Identification and prioritization of myeloid malignancy germline variants in a large cohort of adult AML patients

Blood ◽  
2021 ◽  
Author(s):  
Fei Yang ◽  
Nicola Long ◽  
Tauangtham Anekpuritanang ◽  
Daniel Bottomly ◽  
Jonathan C. Savage ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Sequencing Data ◽  
Germline Variants ◽  
Variant Of Uncertain Significance ◽  
Functional Studies ◽  
Variants Of Unknown Significance ◽  
Manual Curation ◽  
Unknown Significance ◽  
Uncertain Significance ◽  
Whole Exome Sequencing Data

Inherited predisposition to myeloid malignancies is more common than previously appreciated. We analyzed the whole-exome sequencing data of paired leukemia and skin biopsy samples from 391 adult patients from the Beat AML 1.0 consortium. Using the 2015 ACMG guidelines for variant interpretation, we curated 1,547 unique variants from 228 genes. The pathogenic/likely pathogenic (P/LP) germline variants were identified in 53 AML patients (13.6%) in 34 genes. 41% of variants were in DNA damage response genes, and the most frequently mutated genes were CHEK2 (8 patients) and DDX41 (7 patients). 44% of the pathogenic germline variants were in genes considered clinically actionable (tier 1). Pathogenic germline variants were also found in new candidate genes (DNAH5, DNAH9, DNMT3A, SUZ12). No strong correlation was found between the germline mutational rate and age of AML onset. Among 49 patients who have a reported history of at least one family member affected with hematological malignancies, six patients harbored known P/LP germline variants and the remaining patients had at least one variant of uncertain significance, suggesting a need for further functional validation studies. Using CHEK2 as an example, we show that three-dimensional protein modeling can be one of the effective methodologies to prioritize variants of unknown significance for functional studies. Further, we evaluated an in-silico approach that applies ACMG/AMP curation in an automated manner using the tool for assessment and prioritization in exome studies (TAPES), which can minimize manual curation time for variants. Overall, our findings suggest a need to comprehensively understand the predisposition potential of many germline variants in order to enable closer monitoring for disease management and treatment interventions for affected patients and families.

scholarly journals Incidental germline findings during molecular profiling of tumor tissues for precision oncology: molecular survey and methodological obstacles

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Alexandra Lebedeva ◽  
Yulia Shaykhutdinova ◽  
Daria Seriak ◽  
Ekaterina Ignatova ◽  
Ekaterina Rozhavskaya ◽  
...  
Keyword(s):  
Normal Tissue ◽  
Sanger Sequencing ◽  
Computational Prediction ◽  
Bioinformatic Analysis ◽  
Molecular Profiling ◽  
Precision Oncology ◽  
Germline Variants ◽  
Manual Curation ◽  
Uncertain Significance ◽  
Tumor Types

Abstract Background A fraction of patients referred for complex molecular profiling of biopsied tumors may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Neither the bioinformatic analysis nor the reporting of such incidental germline findings are standardized. Methods Data from Next-Generation Sequencing (NGS) of biopsied tumor samples referred for complex molecular profiling were analyzed for germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. When possible, the origin of the variant was validated by Sanger sequencing of the sample of normal tissue. The variants’ pathogenicity was assessed according to ACMG/AMP. Results Tumors were sampled from 183 patients (Males: 75 [41.0%]; Females: 108 [59.0%]; mean [SD] age, 57.7 [13.3] years) and analysed by targeted NGS. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). A total of 56 sequence variants in genes associated with HCS were detected in 40 patients. Of them, 17 variants found in 14 patients were predicted to be of germline origin, with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV), and 9 as variants of uncertain significance (VUS). For the 41 out of 42 (97%) missense variants in HCS-associated genes, the results of computational prediction of variant origin were concordant with that of experimental examination. We estimate that Sanger sequencing of a sample of normal tissue would be required for ~ 1–7% of the total assessed cases with PV or LPV, when necessity to follow with genetic counselling referral in ~ 2–15% of total assessed cases (PV, LPV or VUS found in HCS genes). Conclusion Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of patients with newly detected variants in genes associated with HCS.

scholarly journals A computational and structural analysis of germline and somatic variants affecting the DDR mechanism, and their impact on human diseases

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lorena Magraner-Pardo ◽  
Roman A. Laskowski ◽  
Tirso Pons ◽  
Janet M. Thornton
Keyword(s):  
Prostate Cancer ◽  
Dna Damage ◽  
Dna Damage Response ◽  
Protein Interaction ◽  
Three Dimensional ◽  
Protein Protein Interaction ◽  
Variants Of Unknown Significance ◽  
Damage Response ◽  
Dna Variants ◽  
Unknown Significance

