Marker Of Prognosis In Breast Cancer Research Articles

Down Regulation in Glutathione S-Transferase Stimulate Oxidative Stress and Genetic Susceptibility of Human Breast Cancer

Glutathione S-Transferase is an enzyme that catalyzed the formation of thio-ether conjugates between the endogenous tripeptide glutathione and xenobiotic compounds. Imbalance of glutathione level is observed in a variety of disease including breast cancer. In the present study we observed the alteration in the glutathione level and variation in glutathione S-transferase enzyme supergene family to influence susceptibility to breast cancer disease. Our study include 50 breast cancer tissues sample along with 25 ANCT control. The experiments were performed through high performance liquid chromatography to determine the endogenous glutathione level and multiplex PCR was used to determine GSTM1 & GSTT1 genotypes. The relationship between breast cancer and disease progression and histological grade were estimated by one way ANOVA and descriptive statisctics followed by spearman correlation {S.D±SEM, 95% CI (P<0.05)}. The study show decreased level of glutathione (GSHt P<0.05, GSH, GSSG P>0.05) in breast cancer tissue sample when compared to control, while no significance difference was occurred in GST (P>0.05) concentration when compared to control. In addition significance difference was observed when correlated histological grades {(grade II P<0.05) gradeII & III P>0.05)} with control subjects. We therefore, also investigated the role of GST genotypes to associate the role of this genotype in breast cancer. Genotyping study of GST show that the GSTM1 (P>0.05) null genotype was significantly associated with breast cancer and we found no association with breast cancer and GSTT1 (P<0.05) null genotype. In conclusion our study suggest that the dysregulation of glutathione level were associated with breast cancer and GSTM1 null genotype could be a useful marker for breast cancer prognosis.

The Investigation of Associations between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344, EGFR rs2227983 Polymorphisms and Breast Cancer Phenotype and Prognosis.

Breast cancer is one of the most common oncological diseases among women worldwide. Cell cycle and apoptosis—related genes TP53, BBC3, CCND1 and EGFR play an important role in the pathogenesis of breast cancer. However, the roles of single nucleotide polymorphisms (SNPs) in these genes have not been fully defined. Therefore, this study aimed to analyze the association between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344 and EGFR rs2227983 polymorphisms and breast cancer phenotype and prognosis. For the purpose of the analysis, 171 Lithuanian women were enrolled. Genomic DNA was extracted from peripheral blood; PCR-RFLP was used for SNPs analysis. The results showed that BBC3 rs2032809 was associated with age at the time of diagnosis, disease progression, metastasis and death. CCND1 rs9344 was associated with tumor size, however an association resulted in loss of significance after Bonferroni correction. In survival analysis, significant associations were observed between BBC3 rs2032809 and OS, PFS and MFS. EGFR rs2227983 also showed some associations with OS and PFS (univariate Cox regression analysis). However, the results were in loss of significance (multivariate Cox regression analysis). In conclusion, BBC3 rs2032809 polymorphism was associated with breast cancer phenotype and prognosis. Therefore, it could be applied as potential markers for breast cancer prognosis.

Comprehensive Analysis of the Expression, Prognosis, and Biological Significance of OVOLs in Breast Cancer.

BackgroundThe study aimed to investigate the expression of OVOLs in breast cancer (BRCA) tissues and their value in prognosis.MethodsONCOMINE was used to analyze the expressions of OVOL1, OVOL2, and OVOL3 mRNA between BRCA tissues and normal breast tissues. The Wilcoxon rank sum test and t-test were used to assess the expression of OVOLs between BRCA tissues and unpaired/paired normal breast tissues. GEPIA and ROC curves were used to analyze the relationship between OVOLs expression and clinical pathological stage. Kaplan–Meier plotter was used to analyze prognosis. cBioPortal was used to analyze the mutation of OVOLs. GEPIA was used to analyze the co-expression of OVOLs. GO and KEGG analyses were performed by the DAVID software to predict the function of OVOLs co-expression genes.ResultsThe expression of OVOL1/2 was significantly higher in BRCA tissues than in normal breast tissues. The OVOL3 expression correlated with tumor stage. The AUC of OVOLs was 0.757, 0.754, and 0.537, respectively. OVOL1 high expression was associated with shorter overall survival (HR: 1.48; 95% CI: 1.07–2.04; P=0.018). The OVOLs were associated with pathways including axon guidance, thyroid hormone signaling pathway, and ubiquinone and other terpenoid-quinone biosynthesis.ConclusionOVOL1 is a new potential marker of prognosis in BRCA, and OVOL1/2 are potential therapeutic targets in BRCA.

