安洛替尼在骨肉瘤中的潜在治疗靶点:基于患者来源的异种移植物和下一代测序的表征

IF 3.1 2区 医学 Q2 ONCOLOGY
Cancer Medicine Pub Date : 2024-12-01 DOI:10.1002/cam4.70416
Zuoyao Long, Yajie Lu, Minghui Li, Jing Li, Guojing Chen, Fengwei Wang, Qi Wang, Liangbi Xiang, Zhen Wang
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引用次数: 0

摘要

本研究的目的是分析anlotinib在患者源性异种移植物(PDX)中的潜在治疗靶点,并评估术前化疗联合anlotinib在骨肉瘤患者中的疗效。方法采用43例骨肉瘤标本建立小鼠PDX模型,成功建立21例PDX模型。最后随机选取6只模型进行药效学实验。将荷瘤小鼠随机分为安洛替尼组(3mg /kg)和安慰剂组(各n = 5)。治疗后,取肿瘤进行免疫组化(IHC)和免疫印迹(western blotting)分析。结果在PDX模型的建立中,复发、转移或化疗耐药的供体肿瘤具有较高的移植能力。组织学结果表明,anlotinib通过诱导有丝分裂阻滞、坏死和凋亡,并选择性抑制VEGFR2、PDGFRβ和CD31高表达的肿瘤,显著抑制骨肉瘤的生长。基于这些结果,5例在NAC期间进展的骨肉瘤患者在手术前联合使用安洛替尼和化疗,导致4例患者肿瘤消退。新一代测序显示,大多数肿瘤缩小患者表达中等或高水平的VEGFR2和PDGFRβ mRNA。毒性是可以忍受的。结论高表达VEGFR2、PDGFRβ和CD31的骨肉瘤对安洛替尼更敏感。然而,安洛替尼与化疗在骨肉瘤患者中的协同作用潜力还有待进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Potential Therapeutic Targets of Anlotinib in Osteosarcoma: Characterization Based on Patient-Derived Xenografts and Next-Generation Sequencing

The Potential Therapeutic Targets of Anlotinib in Osteosarcoma: Characterization Based on Patient-Derived Xenografts and Next-Generation Sequencing

Background

The aim of this study was to analyze the potential therapeutic targets of anlotinib using the patient-derived xenografts (PDX) and evaluate the efficacy of the combination of chemotherapy and anlotinib in osteosarcoma patients before surgery.

Methods

Forty-three osteosarcoma specimens were used to establish the PDX model in mice, resulting in Twenty-one PDX successful models. Eventually, six models were randomly selected for the pharmacodynamic experiment. The tumor-bearing mice were randomly divided into the anlotinib (3 mg/kg) and placebo groups (n = 5 each). After treatment, the tumors were harvested and analyzed by immunohistochemistry (IHC) and western blotting.

Results

In PDX model establishment, the tumors from donors with relapse, metastasis or chemoresistance demonstrated higher engraftment capacity. Histology results suggested that anlotinib significantly inhibited the growth of osteosarcoma by inducing mitotic arrest, necrosis and apoptosis, and selective against tumors with high expression of VEGFR2, PDGFRβ and CD31. Based on these results, five osteosarcoma patients who had progressed during NAC were treated with the combination of anlotinib and chemotherapy before surgery, which led to tumor regression in four patients. Next-generation sequencing showed that most patients with tumor reduction expressed medium or high levels of VEGFR2 and PDGFRβ mRNA. The toxicities were tolerable.

Conclusions

In conclusion, osteosarcoma with high expression of VEGFR2, PDGFRβ and CD31 is more sensitive to anlotinib. However, the potential of synergistic effect of anlotinib and chemotherapy in osteosarcoma patients needs further investigation.

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来源期刊
Cancer Medicine
Cancer Medicine ONCOLOGY-
CiteScore
5.50
自引率
2.50%
发文量
907
审稿时长
19 weeks
期刊介绍: Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.
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