Gender-associated expression of tumor markers and a small gene set in breast carcinoma

Differential expression of NAT1 pharmacogene in hormone receptor positive vs. negative female breast tumors may affect drug treatment

Studies have reported overexpression of NAT1 gene for xenobiotic metabolizing arylamine N-acetyltransferase type 1 in estrogen receptor positive breast tumors, and this association has been linked to patient chemoresistance and response to tamoxifen. We probed the expression of NAT1, using quantitative reverse transcription PCR to screen clinically characterized breast cancer tissue cDNA arrays. Primers detecting all NAT1 alternative transcripts were used, and the protocol and results are reported according to consensus guidelines. The clinical information about 166 tumor samples screened is provided, including tumor stage, estrogen and progesterone receptor status and HER2 expression. NAT1 was found to be significantly (P < 0.001) upregulated in hormone receptor positive vs. negative tumors. No correlation was apparent between NAT1 and tumor stage or HER2 expression. Our findings demonstrate a strong correlation between the expression of NAT1 and steroid hormone receptors in breast tumors, supporting its possible utility as a pharmacogenetic biomarker or drug target. Of the two polymorphic NAT genes, NAT1 is the one primarily expressed in breast tissue, and is subjected to regulation by two differential promoters and more than one polyadenylation signal. Hormonal factors may enhance NAT1 gene expression at the transcriptional or epigenetic level, and tamoxifen has additionally been shown to inhibit NAT1 enzymatic activity. The outcome of tamoxifen treatment is also more favorable in patients with NAT1 overexpressing tumors. The study adds to the growing body of evidence implicating NAT1 in breast cancer and its pharmacological treatment.

Trichorhinophalangeal syndrome type 1 (TRPS1) expression in male breast carcinoma

Currently, there is a paucity of highly specific and sensitive markers to identify breast carcinoma in male patients. Immunohistochemical stains commonly used for unmasking primary breast carcinomas include estrogen receptor (ER) and GATA3. However, these markers are commonly expressed in carcinomas originating from other organ systems and can be reduced in breast carcinomas with higher histologic grades. Androgen receptor (AR) may be used to highlight primary male breast cancer, but this marker can also be expressed in other carcinomas. We evaluated TRPS1, a highly sensitive and specific marker for female breast carcinoma, in cases of male breast carcinoma. Through an institutional database search, we identified 72 cases of primary invasive breast carcinoma in male patients. Among ER/progesterone receptor (PR)-positive cancers, 97% showed intermediate or high positivity for both TRPS1 and GATA3. Among HER2-positive cancers, 100% showed intermediate or high positivity for TRPS1 and GATA3. One case of triple-negative breast cancer was collected, showing high positivity for TRPS1 and negativity for GATA3. AR staining was non-specific and heterogeneous: 76% showed high positivity, but the remaining 24% showed low or intermediate positivity. Additionally, among 29 cases of metastatic carcinoma to male breast tissue, 93% were negative for TRPS1, and the remaining 2 cases (7%), which were carcinomas from salivary gland primary tumors, were intermediate positive. TRPS1 is a sensitive and specific marker in the unmasking of male primary invasive breast carcinoma across different subtypes. Additionally, TRPS1 is not expressed in metastatic carcinomas of multiple primaries, with the exception of salivary gland primaries.

The Signal Transducer IL6ST (gp130) as a Predictive and Prognostic Biomarker in Breast Cancer

Novel biomarkers are needed to continue to improve breast cancer clinical management and outcome. IL6-like cytokines, whose pleiotropic functions include roles in many hallmarks of malignancy, rely on the signal transducer IL6ST (gp130) for all their signalling. To date, 10 separate independent studies based on the analysis of clinical breast cancer samples have identified IL6ST as a predictor. Consistent findings suggest that IL6ST is a positive prognostic factor and is associated with ER status. Interestingly, these studies include 4 multigene signatures (EndoPredict, EER4, IRSN-23 and 42GC) that incorporate IL6ST to predict risk of recurrence or outcome from endocrine or chemotherapy. Here we review the existing evidence on the promising predictive and prognostic value of IL6ST. We also discuss how this potential could be further translated into clinical practice beyond the EndoPredict tool, which is already available in the clinic. The most promising route to further exploit IL6ST's promising predicting power will likely be through additional hybrid multifactor signatures that allow for more robust stratification of ER+ breast tumours into discrete groups with distinct outcomes, thus enabling greater refinement of the treatment-selection process.