Time-varying effects of FOXA1 on breast cancer prognosis

Results of previous studies on the associations between Forkhead box A1 (FOXA1) expression in breast cancer tissues and the prognosis varied depending on the follow-up durations. The present study would investigate whether there is a time-varying effect of FOXA1 in breast cancer tissues on the prognosis. FOXA1 expressions were evaluated in 1041 primary invasive breast tumors with tissue microarrays by immunohistochemistry. Cox models with restricted cubic splines and Kaplan-Meier survival analysis were used to examine the associations between FOXA1 and the prognosis. Flexible parametric models were applied to explore the time-varying effect of FOXA1. Overall, the association between FOXA1 expression and the prognosis was not significant but varied on the time of follow-up. Compared to FOXA1 ≤ 270 of H-score, the hazard ratios (HRs) of death for those with 271-285 of FOXA1 expression increased from 0.35 (95% CI 0.14-0.86) at 6months after diagnosis to 2.88 (95% CI 1.35-6.15) at 120months with a crossover at around 36months. Similar patterns were also observed for FOXA1 > 285 of H-score and for progression free survival (PFS). Moreover, when allowed both FOXA1 and estrogen receptor (ER) to change over time in the model (considering that ER had a similar time-varying effect), these time-varying effects remained for FOXA1 on both overall survival (OS) (P < 0.01) and PFS (P = 0.01) but were attenuated for ER (P = 0.13 for OS). This study revealed an independent time-varying effect of FOXA1 on breast cancer prognosis, which would provide an insight into the roles of FOXA1 as a marker of breast cancer prognosis and may help optimize the medication strategies.

Moesin is an independent prognostic marker for ER-positive breast cancer.

Moesin, a cytoskeletal protein belonging to the ezrin-radixin-moesin family serves important roles in cell motility, invasion and metastasis. Moesin has been demonstrated to be of prognostic significance in tumor progression, due to its role in the metastatic process; however, its role in breast cancer is not well characterized. In the present study, the moesin expression was determined using immunohistochemistry in 404 and 46 patients with breast cancer and fibroadenoma, respectively, and the associations between moesin expression and the clinical parameters and prognostic values were analyzed. The positive rate of moesin protein expression was 47.8% (193/404) in breast cancer tissues, which was significantly higher than in fibroadenoma tissues (15.2%, 14/46). Overexpression of moesin was significantly associated with advanced clinical stage (P=0.002), positive lymph node metastasis (P<0.0001), and estrogen receptor (ER; P=0.008) and progesterone receptor (P=0.026) status. Patients with high moesin expression had significantly lower recurrence-free survival time, compared with patient with low moesin expression. Notably, overexpression of moesin was significantly associated with poor prognosis in patients with ER-positive breast cancer, and in patients treated with tamoxifen. Using a Cox proportional hazard regression model, further analysis was conducted, which demonstrated that moesin overexpression was a predictive prognostic factor for reduced overall survival time in patients with ER-positive breast cancer, and in patients treated with tamoxifen. These results indicated that moesin may be a potential marker for poor prognosis in patients with ER-positive breast cancer treated with tamoxifen. In conclusion, moesin serves an important role in the progression of breast cancer, and may be a valuable marker of breast cancer prognosis.

Role of microRNAs in breast cancer development and their potential as biomarkers

Breast cancer is the 2nd most common malignant disease after lung cancer; about 1 in 8 women will develop breast cancer in her lifetime. Cancer progression is a serious complication of the disease that encourages comprehensive investigation of molecular mechanisms underlying breast cancer development. This is also important for healthcare professionals involved in patient management, since they have to choose an optimal treatment regimen. This article discusses the role of microRNAs in the development of breast cancer, their biogenesis, classification, association with various molecular subtypes of breast cancer, and their potential role in the development of new targeted drugs for breast cancer therapy. Current research on the role of microRNAs in breast cancer progression is focused on the development of markers for breast cancer prognosis, diagnostic markers and new targeted drugs.

