B089:精准癌症免疫治疗设计工具在膀胱癌中的应用:非自我样新表位作为预后生物标志物

Guilhem Richard, R. Sweis, L. Moise, M. Ardito, W. Martin, Gad Berdugo, G. Steinberg, A. Groot
{"title":"B089:精准癌症免疫治疗设计工具在膀胱癌中的应用:非自我样新表位作为预后生物标志物","authors":"Guilhem Richard, R. Sweis, L. Moise, M. Ardito, W. Martin, Gad Berdugo, G. Steinberg, A. Groot","doi":"10.1158/2326-6074.CRICIMTEATIAACR18-B089","DOIUrl":null,"url":null,"abstract":"Precision cancer immunotherapy targeting mutations expressed by cancer cells has proven to effectively control the tumor of patients in multiple clinical trials (Sahin et al., Nature 2017; Ott et al., Nature 2017). However, the selection of immunogenic T-cell neo-epitopes remains challenging and many epitopes selected using traditional methodologies fail to induce effector T-cell responses. Poor performance may partially be due to inclusion of mutated epitopes cross-conserved with self-epitopes recognized by regulatory (Treg), anergic, or deleted T-cells. Vaccination with self-epitopes can lead to weak effector responses, active immune suppression, and toxicity due to immune-mediated adverse effects. In addition, most cancer vaccine studies focus on the selection of CD8 T-cell neo-epitopes due to an apparent lack of robust and accurate CD4 T-cell epitope prediction tools. We have developed Ancer, an integrated and streamlined neo-epitope selection pipeline, that accelerates the selection of both CD4 and CD8 T-cell neo-epitopes from next-generation sequencing (NGS) data. Ancer leverages EpiMatrix and JanusMatrix, predictive algorithms that have been extensively validated in prospective vaccine studies for infectious diseases (Moise et al., Hum Vaccines Immunother 2015; Wada et al., Sci Rep 2017). Distinctive features of Ancer are its ability to accurately predict Class II HLA ligands, or CD4 epitopes, with EpiMatrix, and to identify tolerated or Treg epitopes with JanusMatrix. In addition, screening candidate sequences with JanusMatrix enables to the removal of neo-epitopes that may trigger off-target events, which have in some cases abruptly halted the development of promising cancer therapies. Ancer was applied to NGS data derived from the BLCA bladder cancer cohort from The Cancer Genome Atlas (TCGA) database. On average, 55 out of 204 missense mutations in bladder cancer patients’ tumors met Ancer’s quality control standards, in an initial analysis carried out for a representative set of 11 patients. This subset of high-quality missense variants was then screened using Ancer settings defined by the unique HLA of each patient, to derive the best vaccine candidate sequences encompassing these mutations. A median number of 24 (interquartile range: 15-64) candidate sequences were generated for each patient under study. The time required to select sequences for all of the patients in this study was less than two days. This initial analysis of eleven BLCA bladder cancer cohort patients demonstrates the capacity of Ancer to define a sufficient number of candidate sequences for vaccinating bladder cancer patients in a precision immunotherapy setting. We also assessed Ancer’s ability to predict patient outcomes on a larger subset of 58 individuals. While the disease-free status of BLCA patients could not be explained by their tumor mutational burden (AUC = 0.55, p-value = 0.1328), nor by their load of missense mutations (AUC = 0.54, p-value = 0.1740), the number of neoepitopes highly different from self, as defined by Ancer, significantly segregated disease-free patients from patients who recurred or progressed (AUC = 0.68, p-value = 0.0214). These results suggest that defining the number of true neoepitopes using Ancer may represent a novel biomarker for more robust antitumor immune response and higher likelihood of disease-free survival.Our analysis of the BLCA cohort from the TCGA database showcases the value of Ancer in clinical settings. Ancer can be used to identify high-value candidate sequences for inclusion in