MADloy: robust detection of mosaic loss of chromosome Y from genotype-array-intensity data.

BACKGROUND: Accurate protocols and methods to robustly detect the mosaic loss of chromosome Y (mLOY) are needed given its reported role in cancer, several age-related disorders and overall male mortality. Intensity SNP-array data have been used to infer mLOY status and to determine its prominent role in male disease. However, discrepancies of reported findings can be due to the uncertainty and variability of the methods used for mLOY detection and to the differences in the tissue-matrix used. RESULTS: We created a publicly available software tool called MADloy (Mosaic Alteration Detection for LOY) that incorporates existing methods and includes a new robust approach, allowing efficient calling in large studies and comparisons between methods. MADloy optimizes mLOY calling by correctly modeling the underlying reference population with no-mLOY status and incorporating B-deviation information. We observed improvements in the calling accuracy to previous methods, using experimentally validated samples, and an increment in the statistical power to detect associations with disease and mortality, using simulation studies and real dataset analyses. To understand discrepancies in mLOY detection across different tissues, we applied MADloy to detect the increment of mLOY cellularity in blood on 18 individuals after 3 years and to confirm that its detection in saliva was sub-optimal (41%). We additionally applied MADloy to detect the down-regulation genes in the chromosome Y in kidney and bladder tumors with mLOY, and to perform pathway analyses for the detection of mLOY in blood. CONCLUSIONS: MADloy is a new software tool implemented in R for the easy and robust calling of mLOY status across different tissues aimed to facilitate its study in large epidemiological studies.

Optimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies.

PURPOSE: Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients' characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies. METHODS: 68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test FANCA missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies. RESULTS: We identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two FANCA variants reported in mutations databases as 'affecting functions' are SNPs. Deep analysis of sequencing data revealed patients' true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) CONCLUSION: WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.

Novel KIT mutation presenting as marked lentiginosis.

Although lentigines are usually benign, they can be associated with a number of genetic syndromes in which neoplasms and other multi-system pathological processes occur. Here, we report the case of a 6-year-old girl who presented with atypical lentiginosis and hyperpigmentation caused by a de novo genetic variant in the KIT gene.

Detectable clonal mosaicism in blood as a biomarker of cancer risk in Fanconi anemia.

Detectable clonal mosaicism for large chromosomal events has been associated with aging and an increased risk of hematological and some solid cancers. We hypothesized that genetic cancer predisposition disorders, such as Fanconi anemia (FA), could manifest a high rate of chromosomal mosaic events (CMEs) in peripheral blood, which could be used as early biomarkers of cancer risk. We studied the prevalence of CMEs by single-nucleotide polymorphism (SNP) array in 130 FA patients' blood DNA and their impact on cancer risk. We detected 51 CMEs (4.4-159 Mb in size) in 16 out of 130 patients (12.3%), of which 9 had multiple CMEs. The most frequent events were gains at 3q (n = 6) and 1q (n = 5), both previously associated with leukemia, as well as rearrangements with breakpoint clustering within the major histocompatibility complex locus (P = 7.3 × 10-9). Compared with 15 743 age-matched population controls, FA patients had a 126 to 140 times higher risk of detectable CMEs in blood (P < 2.2 × 10-16). Prevalent and incident hematologic and solid cancers were more common in CME carriers (odds ratio [OR] = 11.6, 95% confidence interval [CI] = 3.4-39.3, P = 2.8 × 10-5), leading to poorer prognosis. The age-adjusted hazard risk (HR) of having cancer was almost 5 times higher in FA individuals with CMEs than in those without CMEs. Regarding survival, the HR of dying was 4 times higher in FA individuals having CMEs (HR = 4.0, 95% CI = 2.0-7.9, P = 5.7 × 10-5). Therefore, our data suggest that molecular karyotyping with SNP arrays in easy-to-obtain blood samples could be used for better monitoring of bone marrow clonal events, cancer risk, and overall survival of FA patients.