Prognostic Tool In Breast Cancer Research Articles

Concomitant medications and circulating tumor cells: friends or foes?

The use of concomitant medications by patients with cancer is observed almost globally; however, little attention has been paid to this topic in the medical literature. Most clinical studies do not describe the type and duration of drugs used at the time of inclusion and during treatment or how these drugs may affect the experimental and/or standard therapy. Even less information has been published on the potential interaction between concomitant medications and tumor biomarkers. However, we do know that concomitant drugs can complicate cancer clinical trials and biomarker development, thus contributing to their interaction, leading to side effects, and resulting in suboptimal adherence to anticancer treatment. On the basis of these premises and moving from the study by Jurisova et al., which reported the effect of commonly used drugs on the prognosis of women with breast cancer and the detection of circulating tumor cells (CTCs), we comment on the role of CTCs as an emerging diagnostic and prognostic tool for breast cancer. We also report the known and hypothesized mechanisms of CTC interplay with other tumor and blood components, possibly modulated by widespread drugs, including over-the-counter compounds, and discuss the possible implications of commonly used concomitant medications on CTC detection and clearance. After considering all these points, it is conceivable that concomitant drugs are not necessarily a problem, but on the contrary, their virtuous mechanisms can be exploited to reduce tumor spread and enhance the effect of anticancer therapies.

Preoperative Breast Immune Prognostic Index as Prognostic Factor Predicts the Clinical Outcomes of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.

ObjectiveThis study aims at investigating the potential prognostic significance of the breast immune prognostic index (BIPI) in breast cancer patients who received neoadjuvant chemotherapy (NACT).MethodsThe optimal cutoff value was calculated through the receiver operating characteristic curve (ROC). The correlations between BIPI and clinicopathologic characteristics were determined by the chi-square test or Fisher’s exact test. The Kaplan–Meier method was used to estimate the survival probability, and the log-rank test was used to analyze the differences in the survival probability among patients. The univariate and multivariate Cox proportional hazard regression model was used to screen the independent prognostic factors. A prognostic nomogram for disease-free survival (DFS) and overall survival (OS) was built on the basis of the multivariate analyses. Furthermore, the calibration curve and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram.ResultsAll enrolled patients were split into three subgroups based on the BIPI score. The mean DFS and OS of the BIPI score 0 group and BIPI score 1 group were significantly longer than those of the BIPI score 2 group (42.02 vs. 38.61 vs. 26.01 months, 77.61 vs. 71.83 vs. 53.15 months; p < 0.05). Univariate and multivariate analyses indicated that BIPI was an independent prognostic factor for patients’ DFS and OS (DFS, hazard ratio (HR): 6.720, 95% confidence interval (CI): 1.629–27.717; OS, HR: 8.006, 95% CI: 1.638–39.119). A nomogram with a C-index of 0.873 (95% CI: 0.779–0.966) and 0.801 (95% CI: 0.702–0.901) had a favorable performance for predicting DFS and OS survival rates for clinical use by combining immune scores with other clinical features. The calibration curves at 1-, 3-, and 5-year survival suggested a good consistency between the predicted and actual DFS and OS probability. The DCA demonstrated that the constructed nomogram had better clinical predictive usefulness than only BIPI in predictive clinical applications of 5-year DFS and OS prognostic assessments.ConclusionsThe patients with low BIPI score have better prognoses and longer DFS and OS. Furthermore, the BIPI-based nomogram may serve as a convenient prognostic tool for breast cancer and help in clinical decision-making.

Salivary Human Epidermal Growth Factor Receptors 2 Levels in Patients With Different Stages of Breast Cancer: A Cross Sectional Study

