scholarly journals Epigenomic, genomic, and transcriptomic landscape of schwannomatosis

2020 ◽  
Vol 141 (1) ◽  
pp. 101-116
Author(s):  
Sheila Mansouri ◽  
Suganth Suppiah ◽  
Yasin Mamatjan ◽  
Irene Paganini ◽  
Jeffrey C. Liu ◽  
...  
Keyword(s):  
Gene Fusion ◽  
Somatic Mutations ◽  
Genomic Analysis ◽  
Germline Mutations ◽  
Tumor Location ◽  
Molecular Signature ◽  
Structural Rearrangements ◽  
Genomic Features ◽  
Cancer Predisposition Syndrome ◽  
Neuronal Tumors

AbstractSchwannomatosis (SWNTS) is a genetic cancer predisposition syndrome that manifests as multiple and often painful neuronal tumors called schwannomas (SWNs). While germline mutations in SMARCB1 or LZTR1, plus somatic mutations in NF2 and loss of heterozygosity in chromosome 22q have been identified in a subset of patients, little is known about the epigenomic and genomic alterations that drive SWNTS-related SWNs (SWNTS-SWNs) in a majority of the cases. We performed multiplatform genomic analysis and established the molecular signature of SWNTS-SWNs. We show that SWNTS-SWNs harbor distinct genomic features relative to the histologically identical non-syndromic sporadic SWNs (NS-SWNS). We demonstrate the existence of four distinct DNA methylation subgroups of SWNTS-SWNs that are associated with specific transcriptional programs and tumor location. We show several novel recurrent non-22q deletions and structural rearrangements. We detected the SH3PXD2A-HTRA1 gene fusion in SWNTS-SWNs, with predominance in LZTR1-mutant tumors. In addition, we identified specific genetic, epigenetic, and actionable transcriptional programs associated with painful SWNTS-SWNs including PIGF, VEGF, MEK, and MTOR pathways, which may be harnessed for management of this syndrome.

scholarly journals EPCO-04. GENOMIC AND EPIGENOMIC HALLMARKS OF SCHWANNOMATOSIS SCHWANNOMAS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii69-ii70
Author(s):  
Sheila Mansouri ◽  
Suganth Suppiah ◽  
Yasin Mamatjan ◽  
Irene Paganini ◽  
Jeff Liu ◽  
...  
Keyword(s):  
Gene Fusion ◽  
Somatic Mutations ◽  
Germline Mutations ◽  
Molecular Signatures ◽  
Mismatch Repair Genes ◽  
Structural Rearrangements ◽  
Cancer Predisposition Syndrome ◽  
New Treatments ◽  
Neuronal Tumors ◽  
Repair Genes

Abstract Schwannomatosis (SWNTS) is a genetic cancer predisposition syndrome that manifests as multiple and often, painful neuronal tumors called schwannomas (SWNs). Very little is known about the epigenomic and genomic alterations in SWNTS related SWNs (SWNTS-SWNs) other than germline mutations in SMARCB1 and LZTR1 plus somatic mutations in NF2 and loss of heterozygosity in chromosome 22q. Herein, we have comprehensively established the specific molecular signatures of SWNTS-SWNs. We found that tumor anatomic location was associated with pain and distinct DNA methylation and transcriptional signatures. DNA sequencing revealed several novel non-22q deletions, specifically in LZTR1-mutant cases. Whole-genome sequencing identified novel recurrent structural rearrangements. Further, chromosomal aberrations in SWNTS-SWNs were accompanied by increased transcription of mismatch repair genes. Our transcriptome analysis detected the SH3PXD2A-HTRA1 gene fusion in SWNTS-SWNs, more commonly in LZTR1-mutant tumors. In addition, we identified the specific genetic, epigenetic, and transcriptional hallmarks of painful SWNs that may be harnessed to develop new treatments for this debilitating syndrome.

