Gene Expression Signatures That Predict Outcome of Tamoxifen-Treated Estrogen Receptor-Positive,High-Risk,Primary Breast Cancer Patients: A DBCG Study

Background

Tamoxifen significantly improves outcome for estrogen receptor-positive (ER+) breast cancer, but the 15-year recurrence rate remains 30%. The aim of this study was to identify gene profiles that accurately predicted the outcome of ER+ breast cancer patients who received adjuvant Tamoxifen mono-therapy.

Methodology/Principal Findings

Post-menopausal breast cancer patients diagnosed no later than 2002, being ER+ as defined by >1% IHC staining and having a frozen tumor sample with >50% tumor content were included. Tumor samples from 108 patients treated with adjuvant Tamoxifen were analyzed for the expression of 59 genes using quantitative-PCR. End-point was clinically verified recurrence to distant organs or ipsilateral breast. Gene profiles were identified using a model building procedure based on conditional logistic regression and leave-one-out cross-validation, followed by a non-parametric bootstrap (1000x re-sampling). The optimal profiles were further examined in 5 previously-reported datasets containing similar patient populations that were either treated with Tamoxifen or left untreated (n = 623). Three gene signatures were identified, the strongest being a 2-gene combination of BCL2-CDKN1A, exhibiting an accuracy of 75% for prediction of outcome. Independent examination using 4 previously-reported microarray datasets of Tamoxifen-treated patient samples (n = 503) confirmed the potential of BCL2-CDKN1A. The predictive value was further determined by comparing the ability of the genes to predict recurrence in an additional, previously-published, cohort consisting of Tamoxifen-treated (n = 58, p = 0.015) and untreated patients (n = 62, p = 0.25).

Conclusions/Significance

A novel gene expression signature predictive of outcome of Tamoxifen-treated patients was identified. The validation suggests that BCL2-CDKN1A exhibit promising predictive potential.     

Homogeneous datasets of triple negative breast cancers enable the identification of novel prognostic and predictive signatures

Background

Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.

Methodology/Principal Findings

We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).

Conclusions/Significance

Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures.     

Long-Term Prognostic Performance of Ki67 Rate in Early Stage,pT1-pT2, pN0, Invasive Breast Carcinoma

Background

Molecular signatures may become of use in clinical practice to assess the prognosis of breast cancers. However, although international consensus conferences sustain the use of these new markers in the near future, concerns remain about their degree of discordance and cost-effectiveness in different international settings. The present study aims to validate Ki67 as prognostic factor in a large cohort of early-stage (pT1–pT2, pN0) breast cancer patients.

Methods

456 patients treated in 1995–1996 were identified in the Institut Curie database. Ki67 (MIB1) was retrospectively assessed by immunohistochemistry for all cases. The prognostic value of this index was compared to that of histological grade (HG), Estrogen receptor (ER) and HER2 status. Distant disease free interval, loco-regional recurrence, time-lapse from first metastatic diagnosis to death were analyzed.

Results

All 456 patients were treated by lumpectomy plus axillary dissection and radiotherapy. 27 patients (5.9%) received systemic treatment. Tumors were classified as HG1 in 35%, HG2 in 42% and HG3 in 23% of cases. ER was expressed in 86% of the tumors, HER2 in 5% and 14% were triple negative. The median follow-up was 151 [5–191] months. Distant and loco-regional disease recurrences were observed in 16% and 18%, respectively. High (>20%) Ki67 rate [HR = 3 (1.8–4.8), p<10e−06] and HG3 [HR = 4.4 (2.2–8.6), p = 0.00002] were associated with an increased rate of distant relapse. In multivariate analysis, the Ki67 remained the only significant prognostic factor in the subgroups of ER positive HER2 negative [HR = 2.6 (1.5–4.6), p = 0.0006] and ER positive HER2 negative HG2 tumors [HR = 2.2 (1.01–4.8), p = 0.04].

Conclusions

We validate the prognosis value of the Ki67 rate in small size node negative breast cancer. We conclude that Ki67 is a potential cost-effective decision marker for adjuvant therapy in early-stage HG2, pT1–pT2, pN0, breast cancers.     

