New data on chemotherapy in the adjuvant setting

Incidence and origin of histologically confirmed liver metastases: an explorative case-study of 23,154 patients

Background

The liver is a common metastatic site for a large variety of primary tumors. For both patients with known and unknown primary tumors it is important to understand metastatic patterns to provide tailored therapies.

Objective

To perform a nationwide exploration of the origins of histological confirmed liver metastases.

Results

A total of 23,154 patients were identified. The majority of liver metastases were carcinomas (n=21,400; 92%) of which adenocarcinoma was the most frequent subtype (n=17,349; 75%). Most common primary tumors in patients with adenocarcinoma were from colorectal (n=8,004), pancreatic (n=1,755) or breast origin (n=1,415). In women of 50 years and younger, metastatic adenocarcinoma originated more frequently from breast cancer, while in women older than 70 years liver metastases originated more frequently from gastrointestinal tumors. Liver metastases in men older than 70 years originated often from squamous cell lung carcinoma. An unknown primary tumor was detected in 4,209 (18%) patients, although tumor type could be determined in 3,855 (92%) of them.

Methods

Data were collected using the nationwide network and registry of histo- and cytopathology in the Netherlands (PALGA). All histological confirmed liver metastases between January 2001 and December 2010 were evaluated for tumor type, origin of the primary tumor and were correlated with patient characteristics (age, gender).

Conclusion

The current study provides an overview of the origins of liver metastases in a series of 23,154 patients.

Long-term cost-effectiveness of Oncotype DX® versus current clinical practice from a Dutch cost perspective

INTRODUCTION

This study analyzes the incremental cost-effectiveness of Oncotype DX(®) testing to support adjuvant chemotherapy recommendations, versus current clinical practice, for patients with estrogen receptor-positive (ER(+)), node-negative or micrometastatic (pN1mic) early-stage breast cancer in The Netherlands.

METHODS

Markov model projecting distant recurrence, survival, quality-adjusted life years (QALYs) and healthcare costs over a 30-year time horizon.

RESULTS

Oncotype DX was projected to increase QALYs by 0.11 (0.07-0.58) and costs with €1236 (range: -€142-€1236) resulting in an incremental cost-effectiveness ratio of €11,236/QALY under the most conservative scenario.

CONCLUSION

Reallocation of adjuvant chemotherapy based on Oncotype DX testing is most likely a cost-effective use of scarce resources, improving long-term survival and QALYs at marginal or lower costs.

Emerging biomarkers in breast cancer care

Currently, decision-making for breast cancer treatment in the clinical setting is mainly based on clinical data, histomorphological features of the tumor tissue and a few cancer biomarkers such as steroid hormone receptor status (estrogen and progesterone receptors) and oncoprotein HER2 status. Although various therapeutic options were introduced into the clinic in recent decades, with the objective of improving surgery, radiotherapy, biochemotherapy and chemotherapy, varying response of individual patients to certain types of therapy and therapy resistance is still a challenge in breast cancer care. Therefore, since breast cancer treatment should be based on individual features of the patient and her tumor, tailored therapy should be an option by integrating cancer biomarkers to define patients at risk and to reliably predict their course of the disease and/or response to cancer therapy. Recently, candidate-marker approaches and genome-wide transcriptomic and epigenetic screening of different breast cancer tissues and bodily fluids resulted in new promising biomarker panels, allowing breast cancer prognosis, prediction of therapy response and monitoring of therapy efficacy. These biomarkers are now subject of validation in prospective clinical trials.

Predictive model of outcome of targeted nodal assessment in colorectal cancer

BACKGROUND

Improvement in staging accuracy is the principal aim of targeted nodal assessment in colorectal carcinoma. Technical factors independently predictive of false negative (FN) sentinel lymph node (SLN) mapping should be identified to facilitate operative decision making.

PURPOSE

To define independent predictors of FN SLN mapping and to develop a predictive model that could support surgical decisions.

PATIENTS AND METHODS

Data was analyzed from 2 completed prospective clinical trials involving 278 patients with colorectal carcinoma undergoing SLN mapping. Clinical outcome of interest was FN SLN(s), defined as one(s) with no apparent tumor cells in the presence of non-SLN metastases. To assess the independent predictive effect of a covariate for a nominal response (FN SLN), a logistic regression model was constructed and parameters estimated using maximum likelihood. A probabilistic Bayesian model was also trained and cross validated using 10-fold train-and-test sets to predict FN SLN mapping. Area under the curve (AUC) from receiver operating characteristics curves of these predictions was calculated to determine the predictive value of the model.

RESULTS

Number of SLNs (<3; P = 0.03) and tumor-replaced nodes (P < 0.01) independently predicted FN SLN. Cross validation of the model created with Bayesian Network Analysis effectively predicted FN SLN (area under the curve = 0.84-0.86). The positive and negative predictive values of the model are 83% and 97%, respectively.

CONCLUSION

This study supports a minimum threshold of 3 nodes for targeted nodal assessment in colorectal cancer, and establishes sufficient basis to conclude that SLN mapping and biopsy cannot be justified in the presence of clinically apparent tumor-replaced nodes.

A highly sensitive and specific system for large-scale gene expression profiling

Background

Rapid progress in the field of gene expression-based molecular network integration has generated strong demand on enhancing the sensitivity and data accuracy of experimental systems. To meet the need, a high-throughput gene profiling system of high specificity and sensitivity has been developed.