Regulatory Interplay between miR-181a-5p and Estrogen Receptor Signaling Cascade in Breast Cancer

Simple Summary

Despite huge efforts in breast cancer care programs, patient’s survival rates greatly vary. Differences in response to therapy still represent the major challenge for clinicians and biologists. Define new anticancer mechanisms and innovative predictors for resistance could be a valid strategy to permanently defeat breast cancer. Here we propose the epigenetic based reprogramming of breast cancer, which leverages on the crosstalk between miR-181a-5p and Estrogen Receptor α. This simultaneously approach allows to induce miR-181a-5p and reduce the receptor expression, blocking the estrogen-dependent proliferative pathway underlying breast cancer progression. Since the epigenetic approach insists on transcriptional regulation, it is mostly independent of the acquired resistance mechanisms typically induced by prolonged endocrine therapy and therefore can be used as a sensitizer, neoadjuvant, or in combination with the standard in care treatments against breast cancer.

Abstract

The efficacy and side effects of endocrine therapy in breast cancer (BC) depend largely on estrogen receptor alpha (ERα) expression, the specific drug administered, and treatment scheduling. Although the benefits of endocrine therapy outweigh any adverse effects in the initial stages of BC, later- or advanced-stage tumors acquire resistance to treatments. The mechanisms underlying tumor resistance to therapy are still not well understood, posing a major challenge for BC patient care. Epigenetic regulation and miRNA expression may be involved in the switch from a treatment-sensitive to a treatment-resistant state and could provide a valid therapeutic strategy for ERα negative BC. Here, a hybrid lysine-specific histone demethylase inhibitor, MC3324, displaying selective estrogen receptor down-regulator-like activities in BC, was used to highlight the interplay between epigenetic and ERα signaling. MC3324 anticancer action is mediated by microRNA (miRNA) expression regulation, indicating an innovative function for this molecule. Integrated analysis suggests a crosstalk between estrogen signaling, ERα interactors, miRNAs, and their putative targets. Specifically, miR-181a-5p expression is regulated by MC3324 and has an impact on cellular levels of ERα. A comparison of breast tumor versus healthy mammary tissues confirmed the important role of miR-181a-5p in ERα regulation and points to its putative predictive function in BC therapy.

DOKI: Domain knowledge-driven inference method for reverse-engineering transcriptional regulatory relationships among genes in cancer

Efficient reverse-engineering methods are important for identifying transcriptional regulatory relationships among genes in cancer. These methods are becoming increasingly useful in this era where huge volumes of data are generated through the use of high-throughput technologies such as next-generation sequencing technologies and microarrays. However, it is important to improve current methods because of complications involved in modelling complex biological systems. In this paper, we present a novel approach, Domain Knowledge-driven Inference (DOKI), for identification of transcriptional regulatory relationships among genes, given a biological context such as cancer. Combining data normalization, the use of a probability distribution function and Kullback-Leibler Divergence, DOKI incorporates a domain knowledge-driven criterion to make determinations of the existence of regulatory relationships between given transcription factors and given specific gene targets. Characteristics of DOKI enable it to adequately handle complexities inherent in data, and accurately unearth linear and higher-order dependent relationships among genes. DOKI performed equally well with one established high-performing method and better than three other high-performing methods on relatively small data sets. However, it remarkably outperformed these methods on larger data sets to demonstrate its utility. Furthermore, we demonstrate the relevance of such inference algorithms for identifying novel relationships among genes in breast cancer, as some of the consensus results representing novel relationships were confirmed in previously published experimental results. Thus, DOKI will facilitate current efforts to gain etiological insights and help uncover new targeted therapies for various diseases.

