A novel approach for HLA-A typing in formalin-fixed paraffin-embedded-derived DNA

Villabona, Lisa; Rodríguez, Daniel Salazar; Andersson, Emilia; Seliger, Barbara; Dalianis, Tina; Masucci, Giuseppe

doi:10.1038/modpathol.2013.210

Cited by 5 publications

(16 citation statements)

References 22 publications

(31 reference statements)

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“…As at times, HLA alleles only vary at the singlenucleotide level, some changes brought about by FFPE processing, such as DNA fragmentation or the presence of nucleotide changes, might have contributed to the lower sequencing accuracy in this sample type. A previous study demonstrated the amplification of exons 2, 3, and 4 of HLA-A in only 88% (14/16) from DNA isolated from 10-year-old FFPE tissue samples (36). Among the 5 algorithms included in our study, the performance of HLA-HD was consistent for the WBC, plasma, and tissue samples, which were highly concordant with the SBTbased HLA genotype.…”

Section: Ngs Typically Generates Short Read Lengths (Betweensupporting

confidence: 73%

Benchmarking of 5 algorithms for high-resolution genotyping of human leukocyte antigen class I genes from blood and tissue samples

Hua¹,

Sun²,

Zhao³

et al. 2022

Ann Transl Med

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Background: Specific alterations in human leukocyte antigen class I (HLA-I) loci are associated with clinical outcomes for immune checkpoint inhibitors, which increase the clinical relevance of accurate highresolution HLA genotyping in immuno-oncology applications. Numerous algorithms have been developedfor high-to full-resolution HLA genotyping by next-generation sequencing (NGS) data; however, Sanger sequencing-based typing (SBT) remains the gold standard. With the increasing use of NGS for clinical oncology, it is important to identify the computational tool with comparable performance as the gold standard. This study aimed to benchmark 5 algorithms against SBT for the high-resolution typing of classical HLA-I genes for targeted NGS data from blood and tissue samples.Methods: Paired white blood cell (WBC), plasma, and tissue deoxyribonucleic acid (DNA) samples derived from 22 cancer patients with known HLA genotypes were sequenced using a panel of all the following exons of classical HLA-I genes: HLA-A, HLA-B, and HLA-C. NGS-based genotypes were generated by the 5 different algorithms, including HLA-HD, HLAscan, OptiType, Polysolver, and xHLA. Accuracy was defined as the concordance between the SBT and NGS-based algorithms. Accuracy was computed as the fraction of all the alleles with concordant genotype using the SBT and any of the algorithm over the total number of alleles. Results:In relation to the WBC, plasma, and tissue samples, all 5 algorithms were highly accurate at low-resolution HLA-I genotyping, but had more varied accuracy at high-resolution HLA-I genotyping, particularly in HLA-A. The in-silico analyses revealed that high-resolution genotyping by all 5 algorithms achieved approximately 90% accuracy at sequencing depths of 6,000× -100× for the WBC samples, at 6,000× -700× for the plasma samples, and at 1,000× -100× for the tissue samples. Among the 5 algorithms, HLA-HD was consistently accurate at high-resolution HLA-I genotyping, and had an accuracy of 93.9% for the WBC samples, 87.9% for the plasma samples, and 94.2% for tissue samples even at a 50× sequencing depth. Conclusions:We found that HLA-HD was an accurate algorithm for the high-resolution genotyping of classical HLA-I genes sequenced by our targeted panel, particularly at a sequencing depth ≥300× for blood and tissue samples.

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Section: Ngs Typically Generates Short Read Lengths (Betweensupporting

confidence: 73%

Benchmarking of 5 algorithms for high-resolution genotyping of human leukocyte antigen class I genes from blood and tissue samples

Hua¹,

Sun²,

Zhao³

et al. 2022

Ann Transl Med

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“…For amplification, the following oligonucleotide primers were designed according to a protocol published in ref. 41 : A2-2F: 5′-TCTCAGCCACTCCTCGTC-3′, G-R: 5′-TGTCGAACCGCACGAACTG-3′. After amplification according to ref.…”

Section: Methodsmentioning

confidence: 99%

“…After amplification according to ref. 41 , Sanger sequencing was performed, and the nucleotide at nucleotide position 78 of the HLA-A gene locus (reference sequence NM_001242758.1) was used for classification, GCTC Y CACT with T indicating HLA-A*02:01 and C indicating non-HLA-A*02:01. The method was successfully validated in independent specimens with known HLA type.…”

