Radioligand Therapy Targets in Lung Cancer
We screened every cell-surface protein with tumor immunohistochemistry data in lung cancer (including non-small cell (NSCLC) and small cell lung cancer (SCLC)). 4,217 show detectable protein staining. Established and emerging radioligand targets expressed in lung cancer include EPCAM, HER3 (ERBB3), CEA (CEACAM5) and EGFR. Below, we rank every candidate by tumor expression, internalization and clinical maturity.
Established and emerging radioligand targets in lung cancer
Targets already pursued with radioligands or other targeted modalities that show protein expression in lung cancer:
| Target | IHC in lung cancer | % positive | Internalizes |
|---|---|---|---|
| EPCAM | High (0.83) | 100% | — |
| HER3 (ERBB3) | High (0.70) | 100% | yes |
| CEA (CEACAM5) | High (0.67) | 91% | — |
| EGFR | High (0.63) | 80% | yes |
| B7-H3 (CD276) | High (0.61) | 100% | — |
| STEAP2 | High (0.61) | 92% | — |
| ITGB6 | Medium (0.47) | 83% | — |
| ITGAV | Medium (0.47) | 75% | — |
| c-MET (MET) | Medium (0.42) | 91% | yes |
| TMEFF2 | Medium (0.30) | 64% | — |
| Nectin-4 (NECTIN4) | Medium (0.28) | 58% | no |
| Claudin 18.2 (CLDN18) | Medium (0.24) | 27% | uncertain |
| TROP2 (TACSTD2) | Medium (0.23) | 50% | uncertain |
| Mesothelin (MSLN) | Medium (0.22) | 33% | yes |
| STEAP1 | Medium (0.21) | 27% | — |
| SSTR2 | Low (0.17) | 42% | yes |
| FAP | Low (0.12) | 27% | yes |
| HER2 (ERBB2) | Low (0.09) | 18% | yes |
| KIT | Low (0.06) | 8% | no |
| CD20 (MS4A1) | Low (0.03) | 8% | uncertain |
| DLK1 | Low (0.03) | 8% | — |
Top cell-surface targets for lung cancer radioligand therapy
A data-driven screen of every protein annotated as cell-surface. It deliberately surfaces novel, unvalidated candidates, so confirm localization and expression before prioritizing any of them.
| # | Target | IHC in lung cancer | % positive | Internalizes | Clinical stage |
|---|---|---|---|---|---|
| 1 | GPR139 G protein-coupled receptor 139 | High (1.00) | 100% | yes | Discovery |
| 2 | EGFR epidermal growth factor receptor | High (0.63) | 80% | yes | Clinical |
| 3 | AMFR autocrine motility factor receptor | High (0.94) | 100% | yes | Discovery |
| 4 | HER3 (ERBB3) erb-b2 receptor tyrosine kinase 3 | High (0.70) | 100% | yes | Clinical |
| 5 | IGF1R insulin like growth factor 1 receptor | High (0.67) | 100% | yes | Clinical |
| 6 | FZD6 frizzled class receptor 6 | High (0.85) | 100% | yes | Discovery |
| 7 | S1PR1 sphingosine-1-phosphate receptor 1 | High (0.52) | 82% | yes | Clinical |
| 8 | FZD3 frizzled class receptor 3 | High (0.80) | 100% | yes | Discovery |
| 9 | NOTCH2 notch receptor 2 | High (0.61) | 100% | yes | Clinical |
| 10 | AGTRAP angiotensin II receptor associated protein | High (0.76) | 100% | yes | Discovery |
| 11 | CCRL2 C-C motif chemokine receptor like 2 | High (0.64) | 91% | yes | Discovery |
| 12 | LSR lipolysis stimulated lipoprotein receptor | High (0.77) | 100% | yes | Discovery |
| 13 | CYSLTR2 cysteinyl leukotriene receptor 2 | High (0.61) | 91% | yes | Discovery |
| 14 | HRH4 histamine receptor H4 | High (0.61) | 91% | yes | Clinical |
| 15 | ADGRL1 adhesion G protein-coupled receptor L1 | High (0.73) | 100% | yes | Discovery |