Germline and somatic SNVS calling in NGS panel tumor samples: Approaches to optimize tumor only genomic analysis for cancer precision medicine.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e13011-e13011
Author(s):  
Ruobai Sun ◽  
Pablo Cingolani ◽  
Angeliki Pantazi ◽  
Cheryl Eifert ◽  
Xiu Huang ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Genomic Analysis ◽  
High Specificity ◽  
Cost Effective ◽  
True Positive Rate ◽  
Germline Mutations ◽  
Germline Variants ◽  
Normal Pair ◽  
Tumor Patient ◽  
Large Gene

e13011 Background: Clinical NGS is often limited by tumor only profiling. Discrimination between somatic and likely germline mutations when calling from tumor patient samples is a critical step for clinical genotyping. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal whole genome and whole exome sequencing. Here, we demonstrate approaches of how a cost-effective large gene panel sequencing can be used to call somatic and germline SNVs for tumor only samples. Methods: Tumor, adjacent normal, and matched normal samples are collected from five patients. The somatic mutations were called with GATK Mutect2 in tumor only and adjacent normal. The germline mutations were called individually for all 15 samples with GATK Haplotype caller. To remove germline mutations from tumor only somatic calls, the filters ExAc pop freq, 1000G pop freq, COSMIC were applied on the tumor only somatic calls. PPV (Positive predictive value) for each filter was calculated by dividing the number of somatic mutations in the post-filtering mutation data by the total number of unfiltered mutations. TPR (True Positive Rate, representing sensitivity) was calculated by dividing the number of true somatic mutations in the tumor-only post-filter. Results: Compared with germline mutations called from matched normal, 70% germline mutations were called in RAWE somatic calls. A PPV of 0.71 and a TPR of 0.95 were optimally provided when the filter ExAc pop freq > 0.01 and COSMIC ( > 5 occurrence) applied. For germline mutations called in tumor samples, when compared with those in blood samples and in adjacent normal samples, PPV is 0.99 and TPR is 0.97. For somatic mutations called with tumor-adjacent normal pair mode in Mutect2, PPV is 0.5 and TPR is 0.99. Conclusions: Optimization of tools and parameters in NGS large panels could detect somatic and germline variants with high specificity, sensitivity and accuracy, without matched or adjacent normal. For the germline variants, when adjacent normal is available, it could replace matched normal with high accuracy.

scholarly journals Cutaneous Melanomas Arising during Childhood: An Overview of the Main Entities

2021 ◽  
Vol 8 (3) ◽  
pp. 301-314
Author(s):  
Arnaud de la Fouchardière ◽  
Felix Boivin ◽  
Heather C. Etchevers ◽  
Nicolas Macagno
Keyword(s):  
Lymph Node ◽  
Regional Lymph Node ◽  
Germline Mutations ◽  
Epithelioid Cells ◽  
Superficial Spreading ◽  
Superficial Spreading Melanoma ◽  
Cancer Predisposition Syndrome ◽  
Specific Morphology ◽  
Genetic Features ◽  
Molecular Assessment

Cutaneous melanomas are exceptional in children and represent a variety of clinical situations, each with a different prognosis. In congenital nevi, the risk of transformation is correlated with the size of the nevus. The most frequent type is lateral transformation, extremely rare before puberty, reminiscent of a superficial spreading melanoma (SSM) ex-nevus. Deep nodular transformation is much rarer, can occur before puberty, and must be distinguished from benign proliferative nodules. Superficial spreading melanoma can also arise within small nevi, which were not visible at birth, usually after puberty, and can reveal a cancer predisposition syndrome (CDKN2A or CDK4 germline mutations). Prognosis is correlated with classical histoprognostic features (mainly Breslow thickness). Spitz tumors are frequent in adolescents and encompass benign (Spitz nevus), intermediate (atypical Spitz tumor), and malignant forms (malignant Spitz tumor). The whole spectrum is characterized by specific morphology with spindled and epithelioid cells, genetic features, and an overall favorable outcome even if a regional lymph node is involved. Nevoid melanomas are rare and difficult to diagnose clinically and histologically. They can arise in late adolescence. Their prognosis is currently not very well ascertained. A small group of melanomas remains unclassified after histological and molecular assessment.

scholarly journals Genomic analysis of cancer tissue reveals that somatic mutations commonly occur in a specific motif

2009 ◽  
Vol 30 (1) ◽  
pp. 39-48 ◽  
Author(s):  
Nick M. Makridakis ◽  
Lúcio Fábio Caldas Ferraz ◽  
Juergen K.V. Reichardt
Keyword(s):  
Somatic Mutations ◽  
Genomic Analysis ◽  
Cancer Tissue

Whole-exome sequencing reveals potential germline and somatic mutations in 60 malignant ovarian germ cell tumors