Prognostic genes of breast cancer revealed by gene co-expression network analysis.

The aim of the present study was to identify genes that may serve as markers for breast cancer prognosis by constructing a gene co-expression network and mining modules associated with survival. Two gene expression datasets of breast cancer were downloaded from ArrayExpress and genes from these datasets with a coefficient of variation >0.5 were selected and underwent functional enrichment analysis with the Database for Annotation, Visualization and Integration Discovery. Gene co-expression networks were constructed with the WGCNA package in R. Modules were identified from the network via cluster analysis. Cox regression was conducted to analyze survival rates. A total of 2,669 genes were selected, and functional enrichment analysis of them revealed that they were mainly associated with the immune response, cell proliferation, cell differentiation and cell adhesion. Seven modules were identified from the gene co-expression network, one of which was found to be significantly associated with patient survival time. Expression status of 144 genes from this module was used to cluster patient samples into two groups, with a significant difference in survival time revealed between these groups. These genes were involved in the cell cycle and tumor protein p53 signaling pathway. The top 10 hub genes were identified in the module. The findings of the present study could advance the understanding of the molecular pathogenesis of breast cancer.

Abstract 943: RelA regulates CXCR5/CXCL13 transcription and associated immune response in breast cancer

Abstract It is evident from research outcomes that metastases-associated deaths are predominant in breast cancer. Recent developments on early diagnosis using mammographic screening and the implementation of adjuvant therapies may have reduced breast cancer associated deaths in decent numbers, although new markers for prognosis are of utmost importance for patients with higher risk of developing metastases or recurrence. Chemokines are the key messenger of cellular immune response and can be targeted to reduce the intratumoral regulatory T cells (Treg) for antitumor immunity. Targeting either specific immunomodulators and/or intervening molecular mechanisms is thought to be a potential therapeutic option. In our previous study, we have found that co-expression of CXCR5 and CXCL13 is significantly associated with epithelial to mesenchymal transition (EMT) of cells and lymph node metastasis (LNM) during breast cancer progression. In this study, we are aiming to investigate how the transcriptional regulation of this receptor-ligand pair directs the process of disease development. Interestingly, it was found that RelA (p65), a subunit of NFkB protein, promoted the transcription of both CXCR5 and CXCL13. The putative RelA binding sites were validated using sequential deletion of respective promoter regions of CXCR5 and CXCL13. We observed that expression of CXCR5 significantly (p&amp;lt;0.05) increased with RelA and Nrf2 overexpression and CXCL13 co-stimulation in MDA-MB-231 cell line. RelA was also found to induce the expression of CXCL13 in T-47D and MDA-MB-231 cell line. Significantly, SNAIL, a key EMT regulatory element, was found to be highly expressed in RelA-transfected MDA-MB-231 cell line with or without CXCR5 and CXCL13 co-stimulation. We also observed CXCR5+ T follicular helper (Tfh) and Treg sub-population within the tumor microenvironment, although numbers varied with stages and molecular subtypes. In chemotaxis assay, CXCR5+ Treg cells were found to be predominant among migratory T-cell subsets against RelA overexpression and/or CXCL13 stimulation. Simultaneously, CCL2, a pro-inflammatory chemokine, induced macrophages to secrete CCL22, which in turn, might attract CXCR5+ Treg and Th2 cells into the tumor microenvironment. Study in 4T1-BALB/c breast cancer mouse model demonstrated significant (p&amp;lt;0.05) increase in CXCR5 and CXCL13 expression levels upon immunostimulation. The study may help to understand the prognosis value of CXCR5 and CXCL13 considering the impact of this receptor-ligand pair on the regulation of Tfh/Treg ratio, EMT and LNM. We believe that this investigation may lead to a comprehensive prediction of the tumor fate as well as to explore possible markers for breast cancer prognosis and future chemotherapy with more precision. Citation Format: Sougata Roy Chowdhury, Subir Biswas, Gunjan Mandal, Arindam Bhattacharyya. RelA regulates CXCR5/CXCL13 transcription and associated immune response in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 943. doi:10.1158/1538-7445.AM2017-943

Effectiveness of four inflammatory markers in predicting prognosis in 2374 women with breast cancer

