76 research outputs found
Prognostic ability of a panel of immunohistochemistry markers – retailoring of an 'old solution'
An urgent requirement exists for new prognostic and predictive assays in breast cancer. Despite the development of high-throughput technologies such as DNA microarrays, it would now appear that immunohistochemistry (IHC) may play an increasingly important role in the clinical management of breast cancer. In this editorial, the authors discuss the potential prognostic ability of a panel of IHC markers, and question whether this well-established assay technology may in fact allow for improved prognostic and predictive tests in breast cancer
Mammostrat® as a tool to stratify breast cancer patients at risk of recurrence during endocrine therapy
Association of GATA3, P53, Ki67 status and vascular peritumoral invasion are strongly prognostic in luminal breast cancer
International audienceIntroduction: Breast cancers are traditionally divided into hormone-receptor positive and negative cases. This classification helps to guide patient management. However, a subgroup of hormone-receptor positive patients relapse irrespective of hormonal therapy. Gene expression profiling has classified breast tumours into five major subtypes with significant different outcome. The two luminal subtypes, A and B, show high expression of ESR1, GATA3 and FOXA1 genes. Prognostic biomarkers for oestrogen receptor (ER)-positive cases include progesterone receptor (PR) and androgen receptor (AR), and proteins related to proliferation or apoptotic resistance. The aim of this study was to identify the best predictors of success of hormonal therapy.Methods: By immunohistochemistry we studied 10 markers in a consecutive series of 832 cases of breast carcinoma treated at the Paoli-Calmettes Institute from 1990 to 2002 and deposited onto tissue microarrays (TMA). These markers were luminal-related markers ER, PR, AR, FOXA1 and GATA3 transcription factors, proliferation-related Ki67 and CCND1, ERBB2, anti-apoptotic BCL2 and P53. We also measured vascular peritumoural invasion (VPI), size, grade and lymph node involvement. For 143 cases, gene expression profiles were available. Adjuvant chemotherapy and hormonal therapy were given to high- and low-risk patients, respectively. The 162 events observed and taken into account were metastases.Results: Molecular expression of the 10 parameters and subtype with ER status were strongly correlated. Of the 67 luminal A cases of this series, 63 were ER-positive. Multivariate analyses showed the highly significant prognostic value of VPI (hazard ratio (HR) = 2.47), Ki67 (HR = 2.9), P53 (HR = 2.9) and GATA3 (HR = 0.5) for the 240 patients who received hormonal therapy.Conclusions: A panel of three antibodies (Ki67, P53 and GATA3) associated with VPI can significantly improve the traditional prognosticators in predicting outcome for ER-positive breast cancer patients receiving hormonal therapy
Evaluation of molecular descriptors for antitumor drugs with respect to noncovalent binding to DNA and antiproliferative activity
34 pages, 6 additional files, 5 tables, 4 figures.[Background ] Small molecules that bind reversibly to DNA are among the antitumor drugs currently used in chemotherapy. In the pursuit of a more rational approach to cancer
chemotherapy based upon these molecules, it is necessary to exploit the interdependency between DNA-binding affinity, sequence selectivity and cytotoxicity. For drugs binding noncovalently to DNA, it is worth exploring whether molecular descriptors, such as their molecular weight or the number of potential hydrogen acceptors/donors, can account for their DNA-binding affinity and
cytotoxicity.[Results] Fifteen antitumor agents, which are in clinical use or being evaluated as part of the National Cancer Institute’s drug screening effort, were analyzed in silico to assess the contribution of various molecular descriptors to their DNA-binding affinity, and the capacity of the descriptors and DNA-binding constants for predicting cell cytotoxicity. Equations to predict
drug-DNA binding constants and growth-inhibitory concentrations were obtained by multiple regression following rigorous statistical procedures.[Conclusions] For drugs binding reversibly to DNA, both their strength of binding and their
cytoxicity are fairly predicted from molecular descriptors by using multiple regression methods. The equations derived may be useful for rational drug design. The results obtained agree with that
compounds more active across the National Cancer Institute’s 60-cell line data set tend to have common structural features.Supported by a grant from the former Spanish Ministry of Education and Science (BFU2007-60998) and the FEDER program of the European Community.Peer reviewe