Background: Breast cancer in women is a major health burden across the globe, which accounts for 12% of all new cancer cases and 25% of all cancers in women. Though studies have demonstrated a significant reduction in mortality and morbidity by periodic screening using mammography, its cost and exposure to radiation are prohibitive factors in subjecting the patients to a repetitive mammogram examination. Hence additional adjunct procedures which can overcome these disadvantages and enhance screening are advocated. Human epidermal growth factor receptor-2 (c-erbB-2) is a biomarker that can be detected in saliva of breast cancer patients. An elevated level of this protein indicates the presence of an aggressive tumor with poor prognosis. Aim: The aim of our study was to determine the levels of salivary c-erbB-2 in patients diagnosed with different stages of breast cancer. Methods: 90 patients, histopathologically diagnosed with breast cancer were divided into three groups based on TNM staging (Stage I, II, and III) with 30 patients in each group. 3 ml of unstimulated saliva was collected from these patients and the protein was estimated using ELISA kit. Appropriate statistical tests were used to analyze the demographic details and mean salivary c-erbB-2 levels. Results: The mean salivary c-erbB-2 levels in groups I, II and III were 9.933(±5.105), 59.633(±17.14) and 146.695(±22.418) picograms/mL respectively. There was a significant increase in the levels of the protein with an increase in the TNM staging in patients with breast cancers. Conclusion: This study results throws light on the potential use of salivary c-erB-2 as an adjunct screening and prognostic tool for breast cancer. However further studies are recommended to assess the utility of this biomarker for the diagnosis and posttreatment monitoring of breast cancer.

Core needle biopsy as an alternative to whole section in IHC4 score assessment for breast cancer prognostication

AimsIHC4 score, based on expression of four routine markers (oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and proliferation marker, Ki67), is a recently developed,...

Copy Number Profiling of MammaPrint™ Genes Reveals Association with the Prognosis of Breast Cancer Patients.

PurposeThe MammaPrint™ gene signature, currently used in clinical practice, provides prognostic information regarding the recurrence and potential metastasis in breast cancer patients. However, the prognostic information of the 70 genes included can only be estimated at the RNA expression level. In this study, we investigated whether copy number information of MammaPrint™ genes at the DNA level can be used as a prognostic tool for breast cancer, as copy number variations (CNVs) are major contributors to cancer progression.MethodsWe performed CNV profiling of MammaPrint™ genes in 59 breast cancer cell lines and 650 breast cancer patients, using publicly available data in The Cancer Genome Atlas (TCGA) database. Statistical analyses including Fisher exact test, chi-square test, and Kaplan-Meier survival analyses were performed.ResultsAll MammaPrint™ genes showed recurrent CNVs, particularly in TCGA cohort. CNVs of 32 and 36 genes showed significant associations with progesterone receptor and estrogen rector, respectively. No genes showed a significant association with human epidermal growth factor receptor 2 status and lymph node status. In addition, only six genes were associated with tumor stages. RFC4, HRASLS, NMU, GPR126, SCUBE2, C20orf46, and EBF4 were associated with reduced survival and RASSF7 and ESM1 were associated with reduced disease-free survival.ConclusionBased on these findings, a concordance of CNV-based genomic rearrangement with expression profiling of these genes and their putative roles in disease tumorigenesis was established. The results suggested that the CNV profiles of the MammaPrint™ genes can be used to predict the prognosis of breast cancer patients. In addition, this approach may lead to the development of new cancer biomarkers at the DNA level.

VEGFR OVEREXPRESSION AS A PROMISING PREDICTIVE AND PROGNOSTIC BIOMARKER FOR BREAST CANCER

Background: The majority of breast cancer cases are presented in an advanced stage; hence, there is a need to have a biomarker that is able to function both as a predictive and prognostic tool for breast cancer. Since angiogenesis has been found to be closely related to the invasiveness of breast cancer, angiogenic marker such as vascular endothelial growth factor (VEGF) may be a promising marker for this cancer. Objective: The aim of this study is to determine the association between the VEGF receptor (VEGFR) expression with human epidermal growth factor receptor-2 (HER-2)/ neu and estrogen receptor (ER) /progesterone receptor (PR) expression in an attempt to clarify the role of VEGFR as a potentially novel predictive and prognostic biomarker for breast cancer. Materials and Methods: This study examined 40 tissue biopsies taken from patients diagnosed with breast cancer in H. Adam Malik Hospital Medan, Indonesia. Samples were analyzed by immunohistochemistry to determine the histopathology, grading, lymphovascular invasion and expression of VEGFR, HER-2/neu and ER/PR. Association between dependent and independent variables was conducted using chi-square test and logistic regression. Results: The majority of the cases in this study were infiltrating ductal carcinoma (90%), in stage III (70%), and showed positive TIL (75%). VEGFR expression was found to be upregulated in 21 samples (52.5%). HER-2/neu was positive in 14 patients (35.0%) and ER/PR was positive in 22 patients (55%). The expression of VEGFR positively correlated with HER-2/neu expression (p= 0.002) and negatively correlated with ER/PR expression (p= 0.012). Conclusion: Overexpression of VEGFR is a potential valuable predictive and prognostic biomarker for breast cancer. Antagonising VEGFR may serve as the future target therapy for the disease.

