scholarly journals Whole Exome Sequencing and Targeted Sequencing Reveal the Heterogeneity of Genomic Evolution and Mutational Profile in Smoldering Multiple Myeloma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 237-237
Author(s):  
Karma Salem ◽  
Jihye Park ◽  
Claudia Freymond ◽  
Marzia Capelletti ◽  
Daisy Huynh ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Research Funding ◽  
Plasma Cells ◽  
Targeted Sequencing ◽  
Target Coverage ◽  
Driver Genes ◽  
Whole Exome ◽  
Agilent Sureselect

Abstract Introduction: Recent data shows that multiple myeloma (MM) almost always arises from precursor states called Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM), but not all patients with MGUS or SMM develop MM. Risk factors of progression for SMM patients are largely based on tumor load as represented by an M-protein ≥ 3 g/dL, a free light chain (FLC) ratio outside the range of 0.125 to 8, and ≥ 10% plasma cells in the BM. However, the genetic lesions that underlie progression, the molecular factors that cause rapid versus slow progression, and the factors that distinguish the relatively indolent MGUS from SMM are not well known. Further, the genomic landscape of SMM is not well characterized. One potential factor is MYC overexpression. Bergsagel et al. have found that MYC levels increase when comparing MGUS, SMM and overt MM. Other frequently altered pathways in MM are NF-kB, MAPK and DNA damage. In addition, limited studies of paired SMM and MM samples show that in many cases, the aggressive subclones can already be detected, in small cell fractions, before overt MM develops. However, the cause of progression to MM is unclear, in large part because sequential genomic studies of MGUS/SMM progression have yet to be undertaken. To address these questions, in this study we examine clinically-annotated samples from patients with SMM. Methods: We performed whole exome sequencing (WES) (mean target coverage 50X/100X) on 49 germline-tumor matched samples from patients with SMM (DNA from bone marrow CD138+ plasma cells matched with germline DNA from peripheral blood mononuclear cells). Libraries were constructed using Agilent SureSelect XT2 library prep kit, and hybridized to Agilent's whole exome V5+UTR capture probes and then sequenced on HiSeq 2500 (Illumina). We also performed targeted deep sequencing using a custom enrichment bait set on 25 samples of progressor (n=12) and non-progressor (n=13) SMM samples. Libraries were also constructed with Agilent SureSelect XT2 library prep kit and enriched by hybridizing to an in-house designed customized target bait, then sequenced on HiSeq 2500. Sequencing data were analyzed using previously established analytic pipelines including MuTect, RecapSeg, GISTIC, MutSig, and ABSOLUTE. Results: The number of Somatic Single Nucleotide Variants (SSNVs) seen in SMM ranged from 1 to 98 nonsilent mutations with an average of 1.14 mutations/Mb, which is slightly lower than MM (1.6 mutations/Mb) from previous studies (p-value=0.05). This large and varying range of mutational load among samples suggests that SMM is likely a heterogenous entity where some patients are closer to MGUS and others closer to MM. We identified likely drivers in SMM in about ~32% of the samples, including mutations in MM candidate driver genes such as NRAS, KRAS and PTPN11(overall 36 events were present in COSMIC). SMM also had somatic CNAs in about ~50% of SMM samples, such as hyperdiploidy, gain of chromosome 1q, deletion of 13p and 17p, which match the hallmark chromosome changes seen in MM. Comparing deep targeted sequencing of 100 genes (mean target coverage 361X) in samples from 12 SMM patients who progressed to myeloma vs. 13 SMM patients who did not, we found non-synonymous mutations exclusive to progressors, suggesting that with more samples we may find genetic alterations that predict progression in SMM. Conclusion: This study demonstrates that WES and targeted sequencing of SMM patients can detect MM candidate driver genes as well as hallmark CNAs seen in MM patients. Further, there may be potential different mutational features between progressors and non-progressors. Thus, this approach can be used to identify genetic drivers of clonal progression from MGUS/SMM to MM that may present opportunities for early therapeutic intervention and prevention of disease progression. Disclosures Roccaro: Takeda Pharmaceutical Company Limited: Honoraria. Ghobrial:Takeda: Honoraria; Noxxon: Honoraria; Amgen: Honoraria; Novartis: Honoraria; BMS: Honoraria, Research Funding; Celgene: Honoraria, Research Funding.

