Dataset related to article "Quantitative determination of niraparib and olaparib tumor distribution by mass spectrometry imaging"

The .zip file contains raw data related to the article "Quantitative determination of niraparib and olaparib tumor distribution by mass spectrometry imaging", available from https://www.ijbs.com/v16p1363.htm.

The folder "fig 1 2 3 NIRA" contains raw data related to the experiments with niraparib presented in figures 1, 2 and 3 

The folder "fig 1 2 3 OLA" contains raw data related to the experiments with olaparib presented in figures 1, 2 and 3 

The folders "fig 4" and "fig 6" contain raw data related to figures 4 and 6, respectively.

For any additional information on how to read and reuse the dataset please contact Dr. Ubezio at [e-mail].

ABSTRACT OF THE MANUSCRIPT:

Rationale: Optimal intratumor distribution of an anticancer drug is fundamental to reach an active concentration in neoplastic cells, ensuring the therapeutic effect. Determination of drug concentration in tumor homogenates by LC-MS/MS gives important information about this issue but the spatial information gets lost. Targeted mass spectrometry imaging (MSI) has great potential to visualize drug distribution in the different areas of tumor sections, with good spatial resolution and superior specificity. MSI is rapidly evolving as a quantitative technique to measure the absolute drug concentration in each single pixel.

Methods: Different inorganic nanoparticles were tested as matrices to visualize the PARP inhibitors (PARPi) niraparib and olaparib. Normalization by deuterated internal standard and a custom preprocessing pipeline were applied to achieve a reliable single pixel quantification of the two drugs in human ovarian tumors from treated mice.

Results: A quantitative method to visualize niraparib and olaparib in tumor tissue of treated mice was set up and validated regarding precision, accuracy, linearity, repeatability and limit of detection. The different tumor penetration of the two drugs was visualized by MSI and confirmed by LC-MS/MS, indicating the homogeneous distribution and higher tumor exposure reached by niraparib compared to olaparib. On the other hand, niraparib distribution was heterogeneous in an ovarian tumor model overexpressing the multidrug resistance protein P-gp, a possible cause of resistance to PARPi.

Conclusions: The current work highlights for the first time quantitative distribution of PAPRi in tumor tissue. The different tumor distribution of niraparib and olaparib could have important clinical implications. These data confirm the validity of MSI for spatial quantitative measurement of drug distribution providing fundamental information for pharmacokinetic studies, drug discovery and the study of resistance mechanisms.

该压缩包包含与论文《通过质谱成像定量测定尼拉帕利和奥拉帕利的肿瘤分布》相关的原始数据，可通过https://www.ijbs.com/v16p1363.htm获取。

文件夹“fig 1 2 3 NIRA”包含与图1、2、3中呈现的尼拉帕利（niraparib）相关实验的原始数据；
文件夹“fig 1 2 3 OLA”包含与图1、2、3中呈现的奥拉帕利（olaparib）相关实验的原始数据；
文件夹“fig 4”与“fig 6”分别包含与图4、图6相关的原始数据。

如需了解该数据集的读取与复用相关的更多信息，请联系Ubezio博士，邮箱地址为[e-mail]。

论文摘要

研究背景：抗肿瘤药物的最优瘤内分布是实现肿瘤细胞内有效药物浓度、保障治疗效果的核心前提。通过液相色谱-串联质谱（Liquid Chromatography-Tandem Mass Spectrometry, LC-MS/MS）测定肿瘤匀浆中的药物浓度可获取该维度的重要信息，但会丢失空间分布特征。靶向质谱成像（Mass Spectrometry Imaging, MSI）具备在肿瘤切片的不同区域可视化药物分布的巨大潜力，且拥有优异的空间分辨率与特异性。MSI正快速发展为可测定单个像素内绝对药物浓度的定量技术。

研究方法：本研究测试了多种无机纳米颗粒作为基质，以可视化聚腺苷二磷酸核糖聚合酶抑制剂（PARP inhibitors, PARPi）尼拉帕利与奥拉帕利。通过氘代内标进行归一化处理，并采用定制化预处理流程，实现了对给药小鼠人源卵巢肿瘤中两种药物的单像素定量分析，且结果可靠。

研究结果：本研究建立并验证了一种可可视化给药小鼠肿瘤组织中尼拉帕利与奥拉帕利的定量方法，验证维度包括精密度、准确度、线性、重复性与检出限。通过MSI可视化了两种药物截然不同的肿瘤渗透能力，并经LC-MS/MS验证：相较于奥拉帕利，尼拉帕利的分布更为均匀，且肿瘤暴露量更高。另一方面，在过表达多药耐药蛋白P-糖蛋白（P-glycoprotein, P-gp）的卵巢肿瘤模型中，尼拉帕利的分布呈异质性，这可能是PARPi耐药的潜在诱因。

研究结论：本研究首次揭示了PARPi在肿瘤组织中的定量分布特征。尼拉帕利与奥拉帕利迥异的肿瘤分布模式或具备重要的临床意义。本研究证实了MSI用于药物分布空间定量测定的有效性，可为药代动力学研究、药物开发以及耐药机制探究提供关键信息。