December 10, 2011
GPS presents at the American Society of Hematology (ASH) December 10-13, 2011
American Society of Hematology (ASH) December 10-13, 2011 in San Diego, CA. Click here for more information.
1830 High Throughput Digital Quantification of Genomic Copy Number Alterations in Multiple Myeloma
Program: Oral and Poster Abstracts
Session: 651. Myeloma - Biology and Pathophysiology, excluding Therapy: Poster I
Saturday, December 10, 2011, 5:30 PM-7:30 PM
Hall GH (San Diego Convention Center)
Shashikant Kulkarni, PhD1,2,3*, Nathan Elliott, PhD4*, Mark Fiala, BS5*, Jacob Paasch, BS5*, Michael H. Tomasson, MD3,5, Keith E. Stockerl-Goldstein, MD3,5, John F. DiPersio, MD, PhD3,5, Gary Geiss, PhD4*, Ravi Vij, MD3,5 and Vishwanathan Hucthagowder, PhD1*
1Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 2Department of Genetics, Pediatrics, Washington University School of Medicine, St. Louis, MO 3Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 4NanoString Technologies, Seattle, WA 5Division of Medical Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
Multiple myeloma (MM) is a fatal disease characterized by clonal expansion of malignant plasma cells. The etiopathogenesis of MM is not fully understood. Several numerical and structural chromosomal aberrations have been identified as diagnostic markers and predictors of evolution in MM. Cytogenetic studies in MM patients are often not informative due to technical difficulties related to low proliferation of malignant plasma cells and outgrowth of non-malignant cells. Fluorescence in-situ hybridization (FISH) on CD138+ sorted plasma cells is probably the best method for maximizing diagnostic yield in MM, but is limited to the genomic regions queried. To overcome the limitations of the amount of clinical material available and to be able to interrogate large number of MM specific genomic aberrations, we developed and validated a MM genomic copy number signature. This signature comprised of 183 MM specific genes, was developed by pooling data from extensive meta-analyses on publically available raw data from ~450 MM patients and copy number data generated by high-resolution SNP arrays (Affymetrix) from 39 MM patients in our cohort. To validate this signature of a large number of genes, we tested a recently developed innovative high throughput digital technology NanoString - nCounter assay. This technology captures and counts individual DNA molecules without enzymatic reactions or bias and is notable for its high levels of sensitivity, linearity, multiplex capability, and digital readout. It requires minimal input of DNA (~300ng) making it a valuable tool for genomic copy number signature validation, diagnostic testing, and large translational studies, all of which often are limited by the very small amounts of clinical material available. Digital data was generated using nCounter analysis in 42 newly diagnosed, untreated MM patients. To identify the true acquired somatic copy number changes matched germline (skin) and tumor (sorted CD138+ cells) were analyzed from each of these MM patients. All of the genes tested demonstrated highly significant concordance with our microarray data (P < 0.05). The dynamic range in copy number calls with this assay is very large since there are no saturation issues and there is very low background. In this study, we were able to detect a maximum of 9 copies in some of the targets. We observed amplification of chromosomes 1q(51%), 3(65%), 5(65%), 7(70%), 9(56%), 11(72%), 15(56%), 19(53%), 21(42%), and deletion of chromosomes 1p(25%), 6q(28%), 8p(42%), 12p(40%), 13(47%), 14(26%) and 16q(49%). Interestingly, cytoband 2p11.2 and 14q32.33 consisting IGK and IGH genes were deleted in 75% and 93% of the patient population respectively. Overall, our results correlate well with the known pattern of genomic aberrations in MM. Additional analysis in an extended panel with clinically categorized samples is carried on to test the utility of this myeloma specific gene signature. To the best of our knowledge this is the first application of a high-throughput digital system to validate genomic copy number signature in cancer.