ObjectiveTo analyze the association between four biomarkers and overall survival in patients with breast cancer (BC). MethodologyThis cohort study had a sample of 2374 women over the age of 18, diagnosed and treated in a single reference center for BC in Brazil, during the year 2008–2009. The following pretreatment indices were analyzed: neutrophil–lymphocyte ratio (NLR), a derived neutrophil–lymphocyte ratio (dNLR), absolute neutrophil count (ANC) and platelet–lymphocyte ratio (PLR). A descriptive analysis was performed using median (range) and absolute and relative frequency as categorical variables. Exploratory survival evaluation was performed using the Kaplan-Meier method and the log-rank test for comparison between survival curves, with a statistical significance level of 5%. The variables with p<0.20 were selected for inclusion in a multivariate Cox regression model, considering as statistically significant p<0.05. ResultsAfter adjusting for clinical variables, the biomarkers associated with worse overall survival were NLR >5 (HR=1.66 95%CI 1.08–2.55; p=0.021) and PLR >300 (HR=1.82 95%CI 1.10–2.99; p=0.019). When stratified by molecular subtype, the independent markers related to death were PLR >300 for triple negative (HR 3.27 95%CI 1.38–7.76; p=0.007); NLR >5 (HR 2.47 95%CI 1.16–5.28; p=0.019), ANC >7500 (HR 1.84 95%CI 1.17–2.90; p=0.008) and dNLR >3 (HR 2.45 95%CI 1.29–4.66; p=0.006) for luminal. ConclusionNLR and PLR are independent markers of prognosis in BC. Further studies are needed in patients with overexpression of HER 2.

New look inside human breast ducts with Raman imaging. Raman candidates as diagnostic markers for breast cancer prognosis: Mammaglobin, palmitic acid and sphingomyelin

Looking inside the human body fascinated mankind for thousands of years. Current diagnostic and therapy methods are often limited by inadequate sensitivity, specificity and spatial resolution. Raman imaging may bring revolution in monitoring of disease and treatment. The main advantage of Raman imaging is that it gives spatial information about various chemical constituents in defined cellular organelles in contrast to conventional methods (liquid chromatography/mass spectrometry, NMR, HPLC) that rely on bulk or fractionated analyses of extracted components. We demonstrated how Raman imaging can drive the progress on breast cancer just unimaginable a few years ago. We looked inside human breast ducts answering fundamental questions about location and distribution of various biochemical components inside the lumen, epithelial cells of the duct and the stroma around the duct during cancer development. We have identified Raman candidates as diagnostic markers for breast cancer prognosis: carotenoids, mammaglobin, palmitic acid and sphingomyelin as key molecular targets in ductal breast cancer in situ, and propose the molecular mechanisms linking oncogenes with lipid programming.

Hexokinase and phosphofructokinase activity and intracellular distribution correlate with aggressiveness and invasiveness of human breast carcinoma.

Glycolytic enzymes, such as hexokinase and phosphofructokinase, have been reported to be upregulated in many cancer types. Here, we evaluated these two enzymes in 54 breast cancer samples collected from volunteers subjected to mastectomy, and the results were correlated with the prognosis markers commonly used. We found that both enzymes positively correlate with the major markers for invasiveness and aggressiveness. For invasiveness, the enzymes activities increase in parallel to the tumor size. Moreover, we found augmented activities for both enzymes when the samples were extirpated from patients presenting lymph node involvement or occurrence of metastasis. For aggressiveness, we stained the samples for the estrogen and progesterone receptors, HER-2, p53 and Ki-67. The enzyme activities positively correlated with all markers but Ki-67. Finally, we conclude that these enzymes are good markers for breast cancer prognosis.

Investigation of prognostic value of polymorphisms within estrogen metabolizing genes in Lithuanian breast cancer patients.

