Breast Cancer Research update, jul 3
Written by admin on Jul 6th, 2008 | Filed under: oncology UPDATE
Risk prediction models with incomplete data with application to prediction of estrogen receptor positive breast cancer: prospective data from the Nurses’ Health Study
IntroductionA number of breast cancer risk prediction models have been developed to provide insight into a woman’s individual breast cancer risk. Although circulating levels of estradiol in postmenopausal women predict subsequent breast cancer risk, whether the addition of estradiol levels adds significantly to a model’s predictive power has not previously been evaluated. Methods: Using linear regression, the authors developed an imputed estradiol score using measured estradiol levels (the outcome) and both case status and risk factor data (e.g., body mass index) from a nested case-control study conducted within a large prospective cohort study and used multiple imputation methods to develop an overall risk model including both risk factor data from the main cohort and estradiol levels from the nested case-control study. Results: The authors evaluated the addition of imputed estradiol level to the previously published Rosner and Colditz log incidence model for breast cancer risk prediction within the larger Nurses’ Health Study cohort. Follow-up was from 1980-2000; during this time 1559 invasive estrogen receptor positive breast cancer cases were confirmed. The addition of imputed estradiol levels significantly improved risk prediction; the age-specific concordance statistic increased from 0.635+/-0.007 to 0.645+/-0.007 (p<0.001) after addition of imputed estradiol. Conclusions: Circulating estradiol levels in postmenopausal women appear to add to other lifestyle factors in predicting a woman’s individual risk of breast cancer.
SELDI-TOF proteomic profiling of breast carcinomas identifies clinicopathologically relevant groups of patients similar to previously defined clusters from cDNA expression
Expression profiling and biomarker(s) discovery aim to provide means for tumour diagnosis, classification, therapy response and prognosis. The identification of novel markers could potentially lead to the building of robust early detection strategies and personalized, effective breast cancer therapies that would improve patient outcome. Recent evidence supports the hypothesis that genomic expression profiling using microarray analysis is a reliable method for breast cancer classification and prognostication. However, genes clearly do not act by themselves, or indeed they do not have catalytic or signalling capabilities. Hence, genetic biomarker information alone cannot perfectly predict cancer and its response to treatment. Genes clearly exert their effect after transcription through translation into active proteins. Consequently, postgenomic projects correlating protein expression profiles with tumour classification have led to some established biomarkers. In this regard, these biomarkers associate with disease prediction and can be associated with treatment response. Recently, Brozokova and colleagues demonstrated that surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF MS) profiling of breast cancer tissue proteomes can potentially expand the biomarker repertoire and our knowledge of breast cancer behaviour.
PMC42, a breast progenitor cancer cell line, has normal-like mRNA and miRNA transcriptomes
IntroductionThe use of cultured cell lines as model systems for normal tissue is limited by the molecular alterations accompanying the immortalisation process, including changes in the mRNA and miRNA repertoire. Therefore, identification of cell lines with normal-like expression profiles is of paramount importance in studies of normal gene regulation. Methods: The mRNA and miRNA expression profiles of several breast cell lines of cancerous or normal origin were measured using printed slide arrays, Luminex bead arrays and real-time RT-PCR. Results: We demonstrate that the mRNA expression profiles of two breast cell lines are similar to that of normal breast tissue: HB4a, immortalised normal breast epithelium, and PMC42, a breast cancer cell line that retains progenitor pluripotency allowing in culture differentiation to both secretory and myoepithelial fates. In contrast, only PMC42 exhibits a normal-like miRNA expression profile. We identified a group of miRNAs that are highly expressed in normal breast tissue and PMC42 but are lost in all other cancerous and normal-origin breast cell lines, and observed a similar loss in immortalised lymphoblastoid cell lines compared to healthy uncultured B cells. Moreover, like tumour suppressor genes, these miRNAs are lost in a variety of tumours. We show that the mechanism leading to the loss of these miRNAs in breast cancer cell lines has genomic, transcriptional and post-transcriptional components. Conclusion: We propose that despite its neoplastic origin, PMC42 is an excellent molecular model for normal breast epithelium, providing a unique tool to study breast differentiation and the function of key miRNAs which are typically lost in cancer.
Mammographic density. Measurement of mammographic density
Mammographic density has been strongly associated with increased risk of breast cancer. Furthermore, density is inversely correlated with the accuracy of mammography and, therefore, a measurement of density conveys information about the difficulty of detecting cancer in a mammogram. Initial methods for assessing mammographic density were entirely subjective and qualitative; however, in the past few years methods have been developed to provide more objective and quantitative density measurements. Research is now underway to create and validate techniques for volumetric measurement of density. It is also possible to measure breast density with other imaging modalities, such as ultrasound and MRI, which do not require the use of ionizing radiation and may, therefore, be more suitable for use in young women or where it is desirable to perform measurements more frequently. In this article, the techniques for measurement of density are reviewed and some consideration is given to their strengths and limitations.
The CD44+/CD24- phenotype is enriched in basal-like breast tumors
IntroductionHuman breast tumors are heterogeneous and consist of phenotypically diverse cells. Breast cancer cells with a CD44+/CD24- phenotype have been suggested to have tumor-initiating properties with stem cell-like and invasive features, although it is unclear whether their presence within a tumor has clinical implications. There is also a large heterogeneity between tumors, illustrated by reproducible stratification into various subtypes based on gene expression profiles or histopathological features. We have explored the prevalence of cells with different CD44/CD24 phenotypes within breast cancer subtypes. Methods: Double-staining immunohistochemistry was used to quantify CD44 and CD24 expression in 240 human breast tumors for which information on other tumor markers and clinical characteristics was available. Gene expression data was also accessible for a cohort of the material. Results: A considerable heterogeneity in CD44 and CD24 expression was seen both between and within tumors. A complete lack of both proteins was evident in 35% of the tumors, while 13% contained cells of more than one of the CD44+/CD24-, CD44-/CD24+ and CD44+/CD24+ phenotypes. CD44+/CD24- cells were detected in 31% of the tumors, ranging in proportion from only a few to close to 100% of tumor cells. The CD44+/CD24- phenotype was most common in the basal-like subgroup characterized as negative for the estrogen and progesterone receptors as well as for HER2 and positive for cytokeratin 5/14 and/or EGFR, and particularly common in BRCA1 hereditary tumors of which 94% contained CD44+/CD24- cells. The CD44+/CD24- phenotype was surprisingly scarce in HER2+ tumors, which had a predominantly CD24+ status. A CD44+/CD24- gene expression signature was generated, which included CD44 and alpha-6 integrin (CD49f) among the top-ranked overexpressed genes. Conclusions: We demonstrate an association between basal-like and particularly BRCA1 hereditary breast cancer and presence of CD44+/CD24- cells. However, not all basal-like and very few HER2+ tumors contain CD44+/CD24- cells, which emphasizes that a putative tumorigenic ability may not be confined to cells of this phenotype and that other breast cancer stem cell markers remain to be identified.
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