scholarly journals Clonal haematopoiesis in chronic ischaemic heart failure: prognostic role of clone size for DNMT3A- and TET2-driver gene mutations

2020 ◽  
Author(s):  
Birgit Assmus ◽  
Sebastian Cremer ◽  
Klara Kirschbaum ◽  
David Culmann ◽  
Katharina Kiefer ◽  
...  
Keyword(s):  
Heart Failure ◽  
Somatic Mutations ◽  
Prognostic Significance ◽  
Gene Mutations ◽  
Amplicon Sequencing ◽  
Driver Mutations ◽  
Driver Gene ◽  
Roc Curve Analysis ◽  
Driver Genes ◽  
Clone Size

Abstract Aims Somatic mutations of the epigenetic regulators DNMT3A and TET2 causing clonal expansion of haematopoietic cells (clonal haematopoiesis; CH) were shown to be associated with poor prognosis in chronic ischaemic heart failure (CHF). The aim of our analysis was to define a threshold of variant allele frequency (VAF) for the prognostic significance of CH in CHF. Methods and results We analysed bone marrow and peripheral blood-derived cells from 419 patients with CHF by error-corrected amplicon sequencing. Cut-off VAFs were optimized by maximizing sensitivity plus specificity from a time-dependent receiver operating characteristic (ROC) curve analysis from censored data. 56.2% of patients were carriers of a DNMT3A- (N = 173) or a TET2- (N = 113) mutation with a VAF >0.5%, with 59 patients harbouring mutations in both genes. Survival ROC analyses revealed an optimized cut-off value of 0.73% for TET2- and 1.15% for DNMT3A-CH-driver mutations. Five-year-mortality was 18% in patients without any detected DNMT3A- or TET2 mutation (VAF < 0.5%), 29% with only one DNMT3A- or TET2-CH-driver mutations above the respective cut-off level and 42% in patients harbouring both DNMT3A- and TET2-CH-driver mutations above the respective cut-off levels. In carriers of a DNMT3A mutation with VAF ≥ 1.15%, 5-year mortality was 31%, compared with 18% mortality in those with VAF < 1.15% (P = 0.048). Likewise, in patients with TET2 mutations, 5-year mortality was 32% with VAF ≥ 0.73%, compared with 19% mortality with VAF < 0.73% (P = 0.029). Conclusion The present study defines novel threshold levels for clone size caused by acquired somatic mutations in the CH-driver genes DNMT3A and TET2 that are associated with worse outcome in patients with CHF.

scholarly journals Novel Putative Driver Gene Mutations in Chronic Lymphocytic Leukemia (CLL): Results from a Combined Analysis of Whole-Exome Sequencing of 262 Primary CLL Samples

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1952-1952 ◽  
Author(s):  
Dan A. Landau ◽  
Chip Stewart ◽  
Johannes G. Reiter ◽  
Michael Lawrence ◽  
Carrie Sougnez ◽  
...  
Keyword(s):  
Chronic Lymphocytic Leukemia ◽  
Exome Sequencing ◽  
Gene Mutations ◽  
Clinical Impact ◽  
Lymphocytic Leukemia ◽  
Driver Mutations ◽  
Driver Gene ◽  
Discovery Process ◽  
Driver Genes ◽  
Whole Exome

