Epiregulin is a 46-amino acid protein that belongs to the Epidermal Growth Factor (EGF) family of peptide hormones. Epiregulin binds to the EGF receptor (EGFR/ErbB1) and ErbB4 (HER4) and can stimulate signaling of ErbB2 (HER2/Neu) and ErbB3 (HER3) through ligand-induced heterodimerization with a cognate receptor. Epiregulin possesses a range of functions in both normal physiologic states as well as in pathologic conditions. Epiregulin contributes to inflammation, wound healing, tissue repair, and oocyte maturation by regulating angiogenesis and vascular remodeling and by stimulating cell proliferation. Deregulated epiregulin activity appears to contribute to the progression of a number of different malignancies, including cancers of the bladder, stomach, colon, breast, lung, head and neck, and liver. Therefore, epiregulin and the elements of the EGF/ErbB signaling network that lie downstream of epiregulin appear to be good targets for therapeutic intervention.

ERBB4 (HER4) is a member of the ERBB family of receptor tyrosine kinases, a family that includes the epidermal growth factor receptor (EGFR/ERBB1/HER1), ERBB2 (Neu/HER2), and ERBB3 (HER3). EGFR and ERBB2 are oncoproteins and validated targets for therapeutic intervention in a variety of solid tumors. In contrast, the role that ERBB4 plays in human malignancies is ambiguous. Thus, here we review the literature regarding ERBB4 function in human malignancies. We review the mechanisms of ERBB4 signaling with an emphasis on mechanisms of signaling specificity. In the context of this signaling specificity, we discuss the hypothesis that ERBB4 appears to function as a tumor suppressor protein and as an oncoprotein. Next, we review the literature that describes the role of ERBB4 in tumors of the bladder, liver, prostate, brain, colon, stomach, lung, bone, ovary, thyroid, hematopoietic tissues, pancreas, breast, skin, head, and neck. Whenever possible, we discuss the possibility that ERBB4 mutants function as biomarkers in these tumors. Finally, we discuss the potential roles of ERBB4 mutants in the staging of human tumors and how ERBB4 function may dictate the treatment of human tumors. Significance Statement This articles reviews ERBB4 function in the context of the mechanistic model that ERBB4 homodimers function as tumor suppressors, whereas ERBB4-EGFR or ERBB4-ERBB2 heterodimers act as oncogenes. Thus, this review serves as a mechanistic framework for clinicians and scientists to consider the role of ERBB4 and ERBB4 mutants in staging and treating human tumors.

Metastatic skin cutaneous melanomas remain a significant clinical problem. In particular, those melanomas that do not contain a gain-of-function BRAF allele remain challenging to treat because of the paucity of targets for therapeutic intervention. Thus, here we investigate the role of the ERBB4 receptor tyrosine kinase in skin cutaneous melanomas that contain wild-type BRAF alleles (“BRAF WT melanomas”). We have performed in silico analyses of a public repository (The Cancer Genome Atlas - TCGA) of skin cutaneous melanoma gene expression and mutation data (TCGA-SKCM data set). These analyses demonstrate that ERBB4 overexpression strongly correlates with RAS gene or NF1 mutations that stimulate RAS signaling. Thus, these results have led us to hypothesize that elevated ERBB4 signaling promotes PI3K signaling, which cooperates with elevated RAS signaling to drive BRAF WT melanomas. We have tested this hypothesis using commercially available BRAF WT melanoma cell lines. Overexpression of wild-type ERBB4 stimulates clonogenic proliferation of the MEL-JUSO, MEWO, and IPC-298 BRAF WT melanoma cell lines. Moreover, overexpression of a dominant-negative ERBB4 (K751M) mutant inhibits clonogenic proliferation of the MEL-JUSO and MEWO cell lines. We discuss how these results may impact strategies for treating metastatic BRAF WT skin cutaneous melanomas.

