PharmVIP: A Web-Based Tool for Pharmacogenomic Variant Analysis and Interpretation

Somatic Mutations and Loss of Heterozygosity of HLA Genes Are Frequently Occurred and Tightly Associated with Poor Prognosis in Adult T Cell Leukemia-Lymphoma

P842: Unified comprehensive analysis of NGS and optical genome mapping data for constitutional applications using Bionano VIA software

BackgroundThe human leukocyte antigen (HLA) region, the 3.8-Mb segment of the human genome at 6p21, has been associated with more than 100 different diseases, mostly autoimmune diseases. Due to the complex nature of HLA genes, there are difficulties in elucidating complete HLA gene sequences especially HLA gene haplotype structures by the conventional sequencing method. We propose a novel, accurate, and cost-effective method for generating phase-defined complete sequencing of HLA genes by using indexed multiplex next generation sequencing.ResultsA total of 33 HLA homozygous samples, 11 HLA heterozygous samples, and 3 parents-child families were subjected to phase-defined HLA gene sequencing. We applied long-range PCR to amplify six HLA genes (HLA-A, -C, -B, DRB1, -DQB1, and –DPB1) followed by transposase-based library construction and multiplex sequencing with the MiSeq sequencer. Paired-end reads (2 × 250 bp) derived from the sequencer were aligned to the six HLA gene segments of UCSC hg19 allowing at most 80 bases mismatch. For HLA homozygous samples, the six amplicons of an individual were pooled and simultaneously sequenced and mapped as an individual-tagging method. The paired-end reads were aligned to corresponding genes of UCSC hg19 and unambiguous, continuous sequences were obtained. For HLA heterozygous samples, each amplicon was separately sequenced and mapped as a gene-tagging method. After alignments, we detected informative paired-end reads harboring SNVs on both forward and reverse reads that are used to separate two chromosomes and to generate two phase-defined sequences in an individual. Consequently, we were able to determine the phase-defined HLA gene sequences from promoter to 3′-UTR and assign up to 8-digit HLA allele numbers, regardless of whether the alleles are rare or novel. Parent–child trio-based sequencing validated our sequencing and phasing methods.ConclusionsOur protocol generated phased-defined sequences of the entire HLA genes, resulting in high resolution HLA typing and new allele detection.

Computational analysis of next generation sequencing data and its applications in clinical oncology

Collection and storage of HLA NGS genotyping data for the 17th International HLA and Immunogenetics Workshop

Sensitive detection of internal tandem duplication (ITD) mutation of FLT3 is very important in acute myeloid leukemia. To increase detection sensitivity of FLT3-ITD, we developed new detection algorithm using next generation sequencing (NGS) data. We validated results using nested polymerase chain reaction (PCR) methods. We compared results of NGS data, nested PCR and conventional PCR methods. First, using whole exome sequencing data of 83 AML patients, we applied calling algorithm for FLT3-ITD. Briefly, to detect ITDs with NGS data, the reads are aligned to a reference sequence (UCSC hg19), with BWA which is a read aligner allowing soft-clipping. Some reads can be an indication of the occurrence of ITD and BWA aligns those reads as soft-clipped. Second, we deigned two types of primer for Nested PCR. The first primer was targeted wildly for between exon14 and exon15 of FLT3 gene. Nested PCR primer was deigned to target previously reported regions which are frequently occurred ITD mutation. PCR reactions of two steps were performed using the PCR primers sequentially. In these 83 patients, FLT3-ITD was positive only in 7 patients when tested by conventional PCR methods. When NGS detection method was applied, this resulted in positive FLT3-ITD in 11 patients (11/83, 13%). When validation was performed using nested PCR, FLT3-ITD was confirmed in all of 11 patients. Nested PCR detected additional 4 patient positive for FLT3-ITD in this population. For 68 patients, FLT3-ITD was negative by both NGS and nested PCR method. Overall, NGS method improved sensitivity of FLT3-ITD detection by 57% in this population. And the concordance rate of NGS method and nested PCR was 95.2% (79/83). Then we investigated clinical significance of sensitive FLT3-ITD detection. For this, we performed nested PCR and conventional PCR at the same time in 238 AML patients to detect FLT3-ITD. Positive rate for FLT3-ITD was 20% (48/238) and 10% (24/238) by nested PCR and conventional PCR respectively. When survival analysis was performed, among patients with negative FLT3-ITD result by conventional PCR, patients who showed positive for FLT3-ITD by nested PCR had shorter overall survival compared to those who showed negative for FLT3-ITD by nested PCR. (p = 0.03). This implies that sensitive FLT3-ITD detection using nested PCR is clinically meaningful. Diagnosis of FLT3-ITD is very important genetic factor, leading a therapeutic direction for AML patient. Here we report that we have developed alternative more sensitive detection methods for FLT3-ITD based on nested PCR and NGS. Sensitive detection of FLT3-ITD was clinically meaningful, suggesting that these methods should be incorporated in a future clinical practice. Also, we want to note that, NGS method is capable of quantifying FLT3-ITD size and amount in AML patients. Citation Format: Daeyoon Kim, Yoojin Hong, Youngil Koh, Sung-Soo Yoon, Choong-Hyun Sun, Kwang-Sung Ahn, Seungmook Lee, Hongseok Yun, Suyeon Lee. Improved sensitive detection method of FLT3 (FMS-like tyrosine kinase) internal tandem duplication (ITD) mutation using next-generation sequencing technology and nested PCR. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3186.