809 Genomic Landscape of Immunoglobulin Light Chain (AL) Amyloidosis and Comparative Analyses with Related Malignant Plasma Cell Disorder- Multiple Myeloma
Program: Oral and Poster Abstracts Type: Oral
Session: 651. Myeloma - Biology and Pathophysiology, excluding Therapy: Novel Insights into Clinical Behavior
Monday, December 12, 2011: 5:30 PM
Room 6DE (San Diego Convention Center)
Vishwanathan Hucthagowder, PhD1*, Jahangheer Shaik, PhD1*, Mark Fiala, BS2*, Jacob Paasch, BS2*, Rakesh Nagarajan, MD, PhD1,3*, Keith E. Stockerl-Goldstein, MD2,3, John F. DiPersio, MD, PhD2,3, Michael H. Tomasson, MD2,3, Ravi Vij, MD2,3 and Shashikant Kulkarni, PhD1,3,4*
1Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 2Division of Medical Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 3Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 4Department of Genetics, Pediatrics, Washington University School of Medicine, St. Louis, MO
Immunoglobulin light chain amlyloidosis (AL) is a rare plasma cell disorder characterized by deposition of misfolded light chains in various organ systems with an average survival of 1-2 years. AL is also the most common form of systemic amyloidosis with 1200-3200 newly diagnosed cases reported annually in the United States. Very little is known regarding specific genomic aberrations associated with AL-amyloidosis. Aside from the light chain selection, no phenotypic or genetic features have been identified that distinguish AL amyloidosis from other plasma cell dyscrasias. Understanding the genetics of AL and the molecular mechanisms involved in amyloid formation may lead to early diagnosis and the identification of novel drug targets and therapies. We therefore have attempted to study the genomic landscape of AL patients and MM for comparison. Genomic copy number and loss of heterozygosity (LOH) analyses were performed on DNA derived from tumor (CD138 sorted cells) and matched germline (skin) from biopsy proven AL patients using Affymetrix single nucleotide polymorphism (SNP) 6.0 arrays. Numerous genomic changes with gains in chromosome 1q, 6, 9, 11q, 15, 19 and 21 and loss on chromosome 1p, 2q, 8, 10, 12, 13, 14, 16, 18, 20 and 22 were observed in more than 10% of the patients. Recurrent genomic changes in about 249 segments involving 457 genes were present in about 1/3 of AL patients. In particular, deletion of IGK, IGH, PIK3CA, FLT3, RB1, PCDH9, GPC6, RASA3, ADAM6 genes and amplification of CFHR1, JAK2, GCNT1, TSC1, PGR genes were observed. Gene network analysis showed five distinct major modules consisting of 51 distinct elements and involving PDGF, TP53, interleukin signaling, TRKA signaling, cell cycle and mitotic pathways were enriched. Allele specific copy number analysis in tumor (ASCAT) profile showed increased ploidy status of the AL genome in 47% of the assessed patients. LOH was observed in chromosomes 4, 5, 6, 8, 9, 12, 13, 18 and 22 in 30% of patients, ranging from 5Mb to entire chromosome. Furthermore, genomic comparisons of AL with multiple myeloma (MM) showed the typical archetype of myeloma's signature with exception of gain of chromosomes 3, 5, 7 and loss of chromosome 6q and 8p. Interestingly deletion of IGH, IGK locus and PIK3CA gene were observed at a higher frequency in AL patients. Categorical analysis using isotype specific classification in AL showed a significantly higher frequency of deletion in chromosome 14, 13, 8 and amplification of chromosome 9q in the kappa type than lambda isotype. To the best of our knowledge, this is the first ultra-high resolution study of the genomic landscape of AL amyloidosis. In this study, we have found several novel genes and pathways associated with this rare disease. The numerous copy number alterations of AL thus reflect the genomic complexity and the heterogeneity of this disease. Additional genome-wide analysis in a larger panel with target organ stratified patients is under way and may further our understanding of genetic changes specifically associated with AL.