AbstractDNA-Damage Response (DDR) proteins are crucial for maintaining the integrity of the genome by identifying and repairing errors in DNA. Variants affecting their function can have severe consequences since failure to repair damaged DNA can result in cells turning cancerous. Here, we compare germline and somatic variants in DDR genes, specifically looking at their locations in the corresponding three-dimensional (3D) structures, Pfam domains, and protein–protein interaction interfaces. We show that somatic variants in metastatic cases are more likely to be found in Pfam domains and protein interaction interfaces than are pathogenic germline variants or variants of unknown significance (VUS). We also show that there are hotspots in the structures of ATM and BRCA2 proteins where pathogenic germline, and recurrent somatic variants from primary and metastatic tumours, cluster together in 3D. Moreover, in the ATM, BRCA1 and BRCA2 genes from prostate cancer patients, the distributions of germline benign, pathogenic, VUS, and recurrent somatic variants differ across Pfam domains. Together, these results provide a better characterisation of the most recurrent affected regions in DDRs and could help in the understanding of individual susceptibility to tumour development.

scholarly journals A novel activating JAK1 mutation in chronic eosinophilic leukemia

2021 ◽  
Vol 5 (18) ◽  
pp. 3581-3586 ◽  
Author(s):  
William Shomali ◽  
Alisa Damnernsawad ◽  
Talent Theparee ◽  
David Sampson ◽  
Quinlan Morrow ◽  
...  
Keyword(s):  
World Health ◽  
Variant Of Uncertain Significance ◽  
Jak2 Inhibitor ◽  
Functional Studies ◽  
Chronic Eosinophilic Leukemia ◽  
Uncertain Significance ◽  
Health Organization ◽  
Next Generation Sequencing Ngs ◽  
Stat Pathway

Abstract Hypereosinophilia (HE) has been defined as persistent eosinophilia >1.5 × 109/L; it is broadly divided into primary HE (clonal or neoplastic; HEN), secondary/reactive HE (HER), or HE of undetermined significance (HEUS) when no cause is identified. The use of myeloid next-generation sequencing (NGS) panels has led to the detection of several mutations in patients previously diagnosed with HEUS, reassigning some patients to the category of HEN, specifically the World Health Organization category of chronic eosinophilic leukemia, not otherwise specified (CEL, NOS). Here, we describe a novel somatic JAK1 pseudokinase domain mutation (R629_S632delinsSA) in a patient with HE that had initially been characterized as a variant of uncertain significance. We performed functional studies that demonstrated that this mutation results in growth factor independence of Ba/F3 cells in vitro and activation of the JAK-STAT pathway. These effects were abrogated by the JAK1/JAK2 inhibitor ruxolitinib. R629_S632delinsSA is the first known somatic mutation in JAK1 linked to a clonal eosinophilic neoplasm, and highlights the importance of the JAK-STAT pathway in eosinophil survival.

scholarly journals Integrated Analysis of Germline and Tumor DNA Identifies New Candidate Genes Involved in Familial Colorectal Cancer

Cancers ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 362 ◽  
Author(s):  
Marcos Díaz-Gay ◽  
Sebastià Franch-Expósito ◽  
Coral Arnau-Collell ◽  
Solip Park ◽  
Fran Supek ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Candidate Genes ◽  
Copy Number Variants ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Functional Studies ◽  
Mutational Profiling ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

Colorectal cancer (CRC) shows aggregation in some families but no alterations in the known hereditary CRC genes. We aimed to identify new candidate genes which are potentially involved in germline predisposition to familial CRC. An integrated analysis of germline and tumor whole-exome sequencing data was performed in 18 unrelated CRC families. Deleterious single nucleotide variants (SNV), short insertions and deletions (indels), copy number variants (CNVs) and loss of heterozygosity (LOH) were assessed as candidates for first germline or second somatic hits. Candidate tumor suppressor genes were selected when alterations were detected in both germline and somatic DNA, fulfilling Knudson’s two-hit hypothesis. Somatic mutational profiling and signature analysis were also performed. A series of germline-somatic variant pairs were detected. In all cases, the first hit was presented as a rare SNV/indel, whereas the second hit was either a different SNV (3 genes) or LOH affecting the same gene (141 genes). BRCA2, BLM, ERCC2, RECQL, REV3L and RIF1 were among the most promising candidate genes for germline CRC predisposition. The identification of new candidate genes involved in familial CRC could be achieved by our integrated analysis. Further functional studies and replication in additional cohorts are required to confirm the selected candidates.