Objective To discuss the relationship between human leukocyte antigen (HLA) gene heredity and morbidity of cerebral infarction by a random survey on the allele expression of HLA-A, B and DRB1 seats of patients with cerebral infarction. Methods The genotypes of HLA-A, B and DRB1 alleles in 94 patients with cerebral infarction and 122 healthy blood donors were detected by polymerase chain reaction-sequencing based typing (PCR-SBT) method. Results Sixteen alleles in HLA -A locus,32 alleles in HLA -B locus and 25 alleles in HLA -DRB1 locus expressed themselves in these patients with cerebral infarction. The gene frequency of HLA -A*1102 in patients was lower than that in healthy controls, and negative association was found between HLA -A* 1102 allele and cerebral infarction (RR=0.06,P=0.019). Conclusion The research reveals susceptibility association of HLA -A*1102 with patients having cerebral infarction, displaying close genetic immunity correlation between HLA alleles and pathogenesis of cerebral infarction. So, the research in this paper is useful in the clinical prediction of this disease. Key words: Cerebral infarction; Human leukocyte antigen; Allele

Next generation sequencing and its application in deciphering head and neck cancer

Introduction: Next-generation sequencing (NGS) has become a critical diagnostic assay to identify pathologic SNVs, CNVs, and gene rearrangements. However, it has not been routinely used to assess expression levels of target genes that could indicate patient populations responsive to therapeutics. This is largely due to the absence of reliable bioinformatics tools for the assessment of expression levels within RNA assays. We have developed a novel within-sample distribution-based method that assesses the relative extremity of expression for individual genes. Our predominate focus has been on assessing the expression of NTRK1, NTRK2, NTRK3, ROS1, and ALK, however this method can be readily applied to other genes and NGS platforms. Methods: Within the kinase domain, the expression of a targeted region is represented by the number of unique deduplicated reads for NGS studies and normalized probe expression values (based on spike-in controls) for NanoString studies. A Poisson distribution is used to represent primer expression with the parameters estimated via maximum likelihood. The interquartile range (IQR) of the entirety of the sample's read counts is calculated and only those that do not exceed the third quartile bound by more than 150% of the IQR are considered during parameter estimation. A probability is then assigned to each of the primers based on their read counts. A geometric mean of the individual primer probabilities represents the probability value for the entire gene. Expression values are reported as -log10 (p-value) and cutoffs of 6 and 1 were used to call significant expression for NGS and NanoString platforms, respectively. Results: The NGS-based approach correctly identified significant expression in all gene rearrangement positive cell lines (n = 11). In cell lines not harboring gene rearrangements, the NGS and NanoString platforms showed 100% concordance in calling significant expression (n = 12). In a gene rearrangement negative FFPE cohort, concordance between NGS and NanoString platforms was 97%-99% for target genes (n = 102). ROS1 and ALK were most commonly found to be significantly expressed in FFPE samples (5% and 2%). Conclusions: We have developed a statistical-based approach to detecting expression levels for RNA-based NGS assays. This can be applied to cohort studies to not only identify clinical samples that may benefit from targeted kinase inhibitor therapeutics but also correlate with predicted outcome of disease. Citation Format: Robert Shoemaker, Aaron Berlin, Amy Diliberto, Heather Ely, Marissa Chen, Danielle Murphy, Jason Christiansen, Vince Reuter, Abel Licon. A novel, statistical-based method to determine RNA expression by next-generation sequencing in clinical FFPE samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5274.

