Genetic Polymorphisms in Vitamin D Metabolism and Signaling Genes and Risk of Breast Cancer: A Nested Case-Control Study

Genetic polymorphisms in vitamin D metabolism and signaling genes have been inconsistently associated with risk of breast cancer, though few studies have examined SNPs in vitamin D-related genes other than the vitamin D receptor (VDR) gene and particularly have not examined the association with the retinoid X receptor alpha (RXRA) gene which may be a key vitamin D pathway gene. We conducted a nested case-control study of 734 cases and 1435 individually matched controls from a population-based prospective cohort study, the Northern Sweden Mammary Screening Cohort. Tag and functional SNPs were genotyped for the VDR, cytochrome p450 24A1 (CYP24A1), and RXRA genes. We also genotyped specific SNPs in four other genes related to vitamin D metabolism and signaling (GC/VDBP, CYP2R1, DHCR7, and CYP27B1). SNPs in the CYP2R1, DHCR7, and VDBP gene regions that were associated with circulating 25(OH)D concentration in GWAS were also associated with plasma 25(OH)D in our study (p-trend <0.005). After taking into account the false discovery rate, these SNPs were not significantly associated with breast cancer risk, nor were any of the other SNPs or haplotypes in VDR, RXRA, and CYP24A1. We observed no statistically significant associations between polymorphisms or haplotypes in key vitamin D-related genes and risk of breast cancer. These results, combined with the observation in this cohort and most other prospective studies of no association of circulating 25(OH)D with breast cancer risk, do not support an association between vitamin D and breast cancer risk.     

Ethnic Features of Genetic Susceptibility to Breast Cancer

The results of screening for BRCA1, BRCA2, ATM, NBN, CHEK2, PALB2, BLM gene mutations in 1000 breast cancer (BC) patients from the Republic of Bashkortostan (RB) are presented. Germline mutations in these genes accounted for 7.5% of breast cancer patients. The wide spectrum of mutations was found in women of Slavic origin, including: c.5266dupC, c.181T>G, and c.4034delA in BRCA1; c.5932G>T in ATM; c.657_661del5 in NBN; c.444+1G>A, c.1100delC, and dele9,10(5kb) in CHEK2; c.509_510delGA and c.172_175delTTGT in PALB2; and c.1642C>T in BLM gene.     

Lack of Association between Genetic Polymorphisms in Enzymes Associated with Folate Metabolism and Unexplained Reduced Sperm Counts

Background

The metabolic pathway of folate is thought to influence DNA stability either by inducing single/double stranded breaks or by producing low levels of S-adenosyl-methionine leading to abnormal gene expression and chromosome segregation. Polymorphisms in the genes encoding enzymes in the folate metabolism pathway show distinct geographic and/or ethnic variations and in some cases have been linked to disease. Notably, the gene Methylenetetrahydrofolate reductase (MTHFR) in which the homozygous (TT) state of the polymorphism c.665C>T (p.A222V) is associated with reduced specific activity and increased thermolability of the enzyme causing mild hyperhomocysteinemia. Recently several studies have suggested that men carrying this polymorphism may be at increased risk to develop infertility.

Methodology/Principal Findings

We have tested this hypothesis in a case/control study of ethnic French individuals. We examined the incidence of polymorphisms in the genes MTHFR (R68Q, A222V and E429A), Methionine synthase reductase MTRR; (I22M and S175L) and Cystathionine beta-synthase (CBS; G307S). The case population consisted of DNA samples from men with unexplained azoospermia (n = 70) or oligozoospermia (n = 182) and the control population consisted of normospermic and fertile men (n = 114). We found no evidence of an association between the incidence of any of these variants and reduced sperm counts. In addition haplotype analysis did not reveal differences between the case and control populations.

Conclusions/Significance

We could find no evidence for an association between reduced sperm counts and polymorphisms in enzymes involved in folate metabolism in the French population.     