Whereas recent clinical studies report metastatic melanoma survival rates high as 30–50%, many tumors remain nonresponsive or become resistant to current therapeutic strategies. Analyses of The Cancer Genome Atlas (TCGA) skin cutaneous melanoma (SKCM) data set suggests that a significant fraction of melanomas potentially harbor gain-of-function mutations in the gene that encodes for the ErbB4 receptor tyrosine kinase. In this work, a drug discovery strategy was developed that is based on the observation that the Q43L mutant of the naturally occurring ErbB4 agonist Neuregulin-2beta (NRG2β) functions as a partial agonist at ErbB4. NRG2β/Q43L stimulates tyrosine phosphorylation, fails to stimulate ErbB4-dependent cell proliferation, and inhibits agonist-induced ErbB4-dependent cell proliferation. Compounds that exhibit these characteristics likely function as ErbB4 partial agonists, and as such hold promise as therapies for ErbB4-dependent melanomas. Consequently, three highly sensitive and reproducible (Z’ > 0.5) screening assays were developed and deployed for the identification of small-molecule ErbB4 partial agonists. Six compounds were identified that stimulate ErbB4 phosphorylation, fail to stimulate ErbB4-dependent cell proliferation, and appear to selectively inhibit ErbB4-dependent cell proliferation. Whereas further characterization is needed to evaluate the full therapeutic potential of these molecules, this drug discovery platform establishes reliable and scalable approaches for the discovery of ErbB4 inhibitors.

Introduction. ErbB4 (HER4) is a member of the ErbB family of receptor tyrosine kinases, a family that also includes the epidermal growth factor receptor (EGFR/ErbB1), ErbB2 (HER2/Neu), and ErbB3 (HER3). Gain-of-function ErbB4 mutants are found in a significant fraction of melanoma cell lines, suggesting that ErbB4 is a melanoma oncogene. However, there is a paucity of specific inhibitors for probing ErbB4 function or for treating ErbB4-dependent tumors. Consequently, we are developing high-throughput screening (HTS) approaches to address this void. Experimental Strategy. The Q43L mutant of the naturally-occurring ErbB4 agonist Neuregulin 2beta (NRG2beta) functions as a partial agonist at ErbB4; NRG2beta/Q43L stimulates ErbB4 tyrosine phosphorylation, but does not stimulate ErbB4 coupling to cell proliferation and competitively antagonizes agonist stimulation of ErbB4 coupling to cell proliferation. Therefore, we are developing three high-throughput assays to identify ErbB4 partial agonists that function as antagonists. (1) The primary screen will utilize a sandwich enzyme-linked immunosorbent assay (ELISA) to identify molecules that stimulate ErbB4 tyrosine phosphorylation. (2) The secondary screen will use an MTT proliferation assay to identify molecules that fail to stimulate ErbB4 coupling to cell proliferation. (3) An MTT proliferation assay will be used in the tertiary screen to identify molecules that inhibit agonist-induced ErbB4 coupling to cell proliferation. Molecules that stimulate ErbB4 tyrosine phosphorylation, do not stimulate ErbB4 coupling to cell proliferation, and inhibit agonist-induced ErbB4 coupling to proliferation are highly likely to function as ErbB4 antagonists. Results. (1) A high-throughput ELISA assay reproducibly detects stimulation of ErbB4 tyrosine phosphorylation by the ErbB4 full agonist NRG2beta (Z' = 0.730) and the ErbB4 antagonist (partial agonist) NRG2beta/Q43L (Z' = 0.664). (2) A high-throughput MTT assay reproducibly detects stimulation of ErbB4 coupling to cell proliferation by the ErbB4 full agonist NRG1beta (Z' = 0.236; 10 nM NRG1beta versus unstimulated). (3) A high-throughput MTT assay detects the difference between stimulation of ErbB4 coupling to cell proliferation by 2 nM NRG1beta and 10 nM NRG1beta (Z' = 0.246), suggesting that 80% inhibition of the activity of 10 nM NRG1beta at ErbB4 can be detected using this assay. (4) Initial screening of small molecule libraries using the primary screen has yielded more than 20 hits (potential novel small-molecule ErbB4 ligands). These hits are being validated and subjected to secondary and tertiary screens. Conclusions. We have validated HTS approaches for the identification of small molecule ErbB4 partial agonists and antagonists. The initial implementation of these approaches has yielded promising results. Citation Format: Richard L. Cullum, Ram B. Gupta, David J. Riese, II. A high-throughput screening process for the discovery of melanoma chemotherapeutics targeted at the ErbB4 receptor tyrosine kinase. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Melanoma: From Biology to Therapy; Sep 20-23, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(14 Suppl):Abstract nr B17.