Adjusting Breast Cancer Patient Prognosis with Non-HER2-Gene Patterns on Chromosome 17

Background

HER2 and TOP2A gene status are assessed for diagnostic and research purposes in breast cancer with fluorescence in situ hybridization (FISH). However, FISH probes do not target only the annotated gene, while chromosome 17 (chr17) is among the most unstable chromosomes in breast cancer. Here we asked whether the status of specifically targeted genes on chr17 might help in refining prognosis of early high-risk breast cancer patients.

Methods

Copy numbers (CN) for 14 genes on chr17, 4 of which were within and 10 outside the core HER2 amplicon (HER2- and non-HER2-genes, respectively) were assessed with qPCR in 485 paraffin-embedded tumor tissue samples from breast cancer patients treated with adjuvant chemotherapy in the frame of two randomized phase III trials.

Principal Findings

HER2-genes CN strongly correlated to each other (Spearman’s rho >0.6) and were concordant with FISH HER2 status (Kappa 0.6697 for ERBB2 CN). TOP2A CN were not concordant with TOP2A FISH status (Kappa 0.1154). CN hierarchical clustering revealed distinct patterns of gains, losses and complex alterations in HER2- and non-HER2-genes associated with IHC4 breast cancer subtypes. Upon multivariate analysis, non-HER2-gene gains independently predicted for shorter disease-free survival (DFS) and overall survival (OS) in patients with triple-negative cancer, as compared to luminal and HER2-positive tumors (interaction p = 0.007 for DFS and p = 0.011 for OS). Similarly, non-HER2-gene gains were associated with worse prognosis in patients who had undergone breast-conserving surgery as compared to modified radical mastectomy (p = 0.004 for both DFS and OS). Non-HER2-gene losses were unfavorable prognosticators in patients with 1–3 metastatic nodes, as compared to those with 4 or more nodes (p = 0.017 for DFS and p = 0.001 for OS).

Conclusions

TOP2A FISH and qPCR may not identify the same pathology on chr17q. Non-HER2 chr17 CN patterns may further predict outcome in breast cancer patients with known favorable and unfavorable prognosis.     

Hybrid Models Identified a 12-Gene Signature for Lung Cancer Prognosis and Chemoresponse Prediction

Background

Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35–50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.

Methodology/Principal Findings

From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.

Conclusions/Significance

The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs.     

A Thirteen-Gene Expression Signature Predicts Survival of Patients with Pancreatic Cancer and Identifies New Genes of Interest

Background

Currently, prognostication for pancreatic ductal adenocarcinoma (PDAC) is based upon a coarse clinical staging system. Thus, more accurate prognostic tests are needed for PDAC patients to aid treatment decisions.

Methods and Findings

Affymetrix gene expression profiling was carried out on 15 human PDAC tumors and from the data we identified a 13-gene expression signature (risk score) that correlated with patient survival. The gene expression risk score was then independently validated using published gene expression data and survival data for an additional 101 patients with pancreatic cancer. Patients with high-risk scores had significantly higher risk of death compared to patients with low-risk scores (HR 2.27, p = 0.002). When the 13-gene score was combined with lymph node status the risk-score further discriminated the length of patient survival time (p<0.001). Patients with a high-risk score had poor survival independent of nodal status; however, nodal status increased predictability for survival in patients with a low-risk gene signature score (low-risk N1 vs. low-risk N0: HR = 2.0, p = 0.002). While AJCC stage correlated with patient survival (p = 0.03), the 13-gene score was superior at predicting survival. Of the 13 genes comprising the predictive model, four have been shown to be important in PDAC, six are unreported in PDAC but important in other cancers, and three are unreported in any cancer.

Conclusions

We identified a 13-gene expression signature that predicts survival of PDAC patients and could prove useful for making treatment decisions. This risk score should be evaluated prospectively in clinical trials for prognostication and for predicting response to chemotherapy. Investigation of new genes identified in our model may lead to novel therapeutic targets.     

The CIN4 Chromosomal Instability qPCR Classifier Defines Tumor Aneuploidy and Stratifies Outcome in Grade 2 Breast Cancer

Purpose

Quantifying chromosomal instability (CIN) has both prognostic and predictive clinical utility in breast cancer. In order to establish a robust and clinically applicable gene expression-based measure of CIN, we assessed the ability of four qPCR quantified genes selected from the 70-gene Chromosomal Instability (CIN70) expression signature to stratify outcome in patients with grade 2 breast cancer.

