Evidence map›Paper›PMID 23374644›Full record

ArticleBMC cancer2013

The potential prognostic value of connexin 26 and 46 expression in neoadjuvant-treated breast cancer.

Ivett Teleki, Tibor Krenacs, Marcell A Szasz, Janina Kulka, Barna Wichmann, Cornelia Leo, Barbel Papassotiropoulos, Cosima Riemenschnitter, Holger Moch, Zsuzsanna Varga

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. Pooled it
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  5. Article
  6. Review
  7. Connexins and Glucose Metabolism in Cancer.International journal of molecular sciences · 2022
    Review
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  9. Article
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  12. Review
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  18. The Complex Subtype-Dependent Role of Connexin 43 (GJA1) in Breast Cancer.International journal of molecular sciences · 2018
    Review
  19. Article
  20. 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

10 authors at 3 institutions in 2 countries.

Ivett Teleki1st Department of Pathology & Experimental Cancer Research, Semmelweis University, Budapest, Hungary.
Tibor Krenacs
Marcell A Szasz
Janina Kulka
Barna Wichmann
Cornelia Leo
Barbel Papassotiropoulos
Cosima Riemenschnitter
Holger Moch
Zsuzsanna Varga
Semmelweis University · HUUniversity Hospital of Zurich · CHBreast Center · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral classification systems are available to assess pathological response to neoadjuvant chemotherapy in breast cancer, but reliable biomarkers to predict the efficiency of primary systemic therapy (PST) are still missing. Deregulation of gap junction channel forming connexins (Cx) has been implicated in carcinogenesis and tumour progression through loss of cell cycle control. In this study we correlated Cx expression and cell proliferation with disease survival and pathological response to neoadjuvant chemotherapy in breast cancers using existing classification systems.

methodsThe expression of Cx26, Cx32, Cx43, Cx46 and Ki67 was evaluated in 96 breast cancer patients prior to and after neoadjuvant chemotherapy using duplicate cores in tissue microarrays (TMA). Cx plaques of <1μm were detected with multilayer, multichannel fluorescence digital microscopy. Current classifications to assess residual tumour burden after primary systemic therapy included the EWGBSP, CPS-EG, Miller-Payne, Sataloff and NSABP systems.

resultsIn our cohort dominated by hormone receptor (ER/PR) positive and HER2 negative cases, only the CPS-EG classification showed prognostic relevance: cases with scores 1-2 had significantly better overall survival (p=0.015) than cases with scores 3-5. Pre-chemotherapy Cx43 expression correlated positively with hormone receptor status both before and after chemotherapy and had a negative correlation with HER2 expression pre-chemotherapy. There was a positive correlation between Cx32 and HER2 expression pre-chemotherapy and between Cx32 and Ki67 expression post-chemotherapy. A negative correlation was found between post-chemotherapy Cx46 and Ki67 expression. Decreased post-chemotherapy Cx26 expression (<5%) statistically correlated with better overall survival (p=0.011). Moderate or higher Cx46 expression (>20%) pre- and post-chemotherapy correlated with significantly better survival in the intermediate prognostic subgroups of EWGBSP TR2b (p(pre-chemo)=0.006; Sataloff TB (p(pre-chemo)=0.005; p(post-chemo)=0.029) and in Miller-Payne G3 (p(pre-chemo)=0.002; p(post-chemo)=0.012) classifications. Pre-chemotherapy, Cx46 expression was the only marker that correlated with overall survival within these subgroups.

conclusionOur results suggest that Cx46 and Cx26 expression in breast cancer may improve the assessment of pathological response and refine intermediate prognostic subgroups of residual tumour classifications used after neoadjuvant chemotherapy.

Indexed as

Neoadjuvant TherapyAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBreast NeoplasmsCarcinomaChemotherapy, AdjuvantChi-Square DistributionConnexin 26Connexin 43ConnexinsErb-b2 Receptor Tyrosine KinasesFemaleGap Junction beta-1 ProteinHumansBiomarkers, TumorConnexin 26Connexin 43ConnexinsERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesGap Junction beta-1 ProteinGJA1 protein, humanGJA3 protein, humanGJB2 protein, humanKi-67 AntigenReceptors, EstrogenReceptors, Progesterone

Identifiers

PMID23374644
PMCPMC3583680
OpenAlexW2020015129

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.