Alberto Hernando-Calvo, S Y Cindy Yang, Maria Vila-Casadesús, Ming Han, Zhihui Amy Liu, A Hal K Berman, Anna Spreafico, Albiruni Abdul Razak, Stephanie Lheureux, Aaron R Hansen, Deborah Lo Giacco, Farnoosh Abbas-Aghababazadeh, Judith Matito, Benjamin Haibe-Kains, Trevor J Pugh, Scott V Bratman, Alexey Aleshin, Roger Berche, Omar Saavedra, Elena Garralda, Sawako Elston, Lillian L Siu, Pamela S Ohashi, Ana Vivancos, Philippe L Bedard
{"title":"转录组和循环肿瘤 DNA 纵向生物标记物分析与 Pembrolizumab 治疗晚期实体瘤的临床结果相关联","authors":"Alberto Hernando-Calvo, S Y Cindy Yang, Maria Vila-Casadesús, Ming Han, Zhihui Amy Liu, A Hal K Berman, Anna Spreafico, Albiruni Abdul Razak, Stephanie Lheureux, Aaron R Hansen, Deborah Lo Giacco, Farnoosh Abbas-Aghababazadeh, Judith Matito, Benjamin Haibe-Kains, Trevor J Pugh, Scott V Bratman, Alexey Aleshin, Roger Berche, Omar Saavedra, Elena Garralda, Sawako Elston, Lillian L Siu, Pamela S Ohashi, Ana Vivancos, Philippe L Bedard","doi":"10.1200/PO.24.00100","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Immune gene expression signatures are emerging as potential biomarkers for immunotherapy (IO). VIGex is a 12-gene expression classifier developed in both nCounter (Nanostring) and RNA sequencing (RNA-seq) assays and analytically validated across laboratories. VIGex classifies tumor samples into hot, intermediate-cold (I-Cold), and cold subgroups. VIGex-Hot has been associated with better IO treatment outcomes. Here, we investigated the performance of VIGex and other IO biomarkers in an independent data set of patients treated with pembrolizumab in the INSPIRE phase II clinical trial (ClinicalTrials.gov identifier: NCT02644369).</p><p><strong>Materials and methods: </strong>Patients with advanced solid tumors were treated with pembrolizumab 200 mg IV once every 3 weeks. Tumor RNA-seq data from baseline tumor samples were classified by the VIGex algorithm. Circulating tumor DNA (ctDNA) was measured at baseline and start of cycle 3 using the bespoke Signatera assay. VIGex-Hot was compared with VIGex I-Cold + Cold and four groups were defined on the basis of the combination of VIGex subgroups and the change in ctDNA at cycle 3 from baseline (ΔctDNA).</p><p><strong>Results: </strong>Seventy-six patients were enrolled, including 16 ovarian, 12 breast, 12 head and neck cancers, 10 melanoma, and 26 other tumor types. Objective response rate was 24% in VIGex-Hot and 10% in I-Cold/Cold. VIGex-Hot subgroup was associated with higher overall survival (OS) and progression-free survival (PFS) when included in a multivariable model adjusted for tumor type, tumor mutation burden, and PD-L1 immunohistochemistry. The addition of ΔctDNA improved the predictive performance of the baseline VIGex classification for both OS and PFS.</p><p><strong>Conclusion: </strong>Our data indicate that the addition of ΔctDNA to baseline VIGex may refine prediction for IO.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"8 ","pages":"e2400100"},"PeriodicalIF":5.3000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11371115/pdf/","citationCount":"0","resultStr":"{\"title\":\"Combined Transcriptome and Circulating Tumor DNA Longitudinal Biomarker Analysis Associates With Clinical Outcomes in Advanced Solid Tumors Treated With Pembrolizumab.\",\"authors\":\"Alberto Hernando-Calvo, S Y Cindy Yang, Maria Vila-Casadesús, Ming Han, Zhihui Amy Liu, A Hal K Berman, Anna Spreafico, Albiruni Abdul Razak, Stephanie Lheureux, Aaron R Hansen, Deborah Lo Giacco, Farnoosh Abbas-Aghababazadeh, Judith Matito, Benjamin Haibe-Kains, Trevor J Pugh, Scott V Bratman, Alexey Aleshin, Roger Berche, Omar Saavedra, Elena Garralda, Sawako Elston, Lillian L Siu, Pamela S Ohashi, Ana Vivancos, Philippe L Bedard\",\"doi\":\"10.1200/PO.24.00100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Immune gene expression signatures are emerging as potential biomarkers for immunotherapy (IO). VIGex is a 12-gene expression classifier developed in both nCounter (Nanostring) and RNA sequencing (RNA-seq) assays and analytically validated across laboratories. VIGex classifies tumor samples into hot, intermediate-cold (I-Cold), and cold subgroups. VIGex-Hot has been associated with better IO treatment outcomes. Here, we investigated the performance of VIGex and other IO biomarkers in an independent data set of patients treated with pembrolizumab in the INSPIRE phase II clinical trial (ClinicalTrials.gov identifier: NCT02644369).