BackgroundBreast cancer is the most frequent oncological disease among women. Estrogens are known to play an important role in breast cancer development. Recognition of the relationship between polymorphisms within estrogen metabolizing genes and conventional prognostic factors of breast cancer might improve our knowledge on individualized breast cancer prognosis. Therefore, we aimed to investigate possible associations between germline genetic polymorphisms within GSTM1, GSTT1, GSTP1, SULT1A1 and UGT1A1 genes and breast cancer clinicopathological characteristics together with disease progression.MethodsOur study involved 80 young (younger than 50 years of age) breast cancer patients. PCR-based Restriction Fragment Length Polymorphism (RFLP) assay was used to determine GSTP1 and SULT1A1 genotypes. GSTM1 and GSTT1 null genotypes were detected by multiplex PCR. UGT1A1 polymorphism was investigated with microsatellite analysis. Relationships between genotypes and breast cancer clinicopathological features along with disease progression were estimated by Pearson‘s Chi-square test. Logistic regression analyses were performed to estimate the odds ratios associating different genotypes with clinicopathological characteristics and disease progression.ResultsThe study showed individuals with GSTT1 null genotype to have approximately 3.5 times higher risk for breast cancer progression than those with wild type genotype (OR = 3.472, 95% CI 1.043-11.559, P = 0.043). Moreover, SULT1A1 G638A AA genotype significantly increased the chances of HER2 molecular subtype breast cancer when compared to GG genotype (OR = 19.971, 95% CI 1.716-232.480, P = 0.017). Heterozygotes for GSTP1 A313G genotype were more likely to have positive lymph nodes in comparison to AA genotype carriers (OR = 2.803, 95% CI 1.049-7.487, P = 0.040). No significant correlation was determined for UGT1A1 A(TA)nTAA and GSTM1 +/- polymorphism alone or combined GTTT1 null and GSTM1 null genotype.ConclusionsConclusively, our findings suggest that GSTT1 null genotype and SULT1A1 G638A AA genotype could be uselful genetic markers for breast cancer prognosis. Further analyses on larger sample size are required to highlight the effect of GSTP1 G allele on breast cancer prognosis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12881-015-0147-4) contains supplementary material, which is available to authorized users.

MiR-221/-222 differentiate prognostic groups in advanced breast cancers and influence cell invasion

Background:MiR-221/-222 are frequently overexpressed in breast cancer and are associated with increased malignancy. The specific modification of microRNAs (miRNAs) expression could be a promising strategy in breast cancer therapy, leading to the suppression of tumourigenic processes in tumour cells.Methods:MiR-221/-222 expressions were analysed in 86 breast cancer tissues by quantitative RT–PCR and tested for correlation with immunohistochemistry data and clinical follow-up. In vitro assays were conducted using human breast cancer cell lines with lentiviral overexpression of miR-221/-222.Results:In tumour tissues, miR-221/-222 were associated with the occurrence of distant metastases. In particular, high levels of miR-221 were revealed to have a high prognostic impact for the identification of significantly different groups with advanced tumours. MiR-221/-222 overexpression strongly increased cell proliferation and invasion in vitro. Following miR-221/-222 overexpression an increased uPAR expression and cell invasion were observed.Conclusion:This study demonstrates a significant role for highly expressed miR-221/-222 in advanced breast cancers allowing for the identification of significantly different prognostic groups, particularly for HER2-positive and lymph-node-positive breast cancers. Considering that miR-221/-222 are strongly involved in cell invasion, these miRNAs may be promising markers for breast cancer prognosis and therapy.

Testin is a tumor suppressor and prognostic marker in breast cancer

The testin (TES) gene was previously identified in the fragile chromosomal region FRA7G at 7q31.2. In the present study, we aimed to investigate the candidate tumor suppressor function of TES and explore its correlations to clinicopathologic features and prognosis in breast cancer. In clinical samples, we showed that the expression of TES decreased gradually from normal through ductal hyperplasia without atypia, atypical ductal hyperplasia, and ductal carcinoma in situ, to invasive ductal carcinoma. To explore the possible tumor suppressing function of TES, the expression of TES in breast cancer cells was manipulated by ectopic expression or by RNAi. We revealed that ectopic TES expression significantly inhibited cell proliferation, invasive ability, and angiogenesis, whereas knockdown of TES by RNAi enhanced cell proliferation, invasive ability, and angiogenesis. In an animal model, TES markedly inhibited breast cancer cell xenograft formation in athymic nude mice and reduced breast cancer cell metastasis to lung. Moreover, we revealed that TES inhibited the invasion and angiogenesis of breast cancer partially through miR-29b-mediated MMP-2 inhibition. Using the tissue microarray of breast cancer from Yale University, we found that lower TES expression was an independent prognostic factor for shorter overall survival and disease-free survival with univariate and multivariate analyses. Taken together, these data suggest that TES, as a valuable marker of breast cancer prognosis, plays an important role in the development and progression of breast cancer. TES may be an effective novel target in breast cancer prevention and treatment.

