MDM2 Promoter SNP344T>A (rs1196333) Status Does Not Affect Cancer Risk

The MDM2 proto-oncogene plays a key role in central cellular processes like growth control and apoptosis, and the gene locus is frequently amplified in sarcomas. Two polymorphisms located in the MDM2 promoter P2 have been shown to affect cancer risk. One of these polymorphisms (SNP309T>G; rs2279744) facilitates Sp1 transcription factor binding to the promoter and is associated with increased cancer risk. In contrast, SNP285G>C (rs117039649), located 24 bp upstream of rs2279744, and in complete linkage disequilibrium with the SNP309G allele, reduces Sp1 recruitment and lowers cancer risk. Thus, fine tuning of MDM2 expression has proven to be of significant importance with respect to tumorigenesis. We assessed the potential functional effects of a third MDM2 promoter P2 polymorphism (SNP344T>A; rs1196333) located on the SNP309T allele. While in silico analyses indicated SNP344A to modulate TFAP2A, SPIB and AP1 transcription factor binding, we found no effect of SNP344 status on MDM2 expression levels. Assessing the frequency of SNP344A in healthy Caucasians (n = 2,954) and patients suffering from ovarian (n = 1,927), breast (n = 1,271), endometrial (n = 895) or prostatic cancer (n = 641), we detected no significant difference in the distribution of this polymorphism between any of these cancer forms and healthy controls (6.1% in healthy controls, and 4.9%, 5.0%, 5.4% and 7.2% in the cancer groups, respectively). In conclusion, our findings provide no evidence indicating that SNP344A may affect MDM2 transcription or cancer risk

Population distribution and ancestry of the cancer protective MDM2 SNP285 (rs117039649)

Cataloged from PDF version of article.The MDM2 promoter SNP285C is located on the SNP309G allele. While SNP309G enhances Sp1 transcription factor binding and MDM2 transcription, SNP285C antagonizes Sp1 binding and reduces the risk of breast-, ovary- and endometrial cancer. Assessing SNP285 and 309 genotypes across 25 different ethnic populations (>10.000 individuals), the incidence of SNP285C was 6-8% across European populations except for Finns (1.2%) and Saami (0.3%). The incidence decreased towards the Middle-East and Eastern Russia, and SNP285C was absent among Han Chinese, Mongolians and African Americans. Interhaplotype variation analyses estimated SNP285C to have originated about 14,700 years ago (95% CI: 8,300 - 33,300). Both this estimate and the geographical distribution suggest SNP285C to have arisen after the separation between Caucasians and modern day East Asians (17,000 - 40,000 years ago). We observed a strong inverse correlation (r = -0.805; p < 0.001) between the percentage of SNP309G alleles harboring SNP285C and the MAF for SNP309G itself across different populations suggesting selection and environmental adaptation with respect to MDM2 expression in recent human evolution. In conclusion, we found SNP285C to be a pan-Caucasian variant. Ethnic variation regarding distribution of SNP285C needs to be taken into account when assessing the impact of MDM2 SNPs on cancer risk

Using urine to diagnose large-scale mtDNA deletions in adult patients

Objective: The aim of this study was to evaluate if urinary sediment cells offered a robust alternative to muscle biopsy for the diagnosis of single mtDNA deletions. Methods: Eleven adult patients with progressive external ophthalmoplegia and a known single mtDNA deletion were investigated. Urinary sediment cells were used to isolate DNA, which was then subjected to long-range polymerase chain reaction. Where available, the patient's muscle DNA was studied in parallel. Breakpoint and thus deletion size were identified using both Sanger sequencing and next generation sequencing. The level of heteroplasmy was determined using quantitative polymerase chain reaction. Results: We identified the deletion in urine in 9 of 11 cases giving a sensitivity of 80%. Breakpoints and deletion size were readily detectable in DNA extracted from urine. Mean heteroplasmy level in urine was 38% +/- 26 (range 8 - 84%), and 57% +/- 28 (range 12 - 94%) in muscle. While the heteroplasmy level in urinary sediment cells differed from that in muscle, we did find a statistically significant correlation between these two levels (R = 0.714, P = 0.031(Pearson correlation)). Interpretation: Our findings suggest that urine can be used to screen patients suspected clinically of having a single mtDNA deletion. Based on our data, the use of urine could considerably reduce the need for muscle biopsy in this patient group.Peer reviewe

Genetic Dominant Variants in STUB1, Segregating in Families with SCA48, Display In Vitro Functional Impairments Indistinctive from Recessive Variants Associated with SCAR16.

Variants in STUB1 cause both autosomal recessive (SCAR16) and dominant (SCA48) spinocerebellar ataxia. Reports from 18 STUB1 variants causing SCA48 show that the clinical picture includes later-onset ataxia with a cerebellar cognitive affective syndrome and varying clinical overlap with SCAR16. However, little is known about the molecular properties of dominant STUB1 variants. Here, we describe three SCA48 families with novel, dominantly inherited STUB1 variants (p.Arg51_Ile53delinsProAla, p.Lys143_Trp147del, and p.Gly249Val). All the patients developed symptoms from 30 years of age or later, all had cerebellar atrophy, and 4 had cognitive/psychiatric phenotypes. Investigation of the structural and functional consequences of the recombinant C-terminus of HSC70-interacting protein (CHIP) variants was performed in vitro using ubiquitin ligase activity assay, circular dichroism assay and native polyacrylamide gel electrophoresis. These studies revealed that dominantly and recessively inherited STUB1 variants showed similar biochemical defects, including impaired ubiquitin ligase activity and altered oligomerization properties of the CHIP. Our findings expand the molecular understanding of SCA48 but also mean that assumptions concerning unaffected carriers of recessive STUB1 variants in SCAR16 families must be re-evaluated. More investigations are needed to verify the disease status of SCAR16 heterozygotes and elucidate the molecular relationship between SCA48 and SCAR16 diseases

Treatment with aromatase inhibitors stimulates the expression of Epidermal growth factor receptor-1 and neuregulin 1 in ER positive \ HER-2neu non-amplified primary breast cancers

This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.jsbmb.2016.06.011While estrogens have been shown to modulate EGFR/HER-1 and HER-2/neu expression in experimental systems, the effects of estrogen deprivation on expression levels of the HER-receptors and the neuregulin (NRG)1 ligand in breast cancers remain unknown. Here, we measured EGFR/HER-1-4 and NRG1 mRNA in ER positive tumors from 85 postmenopausal breast cancer patients before and after two weeks (n = 64) and three months (n = 85) of primary treatment with an aromatase inhibitor (AI). In tumors lacking HER-2/neu amplification, quantitative real-time PCR analyses revealed EGFR/HER-1 and NRG1 to vary significantly between the three time points (before therapy, after 2 weeks and after 3 months on treatment; P ≤ 0.001 for both). Pair-wise comparison revealed a significant increase in EGFR/HER-1 already during the first two weeks of treatment (P = 0.049) with a further increase for both EGFR/HER-1 and NRG1 after 3 months on treatment (P ≤ 0.001 and P = 0.001 for both comparing values at 3 months to values at baseline and 2 weeks respectively). No difference between tumors responding versus non-responders was recorded. Further, no significant change in any parameter was observed among HER-2/neu amplified tumors. Analyzing components of the HER-2/neu PI3K/Akt downstream pathway, the PIK3CA H1047R mutation was associated with treatment response (P = 0.035); however no association between either AKT phosphorylation status or PIK3CA gene mutations and EGFR/HER-1 or NRG1 expression levels were observed. Our results indicate primary AI treatment to modulate expression of HER-family members and the growth factor NRG1 in HER-2/neu non-amplified breast cancers in vivo. Potential implications to long term sensitivity warrants further investigations.The study was supported by the Norwegian Cancer Society (https://kreftforeningen.no), The Western Norway Regional Health Authority (http://www.helse-bergen.no/forskning/samarbeidsorganet), Odd Fellow Medisinsk Vitenskapelig Forskningsfond (oddfellow.no) and Martin Flatners legat

Potential Transcriptional Biomarkers to Guide Glucocorticoid Replacement in Autoimmune Addison's Disease

Background No reliable biomarkers exist to guide glucocorticoid (GC) replacement treatment in autoimmune Addison’s disease (AAD), leading to overtreatment with alarming and persistent side effects or undertreatment, which could be fatal. Objective To explore changes in gene expression following different GC replacement doses as a means of identifying candidate transcriptional biomarkers to guide GC replacement in AAD. Methods Step 1: Global microarray expression analysis on RNA from whole blood before and after intravenous infusion of 100 mg hydrocortisone (HC) in 10 patients with AAD. In 3 of the most highly upregulated genes, we performed real-time PCR (rt-PCR) to compare gene expression levels before and 3, 4, and 6 hours after the HC infusion. Step 2: Rt-PCR to compare expression levels of 93 GC-regulated genes in normal versus very low morning cortisol levels in 27 patients with AAD. Results Step 1: Two hours after infusion of 100 mg HC, there was a marked increase in FKBP5, MMP9, and DSIPI expression levels. MMP9 and DSIPI expression levels correlated with serum cortisol. Step 2: Expression levels of CEBPB, DDIT4, FKBP5, DSIPI, and VDR were increased and levels of ADARB1, ARIDB5, and POU2F1 decreased in normal versus very low morning cortisol. Normal serum cortisol levels positively correlated with DSIPI, DDIT4, and FKBP5 expression. Conclusions We introduce gene expression as a novel approach to guide GC replacement in AAD. We suggest that gene expression of DSIPI, DDIT4, and FKBP5 are particularly promising candidate biomarkers of GC replacement, followed by MMP9, CEBPB, VDR, ADARB1, ARID5B, and POU2F1.publishedVersio