Abstract Unbiased high-throughput massively parallel sequencing methods have transformed the process of discovery of novel putative driver gene mutations in cancer. In chronic lymphocytic leukemia (CLL), these methods have yielded several unexpected findings, including the driver genes SF3B1, NOTCH1 and POT1. Recent analysis, utilizing down-sampling of existing datasets, has shown that the discovery process of putative drivers is far from complete across cancer. In CLL, while driver gene mutations affecting >10% of patients were efficiently discovered with previously published CLL cohorts of up to 160 samples subjected to whole exome sequencing (WES), this sample size has only 0.78 power to detect drivers affecting 5% of patients, and only 0.12 power for drivers affecting 2% of patients. These calculations emphasize the need to apply unbiased WES to larger patient cohorts. To this end, we performed a combined analysis of CLL WES data joining together our previously published cohort of 159 CLLs with data from 103 CLLs collected by the International Cancer Genome Consortium (ICGC). The raw sequencing reads from these 262 primary tumor samples (102 CLL with unmutated IGHV, 147 with mutated IGHV, 13 with unknown IGHV status) were processed together and aligned to the hg19 reference genome. Somatic single nucleotide variations (sSNVs) and indels were detected using MuTect. Subsequently, inference of recurrently mutated genes was performed using the MutSig algorithm. This method combined several characteristics such as the overall mutation rate per sample, the gene specific background mutation rate, non-synonymous/synonymous ratio and mutation clustering to detect genes that are affected by mutations more than expected by chance. This analysis identified 40 recurrently mutated genes in this cohort. This included 22 of 25 previously identified recurrently mutated genes in CLL. In addition, 18 novel candidate CLL drivers were identified, mostly affecting 1-2% of patients. The novel candidates included two histone proteins HIST1H1D and HIST1H1C, in addition to the previously identified HIST1H1E. Another was IKZF3, affected by a recurrent sSNV resulting in a p.L162R change in its DNA binding domain, in close proximity to a region recently identified as critical for lenalidomide resistance in multiple myeloma (MM). An additional recurrently mutated gene was nuclear RNA export factor 1 (NXF1), which along with previously known recurrently mutated genes (SF3B1, XPO1, DDX3X), highlights the importance of RNA processing to CLL biology. Finally, this search for putative CLL driver genes also identified ASXL1 and TRAF3, already characterized as drivers in acute myeloid leukemia and MM, respectively. Of the 59 of 262 samples for which RNA-seq data were available, 76% of the identified driver mutations were detected and thereby validated. Validation using RNAseq detection of driver mutations and targeted sequencing within the entire cohort are ongoing. The larger size of our cohort enabled the separate application of the somatic mutation discovery process to samples with mutated or unmutated IGHV. Among the 147 samples with mutated IGHV, only 5 driver genes (TP53, SF3B1, MYD88, CHD2, RANBP2) retained significance. In contrast, analysis of the 102 IGHV unmutated samples revealed a distinct and more diverse pattern of recurrently mutated genes (lacking MYD88 and CHD2, and including NOTCH1, RPS15, POT1, NRAS, EGR2, BRAF, MED12, XPO1, BCOR, IKZF3, MAP2K1, FBXW7 and KRAS). This extended cohort also allowed for better resolution of the clinical impact of those genetic variants with greater than 4% prevalence in the cohort. For example, samples with POT1 mutations were found to be associated with shorter time from sample to therapy compared with those with wild-type POT1 (P= 0.02). Our study demonstrates that with larger cohort size, we can effectively detect putative driver genes with lower prevalence, but which may nonetheless have important biological and clinical impact. Moreover, our interrogation shows that subset analysis can reveal distinct driver patterns in different disease subsets. In particular, the marked clinical difference between CLLs with mutated and unmutated IGHV may reflect the higher likelihood of the latter group to harbor a broader spectrum of driver mutations with a more complex pattern of co-occurrence. Disclosures Brown: Sanofi, Onyx, Vertex, Novartis, Boehringer, GSK, Roche/Genentech, Emergent, Morphosys, Celgene, Janssen, Pharmacyclics, Gilead: Consultancy.

scholarly journals Evaluating the evaluation of cancer driver genes

2016 ◽  
Vol 113 (50) ◽  
pp. 14330-14335 ◽  
Author(s):  
Collin J. Tokheim ◽  
Nickolas Papadopoulos ◽  
Kenneth W. Kinzler ◽  
Bert Vogelstein ◽  
Rachel Karchin
Keyword(s):  
Somatic Mutations ◽  
Gene Prediction ◽  
Gene Mutations ◽  
Evaluation Framework ◽  
Mutation Rates ◽  
Driver Gene ◽  
Driver Genes ◽  
Cancer Driver ◽  
Bona Fide ◽  
Cancer Driver Genes

Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge. Numerous methods have been developed to identify driver genes, but evaluation of the performance of these methods is hindered by the lack of a gold standard, that is, bona fide driver gene mutations. Here, we establish an evaluation framework that can be applied to driver gene prediction methods. We used this framework to compare the performance of eight such methods. One of these methods, described here, incorporated a machine-learning–based ratiometric approach. We show that the driver genes predicted by each of the eight methods vary widely. Moreover, the P values reported by several of the methods were inconsistent with the uniform values expected, thus calling into question the assumptions that were used to generate them. Finally, we evaluated the potential effects of unexplained variability in mutation rates on false-positive driver gene predictions. Our analysis points to the strengths and weaknesses of each of the currently available methods and offers guidance for improving them in the future.

scholarly journals Mutational landscape of primary, metastatic, and recurrent ovarian cancer reveals c-MYC gains as potential target for BET inhibitors

2018 ◽  
Vol 116 (2) ◽  
pp. 619-624 ◽  
Author(s):  
Charles Li ◽  
Elena Bonazzoli ◽  
Stefania Bellone ◽  
Jungmin Choi ◽  
Weilai Dong ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Metastatic Tumors ◽  
Driver Genes ◽  
Primary Tumors ◽  
Mutational Landscape ◽  
Recurrent Tumors ◽  
Bet Inhibitors

Ovarian cancer remains the most lethal gynecologic malignancy. We analyzed the mutational landscape of 64 primary, 41 metastatic, and 17 recurrent fresh-frozen tumors from 77 patients along with matched normal DNA, by whole-exome sequencing (WES). We also sequenced 13 pairs of synchronous bilateral ovarian cancer (SBOC) to evaluate the evolutionary history. Lastly, to search for therapeutic targets, we evaluated the activity of the Bromodomain and Extra-Terminal motif (BET) inhibitor GS-626510 on primary tumors and xenografts harboring c-MYC amplifications. In line with previous studies, the large majority of germline and somatic mutations were found in BRCA1/2 (21%) and TP53 (86%) genes, respectively. Among mutations in known cancer driver genes, 77% were transmitted from primary tumors to metastatic tumors, and 80% from primary to recurrent tumors, indicating that driver mutations are commonly retained during ovarian cancer evolution. Importantly, the number, mutation spectra, and signatures in matched primary–metastatic tumors were extremely similar, suggesting transcoelomic metastases as an early dissemination process using preexisting metastatic ability rather than an evolution model. Similarly, comparison of SBOC showed extensive sharing of somatic mutations, unequivocally indicating a common ancestry in all cases. Among the 17 patients with matched tumors, four patients gained PIK3CA amplifications and two patients gained c-MYC amplifications in the recurrent tumors, with no loss of amplification or gain of deletions. Primary cell lines and xenografts derived from chemotherapy-resistant tumors demonstrated sensitivity to JQ1 and GS-626510 (P = 0.01), suggesting that oral BET inhibitors represent a class of personalized therapeutics in patients harboring recurrent/chemotherapy-resistant disease.

scholarly journals PATH-50. ROUTINE MOLECULAR DIAGNOSIS OF GLIOMA PATIENTS USING A GLIOMA-SPECIFIC NGS PANEL

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi154-vi155
Author(s):  
Koji Yoshimoto ◽  
Nayuta Higa ◽  
Hajime Yonezawa ◽  
Hiroyuki Uchida ◽  
Toshiaki Akahane ◽  
...  
Keyword(s):  
Molecular Diagnosis ◽  
Gene Mutations ◽  
Chromosome 1 ◽  
Clinical Samples ◽  
Driver Gene ◽  
Driver Genes ◽  
Chromosome 1P ◽  
Ffpe Tumor ◽  
Grade Ii ◽  
Key Driver

