Prognostic role of c-met expression in breast cancer patients

Background

Hepatocyte growth factor plays an important role in tumor growth, metastasis and angiogenesis. C-met is HGF''s high affinity receptor.

Aim

The aim of the study was to assess the correlations between c-met expression and clinic-pathological factors in breast cancer tissues. Furthermore, the purpose of the study was to evaluate the prognostic value of the hepatocyte growth factor receptor (HGFR, c-met) expressions in homogenous group of breast cancer patients.

Materials and methods

Tumor samples were collected from 302 patients with breast carcinoma treated with primary surgery. We have assessed the percentage of tumor cells with c-met expression, the intensity of reaction and the ratio of these two factors—immunoreactivity according to the Remmele score.

Results

We have observed no correlations between HGFR immunoreactivities and clinical parameters (tumor size, grade, axillary lymph node status, age). In 5-year observation we have found prognostic value of assessing c-met immunoreactivity in primary tumor.

Conclusion

Our study has revealed prognostic value of c-met. Unlike in other authors’ studies, our patients’ group is very homogenous which might contribute to obtained results.     

CD1d-expressing breast cancer cells modulate NKT cell-mediated antitumor immunity in a murine model of breast cancer metastasis

Background

Tumor tolerance and immune suppression remain formidable obstacles to the efficacy of immunotherapies that harness the immune system to eradicate breast cancer. A novel syngeneic mouse model of breast cancer metastasis was developed in our lab to investigate mechanisms of immune regulation of breast cancer. Comparative analysis of low-metastatic vs. highly metastatic tumor cells isolated from these mice revealed several important genetic alterations related to immune control of cancer, including a significant downregulation of cd1d1 in the highly metastatic tumor cells. The cd1d1 gene in mice encodes the MHC class I-like molecule CD1d, which presents glycolipid antigens to a specialized subset of T cells known as natural killer T (NKT) cells. We hypothesize that breast cancer cells, through downregulation of CD1d and subsequent evasion of NKT-mediated antitumor immunity, gain increased potential for metastatic tumor progression.

Methodology/Principal Findings

In this study, we demonstrate in a mouse model of breast cancer metastasis that tumor downregulation of CD1d inhibits iNKT-mediated antitumor immunity and promotes metastatic breast cancer progression in a CD1d-dependent manner in vitro and in vivo. Using NKT-deficient transgenic mouse models, we demonstrate important differences between type I and type II NKT cells in their ability to regulate antitumor immunity of CD1d-expressing breast tumors.

Conclusions/Significance

The results of this study emphasize the importance of determining the CD1d expression status of the tumor when tailoring NKT-based immunotherapies for the prevention and treatment of metastatic breast cancer.     

Mediterranean Dietary Pattern and Risk of Breast Cancer

Background

A Mediterranean diet has a recognized beneficial effect on health and longevity, with a protective influence on several cancers. However, its association with breast cancer risk remains unclear.

Objective

We aimed to investigate whether adherence to a Mediterranean dietary pattern influences breast cancer risk.

Design

The Swedish Women’s Lifestyle and Health cohort study includes 49,258 women aged 30 to 49 years at recruitment in 1991–1992. Consumption of foods and beverages was measured at enrollment using a food frequency questionnaire. A Mediterranean diet score was constructed based on the consumption of alcohol, vegetables, fruits, legumes, cereals, fish, the ratio of unsaturated to saturated fat, and dairy and meat products. Relative risks (RR) for breast cancer and specific tumor characteristics (invasiveness, histological type, estrogen/progesterone receptor status, malignancy grade and stage) associated with this score were estimated using Cox regression controlling for potential confounders.

Results

1,278 incident breast cancers were diagnosed. Adherence to a Mediterranean dietary pattern was not statistically significantly associated with reduced risk of breast cancer overall, or with specific breast tumor characteristics. A RR (95% confidence interval) for breast cancer associated with a two-point increment in the Mediterranean diet score was 1.08 (1.00–1.15) in all women, and 1.10 (1.01–1.21) and 1.02 (0.91–1.15) in premenopausal and postmenopausal women, respectively. When alcohol was excluded from the Mediterranean diet score, results became not statistically significant.

Conclusions

Adherence to a Mediterranean dietary pattern did not decrease breast cancer risk in this cohort of relatively young women.     