AGR3 in Breast Cancer: Prognostic Impact and Suitable Serum-Based Biomarker for Early Cancer Detection

Blood-based early detection of breast cancer has recently gained novel momentum, as liquid biopsy diagnostics is a fast emerging field. In this study, we aimed to identify secreted proteins which are up-regulated both in tumour tissue and serum samples of breast cancer patients compared to normal tissue and sera. Based on two independent tissue cohorts (n = 75 and n = 229) and one serum cohort (n = 80) of human breast cancer and healthy serum samples, we characterised AGR3 as a novel potential biomarker both for breast cancer prognosis and early breast cancer detection from blood. AGR3 expression in breast tumours is significantly associated with oestrogen receptor α (P<0.001) and lower tumour grade (P<0.01). Interestingly, AGR3 protein expression correlates with unfavourable outcome in low (G1) and intermediate (G2) grade breast tumours (multivariate hazard ratio: 2.186, 95% CI: 1.008-4.740, P<0.05) indicating an independent prognostic impact. In sera analysed by ELISA technique, AGR3 protein concentration was significantly (P<0.001) elevated in samples from breast cancer patients (n = 40, mainly low stage tumours) compared to healthy controls (n = 40). To develop a suitable biomarker panel for early breast cancer detection, we measured AGR2 protein in human serum samples in parallel. The combined AGR3/AGR2 biomarker panel achieved a sensitivity of 64.5% and a specificity of 89.5% as shown by receiver operating characteristic (ROC) curve statistics. Thus our data clearly show the potential usability of AGR3 and AGR2 as biomarkers for blood-based early detection of human breast cancer.     

The Sub-Cellular Localization of WRAP53 Has Prognostic Impact in Breast Cancer

WRAP53 protein controls intracellular trafficking of DNA repair proteins, the telomerase enzyme, and splicing factors. Functional loss of the protein has been linked to carcinogenesis, premature aging and neurodegeneration. The aim of this study was to investigate the prognostic significance of WRAP53 protein expression in breast cancer. A tissue microarray was constructed from primary breast tumors and immunostained by a polyclonal WRAP53 antibody to assess the protein expression pattern. Two different patient cohorts with long term follow-up were studied; a test- and a validation set of 154 and 668 breast tumor samples respectively. Breast cancer patients with tumor cells lacking the expression of WRAP53 in the nucleus had a significantly poorer outcome compared to patients with tumor cells expressing this protein in the nuclei (HR = 1.95, 95%CI = 1.09–3.51, p = 0.025). Nuclear localization of WRAP53 was further shown to be an independent marker of prognosis in multivariate analysis (HR = 2.57, 95%CI = 1.27–5.19, p = 0.008), and also significantly associated with better outcome in patients with TP53 mutation. Here we show that the sub-cellular localization of the WRAP53 protein has a significant impact on breast cancer survival, and thus has a potential as a clinical marker in diagnostics and treatment.     

Computer-Based Image Studies on Tumor Nests Mathematical Features of Breast Cancer and Their Clinical Prognostic Value

Background

The expending and invasive features of tumor nests could reflect the malignant biological behaviors of breast invasive ductal carcinoma. Useful information on cancer invasiveness hidden within tumor nests could be extracted and analyzed by computer image processing and big data analysis.

Methods

Tissue microarrays from invasive ductal carcinoma (n = 202) were first stained with cytokeratin by immunohistochemical method to clearly demarcate the tumor nests. Then an expert-aided computer analysis system was developed to study the mathematical and geometrical features of the tumor nests. Computer recognition system and imaging analysis software extracted tumor nests information, and mathematical features of tumor nests were calculated. The relationship between tumor nests mathematical parameters and patients'' 5-year disease free survival was studied.

