Combined Analysis of SNP Array Data Identifies Novel CNV Candidates and Pathways in Ependymoma and Mesothelioma

Custom Array Comparative Genomic Hybridization: the Importance of DNA Quality, an Expert Eye, and Variant Validation

The presence of false positive and false negative results in the Array Comparative Genomic Hybridization (aCGH) design is poorly addressed in literature reports. We took advantage of a custom aCGH recently carried out to analyze its design performance, the use of several Agilent aberrations detection algorithms, and the presence of false results. Our study provides a confirmation that the high density design does not generate more noise than standard designs and, might reach a good resolution. We noticed a not negligible presence of false negative and false positive results in the imbalances call performed by the Agilent software. The Aberration Detection Method 2 (ADM-2) algorithm with a threshold of 6 performed quite well, and the array design proved to be reliable, provided that some additional filters are applied, such as considering only intervals with average absolute log₂ratio above 0.3. We also propose an additional filter that takes into account the proportion of probes with log₂ratio exceeding suggestive values for gain or loss. In addition, the quality of samples was confirmed to be a crucial parameter. Finally, this work raises the importance of evaluating the samples profiles by eye and the necessity of validating the imbalances detected.

Using high-throughput sequencing transcriptome data for INDEL detection: challenges for cancer drug discovery

INTRODUCTION

A cancer cell is a mosaic of genomic and epigenomic alterations. Distinct cancer molecular signatures can be observed depending on tumor type or patient genetic background. One type of genomic alteration is the insertion and/or deletion (INDEL) of nucleotides in the DNA sequence, which may vary in length, and may change the encoded protein or modify protein domains. INDELs are associated to a large number of diseases and their detection is done based on low-throughput techniques. However, high-throughput sequencing has also started to be used for detection of novel disease-causing INDELs. This search may identify novel drug targets.

AREAS COVERED

This review presents examples of using high-throughput sequencing (DNA-Seq and RNA-Seq) to investigate the incidence of INDELs in coding regions of human genes. Some of these examples successfully utilized RNA-Seq to identify INDELs associated to diseases. In addition, other studies have described small INDELs related to chemo-resistance or poor outcome of patients, while structural variants were associated with a better clinical outcome.

EXPERT OPINION

On average, there is twice as much RNA-Seq data available at the most used repositories for such data compared to DNA-Seq. Therefore, using RNA-Seq data is a promising strategy for studying cancer samples with unknown mechanisms of drug resistance, aiming at the discovery of proteins with potential as novel drug targets.