Schizophrenia is thought to be the most prevalent chronic psychiatric disorder. Researchers have identified numerous proteins associated with the occurrence and development of schizophrenia. This study aimed to identify potential core genes and pathways involved in schizophrenia through exhaustive bioinformatics and next generation sequencing (NGS) data analyses using GSE106589 NGS data of neural progenitor cells and neurons obtained from healthy controls and patients with schizophrenia. The NGS data were downloaded from the Gene Expression Omnibus database. NGS data was processed by the DESeq2 package in R software, and the differentially expressed genes (DEGs) were identified. Gene ontology (GO) enrichment analysis and REACTOME pathway enrichment analysis were carried out to identify potential biological functions and pathways of the DEGs. Protein-protein interaction network, module, micro-RNA (miRNA)-hub gene regulatory network, transcription factor (TF)-hub gene regulatory network, and drug-hub gene interaction network analysis were performed to identify the hub genes, miRNA, TFs, and drug molecules. Potential hub genes were analyzed using receiver operating characteristic curves in the R package. In this investigation, an overall 955 DEGs were identified: 478 genes were remarkably upregulated and 477 genes were distinctly downregulated. These genes were enriched for GO terms and pathways mainly involved in the multicellular organismal process, G protein-coupled receptor ligand binding, regulation of cellular processes, and amine ligand-binding receptors. MYC, FN1, CDKN2A, EEF1G, CAV1, ONECUT1, SYK, MAPK13, TFAP2A, and BTK were considered the potential hub genes. The MiRNA-hub gene regulatory network, TF-hub gene regulatory network, and drug-hub gene interaction network were constructed successfully and predicted key miRNAs, TFs, and drug molecules for schizophrenia diagnosis and treatment. On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of schizophrenia and provide potential targets for further investigation.

A stand-alone BLAST server is available that provides a convenient and amenable platform for the analysis of molluscan sequence information especially the EST sequences generated by traditional sequencing methods. However, it is found that the server has limitations in the annotation of molluscan sequences generated using next-generation sequencing (NGS) platforms due to inconsistencies in molluscan sequence available at NCBI. We constructed a web-based interface for a new stand-alone BLAST, called PANM-DB (Protostome DB) for the analysis of molluscan NGS data. The PANM-DB includes the amino acid sequences from the protostome groups-Arthropoda, Nematoda, and Mollusca downloaded from GenBank with the NCBI taxonomy Browser. The sequences were translated into multi-FASTA format and stored in the database by using the formatdb program at NCBI. PANM-DB contains 6% of NCBInr database sequences (as of 24-06-2015), and for an input of 10,000 RNA-seq sequences the processing speed was 15 times faster by using PANM-DB when compared with NCBInr DB. It was also noted that PANM-DB show two times more significant hits with diverse annotation profiles as compared with Mollusks DB. Hence, the construction of PANM-DB is a significant step in the annotation of molluscan sequence information obtained from NGS platforms. The PANM-DB is freely downloadable from the web-based interface (Malacological Society of Korea, http://malacol.or/kr/blast) as compressed file system and can run on any compatible operating system.

The human leukocyte antigen (HLA) system comprises the most polymorphic genes of the human genome and is famous for its potential pathological roles. To accurately type HLA genes and find HLA-matched donors, which are critical for effective hematopoietic transplantation, HLA typing using next-generation sequencing (NGS) was implemented. We aimed to share the experience of HLA typing using NGS in patients with hematologic malignancies and evaluate its association with hematologic diseases. Data from 211 Korean, non-familial patients diagnosed with a hematologic disease were reviewed, and NGS was performed for 11 HLA loci. Three-field HLA typing with G code was successfully achieved for all loci and the known linkage between HLA-DRB3/4/5 and HLA-DRB1 was fully matched. Therefore, NGS-based HLA typing enables a detailed, high-resolution analysis of the HLA system that can help with the selection of suitable donors. Notably, HLA-DRB1*08:02:01G was significantly associated with myelodysplastic syndrome. Although this result confirms the tendency of some alleles to be associated with hematological disorders, this may not be the case in hematologic malignancies. Nonetheless, NGS-based HLA typing data for HLA-DP, HLA-DQ, and HLA-DRB3/4/5 are still warranted for a better understanding of the corresponding locus.