Validation of the CancerMath prognostic tool for breast cancer in Southeast Asia.

BackgroundCancerMath is a set of web-based prognostic tools which predict nodal status and survival up to 15 years after diagnosis of breast cancer. This study validated its performance in a Southeast Asian setting.MethodsUsing Singapore Malaysia Hospital-Based Breast Cancer Registry, clinical information was retrieved from 7064 stage I to III breast cancer patients who were diagnosed between 1990 and 2011 and underwent surgery. Predicted and observed probabilities of positive nodes and survival were compared for each subgroup. Calibration was assessed by plotting observed value against predicted value for each decile of the predicted value. Discrimination was evaluated by area under a receiver operating characteristic curve (AUC) with 95 % confidence interval (CI).ResultsThe median predicted probability of positive lymph nodes is 40.6 % which was lower than the observed 43.6 % (95 % CI, 42.5 %–44.8 %). The calibration plot showed underestimation for most of the groups. The AUC was 0.71 (95 % CI, 0.70–0.72). Cancermath predicted and observed overall survival probabilities were 87.3 % vs 83.4 % at 5 years after diagnosis and 75.3 % vs 70.4 % at 10 years after diagnosis. The difference was smaller for patients from Singapore, patients diagnosed more recently and patients with favorable tumor characteristics. Calibration plot also illustrated overprediction of survival for patients with poor prognosis. The AUC for 5-year and 10-year overall survival was 0.77 (95 % CI: 0.75–0.79) and 0.74 (95 % CI: 0.71–0.76).ConclusionsThe discrimination and calibration of CancerMath were modest. The results suggest that clinical application of CancerMath should be limited to patients with better prognostic profile.

Ras protein expression as a marker for breast cancer.

Breast cancer, the most common neoplasm in women of all ages, is the leading cause of cancer-related mortality in women worldwide. Markers to help to predict the risk of progression and ultimately provide non-surgical treatment options would be of great benefit. At present, there are no available molecular markers to predict the risk of carcinoma in situ progression to invasive cancer; therefore, all women diagnosed with this type of malignancy must undergo surgery. Breast cancer is a heterogeneous complex disease, and different patients respond differently to different treatments. In breast cancer, analysis using immunohistochemical markers remains an essential component of routine pathological examinations, and plays an import role in the management of the disease by providing diagnostic and prognostic strategies. The aim of the present study was to identify a marker that can be used as a prognostic tool for breast cancer. For this purpose, we firstly used an established breast cancer model. MCF-10F, a spontaneously immortalized breast epithelial cell line was transformed by exposure to estrogen and radiation. MCF-10F cells were exposed to low doses of high linear energy transfer (LET) α particles (150 keV/μm) of radiation, and subsequently cultured in the presence of 17β-estradiol. Three cell lines were used: i) MCF-10F cells as a control; ii) Alpha5 cells, a malignant and tumorigenic cell line; and iii) Tumor2 cells derived from Alpha5 cells injected into nude mice. Secondly, we also used normal, benign and malignant breast specimens obtained from biopsies. The results revealed that the MCF-10F cells were negative for c-Ha-Ras protein expression; however, the Alpha5 and Tumor2 cell lines were positive for c-Ha-Ras protein expression. The malignant breast samples were also strongly positive for c-Ha-Ras expression. The findings of our study indicate that c-Ha-Ras protein expression may be used as a marker to predict the progression of breast cancer; this marker may also ultimately provide non-surgical treatment options for patients who are at a lower risk.

Quantitation of CDH1 promoter methylation in formalin-fixed paraffin-embedded tissues of breast cancer patients using differential high resolution melting analysis.

