Jenny Lazarus1, Morgan D Oneka2, Souptik Barua2, Tomasz Maj1, Mirna Perusina Lanfranca1, Lawrence Delrosario1, Lei Sun1, J Joshua Smith3, Michael I D'Angelica3, Jinru Shia4, Jiayun M Fang5, Jiaqi Shi5, Marina Pasca Di Magliano1, Weiping Zou1, Arvind Rao6,2,7, Timothy L Frankel8. 1. Department of Surgery, University of Michigan, Ann Arbor, MI, USA. 2. Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA. 3. Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 4. Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 5. Department of Pathology, University of Michigan, Ann Arbor, MI, USA. 6. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA. 7. Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA. 8. Department of Surgery, University of Michigan, Ann Arbor, MI, USA. timofran@umich.edu.
Abstract
BACKGROUND: Although immune-based therapy has proven efficacious for some patients with microsatellite instability (MSI) colon cancers, a majority of patients receive limited benefit. Conversely, select patients with microsatellite stable (MSS) tumors respond to checkpoint blockade, necessitating novel ways to study the immune tumor microenvironment (TME). We used phenotypic and spatial data from infiltrating immune and tumor cells to model cellular mixing to predict disease specific outcomes in patients with colorectal liver metastases. METHODS: Formalin fixed paraffin embedded metastatic colon cancer tissue from 195 patients were subjected to multiplex immunohistochemistry (mfIHC). After phenotyping, the G-function was calculated for each patient and cell type. Data was correlated with clinical outcomes and survival. RESULTS: High tumor cell to cytotoxic T lymphocyte (TC-CTL) mixing was associated with both a pro-inflammatory and immunosuppressive TME characterized by increased CTL infiltration and PD-L1+ expression, respectively. Presence and engagement of antigen presenting cells (APC) and helper T cells (Th) were associated with greater TC-CTL mixing and improved 5-year disease specific survival compared to patients with a low degree of mixing (42% vs. 16%, p = 0.0275). Comparison of measured mixing to a calculated theoretical random mixing revealed that PD-L1 expression on APCs resulted in an environment where CTLs were non-randomly less associated with TCs, highlighting their biologic significance. CONCLUSION: Evaluation of immune interactions within the TME of metastatic colon cancer using mfIHC in combination with mathematical modeling characterized cellular mixing of TCs and CTLs, providing a novel strategy to better predict clinical outcomes while identifying potential candidates for immune based therapies.
BACKGROUND: Although immune-based therapy has proven efficacious for some patients with microsatellite instability (MSI) colon cancers, a majority of patients receive limited benefit. Conversely, select patients with microsatellite stable (MSS) tumors respond to checkpoint blockade, necessitating novel ways to study the immune tumor microenvironment (TME). We used phenotypic and spatial data from infiltrating immune and tumor cells to model cellular mixing to predict disease specific outcomes in patients with colorectal liver metastases. METHODS: Formalin fixed paraffin embedded metastatic colon cancer tissue from 195 patients were subjected to multiplex immunohistochemistry (mfIHC). After phenotyping, the G-function was calculated for each patient and cell type. Data was correlated with clinical outcomes and survival. RESULTS: High tumor cell to cytotoxic T lymphocyte (TC-CTL) mixing was associated with both a pro-inflammatory and immunosuppressive TME characterized by increased CTL infiltration and PD-L1+ expression, respectively. Presence and engagement of antigen presenting cells (APC) and helper T cells (Th) were associated with greater TC-CTL mixing and improved 5-year disease specific survival compared to patients with a low degree of mixing (42% vs. 16%, p = 0.0275). Comparison of measured mixing to a calculated theoretical random mixing revealed that PD-L1 expression on APCs resulted in an environment where CTLs were non-randomly less associated with TCs, highlighting their biologic significance. CONCLUSION: Evaluation of immune interactions within the TME of metastatic colon cancer using mfIHC in combination with mathematical modeling characterized cellular mixing of TCs and CTLs, providing a novel strategy to better predict clinical outcomes while identifying potential candidates for immune based therapies.