Whole-Exome Sequencing Identifies a Somatic Cell Mutation Signature That Predicts Relapse Risk and Survival Probability in Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 5-5
Author(s):  
Ehsan Malek ◽  
E. Ricky Chan ◽  
Daniel Qu ◽  
Jane Reese ◽  
Robert Fox ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Signaling Pathways ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Research Funding ◽  
Advisory Board ◽  
High Burden ◽  
Signature Genes ◽  
Whole Exome ◽  
Relapse Group

Introduction: Multiple myeloma (MM) is a plasma cell neoplasm associated with heterogeneous somatic alterations. Despite the development of novel anti-myeloma agents that have significantly prolonged patient survival, disease relapse remains a daunting problem. Our goal was to employ whole-exome sequencing (WES) to better describe the mutational landscape in MM beyond the tumor cell and identify genomic factors that might predict relapse. WES was performed using autograft samples obtained from MM patients that were then treated with high dose melphalan and autologous hematopoietic cell transplant (HCT). We identified a panel of genes that were most frequently mutated in all patients and then identified those genes mutated with greater frequency in patients that relapsed. A relapse burden signature was generated based upon the genes that were most frequently mutated genes in relapsed patients. Finally, the relapse burden signature was correlated with patient progression-free survival (PFS) and overall survival (OS) following autologous HCT. Methods. DNA was extracted from one ml of cryopreserved, mobilized hematopoietic cell product obtained from patients (N=93) that underwent HCT and was provided by the Case Comprehensive Cancer Center Hematopoietic Biorepository Core. Targeted sequencing was performed using the Tempus xE whole exome platform (Tempus, Chicago, IL). Variants were identified using a variant allele frequency (VAF) ≥0.1 for each sample. Variants were tabulated for each gene in each patient. Patients were grouped according to their relapse status; "No Relapse" (N=39) and "Relapse" (N=54) which corresponded to their post-HCT outcome. Relapse time was defined as time from transplant to event. Variants identified in each gene and patient group were counted and ranked. A relapse burden signature was defined and included twenty-two genes over-represented in the relapse group compared to the non-relapse group by > 10%. Genes in the relapse burden signature were subjected to gene set enrichment analysis (GSEA) and cross referenced against Gene Ontology (GO) categories. PFS and OS were defined as the time from transplant until the event of interest, with censoring at time of last follow up. Patients were regrouped according to their mutation burden in the relapse signature genes ("High burden" defined as >=six signature genes with variants) and their OS and PFS were analyzed with an R package (survival) to generate Kaplan-Meier curves and statistical significance based on a Chi-square test between low and high burden patients. Results: In total, 3,523 genes were identified as containing variants. Table 1 lists the top thirty genes that were identified and ranked based upon total number of mutations (mutational count) and most frequently mutated in relapsed and non-relapsed patients (sample count). We then identified those genes that were more frequently mutated by at least 10% in relapsed patients compared to non-relapsed patients (Fig. 1A). GSEA revealed that the relapse burden gene signature was associated with protein O-linked glycosylation, glycan processing, Golgi lumen and innate immune response activating cell surface receptor signaling pathways (Table 2). Interestingly, multiple mucin family members (Muc2, Muc3A, Muc12 and Muc19) were represented in the relapse burden signature. GO analysis indicated that the individual mucin genes were associated with the same signaling pathways that had been associated with the relapse burden signature by GSEA (Table 3). Importantly, a high relapse burden signature was correlated with a statistically significant reduction in both PFS and OS (Fig. 1B, C). Conclusion: Taken together, our results support the feasibility of WES to generate a relapse burden signature that predicts the risk of MM patients for relapse following HCT. Moreover, the mutational landscape associated with relapse, i.e. the specific genes mutated, has provided insights on the mechanisms of relapse. It is noteworthy that the relapse burden signature genes identified here were mutated at a much greater frequency than genes associated with clonal hematopoiesis of indeterminate potential (CHIP). The identification of patient subgroups at heightened risk of relapse can better guide treatment decisions. Future studies will be conducted to evaluate the effect of pathways identified here on myeloma cell survival and to validate actionable therapeutic targets. Disclosures Malek: Bluespark: Research Funding; Takeda: Other: Advisory board , Speakers Bureau; Medpacto: Research Funding; Janssen: Other: Advisory board, Speakers Bureau; Sanofi: Other: Advisory board; Clegene: Other: Advisory board , Speakers Bureau; Amgen: Honoraria; Cumberland: Research Funding. Caimi:Amgen: Other: Advisory Board; Bayer: Other: Advisory Board; Verastem: Other: Advisory Board; Kite pharmaceuticals: Other: Advisory Board; Celgene: Speakers Bureau; ADC therapeutics: Other: Advisory Board, Research Funding. de Lima:Celgene: Research Funding; BMS: Other: Personal Fees, advisory board; Incyte: Other: Personal Fees, advisory board; Kadmon: Other: Personal Fees, Advisory board; Pfizer: Other: Personal fees, advisory board, Research Funding.