personalized therapies while removing potentially tolerated or tolerogenic self-epitopes from consideration. Our next step will be to investigate whether Ancer-defined neoepitope load will serve as a biomarker for prognosis and response to therapy in the full BLCA cohort. Citation Format: Guilhem Richard, Randy F. Sweis, Leonard Moise, Matthew Ardito, William A. Martin, Gad Berdugo, Gary D. Steinberg, Anne S. De Groot. Application of precision cancer immunotherapy design tools to bladder cancer: Non-self-like neoepitopes as a prognostic biomarker [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B089.","PeriodicalId":433681,"journal":{"name":"Mutational Analysis and Predicting Response to Immunotherapy","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Abstract B089: Application of precision cancer immunotherapy design tools to bladder cancer: Non-self-like neoepitopes as a prognostic biomarker\",\"authors\":\"Guilhem Richard, R. Sweis, L. Moise, M. Ardito, W. Martin, Gad Berdugo, G. Steinberg, A. Groot\",\"doi\":\"10.1158/2326-6074.CRICIMTEATIAACR18-B089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Precision cancer immunotherapy targeting mutations expressed by cancer cells has proven to effectively control the tumor of patients in multiple clinical trials (Sahin et al., Nature 2017; Ott et al., Nature 2017). However, the selection of immunogenic T-cell neo-epitopes remains challenging and many epitopes selected using traditional methodologies fail to induce effector T-cell responses. Poor performance may partially be due to inclusion of mutated epitopes cross-conserved with self-epitopes recognized by regulatory (Treg), anergic, or deleted T-cells. Vaccination with self-epitopes can lead to weak effector responses, active immune suppression, and toxicity due to immune-mediated adverse effects. In addition, most cancer vaccine studies focus on the selection of CD8 T-cell neo-epitopes due to an apparent lack of robust and accurate CD4 T-cell epitope prediction tools. We have developed Ancer, an integrated and streamlined neo-epitope selection pipeline, that accelerates the selection of both CD4 and CD8 T-cell neo-epitopes from next-generation sequencing (NGS) data. Ancer leverages EpiMatrix and JanusMatrix, predictive algorithms that have been extensively validated in prospective vaccine studies for infectious diseases (Moise et al., Hum Vaccines Immunother 2015; Wada et al., Sci Rep 2017). Distinctive features of Ancer are its ability to accurately predict Class II HLA ligands, or CD4 epitopes, with EpiMatrix, and to identify tolerated or Treg epitopes with JanusMatrix. In addition, screening candidate sequences with JanusMatrix enables to the removal of neo-epitopes that may trigger off-target events, which have in some cases abruptly halted the development of promising cancer therapies. Ancer was applied to NGS data derived from the BLCA bladder cancer cohort from The Cancer Genome Atlas (TCGA) database. On average, 55 out of 204 missense mutations in bladder cancer patients’ tumors met Ancer’s quality control standards, in an initial analysis carried out for a representative set of 11 patients. This subset of high-quality missense variants was then screened using Ancer settings defined by the unique HLA of each patient, to derive the best vaccine candidate sequences encompassing these mutations. A median number of 24 (interquartile range: 15-64) candidate sequences were generated for each patient under study. The time required to select sequences for all of the patients in this study was less than two days. This initial analysis of eleven BLCA bladder cancer cohort patients demonstrates the capacity of Ancer to define a sufficient number of candidate sequences for vaccinating bladder cancer patients in a precision immunotherapy setting. We also assessed Ancer’s ability to predict patient outcomes on a larger subset of 58 individuals. While the disease-free status of BLCA