Long-term hepatic safety of lomitapide in homozygous familial hypercholesterolaemia.

INTRODUCTION: Lomitapide is a microsomal triglyceride transfer protein inhibitor for patients with homozygous familial hypercholesterolaemia. Due to its mechanism of action, potential hepatic effects of lomitapide are of clinical interest. This study aimed to determine the long-term hepatic safety of lomitapide. METHODS: Data were aggregated from the pivotal phase 3 and extension phase clinical trial with lomitapide (median 5.1 years; serum total bilirubin, transaminases, cytokeratin-18 [CK-18] and enhanced liver fibrosis [ELF] score, fat-soluble vitamins and essential fatty acids), 8-year data from the Lomitapide Observational Worldwide Evaluation Registry (LOWER) and real-world evidence from a cohort of patients treated with lomitapide in Italy (hepatic elastography, and FIB-4 score for hepatic fibrosis). RESULTS: In the phase 3 trial and the LOWER registry, any asymptomatic excursions in liver transaminase levels were not associated with elevations in bilirubin, and no Hy's law cases were detected in up to 8 years follow-up. There were no clinically relevant increases among hepatic biomarkers CK-18, CK-18 fragments or ELF score and fat-soluble vitamins and essential fatty acids remained above normal levels. In 34 patients treated in Italy with lomita pide for more than 9 years, elevations in hepatic fat were mild-to-moderate; hepatic stiffness remained normal, and the mean FIB-4 score remained below the fibrosis threshold value of 2.67. CONCLUSIONS: These data indicate that the hepatic safety of lomitapide remains favourable with no clinically significant elevations in hepatic biomarkers and hepatic stiffness remained normal for more than 9 years follow-up. PHASE 3 TRIAL: NCT00730236; extension phase: NCT00943306; LOWER: NCT02135705.

Validation of cytoplasmic-to-nuclear ratio of survivin as an indicator of improved prognosis in breast cancer.

BACKGROUND: Conflicting data exist regarding the prognostic and predictive impact of survivin (BIRC5) in breast cancer. We previously reported survivin cytoplasmic-to-nuclear ratio (CNR) as an independent prognostic indicator in breast cancer. Here, we validate survivin CNR in a separate and extended cohort. Furthermore, we present new data suggesting that a low CNR may predict outcome in tamoxifen-treated patients. METHODS: Survin expression was assessed using immunhistochemistry on a breast cancer tissue microarray (TMA) containing 512 tumours. Whole slide digital images were captured using an Aperio XT scanner. Automated image analysis was used to identify tumour from stroma and then to quantify tumour-specific nuclear and cytoplasmic survivin. A decision tree model selected using a 10-fold cross-validation approach was used to identify prognostic subgroups based on nuclear and cytoplasmic survivin expression. RESULTS: Following optimisation of the staining procedure, it was possible to evaluate survivin protein expression in 70.1% (n = 359) of the 512 tumours represented on the TMA. Decision tree analysis predicted that nuclear, as opposed to cytoplasmic, survivin was the most important determinant of overall survival (OS) and breast cancer-specific survival (BCSS). The decision tree model confirmed CNR of 5 as the optimum threshold for survival analysis. Univariate analysis demonstrated an association between a high CNR (>5) and a prolonged BCSS (HR 0.49, 95% CI 0.29-0.81, p = 0.006). Multivariate analysis revealed a high CNR (>5) was an independent predictor of BCSS (HR 0.47, 95% CI 0.27-0.82, p = 0.008). An increased CNR was associated with ER positive (p = 0.045), low grade (p = 0.007), Ki-67 (p = 0.001) and Her2 (p = 0.026) negative tumours. Finally, a high CNR was an independent predictor of OS in tamoxifen-treated ER-positive patients (HR 0.44, 95% CI 0.23-0.87, p = 0.018). CONCLUSION: Using the same threshold as our previous study, we have validated survivin CNR as a marker of good prognosis in breast cancer in a large independent cohort. These findings provide robust evidence of the importance of survivin CNR as a breast cancer biomarker, and its potential to predict outcome in tamoxifen-treated patients.