Preoperative Measurement of Breast Cancer Overestimates Tumor Size Compared to Pathological Measurement

Background

Tumor size is one of the most important factors in making clinical and pathological assessment of breast cancer. In the present study, we aimed to determine whether the preoperative measurement of tumor size, by imaging modalities, deviate from the postoperative pathological measurement in breast cancer.

Patients and Methods

1296 patients diagnosed with invasive ductal breast carcinoma (IDC) during 2007 and 2009 were involved. Pre- and postoperative measurements of tumor size were compared using paired t-test and Chi-square test.

Results

The mean maximum diameters of tumors by imaging modalities and pathology were 27.9 mm and 22.4 mm, respectively. There was a statistically significant difference of 5.5 mm (95% CI: 4.7–6.2, p<0.001) between them. The discordance between pre- and post-surgical measurements of tumor size had significant effect on choosing surgery type, causing less application of breast conserving therapy (p<0.0001).

Conclusion

Compared to pathological size, preoperative measurement by imaging modalities tends to overestimate tumor size. These differences could have implications in the treatment of patients with breast cancer.     

XRCC3 and RAD51 Expression Are Associated with Clinical Factors in Breast Cancer

Aims

XRCC3 and RAD51 are two important members in homologous recombination repair pathway. This study was performed to detect the expressions of these two molecules in breast cancer and explore their correlations with clinicopathological factors.

Methods and Results

Immunohistochemistry was used to detect protein expressions of XRCC3 and RAD51 in 248 cases of breast cancer tissue and 78 cases of adjacent non-cancerous tissue. Data showed that expressions for both XRCC3 and RAD51 were significantly increased in breast cancer. High XRCC3 expression was associated with large tumor size and positive PR and HER2 status, while high RAD51 expression was associated with axillary lymph node metastasis and positive PR and HER2 status. The result of multivariate analysis demonstrated that HER2, PR and RAD51 were significantly association with XRCC3. And besides XRCC3, axillary lymph node metastasis and PR were significantly correlated with RAD51.

Conclusions

XRCC3 and RAD51 were significantly associated with clinicopathological factors and they might play important roles in the development and progress of breast cancer.     

Effects of Ambient Particulate Matter on Human Breast Cancer: Is Xenogenesis Responsible?

Background

Recently, evidence from several studies has revealed that air pollution is associated with the increased morbidity and mortality of breast cancer patients. However, to date, the underlying mechanism remains largely unclear. Considering the high prevalence of air pollution and breast cancer in China, it is necessary to understand how air pollution may affect breast cancer.

Methods

We analyzed 1,832 female patients who had resided in the same cities for at least 10 years prior to their diagnosis. Variables including demographic data as well as clinical and tumor characteristics, including the patient’s age at menarche, family history of breast cancer, tumor histopathological type, tumor size, lymph node metastasis, distant metastasis, histological grade, estrogen receptor (ER) status, progesterone receptor (PR) status and human epidermal growth factor receptor 2 (HER-2) status at the time of diagnosis were analyzed.

Results

Compared to patients residing in low-pollution areas, patients living in high-pollution areas demonstrated a younger age at menarche (p<0.001), a greater family history of breast cancer (p = 0.034) and more invasive cancers (p = 0.028) with higher tumor grades (p = 0.028) and estrogen receptor (ER)-positive status (p = 0.022). Differences in tumor grade were only found in ER-positive cases.

Conclusions

Our findings and clinical data indicate that long-term air pollution exposure may contribute to the development of breast cancer by playing the role of a xenoestrogen, and also provides new insight into the association between air pollution and the morbidity and mortality of breast cancer patients. Furthermore, it is urgently necessary to study the association between air pollution and breast cancer to improve the living quality and health of females, and applicable public health strategies may need to be established or modified as soon as possible.     

Crossover Effects of Estrogen Receptor Status on Breast Cancer-Specific Hazard Rates by Age and Race

Background

Previous studies found that the risk of breast cancer–related death is greater in estrogen receptor (ER)-negative disease than in ER-positive disease within 5 years of diagnosis, but greater for ER-positive disease than for ER-negative disease more than 5 years after diagnosis. This phenomenon is referred to as ER-positive and -negative crossover. Our aim was to evaluate this crossover by determining the timing of the hazard of breast cancer death by patient, clinical, and tumor factors.

