Prognostic role of serum thymidine kinase 1 kinetics during neoadjuvant chemotherapy for early breast cancer.

BACKGROUND: Emerging data support the use of thymidine kinase 1 (TK1) activity as a prognostic marker and for monitoring of response in breast cancer (BC). The long-term prognostic value of TK1 kinetics during neoadjuvant chemotherapy is unclear, which this study aimed to elucidate. METHODS: Material from patients enrolled to the single-arm prospective PROMIX trial of neoadjuvant epirubicin, docetaxel and bevacizumab for early BC was used. Ki67 in baseline biopsies was assessed both centrally and by automated digital imaging analysis. TK1 activity was measured from blood samples obtained at baseline and following two cycles of chemotherapy. The associations of TK1 and its kinetics as well as Ki67 with event-free survival and overall survival (OS) were evaluated using multivariable Cox regression models. RESULTS: Central Ki67 counting had excellent correlation with the results of digital image analysis (r = 0.814), but not with the diagnostic samples (r = 0.234), while it was independently prognostic for worse OS [adjusted hazard ratio (HRadj) = 2.72, 95% confidence interval (CI) 1.19-6.21, P = 0.02]. Greater increase in TK1 activity after two cycles of chemotherapy resulted in improved event-free survival (HRadj = 0.50, 95% CI 0.26-0.97, P = 0.04) and OS (HRadj = 0.46, 95% CI 0.95, P = 0.04). There was significant interaction between the prognostic value of TK1 kinetics and Ki67 (pinteraction 0.04). CONCLUSION: Serial measurement of serum TK1 activity during neoadjuvant chemotherapy provides long-term prognostic information in BC patients. The ease of obtaining serial samples for TK1 assessment motivates further evaluation in larger studies.

Serum thymidine kinase activity compared with CA 15-3 in locally advanced and metastatic breast cancer within a randomized trial.

The primary objective was to estimate serum thymidine kinase 1 (TK1) activity, reflecting total body cell proliferation rate including cancer cell proliferation, in women with loco regional inoperable or metastatic breast cancer participating in a prospective and randomized study. Secondary objectives were to analyze TK1 in relation to progression-free survival (PFS), overall survival (OS), therapy response and other tumour characteristics, including CA 15-3, widely used as a standard serum marker for disease progression. TK1 and CA 15-3 were analysed in 198 serum samples collected prospectively from women included in the randomized TEX trial between December 2002 and June 2007. TK1 activity was determined by the ELISA based DiviTum™ assay, and CA 15-3 analyses was generated with the electrochemiluminescence immunoassay Cobas Elecsys CA 15-3 II. High pre-treatment TK1 activity predicted shorter PFS (10 vs. 15 months p = 0.02) and OS (21 vs. 38 months, p < 0.0001), respectively. After adjustment for age, metastatic site and study treatment TK1 showed a trend as predictor of PFS (p = 0.059) and was an independent prognostic factor for OS, (HR 1.81, 95 % confidence interval (CI) 1.26-2.61, p = 0.001). There was a trend of shortened OS for women with high CA 15-3 (p = 0.054) in univariate analysis, but not after adjustment for the above mentioned covariates. Both TK1 (p = 0.0011) and CA 15-3 (p = 0.0004) predicted response to treatment. There were statistically different distributions of TK1 and CA 15-3 in relation to the site of metastases. TK1 activity measured by DiviTum™ predicted therapy response, PFS and OS in loco regional inoperable or disseminated breast cancer. These results suggest that this factor is a useful serum marker. In the present material, a prognostic value of CA 15-3 could not be proven.

Mammographic density and molecular subtypes of breast cancer.

BACKGROUND: Gene expression profiling has led to a subclassification of breast cancers independent of established clinical parameters, such as the Sorlie-Perou subtypes. Mammographic density (MD) is one of the strongest risk factors for breast cancer, but it is unknown if MD is associated with molecular subtypes of this carcinoma. METHODS: We investigated whether MD was associated with breast cancer subtypes in 110 women with breast cancer, operated in Stockholm, Sweden, during 1994 to 1996. Subtypes were defined using expression data from HGU133A+B chips. The MD of the unaffected breast was measured using the Cumulus software. We used multinomial logistic models to investigate the relationship between MD and Sorlie-Perou subtypes. RESULTS: Although the distribution of molecular subtypes differed in women with high vs low MD, this was statistically non-significant (P=0.249), and further analyses revealed no association between the MD and Sorlie-Perou subtypes as a whole, nor with individual subtypes. CONCLUSION: These findings suggest that although MD is one of the strongest risk factors for breast cancer, it does not seem to be differentially associated with breast cancer molecular subtypes. However, larger studies with more comprehensive covariate information are needed to confirm these results.

Quantitative real-time PCR analysis and microarray-based RNA expression of HER2 in relation to outcome.