Background:E-cadherin (CDH1) plays an important role in cell–cell adhesion of epithelial tissues. Loss of E-cadherin expression can lead to loss of tissue integrity, metastasis, and cancer progression. Also loss of E-cadherin expression might be related to aberrant promoter methylation of the CDH1 gene. Many studies have been performed on CDH1 promoter methylation, especially in breast cancer. Although most of the studies have used qualitative methods for methylation analysis, this study is designed to quantitatively investigate CDH1 promoter methylation in breast cancer and its correlation with patients’ clinicopathological features.Materials and Methods:Using differential high resolution melting analysis (D-HRMA), the methylation level of the CDH1 gene promoter was quantified in 98 breast cancer formalin-fixed paraffin-embedded (FFPE) tissues and also 10 fresh frozen normal breast tissues.Results:All samples were detected to be methylated at the CDH1 promoter region. About 74.5% of the breast cancer samples were hypermethylated with an average methylation level of around 60%, while 25.5% of the patients were methylated with the mean methylation level of about 33%, and 90% of the normal samples had a mean methylation level of about 18%. Statistical analyses represented a significant correlation between CDH1 promoter methylation and cancer progression hallmarks, such as, clinical stage, nodal involvement, tumor size, and histological grade.Conclusion:In summary, quantitation of CDH1 promoter methylation can serve as a diagnostic and prognostic tool in breast cancer. Also D-HRMA can be used as a fast and reliable method for quantitation of promoter methylation.

Variable expression levels of keratin and vimentin reveal differential EMT status of circulating tumor cells and correlation with clinical characteristics and outcome of patients with metastatic breast cancer.

BackgroundCTCs expressing variable levels of epithelial and mesenchymal markers in breast cancer have previously been reported. However, no information exists for keratin expression levels of CTCs in association with disease status, whereas assays for the characterization of transitional EMT phenotypes of CTCs in breast cancer are rather lacking. We investigated the correlation between keratin expression of CTCs and patients’ outcome and characterized the EMT status of CTCs via the establishment of a numerical “ratio” value of keratin and vimentin expression levels on a single cell basis.MethodsKeratin expression was evaluated in 1262 CTCs from 61 CTC-positive patients with metastatic breast cancer, using analysis of images obtained through the CellSearch System. For the determination of vimentin/keratin (vim/K) ratios, expression levels of keratin and vimentin were measured in cytospin preparations of luminal (MCF-7 and T47D) and basal (MDA.MB231 and Hs578T) breast cancer cell lines and 110 CTCs from 5 CTC-positive patients using triple immunofluorescence laser scanning microscopy and image analysis.ResultsMCF-7 and T47D displayed lower vim/K ratios compared to MDA.MB231 and Hs578T cells, while MCF-7 cells that had experimentally undergone EMT were characterized by varying intermediate vim/K ratios. CTCs were consisted of an heterogeneous population presenting variable vim/K values with 46% of them being in the range of luminal breast cancer cell lines. Keratin expression levels of CTCs detected by the CellSearch System correlated with triple negative (p = 0.039) and ER-negative (p = 0.025) breast cancer, and overall survival (p = 0.038).ConclusionsKeratin expression levels of CTCs correlate with tumor characteristics and clinical outcome. Moreover, CTCs display significant heterogeneity in terms of the degree of EMT phenotype that probably reflects differential invasive potential. The assessment of the vim/K ratios as a surrogate marker for the EMT status of CTCs merits further investigation as a prognostic tool in breast cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1386-7) contains supplementary material, which is available to authorized users.

Abstract P4-11-34: Validation of the CancerMath prognostic tool for breast cancer in Southeast Asia