Methods

Patients with breast cancer diagnosed between 1990 and 2005 were identified from the Surveillance, Epidemiology, and End Results database. The cohort was evaluated by age at diagnosis, race, tumor ER status, tumor and nodal stage, and tumor grade. Disease-specific (DS) hazard rates were calculated.

Results

Of the 439,444 patients identified, 77.5% had ER-positive disease. Overall, ER-negative to ER-positive DS hazard rates crossed between the years 7 and 8 after diagnosis. Earlier crossover was linked to black or Hispanic race, young age (<40 years), or tumors that were larger, higher grade, or affected the nodes. Young black (<40 years) patients who had a T3/T4 tumor with positive nodes, grade III or undifferentiated, had the earliest crossover, in year 4.

Conclusions

The timing of crossover of death hazard for ER-positive and ER-negative disease varies by clinical and tumor factors. These findings may help guide recommendations regarding the duration of endocrine therapy for patients with ER-positive cancer.     

Minimising immunohistochemical false negative ER classification using a complementary 23 gene expression signature of ER status

Background

Expression of the oestrogen receptor (ER) in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC) or other immunoassays in which the ER expression level is compared to an empirical threshold[1], [2]. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome.

Methodology/Principal Findings

Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes whose expression was both strongly bimodal, mimicking ESR expression status, and highly expressed in breast epithelial cell lines, to derive a 23-gene ER expression signature-based classifier. We assessed our classifiers in seven published breast cancer cohorts by comparing the gene expression-based ER status to IHC-based ER status as a predictor of clinical outcome in both untreated and tamoxifen treated cohorts. In untreated breast cancer cohorts, the 23 gene signature-based ER status provided significantly improved prognostic power compared to IHC-based ER status (P = 0.006). In tamoxifen-treated cohorts, the 23 gene ER expression signature predicted clinical outcome (HR = 2.20, P = 0.00035). These complementary ER signature-based strategies estimated that between 15.1% and 21.8% patients of IHC-based negative ER status would be classified with ER positive breast cancer.

Conclusion/Significance

Expression-based ER status classification may complement IHC to minimise false negative ER status classification and optimise patient stratification for endocrine therapies.     

Socioeconomic Disparity in Breast Cancer Detection in Hong Kong – A High Income City: Retrospective Epidemiological Study Using the Breast Cancer Registry

Background

It is not known whether socioeconomic disparities affect the detection of breast cancer in Asian countries where the incidence of breast cancer is a rising trend. In this study, we explore the socioeconomic profiles of women and the stage of the disease at the time of diagnosis in breast cancer patients aged 40 or over in Hong Kong.

Method

During the period 2008 to 2011, 5393 breast cancer patients registered with the Hong Kong Breast Cancer Registry. Participants and their clinicians were asked to complete standardised questionnaires including patient socio-demographics, health history and risk factors, the course of the disease, post-treatment physical discomfort and psychosocial impact, follow-up recurrence and survival status.

Results

Monthly household incomes, educational levels and the practice of regular screening are independently associated with the stage of the disease at diagnosis. Higher socioeconomic status and a higher educational level were associated with an earlier stage of the disease at the time of diagnosis. Yearly clinical examinations, ultrasound and mammographic screening every 2 to 3 years were significantly associated with the earlier detection of breast cancer.

Conclusion

There were socioeconomic disparities among Hong Kong women who were found to have breast cancer. Population-based screening policies, including raising awareness among women at risk, should be implemented.     

HER-2 assessment in formalin-fixed paraffin-embedded breast cancer tissue by well-based reverse phase protein array

Background

The human epidermal growth factor receptor-2 (HER-2) expression level is a critical element for determining the prognosis and management of breast cancer. HER-2 targeted therapy in breast cancer depends on the reliable assessment of HER-2 expression status but current standard methods are lacking a rigorous quantitative assay. To address this challenge, we developed an assessment of HER-2 expression method by well-based reverse phase protein array (RPPA).

