Hierarchical clustering of flow cytometry data for the study of conventional central chondrosarcoma

We have investigated the use of hierarchical clustering of flow cytometry data to classify samples of conventional central chondrosarcoma, a malignant cartilage forming tumor of uncertain cellular origin, according to similarities with surface marker profiles of several known cell types. Human primary chondrosarcoma cells, articular chondrocytes, mesenchymal stem cells, fibroblasts, and a panel of tumor cell lines from chondrocytic or epithelial origin were clustered based on the expression profile of eleven surface markers. For clustering, eight hierarchical clustering algorithms, three distance metrics, as well as several approaches for data preprocessing, including multivariate outlier detection, logarithmic transformation, and z-score normalization, were systematically evaluated. By selecting clustering approaches shown to give reproducible results for cluster recovery of known cell types, primary conventional central chondrosacoma cells could be grouped in two main clusters with distinctive marker expression signatures: one group clustering together with mesenchymal stem cells (CD49b-high/CD10-low/CD221-high) and a second group clustering close to fibroblasts (CD49b-low/CD10-high/CD221-low). Hierarchical clustering also revealed substantial differences between primary conventional central chondrosarcoma cells and established chondrosarcoma cell lines, with the latter not only segregating apart from primary tumor cells and normal tissue cells, but clustering together with cell lines from epithelial lineage. Our study provides a foundation for the use of hierarchical clustering applied to flow cytometry data as a powerful tool to classify samples according to marker expression patterns, which could lead to uncover new cancer subtypes.

Circulating microRNA profiling in patients with advanced non-squamous NSCLC receiving bevacizumab/erlotinib followed by platinum-based chemotherapy at progression (SAKK 19/05).

OBJECTIVES Molecular subclassification of non small-cell lung cancer (NSCLC) is essential to improve clinical outcome. This study assessed the prognostic and predictive value of circulating micro-RNA (miRNA) in patients with non-squamous NSCLC enrolled in the phase II SAKK (Swiss Group for Clinical Cancer Research) trial 19/05, receiving uniform treatment with first-line bevacizumab and erlotinib followed by platinum-based chemotherapy at progression. MATERIALS AND METHODS Fifty patients with baseline and 24 h blood samples were included from SAKK 19/05. The primary study endpoint was to identify prognostic (overall survival, OS) miRNA's. Patient samples were analyzed with Agilent human miRNA 8x60K microarrays, each glass slide formatted with eight high-definition 60K arrays. Each array contained 40 probes targeting each of the 1347 miRNA. Data preprocessing included quantile normalization using robust multi-array average (RMA) algorithm. Prognostic and predictive miRNA expression profiles were identified by Spearman's rank correlation test (percentage tumor shrinkage) or log-rank testing (for time-to-event endpoints). RESULTS Data preprocessing kept 49 patients and 424 miRNA for further analysis. Ten miRNA's were significantly associated with OS, with hsa-miR-29a being the strongest prognostic marker (HR=6.44, 95%-CI 2.39-17.33). Patients with high has-miR-29a expression had a significantly lower survival at 10 months compared to patients with a low expression (54% versus 83%). Six out of the 10 miRNA's (hsa-miRN-29a, hsa-miR-542-5p, hsa-miR-502-3p, hsa-miR-376a, hsa-miR-500a, hsa-miR-424) were insensitive to perturbations according to jackknife cross-validation on their HR for OS. The respective principal component analysis (PCA) defined a meta-miRNA signature including the same 6 miRNA's, resulting in a HR of 0.66 (95%-CI 0.53-0.82). CONCLUSION Cell-free circulating miRNA-profiling successfully identified a highly prognostic 6-gene signature in patients with advanced non-squamous NSCLC. Circulating miRNA profiling should further be validated in external cohorts for the selection and monitoring of systemic treatment in patients with advanced NSCLC.