Multi-Modality Analysis Improves Survival Prediction in Enucleated Uveal Melanoma Patients.

Purpose: Uveal melanoma (UM) is characterized by multiple chromosomal rearrangements and recurrent mutated genes. The aim of this study was to investigate if copy number variations (CNV) alone and in combination with other genetic and clinico-histopathological variables can be used to stratify for disease-free survival (DFS) in enucleated patients with UM.

Methods: We analyzed single nucleotide polymorphisms (SNP) array data of primary tumors and other clinical variables of 214 UM patients from the Rotterdam Ocular Melanoma Study (ROMS) cohort.

Endogenous Tumor Suppressor microRNA-193b: Therapeutic and Prognostic Value in Acute Myeloid Leukemia.

Purpose Dysregulated microRNAs are implicated in the pathogenesis and aggressiveness of acute myeloid leukemia (AML). We describe the effect of the hematopoietic stem-cell self-renewal regulating miR-193b on progression and prognosis of AML. Methods We profiled miR-193b-5p/3p expression in cytogenetically and clinically characterized de novo pediatric AML (n = 161) via quantitative real-time polymerase chain reaction and validated our findings in an independent cohort of 187 adult patients.

Classification of pediatric acute myeloid leukemia based on miRNA expression profiles.

Pediatric acute myeloid leukemia (AML) is a heterogeneous disease with respect to biology as well as outcome. In this study, we investigated whether known biological subgroups of pediatric AML are reflected by a common microRNA (miRNA) expression pattern. We assayed 665 miRNAs on 165 pediatric AML samples.

Pediatric non-Down syndrome acute megakaryoblastic leukemia is characterized by distinct genomic subsets with varying outcomes.

Acute megakaryoblastic leukemia (AMKL) is a subtype of acute myeloid leukemia (AML) in which cells morphologically resemble abnormal megakaryoblasts. While rare in adults, AMKL accounts for 4-15% of newly diagnosed childhood AML cases. AMKL in individuals without Down syndrome (non-DS-AMKL) is frequently associated with poor clinical outcomes.

MicroRNA-106b~25 cluster is upregulated in relapsed MLL-rearranged pediatric acute myeloid leukemia.

The most important reason for therapy failure in pediatric acute myeloid leukemia (AML) is relapse. In order to identify miRNAs that contribute to the clonal evolution towards relapse in pediatric AML, miRNA expression profiling of 127 de novo pediatric AML cases were used. In the diagnostic phase, no miRNA signatures could be identified that were predictive for relapse occurrence, in a large pediatric cohort, nor in a nested mixed lineage leukemia (MLL)-rearranged pediatric cohort.

Reduced genomic tumor heterogeneity after neoadjuvant chemotherapy is related to favorable outcome in patients with esophageal adenocarcinoma.

Neoadjuvant chemo(radio)therapy followed by surgery is the standard of care for patients with locally advanced resectable esophageal adenocarcinoma (EAC). There is increasing evidence that drug resistance might be related to genomic heterogeneity. We investigated whether genomic tumor heterogeneity is different after cytotoxic chemotherapy and is associated with EAC patient survival.

Subtype prediction in pediatric acute myeloid leukemia: classification using differential network rank conservation revisited.

Background: One of the most important application spectrums of transcriptomic data is cancer phenotype classification. Many characteristics of transcriptomic data, such as redundant features and technical artifacts, make over-fitting commonplace. Promising classification results often fail to generalize across datasets with different sources, platforms, or preprocessing.

Recurrent deletions of IKZF1 in pediatric acute myeloid leukemia.

IKAROS family zinc finger 1/IKZF1 is a transcription factor important in lymphoid differentiation, and a known tumor suppressor in acute lymphoid leukemia. Recent studies suggest that IKZF1 is also involved in myeloid differentiation. To investigate whether IKZF1 deletions also play a role in pediatric acute myeloid leukemia, we screened a panel of pediatric acute myeloid leukemia samples for deletions of the IKZF1 locus using multiplex ligation-dependent probe amplification and for mutations using direct sequencing.

HCsnip: An R Package for Semi-supervised Snipping of the Hierarchical Clustering Tree.

Hierarchical clustering (HC) is one of the most frequently used methods in computational biology in the analysis of high-dimensional genomics data. Given a data set, HC outputs a binary tree leaves of which are the data points and internal nodes represent clusters of various sizes. Normally, a fixed-height cut on the HC tree is chosen, and each contiguous branch of data points below that height is considered as a separate cluster.

Semi-supervised adaptive-height snipping of the hierarchical clustering tree.

Background: In genomics, hierarchical clustering (HC) is a popular method for grouping similar samples based on a distance measure. HC algorithms do not actually create clusters, but compute a hierarchical representation of the data set. Usually, a fixed height on the HC tree is used, and each contiguous branch of samples below that height is considered a separate cluster.

stepwiseCM: An R Package for Stepwise Classification of Cancer Samples Using Multiple Heterogeneous Data Sets.

This paper presents the R/Bioconductor package stepwiseCM, which classifies cancer samples using two heterogeneous data sets in an efficient way. The algorithm is able to capture the distinct classification power of two given data types without actually combining them. This package suits for classification problems where two different types of data sets on the same samples are available.

Colorectal adenoma to carcinoma progression is accompanied by changes in gene expression associated with ageing, chromosomal instability, and fatty acid metabolism.

Background: Colorectal cancer develops in a multi-step manner from normal epithelium, through a pre-malignant lesion (so-called adenoma), into a malignant lesion (carcinoma), which invades surrounding tissues and eventually can spread systemically (metastasis). It is estimated that only about 5% of adenomas do progress to a carcinoma.

Aim: The present study aimed to unravel the biology of adenoma to carcinoma progression by mRNA expression profiling, and to identify candidate biomarkers for adenomas that are truly at high risk of progression.

Stepwise classification of cancer samples using clinical and molecular data.

Background: Combining clinical and molecular data types may potentially improve prediction accuracy of a classifier. However, currently there is a shortage of effective and efficient statistical and bioinformatic tools for true integrative data analysis. Existing integrative classifiers have two main disadvantages: First, coarse combination may lead to subtle contributions of one data type to be overshadowed by more obvious contributions of the other.