Results

Well-based RPPA is based on a robust protein isolation methodology paired with a novel electrochemiluminescence detection system. HER-2 value of well-based RPPA significantly correlated with dot blotting results (R² = 0.939). By well-based RPPA, we successfully detected HER-2 expression in 76 human breast formalin-fixed paraffin-embedded tissue samples. We observed 93.4% (71/76) concordance between well-based RPPA and current HER-2 immunohistochemical assessment guideline. When the cutoff level of HER-2 value was set to 0.689 (HER-2/GAPDH) on the basis of receiver-operating characteristic curve, the area under the curve was 0.975 (95% CI, 0.941-1.000). Sensitivity and specificity of well-based RPPA was 92.1% and 94.7%, respectively.

Conclusions

HER-2 value by well-based RPPA was correlated with the current HER-2 status guideline, suggesting that this normalized HER-2 assessment may offer advantages over unnormalized current immunohistochemical assessment methods.     

The G Protein-Coupled Estrogen Receptor (GPER) Is Expressed in Two Different Subcellular Localizations Reflecting Distinct Tumor Properties in Breast Cancer

Introduction

The G protein-coupled estrogen receptor (GPER) is a novel estrogen receptor that mediates proliferative effects induced by estrogen but also by tamoxifen. The aim of our study was to analyze the frequency of GPER in a large collective of primary invasive breast carcinomas, with special emphasis on the subcellular expression and to evaluate the association with clinicopathological parameters and patient overall survival.

Methods

The tissue microarrays from formalin-fixed, paraffin embedded samples of primary invasive breast carcinomas (n = 981) were analyzed for GPER expression using immunohistochemistry. Expression data were compared to the clinicopathological parameters and overall survival. GPER localization was also analyzed in two immortalized breast cancer cell lines T47D and MCF7 by confocal immunofluorescence microscopy.

Results

A predominantly cytoplasmic GPER expression was found in 189 carcinomas (19.3%), whereas a predominantly nuclear expression was observed in 529 cases (53.9%). A simultaneous comparable positive expression of both patterns was found in 32 of 981 cases (3.2%), and negative staining was detected in 295 cases (30%). Confocal microscopy confirmed the occurrence of cytoplasmic and nuclear GPER expression in T47D and MCF7. Cytoplasmic GPER expression was significantly associated with non-ductal histologic subtypes, low tumor stage, better histologic differentiation, as well as Luminal A and B subtypes. In contrast, nuclear GPER expression was significantly associated with poorly differentiated carcinomas and the triple-negative subtype. In univariate analysis, cytoplasmic GPER expression was associated with better overall survival (p = 0.012).

Conclusion

Our data suggest that predominantly cytoplasmic and/or nuclear GPER expression are two distinct immunohistochemical patterns in breast carcinomas and may reflect different biological features, reason why these patterns should be clearly distinguished in histological evaluations. Prospective studies will be needed to assess whether the expression status of GPER in breast carcinomas should be routinely observed by clinicians, for instance, before implementing endocrine breast cancer treatment.     

Insecurities of Women Regarding Breast Cancer Research: A Qualitative Study

Objectives

Only 1.2%–11% of all potential study participants participate in cancer studies. Low participation rates can result in bias or in a failure to obtain data saturation. Subject-scientific psychology assumes that reasons for acting are based on individual premises. The objective of this study was to render reproducible individual reasons of female breast cancer patients to participate or not participate in breast cancer studies using a qualitative approach.

Methods

Problem-based interviews were conducted with female breast cancer patients. The selection of interview partners continued until theoretical data saturation was achieved.

Results

As main arguments against participation emotional overload and too many medication side-effects were stated. Improvement of health-related values, long-term protection and comprehensive follow-up exams were stated as arguments for participation. Trust in the attending physician was mentioned as influencing both participation and non-participation.

Conclusions

A significant influential factor determining willingness to participate in studies was one''s contentment with patient-physician communication. In order to guarantee an adequate patient decision-making process, keeping existing standards for patient briefings is absolutely mandatory.     

Preliminary experience in sentinel node and occult lesion localization (SNOLL) technique—One center study

Aim

The aim of this study was to present one center experience in applying the SNOLL technique to patients with suspected occult breast lesions.

Background

In the last years, the widespread use of mammographic screening programs resulted in an increasing number of women with nonpalpable suspicious breast lesions requiring further examination. The new method called sentinel node and occult lesion localization (SNOLL) enables the intraoperative detection of nonpalpable breast tumors and sentinel node biopsy in one surgical procedure.

