Prevalence of ERα-397 PvuII C/T, ERα-351 XbaI A/G and PGR PROGINS polymorphisms in Brazilian breast cancer-unaffected women

Up-regulated and hypomethylated genes are causative factors and diagnostic markers of osteoporosis

BACKGROUND

Due to the lack of sensitive diagnostic biomarkers for osteoporosis (OP), there is an urgent need to identify and uncover biomarkers associated with the disease in order to facilitate early clinical diagnosis and effective intervention strategies.

METHODS

GEO2R was employed to conduct a screening of differentially expressed genes (DEGs) within the transcriptome sequencing data obtained from blood samples of OP patients within the GSE163849 dataset. Subsequently, we conducted expression confirmation of the identified DEGs using an additional dataset, GSE35959. To further explore Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, MicroRNA (miRNA) interactions, and drug predictions, we employed the DAVID, miRTarBase, and DrugBank databases. For validation purposes, clinical OP samples paired with normal controls were collected from the Pakistani population. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was employed to assess the expression levels of DEGs and miRNA, while targeted bisulfite sequencing (bisulfite-seq) analysis was used to investigate methylation patterns. DNA and RNA from clinical OP and normal control samples were extracted using appropriate methods.

RESULTS

Out of total identified 269 DEGs, EGFR (epidermal growth factor receptor), HMOX1 (heme oxygenase-1), PGR (progesterone receptor), CXCL10 (C-X-C motif chemokine ligand 10), CCL5 (C-C motif chemokine ligand 5), and IL12B (interleukin 12B) were prioritized as top DEGs in OP patients. Expression validation of these genes on additional Gene Expression Omnibus (GEO) dataset and Pakistani OP patients revealed consistent significant up-regulation of these genes in OP patients. Receiver operating characteristic (ROC) analysis demonstrated that these DEGs displayed considerable diagnostic accuracy for detecting OP. Targeted bisulfite-seq analysis further revealed that EGFR, HMOX1, PGR, CXCL10, CCL5, and IL12B were hypomethylated in OP patients. Moreover, has-miR-27a-5p, a common expression regulator of the EGFR, HMOX1, PGR, CXCL10, CCL5, and IL12B was also significantly down-regulated in OP patients.

CONCLUSION

The DEGs that have been identified hold significant potential for the future development of diagnostic and treatment approaches for OP in preclinical and clinical applications.

Progesterone Receptor Gene Polymorphisms and Breast Cancer Risk

The objective of this systematic review was to investigate the association between polymorphisms in the progesterone receptor gene (PGR) and breast cancer risk. A search of PubMed, Scopus, and Web of Science databases was performed in November 2021. Study characteristics, minor allele frequencies, genotype frequencies, and odds ratios were extracted. Forty studies met the eligibility criteria and included 75 032 cases and 89 425 controls. Of the 84 PGR polymorphisms reported, 7 variants were associated with breast cancer risk in at least 1 study. These polymorphisms included an Alu insertion (intron 7) and rs1042838 (Val660Leu), also known as PROGINS. Other variants found to be associated with breast cancer risk included rs3740753 (Ser344Thr), rs10895068 (+331G/A), rs590688 (intron 2), rs1824128 (intron 3), and rs10895054 (intron 6). Increased risk of breast cancer was associated with rs1042838 (Val660Leu) in 2 studies, rs1824128 (intron 3) in 1 study, and rs10895054 (intron 6) in 1 study. The variant rs3740753 (Ser344Thr) was associated with decreased risk of breast cancer in 1 study. Mixed results were reported for rs590688 (intron 2), rs10895068 (+331G/A), and the Alu insertion. In a pooled analysis, the Alu insertion, rs1042838 (Val660Leu), rs3740753 (Ser344Thr), and rs10895068 (+331G/A) were not associated with breast cancer risk. Factors reported to contribute to differences in breast cancer risk associated with PGR polymorphisms included age, ethnicity, obesity, and postmenopausal hormone therapy use. PGR polymorphisms may have a small contribution to breast cancer risk in certain populations, but this is not conclusive with studies finding no association in larger, mixed populations.

Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review

BACKGROUND

Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density.

METHODS

The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed.

RESULTS

Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait.

CONCLUSION

Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.

Does circulating progesterone mediate the associations of single nucleotide polymorphisms in progesterone receptor (PGR)-related genes with mammographic breast density in premenopausal women?

Progesterone is a proliferative hormone in the breast but the associations of genetic variations in progesterone-regulated pathways with mammographic breast density (MD) in premenopausal women and whether these associations are mediated through circulating progesterone are not clearly defined. We, therefore, investigated these associations in 364 premenopausal women with a median age of 44 years. We sequenced 179 progesterone receptor (PGR)-related single nucleotide polymorphisms (SNPs). We measured volumetric percent density (VPD) and non-dense volume (NDV) using Volpara. Linear regression models were fit on circulating progesterone or VPD/NDV separately. We performed mediation analysis to evaluate whether the effect of a SNP on VPD/NDV is mediated through circulating progesterone. All analyses were adjusted for confounders, phase of menstrual cycle and the Benjamini-Hochberg false discovery (FDR) adjusted p-value was applied to correct for multiple testing. In multivariable analyses, only PGR rs657516 had a direct effect on VPD (averaged direct effect estimate = - 0.20, 95%CI = - 0.38 ~ - 0.04, p-value = 0.02) but this was not statistically significant after FDR correction and the effect was not mediated by circulating progesterone (mediation effect averaged across the two genotypes = 0.01, 95%CI = - 0.02 ~ 0.03, p-value = 0.70). Five SNPs (PGR rs11571241, rs11571239, rs1824128, rs11571150, PGRMC1 rs41294894) were associated with circulating progesterone but these were not statistically significant after FDR correction. SNPs in PGR-related genes were not associated with VPD, NDV and circulating progesterone did not mediate the associations, suggesting that the effects, if any, of these SNPs on MD are independent of circulating progesterone.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12672-021-00438-1.

Hormone-related pathways and risk of breast cancer subtypes in African American women

We sought to investigate genetic variation in hormone pathways in relation to risk of overall and subtype-specific breast cancer in women of African ancestry (AA). Genotyping and imputation yielded data on 143,934 SNPs in 308 hormone-related genes for 3663 breast cancer cases (1098 ER-, 1983 ER+, 582 ER unknown) and 4687 controls from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium. AMBER includes data from four large studies of AA women: the Carolina Breast Cancer Study, the Women's Circle of Health Study, the Black Women's Health Study, and the Multiethnic Cohort Study. Pathway- and gene-based analyses were conducted, and single-SNP tests were run for the top genes. There were no strong associations at the pathway level. The most significantly associated genes were GHRH, CALM2, CETP, and AKR1C1 for overall breast cancer (gene-based nominal p ≤ 0.01); NR0B1, IGF2R, CALM2, CYP1B1, and GRB2 for ER+ breast cancer (p ≤ 0.02); and PGR, MAPK3, MAP3K1, and LHCGR for ER- disease (p ≤ 0.02). Single-SNP tests for SNPs with pairwise linkage disequilibrium r (2) < 0.8 in the top genes identified 12 common SNPs (in CALM2, CETP, NR0B1, IGF2R, CYP1B1, PGR, MAPK3, and MAP3K1) associated with overall or subtype-specific breast cancer after gene-level correction for multiple testing. Rs11571215 in PGR (progesterone receptor) was the SNP most strongly associated with ER- disease. We identified eight genes in hormone pathways that contain common variants associated with breast cancer in AA women after gene-level correction for multiple testing.