References of "Max, Stéphanie"
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See detailGenomic Studies of Multiple Myeloma Reveal an Association between X Chromosome Alterations and Genomic Profile Complexity.
Sticca, Tiberio ULg; CABERG, Jean-Hubert ULg; Wenric, Stéphane ULg et al

in Genes, Chromosomes & Cancer (2017), 56

The genomic profile of multiple myeloma (MM) has prognostic value by dividing patients into a good prognosis hyperdiploid group and a bad prognosis non-hyperdiploid group with a higher incidence of IgH ... [more ▼]

The genomic profile of multiple myeloma (MM) has prognostic value by dividing patients into a good prognosis hyperdiploid group and a bad prognosis non-hyperdiploid group with a higher incidence of IgH translocations. This classification, however, is inadequate and many other parameters like mutations, epigenetic modifications and genomic heterogeneity may influence the prognosis. We performed a genomic study by array-based comparative genomic hybridization (aCGH) on a cohort of 162 patients to evaluate the frequency of genomic gains and losses. We identified a high frequency of X chromosome alterations leading to partial Xq duplication, often associated with Xi deletion in female patients. This partial X duplication could be a cytogenetic marker of aneuploidy as it is correlated with a high number of chromosomal breakages. Patient with high level of chromosomal breakage had reduced survival regardless the region implicated. A higher transcriptional level was shown for genes with potential implication in cancer and located in this altered region. Among these genes, IKBKG and IRAK1 are members of the NFKB pathway which plays an important role in MM and is a target for specific treatments. [less ▲]

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See detailExome copy number variation detection: Use of a pool of unrelated healthy tissue as reference sample
Wenric, Stéphane ULg; Sticca, Tiberio ULg; CABERG, Jean-Hubert ULg et al

in Genetic Epidemiology (2017)

An increasing number of bioinformatic tools designed to detect CNVs (copy number variants) in tumor samples based on paired exome data where a matched healthy tissue constitutes the reference have been ... [more ▼]

An increasing number of bioinformatic tools designed to detect CNVs (copy number variants) in tumor samples based on paired exome data where a matched healthy tissue constitutes the reference have been published in the recent years. The idea of using a pool of unrelated healthy DNA as reference has previously been formulated but not thoroughly validated. As of today, the gold standard for CNV calling is still aCGH but there is an increasing interest in detecting CNVs by exome sequencing. We propose to design a metric allowing the comparison of two CNV profiles, independently of the technique used and assessed the validity of using a pool of unrelated healthy DNA instead of a matched healthy tissue as reference in exome-based CNV detection. We compared the CNV profiles obtained with three different approaches (aCGH, exome sequencing with a matched healthy tissue as reference, exome sequencing with a pool of eight unrelated healthy tissue as reference) on three multiple myeloma samples. We show that the usual analyses performed to compare CNV profiles (deletion/amplification ratios and CNV size distribution) lack in precision when confronted with low LRR values, as they only consider the binary status of each CNV. We show that the metric-based distance constitutes a more accurate comparison of two CNV profiles. Based on these analyses, we conclude that a reliable picture of CNV alterations in multiple myeloma samples can be obtained from whole-exome sequencing in the absence of a matched healthy sample. [less ▲]

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