Altered cytoplasmic-to-nuclear ratio of survivin is a prognostic indicator in breast cancer.

PURPOSE: Survivin (BIRC5) is a promising tumor biomarker. Conflicting data exist on its prognostic effect in breast cancer. These data may at least be partly due to the manual interpretation of immunohistochemical staining, especially as survivin can be located in both the nucleus and cytoplasm. Quantitative determination of survivin expression using image analysis offers the opportunity to develop alternative scoring models for survivin immunohistochemistry. Here, we present such a model. EXPERIMENTAL DESIGN: A breast cancer tissue microarray containing 102 tumors was stained with an anti-survivin antibody. Whole-slide scanning was used to capture high-resolution images. These images were analyzed using automated algorithms to quantify the staining. RESULTS: Increased nuclear, but not cytoplasmic, survivin was associated with a reduced overall survival (OS; P = 0.038) and disease-specific survival (P = 0.0015). A high cytoplasmic-to-nuclear ratio (CNR) of survivin was associated with improved OS (P = 0.005) and disease-specific survival (P = 0.05). Multivariate analysis revealed that the survivin CNR was an independent predictor of OS (hazard ratio, 0.09; 95% confidence interval, 0.01-0.76; P = 0.027). A survivin CNR of >5 correlated positively with estrogen receptor (P = 0.019) and progesterone receptor (P = 0.033) levels, whereas it was negatively associated with Ki-67 expression (P = 0.04), p53 status (P = 0.005), and c-myc amplification (P = 0.016). CONCLUSION: Different prognostic information is supplied by nuclear and cytoplasmic survivin in breast cancer. Nuclear survivin is a poor prognostic marker in breast cancer. Moreover, CNR of survivin, as determined by image analysis, is an independent prognostic factor.

DNA microarray-based transcriptomic profiling of an isogenic cell culture model of breast tumour cell invasion.

BACKGROUND: The process of tumour invasion and subsequent metastasis represents the most lethal aspect of cancer and is responsible for the majority of deaths among cancer patients. Our objective was to identify invasion-specific genes in a series of isogenic breast cancer cell lines of differing invasive potential using DNA microarray-based transcriptomic profiling. MATERIALS AND METHODS: A panel of increasingly invasive breast cancer subclones generated from the primary breast cancer cell line, Hs578T, were subjected to DNA microarray analysis using the Affymetrix HG-U133A array. RESULTS: Data analysis using GeneSpring 6.0 generated a list of 508 differentially expressed genes. A total of 71 genes were down-regulated and 437 genes were up-regulated. Array data for 17 genes was validated using quantitative real-time RT-PCR analysis. A correlation coefficient of 0.9249 was obtained when both technology platforms were compared. CONCLUSION: Potential new biomarkers for the diagnosis and treatment of invasive breast cancer have been identified.

CENP-F expression is associated with poor prognosis and chromosomal instability in patients with primary breast cancer.

DNA microarrays have the potential to classify tumors according to their transcriptome. Tissue microarrays (TMAs) facilitate the validation of biomarkers by offering a high-throughput approach to sample analysis. We reanalyzed a high profile breast cancer DNA microarray dataset containing 96 tumor samples using a powerful statistical approach, between group analyses. Among the genes we identified was centromere protein-F (CENP-F), a gene associated with poor prognosis. In a published follow-up breast cancer DNA microarray study, comprising 295 tumour samples, we found that CENP-F upregulation was significantly associated with worse overall survival (p<0.001) and reduced metastasis-free survival (p<0.001). To validate and expand upon these findings, we used 2 independent breast cancer patient cohorts represented on TMAs. CENP-F protein expression was evaluated by immunohistochemistry in 91 primary breast cancer samples from cohort I and 289 samples from cohort II. CENP-F correlated with markers of aggressive tumor behavior including ER negativity and high tumor grade. In cohort I, CENP-F was significantly associated with markers of CIN including cyclin E, increased telomerase activity, c-Myc amplification and aneuploidy. In cohort II, CENP-F correlated with VEGFR2, phosphorylated Ets-2 and Ki67, and in multivariate analysis, was an independent predictor of worse breast cancer-specific survival (p=0.036) and overall survival (p=0.040). In conclusion, we identified CENP-F as a biomarker associated with poor outcome in breast cancer and showed several novel associations of biological significance.