patients could not be explained by their tumor mutational burden (AUC = 0.55, p-value = 0.1328), nor by their load of missense mutations (AUC = 0.54, p-value = 0.1740), the number of neoepitopes highly different from self, as defined by Ancer, significantly segregated disease-free patients from patients who recurred or progressed (AUC = 0.68, p-value = 0.0214). These results suggest that defining the number of true neoepitopes using Ancer may represent a novel biomarker for more robust antitumor immune response and higher likelihood of disease-free survival.Our analysis of the BLCA cohort from the TCGA database showcases the value of Ancer in clinical settings. Ancer can be used to identify high-value candidate sequences for inclusion in personalized therapies while removing potentially tolerated or tolerogenic self-epitopes from consideration. Our next step will be to investigate whether Ancer-defined neoepitope load will serve as a biomarker for prognosis and response to therapy in the full BLCA cohort. Citation Format: Guilhem Richard, Randy F. Sweis, Leonard Moise, Matthew Ardito, William A. Martin, Gad Berdugo, Gary D. Steinberg, Anne S. De Groot. Application of precision cancer immunotherapy design tools to bladder cancer: Non-self-like neoepitopes as a prognostic biomarker [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B089.\",\"PeriodicalId\":433681,\"journal\":{\"name\":\"Mutational Analysis and Predicting Response to Immunotherapy\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mutational Analysis and Predicting Response to Immunotherapy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B089\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mutational Analysis and Predicting Response to Immunotherapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1158/2326-6074.CRICIMTEATIAACR18-B089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

针对癌细胞表达突变的精准癌症免疫治疗在多个临床试验中被证明可以有效控制患者的肿瘤(Sahin et al., Nature 2017;Ott et al., Nature 2017)。然而,免疫原性t细胞新表位的选择仍然具有挑战性,使用传统方法选择的许多表位无法诱导效应t细胞反应。表现不佳的部分原因可能是包含突变的表位与调节性(Treg)、无能或缺失的t细胞识别的自我表位交叉保守。使用自身抗原表位的疫苗接种可导致弱效应反应、主动免疫抑制和由于免疫介导的不良反应而产生的毒性。此外,由于缺乏可靠和准确的CD4 t细胞表位预测工具,大多数癌症疫苗研究都集中在CD8 t细胞新表位的选择上。我们开发了一种集成的流线型新表位选择管道Ancer,可从下一代测序(NGS)数据中加速CD4和CD8 t细胞新表位的选择。Ancer利用EpiMatrix和JanusMatrix,这两种预测算法已在传染病的前瞻性疫苗研究中得到广泛验证(Moise等人,Hum Vaccines Immunother 2015;Wada et al., Sci Rep 2017)。Ancer的独特之处在于它能够使用epimmatrix准确预测II类HLA配体或CD4表位,并使用JanusMatrix识别耐受或Treg表位。此外,使用JanusMatrix筛选候选序列可以去除可能引发脱靶事件的新表位,这些事件在某些情况下会突然停止有希望的癌症治疗的发展。Ancer应用于来自癌症基因组图谱(TCGA)数据库中BLCA膀胱癌队列的NGS数据。在对11名具有代表性的患者进行的初步分析中,平均而言,膀胱癌患者肿瘤中204个错义突变中有55个符合Ancer的质量控制标准。然后使用每个患者独特的HLA定义的Ancer设置筛选高质量错义变体子集,以获得包含这些突变的最佳候选疫苗序列。为研究中的每个患者生成的候选序列中位数为24(四分位数范围:15-64)。在这项研究中,为所有患者选择序列所需的时间少于两天。这项对11名BLCA膀胱癌队列患者的初步分析表明,Ancer有能力确定足够数量的候选序列,用于在精确免疫治疗环境中接种膀胱癌患者。我们还评估了Ancer在58个个体的更大子集中预测患者预后的能力。虽然BLCA患者的无病状态不能用其肿瘤突变负荷(AUC = 0.55, p值= 0.1328)来解释,也不能用其错义突变负荷(AUC = 0.54, p值= 0.1740)来解释,但根据Ancer的定义,与自身高度不同的新表位数量显著地将无病患者与复发或进展患者区分开来(AUC = 0.68, p值= 0.0214)。这些结果表明,使用Ancer来定义真正的新表位的数量可能代表一种新的生物标志物,用于更强大的抗肿瘤免疫反应和更高的无病生存可能性。我们对TCGA数据库中BLCA队列的分析显示了Ancer在临床环境中的价值。Ancer可用于鉴定高价值的候选序列,以纳入个性化治疗,同时从考虑中去除潜在耐受或耐受性的自我表位。我们的下一步将是研究癌症定义的新表位负荷是否可以作为整个BLCA队列中预后和治疗反应的生物标志物。引文格式:Guilhem Richard, Randy F. Sweis, Leonard Moise, Matthew Ardito, William A. Martin, Gad Berdugo, Gary D. Steinberg, Anne S. De Groot。精准癌症免疫治疗设计工具在膀胱癌中的应用:非自我样新表位作为预后生物标志物[摘要]。第四届CRI-CIMT-EATI-AACR国际癌症免疫治疗会议:将科学转化为生存;2018年9月30日至10月3日;纽约,纽约。费城(PA): AACR;癌症免疫学杂志,2019;7(2增刊):摘要nr B089。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abstract B089: Application of precision cancer immunotherapy design tools to bladder cancer: Non-self-like neoepitopes as a prognostic biomarker
