Abstracts / Human Immunology 75 (2014) 50–141
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LIS ON A SHOESTRING. Nebila Abdulwahab, Patrick Adams, Nicholas R. DiPaola. The Ohio State University, Columbus, OH, United States. Aim: As laboratories are continuing to be cost conscious and at the same time maintain the highest level of information management, a dilemma often comes up as to whether to invest in IT infrastructure or testing technology. Our lab faced the same dilemma several years ago. After trying without much success to get more IT support, we decided to build our own LIS. Method: We used Microsoft Access which allowed for the development of tables which could be queried between many users. Multiple forms were designed unique to each area of the lab and each testing platform. A master set of queries were designed to monitor all quality metrics (e.g. turnaround times, repeat testing, reporting errors, etc.), and testing volumes used for both internal prediction of program growth and external reporting (Medicare Cost Reports). Results: Time spent for reporting growth of our program went from days to hours. We are able to directly send out HLA report through secure mail which reduced paper usage. There was significant reduction in transcriptional errors. We were able to quickly identify HLA types of given characteristics, normal values for our cross matches, even a basic PRA for DP within our population at OSU. The greatest benefit was the ability to add functionality whenever needed without going to anlis o outside vendor. Conclusion: Though not for all labs, writing one’s own LIS can have many benefits. The OSU package handles our volume quite well and should be exportable on any Windows 7 system.
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HLA TYPING VALIDATION BY NEXT GENERATION SEQUENCING (NGS). Ketevan Gendzekhadze 1, Lan-Feng Cao 1, Nelson Wyatt 2, Jean Garcia-Gomez 1, Daniel Geraghty 2, David Senitzer 1. 1 City of Hope, Duarte, CA, United States; 2 Scisco Genetics, Seattle, WA, United States. HLA allele-level typing is mandatory for HCT patients and potential donors. Amplicon based Sanger sequencing is unable to detect HLA haplotypes with known gametic phase, resulting in various ambiguous combinations of several possible HLA genotypes. Resolution of these ambiguous combinations can only be done using, PCR-SSP or PCR-SSO, both of which are expensive and time consuming. NGS technology can process multiple samples, and allele assignment should be relatively simple and should decrease resolve ambiguous genotypes. Our laboratory routinely sequences approximately 100 samples per month for HLA-A, B, C, DRB1, DQB1 and DPB1. We validated the usefulness of NGS to resolve ambiguities and reduce the need for SSP and/or SSO. Commercially available KITs (Scisco Genetics) were used to analyze 110 samples with known HLA genotypes. We amplified exons 2, 3, and 4 of HLA Class I genes and exons 2 and 3 of HLA Class II genes. Phase between exons 2 and 3 for Class I were established by sequencing directly, while the sequences of the Class II exons were established by comparison with the IMGT HLA data base. Allele assignments were made using software developed by Scisco Genetics. We observed 100% concordance for HLA class II alleles, and 92% for Class I alleles. All discrepancies for Class I were due to failure to correctly assign one allele, but not the second allele (different from homozygotes). NGS was able to detect several recently identified HLA alleles, e.g. A⁄02:139 and C⁄04:119. Allele assignment was simplified and fast, but set up was the most laborious and time consuming. However, we are sure that liquid handling robots (Texas BioGene Inc) will be able to automate the pre-PCR and post-PCR steps. KIT can be used to detects HLA genes: such as HLA-DPA1, HLA-DQA1, or HLADRB3,4,5. We are in process of validating more samples, and changing our HLA class I protocol to achieve 100% concordance. We anticipate sharp declines in the need for PCR-SSP and PCR-SSO testing. The benefit of NGS for high resolution HLA typing should be significantly decreased costs, and shortened turnaround times. N. Wyatt: Employee; Company/Organization; Scisco Genetics. Stock Shareholder; Company/Organization; Scisco Genetics. D. Geraghty: Employee; Company/Organization; Scisco Genetics. Stock Shareholder; Company/Organization; Scisco Genetics.
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