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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Artículo Open Access |
| Published: |
Wiley
2024
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| Online Access: | https://pathsocjournals.onlinelibrary.wiley.com/doi/10.1002/path.6274 |
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| _version_ | 1867013295324528640 |
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| author | Xiao Li Jeffrey Eastham Jennifer M Giltnane Wei Zou Andries Zijlstra Evgeniy Tabatsky Romain Banchereau Ching‐Wei Chang Barzin Y Nabet Namrata S Patil Luciana Molinero Steve Chui Maureen Harryman Shari Lau Linda Rangell Yannick Waumans Mark Kockx Darya Orlova Hartmut Koeppen |
| author_facet | Xiao Li Jeffrey Eastham Jennifer M Giltnane Wei Zou Andries Zijlstra Evgeniy Tabatsky Romain Banchereau Ching‐Wei Chang Barzin Y Nabet Namrata S Patil Luciana Molinero Steve Chui Maureen Harryman Shari Lau Linda Rangell Yannick Waumans Mark Kockx Darya Orlova Hartmut Koeppen Xiao Li Jeffrey Eastham Jennifer M Giltnane Wei Zou Andries Zijlstra Evgeniy Tabatsky Romain Banchereau Ching‐Wei Chang Barzin Y Nabet Namrata S Patil Luciana Molinero Steve Chui Maureen Harryman Shari Lau Linda Rangell Yannick Waumans Mark Kockx Darya Orlova Hartmut Koeppen |
| collection | Wiley Open Access |
| contents | Automated tumor immunophenotyping predicts clinical benefit from anti‐PD‐L1 immunotherapy Xiao Li Jeffrey Eastham Jennifer M Giltnane Wei Zou Andries Zijlstra Evgeniy Tabatsky Romain Banchereau Ching‐Wei Chang Barzin Y Nabet Namrata S Patil Luciana Molinero Steve Chui Maureen Harryman Shari Lau Linda Rangell Yannick Waumans Mark Kockx Darya Orlova Hartmut Koeppen The Journal of Pathology Abstract 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. 10.1002/path.6274 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| doi_str_mv | 10.1002/path.6274 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_path_6274 |
| institution | Wiley Open Access |
| license_str_mv | http://onlinelibrary.wiley.com/termsAndConditions#vor |
| publishDate | 2024 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Automated tumor immunophenotyping predicts clinical benefit from anti‐PD‐L1 immunotherapy Xiao Li Jeffrey Eastham Jennifer M Giltnane Wei Zou Andries Zijlstra Evgeniy Tabatsky Romain Banchereau Ching‐Wei Chang Barzin Y Nabet Namrata S Patil Luciana Molinero Steve Chui Maureen Harryman Shari Lau Linda Rangell Yannick Waumans Mark Kockx Darya Orlova Hartmut Koeppen The Journal of Pathology Automated tumor immunophenotyping predicts clinical benefit from anti‐PD‐L1 immunotherapy Xiao Li Jeffrey Eastham Jennifer M Giltnane Wei Zou Andries Zijlstra Evgeniy Tabatsky Romain Banchereau Ching‐Wei Chang Barzin Y Nabet Namrata S Patil Luciana Molinero Steve Chui Maureen Harryman Shari Lau Linda Rangell Yannick Waumans Mark Kockx Darya Orlova Hartmut Koeppen The Journal of Pathology Abstract 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. 10.1002/path.6274 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| title | Automated tumor immunophenotyping predicts clinical benefit from anti‐PD‐L1 immunotherapy |
| topic | The Journal of Pathology |
| url | https://pathsocjournals.onlinelibrary.wiley.com/doi/10.1002/path.6274 |