2021 ◽  
Author(s):  
Juan Chen ◽  
Yan Li ◽  
Jianlei Wu ◽  
Yakun Liu ◽  
Shan Kang
Keyword(s):  
Germ Cell ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Peripheral Blood ◽  
Copy Number ◽  
Somatic Mutations ◽  
Germ Cell Tumors ◽  
Germline Mutations ◽  
Deletion Region ◽  
Whole Exome

Abstract Background Malignant ovarian germ cell tumors (MOGCTs) are rare and heterogeneous ovary tumors. We aimed to identify potential germline mutations and somatic mutations in MOGCTs by whole-exome sequencing. Methods The peripheral blood and tumor samples from these patients were used to identify germline mutations and somatic mutations, respectively. For those genes corresponding to copy number alterations (CNA) deletion and duplication region, functional annotation of was performed. Immunohistochemistry was performed to evaluate the expression of mutated genes corresponding to CNA deletion region. Results In peripheral blood, copy number loss and gain were mostly found in yolk sac tumors (YST). Moreover, POU5F1 was the most significant mutated gene with mutation frequency > 10% in both CNA deletion and duplication region. In addition, strong cytoplasm staining of POU5F1 (corresponding to CNA deletion region) was found in 2 YST and nuclear staining in 2 dysgerminomas (DG) tumor samples. Genes corresponding to CNA deletion region were significantly enriched in the signaling pathway of regulating pluripotency of stem cells. In addition, genes corresponding to CNA duplication region were significantly enriched in the signaling pathways of RIG-I-like receptor, Toll-like receptor, NF-kappa B and Jak–STAT. KRT4, RPL14, PCSK6, PABPC3 and SARM1 mutations were detected in both peripheral blood and tumor samples. Conclusions Identification of potential germline mutations and somatic mutations in MOGCTs may provide a new field in understanding the genetic feature of the rare biological tumor type in the ovary.

scholarly journals The Application of Machine Learning to Improve the Subclassification and Prognostication of Acute Myeloid Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 28-28
Author(s):  
Hassan Awada ◽  
Arda Durmaz ◽  
Carmel Gurnari ◽  
Ashwin Kishtagari ◽  
Manja Meggendorfer ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Somatic Mutations ◽  
Cross Validation ◽  
Steering Committee ◽  
Advisory Board ◽  
Advisory Committees ◽  
Genomic Features ◽  
Acute Myeloid

