Evidence map›Paper›PMID 35789315›Full record

ArticleBreast cancer research and treatment2022

Comparison of immunohistochemistry and RT-qPCR for assessing ER, PR, HER2, and Ki67 and evaluating subtypes in patients with breast cancer.

Lili Chen, Yanyang Chen, Zhongpeng Xie, Jiao Luo, Yuefeng Wang, Jianwen Zhou, Leilei Huang, Hongxia Li, Linhai Wang, Pei Liu and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Breast cancer research and treatment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

13 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Anti-Obesity Effects ofFood science & nutrition · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

13 authors at 1 institution in 1 country.

Lili Chen *Department of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Yanyang Chen *Department of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Zhongpeng Xie *Zhongshan School of Medicine, Sun Yat-sen University, No. 74, ZhongShan Second Road, Guangzhou, 510080, China.
Jiao LuoMolecular Diagnosis and Gene Testing Center, The First Affiliated Hospital, Sun Yat-sen University, No. 58, ZhongShan Second Road, Guangzhou, 510080, China.
Yuefeng WangDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Jianwen ZhouMolecular Diagnosis and Gene Testing Center, The First Affiliated Hospital, Sun Yat-sen University, No. 58, ZhongShan Second Road, Guangzhou, 510080, China.
Leilei HuangDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Hongxia LiDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Linhai WangBeijing OriginPoly BioTec Co., Ltd, Beijing, China.
Pei LiuBeijing OriginPoly BioTec Co., Ltd, Beijing, China.
Man ShuDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Wenhui ZhangDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Zunfu KeMolecular Diagnosis and Gene Testing Center, The First Affiliated Hospital, Sun Yat-sen University, No. 58, ZhongShan Second Road, Guangzhou, 510080, China. kezunfu@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-6251-7246
Sun Yat-sen University · CN

Funding

Key Technologies Research and Development Program 2017YFC1308800National Natural Science Foundation of China 30900650National Natural Science Foundation of China 31430030National Natural Science Foundation of China 81172232National Natural Science Foundation of China 81372501National Natural Science Foundation of China 81502327National Natural Science Foundation of China 81572260National Natural Science Foundation of China 81701834National Natural Science Foundation of China 81773299Natural Science Foundation of Guangdong Province 16ykjc08Natural Science Foundation of Guangdong Province 20090171120070Natural Science Foundation of Guangdong Province 2011B031800025Natural Science Foundation of Guangdong Province 2013B021800126Natural Science Foundation of Guangdong Province 2013B021800259Natural Science Foundation of Guangdong Province 2014A030313052Natural Science Foundation of Guangdong Province 2014J4100132Natural Science Foundation of Guangdong Province 2015A020214010Natural Science Foundation of Guangdong Province 2015ykzd07Natural Science Foundation of Guangdong Province 2016A020215055Natural Science Foundation of Guangdong Province 201704020094Natural Science Foundation of Guangdong Province 2017B070705002Natural Science Foundation of Guangdong Province 9451008901002146Natural Science Foundation of Guangdong Province S2012010008270Natural Science Foundation of Guangdong Province S2012010008378Natural Science Foundation of Guangdong Province S2013010015327
6 · The paper itself

Abstract

purposeCurrently, the most commonly applied method for the determination of breast cancer subtypes is to test estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 by immunohistochemistry (IHC). However, the IHC method has substantial intraobserver and interobserver variability. ESR1, PGR, ERBB2, and MKi67 mRNA tests by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay may improve the diagnostic objectivity and efficiency. Here, we compared the concordance between RT-qPCR and IHC for assessment of the same biomarkers and evaluated the subtypes.

methodsA total of 265 eligible cases were divided into a training cohort and a validation cohort, and the expressions of ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 were tested by IHC and RT-qPCR. Then, the appropriate cutoff of RT-qPCR was calculated in the training cohort. The concordance between RT-qPCR and IHC was calculated for individual marker. In addition, we investigated the subtypes based on the RT-qPCR results.

resultsThe Spearman correlation coefficients between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR were 0.768, 0.699, 0.762, and 0.387, respectively. The cutoff values for the RT-qPCR assay of ESR1 (1%), PGR (1%), ERBB2, and MKi67 (14%) were 35.539, 32.139, 36.398, and 29.176, respectively. The overall percent agreement (OPA) between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR was 92.48%, 73.68%, 92.80%, and 74.44%, respectively. A total of 224 (84.53%) specimens were concordant for the breast cancer subtypes (IHC-based type) by RT-qPCR.

conclusionEvaluation of breast cancer biomarker status by RT-qPCR was highly concordant with IHC. RT-qPCR can be used as a supplementary method to detect molecular markers of breast cancer.

Indexed as

Breast NeoplasmsReceptors, ProgesteroneBiomarkers, TumorErb-b2 Receptor Tyrosine KinasesEstrogen Receptor alphaFemaleHumansImmunohistochemistryKi-67 AntigenReceptors, EstrogenBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesEstrogen Receptor alphaKi-67 AntigenReceptors, EstrogenReceptors, ProgesteroneBreast cancerERHER2Ki67PRRT-qPCRSubtypes

Identifiers

PMID35789315
OpenAlexW4283809007

What OpenQuestion holds

Textmetadata
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.