansNeoadjuvant TherapyNFI Transcription FactorsRNA, MessengerSurvival AnalysisTaxoidsTranscription FactorsAdaptor Proteins, Signal TransducingAntineoplastic AgentsBiomarkers, TumorCalcium-Binding ProteinsDNA-Binding ProteinsELF5 protein, humanNFIB protein, humanNFI Transcription FactorsRNA, MessengerSCUBE2 protein, humanTaxoidsTranscription Factors

Identifiers

PMID32196521
PMCPMC7083332

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.