Dataset Information

Somatic mutations and progressive monosomy modify SAMD9-related phenotypes in humans.

ABSTRACT: It is well established that somatic genomic changes can influence phenotypes in cancer, but the role of adaptive changes in developmental disorders is less well understood. Here we have used next-generation sequencing approaches to identify de novo heterozygous mutations in sterile ? motif domain-containing protein 9 (SAMD9, located on chromosome 7q21.2) in 8 children with a multisystem disorder termed MIRAGE syndrome that is characterized by intrauterine growth restriction (IUGR) with gonadal, adrenal, and bone marrow failure, predisposition to infections, and high mortality. These mutations result in gain of function of the growth repressor product SAMD9. Progressive loss of mutated SAMD9 through the development of monosomy 7 (-7), deletions of 7q (7q-), and secondary somatic loss-of-function (nonsense and frameshift) mutations in SAMD9 rescued the growth-restricting effects of mutant SAMD9 proteins in bone marrow and was associated with increased length of survival. However, 2 patients with -7 and 7q- developed myelodysplastic syndrome, most likely due to haploinsufficiency of related 7q21.2 genes. Taken together, these findings provide strong evidence that progressive somatic changes can occur in specific tissues and can subsequently modify disease phenotype and influence survival. Such tissue-specific adaptability may be a more common mechanism modifying the expression of human genetic conditions than is currently recognized.

SUBMITTER: Buonocore F

PROVIDER: S-EPMC5409795 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Somatic mutations and progressive monosomy modify SAMD9-related phenotypes in humans.

Buonocore Federica F Kühnen Peter P Suntharalingham Jenifer P JP Del Valle Ignacio I Digweed Martin M Stachelscheid Harald H Khajavi Noushafarin N Didi Mohammed M Brady Angela F AF Blankenstein Oliver O Procter Annie M AM Dimitri Paul P Wales Jerry K H JKH Ghirri Paolo P Knöbl Dieter D Strahm Brigitte B Erlacher Miriam M Wlodarski Marcin W MW Chen Wei W Kokai George K GK Anderson Glenn G Morrogh Deborah D Moulding Dale A DA McKee Shane A SA Niemeyer Charlotte M CM Grüters Annette A Achermann John C JC

The Journal of clinical investigation 20170327 5

It is well established that somatic genomic changes can influence phenotypes in cancer, but the role of adaptive changes in developmental disorders is less well understood. Here we have used next-generation sequencing approaches to identify de novo heterozygous mutations in sterile α motif domain-containing protein 9 (SAMD9, located on chromosome 7q21.2) in 8 children with a multisystem disorder termed MIRAGE syndrome that is characterized by intrauterine growth restriction (IUGR) with gonadal, ...[more]

PMID: 28346228

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Project description:PET-based radiomics have been used to noninvasively quantify the metabolic tumor phenotypes; however, little is known about the relationship between these phenotypes and underlying somatic mutations. This study assessed the association and predictive power of 18F-FDG PET-based radiomic features for somatic mutations in non-small cell lung cancer patients. Methods: Three hundred forty-eight non-small cell lung cancer patients underwent diagnostic 18F-FDG PET scans and were tested for genetic mutations. Thirteen percent (44/348) and 28% (96/348) of patients were found to harbor epidermal growth factor receptor (EGFR) or Kristen rat sarcoma viral (KRAS) mutations, respectively. We evaluated 21 imaging features: 19 independent radiomic features quantifying phenotypic traits and 2 conventional features (metabolic tumor volume and maximum SUV). The association between imaging features and mutation status (e.g., EGFR-positive [EGFR+] vs. EGFR-negative) was assessed using the Wilcoxon rank-sum test. The ability of each imaging feature to predict mutation status was evaluated by the area under the receiver operating curve (AUC) and its significance was compared with a random guess (AUC = 0.5) using the Noether test. All P values were corrected for multiple hypothesis testing by controlling the false-discovery rate (FDRWilcoxon, FDRNoether) with a significance threshold of 10%. Results: Eight radiomic features and both conventional features were significantly associated with EGFR mutation status (FDRWilcoxon = 0.01-0.10). One radiomic feature (normalized inverse difference moment) outperformed all other features in predicting EGFR mutation status (EGFR+ vs. EGFR-negative, AUC = 0.67, FDRNoether = 0.0032), as well as differentiating between KRAS-positive and EGFR+ (AUC = 0.65, FDRNoether = 0.05). None of the features was associated with or predictive of KRAS mutation status (KRAS-positive vs. KRAS-negative, AUC = 0.50-0.54). Conclusion: Our results indicate that EGFR mutations may drive different metabolic tumor phenotypes that are captured in PET images, whereas KRAS-mutated tumors do not. This proof-of-concept study sheds light on genotype-phenotype interactions, using radiomics to capture and describe the phenotype, and may have potential for developing noninvasive imaging biomarkers for somatic mutations.

Dataset Information

Somatic mutations and progressive monosomy modify SAMD9-related phenotypes in humans.

Publications

Somatic mutations and progressive monosomy modify SAMD9-related phenotypes in humans.

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