Genetic mutations (somatic or germline), cytogenetic abnormalities and their combinations contribute to the heterogeneity of acute myeloid leukemia (AML) phenotypes. To date, prototypic founder lesions [e.g., t(8;21), inv(16), t(15;17)] define only a fraction of AML subgroups with specific prognoses. Indeed, in a larger proportion of AML patients, somatic mutations or cytogenetic abnormalities potentially serve as driver lesions in combination with numerous acquired secondary hits. However, their combinatorial complexity can preclude the resolution of distinct genomic classifications and overlap across classical pathomorphologic AML subtypes, including de novo/primary (pAML) and secondary AML (sAML) evolving from an antecedent myeloid neoplasm (MN). These prognostically discrete AML subtypes are themselves nonspecific due to variable understanding of their pathogenetic links, especially in cases without overt dysplasia. Without dysplasia, reliance is mainly on anamnestic clinical information that might be unavailable or cannot be correctly assigned due to a short prodromal history of antecedent MN. We explored the potential of genomic markers to sub-classify AML objectively and provide unbiased personalized prognostication, irrespective of the clinicopathological information, and thus become a standard in AML assessment. We collected and analyzed genomic data from a multicenter cohort of 6788 AML patients using standard and machine learning (ML) methods. A total of 13,879 somatic mutations were identified and used to predict traditional pathomorphologic AML classifications. Logistic regression modeling (LRM) detected mutations in CEBPA (both monoallelic "CEBPAMo" and biallelic "CEBPABi"), DNMT3A, FLT3ITD, FLT3TKD, GATA2, IDH1, IDH2R140, NRAS, NPM1 and WT1 being enriched in pAML while mutations in ASXL1, RUNX1, SF3B1, SRSF2, U2AF1, -5/del(5q), -7/del(7q), -17/del(17P), del(20q), +8 and complex karyotype being prevalent in sAML. Despite these significant findings, the genomic profiles of pAML vs. sAML identified by LRM resulted in only 74% cross-validation accuracy of the predictive performance when used to re-assign them. Therefore, we applied Bayesian Latent Class Analysis that identified 4 unique genomic clusters of distinct prognoses [low risk (LR), intermediate-low risk (Int-Lo), intermediate-high risk (Int-Hi) and high risk (HR) of poor survival) that were validated by survival analysis. To link each prognostic group to pathogenetic features, we generated a random forest (RF) model that extracted invariant genomic features driving each group and resulted in 97% cross-validation accuracy when used for prognostication. The model's globally most important genomic features, quantified by mean decrease in accuracy, included NPM1MT, RUNX1MT, ASXL1MT, SRSF2MT, TP53MT, -5/del(5q), DNMT3AMT, -17/del(17p), BCOR/L1MT and others. The LR group was characterized by the highest prevalence of normal cytogenetics (88%) and NPM1MT (100%; 86% with VAF>20%) with co-occurring DNMT3AMT (52%), FLT3ITD-MT (27%; 91% with VAF <50%), IDH2R140-MT (16%, while absent IDH2R172-MT), and depletion or absence of ASXL1MT, EZH2MT, RUNX1MT, TP53MT and complex cytogenetics. Int-Lo had a higher percentage of abnormal cytogenetics cases than LR, the highest frequency of CEBPABi-MT (9%), IDH2R172K-MT (4%), FLT3ITD-MT (14%) and FLT3TKD-MT (6%) occurring without NPM1MT, while absence of NPM1MT, ASXL1MT, RUNX1MT and TP53MT. Int-Hi had the highest frequency of ASXL1MT (39%), BCOR/L1MT (16%), DNMT3AMT without NPM1MT (19%), EZH2MT (9%), RUNX1MT (52%), SF3B1MT (7%), SRSF2MT (38%) and U2AF1MT (12%). Finally, HR had the highest prevalence of abnormal cytogenetics (96%), -5/del(5q) (68%), -7del(7q) (35%), -17del(17p) (31%) and the highest odds of complex karyotype (76%) as well as TP53MT (70%). The model was then internally and externally validated using a cohort of 203 AML cases from the MD Anderson Cancer Center. The RF prognostication model and group-specific survival estimates will be available via a web-based open-access resource. In conclusion, the heterogeneity inherent in the genomic changes across nearly 7000 AML patients is too vast for traditional prediction methods. Using newer ML methods, however, we were able to decipher a set of prognostic subgroups predictive of survival, allowing us to move AML into the era of personalized medicine. Disclosures Advani: OBI: Research Funding; Abbvie: Research Funding; Macrogenics: Research Funding; Glycomimetics: Consultancy, Other: Steering committee/ honoraria, Research Funding; Immunogen: Research Funding; Seattle Genetics: Other: Advisory board/ honoraria, Research Funding; Amgen: Consultancy, Other: steering committee/ honoraria, Research Funding; Kite: Other: Advisory board/ honoraria; Pfizer: Honoraria, Research Funding; Novartis: Consultancy, Other: advisory board; Takeda: Research Funding. Ravandi:Abbvie: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Orsenix: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Xencor: Consultancy, Honoraria, Research Funding; Macrogenics: Research Funding; BMS: Consultancy, Honoraria, Research Funding. Carraway:Novartis: Consultancy, Speakers Bureau; Takeda: Other: Independent Advisory Committe (IRC); Stemline: Consultancy, Speakers Bureau; BMS: Consultancy, Other: Research support, Speakers Bureau; Abbvie: Other: Independent Advisory Committe (IRC); ASTEX: Other: Independent Advisory Committe (IRC); Jazz: Consultancy, Speakers Bureau. Saunthararajah:EpiDestiny: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Kantarjian:Sanofi: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Honoraria, Research Funding; BMS: Research Funding; Abbvie: Honoraria, Research Funding; Aptitute Health: Honoraria; Pfizer: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Jazz: Research Funding; Immunogen: Research Funding; Adaptive biotechnologies: Honoraria; Ascentage: Research Funding; Amgen: Honoraria, Research Funding; BioAscend: Honoraria; Delta Fly: Honoraria; Janssen: Honoraria; Oxford Biomedical: Honoraria. Kadia:Pfizer: Honoraria, Research Funding; Novartis: Honoraria; Cyclacel: Research Funding; Ascentage: Research Funding; Astellas: Research Funding; Cellenkos: Research Funding; JAZZ: Honoraria, Research Funding; Astra Zeneca: Research Funding; Celgene: Research Funding; Incyte: Research Funding; Pulmotec: Research Funding; Abbvie: Honoraria, Research Funding; Genentech: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Amgen: Research Funding. Sekeres:Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda/Millenium: Consultancy, Membership on an entity's Board of Directors or advisory committees. Maciejewski:Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria.

