Evidence map›Paper›PMID 42588669›Full record

ReviewCancers2026

Targeting EGFR Endocytosis and Signaling for Cancer Drug Delivery and Cancer Treatment.

Xinmei Chen, Zhixiang Wang

Abstract readReview
In one paragraph

Review in Cancers, 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

2 authors.

Xinmei ChenDepartment of Medical Genetics, Faculty of Medicine and Dentistry, College of Health Sciences, University of Alberta, Edmonton, AB T6G 2H7, Canada.
Zhixiang WangDepartment of Medical Genetics, Faculty of Medicine and Dentistry, College of Health Sciences, University of Alberta, Edmonton, AB T6G 2H7, Canada.ORCID 0000-0002-6364-6891

Funding

CIHR RES0068855
6 · The paper itself

Abstract

The epidermal growth factor receptor (EGFR) was the first receptor tyrosine kinase identified soon after v-Src was recognized as a tyrosine kinase. EGFR signaling begins when EGF binds to EGFR at the cell surface, inducing receptor dimerization, activation, and autophosphorylation. The resulting phosphotyrosine sites recruit downstream effectors that activate signaling cascades such as the RAS-RAF-MEK-ERK and PI3K-Akt pathways, thereby regulating cell growth, proliferation, and survival. EGF binding also promotes EGFR endocytosis, which can direct the receptor to lysosomal degradation. Aberrant EGFR activity is associated with many cancers, and the receptor has been therapeutically targeted using small-molecule tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs). Furthermore, EGFR endocytosis has been exploited for the targeted delivery of anticancer agents into EGFR-expressing cancer cells through antibody-drug conjugates (ADCs) and antibody-nanoparticle conjugates (ANCs). Although ADCs and ANCs both utilize mAbs as homing mechanisms to recognize cancer-associated antigens, they further harness EGFR endocytosis to deliver therapeutic payloads directly into target cells. In this review, we briefly discuss EGFR structure, activation, signaling, and endocytosis, as well as the mechanisms underlying EGFR function in cancer development. We then focus on current advances and future perspectives in using EGFR endocytosis pathways to improve targeted cancer drug delivery and therapy, particularly in the context of ANCs.

Indexed as

antibody–drug conjugated (ADCs)antibody–nanoparticle conjugates (ANCs)cancerscell signalingdrug deliveryendocytosisepidermal growth factor (EGF) receptor (EGFR)targeted therapeutics

Identifiers

PMID42588669
PMCPMC13464385

What OpenQuestion holds

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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.