Evidence map›Paper›PMID 42592099›Full record

ReviewAntibody therapeutics2026

Epidermal growth factor receptor-targeted near-infrared photoimmunotherapy for epidermal growth factor receptor-expressing advanced solid tumors: a scoping review of barriers and enablers to clinical translation.

Emmanuel O Oisakede, Olawunmi O Oyedeji, Odunola F Atitebi, Ijomah Ugbomah, David B Olawade

Abstract readReview
In one paragraph

Review in Antibody therapeutics, 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

5 authors.

Emmanuel O OisakedeDepartment of Clinical Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, LS9 7TF, United Kingdom.ORCID https://orcid.org/0009-0000-5791-301X
Olawunmi O OyedejiDepartment of Research and Innovation, The Christie NHS Foundation Trust, Manchester, M20 4BX, United Kingdom.
Odunola F AtitebiCan-Survive UK, Manchester, M15 5DD, United Kingdom.
Ijomah UgbomahDepartment of Transformation and Quality Improvement, University Hospitals of Northamptonshire, Kettering, NN16 8UZ, United Kingdom.
David B OlawadeDepartment of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME75NY, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Epidermal growth factor receptor (EGFR)-targeted near-infrared photoimmunotherapy (NIR-PIT) is an emerging drug-device modality that enables spatially selective tumor cell killing through antibody-photoabsorber conjugation and localized light activation. Although clinical translation has advanced in selected settings, particularly head and neck squamous cell carcinoma (HNSCC), barriers and enablers influencing broader implementation across solid tumors have not been systematically mapped. This review focuses specifically on the IR700 (IRDye700DX)-based conjugate cetuximab sarotalocan (RM-1929/ASP-1929), which is the only NIR-PIT construct to have advanced into clinical use, while acknowledging the broader and rapidly expanding photoimmunotherapy landscape. Objective: To synthesize and characterize the biological, technical, clinical, and system-level factors that facilitate or hinder the clinical translation of EGFR-targeted NIR-PIT across EGFR-expressing advanced solid tumors. Methods: A scoping review was conducted in accordance with PRISMA-ScR guidelines. Comprehensive searches of PubMed, Embase, Scopus, ClinicalTrials.gov, and the Cochrane Library identified 28 eligible studies, including preclinical investigations, early-phase clinical trials, observational studies, and case reports or series. Data were charted and synthesized thematically, with study quality appraised to inform interpretation. Results: Preclinical studies consistently demonstrated light-dependent, EGFR-selective cytotoxicity and identified non-linear dose-response relationships that support standardized light dosing strategies. Clinical translation has been most successful in recurrent or unresectable HNSCC, facilitated by tumor accessibility, multidisciplinary workflows, and regulatory approval in Japan. Technical enablers included endoscopic and navigation-assisted light delivery, real-time fluorescence imaging, and the feasibility of repeat treatment without cumulative toxicity. Key barriers included limited light penetration, anatomical constraints, reliance on specialized equipment, and restricted applicability to deep-seated or diffuse disease. Although most adverse events were localized and manageable, rare but serious complications reported across multiple case studies represent an important translational challenge. Evidence outside HNSCC remains sparse and is largely confined to preclinical models. Conclusions: EGFR-targeted NIR-PIT has achieved meaningful clinical translation within a narrow but well-defined therapeutic niche, supported by strong mechanistic rationale and growing real-world experience. Broader adoption is constrained by biological, technical, regulatory and system-level barriers, as well as gaps in comparative effectiveness, long-term outcomes, and health-economic evidence. Addressing these challenges through targeted clinical trials, improved patient selection, and implementation-focused research will be essential to advance NIR-PIT toward wider clinical integration.

Indexed as

Cetuximab sarotalocanclinical translationdrug-device combinationEGFR-targeted therapyhead and neck squamous cell carcinomaIR700near-infrared photoimmunotherapyphotodynamic therapy

Identifiers

PMID42592099
PMCPMC13463628

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.