Abstract 1178: Tissue nanomechanics as a novel, clinically translatable predictive early biomarker of response in combination immunotherapy

Gitika Srivastava,Sara Nizzero,Mark Wasley, Mingee Kim, Kathleen Graham, Papa Diogop Ndiaye, Mariam Gachechiladze,Nahum Puebla-Osorio,Philipp Oertle,Tobias Appenzeller,Vittorio Cristini,Marko Loparic,Marija Plodinec,James W. Welsh

Cancer Research(2024)

引用 0|浏览4
暂无评分
摘要
Abstract Background: Recently, the successful integration of immunotherapy with other treatment modalities has demonstrated its efficacy in enhancing immune activation and suppressing tumors in solid cancers. The most promising of such efforts include the use of low dose radiation (LD-XRT) to prime the tumor microenvironment and enhance the T cell infiltration and activation [Barsoumian HB, et al., 2020; Patel RR, et al., 2021; He K, et al., 2023]. With these advancements, there is an urgent need to develop clinical biomarkers to predict response and optimize treatment decisions. Recent evidence underscores the importance of nanomechanical alterations within the tumor microenvironment as mechanistic indicators of aggressiveness [Plodinec M, et al., 2012]. This study aims to demonstrate the value of ARTIDIS nanomechanical signature as early predictor of elucidate of response to combination LD-XRT/immune checkpoint inhibitors (ICI). Our measurement protocol in mice follows the same settings for biopsies acquired in routine biopsy collection protocol, thus supporting prompt clinical translation and integration. Methods: We established a mouse model of 344SQ lung adenocarcinoma tumors that exhibited resistance to anti-PD1 treatment in 129Sv/Ev mice. These mice underwent treatment protocols involving a combination of anti-PD1 and anti-CTLA4 antibodies, both with and without LD-XRT pre-treatment. Throughout the study, we closely monitored survival rates and tumor growth across diverse experimental groups. Employing the ARTIDIS platform, a cutting-edge technology that integrates atomic force microscopy with proprietary artificial intelligence algorithms, we extracted a multiparametric nanomechanical signature and we evaluated its outcome prediction value. This signature was then complemented by histopathology, multiplex immunofluorescence, and Nanostring assays to elucidate mechanisms of stroma remodulation and immune infiltration. Results: This study identifies the unique nanomechanical signature predictive of response to immunotherapy alone or in combination with radiation. Using the tissue nanomechanical signature as a predictive biomarker, we achieved precise differentiation between responders and non-responders, boasting a 90% sensitivity, 99.1% specificity, and a 96% AUC. To our knowledge, this study is the first to demonstrate the response-predicting power of a tissue derived nanomechanical signature for immune checkpoint inhibitors administered in combination with LD-XRT. These findings support clinical translation of the ARTIDIS nanomechanical signature as a pivotal tool for clinically predicting and evaluating responses to integrated radiation and immunotherapy approaches. Citation Format: Gitika Srivastava, Sara Nizzero, Mark Wasley, Mingee Kim, Kathleen Graham, Papa Diogop Ndiaye, Mariam Gachechiladze, Nahum Puebla-Osorio, Philipp Oertle, Tobias Appenzeller, Vittorio Cristini, Marko Loparic, Marija Plodinec, James W. Welsh. Tissue nanomechanics as a novel, clinically translatable predictive early biomarker of response in combination immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1178.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要