MICA-129 Met/Val polymorphism could be a genetic biomarker for Familial Breast Cancer in the Tunisian population

Identification of candidate genes associated with susceptibility of breast cancer can have a significant impact at a cancer management national healthcare systems level, making genetic testing more affordable and cost-effective. We have previously shown that the major histocompatibility complex class I-related chain A (MICA) was related to breast cancer and plays an important role in modulating immune response mechanisms through NKG2D receptor activation. Compared to our previous study, in this work, we recruited a new cohort composed of 354 unrelated Tunisian women affected by breast cancer and 380 age-matched women as controls, all genotyped for MICA-129 Met/Val (rs 1051792). Subsequently, we exanimated the distribution of this polymorphism in ten families. As a result, an association was found between the Val allele and Val/Val genotype and the risk of breast cancer (p = 2.5 × 10^-15 ; OR = 2.40; p = 6.5 × 10^-13 ; OR = 3.03, respectively). Stratified analysis with age and family history of cancer revealed an association between the Val/Val genotype and younger patients <40 years (p = .003; OR = 2.03). Among those patients having a family history of cancer, 68% had a Val/Val genotype (p = .02; OR = 1.82). In the family study, an analyse of pedigrees revealed that the majority of families showed the development of breast cancer at a young age. Moreover, all patients diagnosed with early-onset breast cancer had a Val/Val genotype. Our results lead us to propose that this polymorphism may be an inherited genetic biomarker contributing to an increased breast cancer risk in Tunisian women.

Population variability of rhesus macaque (Macaca mulatta) NAT1 gene for arylamine N-acetyltransferase 1: Functional effects and comparison with human

Human NAT1 gene for N-acetyltransferase 1 modulates xenobiotic metabolism of arylamine drugs and mutagens. Beyond pharmacogenetics, NAT1 is also relevant to breast cancer. The population history of human NAT1 suggests evolution through purifying selection, but it is unclear whether this pattern is evident in other primate lineages where population studies are scarce. We report NAT1 polymorphism in 25 rhesus macaques (Macaca mulatta) and describe the haplotypic and functional characteristics of 12 variants. Seven non-synonymous single nucleotide variations (SNVs) were identified and experimentally demonstrated to compromise enzyme function, mainly through destabilization of NAT1 protein and consequent activity loss. One non-synonymous SNV (c.560G > A, p.Arg187Gln) has also been characterized for human NAT1 with similar effects. Population haplotypic and functional variability of rhesus NAT1 was considerably higher than previously reported for its human orthologue, suggesting different environmental pressures in the two lineages. Known functional elements downstream of human NAT1 were also differentiated in rhesus macaque and other primates. Xenobiotic metabolizing enzymes play roles beyond mere protection from exogenous chemicals. Therefore, any link to disease, particularly carcinogenesis, may be via modulation of xenobiotic mutagenicity or more subtle interference with cell physiology. Comparative analyses add the evolutionary dimension to such investigations, assessing functional conservation/diversification among primates.

Esophageal Cancer: Should Gender Be Considered as an Influential Factor for Patient Safety in Drug Treatment?

Aim

Analyze the gender difference of esophageal cancer patients in response to drug treatment.

Methods

All publications on clinical trials were collected from PubMed, Scopus, and PMC. Each publication was examined to determine whether the publication is a clinical trial and whether data on gender difference were reported.

Results

Selected from a total of 191 publications, data from 7 trials with a total of 2041 patients were evaluated for gender differences. These clinical trials involve different drugs and disease phenotype. A significant difference was obtained between male and female groups from Student's t-test. There is no conclusive result on age, ethnicity, tumor size, and drug influence.

Conclusions

Gender difference in response to treatment potentially most likely exists in esophageal cancer patients, regardless of age, race, and drugs.

BRCA1/BRCA2 Mutations Shaped by Ancient Consanguinity Practice in Southern Mediterranean Populations

The aim of this study is to investigate the involvement of consanguinity on BRCA1/2 mutation incidence in Southern Mediterranean populations and to confirm their low penetrance by comparison of their recurrence in sporadic and familial breast cancer in a context of ancient consanguinity practice. Our study comprises of two parts: First, a comparison of the consanguinity rates of the South Mediterranean countries in a relationship with the frequency of BRCA1 deleterious mutations in breast cancer families and the recurrence of these mutations. Second, we investigated 23patients with a family history of breast cancer, 51 patients without a family history of breast cancer using next-generation sequencing of BRCA2 and then confirmed by Sanger sequencing for the novel mutation. As results, we clearly show a strong relationship between the frequency of BRCA1 deleterious mutations in breast cancer families and rate of consanguinity, since they are significantly inversely correlated. Four deleterious mutations were found in BRCA2 gene including a novel frame-shift mutationc.9382_9383dup in a patient with familial breast cancer and three other frame-shift mutations c.6591_6592del, c.1310_1313del and c.7654dup in patients with sporadic breast cancer.These results are discussed in a context of selective pressure of ancient consanguinity practice. In conclusion, the study of BRCA1/2 gene in Southern Mediterranean countries revealed low penetrance recurrent mutations in sporadic and familial breast cancer. These mutations have been selected in a context of ancient consanguinity practice along with protective genetic and environmental factors.