Driver Mutation in Waldenstrom's Macroglobullinemia and Their Clonal Heterogeneity during Progression and Relapse

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1092-1092 ◽  
Author(s):  
Jihye Park ◽  
Antonio Sacco ◽  
Salomon Manier ◽  
Karma Salem ◽  
Mira Mashood ◽  
...  
Keyword(s):  
New York ◽  
Disease Progression ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Research Funding ◽  
Targeted Sequencing ◽  
Whole Exome ◽  
Btk Inhibitor ◽  
Serial Samples

Abstract Background: Whole genome sequencing has recently shown the presence of recurrent mutations, such as MYD88, CXCR4 and ARID1A, in patients with Waldenstrom's Macroglobulinemia (WM) at diagnosis. Nevertheless, the contribution of each genomic aberration within the clonal evolution of the tumor during WM progression has not been reported. We therefore aimed to investigate whether sequential genomic events sustain WM disease progression by using whole exome sequencing (WES) and targeted sequencing of serial samples. In addition, we investigated if specific genomic alterations can change in response to treatment with samples before and after proteasome or BTK inhibitor treatments. Methods: We have sequenced 74 samples from 32 patients using WES or targeted sequencing technology. DNA was collected from bone marrow CD19-selected cells that were isolated from 6 patients with WM at different stages of disease (2-3 serial samples per patient, total 15 samples), and was subjected to library construction, followed by Agilent Sure-Select Human All Exon v2.0-based hybrid selection. Germline DNA was isolated from matched CD19-depleted peripheral blood samples. All libraries were sequenced with Illumina Hiseq 2500 instrument (New York Genome Center, Rockefeller University, New York, NY). Reads were aligned to GRCh37, and quality control, mutation calling, insertion and deletion identification, copy number variation detection, coverage calculations were accomplished via Firehose at Broad. Somatic Single Nucleotide Variations (SSNVs) were identified and annotated using MuTect and Oncotator, respectively. Insertions and deletions were detected using Strelka. In addition, the deep targeted sequencing was done with a customized bait set in 59 independent serial samples obtained from 26 patients who were treated with either proteasome inhibitor (Pi)- or BTK inhibitor (BTKi)-based therapies in 12 and 14 cases, respectively. Results: Whole exome sequencing, performed at a total average depth of 83X for germline and 85X for tumor samples, led to the identification of average of 14 non-silent mutations per sample (range 2-60). Base conversion signature showed dominant A>C/G transitions. Copy number analysis showed 6q deletion being the most prevalent one. MYD88 was the most recurrent somatic variants in WM patients (>93%), followed by several genes including IRS4, VCAN, CXCR4 and ALDH2, being detected in ~20-30% of the samples. Specifically, changes in the Cancer Cell Fraction (CCF) of these mutations, such as MYD88 and CXCR4, occurred in the serial samples depending on progression and response to therapy. The mutated genes mentioned above, including MYD88, CXCR4, LRG1 and VCAN, were also observed in targeted sequencing of 59 independent serial samples (mean target coverage 434X). CXCR4 was linked to disease progression exposed to Pi or BTK; but not detected in patients responding to therapies. MYD88 was present in patients with either progressive disease or PR/VGPRs. Specifically, different frequencies of MYD88 mutations were identified in patients with progression or PR/VGPR to BTKi-based therapies compared to Pi-based therapies. LRG1 was detected in a patient in response to Pi, while VCAN was observed in both patients showing progression or response to Pi regimens only. Conclusion: These findings reveal the occurrence of clonal variations in patients with WM during disease progression and response to therapies. MYD88 was confirmed to be the most prevalent somatic aberration, and was present in post-treatment samples of progressors and responders to Pi- or BTKi-based regimens. In contrast, mutations in CXCR4 were enriched in patients with WM progressing to either Pi or BTKi therapies. This study demonstrates that WES and targeted sequencing of serial samples of WM patients can detect clonal variations during disease progression. Disclosures Ghobrial: Celgene: Honoraria, Research Funding; Noxxon: Honoraria; Amgen: Honoraria; BMS: Honoraria, Research Funding; Novartis: Honoraria; Takeda: Honoraria. Roccaro:Takeda Pharmaceutical Company Limited: Honoraria.