Metastatic skin cutaneous melanomas that contain wild-type BRAF alleles ("BRAF WT melanomas") remain a significant clinical challenge, primarily because of the paucity of targets for therapeutic intervention. In prior work, in silico analyses of The Cancer Genome Atlas Skin Cutaneous Melanoma (TCGA-SKCM) dataset suggested that elevated transcription of the gene that encodes the ERBB4 receptor tyrosine kinase may drive BRAF WT melanomas. Moreover, that prior work demonstrated that expression of the wild-type ERBB4 gene (WT ERBB4) stimulates clonogenic proliferation by the MEL-JUSO, MeWo, and IPC-298 human BRAF WT melanoma cell lines. Moreover, expression of a dominant-negative (K751M) ERBB4 mutant (ERBB4 DN) inhibits clonogenic proliferation by the MEL-JUSO and MeWo cell lines. Here we have extended these findings by investigating the role of ERBB4 mutant alleles in BRAF WT melanomas. In silico analyses of the TCGA-SKCM BRAF WT melanoma dataset indicates that ERBB4 missense mutant alleles occur in a non-random manner, suggesting that melanomagenesis selects for the ERBB4 missense mutant alleles. Specifically, ERBB4 missense mutant alleles affect amino acid residues that are weakly correlated with residues conserved in the ERBB3 extracellular domains and the EGFR tyrosine kinase domain. The occurrence of ERBB4 missense mutant alleles in the TCGA-SKCM BRAF WT melanoma dataset is weakly inversely correlated with events that cause ERBB4-independent PI3K pathway signaling and is strongly correlated with events that cause elevated RAS pathway signaling. Thus, the in silico analyses suggest that ERBB4 mutant alleles stimulate PI3K signaling, which cooperates with elevated RAS signaling to drive BRAF WT melanomas. Moreover, the in silico analyses have prioritized the ERBB4 mutant alleles as candidate drivers of BRAF WT melanomas. One of the prioritized ERBB4 mutant alleles (P759L) stimulates greater clonogenic proliferation of MEL- JUSO cells than does WT ERBB4. Thus, our in silico prioritization strategy may effectively identify ERBB4 mutants that drive BRAF WT melanomas. Finally, the results of our in silico analyses suggest that ERBB4-dependent, BRAF WT melanomas may be effectively treated by a combination of a PI3K pathway inhibitor and a RAS pathway inhibitor.