P4-12-01: The Breast-Activity and Healthy Eating after Diagnosis (B-AHEAD) Study – A Randomised Comparison of Weight Control Programmes during Adjuvant Treatment.

Abstract Background: Excess weight at diagnosis and weight gain during treatment are linked to increased mortality from breast cancer. Since 60% of breast cancer patients are overweight at diagnosis and 75% gain weight during treatment, weight control should improve outcome but the optimal intervention is unknown. Aim: To compare 3 programmes for weight control after surgery for primary breast cancer. Methods: We have recruited a randomised trial of 2 diet and exercise weight control interventions (1. a community based supervised group programme, 2. a mail and phone programme) compared to standard written advice (control). We are comparing the relative effects of the 3 programmes on body weight and composition (by dual energy x-ray absorptiometry), cardiovascular risk parameters (lipids, blood pressure), a marker of breast cancer prognosis (insulin resistance), fitness and quality of life over the first year after diagnosis. In total 409 women have been randomised (45% of eligible women) and 21 women have left the trial (5.1%), 357 have completed the 6 month assessments, all are due to complete the trial in December 2011. Results: Weight and body fat results at 6 months indicate that the low cost mail and phone programme is equal to the supervised programme and both are significantly superior to written advice, but not in patients receiving chemotherapy. The high uptake and adherence to the trial shows interest and motivation of a significant number of cancer patients to make positive changes to lifestyle at the time of diagnosis. The final trial results will be presented at the December meeting. This abstract presents independent research commissioned by the National Institute for Health Research under the Research for Patient Benefit programme. The views expressed here are those of the authors and not necessarily those of the funding organisations. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-12-01.

Twist contributes to hormone resistance in breast cancer by downregulating estrogen receptor-α

The role of estrogen receptor alpha (ER) in breast cancer development and as a primary clinical marker for breast cancer prognosis is well documented. In this study, we identified the oncogenic protein TWIST1 (Twist), which is over-expressed in high-grade breast cancers, as a potential negative regulator of ER expression. Functional characterization of ER regulation by Twist was carried out using Twist low (MCF-7, T-47D) and Twist high (Hs 578T, MDA-MB-231, MCF-7/Twist) expressing cell lines. All Twist high cell lines exhibited low ER transcript and protein levels. By chromatin immunoprecipitation and promoter assays, we demonstrated that Twist could directly bind to E-boxes in the ER promoter and significantly down-regulate ER promoter activity in vitro. Functionally, Twist over-expression caused estrogen independent proliferation of breast cells and promoted hormone resistance to the selective estrogen receptor modulator (SERM) tamoxifen and selective estrogen receptor down-regulator (SERD) fulvestrant. Importantly, this effect was reversible on down-regulating Twist. Additionally, orthotopic tumors generated in mice using MCF-7/Twist cells were resistant to tamoxifen. These tumors had high vascular volume and permeability surface area as determined by magnetic resonance imaging (MRI). Mechanistically, Twist recruited DNA methyltransferase 3B (DNMT3B) to the ER promoter leading to a significantly higher degree of ER promoter methylation compared to parental cells. Furthermore, we demonstrated by co-immunoprecipitation that Twist interacted with histone deacetylase 1 (HDAC1) at the ER promoter, causing histone deacetylation and chromatin condensation, further reducing ER transcript levels. Functional re-expression of ER was achieved using demethylating agent 5-azacytidine and histone deacetylase inhibitor valproic acid. Finally, an inverse relationship was observed between Twist and ER expression in human breast tumors. In summary, the regulation of ER by Twist could be an underlying mechanism for loss of ER activity observed in breast tumors and may contribute to the generation of hormone resistant ER negative breast cancer.