Methods

AURKA, FOXM1, TOP2A and TPX2 (CIN4), were selected from the CIN70 signature due to their high level of correlation with histological grade and mean CIN70 signature expression in silico. We assessed the ability of CIN4 to stratify outcome in an independent cohort of patients diagnosed between 1999 and 2002. 185 formalin-fixed, paraffin-embedded (FFPE) samples were included in the qPCR measurement of CIN4 expression. In parallel, ploidy status of tumors was assessed by flow cytometry. We investigated whether the categorical CIN4 score derived from the CIN4 signature was correlated with recurrence-free survival (RFS) and ploidy status in this cohort.

Results

We observed a significant association of tumor proliferation, defined by Ki67 and mitotic index (MI), with both CIN4 expression and aneuploidy. The CIN4 score stratified grade 2 carcinomas into good and poor prognostic cohorts (mean RFS: 83.8±4.9 and 69.4±8.2 months, respectively, p = 0.016) and its predictive power was confirmed by multivariate analysis outperforming MI and Ki67 expression.

Conclusions

The first clinically applicable qPCR derived measure of tumor aneuploidy from FFPE tissue, stratifies grade 2 tumors into good and poor prognosis groups.     

Prevalence of Papillomaviruses,Polyomaviruses, and Herpesviruses in Triple-Negative and Inflammatory Breast Tumors from Algeria Compared with Other Types of Breast Cancer Tumors

Background

The possible role of viruses in breast cancer etiology remains an unresolved question. We hypothesized that if some viruses are involved, it may be in a subgroup of breast cancers only. Epidemiological arguments drove our interest in breast cancer subgroups that are more frequent in Africa, namely inflammatory breast cancer (IBC) and triple-negative breast cancer. We tested whether viral prevalence was significantly higher in these subgroups.

Materials and Methods

One hundred fifty-five paraffin-embedded malignant breast tumors were randomly selected at the pathology laboratory of the University Hospital of Annaba (Algeria) to include one third of IBC and two thirds of non-IBC. They were tested for the presence of DNA from 61 viral agents (46 human papillomaviruses, 10 polyomaviruses, and 5 herpesviruses) using type-specific multiplex genotyping assays, which combine multiplex PCR and bead-based Luminex technology.

Results

Viral DNA was found in 22 (17.9%) of 123 tumors. The most prevalent viruses were EBV1 and HPV16. IBC tumors carried significantly more viruses (any type) than non-IBC tumors (30% vs. 13%, p<0.04). Similarly, triple-negative tumors displayed higher virus-positivity than non-triple-negative tumors (44% vs. 14%, p<0.009).

Conclusions

Our results suggest an association between the presence of viral DNA and aggressive breast cancer phenotypes (IBC, triple-negative). While preliminary, they underline the importance of focusing on subgroups when studying viral etiology in breast cancer. Further studies on viruses in breast cancer should be conducted in much larger samples to confirm these initial findings.     

Selective Androgen Receptor Modulators (SARMs) Negatively Regulate Triple-Negative Breast Cancer Growth and Epithelial:Mesenchymal Stem Cell Signaling

Introduction

The androgen receptor (AR) is the most highly expressed steroid receptor in breast cancer with 75–95% of estrogen receptor (ER)-positive and 40–70% of ER-negative breast cancers expressing AR. Though historically breast cancers were treated with steroidal androgens, their use fell from favor because of their virilizing side effects and the emergence of tamoxifen. Nonsteroidal, tissue selective androgen receptor modulators (SARMs) may provide a novel targeted approach to exploit the therapeutic benefits of androgen therapy in breast cancer.

Materials and Methods

Since MDA-MB-453 triple-negative breast cancer cells express mutated AR, PTEN, and p53, MDA-MB-231 triple-negative breast cancer cells stably expressing wildtype AR (MDA-MB-231-AR) were used to evaluate the in vitro and in vivo anti-proliferative effects of SARMs. Microarray analysis and epithelial:mesenchymal stem cell (MSC) co-culture signaling studies were performed to understand the mechanisms of action.

