Drug Database
EP

epidermal growth factor receptor (EGFR pharmDx / EGFR pharmDx Kit)

✓ Approved

Dako · EGFR · Companion diagnostic

What is epidermal growth factor receptor?

epidermal growth factor receptor is a companion diagnostic developed by Dako. It is approved for therapeutic indications via others.

Drug Profile

Brand NamesEGFR pharmDx, EGFR pharmDx Kit
CompanyDako
Drug ClassCompanion diagnostic
Molecular TargetEGFR
RouteOthers
StatusApproved

Mechanism of Action

Molecular Targets

epidermal growth factor receptor acts on 1 molecular target:

EGFRepidermal growth factor receptor (ERBB1, NNCIS)
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Therapeutic Indications

epidermal growth factor receptor is developed for 1 unique indication across 1 therapeutic area.

Therapeutic AreaConditionPhase
Neoplasms benign, malignant and unspecified (incl cysts and polyps)Uterine cancer✓ Approved

Related Research Articles

PubMedFrontiers in cellular and infection microbiology2026-09-04

Niemann-Pick type C1 protein regulates epidermal growth factor receptor stability in hepatic cells and facilitates the early steps of Hepatitis B virus infection.

Stefan-Buzatoiu Stefania Ariadna SA, Alexandru Flintoaca Petruta-Ramona PR, Dobrica Mihaela-Olivia MO, Petrescu Stefana-Maria SM et al.

Chronic Hepatitis B virus (HBV) infection affects more than 250 million individuals worldwide, causing up to 1 million deaths yearly. Despite the significant disease burden, no curative therapy against HBV is currently available. Accumulating evidence indicate a strong and complex relationship between HBV and the host-cell lipid metabolism. HBV hijacks host lipoprotein transport pathways to gain access to hepatocytes and uses cellular cholesterol and sphingolipids for morphogenesis, while viral replication induces diverse and profound alterations of the hepatic lipid metabolism driving disease progression and tumorigenesis. As a key regulator of the cellular cholesterol homeostasis, the Niemann-Pick C1 (NPC1) protein has increasingly been associated with a wide range of pathologies, including viral infections. In this study, we investigated HBV entry, replication, viral particle envelopment and secretion in cells depleted of NPC1 expression or treated with various FDA-approved NPC1 inhibitors. Our work revealed that both genetic depletion and pharmacological inhibition of NPC1 impaired the early steps of HBV infection while significantly reducing the level and intracellular distribution of the HBV co-receptor, the Epidermal Growth Factor Receptor (EGFR). Mechanistically, NPC1 inhibition promoted EGFR depletion from the plasma membrane by enhancing the endocytic trafficking and degradation of the receptor within the endosomal-lysosomal compartment of hepatic cells. Considering the crucial roles of EGFR in tumorigenesis across multiple cancer types, our study promotes the newly identified NPC1-EGFR regulatory axis as a promising dual target for the development of antiviral and anticancer therapies.

PubMedFrontiers in bioinformatics2026-09-04

Computational blueprint and stereochemical validation of a small peptide derived from Lacticaseibacillus casei VITCM05 targeting estrogen receptor alpha and human epidermal growth factor receptor 2.