scholarly journals Utilizing ExAC to Assess the Hidden Contribution of Variants of Unknown Significance to Sanfilippo Type B Incidence

2018 ◽  
Author(s):  
Wyatt T. Clark ◽  
G. Karen Yu ◽  
Mika Aoyagi-Scharber ◽  
Jonathan H. LeBowitz
Keyword(s):  
Disease Incidence ◽  
Potential Contribution ◽  
Type B ◽  
Lysosomal Storage ◽  
Sequencing Data ◽  
Activity Data ◽  
Missense Variants ◽  
Variants Of Unknown Significance ◽  
Monogenic Diseases ◽  
Unknown Significance

AbstractGiven the large and expanding quantity of publicly available sequencing data, it should be possible to extract incidence information for monogenic diseases from allele frequencies, provided one knows which mutations are causal. We tested this idea on a rare, monogenic, lysosomal storage disorder, Sanfilippo Type B (Mucopolysaccharidosis type IIIB).Sanfilippo Type B is caused by mutations in the gene encoding α-N-acetylglucosaminidase (NAGLU). There were 189 NAGLU missense variants found in the ExAC dataset that comprises roughly 60,000 individual exomes. Only 24 of the 189 missense variants were known to be pathogenic; the remaining 165 variants were of unknown significance (VUS), and their potential contribution to disease is unknown.To address this problem, we measured enzymatic activities of 164 NAGLU missense VUS in the ExAC dataset and developed a statistical framework for estimating disease incidence with associated confidence intervals. We found that 25% of VUS decreased the activity of NAGLU to levels consistent with Sanfilippo Type B pathogenic alleles. We found that a substantial fraction of Sanfilippo Type B incidence (67%) could be accounted for by novel mutations not previously identified in patients, illustrating the utility of combining functional activity data for VUS with population-wide allele frequency data in estimating disease incidence.

scholarly journals Predicting ovarian/breast cancer pathogenic risks of BRCA1 gene variants of unknown significance

2020 ◽  
Author(s):  
Hui-Heng Lin ◽  
Hongyan Xu ◽  
Hongbo Hu ◽  
Zhanzhong Ma ◽  
Jie Zhou ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Random Forest ◽  
Clinical Significance ◽  
Brca1 Gene ◽  
Gene Variants ◽  
Sequencing Data ◽  
Forest Model ◽  
Variants Of Unknown Significance ◽  
Sequencing Technologies ◽  
Unknown Significance

AbstractThe difficulty of early diagnosis for ovarian cancer is an important cause of the high mortal rates of ovarian cancer patients. Instead of symptom-based diagnostic methods, modern sequencing technologies enable the access of human’s genetic information via reading DNA/RNA molecules’ nucleotide base sequences. In such way, genes’ mutations and variants could be identified and hence a better clinical diagnosis in molecular level could be expected. However, as sequencing technologies gain more popularity, novel gene variants with unknown clinical significance are found, giving difficulties to interpretations of patients’ genetic data, precise disease diagnoses as well as the making of therapeutic strategies and decisions. In order to solve these issues, it is of critical importance to figure out ways to analyze and interpret such variants. In this work, BRCA1 gene variants with unknown clinical significance were identified from clinical sequencing data, and then we developed machine learning models so as to predict the pathogenicity for variants with unknown clinical significance. Amongst, in performance benchmarking, our optimized random forest model scored 0.85 in area under receiver-operating characteristic curve, which outperformed other models. Finally, we applied the optimized random forest model to predict the pathogenic risks of 7 BRCA1 variants of unknown clinical significances identified from our sequencing data, and 6315 variants of unknown clinical significance in ClinVar database. As a result, our model predicted 4724 benign and 1591 pathogenic variants, which helped the interpretation of these variants of unknown significance and diagnosis.

scholarly journals Interpreting Osteogenesis Imperfecta Variants of Uncertain Significance in the Context of Physical Abuse: A Case Series

2018 ◽  
Vol 08 (02) ◽  
pp. 063-068
Author(s):  
Jennifer Canter ◽  
Vinod Rao ◽  
Vincent Palusci ◽  
David Kronn ◽  
Michal Manaster ◽  
...  
Keyword(s):  
Child Abuse ◽  
Osteogenesis Imperfecta ◽  
Physical Abuse ◽  
Clinical Significance ◽  
Case Series ◽  
Variants Of Unknown Significance ◽  
Unknown Significance ◽  
Potential Abuse ◽  
Uncertain Significance

