Identification of core genes and clinical roles in pregnancy-associated breast cancer based on integrated analysis of different microarray profile datasets

Abstract

More women are delaying child-birth. Thus, the diagnosis of pregnancy-associated breast cancer (PABC) will continue to increase. The aim of this study was to identify core candidate genes of PABC, and the relevance of the genes on the prognosis of PABC. GSE31192 and GSE53031 microarray profile datasets were downloaded from the Gene Expression Omnibus database and differentially expressed genes were analyzed using the R package and GEO2R tool. Then, Gene Ontology and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Moreover, the Search Tool for the Retrieval of Interacting Genes and the Molecular Complex Detection Cytoscape software plug-in were utilized to visualize protein–protein interactions and to screen candidate genes. A total of 239 DEGs were identified in PABC, including 101 up-regulated genes mainly enriched in fatty acid activation and the fibroblast growth factor signaling pathway, while 138 down-regulated genes particularly involved in activation of DNA fragmentation factor and apoptosis-induced DNA fragmentation. Fourteen hub genes with a high degree of connectivity were selected, including CREB1, ARF3, UBA5, SIAH1, KLHL3, HECTD1, MMP9, TRIM69, MEX3C, ASB6, UBE2Q2, FBXO22, EIF4A3, and PXN. Overall survival (OS) analysis of core candidate genes was performed using the Gene Expression Profiling Interactive Analysis and UALCAN websites. High ASB6 expression was associated with worse OS of PABC patients. Molecular subtypes and menopause status were also associated with worse OS for PABC patients. In conclusion, ASB6 could be a potential predictor and therapeutic target in patient with PABC.

The Genomic Profile of Pregnancy-Associated Breast Cancer: A Systematic Review

“…The search strategy retrieved 23 articles. Of these, 16 were omitted based on the exclusion criteria and 7 were eligible (11)(12)(13)(14)(15)(16)(17). While examining the references of eligible articles, 2 more articles were included (18,19).…”

“…As far as the genomic analysis approach is concerned, four studies were based on formalin-fixed paraffin embedded (FFPE) tissue analysis ( 11 – 13 , 18 ), one study examined fresh frozen tissue ( 14 ), three studies were associated with bioinformatic analysis and microarray profile datasets ( 15 , 16 , 19 ), and one study did not provide precise information regarding the methodology steps ( 17 ). Importantly, all studies included in the review were case-control studies; thus, the groups compared in each study exhibited similar clinicopathological characteristics.…”

“…Zhang et al recently published an analysis on core genes and their clinical roles in PABC. Their research was based on two microarray profile datasets that derived from studies previously described in our review (12,14), but instead focused on the identification of molecular biomarkers using the collective data (15). A total of 239 DEGs were detected in PABC, including 101 up-regulated and 138 down-regulated genes.…”

The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: A Therapeutic Perspective

“…Moreover, ARF3 overexpression promotes breast cancer cell proliferation by regulating the cellcycle G1/S transition, through inhibition of FOXO1 transcription factor activity . Additionally, ARF3 was found to be a candidate gene involved in the progression of Olstad et al, 2003;Ma et al, 2005;Kannangai et al, 2007;Tsai et al, 2012;Schlienger et al, 2015;Davis et al, 2016;Gu et al, Woo et al, 2009;Bidkhori et al, 2013;Howley et al, 2018;Wu Q. et al, 2018ARF6 ↑ Breast, Gastric, Glioma, Liver, Lung, Melanoma, Pancreatic, Prostate, Renal Cell Carcinoma Hashimoto et al, 2004Hu et al, 2009;Knizhnik et al, 2011;Oka et al, 2014;Morgan et al, 2015;Zhang et al, 2015;Hashimoto et al, 2016;Liang et al, 2017; Fujii et al, 2014;Guo et al, 2015;Fujii et al, 2016;Hu et al, 2018;Chen et al, 2019;Harada et al, 2019;Isono et al, Calin et al, 2005;Petrocca et al, 2006;Yendamuri et al, 2008;Siltanen et al, pregnancy-associated breast cancer, based on integrated analysis of microarray profile datasets (Zhang et al, 2019).…”

Emerging role of FBXO22 in carcinogenesis

“…Similarly, low expression of FBXO22 is associated with poor survival in patients with breast cancer 42 . Intriguingly, FBXO22 is downregulated in pregnancy-associated breast cancer via analysis of NCBI-GEO datasets 51 . IHC analysis in renal cell carcinoma (RCC) tissues found that FBXO22 expression levels were decreased in RCC specimens compared with those in normal renal tissues 50 .…”