Introduction: Despite advancements made in the treatment of metastatic melanoma, the 5-year survival rate remains about 20%. The high mortality rate is thought to be due to there being no other clinically actionable targets other than those that have been identified in the RAS/RAF/MEK/MAPK pathway. Our analyses of The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) data set revealed that 15% of the cases harbor at least one nonsynonymous missense mutation in the ERBB4 gene. This mutation incidence is significantly higher than that of the other ERBB genes in the same data set. Additionally, 91% of cases that harbor a nonsynonymous missense ERBB4 mutation also harbor a known melanoma driver mutation in the RAS/RAF/MEK/MAPK pathway suggesting interplay between ErbB4 signaling and the RAS/RAF/MEK/MAPK pathway. However, unlike the validated BRAF melanoma oncogene, ERBB4 mutations in melanoma are extremely heterogenous with 76 unique ERBB4 nonsynonymous missense mutations. None of which have incidence rates of greater than 2%. Furthermore, some of these ERBB4 mutations have already been shown to be necessary for the proliferation of some human melanoma cell lines, demonstrating a need to determine which ERBB4mutations contribute to melanoma tumorigenesis and clinical resistance. Experimental Procedures/Summary of Data: Consequently, various in silico approaches were used to prioritize ERBB4 mutations in melanoma. We found that many TCGA-SKCM ERBB4 mutations affect highly conserved regions. Indeed, 57 ERBB4 mutations affect a residue that is conserved in at least one other ErbB receptor. Moreover, 7 ERBB4 mutations affect a residue that is conserved in another ErbB receptor and is the location of a gain-of-function mutations in the other ERBB gene. Fifteen (15) of the putative ERBB4 melanoma driver mutations are found in other tumor types, and 3 transform the growth of fibroblasts and exhibit ligand-independent signaling. And, finally, we found that the combination of the ERBB4 E542K and E872K mutations and the E452K mutation alone are necessary for the proliferation of some human melanoma cell lines. Conclusions: Unlike genes such as BRAF or NRAS, which contain a single or a small number of “hot spot(s)” for driver mutations, the ERBB4 gene appears to harbor numerous mutations that are likely to function as drivers of melanoma tumorigenesis. Whereas some of the ERBB4 mutations found in melanoma have been identified as bona fide melanoma drivers, most remain uncharacterized. The results of these analyses indicate that many of these uncharacterized mutations are likely to contribute to the malignant phenotype of melanoma. Therefore, there remains a need to distinguish which ERBB4 mutations function as drivers and can serve as biomarkers for response to therapies that disrupt ErbB4 signaling. Citation Format: Richard Lee Cullum, Taraswi Ghosh, Lauren Lucas, Damien Waits, David Riese. Mutations in ERBB4 may account for clinical resistance of melanomas to inhibitors of the RAS/RAF/MEK/MAPK pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2144.

Human malignancies result from the accumulation of genetic and epigenetic changes to normal cells. In many malignancies, gain-of-function mutations in oncogenes and loss-of-function mutations in tumor suppressor genes drive tumorigenesis and tumor progression. The identification of tumor driver mutations and the genes that host such mutations is critical for the molecular staging and targeted therapy of malignancies. Since tumor driver mutations cause tumorigenesis or tumor progression, the proliferation of tumor cells selects for these mutations. Thus, in a gene that hosts tumor driver mutations, there will be a non-random distribution of mutations across the gene, as mutations that provide a selective advantage for the tumor cells will predominate over mutations that do not provide a selective advantage for the tumor cells. Consider a particular gene in a population of tumor genomes; the total number of coincident missense mutations in that gene, defined here as two or more missense mutations that affect a particular codon, will be greater than the total number of coincident missense mutations that arise through random assignment of missense mutations across the gene. Consequently, here we use the R Statistical Computing environment to simulate the random assignment of missense mutations across a user-specified gene. The number of randomly assigned missense mutations is defined by the user and should be equal to the total number of missense mutations observed in the desired gene in the collection of tumor genomes of interest. Based on the simulated random assignment of missense mutations, the R code then determines the total number of simulated coincident and non-coincident mutations. This simulation is repeated a user-defined number of times, and the average number of simulated coincident and non-coincident mutations is calculated from the set of simulations. The R code then uses a Chi-square test to determine whether the observed number of coincident mutations (in the gene of interest in a collection of tumor genomes) significantly exceeds the average number of simulated coincident mutations. A positive result indicates that the gene hosts a non-random distribution of missense mutations and suggests that the gene hosts tumor driver mutations. We have used this R code to analyze mutations in the ERBB4 receptor tyrosine kinase gene that are found in The Cancer Genome Atlas (TCGA) dataset. Our analysis indicates that the number of coincident mutations observed in ERBB4 in the TCGA dataset is statistically greater than the number of coincident mutations that arise from the simulated random assignment of missense mutations across the ERBB4 gene. This finding indicates that the distribution of missense mutations in ERBB4 in the TCGA dataset is non-random.