Supplementary Information from Large-scale Identification of Clonal Hematopoiesis and Mutations Recurrent in Blood Cancers (original) (raw)
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Supplementary Table 5. Unique mutations allowed at hotspots. Listed are 350 mutations reported across the 48 somatic landscape studies that were not listed as queried variants for CHIP in Jaiswal et al. 14 (many of those 48 studies were published around or after that landmark CHIP paper). Columns show the number of mutations resulting in the exact protein exchange and for the total number of protein-altering mutations reported for each amino acid position or splice site locus across the 48 studies. Tallies are for the total number of patients with a reported mutation (No. patients), number of hematological malignancies having at least one reported patient with the mutation (No. hemat. disorders), and the number of studies reporting at least one patient with the mutation (No. studies).
Journal of Molecular Biomarkers & Diagnosis, 2015
Background: Tumor biopsies obtained from patients are often limited in size and availability, and the ability to perform multiple diagnostic assays depends on the quantity and quality of the tissue. Here we describe and evaluate a method for performing DNA-based mutational analyses after immunohistochemistry analysis has been performed, using a single tissue section. Method: Immunohistochemistry analysis was performed on 4-5 µm formalin-fixed paraffin-embedded tumor tissue sections and immunohistochemistry-stained sections were stored for subsequent genomic analysis. DNA was isolated from these immunohistochemistry-stained sections and DNA quality was assessed using a multiplexpolymerase chain reaction method as well as real time quantitative polymerase chain reaction of commonly used reference genes. Subsequently, genomic DNA was pre-amplified and mutations in KRAS, BRAF, NRAS and PIK3CA were detected by validated Taqman assays. Comparisons were made with results from unstained formalinfixed paraffin-embedded sections obtained from the same paraffin block. Results: Our results demonstrate that genomic DNA isolated from immunohistochemistry-stained and unstained formalin-fixed paraffin-embedded tissue sections are comparable in quality and are suitable for downstream analysis using polymerase chain reaction based assays. We also found that the sensitivity and specificity in detecting hotspot mutations are comparable in both sources of genomic DNA. This study reports 100% concordance in detecting hotspot mutations in KRAS, BRAF, NRAS and PIK3CA using quantitative real-time polymerase chain reaction between stained and unstained formalin-fixed paraffin-embedded sections. Conclusion: We conclude that by using our novel approach, it is possible to perform immunohistochemistry staining followed by genomic analysis using a single 4-5 µm section of formalin-fixed paraffin-embedded tissue.
Software and database for the analysis of mutations in
1996
Fibrillin is the major component of extracellular microfibrils. Mutations in the fibrillin gene on chromosome 15 (FBN1) were described at first in the heritable connective tissue disorder, Marfan syndrome (MFS). More recently, FBN1 has also been shown to harbor mutations related to a spectrum of conditions phenotypically related to MFS and many mutations will have to be accumulated before genotype/phenotype relationships emerge. To facilitate mutational analysis of the FBN1 gene, a software package along with a computerized database (currently listing 63 entries) have been created. Each line represents a single FBN1 mutation. The columns contain the following information and abbreviations: Column A. File number. Column B. Exon number at which the mutation is located. Exons are numbered with respect to the translational initiation site given by Pereira et al. (35). Column C. Nucleotide position at which the mutation is located, numbered as above. Column D. Codon number at which the mutation is located, numbered