CA IX is an independent prognostic marker in premenopausal breast cancer patients with one to three positive lymph nodes and a putative marker of radiation resistance.

PURPOSE: Hypoxia in breast cancer is associated with poor prognosis and down-regulation of the estrogen receptor. Carbonic anhydrase IX (CA IX) is a hypoxia-inducible gene that has been associated with poor outcome in many epithelial cancers. Previous studies of CA IX in breast cancer have been carried out on mixed cohorts of premenopausal and postmenopausal patients with locally advanced disease and varying treatment regimens. We examined the potential prognostic and predictive role of CA IX in premenopausal breast cancer patients. EXPERIMENTAL DESIGN: Using tissue microarrays, we analyzed CA IX expression in 400 stage II breast cancers from premenopausal women. The patients had previously participated in a randomized control trial comparing 2 years of tamoxifen to no systemic adjuvant treatment. Median follow-up was 13.9 years. RESULTS: CA IX expression correlated positively with tumor size, grade, hypoxia-inducible factor 1alpha, Ki-67, cyclin E, and cyclin A2 expression. CA IX expression correlated negatively with cyclin D1, estrogen receptor, and progesterone receptor. CA IX expression was associated with a reduced relapse-free survival (P=0.032), overall survival (P=0.022), and breast cancer-specific survival (P=0.005). Multivariate analysis revealed that CA IX was an independent prognostic marker in untreated patients with one to three positive lymph nodes (hazard ratio, 3.2; 95% confidence interval, 1.15-9.13; P=0.027). CONCLUSION: CA IX is marker of poor prognosis in premenopausal breast cancer patients and it is an independent predictor of survival in patients with one to three positive lymph nodes. As all these patients received locoregional radiation therapy, CA IX may be associated with resistance to radiotherapy.

The development and validation of the Virtual Tissue Matrix, a software application that facilitates the review of tissue microarrays on line.

BACKGROUND: The Tissue Microarray (TMA) facilitates high-throughput analysis of hundreds of tissue specimens simultaneously. However, bottlenecks in the storage and manipulation of the data generated from TMA reviews have become apparent. A number of software applications have been developed to assist in image and data management; however no solution currently facilitates the easy online review, scoring and subsequent storage of images and data associated with TMA experimentation. RESULTS: This paper describes the design, development and validation of the Virtual Tissue Matrix (VTM). Through an intuitive HTML driven user interface, the VTM provides digital/virtual slide based images of each TMA core and a means to record observations on each TMA spot. Data generated from a TMA review is stored in an associated relational database, which facilitates the use of flexible scoring forms. The system allows multiple users to record their interpretation of each TMA spot for any parameters assessed. Images generated for the VTM were captured using a standard background lighting intensity and corrective algorithms were applied to each image to eliminate any background lighting hue inconsistencies or vignetting. Validation of the VTM involved examination of inter-and intra-observer variability between microscope and digital TMA reviews. Six bladder TMAs were immunohistochemically stained for E-Cadherin, beta-Catenin and PhosphoMet and were assessed by two reviewers for the amount of core and tumour present, the amount and intensity of membrane, cytoplasmic and nuclear staining. CONCLUSION: Results show that digital VTM images are representative of the original tissue viewed with a microscope. There were equivalent levels of inter-and intra-observer agreement for five out of the eight parameters assessed. Results also suggest that digital reviews may correct potential problems experienced when reviewing TMAs using a microscope, for example, removal of background lighting variance and tint, and potential disorientation of the reviewer, which may have resulted in the discrepancies evident in the remaining three parameters.

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.