Trimodal distribution of arylamine N-acetyltransferase 1 mRNA in breast cancer tumors: association with overall survival and drug resistance

BACKGROUND

Arylamine N-acetyltransferase 1 (NAT1) is a drug metabolizing enzyme that has been associated with cancer cell proliferation in vitro and with survival in vivo. NAT1 expression has been associated with the estrogen receptor and it has been proposed as a prognostic marker for estrogen receptor positive cancers. However, little is known about the distribution of NAT1 mRNA across an entire patient population or its effects on outcomes. To address this, gene expression data from breast cancer patient cohorts were investigated to identify sub-populations based on the level of NAT1 expression. Patient survival and drug response was examined to determine whether NAT1 mRNA levels influenced any of these parameters.

RESULTS

NAT1 expression showed a trimodal distribution in breast cancer samples (n = 1980) but not in tumor tissue from ovarian, prostate, cervical or colorectal cancers. In breast cancer, NAT1 mRNA in each sub-population correlated with a separate set of genes suggesting different mechanisms of NAT1 gene regulation. Kaplan-Meier plots showed significantly better survival in patients with highest NAT1 mRNA compared to those with intermediate or low expression. While NAT1 expression was elevated in estrogen receptor-positive patients, it did not appear to be dependent on estrogen receptor expression. Overall survival was analyzed in patients receiving no treatment, hormone therapy or chemotherapy. NAT1 expression correlated strongly with survival in the first 5 years in those patients receiving chemotherapy but did not influence survival in the other two groups. This suggests that low NAT1 expression is associated with chemo-resistance. The sensitivity of NAT1 mRNA levels as a single parameter to identify non-responders to chemotherapy was 0.58 at a log(2) < 6.5.

CONCLUSIONS

NAT1 mRNA can be used to segregate breast cancer patients into sub-populations that demonstrate different overall survival. Moreover, low NAT1 expression shows a distinct poor response to chemotherapy. Analysis of NAT1 expression may be useful for identifying specific individuals who would benefit from alternative therapy or drug combinations. However, additional information is required to increase the sensitivity of identifying non-responders.

Characterisation of male breast cancer: a descriptive biomarker study from a large patient series

Male breast cancer (MBC) is rare. We assembled 446 MBCs on tissue microarrays and assessed clinicopathological information, together with data from 15 published studies, totalling 1984 cases. By immunohistochemistry we investigated 14 biomarkers (ERα, ERβ1, ERβ2, ERβ5, PR, AR, Bcl-2, HER2, p53, E-cadherin, Ki67, survivin, prolactin, FOXA1) for survival impact. The main histological subtype in our cohort and combined analyses was ductal (81%, 83%), grade 2; (40%, 44%), respectively. Cases were predominantly ERα (84%, 82%) and PR positive (74%, 71%), respectively, with HER2 expression being infrequent (2%, 10%), respectively. In our cohort, advanced age (>67) was the strongest predictor of overall (OS) and disease free survival (DFS) (p = 0.00001; p = 0.01, respectively). Node positivity negatively impacted DFS (p = 0.04). FOXA1 p = 0.005) and AR p = 0.009) were both positively prognostic for DFS, remaining upon multivariate analysis. Network analysis showed ERα, AR and FOXA1 significantly correlated. In summary, the principle phenotype of MBC was luminal A, ductal, grade 2. In ERα+ MBC, only AR had prognostic significance, suggesting AR blockade could be employed therapeutically.