Abstract Background: CancerMath is a set of web-based prognostic tools for non-metastatic breast cancer patients. It predicts probability of nodal and nipple involvement as well as overall and cancer-specific survival with and without adjuvant therapy at any of the 15 years after diagnosis. But it has not been externally validated outside United States. This study assessed its performance in a Southeast Asian setting. Methods: Using Singapore Malaysia Hospital Based Breast Cancer Registry, clinical information were retrieved from 7064 Stage I to stage III breast cancer patients who were diagnosed between 1990 and 2011 and underwent surgery. Probability of positive nodes and overall survival at any of the 15 years after diagnosis were computed using the CancerMath algorithm. Predicted and observed outcomes were compared. Discriminative ability was evaluated by area under a receiver operating characteristic curve (AUC). And calibration was assessed by plotting observed survival against predicted survival for each decile of the predicted survival and a 45 degree line was added to illustrated perfect agreement. Results: Nodal status calculator predicted 40.6% of patients to be node positive which was similar to the observed 43.6%. The AUC was 0.71 (95% CI, 0.70-0.72). For outcome calculator, the observed and predicted overall survivals was 83.4% vs 87.3% at 5 year after diagnosis and 70.4% vs 75.3% at 10 year after diagnosis. The difference appeared smaller for patients from Singapore (5-year and 10-year predicted-observed= 2.5% and 0% respectively) comparing to patients from Malaysia (5-year and 10-year predicted-observed= 5.8% and 8.0% respectively), as well as for patients diagnosed in more recent years. The AUC for 5-year and 10-year overall survival was 0.77 (95% CI: 0.75-0.79) and 0.74 (95% CI: 0.71-0.76). For cases with relatively good and moderate prognosis, CancerMath predictions were similar to observed outcome as the plotted dots in the calibration plot were close to the 45 degree reference line from the fourth decile onwards. For therapy calculator, overestimation of survival persisted for most demographic, pathologic and treatment subgroups, especially for women younger than 40 years, with larger and high-grade tumor and with more lymph nodes involved. The AUC for 5-year overall survival is 0.73 (95% CI: 0.70-0.77). And with the exception of two groups, all plotted dots were below the 45 degree reference line in the calibration plot . Conclusion: The discriminative performance and calibration of CancerMath was fair in this validation study. The greater discordance observed in Malaysian patients might be explained by different life expectancy, adverse tumor characteristics, compliance to treatment and lifestyle after diagnosis between Singapore, Malaysia and United States. The results suggested that direct application of CancerMath should only be limited to certain subgroups in Southeast Asia. Citation Format: Nur Aishah Taib, Hui Miao, Helena M Verkooijen, Mikael Hartman, Hoong-Seam Wong, Cheng-Har Yip, Ern-Yu Tan, Soo-Chin Lee, Nirmala Bhoo-Pathy. Validation of the CancerMath prognostic tool for breast cancer in Southeast Asia [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-34.

Abstract 5332: MicroRNA profile of triple-negative breast cancer and prognosis.

Abstract Background: Triple-negative breast cancer (TNBC, estrogen receptor [ER]-, progesterone receptor [PR]-, and human epidermal growth factor receptor 2 [HER2]-negative) is often aggressive and lack molecular targets for therapy. As gene regulators, microRNAs (miRNA) are important in cancer etiology but their utility as tumor biomarkers for cancer diagnosis and prognosis is yet unclear. Methods: To characterize the differential expression pattern of miRNA in TNBC from non-TNBC, we performed a whole miRNome profiling using TaqMan based quantitative PCR array of 754 miRNAs constructed based on miRBase 19 (Life Technologies, CA). Total RNA was extracted from frozen breast tumors and only RNA samples with good quality were included in the array experiment. Rigorous post-experiment quality controls were further conducted to remove unreliable plates. Moderate t-test was used to identify TNBC-specific miRNAs and Cox proportional hazard model was used to explore miRNAs that predict progression-free survival. Benjamini and Hochberg's false discovery rate method was used to correct for multiple testing. Results: Samples from 85 patients were included in the final analysis, including 71 Caucasians, 7 African Americans, and 7 others. The average age (±SD) was 54.9 ± 9.1 years. 17 patients had stage 1 tumor, 30 stage 2A, 26 stage 2B, 7 stage 3A, and 5 stage 3B. There were 42 samples with ER+, 37 PR+, 25 HER2+, and 25 categorized as TNBC. 363 out of 754 miRNAs showed expression in at least half of the samples and were included for further analysis. Of the 363 miRNAs, we found 98 to be significantly different between TNBC and non-TNBC after multiple testing correction. The most significant miRNA (miR-190b) was down-regulated in TNBC by about 20-fold (p=1.6x10-9). In fact, most of these miRNAs are down-regulated in TNBC compared to non-TNBC. During a median follow-up of 10.9 years, 29 patients died and 7 patients survived but had progressive disease of breast cancer. After multiple testing correction, we found 6 miRNAs showing significant association with progression-free survival. Interestingly, none of these 6 miRNAs were related to TNBC, suggesting that their prognostic value is independent of breast cancer subtypes. Conclusion: Our study demonstrates the existence of a set of miRNAs specific to TNBC, which has a clear “fingerprint” to differentiate TNBC from non-TNBC. We also identified different set of miRNAs that could serve as prognostic markers. Despite the small sample set, our results promisingly indicate the potential of miRNA as diagnostic and prognostic tool for breast cancer. A replication study with larger sample size would be in order. Citation Format: Toshio F. Yoshimatsu, Katharine Yao, Karen Kaul, Mary A. Turk, Olufunmilayo I. Olopade, Dezheng Huo. MicroRNA profile of triple-negative breast cancer and prognosis. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5332. doi:10.1158/1538-7445.AM2013-5332