Results

There were 8 mathematical parameters extracted by expert-aided computer analysis system. Three mathematical parameters (number, circularity and total perimeter) with area under curve >0.5 and 4 mathematical parameters (average area, average perimeter, total area/total perimeter, average (area/perimeter)) with area under curve <0.5 in ROC analysis were combined into integrated parameter 1 and integrated parameter 2, respectively. Multivariate analysis showed that integrated parameter 1 (P = 0.040) was independent prognostic factor of patients'' 5-year disease free survival. The hazard risk ratio of integrated parameter 1 was 1.454 (HR 95% CI [1.017–2.078]), higher than that of N stage (HR 1.396, 95% CI [1.125–1.733]) and hormone receptor status (HR 0.575, 95% CI [0.353–0.936]), but lower than that of histological grading (HR 3.370, 95% CI [1.125–5.364]) and T stage (HR 1.610, 95% CI [1.026 –2.527]).

Conclusions

This study indicated integrated parameter 1 of mathematical features (number, circularity and total perimeter) of tumor nests could be a useful parameter to predict the prognosis of early stage breast invasive ductal carcinoma.     

花生四烯酸代谢相关酶和ERK与乳腺癌转移关系

花生四烯酸代谢相关酶环加氧酶(COX)、脂氧合酶(LOX)和活化的胞外信号调节激酶（p-ERK1/2）等与乳腺癌发生发展具有密切关系.为了进一步阐明它们在乳腺癌转移中的作用及其分子机制,应用反转录PCR（RT-PCR）、免疫印迹和免疫组化等方法,分别检测了乳腺癌细胞系、乳腺癌组织、癌旁组织和转移淋巴结组织中COX-2、5-LOX、12R-LOX、cPLA2和p-ERK1/2的表达水平.结果显示,与对照组相比,在具有高转移潜能的乳腺癌LM MCF-7细胞和MDA-MB-231细胞以及转移淋巴结组织中,COX-2、5-LOX、12R-LOX、cPLA2和p-ERK1/2均有较高水平表达.进而发现,p-ERK1/2的特异性抑制剂PD98059可拮抗LM-MCF-7细胞和MDA-MB-231细胞中COX-2、5-LOX、12R-LOX和cPLA2的高表达.上述结果表明,p-ERK1/2可以通过促进花生四烯酸代谢相关酶的表达促进乳腺癌细胞发生转移.     

指长比与乳腺癌的相关性研究

本文研究了宁夏汉族女性256例(正常对照:128例,乳腺癌患者:128例)左右手指长比(2D∶3D、2D∶4D、2D∶5D、3D∶4D、3D∶5D、4D∶5D),比较其均值的差异性;分析了指长比与年龄间的关系。结果表明:1)宁夏汉族正常女性与乳腺癌患者组指长比均值呈现2D∶3D<2D∶4D<3D∶4D<2D∶5D<4D∶5D<3D∶5D的趋势;2)乳腺癌患者组指长比均值均高于正常对照组,2D∶3D(P<0.05)、2D∶4D(P<0.01)、2D∶5D(左手P4D的比例高于对照组;3)乳腺癌患者组指长比均值与发病年龄呈高度负相关(P<0.001)。     

Study of Integrated Heterogeneous Data Reveals Prognostic Power of Gene Expression for Breast Cancer Survival

BackgroundStudies show that thousands of genes are associated with prognosis of breast cancer. Towards utilizing available genetic data, efforts have been made to predict outcomes using gene expression data, and a number of commercial products have been developed. These products have the following shortcomings: 1) They use the Cox model for prediction. However, the RSF model has been shown to significantly outperform the Cox model. 2) Testing was not done to see if a complete set of clinical predictors could predict as well as the gene expression signatures.Methodology/FindingsWe address these shortcomings. The METABRIC data set concerns 1981 breast cancer tumors. Features include 21 clinical features, expression levels for 16,384 genes, and survival. We compare the survival prediction performance of the Cox model and the RSF model using the clinical data and the gene expression data to their performance using only the clinical data. We obtain significantly better results when we used both clinical data and gene expression data for 5 year, 10 year, and 15 year survival prediction. When we replace the gene expression data by PAM50 subtype, our results are significant only for 5 year and 15 year prediction. We obtain significantly better results using the RSF model over the Cox model. Finally, our results indicate that gene expression data alone may predict long-term survival.Conclusions/SignificanceOur results indicate that we can obtain improved survival prediction using clinical data and gene expression data compared to prediction using only clinical data. We further conclude that we can obtain improved survival prediction using the RSF model instead of the Cox model. These results are significant because by incorporating more gene expression data with clinical features and using the RSF model, we could develop decision support systems that better utilize heterogeneous information to improve outcome prediction and decision making.     

