Dataset related to article "Multiplexed Imaging Mass Cytometry Analysis in Preclinical Models of Pancreatic Cancer"

This record contains raw data related to article "Multiplexed Imaging Mass Cytometry Analysis in Preclinical Models of Pancreatic Cancer"

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers. PDAC is characterized by a complex tumor microenvironment (TME), that plays a pivotal role in disease progression and resistance to therapy. Investigating the spatial distribution and interaction of TME cells with the tumor is the basis for understanding the mechanisms underlying disease progression and represents a current challenge in PDAC research. Imaging mass cytometry (IMC) is the major multiplex imaging technology for the spatial analysis of tumor heterogeneity. However, there is a dearth of reports of multiplexed IMC panels for different preclinical mouse models, including pancreatic cancer. We addressed this gap by utilizing two preclinical models of PDAC: the genetically engineered, bearing KRAS–TP53 mutations in pancreatic cells, and the orthotopic, and developed a 28–marker panel for single–cell IMC analysis to assess the abundance, distribution and phenotypes of cells involved in PDAC progression and their reciprocal functional interactions. Herein, we provide an unprecedented definition of the distribution of TME cells in PDAC and compare the diversity between transplanted and genetic disease models. The results obtained represent an important and customizable tool for unraveling the complexities of PDAC and deciphering the mechanisms behind therapy resistance.

本数据集包含与论文《胰腺癌临床前模型中的多重成像质谱流式分析（Multiplexed Imaging Mass Cytometry Analysis in Preclinical Models of Pancreatic Cancer）》相关的原始数据。

摘要
胰腺导管腺癌（Pancreatic ductal adenocarcinoma, PDAC）是致死率最高的恶性肿瘤之一。PDAC以复杂的肿瘤微环境（Tumor Microenvironment, TME）为核心特征，其在疾病进展与治疗抵抗过程中发挥关键调控作用。解析肿瘤微环境细胞与肿瘤细胞的空间分布及相互作用，是阐明疾病进展机制的核心基础，同时也是当前PDAC研究领域的重大挑战。
成像质谱流式（Imaging Mass Cytometry, IMC）是目前用于肿瘤异质性空间分析的主流多重成像技术。然而，当前针对包括胰腺癌在内的各类临床前小鼠模型的多重IMC检测面板的相关研究报道仍较为匮乏。
针对这一研究缺口，我们选用两种PDAC临床前模型：一是在胰腺细胞中携带KRAS-TP53突变的基因工程模型，二是原位移植模型，并开发了一套包含28个标志物的单细胞IMC分析面板，用以评估PDAC进展相关细胞的丰度、分布与表型，以及它们之间的相互功能调控关系。
在此，我们首次系统性明确了PDAC肿瘤微环境细胞的分布特征，并对比了移植瘤模型与基因工程模型之间的细胞多样性差异。本研究所得成果可为解析PDAC的复杂生物学特性、阐明治疗抵抗的潜在机制提供一款重要且可定制化的研究工具。