Development of a customizable mouse backbone spectral flow cytometry panel to delineate immune cell populations in normal and tumor tissues

开发可定制的小鼠骨架光谱流式细胞术分析平台,用于区分正常组织和肿瘤组织中的免疫细胞群

阅读:5
作者:Ana Leda F Longhini # ,Inés Fernández-Maestre # ,Margaret C Kennedy ,Matthew G Wereski ,Shoron Mowla ,Wenbin Xiao ,Scott W Lowe ,Ross L Levine # ,Rui Gardner #

Abstract

Introduction: In vivo studies of cancer biology and assessment of therapeutic efficacy are critical to advancing cancer research and ultimately improving patient outcomes. Murine cancer models have proven to be an invaluable tool in pre-clinical studies. In this context, multi-parameter flow cytometry is a powerful method for elucidating the profile of immune cells within the tumor microenvironment and/or play a role in hematological diseases. However, designing an appropriate multi-parameter panel to comprehensively profile the increasing diversity of immune cells across different murine tissues can be extremely challenging. Methods: To address this issue, we designed a panel with 13 fixed markers that define the major immune populations -referred to as the backbone panel- that can be profiled in different tissues but with the option to incorporate up to seven additional fluorochromes, including any marker specific to the study in question. Results: This backbone panel maintains its resolution across different spectral flow cytometers and organs, both hematopoietic and non-hematopoietic, as well as tumors with complex immune microenvironments. Discussion: Having a robust backbone that can be easily customized with pre-validated drop-in fluorochromes saves time and resources and brings consistency and standardization, making it a versatile solution for immuno-oncology researchers. In addition, the approach presented here can serve as a guide to develop similar types of customizable backbone panels for different research questions requiring high-parameter flow cytometry panels.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。