PYCARD基因在乳腺癌的表达情况及预后分析

乳腺癌是全球女性最常见的恶性肿瘤,准确的早期诊断和预后生物标志物可以提高治疗的效率.细胞凋亡相关的斑点样蛋白(apoptosis-associated specklike protein,ASC)是一种衔接蛋白,在肿瘤发生中有重要的作用.为了进一步探究ASC的作用机制,通过分析ASC蛋白的编码基因PYCARD在Oncomine数据库mRNA表达情况,MethHC数据库分析甲基化水平,bc-GenExMiner v4.3分析PYCARD在不同乳腺癌类型中的表达情况,再利用PrognoScan数据库分析PYCARD与乳腺癌患者预后的关系,并发现PYCARD基因在乳腺癌中8例高表达,癌症组织中PYCARD的甲基化水平比正常组织显著升高,乳腺癌患者PYCRAD基因与临床病理参数有关系.预后结果分析发现PYCARD mRNA高表达患者在总生存期(overall survival,OS)、无远处转移生存率(distant metastasis free survival,DMFS)、和无复发生存期存活率(relapse free survival,RFS)上高于低表达患者.PYCARD基因在乳腺癌高表达,而预后结果又显示高表达患者的存活率高于低表达,这很有可能与PYCARD基因甲基化水平有关.本研究在指导乳腺癌治疗和评估预后方面具有一定临床意义.     

Immunoexpression Analysis and Prognostic Value of BLCAP in Breast Cancer

Bladder Cancer Associated Protein (BLCAP, formerly Bc10), was identified by our laboratory as being down-regulated in bladder cancer with progression. BLCAP is ubiquitously expressed in different tissues, and several studies have found differential expression of BLCAP in various cancer types, such as cervical and renal cancer, as well as human tongue carcinoma and osteosarcoma. Here we report the first study of the expression patterns of BLCAP in breast tissue. We analyzed by immunohistochemistry tissue sections of normal and malignant specimens collected from 123 clinical high-risk breast cancer patients within the Danish Center for Translational Breast Cancer Research (DCTB) prospective study dataset. The staining pattern, the distribution of the immunostaining, and its intensity were studied in detail. We observed weak immunoreactivity for BLCAP in mammary epithelial cells, almost exclusively localizing to the cytoplasm and found that levels of expression of BLCAP were generally higher in malignant cells as compared to normal cells. Quantitative IHC analysis of BLCAP expression in breast tissues confirmed this differential BLCAP expression in tumor cells, and we could establish, in a 62-patient sample matched cohort, that immunostaining intensity for BLCAP was increased in tumors relative to normal tissue, in more than 45% of the cases examined, indicating that BLCAP may be of value as a marker for breast cancer. We also analyzed BLCAP expression and prognostic value using a set of tissue microarrays comprising an independent cohort of 2,197 breast cancer patients for which we had follow-up clinical information.     

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective

To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI).

Method

To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model.

Results

Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen.

Conclusions

The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.     