| 16 | NR3C2 nuclear receptor subfamily 3 group C member 2 | High (0.69) | 100% | uncertain | Clinical |
| 17 | MST1R macrophage stimulating 1 receptor | High (0.56) | 92% | yes | Clinical |
| 18 | ITPR3 inositol 1,4,5-trisphosphate receptor type 3 | High (0.72) | 100% | yes | Discovery |
| 19 | SEMA6A semaphorin 6A | High (0.97) | 100% | — | Discovery |
| 20 | NOTCH1 notch receptor 1 | High (0.55) | 91% | yes | Clinical |
| 21 | c-MET (MET) MET proto-oncogene, receptor tyrosine kinase | Medium (0.42) | 91% | yes | Clinical |
| 22 | CX3CL1 C-X3-C motif chemokine ligand 1 | High (1.00) | 100% | — | Clinical |
| 23 | APH1A aph-1A gamma-secretase subunit | High (0.97) | 100% | — | Clinical |
| 24 | BCL2L2-PABPN1 BCL2L2-PABPN1 readthrough | High (0.97) | 100% | — | Clinical |
| 25 | KCNG1 potassium voltage-gated channel modifier subfamily G member 1 | High (0.77) | 100% | — | Clinical |
Internalizing receptors in lung cancer
Targets expressed in lung cancer that the literature reports internalize after ligand binding. Internalization traps the radionuclide inside the tumor cell, which matters most for β-emitters like 177Lu and for α-emitters like 225Ac:
GPR139 · EGFR · AMFR · HER3 (ERBB3) · IGF1R · FZD6 · S1PR1 · FZD3 · NOTCH2 · AGTRAP · CCRL2 · LSR
Lung Cancer targets already in clinical development
Targets with a clinical-stage drug program (any modality) that are also expressed in lung cancer. Clinical precedent lowers development risk but usually means more competition:
EGFR · HER3 (ERBB3) · IGF1R · S1PR1 · NOTCH2 · HRH4 · NR3C2 · MST1R · NOTCH1 · c-MET (MET) · CX3CL1 · APH1A
How these lung cancer targets are ranked
Candidates are limited to proteins annotated as cell-surface (UniProt via Open Targets), because a radioligand has to reach its target from circulation. They are ranked by Nuclens' radiopharmaceutical pre-screen: immunohistochemistry staining and patient-sample positivity in lung cancer, literature evidence of internalization and shedding, clinical maturity, and cancer association. It is a first-pass triage, not a substitute for wet-lab validation or dosimetry. For the full framework, see what makes a good radioligand therapy target and emerging radioligand targets beyond PSMA.
Rank lung cancer targets against your own criteria: isotope, organ limits, novelty.
Run a free lung cancer analysisRadioligand therapy targets in other cancers
- Prostate Cancer
- Neuroendocrine Tumors
- Pancreatic Cancer
- Breast Cancer
- Ovarian Cancer
- Colorectal Cancer
- Kidney Cancer
- Bladder Cancer
- Gastric Cancer
- Liver Cancer
- Glioma
- Melanoma
- Head and Neck Cancer
- Thyroid Cancer
- Lymphoma
- Cervical Cancer
- Endometrial Cancer
- Skin Cancer
- Testicular Cancer
Data sources
Subcellular localization: UniProt via Open Targets (CC BY 4.0 / CC0). Tumor immunohistochemistry: Human Protein Atlas (CC BY-SA 4.0). Clinical trials: ClinicalTrials.gov (public domain). Gene essentiality: DepMap (CC BY 4.0). Internalization and shedding: AI-extracted from PubMed abstracts, so verify against the cited papers before relying on them. Nuclens is a first-pass triage layer, not a substitute for wet-lab validation or clinical dosimetry. Derived expression data on this page is shared under CC BY-SA 4.0.