Oncology and Pharmacogenomics Insights in Polycystic Ovary Syndrome: An Integrative Analysis

Abstract

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovaries. Epidemiological findings revealed that women with PCOS are prone to develop certain cancer types due to their shared metabolic and endocrine abnormalities. However, the mechanism that relates PCOS and oncogenesis has not been addressed. Herein, in this review article the genomic status, transcriptional and protein profiles of 264 strongly PCOS related genes (PRG) were evaluated in endometrial cancer (EC), ovarian cancer (OV) and breast cancer (BC) exploring oncogenic databases. The genomic alterations of PRG were significantly higher when compared with a set of non-diseases genes in all cancer types. PTEN had the highest number of mutations in EC, TP53, in OC, and FSHR, in BC. Based on clinical data, women older than 50 years and Black or African American females carried the highest ratio of genomic alterations among all cancer types. The most altered signaling pathways were p53 in EC and OC, while Fc epsilon RI in BC. After evaluating PRG in normal and cancer tissue, downregulation of the differentially expressed genes was a common feature. Less than 30 proteins were up and downregulated in all cancer contexts. We identified 36 highly altered genes, among them 10 were shared between the three cancer types analyzed, which are involved in the cell proliferation regulation, response to hormone and to endogenous stimulus. Despite limited PCOS pharmacogenomics studies, 10 SNPs are reported to be associated with drug response. All were missense mutations, except for rs8111699, an intronic variant characterized as a regulatory element and presumably binding site for transcription factors. In conclusion, in silico analysis revealed key genes that might participate in PCOS and oncogenesis, which could aid in early cancer diagnosis. Pharmacogenomics efforts have implicated SNPs in drug response, yet still remain to be found.

Keywords: bioinformatic; breast cancer (BC); endometrial cancer (EC); ovarian cancer (OC); pharmacogenomics; polycystic ovary syndrome (PCOS).

Figure 1

Exploration of associated PCOS genes (PRG [n=264]). (A) Most significant GO: biological processes, Reactome pathways, WikiPathways (WP) and Human Phenotype Ontology according to g:Profler Manhattan plot. (B) Circos plot of PRG with hallmarks of cancer taken from COSMIC database.

Figure 2

Genomic alterations in endometrial, ovarian and breast cancer according to PanCancer Atlas. (A) Frequency of genomic alterations per gen set (associated PCOS genes (PRG [n=264]) and not associated PCOS genes (PNRG [n=300]) in each cancer type. Mann-Whitney U test with significant level of p < 0.05. (B) Percentage of genomic alterations types in each cancer type. (C) Identification endometrial, ovarian and breast cancer driver genes found in the list of PRG.

Figure 3

Genomic alterations based on age and race categories in endometrial, ovarian and breast cancer using PanCancer Atlas data in cBioPortal. (A) Cumulative ratio of genomic alterations in women aged 50 or less and older than 50 years, per cancer type. (B) Ranking of genes with the highest number of genomic mutations per age group in each cancer type. Mann-Whitney U test with significant level of p < 0.05. (C) Cumulative ratio of genomic alterations per race category in three cancer types. (D) Ranking of genes with the highest number of genomic mutations per race group in the three cancer types. Dunn-Bonferroni post hoc method was performed following a significant Kruskal-Wallis test, only significant p-values are presented.

Figure 4

Pathway enrichment analysis endometrial, ovarian and breast cancer. (A) Significantly enriched KEGG pathways of associated PCOS related genes (PRG [n=264]) retrieved from DAVID bioinformatics platform. The number in each bar are the gene count per pathways. (B) Circos plot depicting the most altered pathways (first quartile colored in each cancer type).

Figure 5

Gene and protein expression profiling of PCOS related genes (PRG) in endometrial, ovarian and breast cancer compared with normal tissue. (A) Heatmap displays the differential expressed genes with |Log2FC| = 1, FDR < 0.001 from GEPIA database. Empty spaces indicate absence of differential expression. (B) Correlation plot comparing immunohistochemical protein expression profile between cancer samples and healthy tissue according to The Human Protein Atlas (HPA) in each cancer type.

Figure 6

Key genes between gynecological cancer and PCOS. (A) Venn diagrams depicting the number of unique and shared associated PCOS across the three omics approaches. The list of genes at the left are the genes that appeared in the three omics approaches in each cancer type. (B) The Venn diagram shows PCOS related genes altered in at least two omics approaches in breast and gynecological cancers to stablish a relationship between the syndrome and cancer genetics.

Figure 7

UCSC Genome Brower (Human Feb 2009 (GRCh37/hg19 assembly) displaying rs8111699 (highlighted) and tracks representing histone marks and transcription factors in the first intron of STK11. For histone marks peak height is proportional to the signal amplitude with colors representing databases in seven different cell lines*. For transcription factor binding tracks, the length of the box indicates region of occupancy and the darkness is proportional to the signal strength observed in several cell lines. To the right there is the number of cell types contributing to the cluster or a fraction that corresponds the number of cell where the factor was detected out of all cell assayed. The letters represent the cell abbreviation L, HepG2; K, K562; a, adrenal gland; G, GM12878; t, tibial nerve. * 7 Cell lines for histone marks from ECODE: GM12878 (B-lymphocyte, lymphoblastoid), H1-hESC (embryonic stem cells), HSMM (skeletal muscle myoblasts), HUVEC (umbilical vein endothelial cells), K562 (erythroleukemic), NHEK (epidermal keratinocytes), NHLF (lung fibroblasts).