Comparison of visual and automated assessment of microvessel density and their impact on outcome in primary operable invasive ductal breast cancer

Angiogenesis is essential for tumor growth and metastasis, and several studies have reported increased angiogenesis, as quantified by microvessel density, to be a powerful prognostic tool in breast cancer. Therefore, there is considerable interest in automated assessment of microvessel density with possible benefits in improved accuracy, increased precision, and handling workload. Visual and automated assessment of microvessel density (CD34(+)) and survival were examined in patients with primary operable invasive ductal breast cancer. Tissue microarrays (n = 356 patients) immunostained for microvessel density (CD34(+)) were scored visually and automatically with the Slidepath Tissue IA system (Dublin, Ireland). Visual and automated microvessel density (CD34(+)) were in agreement (interclass correlation coefficient = 0.69, P < .001). Visual but not the automated method for microvessel density (CD34(+)) was associated with locoregional treatment and metastasis. On univariate survival analysis, visual but not automated method for microvessel density (CD34(+)) was associated with recurrence-free and cancer-specific survival in patients with invasive ductal breast cancer (P < .01). Although automated assessment of microvessel density (CD34(+)) is in reasonable agreement, it poorly predicts outcome in patients with operable invasive ductal breast cancer.

Abstract 3489: In silico analysis of angiogenesis pathway as a prognostic tool in breast cancer

Abstract Gene expression profiling studies have enabled us to study breast cancer biology at a molecular level. Studies have been geared at identifying better and comprehensive prognostic markers for the development of targeted therapeutics. With the growing use of anti-angiogenic agents as second line agents, we aim to study the prognostic role of angiogenesis related genes through retrospective analyses of publicly available breast cancer gene expression datasets. Three gene expression datasets from studies by van't Veer et al, Sorlie et al., and Sotiriou et al were analyzed. The data was downloaded from the BRB Array Tools archives and analyzed using BRB Array Tools. Since, we were particularly interested in genes related to angiogenesis; we selected the (CGAP) angiogenesis subset for the purpose of survival analyses. Two endpoints, overall survival (OS) and relapse free survival (RFS), were analyzed. Data for OS was not available for van't Veer et al. A subset analysis for estrogen receptor positive cases was performed. HIF1A was prognostic for OS and RFS in all datasets. VEGF was associated with survival only in ER+ cases. EGFR is prognostic for RFS but not OS. Several other angiogenesis genes were noted to affect prognosis in terms of OS and RFS (Table 1). Analysis of other publically available datasets will be undertaken to further validate these findings in ER+ and negative subgroups of breast cancer. These analyses highlight the importance of VEGF as an important marker among ER+ breast cancer patients. Thus, anti-angiogenic agents targeting VEGF may appear to play an important therapeutic role in this subset of patients. The analysis provides additional evidence of the importance of HIF1A in breast cancer. This may help identifying sub-populations of breast cancer that are most likely to respond to targeted therapies. Further immunohistochemical validation in in-vitro models will be performed. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3489. doi:10.1158/1538-7445.AM2011-3489

Abstract P3-10-02: Circulating miRNA Signature: Potential Screening and Prognostic Tool for Breast Cancer