Leveraging The Old With The New: Exploring and Integrating Historic Microarray Studies With Next Generation Sequencing For Multiple Myeloma

Motivation. The third generation sequencing (3GS) technology generates long sequences of thousands of bases. However, its current error rates are estimated in the range of 15–40%, significantly higher than those of the prevalent next generation sequencing (NGS) technologies (less than 1%). Fundamental bioinformatics tasks such as de novo genome assembly and variant calling require high-quality sequences that need to be extracted from these long but erroneous 3GS sequences.Results. We describe a versatile and efficient linear complexity consensus algorithm Sparc to facilitate de novo genome assembly. Sparc builds a sparse k-mer graph using a collection of sequences from a targeted genomic region. The heaviest path which approximates the most likely genome sequence is searched through a sparsity-induced reweighted graph as the consensus sequence. Sparc supports using NGS and 3GS data together, which leads to significant improvements in both cost efficiency and computational efficiency. Experiments with Sparc show that our algorithm can efficiently provide high-quality consensus sequences using both PacBio and Oxford Nanopore sequencing technologies. With only 30× PacBio data, Sparc can reach a consensus with error rate <0.5%. With the more challenging Oxford Nanopore data, Sparc can also achieve similar error rate when combined with NGS data. Compared with the existing approaches, Sparc calculates the consensus with higher accuracy, and uses approximately 80% less memory and time.Availability. The source code is available for download at https://github.com/yechengxi/Sparc.

e23528 Background: The rarity and heterogeneity of sarcoma has been complicating the diagnosis of sarcoma for years. Even expert pathologists of sarcoma could make mistakes in the diagnosis of this disease. The availability of Next Generation Sequencing (NGS) data enabled more accurate diagnosis of sarcoma. In this study, we systematically described the application of NGS on the diagnosis of sarcoma and the contribution of NGS to the diagnostic accuracy of sarcoma. Methods: A multi-center, retrospective study included 235 sarcoma patients’ tumor and paired normal samples that were sent from 56 hospitals to a College of American Pathologists (CAP) accredited and Clinical Laboratory Improvement Amendments (CLIA) certified laboratory, at Shanghai, China for Next Generation Sequencing (NGS) was performed. Using next generation sequencing based YS panel consisting 450 genes, these 235 sarcoma patients’ sample were sequenced and the NGS data was analyzed. The initial diagnosis without NGS information was reconsidered by expert pathologists. Results: Taking into consideration both the initial diagnosis and the NGS results, the final diagnosis of these 235 sarcoma cases included 8 low grade malignant fibromyxoid tumors, 11 dermatofibrosarcoma protuberans (DFSP), 38 myxoliposarcomas, 22 alveolar rhabdomyosarcomas, 11 alveolar soft tissue sarcoma, 2 desmoplastic small round cell tumors, 37 NTRK rearrangement spindle cell tumors, 40 Ewing’s sarcoma and 66 synoviosarcomas. In total, 29% initial diagnoses were changed according to NGS identified fusions, including 13% low grade malignant fibromyxoid tumors (1 FUS- CREB3L2 fusion), 27% DFSPs (3 COL1A1- PDGFB fusions), 11% myxoliposarcomas (3 FUS- DDIT3 fusions and 1 EWSR1- DDIT3 fusion), 14% alveolar rhabdomyosarcomas (2 PAX7- FOXO1 fusions and 1 FOXO1- LINC00598 fusion), 18% alveolar soft tissue sarcomas (2 ASPSCR1- TFE3 fusions), 50% desmoplastic small round cell tumor (1 EWSR1- WT1 fusion), 95% NTRK rearrangement spindle cell tumors, 13% Ewing’s sarcomas (3 EWSR1- FLI1 fusions and 2 EWSR1- ERG fusions) and 21% synoviosarcomas (9 SS18- SSX1 fusions and 5 SS18- SSX2 fusions). Conclusions: NGS would be highly recommended for accurate diagnosis of sarcoma, especially for NTRK rearrangement spindle cell tumor, the majority of which were confirmed according to NGS identified fusions.