Abstract Background Increased aberrant expression or activation of the epidermal growth factor receptor (EGFR) family members has been reported in a wide range of cancers, and the EGFR family of tyrosine kinases has emerged as an important therapeutic target in malignancies. However, the expression patterns and exact roles of each distinct EGFR family member, which contribute to tumorigenesis and progression of ovarian cancer (OC), are yet to be elucidated. Materials and methods In the current study, we report the distinct expression and prognostic value of EGFR family members in patients with OC by analyzing a series of databases including ONCOMINE, Gene Expression Profiling Interactive Analysis, Kaplan–Meier plotter, cBioPortal, and Database for Annotation, Visualization and Integrated Discovery . Results It was found that in patients with OC, mRNA expression levels of ERBB2/3/4 were significantly upregulated, whereas the transcription levels of EGFR were downregulated. Aberrant EGFR expression and ERBB2/3/4 mRNA levels were associated with OC prognosis. Conclusion These results suggest that EGFR and ERBB3/4 are distinct prognostic biomarkers and may be potential targets for OC. These results may be beneficial to better understand the molecular underpinning of OC and may be useful to develop tools for more accurate OC prognosis and for promoting the development of EGFR-targeted inhibitors for OC treatment. Keywords: EGFR, ovarian cancer, database mining, prognostic value, bioinformatics analysis Introduction Ovarian cancer (OC) shows the highest cancer-related death rate among gynecological malignancies, with an estimated 204,000 cases and 125,000 deaths annually worldwide.[33]^1^,[34]^2 Over 75% of patients are not diagnosed until the disease is advanced (stages III and IV). Current prognostic factors do not allow reliable prediction of response to chemotherapy and survival for individual OC patients. The poor rate of survival and the high rate of lethality are partly due to lack of effective biomarkers for prognosis. Therefore, there is a pressing need to find reliable predictive biomarkers for prognosis and to develop novel therapeutic strategies for OC patients.[35]^2^,[36]^3 The epidermal growth factor receptor (EGFR) tyrosine kinase family consists of four members: EGFR, ERBB2, ERBB3, and ERBB4. These receptors are activated when a ligand binds to their extracellular ligand binding domain, which triggers receptor homodimerization or heterodimerization, resulting in the activation of several downstream cell signaling pathways and ultimately in tumor cell proliferation, reduced apoptosis, and tumor migration and invasion.[37]^4^–[38]^6 In the past three decades, increased aberrant expression or activation of the EGFR family members has been reported in a wide range of cancers, and in some studies, has also been associated with poor prognosis and resistance to therapeutic options.[39]^5^,[40]^7 Moreover, the EGFR family of tyrosine kinases has emerged as an important therapeutic target in malignancies, and to date, numerous antibodies, recombinant proteins, peptide mimetics, and small molecules, such as cetuximab, panitumumab, trastuzumab, gefitinib, erlotinib, and lapatinib, have been developed for targeting EGFR family receptors as therapeutic targets for many kinds of solid tumors.[41]^4^,[42]^7 Recent reports have suggested that the functions of different EGFR members contribute to OC tumorigenesis. However, the clinicopathological and prognostic value and expression patterns of EGFR family members in OC remain controversial.[43]^8^–[44]^10 In addition, the role of EGFR family members in OC and the underlying molecular mechanism responsible for its involvement in tumor development and progression are largely unknown. The development of microarray and RNA-sequencing technology has revolutionized RNA and DNA research, which has become a crucial component of biology and biomedical research.[45]^11^,[46]^12 In the current study, we extended the knowledge base related to OC based on a variety of large databases, with the purpose of determining the expression patterns, genetic alteration, potential functions, and distinct prognostic values of EGFR family members in OC. Materials and methods Ethics statement This study was approved by the Academic Committee of the People’s Hospital of China Three Gorges University, and conducted according to the principles expressed in the Declaration of Helsinki. All the datasets were retrieved from the databases, so it was confirmed that written informed consent had been obtained from all patients. ONCOMINE analysis The gene expression array datasets of ONCOMINE ([47]www.oncomine.org), which is a publicly accessible, online cancer microarray database helps facilitate research data from genome-wide expression analyses. ONCOMINE was used to analyze the mRNA levels of EGFR family members in OC.[48]^13^,[49]^14 In this study, the Student’s t-test was used to generate P-values for comparison between cancer specimens and normal control datasets. The cutoff P-value and fold change were defined as 0.05 and 1, respectively. Gene Expression Profiling Interactive Analysis (GEPIA) dataset analysis GEPIA is an interactive web server for estimating mRNA expression data based on 9,736 tumors and 8,587 normal samples in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression dataset projects. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection, and dimensionality reduction analysis.