Evidence map›Paper›PMID 32269999›Full record

ArticleFrontiers in molecular biosciences2020

A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy.

Yanhua Chen, Hao Cai, Wannan Chen, Qingzhou Guan, Jun He, Zheng Guo, Jing Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Yanhua ChenFujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Hao CaiMedical Big Data and Bioinformatics Research Center, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Wannan ChenKey Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Qingzhou GuanHenan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou, China.
Jun HeFujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Zheng GuoFujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Jing LiFujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Fujian Medical University · CNFirst Affiliated Hospital of Gannan Medical University · CNFirst Affiliated Hospital of Henan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For estrogen receptor (ER)-negative breast cancer patients, paclitaxel (P), doxorubicin (A) and cyclophosphamide (C) neoadjuvant chemotherapy (NAC) is the standard therapeutic regimen. Pathologic complete response (pCR) and residual disease (RD) are common surrogate measures of chemosensitivity. After NAC, most patients still have RD; of these, some partially respond to NAC, whereas others show extreme resistance and cannot benefit from NAC but only suffer complications resulting from drug toxicity. Here we developed a qualitative transcriptional signature, based on the within-sample relative expression ordering (REO) of gene pairs, to identify extremely resistant samples to PAC NAC. Using gene expression data for ER-negative breast cancer patients including 113 pCR samples and 137 RD samples from four datasets, we selected 61 gene pairs with reversal REO patterns between the two groups as the resistance signature, denoted as NR61. Samples with more than 37 signature gene pairs that had the same REO patterns within the extremely resistant group were defined as having extreme resistance; otherwise, they were considered responders. In the GSE25055 and GSE25065 dataset, the NR61 signature could correctly identify 44 (97.8%) of the 45 pCR samples and 22 (95.7%) of the 23 pCR samples as responder samples, respectively; it also identified 13 (16.9%) of 77 RD samples and 8 (21.1%) of 38 RD samples as extremely resistant samples, respectively. Survival analysis showed that the distant relapse-free survival (DRFS) time of the 14 extremely resistant cases was significantly shorter than that of the 108 responders (

Indexed as

breast cancerextreme resistanceneoadjuvant chemotherapypathological complete responserelative expression ordering

Identifiers

PMID32269999
PMCPMC7109260
OpenAlexW3013880653

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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.