Abstract AIM The 2016 WHO classification requires molecular diagnosis in routine glioma diagnostics. However, analysis of key driver gene mutations and chromosome 1p/19q co-deletions cannot be performed in a single platform. In this study, we evaluated the feasibility of a glioma-specific NGS panel for molecular diagnosis of glioma patients. MATERIALS AND METHODS We developed a glioma-specific NGS panel consisting of 48 genes, including glioma-relevant key driver genes and 21 genes mapped to chromosome 1 and 19. DNA was extracted from formaldehyde fixed-paraffin embedded (FFPE) tumor tissues histologically identified by a pathologist, and from patient-derived blood as a control. In this system, we implemented a molecular barcodes method to enhance confidence in clinical samples and analyzed 80 glioma patients (Grade II: 17 cases, Grade III: 16 cases, Grade IV: 47 cases). RESULTS From these 80 cases, IDH1 and H3F3A mutations were detected in 23 cases (29%) and 2 cases (5%), respectively. The 1p/19q co-deletion was detected in 15 cases (19%), with all cases also containing IDH1 mutations. In Grade IV cases, EGFR, PDGFR, and FGFR mutations were detected in 6% (amp 19%), 9%, and 4% (amp 17%) of cases, respectively. PTEN, TP53, NF1, RB1, and CDKN2A mutations were detected in 37% (del 72%), 45% (del 13%), 21% (del 23%), 15% (del 60%), and 2% (del 53%) of cases, respectively. CONCLUSION Diagnosis of glioma patients with this glioma-specific NGS panel is feasible.

scholarly journals Diversity spectrum analysis identifies mutation-specific effects of cancer driver genes

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Xiaobao Dong ◽  
Dandan Huang ◽  
Xianfu Yi ◽  
Shijie Zhang ◽  
Zhao Wang ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Spectrum Analysis ◽  
Driver Mutations ◽  
Driver Gene ◽  
Cancer Type ◽  
Driver Genes ◽  
Drug Responses ◽  
Cancer Driver ◽  
Specific Effects ◽  
Cancer Driver Genes

AbstractMutation-specific effects of cancer driver genes influence drug responses and the success of clinical trials. We reasoned that these effects could unbalance the distribution of each mutation across different cancer types, as a result, the cancer preference can be used to distinguish the effects of the causal mutation. Here, we developed a network-based framework to systematically measure cancer diversity for each driver mutation. We found that half of the driver genes harbor cancer type-specific and pancancer mutations simultaneously, suggesting that the pervasive functional heterogeneity of the mutations from even the same driver gene. We further demonstrated that the specificity of the mutations could influence patient drug responses. Moreover, we observed that diversity was generally increased in advanced tumors. Finally, we scanned potentially novel cancer driver genes based on the diversity spectrum. Diversity spectrum analysis provides a new approach to define driver mutations and optimize off-label clinical trials.

Somatic Mutational Landscape of AML with Inv(16) and t(8;21) Identifies Two Distinct Patterns in Relapse Tumors

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2362-2362
Author(s):  
Raman B. Sood ◽  
Nancy F Hansen ◽  
Frank X Donovan ◽  
Blake Carrington ◽  
Baishali Maskeri ◽  
...  
Keyword(s):  
Conflicts Of Interest ◽  
Clonal Evolution ◽  
Treatment Strategies ◽  
Gene Mutations ◽  
Driver Gene ◽  
Intrinsic Resistance ◽  
Driver Genes ◽  
In Vivo Models