Materials and methods

46 patients with suspected malignant lesions or diagnosed non-palpable breast cancer were subjected to a pre-operative SNOLL procedure. The day before the surgery, they were administered two radiotracers: one to localize the tumor and the other to localize the sentinel node. During the surgery, the breast tumor and the sentinel node, which in most cases had been examined intraoperatively, were detected with a handheld gamma probe and resected under its control.

Results

All 46 (100%) patients had their occult breast lesions resected. Histopathologic examination revealed cancer in 40 patients: in situ in 2 cases, invasive in 38 cases. All these patients had their sentinel nodes examined. In one case only, the sentinel node could not be located with a gamma probe. Intraoperative tests showed the sentinel node to be metastatic in 5 patients, who were then given a simultaneous axillary lymphadenectomy. In addition, the final histopathologic examination revealed metastasis to the sentinel node in one patient, who had to be reoperated.

Conclusion

SNOLL is a modern technique that enables a precise intraoperative localization of non-palpable suspected malignant breast lesions in combination with a sentinel node biopsy. Extended application of intraoperative management leads to significant decrease in the number of reoperations performed in patients with early bread cancer.     

Circulating Tumor Cells Count and Morphological Features in Breast,Colorectal and Prostate Cancer

Background

Presence of circulating tumor cells (CTC) in patients with metastatic breast, colorectal and prostate cancer is indicative for poor prognosis. An automated CTC (aCTC) algorithm developed previously to eliminate the variability in manual counting of CTC (mCTC) was used to extract morphological features. Here we validated the aCTC algorithm on CTC images from prostate, breast and colorectal cancer patients and investigated the role of quantitative morphological parameters.

Methodology

Stored images of samples from patients with prostate, breast and colorectal cancer, healthy controls, benign breast and colorectal tumors were obtained using the CellSearch system. Images were analyzed for the presence of aCTC and their morphological parameters measured and correlated with survival.

Results

Overall survival hazard ratio was not significantly different for aCTC and mCTC. The number of CTC correlated strongest with survival, whereas CTC size, roundness and apoptosis features reached significance in univariate analysis, but not in multivariate analysis. One aCTC/7.5 ml of blood was found in 7 of 204 healthy controls and 9 of 694 benign tumors. In one patient with benign tumor 2 and another 9 aCTC were detected.

Significance of the study

CTC can be identified and morphological features extracted by an algorithm on images stored by the CellSearch system and strongly correlate with clinical outcome in metastatic breast, colorectal and prostate cancer.     

Bayesian neural networks for detecting epistasis in genetic association studies

Background

Discovering causal genetic variants from large genetic association studies poses many difficult challenges. Assessing which genetic markers are involved in determining trait status is a computationally demanding task, especially in the presence of gene-gene interactions.

Results

A non-parametric Bayesian approach in the form of a Bayesian neural network is proposed for use in analyzing genetic association studies. Demonstrations on synthetic and real data reveal they are able to efficiently and accurately determine which variants are involved in determining case-control status. By using graphics processing units (GPUs) the time needed to build these models is decreased by several orders of magnitude. In comparison with commonly used approaches for detecting interactions, Bayesian neural networks perform very well across a broad spectrum of possible genetic relationships.

Conclusions

The proposed framework is shown to be a powerful method for detecting causal SNPs while being computationally efficient enough to handle large datasets.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0368-0) contains supplementary material, which is available to authorized users.     

Label-Free Delineation of Brain Tumors by Coherent Anti-Stokes Raman Scattering Microscopy in an Orthotopic Mouse Model and Human Glioblastoma

Background

Coherent anti-Stokes Raman scattering (CARS) microscopy provides fine resolution imaging and displays morphochemical properties of unstained tissue. Here, we evaluated this technique to delineate and identify brain tumors.

Methods

Different human tumors (glioblastoma, brain metastases of melanoma and breast cancer) were induced in an orthotopic mouse model. Cryosections were investigated by CARS imaging tuned to probe C-H molecular vibrations, thereby addressing the lipid content of the sample. Raman microspectroscopy was used as reference. Histopathology provided information about the tumor''s localization, cell proliferation and vascularization.