Results

Dihydrotestosterone and SARMs, but not bicalutamide, inhibited the proliferation of MDA-MB-231-AR. The SARMs reduced the MDA-MB-231-AR tumor growth and tumor weight by greater than 90%, compared to vehicle-treated tumors. SARM treatment inhibited the intratumoral expression of genes and pathways that promote breast cancer development through its actions on the AR. SARM treatment also inhibited the metastasis-promoting paracrine factors, IL6 and MMP13, and subsequent migration and invasion of epithelial:MSC co-cultures.

Conclusion

1. AR stimulation inhibits paracrine factors that are important for MSC interactions and breast cancer invasion and metastasis. 2. SARMs may provide promise as novel targeted therapies to treat AR-positive triple-negative breast cancer.     

Prognostic Value of Metastatic Axillary Lymph Node Ratio for Chinese Breast Cancer Patients

Objective

The prevalence of breast cancer varies among countries and regions. This retrospective study investigated the prognostic value of the lymph node ratio (LNR) compared with the number of positive lymph nodes (pN) in Chinese breast cancer patients.

Methods

The medical records of female breast cancer patients (N = 2591) were retrospectively evaluated. The association of LNR and TMN staging system were compared with respect to overall, disease-free, and distant metastasis-free survival.

Results

Out of 2591 patients, 2495 underwent modified radical surgery and 96 received breast conserving surgery. All patients had adjuvant chemotherapy following surgery. The median follow up period 66.9 months (range 5–168 months). The 5-year and 10-year overall survival rates were 89.3% and 78.8%, respectively, and 5-year disease-free survival and distant metastasis-free survival rates were 81.6% and 83.5%, respectively. Univariate analysis indicated that in general T, pN, LNR, as well as tumor expression of the estrogen receptor, progesterone receptor, and HER2 were associated with overall, disease-free, and distant metastasis-free survival (all P-values <0.05). Mutlivariate analysis found pN stage and LNR were independent predictors of overall, disease-free, and distant metastasis-free survival (all P-values <0.001). If pN stage and LNR were both included in a multivariate analysis, LNR was still an independent prognostic factor for overall, disease-free, and distant metastasis-free survival (all P-values <0.001).

Conclusion

Our findings support the use of LNR as a predictor of survival in Chinese patients with breast cancer, and that LNR is superior to pN stage in determining disease prognosis.     

Genomic Predictors for Recurrence Patterns of Hepatocellular Carcinoma: Model Derivation and Validation

Background

Typically observed at 2 y after surgical resection, late recurrence is a major challenge in the management of hepatocellular carcinoma (HCC). We aimed to develop a genomic predictor that can identify patients at high risk for late recurrence and assess its clinical implications.

Methods and Findings

Systematic analysis of gene expression data from human liver undergoing hepatic injury and regeneration revealed a 233-gene signature that was significantly associated with late recurrence of HCC. Using this signature, we developed a prognostic predictor that can identify patients at high risk of late recurrence, and tested and validated the robustness of the predictor in patients (n = 396) who underwent surgery between 1990 and 2011 at four centers (210 recurrences during a median of 3.7 y of follow-up). In multivariate analysis, this signature was the strongest risk factor for late recurrence (hazard ratio, 2.2; 95% confidence interval, 1.3–3.7; p = 0.002). In contrast, our previously developed tumor-derived 65-gene risk score was significantly associated with early recurrence (p = 0.005) but not with late recurrence (p = 0.7). In multivariate analysis, the 65-gene risk score was the strongest risk factor for very early recurrence (<1 y after surgical resection) (hazard ratio, 1.7; 95% confidence interval, 1.1–2.6; p = 0.01). The potential significance of STAT3 activation in late recurrence was predicted by gene network analysis and validated later. We also developed and validated 4- and 20-gene predictors from the full 233-gene predictor. The main limitation of the study is that most of the patients in our study were hepatitis B virus–positive. Further investigations are needed to test our prediction models in patients with different etiologies of HCC, such as hepatitis C virus.