Abstract Acute myeloid leukemia (AML) is a heterogeneous disease with a wide prognostic spectrum ranging from poor to good depending upon the underlying mutations and/or cytogenetic abnormalities. Although AMLs with inv(16)/t(16:16) or t(8,21), collectively referred to as core binding factor leukemias (CBF-AMLs), are classified as prognostically favorable, such patients often succumb to their disease following relapse after an initial response to cytarabine/anthracyclin-based treatment regimens. Thus, to develop successful treatment strategies, it is critical to understand the mechanisms leading to disease relapse and target them with novel therapeutic approaches. To pursue this goal, we applied genomic approaches (whole exome sequencing and single nucleotide polymorphism arrays) on DNA from samples collected at sequential time points (i.e., diagnosis, complete remission and relapse) in seven patients with inv(16) and six patients with t(8;21). We identified mutations in several previously identified AML driver genes, such as KIT, FLT3, DNMT3A, EZH2, SMC1A, SMC3, WT1 and NRAS. Three relapse samples showed mosaicism for monosomy/disomy of the region of chromosome 3 containing GATA2. Overall, our data revealed two distinct profiles that support different mechanisms of relapse: 1) diagnosis and relapse blasts harbor the same driver gene mutations, indicating the intrinsic resistance of the major clones present at diagnosis to treatment regimen used; 2) diagnosis and relapse tumors have different driver gene mutations, indicating disease clonal evolution possibly through treatment selective pressure. Furthermore, our data has identified previously unreported putative driver genes for AML. Among these, we identified same somatic variant (R222G) in DHX15, an RNA helicase involved in splicing, in two patients at diagnosis. The variant was also detected at relapse in one of these patients. Functional validation of the mechanistic roles of wild type and mutated DHX15 in hematopoiesis and leukemogenesis, respectively, is ongoing in in vitro and in vivo models. Disclosures No relevant conflicts of interest to declare.

Targeted, Deep Sequencing of Adult AML Patients Treated on the AMLCG-2008 Trial Detects Clonal Heterogeneity in 52% of Patients at Initial Diagnosis and Reveals Patterns of Clonal Evolution

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 697-697
Author(s):  
Maja Rothenberg-Thurley ◽  
Stephanie Schneider ◽  
Tobias Herold ◽  
Nikola P Konstandin ◽  
Annika Dufour ◽  
...  
Keyword(s):  
Gene Mutations ◽  
Driver Mutations ◽  
Published Data ◽  
High Dose ◽  
Clonal Heterogeneity ◽  
Driver Genes ◽  
Single Nucleotide ◽  
Patient Cohort ◽  
Recurrent Mutations ◽  
Frequent Event