</p><p><strong>Materials and methods: </strong>Patients with advanced solid tumors were treated with pembrolizumab 200 mg IV once every 3 weeks. Tumor RNA-seq data from baseline tumor samples were classified by the VIGex algorithm. Circulating tumor DNA (ctDNA) was measured at baseline and start of cycle 3 using the bespoke Signatera assay. VIGex-Hot was compared with VIGex I-Cold + Cold and four groups were defined on the basis of the combination of VIGex subgroups and the change in ctDNA at cycle 3 from baseline (ΔctDNA).</p><p><strong>Results: </strong>Seventy-six patients were enrolled, including 16 ovarian, 12 breast, 12 head and neck cancers, 10 melanoma, and 26 other tumor types. Objective response rate was 24% in VIGex-Hot and 10% in I-Cold/Cold. VIGex-Hot subgroup was associated with higher overall survival (OS) and progression-free survival (PFS) when included in a multivariable model adjusted for tumor type, tumor mutation burden, and PD-L1 immunohistochemistry. The addition of ΔctDNA improved the predictive performance of the baseline VIGex classification for both OS and PFS.</p><p><strong>Conclusion: </strong>Our data indicate that the addition of ΔctDNA to baseline VIGex may refine prediction for IO.</p>\",\"PeriodicalId\":14797,\"journal\":{\"name\":\"JCO precision oncology\",\"volume\":\"8 \",\"pages\":\"e2400100\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11371115/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JCO precision oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1200/PO.24.00100\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JCO precision oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1200/PO.24.00100","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
Combined Transcriptome and Circulating Tumor DNA Longitudinal Biomarker Analysis Associates With Clinical Outcomes in Advanced Solid Tumors Treated With Pembrolizumab.
Purpose: Immune gene expression signatures are emerging as potential biomarkers for immunotherapy (IO). VIGex is a 12-gene expression classifier developed in both nCounter (Nanostring) and RNA sequencing (RNA-seq) assays and analytically validated across laboratories. VIGex classifies tumor samples into hot, intermediate-cold (I-Cold), and cold subgroups. VIGex-Hot has been associated with better IO treatment outcomes. Here, we investigated the performance of VIGex and other IO biomarkers in an independent data set of patients treated with pembrolizumab in the INSPIRE phase II clinical trial (ClinicalTrials.gov identifier: NCT02644369).
Materials and methods: Patients with advanced solid tumors were treated with pembrolizumab 200 mg IV once every 3 weeks. Tumor RNA-seq data from baseline tumor samples were classified by the VIGex algorithm. Circulating tumor DNA (ctDNA) was measured at baseline and start of cycle 3 using the bespoke Signatera assay. VIGex-Hot was compared with VIGex I-Cold + Cold and four groups were defined on the basis of the combination of VIGex subgroups and the change in ctDNA at cycle 3 from baseline (ΔctDNA).
Results: Seventy-six patients were enrolled, including 16 ovarian, 12 breast, 12 head and neck cancers, 10 melanoma, and 26 other tumor types. Objective response rate was 24% in VIGex-Hot and 10% in I-Cold/Cold. VIGex-Hot subgroup was associated with higher overall survival (OS) and progression-free survival (PFS) when included in a multivariable model adjusted for tumor type, tumor mutation burden, and PD-L1 immunohistochemistry. The addition of ΔctDNA improved the predictive performance of the baseline VIGex classification for both OS and PFS.
Conclusion: Our data indicate that the addition of ΔctDNA to baseline VIGex may refine prediction for IO.