Results

By using specially designed primers, the new system amplifies sequences in neighboring exons separated by big introns so that mRNA sequences may be effectively discriminated from other highly related sequences including their genes, unprocessed transcripts, pseudogenes and pseudogene transcripts. Probes used for microarray detection consist of sequences in the two neighboring exons amplified by the primers. In conjunction with a newly developed high-throughput multiplex amplification system and highly simplified experimental procedures, the system can be used to analyze >1,000 mRNA species in a single assay. It may also be used for gene expression profiling of very few (n = 100) or single cells. Highly reproducible results were obtained from duplicate samples with the same number of cells, and from those with a small number (100) and a large number (10,000) of cells. The specificity of the system was demonstrated by comparing results from a breast cancer cell line, MCF-7, and an ovarian cancer cell line, NCI/ADR-RES, and by using genomic DNA as starting material.

Conclusion

Our approach may greatly facilitate the analysis of combinatorial expression of known genes in many important applications, especially when the amount of RNA is limited.

Urokinase-type plasminogen activator and plasminogen activator inhibitor type-1 mRNA assessment in breast cancer by means of NASBA: correlation with protein expression

Urokinase plasminogen activator (uPA) and its main inhibitor, plasminogen activator inhibitor type-1 (PAI-1) determined in tumor tissue by means of enzyme-linked immunosorbent assay (ELISA) can discriminate patients with primary breast cancer at high risk vs low risk for recurrence. The aim of this study was to analyze uPA and PAI-1 messenger RNA (mRNA) expression by means of quantitative nucleic acid sequence-based amplification (NASBA) on 77 primary breast tumor samples and to correlate this expression with the uPA and PAI-1 protein content. We observed that the 2 markers were significantly overexpressed (uPA, P < .0001; PAI-1, P = .0042) in mRNA in the ELISA+ group. The receiver operating characteristic (ROC) curves demonstrated high concordance between NASBA and ELISA (area under the ROC curve of 0.84 and 0.70 for uPA and PAI-1, respectively) and showed that uPA and PAI-1 status could be predicted by using the molecular assay with sensitivity and specificity values of 80.8% and 82.4% and sensitivity and specificity values of 66.7% and 74.0%, respectively.

Application of DNA microarray technology in determining breast cancer prognosis and therapeutic response

There are > 1.15 million cases of breast cancer diagnosed worldwide annually, and it is the second leading cause of cancer death in the European Union. The optimum management of patients with breast cancer requires accurate prognostic and predictive factors. At present, only a small number of such factors are used clinically. DNA microarrays have the potential to measure the expression of tens of thousands of genes simultaneously. Recent preliminary findings suggest that DNA microarray-based gene expression profiling can provide powerful and independent prognostic information in patients with newly diagnosed breast cancer. As well as providing prognostic information, emerging results suggest that DNA microarrays can also be used for predicting response or resistance to treatment, especially to neoadjuvant chemotherapy. Prior to clinical application, these preliminary findings must be validated using large-scale prospective studies. This article reviews these advances and also examines the role of DNA microarrays in reducing the number of patients who receive inappropriate chemotherapy. The most recent data supporting the integration of various publicly available data sets is also reviewed in detail.

Postoperative dose-dense sequential chemotherapy with epirubicin, followed by CMF with or without paclitaxel, in patients with high-risk operable breast cancer: a randomized phase III study conducted by the Hellenic Cooperative Oncology Group

PURPOSE

The aim of this study was to explore the effect of dose-dense sequential chemotherapy with or without paclitaxel primarily on disease-free survival (DFS) and secondarily on overall survival (OS) in patients with high-risk operable breast cancer.

PATIENTS AND METHODS

From June 1997 until November 2000, 604 patients with T1-3N1M0 or T3N0M0 tumors were randomized to three cycles of epirubicin 110 mg/m2 followed by three cycles of paclitaxel 250 mg/m2 followed by three cycles of 'intensified' CMF (cyclophosphamide 840 mg/m2, methotrexate 47 mg/m2 and fluorouracil 840 mg/m2) (group A), or to four cycles of epirubicin followed by four cycles of CMF, as in group A (group B). All cycles were given every 2 weeks with granulocyte colony-stimulating factor support.

RESULTS

A total of 595 patients were eligible. Median follow-up was 61.7 months for group A and 62 months for group B. The 3-year DFS was 80% in group A and 77% in group B. Survival rates were 93% and 90%, respectively. The effect of treatment on the hazard of death was different according to hormonal receptor status. More specifically, in patients with negative receptor status the hazard of death was significantly higher for group B (hazard ratio 2.42). Both regimens were well tolerated and severe acute side-effects were infrequent. No cases of severe cardiotoxicity or acute leukemia were recorded.

CONCLUSIONS

The present study failed to demonstrate a significant difference in DFS or OS between the two treatment groups. However, our study has shown clearly that high-dose paclitaxel can be safely incorporated to dose-dense sequential chemotherapy.

Bringing Molecular Prognosis and Prediction to the Clinic

In the past 30 years, important advances have been made in the knowledge of breast cancer biology and in the treatment of the disease. However, the translation of these advances into clinical practice has been slow. With the advent of molecular-based medicine, it is hoped that the bridge between the bench and the bedside will continue to be shortened. Because breast cancer is a heterogeneous disease with wide-ranging subsets of patients who have different prognoses and who respond differently to treatments, the identification of patients who need treatment and the definition of the best therapy for an individual have become the priorities in breast cancer care. This article will review the crucial role of prognostic and predictive factors in achieving these goals. A critical review of classical and newer individual molecular markers, such as hormone receptors, HER2, urokinase-type plasminogen activator and plasminogen activator inhibitor 1, cyclin E, topoisomerase II, and p53, was performed, and the preliminary results obtained using the new gene expression profiling technology are described along with their potential clinical implications.