Automated tumor immunophenotyping predicts clinical benefit from anti‐PD‐L1 immunotherapy

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if den...

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Bibliographic Details
Published in:	The Journal of pathology Vol. 263; no. 2; pp. 190 - 202
Main Authors:	Li, Xiao, Eastham, Jeffrey, Giltnane, Jennifer M, Zou, Wei, Zijlstra, Andries, Tabatsky, Evgeniy, Banchereau, Romain, Chang, Ching‐Wei, Nabet, Barzin Y, Patil, Namrata S, Molinero, Luciana, Chui, Steve, Harryman, Maureen, Lau, Shari, Rangell, Linda, Waumans, Yannick, Kockx, Mark, Orlova, Darya, Koeppen, Hartmut
Format:	Journal Article
Language:	English
Published:	Chichester, UK John Wiley & Sons, Ltd 01-06-2024 Wiley Subscription Services, Inc
Subjects:	anti‐PD‐L1 immunotherapy Apoptosis artificial intelligence Automation Automation - methods B7-H1 Antigen - antagonists & inhibitors Biomarkers Biomarkers, Tumor - analysis Breast cancer Cancer Cancer immunotherapy Carcinoma, Non-Small-Cell Lung - drug therapy Carcinoma, Non-Small-Cell Lung - immunology Carcinoma, Non-Small-Cell Lung - pathology CD8 antigen CD8+ T cell Cohort Studies Decision making Effector cells Humans immunophenotype Immunophenotyping - methods Immunotherapy Inflammation Lung cancer Malignancy Molecular Targeted Therapy Neoplasms - drug therapy Neoplasms - immunology Neoplasms - pathology non‐small cell lung cancer panCK/CD8 immunohistochemistry PD-L1 protein Small cell lung carcinoma Solid tumors Spatial distribution survival analysis Treatment Outcome Triple Negative Breast Neoplasms - drug therapy Triple Negative Breast Neoplasms - immunology Triple Negative Breast Neoplasms - pathology triple‐negative breast cancer Tumor microenvironment panCK/CD8 immunohistochemistry survival analysis triple‐negative breast cancer immunophenotype anti‐PD‐L1 immunotherapy CD8+ T cell artificial intelligence non‐small cell lung cancer
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Summary:	Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision‐making is still missing. We developed approaches to categorize solid tumors into ‘desert’, ‘excluded’, and ‘inflamed’ types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on ‘manual’ observation is predictive for clinical benefit from anti‐programmed death ligand 1 therapy in two large cohorts of patients with non‐small cell lung cancer or triple‐negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist‐based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.
Bibliography:	These authors contributed equally to this work. Conflict of interest statement: XL, JE, JMG, WZ, AZ, RB, CWC, BYN, NSP, LM, SC, MH, SL, LR, and HK are employees of Genentech, Inc. XL, JE, DO, and HK are inventors on a patent related to automated immunophenotyping of tumors. ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0022-3417 1096-9896 1096-9896
DOI:	10.1002/path.6274