Shree Kumari G R GR, Vaithilingam Mohanasrinivasan M

Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide, necessitating the development of safer and more targeted therapeutic strategies. This study computationally extends our previous experimental investigation of a peptide derived from Lacticaseibacillus casei by evaluating its interactions with two clinically relevant breast cancer targets, estrogen receptor alpha (ERα; PDB ID: 3ERT) and human epidermal growth factor receptor 2 (HER2; PDB ID: 1N8Z). The peptide structure was predicted using PEP-FOLD and its stereochemical quality was assessed using a Ramachandran plot. Molecular docking was performed against ERα and HER2, followed by molecular dynamics simulations to evaluate structural stability. Binding free energy, binding affinity, dissociation constant, principal component analysis (PCA), free energy landscape (FEL), molecular mechanics (MM)/Poisson-Boltzmann surface area (PBSA) calculations, and in silico ADMET and toxicity predictions were performed to comprehensively characterise peptide-protein interactions. The predicted peptide model exhibited 84.8% of residues located in the most favoured regions, while 15.2% were located in additionally allowed regions of the Ramachandran plot, indicating satisfactory stereochemical quality. Molecular docking demonstrated favourable interactions with both ERα and HER2, with HER2 showing a marginally more favourable docking score. Molecular dynamics simulations indicated stable peptide-protein complexes throughout the simulation period, as supported by root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen-bond analyses. MM/PBSA calculations predicted stronger binding for the HER2 (1N8Z) complex (ΔG = -28.83 kJ/mol) than for the ERα (3ERT) complex (ΔG = -11.65 kJ/mol), highlighting the complementary nature of docking and dynamic free-energy estimation, which produced different receptor rankings. PCA and FEL analyses further demonstrated stable conformational sampling for both complexes. ADMET predictions suggested favourable peptide-like physicochemical properties while identifying pharmacokinetic and toxicity parameters that require further experimental validation. This computational study suggests that the L. casei-derived peptide exhibits favourable predicted interactions with ERα and HER2 and forms structurally stable peptide-protein complexes under simulated physiological conditions. These findings provide a computational framework for prioritising this probiotic-derived peptide for subsequent experimental validation and further investigation as a potential peptide-based therapeutic candidate for breast cancer.

PubMedAntioxidants & redox signaling2026-09-04

WITHDRAWAL-Administrative Duplicate Publication: Corrigendum to: Suppression of Cardiac Autophagy by Hyperinsulinemia in Insulin Receptor-Deficient Hearts Is Mediated by Insulin-Like Growth Factor Receptor Signaling.

PubMedRenal failure2026-09-04

Diagnostic and prognostic value of fibroblast growth factor 23 in acute kidney injury: systematic review and meta-analysis.

Pei Xiaohang X, Gao Hang H, Zhang Lina L

Background: Acute kidney injury (AKI) is associated with high mortality and adverse outcomes. Fibroblast growth factor 23 (FGF23) has emerged as a potential biomarker for AKI; however, its diagnostic and prognostic utility remains inconsistent.Methods: We conducted a systematic review and meta-analysis of studies evaluating circulating intact FGF23 (iFGF23) or C-terminal FGF23 (cFGF23) (PROSPERO: CRD42022302659). PubMed, EMBASE, CNKI, and Wanfang databases were searched through June 9, 2026. QUADAS-2 was used for quality assessment. A random-effects bivariate model pooled sensitivity, specificity, positive/negative likelihood ratio (PLR/NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (SROC AUC).Results: Twenty-three studies were included: 17 diagnostic, 6 prognostic (one addressing both). For AKI diagnosis, the pooled sensitivity was 0.79 (95% CI 0.73-0.86), specificity 0.82 (95% CI 0.75-0.89), PLR 4.40 (95% CI 2.59-6.21), NLR 0.25 (95% CI 0.16-0.34), DOR 17.49 (95% CI 8.67-35.16), and SROC AUC 0.87 (95% CI 0.81-0.92). Substantial heterogeneity was observed (I2 = 67%), with iFGF23 demonstrating higher accuracy than cFGF23 (AUC 0.91 vs 0.81). For AKI mortality, pooled sensitivity was 0.77 (95% CI 0.69-0.84), specificity 0.76 (95% CI 0.70-0.82), DOR 10.89 (95% CI 6.86-17.30), and SROC AUC 0.77 (95% CI 0.70-0.83). Significant heterogeneity was noted (I2 = 86.2% for sensitivity, 80.4% for specificity). No significant publication bias was detected.Conclusions: Circulating FGF23 exhibits moderate-to-high diagnostic and moderate prognostic performance in AKI, though interpretation is limited by substantial heterogeneity. It may serve as a complementary biomarker for risk stratification, pending further validation with standardized protocols.

