Evidence map›Paper›PMID 42463770›Full record

ArticleOncogene2026

Multiparatopic antibodies overcome tyrosine kinase inhibitor resistance by inducing lysosomal degradation of EGFR mutants.

Chunjie Lin, Jie Liu, Jiacheng Ni, Dingrui Chen, Yafei Liu, Wanyinhui Zhu, Yinuo Sheng, Yunling Wang, Yingbin Gao, Sitong Zhang and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Oncogene, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Chunjie Lin *Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.ORCID http://orcid.org/0000-0002-8188-157X
Jie Liu *Fujian Provincial Key Laboratory of Innovative Drug Target Research, School of Pharmaceutical Sciences, Xiamen University, Xiamen, 361102, China.
Jiacheng NiZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.
Dingrui ChenZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.ORCID http://orcid.org/0000-0002-7868-6917
Yafei LiuDepartment of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Wanyinhui ZhuZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.ORCID http://orcid.org/0009-0004-0739-197X
Yinuo ShengZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.
Yunling WangBiochee Biotech Co., Ltd., Xiamen, 361102, China.
Yingbin GaoZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.
Sitong ZhangZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.
Weirui MaZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China.
Yaoji LiangBiochee Biotech Co., Ltd., Xiamen, 361102, China. yaoji.liang@biochee.com.
Deli HuangZhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China. delih@zju.edu.cn.ORCID http://orcid.org/0009-0006-7040-6104

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acquired resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) remains a major challenge in the treatment of non-small cell lung cancer (NSCLC). To address this issue, we developed a novel therapeutic strategy based on multiparatopic antibodies that induce targeted degradation of EGFR, independent of driver mutations typically residing in the cytosolic domain. We engineered nanobodies (Nbs) recognizing four distinct epitopes within the EGFR extracellular domain into biparatopic and triparatopic antibody formats. These antibodies effectively promoted EGFR clustering, endocytosis, and lysosomal degradation, resulting in potent suppression of downstream signaling and cell proliferation in NSCLC cell lines carrying diverse EGFR mutations, including those resistant to osimertinib. The degradation process was epitope-dependent and mediated through a dynamin-dependent endocytic pathway. Triparatopic antibodies exhibited superior antitumor efficacy compared to both biparatopic antibodies and osimertinib in xenograft models of TKI-sensitive and TKI-resistant NSCLC cells. Moreover, these antibodies displayed additive effects when combined with osimertinib. We further demonstrated that this degradation mechanism extends beyond EGFR, as antibody-mediated crosslinking similarly triggered PD-L1 degradation. Collectively, this study indicates multiparatopic antibodies as a potent and mechanistically distinct strategy to overcome TKI resistance by directly degrading the target oncoprotein, with broad applicability to other pathogenic cell surface proteins.

Indexed as

Carcinoma, Non-Small-Cell LungDrug Resistance, NeoplasmLung NeoplasmsLysosomesProtein Kinase InhibitorsAcrylamidesAniline CompoundsAnimalsCell Line, TumorCell ProliferationErbB ReceptorsHumansIndolesMiceMutationProteolysisAcrylamidesAniline CompoundsEGFR protein, humanErbB ReceptorsIndolesosimertinibProtein Kinase InhibitorsPyrimidines

Identifiers

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.