探讨低氧、低氧诱导因子1与放射治疗光氧化还原比的关系。

Biophotonics discovery Pub Date : 2024-04-01 Epub Date: 2024-05-28 DOI:10.1117/1.bios.1.1.015003
Jesse D Ivers, Nagavenkatasai Puvvada, Charles M Quick, Narasimhan Rajaram
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引用次数: 0

摘要

意义:放射耐药是癌症治疗失败的主要因素,可能由多种途径驱动。保留因子空间共定位的多变量可视化有助于理解耐药机制和识别反应的生物标志物。目的:研究两种已知的辐射抗性和敏感性细胞系中缺氧、缺氧诱导因子1 (HIF-1α)和代谢对放射治疗反应的时空关系。方法:采用双光子激发荧光和荧光寿命成像显微镜定量冰冻肿瘤切片的光学氧化还原比(ORR)和NAD(P)H荧光寿命和结合分数,并与免疫组织化学染色成像低氧分数和HIF-1α共同登记。结果:缺氧、HIF-1α和ORR的直方图分析显示,低缺氧和高HIF-1α区域的ORR增加,表明放射治疗后HIF-1α的稳定可能是由于活性氧的增加。此外,放疗后耐药肿瘤中ORR较低的区域结合的NAD(P)H分数较高,表明脂肪酸合成增加。结论:多变量直方图方法可以揭示肿瘤图像批量分析中未观察到的隐藏趋势,可能有助于理解生物标志物和辐射耐药机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigating the relationship between hypoxia, hypoxia-inducible factor 1, and the optical redox ratio in response to radiation therapy.

Significance: Radiation resistance is a major contributor to cancer treatment failure and is likely driven by multiple pathways. Multivariate visualization that preserves the spatial co-localization of factors could aid in understanding mechanisms of resistance and identifying biomarkers of response.

Aim: We aim to investigate the spatial and temporal relationship between hypoxia, hypoxia-inducible factor 1 (HIF-1α), and metabolism in response to radiation therapy in two cell lines of known radiation resistance and sensitivity.

Approach: Two-photon excited fluorescence and fluorescence lifetime imaging microscopy were used to quantify the optical redox ratio (ORR) and NAD(P)H fluorescent lifetime and bound fraction in frozen tumor sections and co-registered with immunohistochemical stain-based imaging of hypoxic fraction and HIF-1α.

Results: Histogram analysis of hypoxia, HIF-1α, and ORR revealed an increase in the ORR in regions of low hypoxia and high HIF-1α, indicating that the stabilization of HIF-1α is likely due to an increase in reactive oxygen species following radiation therapy. In addition, the bound NAD(P)H fraction was higher in regions with a low ORR in resistant tumors following radiation, suggesting an increase in fatty acid synthesis.

Conclusions: A multivariate histogram approach can reveal hidden trends not observed in bulk analysis of tumor images and may be useful in understanding biomarkers and mechanisms of radiation resistance.

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