Evidence map›Paper›PMID 40473905›Full record

ArticleOncogene2025

NRF2-mediated persistent adaptation of oesophageal adenocarcinoma cells to HER2 inhibition.

Wei Zhang, Jiaqing Lang, Sorayut Chattrakarn, Chun Wai Wong, Shiyang Li, Karmern Kan, Hongcai Liu, Wenchao Gu, Jingwei Zhang, Jukka Westermarck and 3 more

Abstract read
In one paragraph

Article in Oncogene, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Wei Zhang *Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health (FBMH), University of Manchester, Manchester, UK.
Jiaqing Lang *Division of Molecular and Cellular Function, School of Biological Sciences, FBMH, University of Manchester, Manchester, UK.
Sorayut Chattrakarn *Lydia Becker Institute of Immunology and Inflammation, FBMH, University of Manchester, Manchester, UK.
Chun Wai WongDivision of Molecular and Cellular Function, School of Biological Sciences, FBMH, University of Manchester, Manchester, UK.
Shiyang LiDivision of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, FBMH, University of Manchester, Manchester, UK.
Karmern KanDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health (FBMH), University of Manchester, Manchester, UK.ORCID http://orcid.org/0009-0004-3700-3309
Hongcai LiuDepartment of Neurology, Sankt Rochus Kliniken Bad Schönborn, Bad Schönborn, Germany.
Wenchao GuDepartment of Artificial Intelligence Medicine, Chiba University, Chiba, Japan.ORCID http://orcid.org/0000-0002-1505-9887
Jingwei ZhangDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health (FBMH), University of Manchester, Manchester, UK.
Jukka WestermarckTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID http://orcid.org/0000-0001-7478-3018
Alan J WhitmarshDivision of Molecular and Cellular Function, School of Biological Sciences, FBMH, University of Manchester, Manchester, UK.
Andrew D SharrocksDivision of Molecular and Cellular Function, School of Biological Sciences, FBMH, University of Manchester, Manchester, UK.ORCID http://orcid.org/0000-0001-7395-9552
Cathy TournierDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health (FBMH), University of Manchester, Manchester, UK. cathy.tournier@manchester.ac.uk.ORCID http://orcid.org/0000-0002-4618-2570

Funding

Wellcome TrustWellcome Trust (Wellcome) 108867/B/15/ZWellcome Trust (Wellcome) 222806/Z/21/ZWorldwide Cancer Research 15-1283
6 · The paper itself

Abstract

The human epidermal growth factor receptor 2 (HER2, also known as ERBB2) is a commonly over-expressed oncoprotein in oesophageal adenocarcinoma (OAC). Nonetheless, HER2-blocking agents have failed to significantly improve the outcome for OAC patients, despite achieving striking clinical success in breast cancer. To address this conundrum, we investigated how resistance progressively emerges when HER2 is targeted. We discovered that OAC cell lines that are capable of surviving in the presence of the dual HER1/HER2 tyrosine kinase inhibitor lapatinib exhibit a significant increase in the protein level of nuclear factor erythroid 2-related factor 2 (NRF2). Indeed, NRF2 knockdown enhanced the cytotoxic effect of lapatinib, while increased NRF2 expression in OAC cells reduced their sensitivity to HER inhibition. Furthermore, prolonged overexpression of NRF2 made OAC cell lines increasingly dependent on NRF2 for growth. Further analyses indicated that the activation of NRF2-mediated transcription that was associated with lapatinib-induced persistent and resistant phenotypes coincided with a subsequent increase in glutathione metabolism. Importantly, lapatinib resistant OAC xenografts become exquisitely sensitive to pharmacological inhibition of the NRF2 pathway. Together, these findings highlight a promising therapeutic strategy for treating refractory OAC by targeting the NRF2 pathway in combination with receptor tyrosine kinase inhibition.

Indexed as

AdenocarcinomaErb-b2 Receptor Tyrosine KinasesEsophageal NeoplasmsNF-E2-Related Factor 2AnimalsAntineoplastic AgentsCell Line, TumorCell ProliferationDrug Resistance, NeoplasmFemaleHumansLapatinibMiceProtein Kinase InhibitorsXenograft Model Antitumor AssaysAntineoplastic AgentsERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesLapatinibNFE2L2 protein, humanNF-E2-Related Factor 2Protein Kinase Inhibitors

Identifiers

PMID40473905
PMCPMC12336050

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.