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通过数字病理学方法对非小细胞肺癌患者来源异种移植模型进行代谢分类:一项试点研究。

Metabolic classification of non-small cell lung cancer patient-derived xenografts by a digital pathology approach: A pilot study.

作者信息

Ferrarini Federica, Zulato Elisabetta, Moro Massimo, Del Bianco Paola, Borzi Cristina, Esposito Giovanni, Zanin Tiziana, Sozzi Gabriella, Indraccolo Stefano

机构信息

Immunology and Molecular Oncology Diagnostics Unit, Istituto Oncologico Veneto IOV IRCCS, Padova, Italy.

Basic and Translational Oncology Unit, Istituto Oncologico Veneto IOV IRCCS, Padova, Italy.

出版信息

Front Oncol. 2023 Feb 28;13:1070505. doi: 10.3389/fonc.2023.1070505. eCollection 2023.

Abstract

INTRODUCTION

Genetically characterized patient-derived tumor xenografts (PDX) are a valuable resource to understand the biological complexity of cancer and to investigate new therapeutic approaches. Previous studies, however, lack information about metabolic features of PDXs, which may limit testing of metabolism targeting drugs.

METHODS

In this pilot study, we investigated by immunohistochemistry (IHC) expression of five essential metabolism-associated markers in a set of lung adenocarcinoma PDX samples previously established and characterized. We exploited digital pathology to quantify expression of the markers and correlated results with tumor cell proliferation, angiogenesis and time of PDX growth in mice.

RESULTS

Our results indicate that the majority of the analyzed PDX models rely on oxidative phosphorylation (OXPHOS) metabolism, either alone or in combination with glucose metabolism. Double IHC enabled us to describe spatial expression of the glycolysis-associated monocarboxylate transporter 4 (MCT4) marker and the OXPHOS-associated glutaminase (GLS) marker. GLS expression was associated with cell proliferation and with expression of liver-kinase B1 (LKB1), a tumor suppressor involved in the regulation of multiple metabolic pathways. Acetyl CoA carboxylase (ACC) was associated with the kinetics of PDX growth.

CONCLUSION

Albeit limited by the small number of samples and markers analyzed, metabolic classification of existing collections of PDX by this mini panel will be useful to inform pre-clinical testing of metabolism-targeting drugs.

摘要

引言

经过基因特征分析的患者来源肿瘤异种移植模型(PDX)是了解癌症生物学复杂性和研究新治疗方法的宝贵资源。然而,先前的研究缺乏关于PDX代谢特征的信息,这可能会限制对代谢靶向药物的测试。

方法

在这项初步研究中,我们通过免疫组织化学(IHC)研究了一组先前建立并表征的肺腺癌PDX样本中五种基本代谢相关标志物的表达。我们利用数字病理学对标志物的表达进行定量,并将结果与肿瘤细胞增殖、血管生成以及PDX在小鼠体内的生长时间相关联。

结果

我们的结果表明,大多数分析的PDX模型依赖氧化磷酸化(OXPHOS)代谢,单独或与葡萄糖代谢结合。双重免疫组织化学使我们能够描述糖酵解相关的单羧酸转运蛋白4(MCT4)标志物和OXPHOS相关的谷氨酰胺酶(GLS)标志物的空间表达。GLS表达与细胞增殖以及肝脏激酶B1(LKB1)的表达相关,LKB1是一种参与多种代谢途径调节的肿瘤抑制因子。乙酰辅酶A羧化酶(ACC)与PDX生长动力学相关。

结论

尽管受到分析样本和标志物数量较少的限制,但通过这个小型检测板对现有PDX样本集进行代谢分类,将有助于指导代谢靶向药物的临床前测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8077/10011479/ecfeb0943cdf/fonc-13-1070505-g001.jpg

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