In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines

Over 30 years after the first cancer vaccine clinical trial (CT), scientists still search the missing link between immunogenicity and clinical responses. A predictor able to estimate the outcome of cancer vaccine CTs would greatly benefit vaccine development. Published results of 94 CTs with 64 ther...

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Autores principales:	Orsolya Lőrincz, József Tóth, Levente Molnár, István Miklós, Kata Pántya, Mónika Megyesi, Eszter Somogyi, Zsolt Csiszovszki, Enikő R. Tőke
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	cancer vaccine HLA genotype in silico trial immune response rate clinical response rate Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/08b4225fb7a54e868665dfbd637a2052
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spelling	oai:doaj.org-article:08b4225fb7a54e868665dfbd637a20522021-11-25T17:10:47ZIn Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines10.3390/cells101130482073-4409https://doaj.org/article/08b4225fb7a54e868665dfbd637a20522021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4409/10/11/3048https://doaj.org/toc/2073-4409Over 30 years after the first cancer vaccine clinical trial (CT), scientists still search the missing link between immunogenicity and clinical responses. A predictor able to estimate the outcome of cancer vaccine CTs would greatly benefit vaccine development. Published results of 94 CTs with 64 therapeutic vaccines were collected. We found that preselection of CT subjects based on a single matching HLA allele does not increase immune response rates (IRR) compared with non-preselected CTs (median 60% vs. 57%, <i>p</i> = 0.4490). A representative in silico model population (MP) comprising HLA-genotyped subjects was used to retrospectively calculate in silico IRRs of CTs based on the percentage of MP-subjects having epitope(s) predicted to bind ≥ 1–4 autologous HLA allele(s). We found that in vitro measured IRRs correlated with the frequency of predicted multiple autologous allele-binding epitopes (AUC 0.63–0.79). Subgroup analysis of multi-antigen targeting vaccine CTs revealed correlation between clinical response rates (CRRs) and predicted multi-epitope IRRs when HLA threshold was ≥ 3 (<i>r</i> = 0.7463, <i>p</i> = 0.0004) but not for single HLA allele-binding epitopes (<i>r</i> = 0.2865, <i>p</i> = 0.2491). Our results suggest that CRR depends on the induction of broad T-cell responses and both IRR and CRR can be predicted when epitopes binding to multiple autologous HLAs are considered.Orsolya LőrinczJózsef TóthLevente MolnárIstván MiklósKata PántyaMónika MegyesiEszter SomogyiZsolt CsiszovszkiEnikő R. TőkeMDPI AGarticlecancer vaccineHLA genotypein silico trialimmune response rateclinical response rateBiology (General)QH301-705.5ENCells, Vol 10, Iss 3048, p 3048 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cancer vaccine HLA genotype in silico trial immune response rate clinical response rate Biology (General) QH301-705.5
spellingShingle	cancer vaccine HLA genotype in silico trial immune response rate clinical response rate Biology (General) QH301-705.5 Orsolya Lőrincz József Tóth Levente Molnár István Miklós Kata Pántya Mónika Megyesi Eszter Somogyi Zsolt Csiszovszki Enikő R. Tőke In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines
description	Over 30 years after the first cancer vaccine clinical trial (CT), scientists still search the missing link between immunogenicity and clinical responses. A predictor able to estimate the outcome of cancer vaccine CTs would greatly benefit vaccine development. Published results of 94 CTs with 64 therapeutic vaccines were collected. We found that preselection of CT subjects based on a single matching HLA allele does not increase immune response rates (IRR) compared with non-preselected CTs (median 60% vs. 57%, <i>p</i> = 0.4490). A representative in silico model population (MP) comprising HLA-genotyped subjects was used to retrospectively calculate in silico IRRs of CTs based on the percentage of MP-subjects having epitope(s) predicted to bind ≥ 1–4 autologous HLA allele(s). We found that in vitro measured IRRs correlated with the frequency of predicted multiple autologous allele-binding epitopes (AUC 0.63–0.79). Subgroup analysis of multi-antigen targeting vaccine CTs revealed correlation between clinical response rates (CRRs) and predicted multi-epitope IRRs when HLA threshold was ≥ 3 (<i>r</i> = 0.7463, <i>p</i> = 0.0004) but not for single HLA allele-binding epitopes (<i>r</i> = 0.2865, <i>p</i> = 0.2491). Our results suggest that CRR depends on the induction of broad T-cell responses and both IRR and CRR can be predicted when epitopes binding to multiple autologous HLAs are considered.
format	article
author	Orsolya Lőrincz József Tóth Levente Molnár István Miklós Kata Pántya Mónika Megyesi Eszter Somogyi Zsolt Csiszovszki Enikő R. Tőke
author_facet	Orsolya Lőrincz József Tóth Levente Molnár István Miklós Kata Pántya Mónika Megyesi Eszter Somogyi Zsolt Csiszovszki Enikő R. Tőke
author_sort	Orsolya Lőrincz
title	In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines
title_short	In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines
title_full	In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines
title_fullStr	In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines
title_full_unstemmed	In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines
title_sort	in silico model estimates the clinical trial outcome of cancer vaccines
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/08b4225fb7a54e868665dfbd637a2052
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In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines

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