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Institute
Multiple myeloma (MM) is a largely incurable plasma cell malignancy with a poorly understood and heterogeneous clinical course. To identify potential, functionally relevant somatic mutations in MM, we performed whole-exome sequencing of five primary MM, corresponding germline DNA and six MM cell lines, and developed a bioinformatics strategy that also integrated published mutational data of 38 MM patients. Our analysis confirms that identical, recurrent mutations of single genes are infrequent in MM, but highlights that mutations cluster in important cellular pathways. Specifically, we show enrichment of mutations in adhesion molecules of MM cells, emphasizing the important role for the interaction of the MM cells with their microenvironment. We describe an increased rate of mutations in receptor tyrosine kinases (RTKs) and associated signaling effectors, for example, in EGFR, ERBB3, KRAS and MAP2K2, pointing to a role of aberrant RTK signaling in the development or progression of MM. The diversity of mutations affecting different nodes of a particular signaling network appears to be an intrinsic feature of individual MM samples, and the elucidation of intra- as well as interindividual redundancy in mutations that affect survival pathways will help to better tailor targeted therapeutic strategies to the specific needs of the MM patient.
Clinical relevance of systematic phenotyping and exome sequencing in patients with short stature
(2018)
Purpose
Short stature is a common condition of great concern to patients and their families. Mostly genetic in origin, the underlying cause often remains elusive due to clinical and genetic heterogeneity.
Methods
We systematically phenotyped 565 patients where common nongenetic causes of short stature were excluded, selected 200 representative patients for whole-exome sequencing, and analyzed the identified variants for pathogenicity and the affected genes regarding their functional relevance for growth.
Results
By standard targeted diagnostic and phenotype assessment, we identified a known disease cause in only 13.6% of the 565 patients. Whole-exome sequencing in 200 patients identified additional mutations in known short-stature genes in 16.5% of these patients who manifested only part of the symptomatology. In 15.5% of the 200 patients our findings were of significant clinical relevance. Heterozygous carriers of recessive skeletal dysplasia alleles represented 3.5% of the cases.
Conclusion
A combined approach of systematic phenotyping, targeted genetic testing, and whole-exome sequencing allows the identification of the underlying cause of short stature in at least 33% of cases, enabling physicians to improve diagnosis, treatment, and genetic counseling. Exome sequencing significantly increases the diagnostic yield and consequently care in patients with short stature.
Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.