Conclusions

Two independently developed predictors reflected well the differences between early and late recurrence of HCC at the molecular level and provided new biomarkers for risk stratification. Please see later in the article for the Editors'' Summary     

A Prognostic Model for Triple-Negative Breast Cancer Patients Based on Node Status,Cathepsin-D and Ki-67 Index

Objective

The aim of this study was to evaluate clinicopathologic factors that could possibly affect the outcome of patients with triple negative breast cancer and subsequently build a prognostic model to predict patients’ outcome.

Methods

We retrospectively analyzed clinicopathologic characteristics and outcome of 504 patients diagnosed with triple-negative invasive ductal breast cancer. 185 patients enrolled between 2000 and 2002 were designated to the training set. The variables that had statistically significant correlation with prognosis were combined to build a model. The prognostic value of the model was further validated in the separate validation set containing 319 patients enrolled between 2003 and 2006.

Results

The median follow-up duration was 66 months. 174 patients experienced recurrence, and 111 patients died. Positivity for ≥4 lymph nodes, Cathepsin-D positivity, and Ki-67 index ≥20% were independent factors for DFS, while the lymph nodes status and Ki-67 index were the prognostic factors for OS. The prognostic model was established based on the sum of all three factors, where positivity for ≥4 lymph nodes, Cathepsin-D and Ki-67 index ≥20% would individually contribute 1 point to the risk score. The patients in the validation set were assigned to a low-risk group (0 and 1 point) and a high-risk group (2 and 3 points). The external validation analysis also demonstrated that our prognostic model provided the independent high predictive accuracy of recurrence.

Conclusion

This model has a considerable clinical value in predicting recurrence, and will help clinicians to design an appropriate level of adjuvant treatment and schedule adequate appointments of surveillance visits.     

Intratumoral CD8+ Cytotoxic Lymphocyte Is a Favorable Prognostic Marker in Node-Negative Breast Cancer

Background

The prognostic effect of tumor infiltrating CD8⁺ cytotoxic lymphocytes (CTLs) in breast cancer is controversial. We analyzed the association between CD8⁺ CTLs and survival of untreated node-negative breast cancer patients.

Material and Methods

CD8⁺ CTLs infiltrate was evaluated by immunostaining in a cohort of 332 node-negative breast cancer patients with a median follow-up of 152 months. The prognostic significance of CD8⁺ CTLs for disease-free survival (DFS) and breast cancer-specific overall survival (OS) was evaluated with Kaplan-Meier survival analysis as well as univariate analysis and multivariate Cox analysis adjusted for age at diagnosis, pT stage, histological grade, estrogen receptor (ER) status, progesterone receptor (PR) status, Ki-67 expression and human epidermal growth factor receptor 2 (HER-2) status.

Results

285 (85.8%) patients showed strong CD8⁺ CTLs infiltrate positive status. Univariate analysis showed that CD8⁺ CTLs had statistically significant association with DFS (P = 0.004, hazard ratio [HR] = 0.454, 95% confidence interval [CI] = 0.265–0.777) and OS (P = 0.014, HR = 0.430, 95% CI = 0.220–0.840) in the entire cohort. The significance of CD8⁺ CTLs was especially strong in ER negative, HER-2 negative and ER, PR, HER-2 triple-negative breast cancers. In Kaplan-Meier analysis, CD8⁺ CTLs had significant effect on prognosis of patients (Log-rank test: P = 0.003 for DFS and P = 0.011 for OS), independent of established clinical factors for DFS (P = 0.002, HR = 0.418, 95% CI = 0.242–0.724) as well as for OS (P = 0.009, HR = 0.401, 95% CI = 0.202–0.797).     

New Insight into Ki67 Expression at the Invasive Front in Breast Cancer

Purpose

To investigate the distribution of Ki67+ cells in breast cancer in relation to clinical-pathological parameters and prognosis.

Materials and Methods

Ki67 expression status was detected in 1,086 breast cancer specimens using immunohistochemistry staining and examining the relationship between the Ki67+ cells'' location. Subsequently, clinical-pathological parameters and prognosis were determined.