BACKGROUND: Our aim was to use quantitative real-time PCR (Q-PCR) and RNA expression profiles (RNA-EPs) to investigate HER2 status in relation to outcome. PATIENTS AND METHODS: Cut-off levels for Q-PCR and RNA-EP were established in relation to immunohistochemistry (IHC) validated by FISH in a test set of frozen tissue samples from 40 primary breast cancers. The HER2 status was subsequently studied in another validation set of 306 tumors, where Q-PCR and RNA-EP results were compared with previously carried out IHC that we had validated by chromogenic in situ hybridization (CISH). RESULTS: Q-PCR and RNA-EP offered similar sensitivity (90% versus 77%), specificity (93% versus 95%), and negative (99% versus 98%) and positive (63% versus 61%) predictive values for HER2 determinations. Analyses of relapse-free survival (RFS) and overall survival on the basis of 5 and 10 years of follow-up indicated equivalent hazard ratios for all three techniques. In contrast to IHC/CISH, both Q-PCR and RNA-EP analyses of HER2 also gave statistically significant results regarding RFS and breast cancer-corrected survival after 10 years of follow-up. CONCLUSION: The use of RNA-EP and Q-PCR to analyze HER2 in frozen and formalin-fixed breast cancer samples may be an alternate approach to IHC in combination with FISH/CISH.

Gene expression profiling for prognosis using Cox regression.

Given the promise of rich biological information in microarray data we will expect an increasing demand for a robust, practical and well-tested methodology to provide patient prognosis based on gene expression data. In standard settings, with few clinical predictors, such a methodology has been provided by the Cox proportional hazard model, but no corresponding methodology is available to deal with the full set of genes in microarray data. Furthermore, we want the procedure to be able to deal with the general survival data that include censored information. Conceptually such a procedure can be constructed quite easily, but its implementation will never be straightforward due to computational problems. We have developed an approach that relies on an extension of the Cox proportional likelihood that allows random effects parameters. In this approach, we use the full set of genes in the analysis and deal with survival data in the most general way. We describe the development of the model and the steps in the implementation, including a fast computational formula based on a subsampling of the risk set and the singular value decomposition. Finally, we illustrate the methodology using a data set obtained from a cohort of breast cancer patients.

Can axillary dissection be avoided by improved molecular biological diagnosis?

Axillary dissection is presently a routine staging procedure in the management of breast cancer. The use of adjuvant systemic treatment is largely based on the diagnosis of axillary metastases. Routine axillary dissection leads to acute and chronic side-effects in a large proportion of patients. The sentinel node technique is presently explored with the aim of decreasing the need for standard axillary dissection. A complementary way forward is to analyse the primary breast cancer for molecular markers with prognostic significance with reference to the risk for metastatic capacity and thereby obtain a 'biological staging' and identify those patients in need of systemic adjuvant therapy. A large number of molecular biological factors have been shown to have prognostic significance in breast cancer e.g. c-erbB-2, p53, uPA, PAI-I and VEGF. This article reviews the expression of these and other factors in the primary breast cancers in relation to the risk for axillary and systemic metastatic disease, with the long-term aim of excluding routine axillary dissection.

Radiation pneumonitis after breast cancer irradiation: analysis of the complication probability using the relative seriality model.

BACKGROUND: Toxicity of the respiratory system is quite common after radiotherapy of thoracic tumors; breast cancer patients represent one of the groups for which there is also a long expected survival. The quantification of lung tissue response to irradiation is important in designing treatments associated with a minimum of complications and maximum tumor control. METHODS: The study population consisted of 68 patients who received irradiation for breast cancer at Stage II. Radiation pneumonitis was retrospectively assessed on the basis of clinical symptoms and radiological findings. For each patient, a measure of the exposure (i.e., the lung dose-volume histogram [DVH]) and a measure of the outcome was available. Based on these data, a maximum likelihood fitting to the relative seriality model was performed. The uncertainties of the model parameters were calculated and their impact on the dose-response curve was studied. The optimum parameter set was then applied to 5 other patient groups treated for breast cancer, and the normal tissue complication probability (NTCP) was calculated. Each group was individuated by the radiotherapy treatment technique used; the dose distribution in the lung was described by a mean DVH and the incidence of radiation pneumonitis in each group was known. Lung radiosensitivity was assumed to be homogeneous through all of the calculations. RESULTS: The relative seriality model could describe the dataset. The volume effect was found to be relevant in the description of radiation pneumonitis. Age was found to be associated with increased risk of radiation pneumonitis. Two distinct dose-response curves were obtained by splitting the group according to age. The impact of the parameter uncertainties on the dose-response curve was quite large. The parameter set determined could be used predictively on 3 of the 5 patient groups. CONCLUSION: The complication data could be modeled with the relative seriality model. However, further independent datasets, classified according to the same endpoint, must be analyzed before introducing NTCP modeling in clinical practice.