Section: Methodsmentioning

confidence: 99%

“…In order to specifically address HLA-type dependence of immunoediting, HLA-A*02:01 status was determined in MSI CRC and EC 40,41 . HLA-A*02:01 was present in 34 (47.9%) of 71 MSI CRC and 13 (47.1%) of 27 MSI EC samples, in line with proportions reported for German populations (prevalence of HLA-A*02:01: 46.2%, n = 39,689, www.allelefrequencies.net).…”

Section: And Supplementary Data 2)mentioning

confidence: 99%

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The shared frameshift mutation landscape of microsatellite-unstable cancers suggests immunoediting during tumor evolution

et al. 2020

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The immune system can recognize and attack cancer cells, especially those with a high load of mutation-induced neoantigens. Such neoantigens are abundant in DNA mismatch repair (MMR)-deficient, microsatellite-unstable (MSI) cancers. MMR deficiency leads to insertion/deletion (indel) mutations at coding microsatellites (cMS) and to neoantigen-inducing translational frameshifts. Here, we develop a tool to quantify frameshift mutations in MSI colorectal and endometrial cancer. Our results show that frameshift mutation frequency is negatively correlated to the predicted immunogenicity of the resulting peptides, suggesting counterselection of cell clones with highly immunogenic frameshift peptides. This correlation is absent in tumors with Beta-2-microglobulin mutations, and HLA-A*02:01 status is related to cMS mutation patterns. Importantly, certain outlier mutations are common in MSI cancers despite being related to frameshift peptides with functionally confirmed immunogenicity, suggesting a possible driver role during MSI tumor evolution. Neoantigens resulting from shared mutations represent promising vaccine candidates for prevention of MSI cancers.

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“…The product of the cDNA synthesis was subsequently taken for a SYBR-Green based qPCR, as previously described by Lindquist et al (9). The following genes were examined: HPV16 E5, E7, with primers as described in Ramqvist et al (29) and HLA-A for exon 3 with primers as described by Villabona et al (30). GUS B was added as an endogenous control.…”

Section: Flow Cytometry For Evaluation Of Hla Class I Expression Celmentioning

confidence: 99%

Effects of irradiation on human leukocyte antigen class I expression in human papillomavirus positive and negative base of tongue and mobile tongue squamous cell carcinoma cell lines

Haeggblom

Nordfors

Tertipis

et al. 2017

International Journal of Oncology

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Human papillomavirus (HPV) infection is a risk factor for oropharyngeal cancer, besides smoking and alcohol. Patients with HPV-positive tumors have a better prognosis than those with HPV-negative tumors. Furthermore, patients with HPV-positive tumors, with high CD8+ tumor infiltrating lymphocyte counts or absent/low human leukocyte antigen (HLA) class I expression have the best outcome. The latter is paradoxical, since HLA class I expression is important for tumor recognition. Below, the hypothesis that radiation therapy increases HLA class I expression was tested. HPV16 positive head and neck cancer cell lines UPCI-SCC-154, UPCI-SCC-090 and UM-SCC-47, and the HPV-negative cancer cell line UT-SCC-14, were treated with 2-10 Gray (Gy) and tested for HLA class I expression, cell cycle changes and apoptosis by flow cytometry. HPV16 E5, E7 and HLA-A mRNA expression was tested by quantitative PCR. A dose of 10 Gy resulted in a tendency of increased HLA class I cell surface expression for all cell lines and reached statistical significance for UPCI-SCC-154 and UPCI-SCC-090. There were, however, no significant changes in HLA-A mRNA expression in any of the cell lines, or HPV16 E5, or E7 mRNA expression for UPCI-SCC-47 and UPCI-SCC-154, while for UPCI-SCC-090 HPV16 E5 mRNA decreased. In all cell lines there was a shift towards G2/M phase and increased apoptosis after irradiation with 10 Gy. To conclude, irradiation with 10 Gy increased HLA class I expression in the HPV-positive cell lines UPCI-SCC-154 and UPCI-SCC-090. A similar tendency was observed for HPV-positive UM-SCC-47 and HPV-negative UT-SCC-14.

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A novel approach for HLA-A typing in formalin-fixed paraffin-embedded-derived DNA

Cited by 5 publications

References 22 publications

Benchmarking of 5 algorithms for high-resolution genotyping of human leukocyte antigen class I genes from blood and tissue samples

Benchmarking of 5 algorithms for high-resolution genotyping of human leukocyte antigen class I genes from blood and tissue samples

The shared frameshift mutation landscape of microsatellite-unstable cancers suggests immunoediting during tumor evolution

Effects of irradiation on human leukocyte antigen class I expression in human papillomavirus positive and negative base of tongue and mobile tongue squamous cell carcinoma cell lines

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