3547 Detection of FLT3 Internal Tandem Duplications in Acute Myeloid Leukemia by Targeted Multi-Gene Next Generation Sequencing
Program: Oral and Poster Abstracts
Session: 611. Leukemias - Biology, Cytogenetics and Molecular Markers in Diagnosis and Prognosis: Poster III
Monday, December 12, 2011, 6:00 PM-8:00 PM
Hall GH (San Diego Convention Center)
David H Spencer, MD/PhD1*, Haley Abel, Ph.D.2*, Philippe Szankasi, PhD3, Todd W. Kelley, MD4, Shashikant Kulkarni, PhD5*, Mark A. Watson, MD, PhD6*, John D Pfeifer, MD, PhD7* and Eric J. Duncavage, MD8
1Department of Pathology & Immunology, Washington University School of Medicine/Barnes-Jewish Hospital, St. Louis, MO 2Department of Genetics, Washington University, St. Louis, MO 3Research and Development, ARUP Laboratories, Salt Lake City, UT 4Department of Pathology, University of Utah, Salt Lake City, UT 5Department of Pathology and Immunology, Washington University, Saint Louis, MO 6Department of Pathology and Immunology, Siteman Cancer Center, Washington University, St. Louis, MO 7Department of Molecular and Anatomic Pathology, Washington University, saint Louis, MO 8Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, MO
Recurrent somatic mutations are valuable prognostic markers in cytogenetically normal Acute Myeloid Leukemia (AML). The most common of these mutations is a 9 to ~150 bp internal tandem duplication (ITD) in the fms-related tyrosine kinase 3 (FLT3) gene, which is typically identified via PCR amplification and capillary electrophoresis. Since testing for individual mutations in this manner will become laborious and expensive as the number of clinically relevant mutations increases, we and others have proposed using targeted next-generation sequencing (NGS) for comprehensive detection of somatic mutations in multiple genes simultaneously. Successful application of this approach will require automated analysis methods capable of sensitive detection of a variety of mutation types, including single-base substitutions and insertions/deletions, with a low false-positive rate. However, the accuracy of current methods for identifying medium-sized insertions such as the FLT3 ITDs has not been established. Therefore, we sought to determine the ability of several common analysis tools to identify FLT3 ITDs from Illumina NGS sequence data.
We performed targeted sequencing of 10 samples with known FLT3 ITDs ranging between 17 and 93 base-pairs (bp) as part of a larger test panel of 28 genes commonly mutated in AML and other malignancies. Nine of the FLT3 ITD-positive samples were from patients with newly diagnosed AML and were confirmed by PCR and capillary electrophoresis. A cancer cell line known to be heterozygous for a 30 bp FLT3 ITD, MV4-11, was also included. Indexed Illumina sequencing libraries were generated using automated library preparation and enriched for target regions using solution-phase hybridization-capture with biotinylated cRNA probes targeting exons +/- 200 bp plus 1 kb flanking the FLT3 gene and the 27 other genes in the panel. Enriched libraries were sequenced in multiplex on an Illumina HiSeq instrument using 2 x 101 bp reads. Demultiplexed reads were mapped to the hg19 reference sequence with novoalign, and indels were called in a 1 kilobase-pair region surrounding the FLT3 ITD with samtools, GATK, maq, CLC Genomics Workbench, PINDEL, and DINDEL using default parameters, in addition to de novo assembly of reads with partial similarity to the region using phrap. Insertion calls were then compared to results from PCR and capillary electrophoresis.
Multiplex sequencing resulted in 585 to 1,000-fold raw coverage of the FLT3 gene for the 10 study samples (Table 1). No FLT3 ITD insertions were detected in any sample using the common NGS analysis tools samtools, GATK, maq, DINDEL, and CLC Genomics Workbench. However, PINDEL identified insertions between 17 and 72 bp in 9 of 10 FLT3 ITD-positive samples. PINDEL failed to detect a 93 bp ITD insertion (the largest insertion in this set) in one patient sample, as well as an 84 bp insertion in a patient with two insertions (81 and 54 bp) detected by standard methods. De novo assembly of the FLT3 ITD region also resulted in detection of insertions in 9 of the 10 cases. No insertions were called in an additional set of 15 samples without known FLT3 ITDs.
We evaluated the ability of several NGS analysis tools to detect previously known FLT3 ITDs in multi-gene targeted NGS data. Most of the general-purpose analysis tools we tested were unable to detect FLT3 ITD insertions. However, two approaches detected known FLT3 ITD insertions in 90% of the samples tested in this study, including the program PINDEL and de-novo assembly of the FLT3 ITD region using phrap. These results demonstrate that medium-sized FLT3 ITD insertions can be detected in clinical samples by high coverage NGS sequencing with the appropriate analysis pipeline. However, further methods for reliable detection of larger (>70bp) insertions must be developed before clinical NGS-based methods can be applied to the detection of the full spectrum of somatic mutations present in leukemias and other malignancies.
Click here to see more.