Abstract Background: Recurrent mutations in >100 different genes have been described in AML, but the clinical relevance of most of these alterations has not been defined. Moreover, high-throughput sequencing techniques revealed that AML patients (pts) may harbor multiple, genetically related disease subclones. It is unclear whether clonal heterogeneity at diagnosis also associates with clinical characteristics or outcomes. To address these questions, we set out to characterize a relatively large, uniformly treated patient cohort for mutations in known and putative AML driver genes. Patients and Methods: We studied pretreatment blood or bone marrow specimens from adult AML pts who received high-dose cytarabine-based induction chemotherapy within the German multicenter AMLCG-2008 trial. Sequence variants (single nucleotide variants and insertions/deletions up to approx. 150bp) in 70 genes known to be mutated in AML or other hematologic neoplasms were analyzed by multiplexed amplicon resequencing (Agilent Haloplex; target region, 321 kilobases). Sequencing was performed on an Illumina MiSeq instrument using 2x250bp paired-end reads. A variant allele frequency (VAF) threshold of 2% was set for mutation detection, corresponding to heterozygous mutations present in 4% of cells in a specimen. Variants were classified as known/putative driver mutations, variants of unknown significance, or known germline polymorphisms based on published data (including dbSNP, the Catalogue Of Somatic Mutations In Cancer [COSMIC] and The Cancer Genome Atlas [TCGA]). In patients with more than one single nucleotide variant, the chi square test was used assess if the observed VAFs, adjusted for ploidy, were compatible with the presence of a single clone. Results: Material for genetic analyses was available for 280 of the 396 participants (71%) enrolled on the AMLC-2008 trial. To date, analyses have been completed for 248 pts (130 male, 118 female; median age, 54y; range 19-81y). Updated results for the entire cohort will be presented at the meeting. Mean coverage of target regions was >600-fold, and on average, 98.2% of target bases were covered >30-fold. We detected a total of 914 mutations in 46 genes, including 37 genes mutated in >1 patient (Fig. A). Nine genes (NPM1, FLT3, DNMT3A, NRAS, WT1, IDH2, RUNX1, TET2 and ASXL1) were mutated in >10% of patients (red dashed line in Fig. A). We found a median of 4 mutations per patient (range: 0-10). Of note, only 1 patient had no detectable mutation and no abnormality on cytogenetic analysis. Patients with Intermediate-risk cytogenetics according to the MRC classification harbored a higher number of driver gene mutations (median, 4) compared to patients with MRC Favorable (median, 2 mutations) or Unfavorable (median, 3 mutations) cytogenetics (P<.001). When analyzing patterns of co-occurring and mutually exclusive mutations, we confirmed well-known associations (e.g., between CEBPA and GATA2 mutations) and identified novel pairs of mutations that frequently occur in combination and, to our knowledge, have not yet been reported in AML (e.g., ASXL1/STAG2, SRSF2/STAG2). These findings may guide functional studies on the molecular mechanisms of leukemogenesis. We found evidence for clonal heterogeneity in 129 (52%) of 248 pts, based on the presence of mutations with significantly (P<.001) different VAFs within the same sample. Our analyses reveal differences in allele frequencies between different AML driver genes. Mutations can be grouped into "early" events that often are present in the founding clone, and "late" events which frequently appear to be restricted to subclones (Fig. B). Conclusion: Targeted sequencing allowed detection of mutations affecting a panel of known and putative AML driver genes in clinical specimens with high sensitivity. Our data from the AMLCG-2008 patient cohort reveal novel patterns of cooperating gene mutations, and show that the presence of subclonal driver mutations is a frequent event in AML pts. Differentiating between "founding clone" mutations, and subclonal mutations that typically occur later in the disease has implications for choosing targeted therapies aimed at disease eradication. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.

Profiling the Genomic Landscape at the Early Stages of CLL: Low Genomic Complexity and Paucity of Driver Mutations in MBL and Indolent CLL

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3214-3214 ◽  
Author(s):  
Andreas Agathangelidis ◽  
Viktor Ljungström ◽  
Lydia Scarfò ◽  
Claudia Fazi ◽  
Maria Gounari ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Research Funding ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Driver Genes ◽  
Hematopoietic Stem ◽  
Genomic Complexity ◽  
Targeted Deep Sequencing