PubMedFrontiers in immunology2026-09-04

Lipid metabolism and the immune microenvironment in gastric cancer.

Wang Zhuoyang Z, Du Yichen Y, Gu Qinglin Q, Liu Xinjie X et al.

The treatment of gastric cancer (GC) has entered an era of precision medicine combining molecular subtyping, immune checkpoint inhibitors (ICIs), anti-human epidermal growth factor receptor 2 (HER2), anti-claudin 18.2 (CLDN18.2), anti-angiogenic therapy, and chemotherapy. However, efficacy remains limited by tumor microenvironment (TME) heterogeneity, immune exclusion, myeloid suppression, nutrient competition, and metabolic adaptation. Lipid metabolic reprogramming represents a class of mechanisms with high translational value among metabolic immune checkpoints in GC: it supports tumor-cell membrane synthesis, redox homeostasis, peritoneal/omental metastasis, and adaptation to therapeutic stress, while also affecting regulatory T cells (Tregs), tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), dendritic cells, and CD8+ T cells. This review focuses on cluster of differentiation 36 (CD36)-mediated fatty acid uptake; carnitine palmitoyltransferase 1A (CPT1A)-dependent fatty acid oxidation (FAO); fatty acid synthase (FASN), acetyl-CoA carboxylase (ACC), sterol regulatory element-binding protein 1 (SREBP-1), and stearoyl-CoA desaturase 1 (SCD1)-mediated de novo lipogenesis; cholesterol and lipid-droplet metabolism; lipid-mediated post-translational modifications; lipid peroxidation; and ferroptosis. Lipid metabolism-targeted therapy should be positioned as a biomarker-driven combination strategy rather than as non-selective monotherapy. Future studies should integrate single-cell and spatial transcriptomics with lipidomics, imaging mass spectrometry, and paired pre- and post-treatment biopsies to define cell type-specific lipid dependencies and pharmacodynamic markers. Clinical translation will require prospective validation that a candidate intervention changes the intended lipid pathway in the intended tumor or immune-cell compartment without disabling metabolically essential normal tissues.

PubMedFrontiers in endocrinology2026-09-04

Proteoformics-driven new concept of human growth hormone in clinical endocrinology.

Zhang Qi Q, Ma Yuchen Y, Liu Ying Y, Ali Arshad A et al.

Growth hormone (GH) is a multifunctional regulator in somatic growth, metabolism, and tissue repair. Its pulsatile secretion is regulated by hypothalamic GH-releasing hormone (GHRH) and somatostatin (SST), and feedback inhibition by insulin-like growth factor 1 (IGF-1). Dysregulation of GH underlies several clinical disorders, including GH deficiency (GHD), acromegaly, and gigantism. The emerging concept of proteoformics has fundamentally reshaped the traditional view of GH: although human GH is encoded by a single gene, it gives rise to multiple proteoforms (GHPs) with distinct biological activities. In-depth study on GHPs pattern benefits understanding its precise molecular mechanism, discovering new therapeutic targets/drugs, and constructing GHPs-based biomarkers. Integration of proteoformics with multi-omics facilitates the construction of dynamic regulatory networks for GH signaling, thereby providing robust support for biomarker discovery and precision medicine strategies in GH-related diseases. Proteoform-based personalized therapy holds promise to advance current treatments such as somatostatin receptor ligands (SRLs), growth hormone receptor (GHR) antagonists, and long-acting GH formulations, with emerging therapies like antisense oligonucleotides and oral GHRH agonists showing preliminary promise. This review examines the potential role of proteoform-centered multi-omics in advancing personalized diagnosis and treatment, discusses challenges in clinical translation, and outlines a roadmap for integrating GH proteoformics into predictive, preventive, and personalized medicine (3PM).

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