Abstract Introduction: Genetic profiling of breast tumors revolutionized the classification of breast cancer and unravelled the complexity of this phenotypically diverse disease. However there appears to be discordance between the various mRNA-based single sample predictors which stratify tumors into subgroups. Clinical decision making based on a tumor's mRNA expression is therefore concerning. The potential of mi(cro) RNAs as novel tumor markers has been the focus of recent scrutiny due to their tissue specificity, stability and superiority to mRNA in tumor classification. Additionally, the ability to quantify tumor-associated miRNAs in the circulation and their correlations with clinicopathologic variables, highlights their potential to improve upon existing breast tumor classification methods. Systemic miR-195 and let-7a have been shown to hold properties as breast tumor markers. The aim of this study was to identify a larger panel of miRNAs which augment the sensitivity and specificity of circulating miRNAs as diagnostic and prognostic markers for breast cancer. Methods: The expression levels of 9 miRNAs were evaluated in 345 preoperative cancer patients including 265 breast cancers and 80 non-breast malignancies, and 63 age-matched disease-free controls using RQ-PCR. MiRNA quantification was also performed on tumor tissue from 83 age and stage matched breast cancer patients. Advanced QBase Plus software and SPSS were used for biostatistical analysis of the data and correlation with clinicopathologic variables. Results: This study confirmed significantly deranged expression levels of systemic miR-195 and let-7a in an independent validation cohort of breast cancer patients (p &amp;lt; 0.001 and p &amp;lt; 0.001 respectively). In addition miR-181c and miR-342 were identified as breast cancer specific biomarkers. Elevated levels of this 4-miRNA signature in breast cancer patients, including those with in-situ carcinoma, increased the discriminatory power of this test for breast cancer (all types) to 94% (P&amp;lt;0.001). Circulating levels of these 4 miRNAs correlated with tumor miRNA expression, and decreased to basal levels by 2 weeks following curative tumor resection. Additionally circulating miRNA levels correlated with clinicopathological variables such as tumor size and hormone receptor status. A subset of 2 systemic miRNAs was predictive of the Luminal A subtype of breast cancer (ER/PR positive, Her2/neu negative) with 91% accuracy. Conclusion: This study validates the recent novel finding of dysregulated tumor-specific miRNAs in the circulation of breast cancer patients. Considering that the sensitivity of mammography is 75-90%, this circulating miRNA signature could improve upon existing breast cancer screening methods, given that it was significantly altered even in patients with in-situ carcinoma. These results indicate that circulating miRNA analysis holds immense potential in the future individualized management of breast cancer patients. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P3-10-02.

Prognostic contribution of the HER-2 oncogene overexpression to the Nottingham Prognostic Index in breast cancer

The Nottingham prognostic index (NPI) is a widely adopted prognostic tool in breast cancer. The HER-2 oncogene overexpression is also associated with higher risk. The aim of our study is to investigate the correlation between the NPI and HER-2 in breast cancer. Two hundred and five patients with breast cancer managed in the Department of Surgery, University of Hong Kong Medical Centre, at Queen Mary Hospital between January 1995 and December 1997 were studied. This is a retrospective analysis of prospectively collected database. Variables evaluated for the analysis of prognostic significance included tumor size, axillary lymph node status, histological grade, estrogen and progesterone receptor status and HER-2 oncogene expression. NPI was calculated from tumor size, lymph node status and histological grade. In univariate analysis, tumor size, axillary lymph node status, distant metastasis status, HER-2 oncogene overexpression and NPI score were found to be significant variables. Significant poorer overall survival was also observed with higher NPI category and positive HER-2. Only tumor size and NPI category with subdivision by HER-2 status were independent factors in multivariate analysis . The combination of the HER-2 oncogene expression status with the widely adopted NPI provides a reliable way to predict prognosis in breast cancer patients.

Quality of life assessment as a prognostic tool in breast cancer

6122 Background: While the use of quality of life (QoL) assessments has been increasing in the clinical oncology community, few studies have examined the prognostic significance of QoL in breast cancer. To examine this issue, we investigated the association between baseline QoL and survival in breast cancer. Methods: A case series of 105 patients with stages I-IV breast cancer treated at Cancer Treatment Centers of America® at Midwestern Regional Medical Center between March 2001 and October 2003 were included in this study. QoL was evaluated using the EORTC QLQ-C30 (EORTC) and the Ferrans and Powers Quality of Life Index (QLI). Patients were dichotomized into two groups based on the median scores for all QoL domains. Kaplan Meier method was used to evaluate survival. Log-Rank test was used to study the equality of survival distributions across strata. Results: Patients with QLI health function scores above the median (17.65) had an overall median survival of 22.8 months, compared to those with scores below the median, 15.74 months (p = 0.004). Similarly, patients with global health EORTC scores above the median (58.33) had an overall median survival of 23.21 months compared to 11.57 months for those with scores below the median (p=0.002). Both associations retained statistical significance even after controlling for tumor stage (QLI health function, p = 0.003 and EORTC global health, p = 0.001). Conclusion: This study suggests that baseline QoL can provide useful prognostic information in breast cancer. Further studies should focus on more extensive evaluation of the prognostic significance of QoL in the cancer treatment setting. No significant financial relationships to disclose.