The expression and clinical significance of CXCR3/CXCL10 in human breast cancer

Objective To investigate the expression and clinical significance of CXCR3/CXCL10in human cancer.Methods CXCR3 and CXCL10 were detected in 60 paraffinic tissues of patients with primary breast cancer,20 of mammary fibroma and 20 of mastopathy by immunohistochemistry S-P method and two stage method.Results The expression of CXCR3 (40/60,66.7％ ) and CXCL10 (45/60,75％)in breast cancer was higher than that in mastopathy [CXCR3(8/20,40％ )x2 =4.44,P =0.035 ;CXCL10( 10/20,50％ )x2 =4.36,P =0.037)].The expression of CXCR3 was related to status of axillary lymph node metastasis,clinical stage and the expression of HER-2 (x2 =4.15,P =0.042; x2 =7.74,P =0.021 ;x2 =4.27,P =0.039).The expression of CXCR3 had positive relationship to the number axillary lymph node metastasis( rs =0.375,P =0.003 ),clinical stage ( rs =0.451,P =0.000).Conclusions CXCR3 may be related to the progression and metastasis of breast cancer,and it may be used as a marker of breast cancer prognosis. Key words: Breast neoplasms/ME; Receptors, CXCR3/ME ; Chemokine CXCL10/ME

Abstract 3303: Investigation of SPAG5 gene expression as a molecular marker for breast cancer prognosis

Abstract Breast cancer is a clinically heterogeneous disease, making it imperative to use biomarkers, such as the estrogen receptor (ER) and human epidermal growth factor 2 (HER2), to stratify patients into specific prognostic groups. Biomarker stratification provides patients with more accurate diagnoses, predictions of clinical outcomes, and offers targeted therapeutic options. SPAG5 (Sperm Associated Antigen 5) is involved in the maintenance of spindle-pole integrity, efficient chromosomal alignment, and cell proliferation. Its role in cell division may be a cancer susceptibility factor. Low expression of SPAG5 has been correlated with good prognosis and absence of metastases in ER+ breast cancer. However, its relationship to other molecular subtypes of breast cancer and its functional role in the disease are relatively unknown. The purpose of this study was to investigate the role of SPAG5 in breast cancer through (i) microarray analysis and (ii) correlating its expression with invasiveness, a factor involved in disease progression. In part (i), SPAG5 expression in breast cancers was evaluated by using five Affymetrix, three Agilent and one Illumina microarray datasets. The associations between SPAG5 expression and various tumor pathologies were analyzed via log2 expression ratios. Pathologies that were investigated included the ER+ subtype, HER2 overexpression, lymph node metastasis, and breast cancer stem cell-like/undifferentiated tumors. In part (ii), SPAG5 expression across five breast cancer epithelial cell lines of varying invasive ability (MDA-MB-231, MDA-MB-157, BT549, MCF-7, and CAMA1) was investigated. The cells were cultured at normal conditions and lysed using the CytoBusterTM protein extraction reagent. The supernatants were collected by microcentrifugation at 16,000 rcf at 4°C for 5 minutes. Western blotting was completed using standard techniques. From the microarray analysis, overexpression of SPAG5 showed strong associations with HER2 overexpression, ER-negative and triple-negative cancers, high grade tumors, metastasis, and poor clinical outcomes in a total of 1595 breast cancers. Via immunoblotting, it was shown that higher levels of SPAG5 accompanied highly invasive cell lines (MDA-MB-231, MDA-MB-157, and BT549) and lower levels occurred in weakly invasive cells (MCF-7 and CAMA1). These results suggest that SPAG5 is a biomarker of malignancy and invasiveness and may be a novel therapeutic target for the prevention of metastasis. Stratification into specific prognostic groups using SPAG5 as a biomarker could lead to early detection and intervention of breast cancers likely to metastasize. It is possible that treatments targeting the modulation of SPAG5 expression levels may also aid in improving clinical outcomes. Ongoing functional analysis of SPAG5 will elucidate its role in breast cancer and metastasis and aid in further characterization of SPAG5. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3303.

