A Reum Kim1, Kyu Sung Choi1, Min-Sung Kim2,3, Kyung-Min Kim2,3, Ho Kang2,3, Sojin Kim2,3, Tamrin Chowdhury2,3, Hyeon Jong Yu2,3, Chae Eun Lee2,3, Joo Ho Lee3,4, Soon-Tae Lee3,5, Jae Kyung Won3,6, Jin Wook Kim2,3, Yong-Hwy Kim2,3, Tae Min Kim3,7, Sung-Hye Park3,6, Seung Hong Choi8,9, Eui-Cheol Shin10, Chul-Kee Park11,12. 1. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea. 2. Department of Neurosurgery, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. 3. Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. 4. Department of Radiation Oncology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. 5. Department of Neurology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. 6. Department of Pathology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. 7. Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. 8. Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. verocay@snuh.org. 9. Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. verocay@snuh.org. 10. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea. ecshin@kaist.ac.kr. 11. Department of Neurosurgery, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. nsckpark@snu.ac.kr. 12. Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. nsckpark@snu.ac.kr.
Abstract
PURPOSE: To understand the tumor immune microenvironment precisely, it is important to secure the quantified data of tumor-infiltrating immune cells, since the immune cells are true working unit. We analyzed unit immune cell number per unit volume of core tumor tissue of high-grade gliomas (HGG) to correlate their immune microenvironment characteristics with clinical prognosis and radiomic signatures. METHODS: The number of tumor-infiltrating immune cells from 64 HGG core tissue were analyzed using flow cytometry and standardized. After sorting out patient groups according to diverse immune characteristics, the groups were tested if they have any clinical prognostic relevance and specific radiomic signature relationships. Sparse partial least square with discriminant analysis using multimodal magnetic resonance images was employed for all radiomic classifications. RESULTS: The median number of CD45 + cells per one gram of HGG core tissue counted 865,770 cells which was equivalent to 8.0% of total cells including tumor cells. There was heterogeneity in the distribution of immune cell subpopulations among patients. Overall survival was significantly better in T cell-deficient group than T cell-enriched group (p = 0.019), and T8 dominant group than T4 dominant group (p = 0.023). The number of tumor-associated macrophages (TAM) and M2-TAM was significantly decreased in isocitrate dehydrogenase mutated HGG. Radiomic signature classification showed good performance in predicting immune phenotypes especially with features extracted from apparent diffusion coefficient maps. CONCLUSIONS: Absolute quantification of tumor-infiltrating immune cells confirmed the heterogeneity of immune microenvironment in HGG which harbors prognostic impact. This immune microenvironment could be predicted by radiomic signatures non-invasively.
PURPOSE: To understand the tumor immune microenvironment precisely, it is important to secure the quantified data of tumor-infiltrating immune cells, since the immune cells are true working unit. We analyzed unit immune cell number per unit volume of core tumor tissue of high-grade gliomas (HGG) to correlate their immune microenvironment characteristics with clinical prognosis and radiomic signatures. METHODS: The number of tumor-infiltrating immune cells from 64 HGG core tissue were analyzed using flow cytometry and standardized. After sorting out patient groups according to diverse immune characteristics, the groups were tested if they have any clinical prognostic relevance and specific radiomic signature relationships. Sparse partial least square with discriminant analysis using multimodal magnetic resonance images was employed for all radiomic classifications. RESULTS: The median number of CD45 + cells per one gram of HGG core tissue counted 865,770 cells which was equivalent to 8.0% of total cells including tumor cells. There was heterogeneity in the distribution of immune cell subpopulations among patients. Overall survival was significantly better in T cell-deficient group than T cell-enriched group (p = 0.019), and T8 dominant group than T4 dominant group (p = 0.023). The number of tumor-associated macrophages (TAM) and M2-TAM was significantly decreased in isocitrate dehydrogenase mutated HGG. Radiomic signature classification showed good performance in predicting immune phenotypes especially with features extracted from apparent diffusion coefficient maps. CONCLUSIONS: Absolute quantification of tumor-infiltrating immune cells confirmed the heterogeneity of immune microenvironment in HGG which harbors prognostic impact. This immune microenvironment could be predicted by radiomic signatures non-invasively.
Authors: Zhenjiang Liu; Qingda Meng; Jiri Bartek; Thomas Poiret; Oscar Persson; Lalit Rane; Elena Rangelova; Christopher Illies; Inti Harvey Peredo; Xiaohua Luo; Martin Vijayakumar Rao; Rebecca Axelsson Robertson; Ernest Dodoo; Markus Maeurer Journal: Oncoimmunology Date: 2016-11-29 Impact factor: 8.110
Authors: P Pouillart; L Schwarzenberg; G Mathé; M Schneider; C Jasmin; M Hayat; R Weiner; F de Vassal; J L Amiel; H P Beyer; S Fajbisowicz Journal: Nouv Presse Med Date: 1972-06-24
Authors: Konrad Gabrusiewicz; Benjamin Rodriguez; Jun Wei; Yuuri Hashimoto; Luke M Healy; Sourindra N Maiti; Ginu Thomas; Shouhao Zhou; Qianghu Wang; Ahmed Elakkad; Brandon D Liebelt; Nasser K Yaghi; Ravesanker Ezhilarasan; Neal Huang; Jeffrey S Weinberg; Sujit S Prabhu; Ganesh Rao; Raymond Sawaya; Lauren A Langford; Janet M Bruner; Gregory N Fuller; Amit Bar-Or; Wei Li; Rivka R Colen; Michael A Curran; Krishna P Bhat; Jack P Antel; Laurence J Cooper; Erik P Sulman; Amy B Heimberger Journal: JCI Insight Date: 2016-02-25
Authors: Enrique Orrego; Carlos A Castaneda; Miluska Castillo; Luis A Bernabe; Sandro Casavilca; Arnab Chakravarti; Wei Meng; Pamela Garcia-Corrochano; Maria R Villa-Robles; Rocio Zevallos; Omar Mejia; Pedro Deza; Carolina Belmar-Lopez; Luis Ojeda Journal: CNS Oncol Date: 2018-10-09