微血管密度基因标记的研制及其在精准医学中的应用。

IF 2 Q3 ONCOLOGY
Megumi Kuronishi, Yoichi Ozawa, Takayuki Kimura, Shuyu Dan Li, Yu Kato
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引用次数: 0

摘要

抗血管生成药物和免疫检查点抑制剂联合治疗已显示出增强的临床活性,并已被批准用于治疗多种肿瘤类型。尽管进行了广泛的研究,但对联合治疗的预测性生物标志物仍然知之甚少。微血管密度(MVD)是免疫组织化学(IHC)测量异常血管生成的替代标志物,与抗血管生成抑制剂单药治疗的反应有关。然而,获得足够质量的肿瘤组织进行免疫组化分析并不总是可行的,而且基于免疫组化的MVD测量在大型公共数据集中是不可用的。在这项研究中,我们建立了一个基于rna测序数据的MVD基因评分,通过使用RNA-seq和IHC测量的MVD在12个小鼠同基因肿瘤模型中反映MVD。我们在小鼠和人类肿瘤数据集中探索了MVD基因评分和预测抗pd -1治疗反应的基因标记之间的关系。MVD基因评分与lenvatinib(一种主要靶向vegfr和fgfr的多重酪氨酸激酶抑制剂)在小鼠肿瘤模型中的抗肿瘤活性以及IHC在市买的人福尔马林固定石蜡包埋肿瘤样品中测量的MVD相关。肿瘤基因组图谱中的肿瘤类型根据MVD基因评分和t细胞炎症基因表达谱(TcellinfGEP)分为四个亚组,这些亚组与临床治疗指征相关。总之,新开发的MVD基因评分可以在无法获得IHC数据的大型公共数据集中估计MVD,并且与TcellinfGEP一起具有潜在的临床应用价值,可以用于精确医学表征患者的肿瘤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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