[50]^15 The Kaplan–Meier plotter analysis The prognostic value of the mRNA expression of EGFR family members was evaluated using an online database, Kaplan–Meier Plotter ([51]www.kmplot.com), which contains gene expression data and survival information of 1,816 clinical OC patients. To analyze the overall survival (OS), progression-free survival (PFS), and post-progression survival (PPS) of patients with OC, patient samples were split into two groups by median expression (high vs low expression) and assessed by a Kaplan–Meier survival plot, with a HR with 95% CI and log-rank P-value.[52]^16 TCGA and CBioPortal analysis Gene alteration frequency of EGFR family member mRNA in OC was performed using CBioPortal for Cancer Genomics ([53]http://www.cbioportal.org). The genomic profiles included mutations, putative copy-number alterations from GISTIC, mRNA expression z scores, and protein expression z scores.[54]^17 Functional enrichment and bioinformatics analysis GeneMANIA ([55]http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists, and prioritizing genes for functional assays. GeneMANIA was used to conduct correlation analysis of EGFR family members at the gene level, which revealed relationships in pathways, shared protein domains, co-localization, and co-expression.[56]^18 Finally, enrichment analysis was performed with The Database for Annotation, Visualization and Integrated Discovery (DAVID) (version 6.7) for EGFR family members and their neighboring genes. DAVID includes the gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.[57]^19^,[58]^20 Results Transcription levels of EGFR family members in patients with OC Using ONCOMINE analysis, four EGFR family members have been identified in human cancers, including hematological malignancies and solid tumors ([59]Figure 1). ONCOMINE analysis revealed that the mRNA expression levels of ERBB3 were significantly upregulated in patients with OC in three datasets. In Hendrix’s dataset,[60]^21 ERBB3 is overexpressed compared with that in the normal samples in all OC types – ovarian mucinous adenocarcinoma with a fold change of 2.355, ovarian clear cell adenocarcinoma with a fold change of 2.308, ovarian endometrioid adenocarcinoma with a fold change of 1.897, and ovarian serous adenocarcinoma with a fold change of 1.857. In Adib’s dataset,[61]^22 ERBB3 is overexpressed in ovarian serous adenocarcinoma with a fold change of 1.807. In Lu’s dataset,[62]^23 ERBB3 is overexpressed in ovarian endometrioid adenocarcinoma with a fold change of 1.635 and in ovarian serous adenocarcinoma with a fold change of 1.947 compared with that in the normal samples. The transcription levels of EGFR in ovarian serous adenocarcinoma were lower than that in normal ovarian tissues in two datasets (fold changes were −1.223 and −1.349, respectively)[63]^22^,[64]^24 ([65]Table 1). Figure 1. [66]Figure 1 [67]Open in a new tab The transcription levels of EGFR family members in different types of cancers (ONCOMINE). Notes: The graphic demonstrated the numbers of datasets with statistically significant mRNA overexpression (red) or down-expression (blue) of the target gene. The threshold was designed with following parameters: P-value =0.001; fold-change =1.5 and data type, mRNA. Abbreviations: EGFR, epidermal growth factor receptor; ERBB2, receptor tyrosine-protein kinase erbB-2; ERBB3, receptor tyrosine-protein kinase erbB-3; ErbB4, receptor tyrosine-protein kinase erbB-4. Table 1. The transcription levels of EGFR family members between different types of OC and normal tissues (ONCOMINE) EGFR family members Types of OC vs normal Fold change t-Test P-value Ref PMID __________________________________________________________________ EGFR Ovarian serous adenocarcinoma vs normal −1.223 −1.44 0.906 Adib Ovarian 14760385 Ovarian serous adenocarcinoma vs normal −1.349 −2.226 0.983 Yoshihara Ovarian 19486012 ERBB2 Ovarian endometrioid adenocarcinoma vs normal 1.402 11.344 2.35E–12 Hendrix Ovarian 16452189 Ovarian mucinous adenocarcinoma vs normal 1.47 9.83 3.85E–08 Hendrix Ovarian 16452189 Ovarian serous adenocarcinoma vs normal 1.408 13.145 2.76E–12 Hendrix Ovarian 16452189 Ovarian clear cell adenocarcinoma vs normal 1.826 7.306 5.99E–05 Hendrix Ovarian 16452189 Ovarian serous surface papillary carcinoma vs normal 1.75 5.939 8.97E–05 Welsh Ovarian 11158614 Ovarian serous adenocarcinoma vs normal 1.984 4.55 6.53E–06 Yoshihara Ovarian 19486012 Ovarian carcinoma vs normal 2.484 8.219 2.85E–06 Bonome Ovarian 18593951 Ovarian clear cell adenocarcinoma vs normal 1.672 4.176 2.00E–03 Lu Ovarian 15161682 ERBB3 Ovarian mucinous adenocarcinoma vs normal 2.355 14.003 2.04E–09 Hendrix Ovarian 16452189 Ovarian clear cell adenocarcinoma vs normal 2.308 13.845 5.07E–08 Hendrix Ovarian 16452189 Ovarian endometrioid adenocarcinoma vs normal 1.897 13.296 3.89E–07 Hendrix Ovarian 16452189 Ovarian serous adenocarcinoma vs normal 1.857 13.245 1.05E–06 Hendrix Ovarian 16452189 Ovarian serous adenocarcinoma vs normal 1.807 5.877 6.89E–04 Adib Ovarian 14760385 Ovarian endometrioid adenocarcinoma vs normal 1.635 4.022 9.14E–04 Lu Ovarian 15161682 Ovarian serous adenocarcinoma vs normal 1.947 4.391 1.07E–04 Lu Ovarian 15161682 Ovarian serous adenocarcinoma vs normal 11.326 7.647 2.03E–06 Yoshihara Ovarian 19486012 ERBB4 Ovarian serous adenocarcinoma vs normal 1.725 13.668 1.67E–17 Hendrix Ovarian 16452189 Ovarian endometrioid adenocarcinoma vs normal 1.465 9.503 5.91E–12 Hendrix Ovarian 16452189 Ovarian clear cell adenocarcinoma vs normal 1.646 4.866 8.73E–04 Hendrix Ovarian 16452189 [68]Open in a new tab Notes: P-value was analyzed using the t-test. The bold font indicates that the difference was statistically significant between the OC and normal tissue group. Abbreviations: EGFR, epidermal growth factor receptor; ERBB2, receptor tyrosine-protein kinase erbB-2; ERBB3, receptor tyrosine-protein kinase erbB-3; ERBB4, receptor tyrosine-protein kinase erbB-4; OC, ovarian cancer; PMID, PubMed unique identifier; Ref, references.