Quality of life assessment as a prognostic tool in breast cancer

6122 Background: While the use of quality of life (QoL) assessments has been increasing in the clinical oncology community, few studies have examined the prognostic significance of QoL in breast cancer. To examine this issue, we investigated the association between baseline QoL and survival in breast cancer. Methods: A case series of 105 patients with stages I-IV breast cancer treated at Cancer Treatment Centers of America® at Midwestern Regional Medical Center between March 2001 and October 2003 were included in this study. QoL was evaluated using the EORTC QLQ-C30 (EORTC) and the Ferrans and Powers Quality of Life Index (QLI). Patients were dichotomized into two groups based on the median scores for all QoL domains. Kaplan Meier method was used to evaluate survival. Log-Rank test was used to study the equality of survival distributions across strata. Results: Patients with QLI health function scores above the median (17.65) had an overall median survival of 22.8 months, compared to those with scores below the median, 15.74 months (p = 0.004). Similarly, patients with global health EORTC scores above the median (58.33) had an overall median survival of 23.21 months compared to 11.57 months for those with scores below the median (p=0.002). Both associations retained statistical significance even after controlling for tumor stage (QLI health function, p = 0.003 and EORTC global health, p = 0.001). Conclusion: This study suggests that baseline QoL can provide useful prognostic information in breast cancer. Further studies should focus on more extensive evaluation of the prognostic significance of QoL in the cancer treatment setting. No significant financial relationships to disclose.

A principal component analysis of patients, disease and treatment variables: a new prognostic tool in breast cancer after mastectomy

Purpose To demonstrate unique information potential of a powerful multivariate data processing method, principal component analysis (PCA), in detecting complex interrelationships between diverse patient, disease and treatment variables and in prognostication of therapy's outcome and response of patients after mastectomy. Patients and Methods One hundred-forty-two patients with breast cancer were retrospectively evaluated. The patients were selected from a group of 201 patients who had been treated and observed in the same oncology ward. The selection was based on availability of complete set of information describing each patient. The set consisted of 60 specific data. A matrix of 142 × 60 data points was subjected to PCA using a professional, statistical software (commercially available) and a personal computer. Results Two principal components, PC1 and PC2, were extracted. They accounted for 26% of total data variance. Projections of 60 variables and 142 patients were made on a plane determined by PC1 and PC2. A clear clustering of the variables and of the patients was observed. It was discussed in terms of similarity (dissimilarity) of the variables and the patients, respectively. A strikingly clear separation was demonstrated to exist between the group of patients living over 7 years after mastectomy and the group of deceased patients. Conclusion PCA offers a new promising alternative of statistical analysis of multivariable data on cancer patients. Using the PCA, potentially useful information on both the factors affecting treatment outcome and general prognosis, may be extracted from large data sets.

Independent Prognostic Factors in Breast Cancer Patients

Background: Recently tumor microvessel density has been shown to be a powerful prognostic tool in breast cancer. We attempted to assess its significance as a prognostic factor. Methods: We analyzed the medical records of 100 patients using univariate and multivariate analyses of nine factors as follows; age, tumor size, nodal status, estrogen receptor, C-erbB2, p53, microvessel density, DNA ploidy pattern, and S-phase fraction. Results: Nodal status and microvessel density were independent prognostic indicators for both survival and relapse-free survival. Microvessel density was independent in the node-negative subgroup for survival, but not independent in the node-positive subgroup, while it was independent in both the node-negative and node-positive subgroups for relapse-free survival. Short-term survival rates in the high and low vessel density subgroups were almost the same, and all patients with early death were node-positive. Conclusion: Microvessel density was an important prognostic factor especially in node-negative patients and more significant in long-term survival.