Mixture classification model based on clinical markers for breast cancer prognosis

Accurate cancer prognosis prediction is critical to cancer treatment. There have been many prognosis models based on clinical markers, but few of them are satisfied in clinical applications. And with the development of microarray technologies, cancer researchers have discovered many genes as new markers from the gene expression data and have further developed powerful prognosis models based on these so-called genetic biomarkers. However, the application of such biomarkers still suffers from some problems. The first one is there are a great number of genes and a few samples in the gene expression data so that it is difficult to select a unified gene set to establish a stable classifier for prognosis. The second one is that, due to the experimental and technical reasons, there are existing noises and redundancies in gene expression data, which may lead to building a prognosis predictor with poor performance. The last but not the least one is the microarray experiments are so expensive currently that it is hard to obtain abundant samples. Therefore, it is practical to develop prognosis methods mainly based on conventional clinical markers in real cancer treatment applications. This paper aims to establish an accurate classification model for cancer prognosis, in order to make full use of the invaluable information in clinical data, especially which is usually ignored by most of the existing methods when they aim for high prediction accuracies. First, this paper gives the formal description of general classification problem, and presents a novel mixture classification model to make full use of the invaluable information in clinical data, which is similar to the traditional ensemble classification models except for putting strict constraints on the construction of mapping functions to avoid voting process. Then, a two-layer instance of the proposed model, named as MRS (Mixture of Rough set and Support vector machine), is constructed by integrating rough set and support vector machine (SVM) classification methods, in which, the rough set classifier acts as the first layer to identify some singular samples in data, and the SVM classifier acts as the second layer to classify the remaining samples. Finally, MRS is used to make prognosis prediction on two open breast cancer datasets. One dataset, denoted as BRC-1 hereafter, is a high quality, publicly available dataset of 97 breast cancer tumors of node-negative patients. The other, denoted as BRC-2 hereafter, uses baseline human primary breast tumor data from LBL breast cancer cell collection containing 174 samples. We have done two experiments on BRC-1 and BRC-2, respectively. In the first experiment, the BRC-1 dataset is divided into train set with 78 patients (34 ones belonging to poor prognosis group and 44 ones belonging to good prognosis group) and test set with 19 patients (12 ones belonging to poor prognosis group and 7 ones belonging to good prognosis). After trained on the train set, the MRS can correctly classify all the 12 patients with poor prognosis, and 6 of 7 patients with good prognosis in the test set. The results are better than previous researches, even better than the 70-gene based biomarkers. And in the second experiment, we construct the classifiers using BRC-2 dataset, and compare MRS with other representative methods in Weka software by 5-fold cross-validation, and comparison results show that MRS has higher prediction accuracy than those methods. The proposed mixture classification model can easily integrate methods with different characteristics. It can overcome the shortcomings of traditional voting-based ensemble models and thus can make full use of the information in clinical data. The experimental results illustrate that our implemented MRS classifier can predict the breast cancer prognosis more accurately than previous prognostic methods.

Function of Histone Deacetylase 6 as a Cofactor of Nuclear Receptor Coregulator LCoR

Ligand-dependent corepressor LCoR was identified as a protein that interacts with the estrogen receptor alpha (ERalpha) ligand binding domain in a hormone-dependent manner. LCoR also interacts directly with histone deacetylase 3 (HDAC3) and HDAC6. Notably, HDAC6 has emerged as a marker of breast cancer prognosis. However, although HDAC3 is nuclear, HDAC6 is cytoplasmic in many cells. We found that HDAC6 is partially nuclear in estrogen-responsive MCF7 cells, colocalizes with LCoR, represses transactivation of estrogen-inducible reporter genes, and augments corepression by LCoR. In contrast, no repression was observed upon HDAC6 expression in COS7 cells, where it is exclusively cytoplasmic. LCoR binds to HDAC6 in vitro via a central domain, and repression by LCoR mutants lacking this domain was attenuated. Kinetic chromatin immunoprecipitation assays revealed hormone-dependent recruitment of LCoR to promoters of ERalpha-induced target genes in synchrony with ERalpha. HDAC6 was also recruited to these promoters, and repeat chromatin immunoprecipitation experiments confirmed the corecruitment of LCoR with ERalpha and with HDAC6. Remarkably, however, although we find evidence for corecruitment of LCoR and ERalpha on genes repressed by the receptor, LCoR and HDAC6 failed to coimmunoprecipitate, suggesting that they are part of distinct complexes on these genes. Although small interfering RNA-mediated knockdown of LCoR or HDAC6 augmented expression of an estrogen-sensitive reporter gene in MCF7 cells, unexpectedly their ablation led to reduced expression of some endogenous estrogen target genes. Taken together, these data establish that HDAC6 can function as a cofactor of LCoR but suggest that they may act in enhance expressing some target genes.