AbstractUnexplained childhood fracture(s) warrant consideration of physical abuse and osteogenesis imperfecta (OI). Genetic OI testing may identify “variants of unknown significance (VUS).” Interpretation of VUS in context of potential abuse may have protective, criminal, and medical impacts. This case series explores practices regarding clinicians' interpretation of VUS during child abuse evaluations. Variability was noted regarding factors considered for interpreting clinical significance. Based on these cases, recommendations for careful and thorough evaluation are detailed, including proposed use of a limited follow-up skeletal survey in 3 months, as a consideration to assess healing of prior fractures and to look for any additional injuries.

Constitutive mismatch repair defect syndrome: New insights from whole exome sequencing data and functional studies

2016 ◽  
Vol 231 ◽  
pp. S12
Author(s):  
Ahmet Okay Caglayan ◽  
Zeynep E. Erson Omay ◽  
Yavuz Koksal ◽  
Suleyman Coskun ◽  
Ekrem Unal ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Mismatch Repair ◽  
Whole Exome Sequencing ◽  
Sequencing Data ◽  
Functional Studies ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Repair Defect

scholarly journals PRPH2 mutation update: In silico assessment of 245 reported and 7 novel variants in patients with retinal disease

2021 ◽  
Author(s):  
Manon H.C.A Peeters ◽  
Mubeen Khan ◽  
Anoek A.M.B Rooijakkers ◽  
Timo Mulders ◽  
Lonneke Haer-Wigman ◽  
...  
Keyword(s):  
Retinal Disease ◽  
Variants Of Unknown Significance ◽  
Novel Variants ◽  
Unknown Significance ◽  
Uncertain Significance ◽  
Variation Database ◽  
The Many ◽  
Source Variation ◽  
Additional Index

Mutations in PRPH2, encoding peripherin-2, are associated with the development of a wide variety of inherited retinal diseases (IRDs). To determine the causality of the many PRPH2 variants that have been discovered over the last decades, we surveyed all published PRPH2 variants up to July 2020, describing 720 index patients that in total carried 245 unique variants. In addition, we identified seven novel PRPH2 variants in eight additional index patients. The pathogenicity of all variants was determined using the ACMG guidelines. With this, 107 variants were classified as pathogenic, 92 as likely pathogenic, one as benign, and two as likely benign. The remaining 50 variants were classified as variants of uncertain significance. Interestingly, of the in total 252 PRPH2 variants, more than half (n=137) were missense variants. All variants were uploaded into the Leiden Open source Variation Database. Our study underscores the need of experimental assays for variants of unknown significance to improve pathogenicity classification, which is needed to better understand genotype-phenotype correlations, and in the long-term, hopefully also support the development of therapeutic strategies for patients with PRPH2-associated IRD.

scholarly journals Predicting Ovarian/Breast Cancer Pathogenic Risks of Human BRCA1 Gene Variants of Unknown Significance

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Hui-Heng Lin ◽  
Hongyan Xu ◽  
Hongbo Hu ◽  
Zhanzhong Ma ◽  
Jie Zhou ◽  
...  
Keyword(s):  
Random Forest ◽  
Clinical Significance ◽  
High Throughput Sequencing ◽  
Brca1 Gene ◽  
Random Forest Model ◽  
Gene Variants ◽  
Sequencing Data ◽  
Forest Model ◽  
Variants Of Unknown Significance ◽  
Unknown Significance

High-throughput sequencing is gaining popularity in clinical diagnoses, but more and more novel gene variants with unknown clinical significance are being found, giving difficulties to interpretations of people’s genetic data, precise disease diagnoses, and the making of therapeutic strategies and decisions. In order to solve these issues, it is of critical importance to figure out ways to analyze and interpret such variants. In this work, BRCA1 gene variants with unknown clinical significance were identified from clinical sequencing data, and then, we developed machine learning models so as to predict the pathogenicity for variants with unknown clinical significance. Through performance benchmarking, we found that the optimized random forest model scored 0.85 in area under receiver operating characteristic curve, which outperformed other models. Finally, we applied the best random forest model to predict the pathogenicity of 6321 BRCA1 variants from both sequencing data and ClinVar database. As a result, we obtained the predictive pathogenic risks of BRCA1 variants of unknown significance.

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