Results

The morphochemical contrast of CARS images enabled identifying brain tumors irrespective of the tumor type and properties: All tumors were characterized by a lower CARS signal intensity than the normal parenchyma. On this basis, tumor borders and infiltrations could be identified with cellular resolution. Quantitative analysis revealed that the tumor-related reduction of CARS signal intensity was more pronounced in glioblastoma than in metastases. Raman spectroscopy enabled relating the CARS intensity variation to the decline of total lipid content in the tumors. The analysis of the immunohistochemical stainings revealed no correlation between tumor-induced cytological changes and the extent of CARS signal intensity reductions. The results were confirmed on samples of human glioblastoma.

Conclusions

CARS imaging enables label-free, rapid and objective identification of primary and secondary brain tumors. Therefore, it is a potential tool for diagnostic neuropathology as well as for intraoperative tumor delineation.     

Household Income Is Associated with the p53 Mutation Frequency in Human Breast Tumors

Background

A study from Scotland reported that the p53 mutation frequency in breast tumors is associated with socio-economic deprivation.

Methods

We analyzed the association of the tumor p53 mutational status with tumor characteristics, education, and self-reported annual household income (HI) among 173 breast cancer patients from the greater Baltimore area, United States.

Results

p53 mutational frequency was significantly associated with HI. Patients with < $15,000 HI had the highest p53 mutation frequency (21%), followed by the income group between $15,000 and $60,000 (18%), while those above $60,000 HI had the fewest mutations (5%). When dichotomized at $60,000, 26 out of 135 patients in the low income category had acquired a p53 mutation, while only 2 out of 38 with a high income carried a mutation (P < 0.05). In the adjusted logistic regression analysis with 3 income categories (trend test), the association between HI and p53 mutational status was independent of tumor characteristics, age, race/ethnicity, tobacco smoking and body mass. Further analyses revealed that HI may impact the p53 mutational frequency preferentially in patients who develop an estrogen receptor (ER)-negative disease. Within this group, 42% of the low income patients (< $15,000 HI) carried a mutation, followed by the middle income group (21%), while those above $60,000 HI did not carry mutations (P _trend < 0.05).

Conclusions:

HI is associated with the p53 mutational frequency in patients who develop an ER-negative disease. Furthermore, high income patients may acquire fewer p53 mutations than other patients, suggesting that lifetime exposures associated with socio-economic status may impact breast cancer biology.     

Association between SPARC mRNA Expression,Prognosis and Response to Neoadjuvant Chemotherapy in Early Breast Cancer: A Pooled in-silico Analysis

Introduction

SPARC is an important regulator of the extracellular matrix and has been suggested to improve delivery of albumin-bound cytotoxics. However, little is known regarding its role in breast cancer (BC).

Methods

We conducted a pooled analysis of publically available datasets, in which BC patients who received no systemic therapy or received neoadjuvant chemotherapy were eligible. Patients were assigned to molecular subtypes using PAM-50. We computed a SPARC module (SPARC7), composed of genes with an absolute correlation with SPARC >0.7. In the systemically untreated cohort, we evaluated 1) expression of SPARC/SPARC7 according to breast cancer subtype, 2) association between SPARC/SPARC7 and biological processes related to proliferation, immune and stroma, and 3) association between SPARC/SPARC7 and relapse-free survival in a Cox model in all patients and in the different molecular subtypes adjusted for tumor size, nodal status, histological grade, and age. In the neoadjuvant cohort, we evaluated the association between SPARC and pCR in a logistic regression model, adjusted for the same clinicopathologic factors.

Results

948 (10 datasets), and 791 (8 datasets) patients were included in the systemically untreated and neoadjuvant cohorts, respectively. High SPARC expression was associated with small tumor size, low histological grade and luminal-A tumors (all p<0.0001). There was a positive correlation between SPARC and stroma-related modules but negative correlation with proliferation modules. High SPARC expression was associated with poor prognosis in patients with basal and HER2+ breast cancer even after adjusting for clinicopathologic parameters. In the neoadjuvant cohort, a subgroup analysis suggested that high SPARC is associated with low rates of pCR in the HER2 subtype. Same results were observed on replacing SPARC by SPARC7.

Conclusion

This analysis suggests a potential role of SPARC in determining prognosis and response to primary chemotherapy in early BC. This information could guide further development of albumin-bound cytotoxics in BC.     

Predicting breast cancer using an expression values weighted clinical classifier

Background

Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier.LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.

Results

We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies.

Conclusions

Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems.