Six-locus high resolution HLA haplotype frequencies derived from mixed-resolution DNA typing for the entire US donor registry

Gragert, Loren; Madbouly, Abeer; Freeman, John L.; Maiers, Martin

doi:10.1016/j.humimm.2013.06.025

Cited by 335 publications

(452 citation statements)

References 23 publications

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“…The haplotype HLA-A*01:01-C*07:01-B*08:01-DRB3*01:01-DRB1*03:01-DQA1*05:01-DQB1*02:01 was the most frequent, with 70% (50/71) of the confirmed FNAIT cases carrying it or part of it (including at least all the class II alleles). The frequency of this haplotype (or part of it) is 9% in Caucasoids with European background (Gragert et al, 2013). The next frequent (25%, 18/71) haplotype in this study population was DRB3*01:01-DRB1*13:01-DQA1*01:03-DQB1*06:03 including only HLA class II loci; this haplotype frequency is 3% in Caucasoids.…”

Section: Hla Haplotype Analysismentioning

confidence: 52%

Maternal HLA genotyping is not useful for predicting severity of fetal and neonatal alloimmune thrombocytopenia

et al. 2016

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SummaryLack of reliable laboratory parameters is the main challenge in the management of fetal and neonatal alloimmune thrombocytopenia (FNAIT). Despite the long-known association between the HLA-DRB3*01:01 allele and human platelet antigen 1a (HPA-1a) alloimmunisation, maternal human leucocyte antigen (HLA) typing has been of little clinical value. Recently, other DRB3 allele variants have been suggested to predict the severity of FNAIT. In this nationwide population-based retrospective cohort study, we performed extensive HLA typing of 96 women, accounting for 87% of our cohort of 110 families with confirmed or possible HPA-1a-immunisation. The HLA type was compared with anti-HPA-1a levels, severity of neonatal disease and responsiveness to maternally administrated intravenous gammaglobulin (IVIG). HLA haplotypes were constructed to investigate further HLA associations. Despite significantly lower anti-HPA-1a levels in DRB3*01:01-negative women, the carrier status of this particular allele could not be used to confirm or rule out FNAIT in the absence of detectable antibodies. In the haplotype analysis, the DRB3*01:01 allele was the actual factor associated with FNAIT. No other HLA allele was shown to be of additional value as a predictor of severe FNAIT or non-responsiveness to IVIG treatment. Thus, HLA genotyping was not found useful in differentiating high-and low-risk pregnancies or in guiding antenatal treatment in affected families.

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Section: Hla Haplotype Analysismentioning

confidence: 52%

Maternal HLA genotyping is not useful for predicting severity of fetal and neonatal alloimmune thrombocytopenia

et al. 2016

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“…35 RAVEN automatically crosschecked these peptides by a text search algorithm with ApacheLucene 36,37 against the human reference-proteome (UniProt release 2015_06) to exclude sequence identity with non-specifically expressed proteins. In total, RAVEN predicted 7247 9-mer peptides with high MHC-I-affinity (defined as a dissociation constant K d ≤ 150 nM) of which 6589 had no sequence identity with any other protein (Supplementary Table 6).…”

Section: Resultsmentioning

confidence: 99%

Systematic identification of cancer-specific MHC-binding peptides with RAVEN

Baldauf¹,

Gerke²,

Kirschner

et al. 2018

OncoImmunology

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Immunotherapy can revolutionize anti-cancer therapy if specific targets are available. Immunogenic peptides encoded by cancer-specific genes (CSGs) may enable targeted immunotherapy, even of oligo-mutated cancers, which lack neo-antigens generated by protein-coding missense mutations. Here, we describe an algorithm and user-friendly software named RAVEN (Rich Analysis of Variable gene Expressions in Numerous tissues) that automatizes the systematic and fast identification of CSG-encoded peptides highly affine to Major Histocompatibility Complexes (MHC) starting from transcriptome data. We applied RAVEN to a dataset assembled from 2,678 simultaneously normalized gene expression microarrays comprising 50 tumor entities, with a focus on oligo-mutated pediatric cancers, and 71 normal tissue types. RAVEN performed a transcriptome-wide scan in each cancer entity for gender-specific CSGs, and identified several established CSGs, but also many novel candidates potentially suitable for targeting multiple cancer types. The specific expression of the most promising CSGs was validated in cancer cell lines and in a comprehensive tissue-microarray. Subsequently, RAVEN identified likely immunogenic CSG-encoded peptides by predicting their affinity to MHCs and excluded sequence identity to abundantly expressed proteins by interrogating the UniProt protein-database. The predicted affinity of selected peptides was validated in T2-cell peptide-binding assays in which many showed binding-kinetics like a very immunogenic influenza control peptide. Collectively, we provide an exquisitely curated catalogue of cancer-specific and highly MHC-affine peptides across 50 cancer types, and a freely available software (https://github.com/JSGerke/RAVENsoftware) to easily apply our algorithm to any gene expression dataset. We anticipate that our peptide libraries and software constitute a rich resource to advance anti-cancer immunotherapy.

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“…As far as we know, this paper is the first benefit cost analysis that considers the adult registry and the cord blood bank as a simultaneous allocation problem, taking account of substitutability between these resources. It is also the first to account for international exchanges of stem cell material and it is the first benefit-cost study to use the most recently available and highly detailed estimates of the frequencies of immunity type data, which were published by Gragert et al (2013) 3…”

Section: Related Researchmentioning

confidence: 99%

“…Since these studies were published, the med-ical profession has concluded that matching at a more finely partitioned level is advantageous, and a new data source that presents estimates of the distribution according to this more detailed partition has become available (Gragert et al, 2013). Our benefit cost analysis is based on this new data source.…”

Section: Related Researchmentioning

confidence: 99%

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Saving lives with stem cell transplants

2015

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Blood stem cell transplants can be life-saving for some patients, but the chances of finding a matching donor are small unless a large number of potential donors are evaluated. Many nations maintain large registries of potential donors who have offered to donate stem cells if they are the best available match for a patient needing a transplant. An alternative source of stem cells, umbilical cord blood, is stored in banks. Everyone faces a small probability of needing a transplant which will increase their likelihood of survival. The registries and cord blood banks are thus an interesting example of a pure public good with widely dispersed benefits. This paper explores the gains in survival probability that arise from increased registry and bank sizes and uses value of statistical life methods to estimate benefits and compare them to costs. Our results suggest that for the United States and for the world as a whole, the sum of marginal benefits of an increase in either the adult registry or the cord blood bank exceeds marginal costs. However, marginal benefit-cost ratios for the adult registry are much greater than those for the cord blood banks, which suggests that to the extent that these two sources of life saving compete for public funds it may be preferable to prioritize expansion of the adult registry over cord blood banks.

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Six-locus high resolution HLA haplotype frequencies derived from mixed-resolution DNA typing for the entire US donor registry

Cited by 335 publications

References 23 publications

Maternal HLA genotyping is not useful for predicting severity of fetal and neonatal alloimmune thrombocytopenia

Maternal HLA genotyping is not useful for predicting severity of fetal and neonatal alloimmune thrombocytopenia

Systematic identification of cancer-specific MHC-binding peptides with RAVEN

Saving lives with stem cell transplants

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