Single Cell Whole Exome Sequencing in an Index Case of Amp1q21 Multiple Myeloma to Define Intraclonal Variation

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5651-5651
Author(s):  
Dean Bryant ◽  
Will Tapper ◽  
Nicola J Weston-Bell ◽  
Arnold Bolomsky ◽  
Li Song ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
T Cells ◽  
Single Cell ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Plasma Cell ◽  
Index Case ◽  
High Confidence ◽  
Whole Exome ◽  
Agilent Sureselect

Abstract Introduction Multiple myeloma (MM) is a largely incurable plasma cell malignancy characterised by marked genomic heterogeneity, in which chromosome 1q21 amplification (amp1q21) associates with poor prognosis. Genomic analysis using next generation sequencing has identified recurrent mutations, but no universal acquired somatic mutation(s) have emerged in MM, suggesting that understanding pathways of survival will require analysis of individual tumours in distinct disease subsets. To compound complexity of the problem, intraclonal variation (ICV), known as a major driver mechanism in cancer plasticity, in which clonal competitor cells undergo selection during disease evolution and progression by Darwinian principles, will need to be fully mapped at the genome level. Identifying the true level of ICV in a tumour will thus require analysis at the level of whole exome sequencing (WES) in single cells (SCs). In this study, we sought to establish WES methodology able to identify ICV in SCs in an index case of amp1q21 MM. Methods Cell selection and sequencing CD138+ tumour cells and CD3+ T-cells were isolated from a presentation case of amp1q21 MM as bulk populations to high purity (>97%). Single MM cells and normal T cells were individually isolated and used for single cell (SC) whole exome sequencing (WES). Whole genome amplification (WGA) was performed by multiple displacement amplification (Qiagen REPLI-g Mini kit), and exome capture was performed using Agilent SureSelect. Libraries were then 90 bp paired end sequenced on an Illumina HiSeq2000 (BGI, China). Data analysis Data was produced for bulk (1000 cells) MM and bulk germline T cells, twenty MM SCs and five T cell SCs. Raw data was aligned to hg19 reference sequence using NovoAlignMPI (v3.02.03). Variant calling was performed using SAMtools (v1.2.1) and VarScan (v2.3.6) and variants were annotated using ANNOVAR. High confidence variants were called in the bulk tumour WES by pairwise comparison with bulk germline WES. Variant lists were also cross-searched against various variant databases (CG46, 1000 genomes, dbSNP, esp650 and in-house database) in order to exclude variants that occur in the general population. Multiple quality control measures were employed to reduce the