Results

In total, Ki67 protein expression was found in 781 (71.92%) of the 1,086 breast cancer specimens. Among the 781 Ki67+ cases, 461 were defined as diffuse type and 320 were defined as borderline type. After universal correlation analysis, significant differences were observed in age, histological grade, metastatic nodes, postoperative distant metastasis, and molecular subtype between Ki67+ and Ki67− cases (P = 0.01, 0.001, 0.001, 0.001, and 0.001, respectively). After subgroup analysis, the borderline cases were found to be characterized by a high distant metastasis rate compared to the diffuse cases as well as the Ki67− cases (P = 0.001). No differences were observed between diffuse type or Ki67− cases (P = 0.105). Multivariate analysis showed that age, tumor size, histological grade, lymph node metastasis, molecular subtype, and the Ki67 distribution pattern were observed to be related to postoperative distant metastasis (all P<0.05). Furthermore, borderline type was shown to attain a significantly more distant bone and liver metastasis and worse disease-specific survival than the other types (P = 0.001). In the Cox regression test, the Ki67 distribution pattern was detected as an independent prognostic factor (P = 0.001).

Conclusion

The distribution pattern of Ki67 may be a new independent prognostic factor for breast cancer.     

Insulin-Like Growth Factor Receptor I (IGF-IR) and Vascular Endothelial Growth Factor Receptor 2 (VEGFR-2) Are Expressed on the Circulating Epithelial Tumor Cells of Breast Cancer Patients

Background

Circulating epithelial tumor cell (CETC) analysis is a promising diagnostic field for estimating the risk for metastatic relapse and progression in patients with malignant disease. CETCs characterization can be used as a liquid biopsy for prognostic and predictive purposes in breast and other cancers. IGF-IR and VEGFR-2 play an important role in tumor growth and the progression of cancer disease. The purpose of the current study was therefore to investigate their expression on CETCs.

Methods

CETCs were determined from the blood of 50 patients suffering from breast cancer. The number of vital CETCs and the expression of IGF-IR and VEGFR-2 were investigated using the maintrac® method.

Results

IGF-IR and VEGFR-2 expression on the surface of CETCs were detected in 84% of patients. A statistically high correlation was found between IGF-IR and VEGFR-2 (r = 0.745 and p<0.001) on the CETCs. The co-expression of both receptors was confirmed in some experiments and ranged between 70% and 100%. Statistically significant correlations were observed between the number of CETCs and IGF-IR (r = 0.315 and p<0.05) and VEGFR-2 (r = 0.310 and p<0.05) expression. The presence of CETCs and the level of IGF-IR and VEGFR-2 expression were not associated with tumor stage, hormone receptor status or nodal/distant metastasis.

Summary

In this study, a parallel and co-expression of IGF-IR and VEGFR-2 was examined on the surface of CETCs in breast cancer patients for the first time. Characterization of CETCs may be a promising approach for the rational design of targeted anticancer therapies.     

Evidence That Breast Tissue Stiffness Is Associated with Risk of Breast Cancer

Background

Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer.

Methods

Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors.

Results

After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements.

Conclusion

An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement.     

Prognostic Significance of ESR1 Gene Amplification,mRNA/Protein Expression and Functional Profiles in High-Risk Early Breast Cancer: A Translational Study of the Hellenic Cooperative Oncology Group (HeCOG)

Background

Discrepant data have been published on the incidence and prognostic significance of ESR1 gene amplification in early breast cancer.

Patients and Methods

Formalin-fixed paraffin-embedded tumor blocks were collected from women with early breast cancer participating in two HeCOG adjuvant trials. Messenger RNA was studied by quantitative PCR, ER protein expression was centrally assessed using immunohistochemistry (IHC) and ESR1 gene copy number by dual fluorescent in situ hybridization probes.

Results

In a total of 1010 women with resected node-positive early breast adenocarcinoma, the tumoral ESR1/CEP6 gene ratio was suggestive of deletion in 159 (15.7%), gene gain in 551 (54.6%) and amplification in 42 cases (4.2%), with only 30 tumors (3%) harboring five or more ESR1 copies. Gene copy number ratio showed a significant, though weak correlation to mRNA and protein expression (Spearman''s Rho <0.23, p = 0.01). ESR1 clusters were observed in 9.5% (57 gain, 38 amplification) of cases. In contrast to mRNA and protein expression, which were favorable prognosticators, gene copy number changes did not obtain prognostic significance. When ESR1/CEP6 gene ratio was combined with function (as defined by ER protein and mRNA expression) in a molecular classifier, the Gene Functional profile, it was functional status that impacted on prognosis. In univariate analysis, patients with functional tumors (positive ER protein expression and gene ratio normal or gain/amplification) fared better than those with non-functional tumors with ESR1 gain (HR for relapse or death 0.49–0.64, p = 0.003). Significant interactions were observed between gene gain/amplification and paclitaxel therapy (trend for DFS benefit from paclitaxel only in patients with ESR1 gain/amplification, p = 0.066) and Gene Functional profile with HER2 amplification (Gene Functional profile prognostic only in HER2-normal cases, p = 0.029).

