Relationship of body mass index with aromatisation and plasma and tissue oestrogen levels in postmenopausal breast cancer patients treated with aromatase inhibitors

Background: Recent data have raised concern about the clinical efficacy of aromatase inhibitors in overweight and/or obese breast cancer patients. We report in vivo aromatase inhibition and plasma and tissue oestrogen levels in relation to body mass index (BMI) status among breast cancer patients treated with different aromatase inhibitors. Methods: We compared data on in vivo aromatase inhibition (64 patients) as well as plasma and tissue oestrogen levels from patients participating in our studies to BMI values. Results: We found a weak positive correlation between pretreatment aromatisation level and BMI (n = 64; R = 0.236; p = 0.060) but no correlation between on-treatment aromatisation levels or percentage aromatase inhibition and BMI within patient subgroups treated with any of a panel of aromatase inhibitors. Pre-treatment levels of plasma estradiol (p < 0.001), estrone (p = 0.001) and estrone sulphate (p = 0.002) correlated to BMI. While on-treatment levels of plasma estrane sulphate correlated to BMI in patients on letrozole (R = 0.601; p = 0.001; n = 25 for all) or anastrozole (n = 12; R = 0.611; p = 0.035) therapy, letrozole suppressed plasma estrone sulphate more than anastrozole independent of BMI. No correlation between on-treatment tumour oestrogen levels and BMI was recorded. Conclusions: Our unique data do not support a lack of effective aromatase inhibition in overweight patients or therefore a need for alternative therapy. The higher levels of estrogens in overweight postmenopausal breast cancer patients before and during aromatase inhibition may be due to effects of BMI on oestrogen metabolism rather than aromatisation.publishedVersio

Relationship of body mass index with aromatisation and plasma and tissue oestrogen levels in postmenopausal breast cancer patients treated with aromatase inhibitors

Background: Recent data have raised concern about the clinical efficacy of aromatase inhibitors in overweight and/or obese breast cancer patients. We report in vivo aromatase inhibition and plasma and tissue oestrogen levels in relation to body mass index (BMI) status among breast cancer patients treated with different aromatase inhibitors. Methods: We compared data on in vivo aromatase inhibition (64 patients) as well as plasma and tissue oestrogen levels from patients participating in our studies to BMI values. Results: We found a weak positive correlation between pretreatment aromatisation level and BMI (n = 64; R = 0.236; p = 0.060) but no correlation between on-treatment aromatisation levels or percentage aromatase inhibition and BMI within patient subgroups treated with any of a panel of aromatase inhibitors. Pre-treatment levels of plasma estradiol (p < 0.001), estrone (p = 0.001) and estrone sulphate (p = 0.002) correlated to BMI. While on-treatment levels of plasma estrane sulphate correlated to BMI in patients on letrozole (R = 0.601; p = 0.001; n = 25 for all) or anastrozole (n = 12; R = 0.611; p = 0.035) therapy, letrozole suppressed plasma estrone sulphate more than anastrozole independent of BMI. No correlation between on-treatment tumour oestrogen levels and BMI was recorded. Conclusions: Our unique data do not support a lack of effective aromatase inhibition in overweight patients or therefore a need for alternative therapy. The higher levels of estrogens in overweight postmenopausal breast cancer patients before and during aromatase inhibition may be due to effects of BMI on oestrogen metabolism rather than aromatisation

The novel microRNAs hsa-miR-nov7 and hsamiR- nov3 are over-expressed in locally advanced breast cancer

miRNAs are an important class of small non-coding RNAs, which play a versatile role in gene regulation at the post-transcriptional level. Expression of miRNAs is often deregulated in human cancers. We analyzed small RNA massive parallel sequencing data from 50 locally advanced breast cancers aiming to identify novel breast cancer related miRNAs. We successfully predicted 10 novel miRNAs, out of which 2 (hsa-miR-nov3 and hsa-miR-nov7) were recurrent. Applying high sensitivity qPCR, we detected these two microRNAs in 206 and 214 out of 223 patients in the study from which the initial cohort of 50 samples were drawn. We found hsa-miR-nov3 and hsa-miR-nov7 both to be overexpressed in tumor versus normal breast tissue in a separate set of 13 patients (p = 0.009 and p = 0.016, respectively) from whom both tumor tissue and normal tissue were available. We observed hsa-miR-nov3 to be expressed at higher levels in ER-positive compared to ER-negative tumors (p = 0.037). Further stratifications revealed particularly low levels in the her2-like and basal-like cancers compared to other subtypes (p = 0.009 and 0.040, respectively). We predicted target genes for the 2 microRNAs and identified inversely correlated genes in mRNA expression array data available from 203 out of the 223 patients. Applying the KEGG and GO annotations to target genes revealed pathways essential to cell development, communication and homeostasis. Although a weak association between high expression levels of hsa-miR-nov7 and poor survival was observed, this did not reach statistical significance. hsa-miR-nov3 expression levels had no impact on patient survival.publishedVersio

Polymorphisms in the TP53-MDM2-MDM4-axis in patients with rheumatoid arthritis

Background In addition to being a tumour suppressor, TP53 is a suppressor of inflammation, and dysfunction of this gene has been related to autoimmune diseases. Patients with autoimmunity, such as rheumatoid arthritis (RA) have an increased risk of certain cancers, like lymphomas, indicating that some underlying mechanisms may modulate risk of both cancers and autoimmunity. Methods We genotyped 5 common genetic variants in TP53 and its main regulators MDM2 and MDM4 in a sample of 942 RA patients and 3,747 healthy controls, and mined previously published GWAS-data, to assess the potential impact of these variants on risk of RA. Results For the TP53 Arg72Pro polymorphism (rs1042522), MDM4 SNP34091 (rs4245739) and MDM2 SNP285C (rs117039649), we found no association to risk of RA. For MDM2 SNP309 (rs2279744), the minor G-allele was associated with a reduced risk of RA (OR: 0.87; CI: 0.79–0.97). This association was also seen in genotype models (OR: 0.86; CI: 0.74–0.99 and OR: 0.79; CI 0.63–0.99; dominant and recessive model, respectively), but was not validated in a large GWAS data set. For MDM2 del1518 (rs3730485), the minor del-allele was associated with an increased risk of RA in the dominant model (OR: 1.18; CI: 1.02–1.38). Stratifying RA cases and controls into phylogenetic subgroups according to the combined genotypes of all three MDM2 polymorphism, we found individuals with the del158-285–309 genotype del/ins-G/G-T/T to have an increased risk of RA as compared to those with the ins/ins-G/G-G/G genotype (OR: 1.56; CI: 1.18–2.06) indicating opposite effects of the del1518 del-allele and the SNP309 G-allele. Conclusion We find a potential association between the MDM2 del1518 variant and RA, and indications that combinatorial genotypes and haplotypes in the MDM2 locus may be related to RA.publishedVersio

Expression of full-length p53 and its isoform Δp53 in breast carcinomas in relation to mutation status and clinical parameters

BACKGROUND: The tumor suppressor gene p53 (TP53) controls numerous signaling pathways and is frequently mutated in human cancers. Novel p53 isoforms suggest alternative splicing as a regulatory feature of p53 activity. RESULTS: In this study we have analyzed mRNA expression of both wild-type and mutated p53 and its respective Δp53 isoform in 88 tumor samples from breast cancer in relation to clinical parameters and molecular subgroups. Three-dimensional structure differences for the novel internally deleted p53 isoform Δp53 have been predicted. We confirmed the expression of Δp53 mRNA in tumors using quantitative real-time PCR technique. The mRNA expression levels of the two isoforms were strongly correlated in both wild-type and p53-mutated tumors, with the level of the Δp53 isoform being approximately 1/3 of that of the full-length p53 mRNA. Patients expressing mutated full-length p53 and non-mutated (wild-type) Δp53, "mutational hybrids", showed a slightly higher frequency of patients with distant metastasis at time of diagnosis compared to other patients with p53 mutations, but otherwise did not differ significantly in any other clinical parameter. Interestingly, the p53 wild-type tumors showed a wide range of mRNA expression of both p53 isoforms. Tumors with mRNA expression levels in the upper or lower quartile were significantly associated with grade and molecular subtypes. In tumors with missense or in frame mutations the mRNA expression levels of both isoforms were significantly elevated, and in tumors with nonsense, frame shift or splice mutations the mRNA levels were significantly reduced compared to those expressing wild-type p53. CONCLUSION: Expression of p53 is accompanied by the functionally different isoform Δp53 at the mRNA level in cell lines and human breast tumors. Investigations of "mutational hybrid" patients highlighted that wild-type Δp53 does not compensates for mutated p53, but rather may be associated with a worse prognosis. In tumors, both isoforms show strong correlations in different mutation-dependent mRNA expression patterns

Multilocus analysis of SNP and metabolic data within a given pathway

BACKGROUND: Complex traits, which are under the influence of multiple and possibly interacting genes, have become a subject of new statistical methodological research. One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common multifactorial diseases and their association to different quantitative phenotypic traits. RESULTS: Two types of data from the same metabolic pathway were used in the analysis: categorical measurements of 18 SNPs; and quantitative measurements of plasma levels of several steroids and their precursors. Using the combinatorial partitioning method we tested various thresholds for each metabolic trait and each individual SNP locus. One SNP in CYP19, 3UTR, two SNPs in CYP1B1 (R48G and A119S) and one in CYP1A1 (T461N) were significantly differently distributed between the high and low level metabolic groups. The leave one out cross validation method showed that 6 SNPs in concert make 65% correct prediction of phenotype. Further we used pattern recognition, computing the p-value by Monte Carlo simulation to identify sets of SNPs and physiological characteristics such as age and weight that contribute to a given metabolic level. Since the SNPs detected by both methods reside either in the same gene (CYP1B1) or in 3 different genes in immediate vicinity on chromosome 15 (CYP19, CYP11 and CYP1A1) we investigated the possibility that they form intragenic and intergenic haplotypes, which may jointly account for a higher activity in the pathway. We identified such haplotypes associated with metabolic levels. CONCLUSION: The methods reported here may enable to study multiple low-penetrance genetic factors that together determine various quantitative phenotypic traits. Our preliminary data suggest that several genes coding for proteins involved in a common pathway, that happen to be located on common chromosomal areas and may form intragenic haplotypes, together account for a higher activity of the whole pathway