number of false positive calls. Results and Discussion Data and bioinformatics pipelines are of a high quality SC WES generated raw data reads that were similar to bulk WES of 1000 cells, with comparable mapping to Agilent SureSelect target exome (69-76% SC vs. 70% bulk) and mean fold coverage (56.8-59.1x vs. 59.7x bulk). On average, 82% of the exome was covered sufficiently for somatic variant (SV) calling (often considered as ≥ 5x), which was higher than seminal published SC WES studies (70-80%) (Hou et al., Cell, 2012; Xu et al., Cell, 2012). We identified 33 potentially deleterious SVs in the bulk tumour exome with high confidence bioinformatics, 21 of which were also identified in one or more SC exomes. The variants identified include suspected deleterious mutations in genes involved in MAPK pathway, plasma cell differentiation, and those with known roles in B cell malignancies. To confirm SV calls, randomly selected variants were validated by conventional Sanger sequencing, and of 15/15 variants in the bulk WES and of 55/55 variants in SCs, to obtain 100% concordance. Intraclonal variation in MM Significantly, ICV was apparent from the SC exome variant data. Total variant counts varied considerably among SCs and most variant positions had at least several cells where no evidence of the variant existed. Bulk WES lacks crucial information We identified an additional 23 variants that were present in 2+ SC exomes, but absent in the bulk MM tumour exomes. Of these, 30% (7 variants) were examined for validation, and were amplifiable in at least one cell to deliver 100% concordance with variant calls. These variants are of significant interest as they reveal a marked occurrence of subclonal mutations in the MM tumour population that are not identified by bulk exome sequencing. They indicate that the mutational status of the MM genome may be substantially underestimated by analysis at the bulk tumour population level. Conclusion In this work we establish the feasibility of SC WES as a method for defining intraclonal genetic variation in MM. Disclosures No relevant conflicts of interest to declare.

Whole Exome Sequencing from Nine Independent Sites of Extraosseous Disease in a Single Patient with Relapsed Multiple Myeloma Show That Extramedullary Disease Arise through a Combination of Branched and Parallel Evolution

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 2090-2090
Author(s):  
Heather Landau ◽  
Jun Fan ◽  
Sergio A. Giralt ◽  
Jonathan U. Peled ◽  
Hani Hassoun ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Exome Sequencing ◽  
Board Of Directors ◽  
Whole Exome Sequencing ◽  
Research Funding ◽  
Parallel Evolution ◽  
High Quality ◽  
Advisory Committees ◽  
Extramedullary Disease ◽  
Whole Exome

