Väyrynen, J. P., Lau, M. C., Haruki, K., Väyrynen, S. A., Dias Costa, A., Borowsky, J., Zhao, M., Fujiyoshi, K., Arima, K., Twombly, T. S., Kishikawa, J., Gu, S., Aminmozaffari, S., Shi, S., Baba, Y., Akimoto, N., Ugai, T., Da Silva, A., Song, M., … Nowak, J. A. (2020). Prognostic Significance of Immune Cell Populations Identified by Machine Learning in Colorectal Cancer Using Routine Hematoxylin and Eosin–Stained Sections. Clinical Cancer Research, 26(16), 4326–4338. https://doi.org/10.1158/1078-0432.ccr-20-0071
Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin and eosin–stained sections
|Author:||Väyrynen, Juha P.1,2,3; Lau, Mai Chan2; Haruki, Koichiro2,4;|
1Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA
2Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
3Cancer and Translational Medicine Research Unit, Medical Research Center Oulu, Oulu University Hospital, and University of Oulu, Oulu, Finland
4Department of Surgery, The Jikei University School of Medicine, Tokyo, Japan
5Conjoint Gastroenterology Department, QIMR Berghofer Medical Research Institute, Queensland, Australia
6Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
7Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
8Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA
9Division of Gastroenterology, Massachusetts General Hospital, Boston, MA
10Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
11Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA
12Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
13Yale Cancer Center, New Haven, CT
14Department of Medicine, Yale School of Medicine, New Haven, CT
15Smilow Cancer Hospital, New Haven, CT
16Broad Institute of MIT and Harvard, Cambridge, MA
17Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
18Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA;
19Cancer Immunology and Cancer Epidemiology Programs, Dana-Farber Harvard Cancer Center, Boston, MA
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021042611913
American Association for Cancer Research,
|Publish Date:|| 2021-05-21
Purpose: Although high T-cell density is a well-established favorable prognostic factor in colorectal cancer, the prognostic significance of tumor-associated plasma cells, neutrophils, and eosinophils is less well-defined.
Experimental Design: We computationally processed digital images of hematoxylin and eosin (H&E)–stained sections to identify lymphocytes, plasma cells, neutrophils, and eosinophils in tumor intraepithelial and stromal areas of 934 colorectal cancers in two prospective cohort studies. Multivariable Cox proportional hazards regression was used to compute mortality HR according to cell density quartiles. The spatial patterns of immune cell infiltration were studied using the GTumor:Immune cell function, which estimates the likelihood of any tumor cell in a sample having at least one neighboring immune cell of the specified type within a certain radius. Validation studies were performed on an independent cohort of 570 colorectal cancers.
Results: Immune cell densities measured by the automated classifier demonstrated high correlation with densities both from manual counts and those obtained from an independently trained automated classifier (Spearman’s ρ 0.71–0.96). High densities of stromal lymphocytes and eosinophils were associated with better cancer-specific survival [Ptrend < 0.001; multivariable HR (4th vs 1st quartile of eosinophils), 0.49; 95% confidence interval, 0.34–0.71]. High GTumor:Lymphocyte area under the curve (AUC0,20μm; Ptrend = 0.002) and high GTumor:Eosinophil AUC0,20μm (Ptrend < 0.001) also showed associations with better cancer-specific survival. High stromal eosinophil density was also associated with better cancer-specific survival in the validation cohort (Ptrend < 0.001).
Conclusions: These findings highlight the potential for machine learning assessment of H&E-stained sections to provide robust, quantitative tumor-immune biomarkers for precision medicine.
Clinical cancer research
|Pages:||4326 - 4338|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
This work was supported by U.S. NIH grants (P01 CA87969 to M.J. Stampfer; UM1 CA186107 to M.J. Stampfer; P01 CA55075 to W.C. Willett; UM1 CA167552 to W.C. Willett; U01 CA167552 to W.C. Willett and L.A. Mucci; P50 CA127003 to C.S. Fuchs; R01 CA118553 to C.S. Fuchs; R01 CA169141 to C.S. Fuchs; R01 CA137178 to A.T. Chan; K24 DK098311 to A.T. Chan; R35 CA197735 to S. Ogino; R01 CA151993 to S. Ogino; K07 CA190673 to R. Nishihara; R03 CA197879 to K. Wu; R21 CA222940 to K. Wu and M. Giannakis; and R21 CA230873 to K. Wu and S. Ogino); by Cancer Research UK Grand Challenge Award (OPTIMISTICC, UK C10674/A27140 to M. Giannakis and S. Ogino); by Nodal Award (2016-02) from the Dana-Farber Harvard Cancer Center (to S. Ogino); by the Stand Up to Cancer Colorectal Cancer Dream Team Translational Research Grant (SU2C-AACR-DT22-17 to C.S. Fuchs and M. Giannakis), administered by the American Association for Cancer Research, a scientific partner of SU2C; and by grants from the Project P Fund, The Friends of the Dana-Farber Cancer Institute, Bennett Family Fund, and the Entertainment Industry Foundation through National Colorectal Cancer Research Alliance. K. Haruki was supported by fellowship grants from the Uehara Memorial Foundation and the Mitsukoshi Health and Welfare Foundation. S.A. Väyrynen was supported by grants from the Finnish Cultural Foundation and Orion Research Foundation sr. J. Borowsky was supported by a grant from the Australia Awards-Endeavour Scholarships and Fellowships Program. K. Fujiyoshi was supported by a fellowship grant from the Uehara Memorial Foundation. K. Arima was supported by grants from Overseas Research Fellowship from Japan Society for the Promotion of Science (JP201860083). K. Wu was supported by an Investigator Initiated Grant from the American Institute for Cancer Research (AICR). M. Giannakis was supported by a Conquer Cancer Foundation of ASCO Career Development Award. A.T. Chan is a Stuart and Suzanne Steele MGH Research Scholar.
© 2020 American Association for Cancer Research.