MINT: a multivariate integrative method to identify reproducible molecular signatures across independent experiments and platforms

Background

Molecular signatures identified from high-throughput transcriptomic studies often have poor reliability and fail to reproduce across studies. One solution is to combine independent studies into a single integrative analysis, additionally increasing sample size. However, the different protocols and technological platforms across transcriptomic studies produce unwanted systematic variation that strongly confounds the integrative analysis results. When studies aim to discriminate an outcome of interest, the common approach is a sequential two-step procedure; unwanted systematic variation removal techniques are applied prior to classification methods.

Results

To limit the risk of overfitting and over-optimistic results of a two-step procedure, we developed a novel multivariate integration method, MINT, that simultaneously accounts for unwanted systematic variation and identifies predictive gene signatures with greater reproducibility and accuracy. In two biological examples on the classification of three human cell types and four subtypes of breast cancer, we combined high-dimensional microarray and RNA-seq data sets and MINT identified highly reproducible and relevant gene signatures predictive of a given phenotype. MINT led to superior classification and prediction accuracy compared to the existing sequential two-step procedures.

Conclusions

MINT is a powerful approach and the first of its kind to solve the integrative classification framework in a single step by combining multiple independent studies. MINT is computationally fast as part of the mixOmics R CRAN package, available at http://www.mixOmics.org/mixMINT/and http://cran.r-project.org/web/packages/mixOmics/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1553-8) contains supplementary material, which is available to authorized users.

Genome-wide detection of allelic genetic variation to predict biochemical recurrence after radical prostatectomy among prostate cancer patients using an exome SNP chip

PURPOSES

Genetic variations among prostate cancer patients who underwent radical prostatectomies were evaluated to predict biochemical recurrence, and used to develop a clinical-genetic model that combines data on clinicopathological factors of prostate cancer and individual genetic variations.

MATERIALS AND METHODS

We genotyped 242,186 SNPs on a custom HumanExome BeadChip v1.0 (Illuminam Inc.) from the blood DNA of 776 PCa patients who underwent radical prostatectomy. Genetic data were analyzed to calculate an odds ratio as an estimate of the relative risk of biochemical recurrence. And we compared accuracies from the multivariate model incorporating clinicopathological factors between included and excluded selected lead single nucleotide polymorphisms. Biochemical recurrence-free survival outcomes also analyzed using these genetic variations.

RESULTS

Genetic array analysis indicated that eight single nucleotide polymorphisms (rs77080351, rs200944490, rs2071292, rs117237810, rs191118242, rs4965121, rs61742396, and rs6573513) were significant to predict biochemical recurrence after radical prostatectomy. When a multivariate model incorporating clinicopathological factors was devised to predict biochemical recurrence, the predictive accuracy of model was 85.1 %. By adding in two individual variations of single nucleotide polymorphisms in the multivariate model, the predictive accuracy increased to 87.7 % (P = 0.045). With three variations of single nucleotide polymorphisms, the predictive accuracy further improved to 89.0 % (P = 0.025). These genetic variations had a significantly decreased biochemical recurrence-free survival rate.

CONCLUSIONS

Based on exome array, the selected single nucleotide polymorphisms were predictors for biochemical recurrence. The addition of individualized genetic information effectively enhanced the predictive accuracy of biochemical recurrence among prostate cancer patients who underwent radical prostatectomy.

The link between Parkinson's disease and breast and prostate cancers: A meta-analysis

PURPOSE

Clinical observations have shown an increased morbidity for breast cancer or prostate cancer in patients with Parkinson's disease (PD), however, other reports have noted contradictory results. This pooled analysis was utilized to test whether PD is associated with the risk of breast or prostate cancer.

METHODS

We searched PubMed, Embase and Cochrane library and conducted a meta-analysis to clarify the correlation of PD with breast and/or prostate cancer risk. We identified 16 eligible articles from which odds ratios with 95% confident intervals were assessed as main measures in the pooled estimation. Subgroup analyses and cumulative meta-analysis were also performed.

RESULTS

Our results showed no PD risk associated with breast or prostate cancer in the overall population, which was supported by the results of cumulative meta-analyses. The subgroup analyses suggested no significant risk of breast or prostate cancer in patients with PD within relevant subsets, i.e. gender, ethnicity, PD diagnosis time or study design. No evidence of publication bias was observed across the involved studies.

CONCLUSIONS

This meta-analysis indicates a lack of association between PD and risk of breast or prostate cancer.