Abstract Introduction: Multiple myeloma (MM) is the second most common hematologic malignancy. Recent sequencing studies show evidence of massive genetic heterogeneity reflected in multiple parallel subclones already at diagnosis. Different subclones respond differently to given therapy. The role of treatment-driven subclonal skewing and intrinsic acquired mutations is poorly understood in the relapse setting. At relapse, the distribution of subclones throughout the bone marrow and at extramedullary sites is currently unknown. Methods: We performed a research autopsy on a single individual with IgG kappa MM who survived with multiple metastatic sites of disease for 10 years after diagnosis. Genomic DNA was extracted from histologically confirmed snap frozen normal tissue and nine independent sites of extraosseous disease. Whole exome sequencing (150X) was performed by the MSK Genomics Core. Data were filtered to remove germline polymorphisms and enrich for high quality somatic variants. Phylogenetics and subclonal analyses were performed using Treeomics and SCHISM. Results: The average on target coverage was 177X with 73% of bases covered a minimum of 100x. A total of 6348 somatic variants were initially identified. After filtering for high quality somatic variants, 1330 remained with 220 of these variants common to all MM samples and an average of 628 variants per sample. Annotation of high quality variants revealed potentially deleterious somatic mutations in NRAS, FAM46C, DYNC1, CREBBP, ATM, BIRC3, MGA, PPP6C and SMARCA4. Phylogenetics analyses (shown below) indicated the metastases arose through a combination of branched and parallel evolution, with the ATM mutation arising in one branch (one metastasis) that was distinct from a second clonal population containing the NRAS, FAM46C, BIRC3, CREBBP, DYNC1 and PPP6C mutations that were present in all eight other metastases. The MGA and SMARCA4 mutations further identified two additional subclones arising in from the NRAS/FAM46C mutant common ancestral clone. Clonality analyses independently supported this hierarchy by identifying NRAS and FAM46C as early clonal events and MGA and SMARCA4 as late events in the progression of this patient's disease. It also suggested a degree of subclonal mixing within each metastatic site. Conclusions: Using whole exome sequencing from nine independent sites of extraosseous disease in a single MM patient with relapse 10 years after initial diagnosis, we show that extramedullary disease arise through a combination of branched and parallel evolution. Two additional patients have also undergone research autopsy and results will be presented at the meeting. Figure Figure. Disclosures Landau: Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx/Amgen: Research Funding; Spectrum Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy. Hassoun:Binding Site: Research Funding; Novartis: Consultancy; Celgene: Research Funding; Takeda: Consultancy, Research Funding. Korde:Medscape: Honoraria. Landgren:Medscape Myeloma Program: Honoraria; Takeda: Honoraria; Amgen: Honoraria, Research Funding; BMS: Honoraria; Merck: Honoraria; Celgene: Honoraria, Research Funding.

Whole Exome Sequencing of Aberrant Plasma Cells in a Patient with Multiple Myeloma Minimal Residual Disease

2017 ◽  
Vol 30 (Suppl 2) ◽  
pp. 2S75-2S80
Author(s):  
Martina Zátopková ◽  
Jana Filipová ◽  
Tomáš Jelínek ◽  
Petr Vojta ◽  
Tereza Ševčíková ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Exome Sequencing ◽  
Minimal Residual Disease ◽  
Whole Exome Sequencing ◽  
Plasma Cells ◽  
Residual Disease ◽  
Whole Exome ◽  
Minimal Residual

P-047: Clonal evolution in multiple myeloma evaluated by Whole Exome Sequencing

2021 ◽  
Vol 21 ◽  
pp. S64
Author(s):  
Ritu Gupta ◽  
Gurvinder Kaur ◽  
Akanksha Farswan ◽  
Lingaraja Jena ◽  
Anubha Gupta ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Clonal Evolution ◽  
Whole Exome

scholarly journals Defining Clonal Plasticity Using Whole Exome Sequencing in Single Cells in an Index Case of amp1q21 Multiple Myeloma

2017 ◽  
Vol 17 (1) ◽  
pp. e108
Author(s):  
Surinder Sahota ◽  
Dean Bryant ◽  
Nicola Weston-Bell ◽  
Will Tapper ◽  
Arnold Bolomsky ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Index Case ◽  
Single Cells ◽  
Whole Exome

scholarly journals Whole-exome sequencing of cell-free DNA and circulating tumor cells in multiple myeloma

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
S. Manier ◽  
J. Park ◽  
M. Capelletti ◽  
M. Bustoros ◽  
S. S. Freeman ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Exome Sequencing ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Whole Exome Sequencing ◽  
Cell Free Dna ◽  
Free Dna ◽  
Whole Exome

scholarly journals The Profile of Genetic Mutations in Papillary Thyroid Cancer Detected by Whole Exome Sequencing