Conclusions

ESR1 gene deletion and amplification do not constitute per se prognostic markers, instead they can be classified to distinct prognostic groups according to their protein-mediated functional status.     

Progesterone Receptor Status and Ki-67 Index May Predict Early Relapse in Luminal B/HER2 Negative Breast Cancer Patients: A Retrospective Study

Purpose

Few studies has documented early relapse in luminal B/HER2-negative breast cancer. We examined prognostic factors for early relapse among these patients to improve treatment decision-making.

Patients and Methods

A total 398 patients with luminal B/HER2-negative breast cancer were included. Kaplan-Meier curves were applied to estimate disease-free survival and Cox regression to identify prognostic factors.

Results

Progesterone receptor (PR) negative expression was associated with higher tumor grade (p<.001) and higher Ki-67 index (p = .010). PR-negative patients received more chemotherapy than the PR-positive group (p = .009). After a median follow-up of 28 months, 17 patients (4.3%) had early relapses and 8 patients (2.0%) died of breast cancer. The 2-year disease-free survival was 97.7% in the PR-positive and 90.4% in the PR-negative groups (Log-rank p = .002). Also, patients with a high Ki-67 index (defined as >30%) had a reduced disease-free survival (DFS) when compared with low Ki-67 index group (≤30%) (98.0% vs 92.4%, respectively, Log-rank p = .013). In multivariate analysis, PR negativity was significantly associated with a reduced DFS (HR = 3.91, 95% CI 1.29–11.88, p = .016).

Conclusion

In this study, PR negativity was a prognostic factor for early relapse in luminal B/HER2-negative breast cancer, while a high Ki-67 index suggested a higher risk of early relapse.     

Validation of Expression Patterns for Nine miRNAs in 204 Lymph-Node Negative Breast Cancers

Introduction

Although lymph node negative (LN-) breast cancer patients have a good 10-years survival (∼85%), most of them still receive adjuvant therapy, while only some benefit from this. More accurate prognostication of LN- breast cancer patient may reduce over- and under-treatment. Until now proliferation is the strongest prognostic factor for LN- breast cancer patients. The small molecule microRNA (miRNA) has opened a new window for prognostic markers, therapeutic targets and/or therapeutic components. Previously it has been shown that miR-18a/b, miR-25, miR-29c and miR-106b correlate to high proliferation.

Methods

The current study validates nine miRNAs (miR-18a/b miR-25, miR-29c, miR-106b, miR375, miR-424, miR-505 and let-7b) significantly correlated with established prognostic breast cancer biomarkers. Total RNA was isolated from 204 formaldehyde-fixed paraffin embedded (FFPE) LN- breast cancers and analyzed with quantitative real-time Polymerase Chain Reaction (qPCR). Independent T-test was used to detect significant correlation between miRNA expression level and the different clinicopathological features for breast cancer.

Results

Strong and significant associations were observed for high expression of miR-18a/b, miR-106b, miR-25 and miR-505 to high proliferation, oestrogen receptor negativity and cytokeratin 5/6 positivity. High expression of let-7b, miR-29c and miR-375 was detected in more differentiated tumours. Kaplan-Meier survival analysis showed that patients with high miR-106b expression had an 81% survival rate vs. 95% (P = 0.004) for patients with low expression.

Conclusion

High expression of miR-18a/b are strongly associated with basal-like breast cancer features, while miR-106b can identify a group with higher risk for developing distant metastases in the subgroup of Her2 negatives. Furthermore miR-106b can identify a group of patients with 100% survival within the otherwise considered high risk group of patients with high proliferation. Using miR-106b as a biomarker in conjunction to mitotic activity index could thereby possibly save 18% of the patients with high proliferation from overtreatment.