Authors: M Guidoboni; R Gafà; A Viel; C Doglioni; A Russo; A Santini; L Del Tin; E Macrì; G Lanza; M Boiocchi; R Dolcetti Journal: Am J Pathol Date: 2001-07 Impact factor: 4.307
Authors: Steven C Katz; Venu Pillarisetty; Zubin M Bamboat; Jinru Shia; Cyrus Hedvat; Mithat Gonen; William Jarnagin; Yuman Fong; Leslie Blumgart; Michael D'Angelica; Ronald P DeMatteo Journal: Ann Surg Oncol Date: 2009-07-01 Impact factor: 5.344
Authors: Tyler J Curiel; Shuang Wei; Haidong Dong; Xavier Alvarez; Pui Cheng; Peter Mottram; Roman Krzysiek; Keith L Knutson; Ben Daniel; Maria Carla Zimmermann; Odile David; Matthew Burow; Alan Gordon; Nina Dhurandhar; Leann Myers; Ruth Berggren; Akseli Hemminki; Ronald D Alvarez; Dominique Emilie; David T Curiel; Lieping Chen; Weiping Zou Journal: Nat Med Date: 2003-04-21 Impact factor: 53.440
Authors: Tyler J Curiel; George Coukos; Linhua Zou; Xavier Alvarez; Pui Cheng; Peter Mottram; Melina Evdemon-Hogan; Jose R Conejo-Garcia; Lin Zhang; Matthew Burow; Yun Zhu; Shuang Wei; Ilona Kryczek; Ben Daniel; Alan Gordon; Leann Myers; Andrew Lackner; Mary L Disis; Keith L Knutson; Lieping Chen; Weiping Zou Journal: Nat Med Date: 2004-08-22 Impact factor: 53.440
Authors: Yvette Schwitalle; Matthias Kloor; Susanne Eiermann; Michael Linnebacher; Peter Kienle; Hanns Peter Knaebel; Mirjam Tariverdian; Axel Benner; Magnus von Knebel Doeberitz Journal: Gastroenterology Date: 2008-01-11 Impact factor: 22.682
Authors: Yulia I Nussbaum; Yariswamy Manjunath; Kanve N Suvilesh; Wesley C Warren; Chi-Ren Shyu; Jussuf T Kaifi; Matthew A Ciorba; Jonathan B Mitchem Journal: Int J Mol Sci Date: 2021-04-30 Impact factor: 5.923
Authors: Hanna Elomaa; Maarit Ahtiainen; Sara A Väyrynen; Shuji Ogino; Jonathan A Nowak; Marjukka Friman; Olli Helminen; Erkki-Ville Wirta; Toni T Seppälä; Jan Böhm; Markus J Mäkinen; Jukka-Pekka Mecklin; Teijo Kuopio; Juha P Väyrynen Journal: Br J Cancer Date: 2022-04-21 Impact factor: 9.075
Authors: Brian D Griffith; Simon Turcotte; Jenny Lazarus; Fatima Lima; Samantha Bell; Lawrence Delrosario; Jake McGue; Santhoshi Krishnan; Morgan D Oneka; Hari Nathan; J Joshua Smith; Michael I D'Angelica; Jinru Shia; Marina Pasca Di Magliano; Arvind Rao; Timothy L Frankel Journal: Cancers (Basel) Date: 2022-08-24 Impact factor: 6.575
Authors: Diederik J Höppener; Pieter M H Nierop; Joost Hof; Kostandinos Sideras; Guoying Zhou; Lydia Visser; Annette S H Gouw; Koert P de Jong; Dave Sprengers; Jaap Kwekkeboom; Peter B Vermeulen; Dirk J Grünhagen; Cornelis Verhoef Journal: Br J Cancer Date: 2020-05-18 Impact factor: 7.640