Abstract Chronic lymphocytic leukemia (CLL) is preceded by monoclonal B cell lymphocytosis (MBL), characterized by the presence of monoclonal CLL-like B cells in the peripheral blood, yet at lower numbers than those required for the diagnosis of CLL. MBL is distinguished into low-count (LC-MBL) and high-count (HC-MBL), based on the number of circulating CLL-like cells. While the former does not virtually progress into a clinically relevant disease, the latter may evolve into CLL at a rate of 1% per year. In CLL, genomic studies have led to the discovery of recurrent gene mutations that drive disease progression. These driver mutations may be detected in HC-MBL and even in multipotent hematopoietic progenitor cells from CLL patients, suggesting that they may be essential for CLL onset. Using whole-genome sequencing (WGS) we profiled LC-MBL and HC-MBL cases but also CLL patients with stable lymphocytosis (range: 39.8-81.8*109 CLL cells/l) for >10 years (hereafter termed indolent CLL). This would refine our understanding of the type of genetic aberrations that may be involved in the initial transformation rather than linked to clinical progression as is the case for most, if not all, CLL driver mutations. To this end, we whole-genome sequenced CD19+CD5+CD20dim cells from 6 LC-MBL, 5 HC-MBL and 5 indolent CLL cases; buccal control DNA and polymorphonuclear (PMN) cells were analysed in all cases. We also performed targeted deep-sequencing on 11 known driver genes (ATM, BIRC3, MYD88, NOTCH1, SF3B1, TP53, EGR2, POT1, NFKBIE, XPO1, FBXW7) in 8 LC-MBL, 13 HC-MBL and 7 indolent CLL cases and paired PMN samples. Overall similar mutation signatures/frequencies were observed for LC/HC-MBL and CLL concerning i) the entire genome; with an average of 2040 somatic mutations observed for LC-MBL, 2558 for HC-MBL and 2400 for CLL (186 for PMN samples), as well as ii) in the exome; with an average of non-synonymous mutations of 8.9 for LC-MBL, 14.6 for HC-MBL, 11.6 for indolent CLL (0.9 for PMN samples). Regarding putative CLL driver genes, WGS analysis revealed only 2 somatic mutations within NOTCH1, and FBXW7 in one HC-MBL case each. After stringent filtering, 106 non-coding variants (NCVs) of potential relevance to CLL were identified in all MBL/CLL samples and 4 NCVs in 2/24 PMN samples. Seventy-two of 110 NCVs (65.5%) caused a potential breaking event in transcription factor binding motifs (TFBM). Of these, 29 concerned cancer-associated genes, including BTG2, BCL6 and BIRC3 (4, 2 and 2 samples, respectively), while 16 concerned genes implicated in pathways critical for CLL e.g. the NF-κB and spliceosome pathways. Shared mutations between MBL/CLL and their paired PMN samples were identified in all cases: 2 mutations were located within exons, whereas an average of 15.8 mutations/case for LC-MBL, 8.2 for HC-MBL and 9 for CLL, respectively, concerned the non-coding part. Finally, 16 sCNAs were identified in 9 MBL/CLL samples; of the Döhner model aberrations, only del(13q) was detected in 7/9 cases bearing sCNAs (2 LC-MBL, 3 HC-MBL, 2 indolent CLL). Targeted deep-sequencing analysis (coverage 3000x) confirmed the 2 variants detected by WGS, i.e. in NOTCH1 (n=1) and FBXW7 (n=1), while 4 subclonal likely damaging variants were detected with a VAF <10% in POT1 (n=2), TP53 (n=1), and SF3B1 (n=1) in 4 HC-MBL samples. In conclusion, LC-MBL and CLL with stable lymphocytosis for >10 years display similar low genomic complexity and absence of exonic driver mutations, assessed both with WGS and deep-sequencing, underscoring their common low propensity to progress. On the other hand, HC-MBL comprising cases that may ultimately evolve into clinically relevant CLL can acquire exonic driver mutations associated with more dismal prognosis, as exemplified by subclonal driver mutations detected by deep-sequenicng. The existence of NCVs in TFBMs targeting pathways critical for CLL prompts further investigation into their actual relevance to the clinical behavior. Shared mutations between CLL and PMN cells indicate that some somatic mutations may occur before CLL onset, likely at the hematopoietic stem-cell level. Their potential oncogenic role likely depends on the cellular context and/or microenvironmental stimuli to which the affected cells are exposed. Disclosures Stamatopoulos: Novartis: Honoraria, Research Funding; Janssen: Honoraria, Other: Travel expenses, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Abbvie: Honoraria, Other: Travel expenses. Ghia:Adaptive: Consultancy; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; Roche: Honoraria, Research Funding.

