{"title":"微血管密度基因标记的研制及其在精准医学中的应用。","authors":"Megumi Kuronishi, Yoichi Ozawa, Takayuki Kimura, Shuyu Dan Li, Yu Kato","doi":"10.1158/2767-9764.CRC-24-0403","DOIUrl":null,"url":null,"abstract":"<p><p>Combination therapy with anti-angiogenic drugs and immune checkpoint inhibitors has shown enhanced clinical activity and has been approved for the treatment of multiple tumor types. Despite extensive research, predictive biomarkers for combination therapy remain poorly understood. Microvessel density (MVD), a surrogate marker for aberrant angiogenesis measured by immunohistochemistry (IHC), has been associated with response to monotherapy with anti-angiogenesis inhibitors. However, obtaining tumor tissue with a sufficient mass for IHC analysis is not always practical, and IHC-based MVD measurements are unavailable in large public datasets. In this study, we developed an MVD gene score based on RNA-sequencing data that reflects MVD by using RNA-seq and MVD measured by IHC in 12 mouse syngeneic tumor models. We explored the relationship between the MVD gene score and a gene signature predicting the response to anti-PD-1 therapy in mouse and human tumor datasets. The MVD gene score correlated with the antitumor activity of lenvatinib, a multiple tyrosine kinase inhibitor mainly targeting VEGFRs and FGFRs, in mouse tumor models and MVD measured by IHC in commercially available human formalin-fixed, paraffin-embedded tumor samples. Tumor types in The Cancer Genome Atlas were classified into four subgroups based on the MVD gene score and T-cell inflamed gene expression profile (TcellinfGEP), which were correlated with clinical indications for treatment. In conclusion, the newly developed MVD gene score enables the estimation of MVD in large public datasets where IHC data are unavailable and has potential clinical utility together with the TcellinfGEP to characterize patients' tumors for precision medicine.</p>","PeriodicalId":72516,"journal":{"name":"Cancer research communications","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of a microvessel density gene signature and its application in precision medicine.\",\"authors\":\"Megumi Kuronishi, Yoichi Ozawa, Takayuki Kimura, Shuyu Dan Li, Yu Kato\",\"doi\":\"10.1158/2767-9764.CRC-24-0403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Combination therapy with anti-angiogenic drugs and immune checkpoint inhibitors has shown enhanced clinical activity and has been approved for the treatment of multiple tumor types. Despite extensive research, predictive biomarkers for combination therapy remain poorly understood. Microvessel density (MVD), a surrogate marker for aberrant angiogenesis measured by immunohistochemistry (IHC), has been associated with response to monotherapy with anti-angiogenesis inhibitors. However, obtaining tumor tissue with a sufficient mass for IHC analysis is not always practical, and IHC-based MVD measurements are unavailable in large public datasets. In this study, we developed an MVD gene score based on RNA-sequencing data that reflects MVD by using RNA-seq and MVD measured by IHC in 12 mouse syngeneic tumor models. We explored the relationship between the MVD gene score and a gene signature predicting the response to anti-PD-1 therapy in mouse and human tumor datasets. The MVD gene score correlated with the antitumor activity of lenvatinib, a multiple tyrosine kinase inhibitor mainly targeting VEGFRs and FGFRs, in mouse tumor models and MVD measured by IHC in commercially available human formalin-fixed, paraffin-embedded tumor samples. Tumor types in The Cancer Genome Atlas were classified into four subgroups based on the MVD gene score and T-cell inflamed gene expression profile (TcellinfGEP), which were correlated with clinical indications for treatment. In conclusion, the newly developed MVD gene score enables the estimation of MVD in large public datasets where IHC data are unavailable and has potential clinical utility together with the TcellinfGEP to characterize patients' tumors for precision medicine.</p>\",\"PeriodicalId\":72516,\"journal\":{\"name\":\"Cancer research communications\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-01-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer research communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1158/2767-9764.CRC-24-0403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer research communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1158/2767-9764.CRC-24-0403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
Development of a microvessel density gene signature and its application in precision medicine.
Combination therapy with anti-angiogenic drugs and immune checkpoint inhibitors has shown enhanced clinical activity and has been approved for the treatment of multiple tumor types. Despite extensive research, predictive biomarkers for combination therapy remain poorly understood. Microvessel density (MVD), a surrogate marker for aberrant angiogenesis measured by immunohistochemistry (IHC), has been associated with response to monotherapy with anti-angiogenesis inhibitors. However, obtaining tumor tissue with a sufficient mass for IHC analysis is not always practical, and IHC-based MVD measurements are unavailable in large public datasets. In this study, we developed an MVD gene score based on RNA-sequencing data that reflects MVD by using RNA-seq and MVD measured by IHC in 12 mouse syngeneic tumor models. We explored the relationship between the MVD gene score and a gene signature predicting the response to anti-PD-1 therapy in mouse and human tumor datasets. The MVD gene score correlated with the antitumor activity of lenvatinib, a multiple tyrosine kinase inhibitor mainly targeting VEGFRs and FGFRs, in mouse tumor models and MVD measured by IHC in commercially available human formalin-fixed, paraffin-embedded tumor samples. Tumor types in The Cancer Genome Atlas were classified into four subgroups based on the MVD gene score and T-cell inflamed gene expression profile (TcellinfGEP), which were correlated with clinical indications for treatment. In conclusion, the newly developed MVD gene score enables the estimation of MVD in large public datasets where IHC data are unavailable and has potential clinical utility together with the TcellinfGEP to characterize patients' tumors for precision medicine.