Associations of ATR and CHEK1 Single Nucleotide Polymorphisms with Breast Cancer

DNA damage and replication checkpoints mediated by the ATR-CHEK1 pathway are key to the maintenance of genome stability, and both ATR and CHEK1 have been proposed as potential breast cancer susceptibility genes. Many novel variants recently identified by the large resequencing projects have not yet been thoroughly tested in genome-wide association studies for breast cancer susceptibility. We therefore used a tagging SNP (tagSNP) approach based on recent SNP data available from the 1000 genomes projects, to investigate the roles of ATR and CHEK1 in breast cancer risk and survival. ATR and CHEK1 tagSNPs were genotyped in the Sheffield Breast Cancer Study (SBCS; 1011 cases and 1024 controls) using Illumina GoldenGate assays. Untyped SNPs were imputed using IMPUTE2, and associations between genotype and breast cancer risk and survival were evaluated using logistic and Cox proportional hazard regression models respectively on a per allele basis. Significant associations were further examined in a meta-analysis of published data or confirmed in the Utah Breast Cancer Study (UBCS). The most significant associations for breast cancer risk in SBCS came from rs6805118 in ATR (p=7.6x10^-5) and rs2155388 in CHEK1 (p=3.1x10^-6), but neither remained significant after meta-analysis with other studies. However, meta-analysis of published data revealed a weak association between the ATR SNP rs1802904 (minor allele frequency is 12%) and breast cancer risk, with a summary odds ratio (confidence interval) of 0.90 (0.83-0.98) [p=0.0185] for the minor allele. Further replication of this SNP in larger studies is warranted since it is located in the target region of 2 microRNAs. No evidence of any survival effects of ATR or CHEK1 SNPs were identified. We conclude that common alleles of ATR and CHEK1 are not implicated in breast cancer risk or survival, but we cannot exclude effects of rare alleles and of common alleles with very small effect sizes.     

肿瘤生长的能量代谢特点及其临床应用

肿瘤细胞与人体正常细胞在代谢上有些不同,这主要体现在能量代谢和物质代谢上。肿瘤细胞能量代谢的特点表现在活跃地摄取葡萄糖和谷胺酰胺,进行有氧糖酵解(Warburg效应)。这种看上去很不经济的能量供给方式对肿瘤细胞却是必需的,它既为肿瘤细胞的不断生长提供能量,也为它们提供了生物合成的原料。肿瘤不同的代谢方式既是挑战也是机遇,弄清肿瘤细胞的代谢机制,对肿瘤早期诊断和靶向治疗具有重要意义。     

MiR-27 as a Prognostic Marker for Breast Cancer Progression and Patient Survival

Background

MicroRNA-27a (miR-27a) is thought to be an onco-microRNA that promotes tumor growth and metastasis by downregulating ZBTB10. The potential predictive value of miR-27a was studied in breast cancer patients.

Methods

The expression of miR-27a and ZBTB10 was examined in 102 breast cancer cases using in situ hybridization (ISH) and immunohistochemistry techniques and were evaluated semi-quantitatively by examining the staining index. The Correlation of miR-27a and ZBTB10 expression was analyed by Spearman Rank Correlation. The association of miR-27a and ZBTB10 expression with clinicopathological characteristics was analyzed using the χ² test, and their effects on patient survival were analyzed by a log-rank test and the Kaplan-Meier method. Univariate and multivariate Cox regression analyses were used to evaluate the prognostic values of miR-27a and ZBTB10.

Results

miR-27a was markedly up-regulated in invasive breast cancers that expressed low levels of ZBTB10 (P<0.001). A reverse correlation between miR-27a and ZBTB10 was also observed in breast cancer tissue samples (r_s = −0.478, P<0.001). Furthermore, the expression of miR-27a and ZBTB10 was significantly correlated with clinicopathological parameters, including tumor size, lymph node metastasis and distant metastasis (P<0.05), but not with receptor status. Patients with high miR-27a or low ZBTB10 expression tended to have significantly shorter disease-free survival times (57 months and 53 months, respectively, P <0.001) and overall survival times (58 months and 55 months, respectively, P <0.001). Univariate and multivariate analysis showed that both miR-27a and ZBTB10 were independent prognostic factors of disease-free survival in breast cancer patients (P <0.001), while only miR-27a was an independent predictor of overall survival (P <0.001).

Conclusions

High miR-27a expression is associated with poor overall survival in patients with breast cancer, which suggests that miR-27a could be a valuable marker of breast cancer progression.     