scholarly journals Targeted Mutational Analysis of Cortisol-Producing Adenomas

2021 ◽  
Author(s):  
Juilee Rege ◽  
Jessie Hoxie ◽  
Chia-Jen Liu ◽  
Morgan N Cash ◽  
James M Luther ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Mutational Analysis ◽  
Cushing Syndrome ◽  
Gene Mutations ◽  
Amplicon Sequencing ◽  
Formalin Fixed Paraffin ◽  
Mutation Profile ◽  
Somatic Gene ◽  
Formalin Fixed Paraffin Embedded ◽  
Aldosterone Producing Adenoma

Abstract Background Somatic gene mutations have been identified in only about half of cortisol-producing adenomas (CPA). Affected genes include PRKACA, GNAS, PRKAR1A, and CTNNB1. Objective To expand our understanding of the prevalence of somatic mutations in CPA from patients with overt Cushing syndrome (OCS) and “subclinical” mild autonomous cortisol excess (MACE), with an immunohistochemistry (IHC)‒guided targeted amplicon sequencing approach using formalin-fixed paraffin-embedded (FFPE) tissue. Method We analyzed FFPE adrenal tissue from 77 patients (n=12 men, 65 women) with either OCS (n=32) or MACE (n=45). Using IHC for 17α-hydroxylase/17,20-lyase (CYP17A1) and 3β-hydroxysteroid dehydrogenase (HSD3B2), we identified 78 CPA (32 OCS-CPA and 46 MACE-CPA). Genomic DNA was isolated from the FFPE CPA and subjected to targeted amplicon sequencing for identification of somatic mutations. Results Somatic mutations were identified in 71.8% (56/78) of the CPA. While PRKACA was the most frequently mutated gene in OCS-CPA (14/32, 43.8%), somatic genetic aberrations in CTNNB1 occurred in 56.5% (26/46) of the MACE-CPA. Most GNAS mutations were observed in MACE-CPA (5/7,71.4%). No mutations were observed in PRKAR1A. In addition to the known mutations, we identified one previously unreported mutation in PRKACA. Two patients with MACE harbored two adjacent tumors within the same adrenal gland: one patient had two CPA, and the other patient had a CPA and an aldosterone-producing adenoma (identified by IHC for aldosterone synthase). Conclusion Comprehensive FFPE IHC-guided gene-targeted sequencing approach identified somatic mutations in 71.8% of the CPA. OCS-CPA demonstrated a distinct mutation profile compared to MACE-CPA.

scholarly journals Cancer-specific associations of driver genes with immunotherapy outcome

2020 ◽  
Author(s):  
Tomi Jun ◽  
Tao Qing ◽  
Guanlan Dong ◽  
Maxim Signaevski ◽  
Julia F Hopkins ◽  
...  
Keyword(s):  
Immune Checkpoint Inhibitor ◽  
Gene Mutations ◽  
Driver Gene ◽  
Oncogenic Signaling ◽  
Multiple Cancer ◽  
Driver Genes ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Types ◽  
Oncogenic Signaling Pathways

AbstractGenomic features such as microsatellite instability (MSI) and tumor mutation burden (TMB) are predictive of immune checkpoint inhibitor (ICI) response. However, they do not account for the functional effects of specific driver gene mutations, which may alter the immune microenvironment and influence immunotherapy outcomes. By analyzing a multi-cancer cohort of 1,525 ICI-treated patients, we identified 12 driver genes in 6 cancer types associated with treatment outcomes, including genes involved in oncogenic signaling pathways (NOTCH, WNT, FGFR) and chromatin remodeling. Mutations of PIK3CA, PBRM1, SMARCA4, and KMT2D were associated with worse outcomes across multiple cancer types. In comparison, genes showing cancer-specific associations—such as KEAP1, BRAF, and RNF43—harbored distinct variant types and variants, some of which were individually associated with outcomes. In colorectal cancer, a common RNF43 indel was a putative neoantigen associated with higher immune infiltration and favorable ICI outcomes. Finally, we showed that selected mutations were associated with PD-L1 status and could further stratify patient outcomes beyond MSI or TMB, highlighting their potential as biomarkers for immunotherapy.

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