as above. If the mutation spans more than one codon, e.g. there is a deletion of several bases, only the first (5′) codon is entered. Column E. Normal base sequence of the codon in which the mutation occurred. Column F. Mutated base sequence of the codon in which the mutation occurred. If the mutation is a base pair deletion or insertion this is indicated by 'del' or 'ins' followed by the number of bases deleted or inserted and the position of this deletion or insertion in the codon (a, b or c). The nucleotide position is the first that is deleted or the one preceding the insertion. For example, 'del66b' is a deletion of 66 bases including the second base of the codon; 'ins4b' is an insertion of 4 bases occurring between the second and the third base of the codon. Column G. Concerns base substitutions. It gives the base change, by convention, read from the coding strand. If the mutation predicts a premature protein-termination, the novel stop codon position is given, e.g. 'stop at 2115'. Column H. Mutation name according to Beaudet et al. (41). To designate missense mutations, the number of the amino acid position is flanked by the single letter code corresponding to the normal amino acid prior to the number, and the mutant amino acid following the number (e.g. Gly to Ala at codon 85 is designated 'G85A'). Nonsense mutations are designated similarly to missense mutations except that X is used to indicate any termination codon (e.g. Tyr to stop at codon 76 is designated 'Y76X'). Frameshift, insertion and deletion mutations are designated by the nucleotide number followed by 'ins' for insertion or 'del' for deletion. The nucleotide position is the first that is deleted or the one preceding it in the case of insertions. Exact nucleotides are indicated for two or less bases (e.g. 441delA). For three or more bases, the insertion or deletion is specified by the size of the change (e.g. 852del22 indicates a 22 bp deletion starting from nucleotide 852). Splicing mutations are designated by a plus (+) or minus (-) nucleotide relative to the first or last base at the nearest exon (711+1G→T is a G to T substitution in the first base of the intron following the exon that ends at nucleotide 711). Column I. Wild type amino acid. Column J. Mutant amino acid. Deletion and insertion mutations which result in a frameshift are designated by 'Frameshift'. Nonsense mutations are designated by 'stop'. Column K. Protein domain in which the mutation occurs. Each motif group is numbered separately and according to their position with respect to the amino terminal end of the protein, e.g. 'cb EGF-like' (for calcium-binding EGF-like motifs) #1 to 43, 'EGF-like' (for non calcium-binding EGF-like motifs) #1 to 4, '8-cys' (for '8-cysteine' motifs) # 1 to 7, 'Hybrid motifs' # 1 to 2 (35). Columns L-Q. Diagnostic manifestations in the systems listed by Beighton et al. (42). In all these columns, '?' indicates either lack of or unspecified data until more precise information is available. Column L. Presence (+) or absence (-) of skeletal manifestations. Column M. Presence (+) or absence (-) of ocular manifestations. Column N. Presence (+) or absence (-) of cardiovascular manifestations. Column O. Presence (+) or absence (-) of pulmonary manifestations. Column P. Presence (+) or absence (-) of manifestations in skin and integument. Column Q. Presence (+) or absence (-) of manifestations in central nervous system. Column R. Reference number indicating the publication in which the mutation is described. Full citations (authors, year, tittle, volume, pages) are provided with the database. If the same mutation has been reported for the same patient in different papers only one entry is made. If the same mutation has been reported for unrelated patients, a separate entry is made for each patient. Note: The present version of the database cannot accommodate two mutational events in a given allele therefore the compound deletion reported by Nijbroek et al. (23), i.e. del3901-4; 3908-9 d is not included.