Precision cancer immunotherapy targeting mutations expressed by cancer cells has proven to effectively control the tumor of patients in multiple clinical trials (Sahin et al., Nature 2017; Ott et al., Nature 2017). However, the selection of immunogenic T-cell neo-epitopes remains challenging and many epitopes selected using traditional methodologies fail to induce effector T-cell responses. Poor performance may partially be due to inclusion of mutated epitopes cross-conserved with self-epitopes recognized by regulatory (Treg), anergic, or deleted T-cells. Vaccination with self-epitopes can lead to weak effector responses, active immune suppression, and toxicity due to immune-mediated adverse effects. In addition, most cancer vaccine studies focus on the selection of CD8 T-cell neo-epitopes due to an apparent lack of robust and accurate CD4 T-cell epitope prediction tools. We have developed Ancer, an integrated and streamlined neo-epitope selection pipeline, that accelerates the selection of both CD4 and CD8 T-cell neo-epitopes from next-generation sequencing (NGS) data. Ancer leverages EpiMatrix and JanusMatrix, predictive algorithms that have been extensively validated in prospective vaccine studies for infectious diseases (Moise et al., Hum Vaccines Immunother 2015; Wada et al., Sci Rep 2017). Distinctive features of Ancer are its ability to accurately predict Class II HLA ligands, or CD4 epitopes, with EpiMatrix, and to identify tolerated or Treg epitopes with JanusMatrix. In addition, screening candidate sequences with JanusMatrix enables to the removal of neo-epitopes that may trigger off-target events, which have in some cases abruptly halted the development of promising cancer therapies. Ancer was applied to NGS data derived from the BLCA bladder cancer cohort from The Cancer Genome Atlas (TCGA) database. On average, 55 out of 204 missense mutations in bladder cancer patients’ tumors met Ancer’s quality control standards, in an initial analysis carried out for a representative set of 11 patients. This subset of high-quality missense variants was then screened using Ancer settings defined by the unique HLA of each patient, to derive the best vaccine candidate sequences encompassing these mutations. A median number of 24 (interquartile range: 15-64) candidate sequences were generated for each patient under study. The time required to select sequences for all of the patients in this study was less than two days. This initial analysis of eleven BLCA bladder cancer cohort patients demonstrates the capacity of Ancer to define a sufficient number of candidate sequences for vaccinating bladder cancer patients in a precision immunotherapy setting. We also assessed Ancer’s ability to predict patient outcomes on a larger subset of 58 individuals. While the disease-free status of BLCA patients could not be explained by their tumor mutational burden (AUC = 0.55, p-value = 0.1328), nor by their load of missense mutations (AUC = 0.54, p-value = 0.1740), the number of neoepitopes highly different from self, as defined by Ancer, significantly segregated disease-free patients from patients who recurred or progressed (AUC = 0.68, p-value = 0.0214). These results suggest that defining the number of true neoepitopes using Ancer may represent a novel biomarker for more robust antitumor immune response and higher likelihood of disease-free survival.Our analysis of the BLCA cohort from the TCGA database showcases the value of Ancer in clinical settings. Ancer can be used to identify high-value candidate sequences for inclusion in personalized therapies while removing potentially tolerated or tolerogenic self-epitopes from consideration. Our next step will be to investigate whether Ancer-defined neoepitope load will serve as a biomarker for prognosis and response to therapy in the full BLCA cohort. Citation Format: Guilhem Richard, Randy F. Sweis, Leonard Moise, Matthew Ardito, William A. Martin, Gad Berdugo, Gary D. Steinberg, Anne S. De Groot. Application of precision cancer immunotherapy design tools to bladder cancer: Non-self-like neoepitopes as a prognostic biomarker [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B089.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信