中国湖南人群GSTM1和GSTT1基因多态性与肺癌易感性关系的研究

应用病例-对照分析研究(对照组205例,肺癌病例组104例),抽提静脉血基因组DNA,采用PCR及多重PCR方法,检测谷胱甘肽转移酶GSTM1和GSTT1单独及联合缺失基因型的遗传多态性在中国湖南人群中肺癌患者和正常人群体中的分布,探讨这些多态性基因型与肺癌易感性的关系.结果显示GSTM1-/-基因型在湖南地区居民肺癌群体和正常对照人群中的频率分别为62.5%和46.3%(P<0.05);肺癌患者组GSTT1-/-基因型的频率(66.3%)显著高于正常对照组(42.4%)(P<0.05).GSTM1-/-和GSTT1-/-联合基因型在肺癌组和正常对照组中的频率分别为41.3%和22.4%(P<0.05).SPSS11.5软件统计学分析表明,这些基因型在肺癌患者组和正常对照组人群中的发生频率具有显著性差异.由此可知GSTM1基因缺失和GSTT1基因缺失分别与肺癌的易感性相关;GSTM1和GSTT1基因联合缺失与肺癌的发生和发展呈现显著正相关.     

Association of Genetic Polymorphisms in CDH1 and CTNNB1 with Breast Cancer Susceptibility and Patients' Prognosis among Chinese Han Women

This study aims to investigate whether the germline variants in CDH1 and CTNNB1 would affect breast cancer susceptibility and patients’ prognosis among Chinese Han women using a haplotype-based association analysis. We genotyped 12 haplotype-tagging single nucleotide polymorphisms (htSNPs) in CDH1 and CTNNB1 among 1,160 BC cases and 1,336 age-matched cancer-free controls using the TaqMan^® Genotyping Assay. For association analyses of germline variants with breast cancer susceptibility, the results showed that rs7200690, rs7198799, rs17715799, rs13689 and diplotype CGC/TGC (rs7200690 + rs12185157 + rs7198799) in CDH1 as well as rs2293303 in CTNNB1 were associated with increased breast cancer risk. In addition, the Generalized Multifactor Dimensionality Reduction (GMDR) and logistic regression analysis predicted an interaction on breast cancer risk between rs17715799 and rs13689 as well as rs13689 and menarche-FFTP (First Full-Term Pregnancy) interval. For survival analyses, the results demonstrated that the minor allele homozygotes of rs13689 and haplotype TGC in CDH1 were linked with unfavorable event-free survival of breast cancer, whereas, rs4783689 of CDH1 showed the opposite effect under dominant model. Notably, the stratified analysis revealed that rs7186053 was associated with favorable event-free survival among patients with estrogen receptor (ER)-positive, progesterone receptor (PR)-positive or lymph node metastasis negative patients. Moreover, rs7200690 and rs7198799 in CDH1 as well as rs4533622 in CTNNB1 were associated with worse event-free survival among patients with clinical stage 0-I tumors. This study indicated that the genetic polymorphisms of CDH1 and CTNNB1 were associated with breast cancer susceptibility and patients’ prognosis.     

Computational and Structural Investigation of Deleterious Functional SNPs in Breast Cancer BRCA2 Gene

In this work, we have analyzed the genetic variation that can alter the expression and the function in BRCA2 gene using computational methods. Out of the total 534 SNPs, 101 were found to be non synonymous (nsSNPs). Among the 7 SNPs in the untranslated region, 3 SNPs were found in 5′ and 4 SNPs were found in 3′ un-translated regions (UTR). Of the nsSNPs 20.7% were found to be damaging by both SIFT and PolyPhen server among the 101 nsSNPs investigated. UTR resource tool suggested that 2 SNPs in the 5′ UTR region and 4 SNPs in the 3′ UTR regions might change the protein expression levels. The mutation from asparagine to isoleucine at the position 3124 of the native protein of BRCA2 gene was most deleterious by both SIFT and PolyPhen servers. A structural analysis of this mutated protein and the native protein was made which had an RMSD value of 0.301 nm. Based on this work, we proposed that this most deleterious nsSNP with an SNPid rs28897759 is an important candidate for the cause of breast cancer by BRCA2 gene.