scholarly journals Distinct Genomic Landscape of Colorectal Mucinous Carcinoma Determined via Comprehensive Genomic Profiling: Steps to a New Treatment Strategy

2021 ◽  
Vol 11 ◽  
Author(s):  
Liang Huang ◽  
Shuanglin Luo ◽  
Xingwei Zhang ◽  
Yonghua Cai ◽  
Fangqin Xue ◽  
...  
Keyword(s):  
Treatment Strategies ◽  
Mucinous Carcinoma ◽  
Molecular Signature ◽  
Response To Treatment ◽  
Mutation Rates ◽  
Genomic Features ◽  
Genomic Landscape ◽  
Comprehensive Genomic Profiling ◽  
New Treatment ◽  
Generation Sequencing

Colorectal mucinous carcinoma (MC) is associated with inferior prognosis and response to treatment compared to adenocarcinoma (AC). The molecular landscapes of MC and adenocarcinoma with mucous composition (AMC) are not well-defined. We aimed to describe the genomic landscape of MC and AMC in a large colorectal cancer cohort. Tumor samples from patients with MC, AMC, or AC were analyzed using next-generation sequencing. MC had a molecular signature distinct from that of AC; genomic features were similar between AMC and MC but not between AMC and AC. HER2 amplification and TP53 and APC mutation rates were lower, whereas SMAD4, PIK3CA, ACVR2A, KMT2D, LRP1, TGFBR2, GRIN2A, BRAF V600E, PTEN, and BRCA2 mutation rates were higher in MC than in AC. The mutation frequencies in MAPK, PI3K, and TGF-β pathways were higher, whereas those of cell cycle proteins and Wnt were lower in MC and AMC than in AC. The proportion of hypermutated tumors was significantly higher in MC and AMC than in AC. As MC has a distinct molecular signature from AC, immunotherapy can be potentially applied in treating MC. Similar molecular profiles of AMC and MC suggest that treatment strategies for MC, but not AC, can be used for AMC treatment.

scholarly journals In vivo and in vitro oncogenic effects of HIF2A mutations in pheochromocytomas and paragangliomas

2013 ◽  
Vol 20 (3) ◽  
pp. 349-359 ◽  
Author(s):  
Rodrigo A Toledo ◽  
Yuejuan Qin ◽  
Subramanya Srikantan ◽  
Nicole Paes Morales ◽  
Qun Li ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Target Genes ◽  
Germline Mutations ◽  
Vascular Tumors ◽  
Wild Type ◽  
Pheochromocytoma Pc12 ◽  
Hereditary Tumors ◽  
Tumor Dna

Pheochromocytomas and paragangliomas are highly vascular tumors of the autonomic nervous system. Germline mutations, including those in hypoxia-related genes, occur in one third of the cases, but somatic mutations are infrequent in these tumors. Using exome sequencing of six paired constitutive and tumor DNA from sporadic pheochromocytomas and paragangliomas, we identified a somatic mutation in the HIF2A (EPAS1) gene. Screening of an additional 239 pheochromocytomas/paragangliomas uncovered three other HIF2A variants in sporadic (4/167, 2.3%) but not in hereditary tumors or controls. Three of the mutations involved proline 531, one of the two residues that controls HIF2α stability by hydroxylation. The fourth mutation, on Ser71, was adjacent to the DNA binding domain. No mutations were detected in the homologous regions of the HIF1A gene in 132 tumors. Mutant HIF2A tumors had increased expression of HIF2α target genes, suggesting an activating effect of the mutations. Ectopically expressed HIF2α mutants in HEK293, renal cell carcinoma 786-0, or rat pheochromocytoma PC12 cell lines showed increased stability, resistance to VHL-mediated degradation, target induction, and reduced chromaffin cell differentiation. Furthermore, mice injected with cells expressing mutant HIF2A developed tumors, and those with Pro531Thr and Pro531Ser mutations had shorter latency than tumors from mice with wild-type HIF2A. Our results support a direct oncogenic role for HIF2A in human neoplasia and strengthen the link between hypoxic pathways and pheochromocytomas and paragangliomas.

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