2023
Supplementary Table 8. CHIP mutations not exclusive to hotspots identified in the three non-cancer cohorts. Listed are 189 CHIP mutations identified in 183 persons of the three non-cancer cohorts (N=4,530) occurring in hematopoietic-associated genes but not required to occur at a hematologic hotspot, identified as per the criteria used in Jaiswal et al. 14. These mutations were required to meet a variant allele frequency (VAF) threshold of 4%. Cohort* SRR ID # Chr. Start pos. (hg19) End pos. (hg19) Ref. Alt. Ref. reads Alt. reads VAF Ref./Alt. reads on both strands Transcript Mutation M/F † Age ‡ No. patients/ hemat. disorders/ studies hotspot observed in 48 studies § gnomAD allele frequency (exome) gnomAD allele frequency (genome)
Utility of Multiplex Mutation Analysis in the Diagnosis of Chronic Myelomonocytic Leukemia
Journal of Leukemia, 2013
Chronic myelomonocytic leukemia (CMML) is a myeloid neoplasm characterized by both myeloproliferative and myelodysplastic features in addition to persistent peripheral blood monocytosis (>1×10 9 /L) that is required for the diagnosis. Clonal cytogenetic abnormalities are identified in only 20%-30% of CMML patients and it can be diagnostically challenging to exclude reactive monocytosis in some cases. Several gene mutations have recently been implicated in the pathogenesis of CMML that involve tyrosine kinase-signaling pathways, transcriptional regulation, metabolism, splicing, and epigenetic regulatory mechanisms. This study was designed to assess recurrent mutations in CMML using a multiplex mass spectrometry based approach, and to determine the utility of mutation screening in CMML, particularly in cytogenetically normal cases. The Oregon Health and Science University (OHSU) surgical pathology database was searched from 2010-2012 to identify consecutive CMML cases fulfilling WHO diagnostic criteria. Cytogenetic analyses and molecular studies were performed on the diagnostic bone marrow specimens. DNA extracts were screened for point mutations using a multiplex PCR panel with mass-spectroscopy read out that covers 370 point mutations across 31 genes associated with leukemia. Of the 48 CMML cases identified in the OHSU files, 43 had available cytogenetic studies. Of these, 10/43 cases (23%) had cytogenetic abnormalities including: trisomy 8 (n=4), trisomy 21 (n=2), deletion 7q (n=1), del 13q (n=1), complex karyotype (n=1) and t (3;3) (n=1). Of the cases with cytogenetic data, 22 had available DNA for mutation analysis, and 11 of these genotyped cases (50%) had detectable mutations in the following genes: CBL (n=3), CKIT, JAK2, KRAS (n=2), NRAS (n=3) and NPM1. Nine cases with detected mutations had normal cytogenetics. Concomitant molecular and cytogenetic abnormalities were seen in 2 cases: one case with trisomy 8 and CBL C384Y and one case with trisomy 21 and JAK2 V617F. In the 22 cases with available cytogenetic and molecular data, performing routine multiplex molecular testing in addition to cytogenetic studies in CMML patients increased the detection of genetic abnormalities from 23% (5/22) to 64% (14/22), with frequent CBL and RAS mutations in our cohort. This study confirms that gene mutations are common events in CMML, and multiplex mutation analysis can be applied in the clinical setting to assist in diagnosis and may identify actionable mutations for targeted therapy. complex karyotype), and intermediate risk (all other single or double abnormalities) [6]. However, none of these cytogenetic findings are specific for CMML and the overall incidence of chromosomal abnormalities is approximately 20-30% [1]. A significant majority of CMML cases are diagnosed without a cytogenetic abnormality to support the diagnosis or allow risk stratification. Several gene mutations have recently been implicated in the pathogenesis of CMML and involve tyrosine kinase-signaling pathways, transcriptional regulation, epigenetic regulatory mechanisms, and genes involved in the splicing machinery [7-15,16]. In this study, we evaluated the frequency of cytogenetic abnormalities in CMML and report our single institution experience of mutational analysis with a multiplex mass spectrometry based approach.
Bovolenta et al. Human Mutation Mar;33(3):572-81. doi: 10.1002/humu.22017
Duchenne and Becker muscular dystrophies are caused by mutations in the dystrophin gene. Both the enormous size of this gene and heterogeneous set of causative mutations behind these pathologies may hamper and even prevent accurate molecular diagnosis. Often RNA analysis is required not only to identify mutations escaping MLPA/CGH or exon sequencing but also to validate the functional effect of novel variations that may affect the exon composition of the DMD gene. We present the design and experimental validation of a new, simple, and easy-to-use platform we call FluiDMD. This platform is based on the Applied Biosystems 7900HT TaqMan R low-density array technology and is able to define the fullexon composition, profile the dystrophin isoforms present, establish changes in mRNA decay, and potentially identify all deletions/duplications and splicing affecting mutations contemporaneously. Moreover, we demonstrate that this system accurately detects the pathogenic effect of all dystrophin mutations belonging to any category, thereby highlighting the functional validation capacity of this system. The high efficacy and sensitivity of this tool in detecting mutations in the dystrophin transcript can be exploited in a variety of cells/tissues, in particular skin, which is harvested by causing minimum patient discomfort. We therefore propose FluiDMD as a validated diagnostic biomarker for molecular profiling of dystrophinopathies. Hum Mutat 33:572-581, 2012. C 2011 Wiley Periodicals, Inc. KEY WORDS: diagnostic biomarker; DMD mutations; fluidic cards; RNA analysis C 2011 WILEY PERIODICALS, INC.