2018 ◽  
Vol 50 (1) ◽  
pp. 169-178 ◽  
Author(s):  
Yi Fang ◽  
Xiao Ma ◽  
Jing Zeng ◽  
Yanwen Jin ◽  
Yong Hu ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Exome Sequencing ◽  
Papillary Thyroid Cancer ◽  
Whole Exome Sequencing ◽  
Sanger Sequencing ◽  
Signal Pathways ◽  
Papillary Thyroid ◽  
Driver Genes ◽  
Mutational Status ◽  
Whole Exome

Background/Aims: The purpose of the study was to investigate the altered driver genes and signal pathways during progression of papillary thyroid cancer (PTC) via next-generation sequencing technology. Methods: The DNA samples for whole exome sequencing (WES) analyses were extracted from 11 PTC tissues and adjacent normal tissues samples. Direct Sanger sequencing was applied to validate the identified mutations. Results: Among the 11 pairs of tissues specimens, 299 single nucleotide variants (SNVs) in 75 genes were identified. The most common pattern of base pair substitutions was T:A>C:G (49.83%), followed by C:G>T:A (18.06%) and C:G>G:C (15.05%). The altered genes were mainly implicated in MAPK (mitogen-activated protein kinase), PPAR (peroxisome proliferator-activated receptors), and p53 signaling pathways. In addition, 12 novel identified driver genes were validated by Sanger sequencing. The mutations of FAM133A, DPCR1, JAK1, C10orf10, EPB41L3, GPRASP1 and IWS1 exhibited in multiple PTC cases. Furthermore, the PTC cases exhibited individual mutational signature, even the same gene might present different mutational status in different cases. Conclusion: Multiple PTC-related somatic mutations and signal pathways are identified via WES and Sanger sequencing methods. The novel identified mutations in genes such as FAM133A, DPCR1, and JAK1 may be potential therapeutic targets for PTC patients.

scholarly journals USP8 and TP53 Drivers are Associated with CNV in a Corticotroph Adenoma Cohort Enriched for Aggressive Tumors

2020 ◽  
Author(s):  
Andrew V Uzilov ◽  
Patricia Taik ◽  
Khadeen C Cheesman ◽  
Pedram Javanmard ◽  
Kai Ying ◽  
...  
Keyword(s):  
At Risk ◽  
Aggressive Behavior ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutations ◽  
Care Center ◽  
Tertiary Care ◽  
Driver Genes ◽  
Cushing Disease ◽  
Whole Exome

Abstract Context Pituitary corticotroph adenomas are rare tumors that can be associated with excess adrenocorticotropin (ACTH) and adrenal cortisol production, resulting in the clinically debilitating endocrine condition Cushing disease. A subset of corticotroph tumors behave aggressively, and genomic drivers behind the development of these tumors are largely unknown. Objective To investigate genomic drivers of corticotroph tumors at risk for aggressive behavior. Design Whole-exome sequencing of patient-matched corticotroph tumor and normal deoxyribonucleic acid (DNA) from a patient cohort enriched for tumors at risk for aggressive behavior. Setting Tertiary care center Patients Twenty-seven corticotroph tumors from 22 patients were analyzed. Twelve tumors were macroadenomas, of which 6 were silent ACTH tumors, 2 were Crooke’s cell tumors, and 1 was a corticotroph carcinoma. Intervention Whole-exome sequencing. Main outcome measure Somatic mutation genomic biomarkers. Results We found recurrent somatic mutations in USP8 and TP53 genes, both with higher allelic fractions than other somatic mutations. These mutations were mutually exclusive, with TP53 mutations occurring only in USP8 wildtype (WT) tumors, indicating they may be independent driver genes. USP8-WT tumors were characterized by extensive somatic copy number variation compared with USP8-mutated tumors. Independent of molecular driver status, we found an association between invasiveness, macroadenomas, and aneuploidy. Conclusions Our data suggest that corticotroph tumors may be categorized into a USP8-mutated, genome-stable subtype versus a USP8-WT, genome-disrupted subtype, the latter of which has a TP53-mutated subtype with high level of chromosome instability. These findings could help identify high risk corticotroph tumors, namely those with widespread CNV, that may need closer monitoring and more aggressive treatment.

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