作者
Jong W. Yu,Sabyasachi Bhattacharya,Niranjan Yanamandra,David Kilian,Seonki Hong,Sapna Yadavilli,Yuliya Katlinskaya,Heather Kaczynski,Michael Conner,William G. Benson,Ashleigh Hahn,Laura Seestaller-Wehr,Meixia Bi,Nicholas J. Vitali,Lyuben Tsvetkov,Wendy S. Halsey,Ashley M. Hughes,Christopher Traini,Hui Zhou,Junping Jing,Tae Lee,David J. Figueroa,Sara Brett,Christopher B. Hopson,James Smothers,Axel Hoos,Roopa Srinivasan
摘要
Mouse syngeneic tumor models are widely used tools to demonstrate activity of novel anti-cancer immunotherapies. Despite their widespread use, a comprehensive view of their tumor-immune compositions and their relevance to human tumors has only begun to emerge. We propose each model possesses a unique tumor-immune infiltrate profile that can be probed with immunotherapies to inform on anti-tumor mechanisms and treatment strategies in human tumors with similar profiles. In support of this endeavor, we characterized the tumor microenvironment of four commonly used models and demonstrate they encompass a range of immunogenicities, from highly immune infiltrated RENCA tumors to poorly infiltrated B16F10 tumors. Tumor cell lines for each model exhibit different intrinsic factors in vitro that likely influence immune infiltration upon subcutaneous implantation. Similarly, solid tumors in vivo for each model are unique, each enriched in distinct features ranging from pathogen response elements to antigen presentation machinery. As RENCA tumors progress in size, all major T cell populations diminish while myeloid-derived suppressor cells become more enriched, possibly driving immune suppression and tumor progression. In CT26 tumors, CD8 T cells paradoxically increase in density yet are restrained as tumor volume increases. Finally, immunotherapy treatment across these different tumor-immune landscapes segregate into responders and non-responders based on features partially dependent on pre-existing immune infiltrates. Overall, these studies provide an important resource to enhance our translation of syngeneic models to human tumors. Future mechanistic studies paired with this resource will help identify responsive patient populations and improve strategies where immunotherapies are predicted to be ineffective.