Romanian Review of Laboratory Medicine, 2014
Introduction: Acute myeloid leukemia (AML) is a heterogeneous disease characterized by a late onset (it is rare in children), aggressive phenotype and dismal prognosis especially in patients in the older group (>65 years). For risk stratification of patients standard cytogenetic is used along with molecular techniques for point mutation identification. Here we describe a new method using next generation sequencing for identification of mutation in 5 AML recurrently mutated genes-RUNX1, FLT3, DNMT3A, IDH1 and IDH2. Materials and methods: Samples from 40 patients with normal karyotype AML referred to Fundeni Clinical Institute were sequenced. Primer design was performed using LaserGene Genomics suit. Next generation sequencing was performed on MiSeq (Illumina) and results were analyzed using LaserGene Genomics suit. Results of next generation sequencing were compared to Sanger sequencing. Results: No additional mutations were identified in samples from nine patients presenting FLT3-ITD and/or NPM1 mutations. In 25 out of 31 patients with normal karyotype and no FLT3-ITD and NPM1 mutations, we identified mutations in one of the 5 aforementioned genes. All these mutations identified by next generation sequencing were confirmed using the classical Sanger sequencing. Conclusions: We validated a very useful method for mutation identification in AML patients using next generation sequencing. There are many advantages exhibited by this method: it is more cost efficient and it has a higher sensitivity of mutation detection than Sanger sequencing, it has been described as being quantitative and in our case it allowed risk stratification for most of the normal karyotype AML samples which were FLT3-ITD and NPM1 negative.
mutation-profiling-impacts-clinical-decision-making.pdf
Introduction Indeterminate cytology occurs in a significant number of patients with solid pancreaticobiliary lesion that undergo endoscopic ultrasonography fine needle aspiration or endoscopic retrograde cholangio-pancreatography and can incur further expensive testing and inappropriate surgical intervention. Mutation profiling improves diagnostic accuracy and yield but the impact on clinical management is uncertain. We determined the performance of mutation profiling in clinical practice and its impact on management in solid pancreaticobiliary patients with indeterminate cytology. Methods Solid pancreaticobiliary patients with non-diagnostic, benign, atypical or suspicious cytology who had past mutation profiling testing were included. Mutation profiling examined KRAS mutation and a tumor suppressor gene associated loss of heterozygosity mutation panel covering 10 genomic loci. Two endosonographers made management recommendations without and then with mutation profiling results, indicating their level of confidence. Results Mutation profiling improved diagnostic accuracy in 232 patients with indeterminate cytology. Among patients with non-diagnostic cytology, low risk mutation profiling provided high specificity and negative predictive value for the absence of malignancy while high risk mutation profiling identified malignancies otherwise undetected. Mutation profiling increased clinician confidence in management recommendations and resulted in more conservative management in 10% of patients. Mutation profiling increased the rate of benign disease in patients recommended for conservative management (84% to 92%, p<0.05) and the rate of malignant disease in patients recommended for aggressive treatment (53% to 71%, p<0.05). Discussion Mutation profiling improved diagnostic accuracy and significantly impacted management decisions. Low risk mutation profiling results increased recommendations for conservative management and increased the rate of benign outcomes those patients, helping to avoid unnecessary aggressive interventions and improve patient outcomes.