Effect of Polymorphisms in XPD on Clinical Outcomes of Platinum-Based Chemotherapy for Chinese Non-Small Cell Lung Cancer Patients
PURPOSE: Xeroderma pigmentosum group D (XPD) codes for a DNA helicase involved in nucleotide excision repair that removes platinum-induced DNA damage. Genetic polymorphisms of XPD may affect DNA repair capacity and lead to individual differences in the outcome of patients after chemotherapy. This study aims to identify whether XPD polymorphisms affect clinical efficacy among advanced non-small cell lung cancer (NSCLC) patients treated with platinum-based chemotherapy. EXPERIMENTAL DESIGN: 353 stage III-IV NSCLC patients receiving platinum-based chemotherapy as the first-line treatment were enrolled in this study. Four potentially functional XPD polymorphisms (Arg(156)Arg, Asp(312)Asn, Asp(711)Asp and Lys(751)Gln) were genotyped by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry or PCR-based sequencing. RESULTS: Variant genotypes of XPD Asp(312)Asn, Asp(711)Asp and Lys(751)Gln were significantly associated with poorer NSCLC survival (P = 0.006, 0.006, 0.014, respectively, by log-rank test). The most common haplotype GCA (in order of Asp(312)Asn, Asp(711)Asp and Lys(751)Gln) also exhibited significant risk effect on NSCLC survival (log-rank P = 0.001). This effect was more predominant for patients with stage IIIB disease (P = 2.21×10(-4), log-rank test). Increased risks for variant haplotypes of XPD were also observed among patients with performance status of 0-1 and patients with adenocarcinoma. However, no significant associations were found between these polymorphisms, chemotherapy response and PFS. CONCLUSIONS: Our study provides evidence for the predictive role of XPD Asp(312)Asn, Asp(711)Asp and Lys(751)Gln polymorphisms/haplotype on NSCLC prognosis in inoperable advanced NSCLC patients treated with platinum-based chemotherapy
Tamoxifen resistance in early breast cancer: statistical modelling of tissue markers to improve risk prediction
BACKGROUND: For over two decades, the Nottingham Prognostic Index (NPI) has been used in the United Kingdom to calculate risk scores and inform management about breast cancer patients. It is derived using just three clinical variables - nodal involvement, tumour size and grade. New scientific methods now make cost-effective measurement of many biological characteristics of tumour tissue from breast cancer biopsy samples possible. However, the number of potential explanatory variables to be considered presents a statistical challenge. The aim of this study was to investigate whether in ER+ tamoxifen-treated breast cancer patients, biological variables can add value to NPI predictors, to provide improved prognostic stratification in terms of overall recurrence-free survival (RFS) and also in terms of remaining recurrence free while on tamoxifen treatment (RFoT). A particular goal was to enable the discrimination of patients with a very low risk of recurrence. METHODS: Tissue samples of 401 cases were analysed by microarray technology, providing biomarker data for 72 variables in total, from AKT, BAD, HER, MTOR, PgR, MAPK and RAS families. Only biomarkers screened as potentially informative (i.e., exhibiting univariate association with recurrence) were offered to the multivariate model. The multiple imputation method was used to deal with missing values, and bootstrap sampling was used to assess internal validity and refine the model. RESULTS: Neither the RFS nor RFoT models derived included Grade, but both had better predictive and discrimination ability than NPI. A slight difference was observed between models in terms of biomarkers included, and, in particular, the RFoT model alone included HER2. The estimated 7-year RFS rates in the lowest-risk groups by RFS and RFoT models were 95 and 97%, respectively, whereas the corresponding rate for the lowest-risk group of NPI was 89%. CONCLUSION: The findings demonstrate considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. In particular, the ability to identify a low-risk group with minimal risk of recurrence is likely to have clinical appeal. With larger data sets and longer follow-up, this modelling approach has the potential to enhance an understanding of the interplay of biological characteristics, treatment and cancer recurrence. British Journal of Cancer (2010) 102, 1503 - 1510. doi:10.1038/sj.bjc.6605627 www.bjcancer.co
Systematic antibody generation and validation via tissue microarray technology leading to identification of a novel protein prognostic panel in breast cancer
Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential
- …