KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response
Current methods for biomarker discovery and target identification in immuno-oncology rely on static snapshots of tumor immunity. To thoroughly characterize the temporal nature of antitumor immune responses, we developed a 34-parameter spectral flow cytometry panel and performed high-throughput analy...
| Main Authors: | , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2023-09-01
|
| Series: | Journal for ImmunoTherapy of Cancer |
| Online Access: | https://jitc.bmj.com/content/11/9/e006782.full |
| _version_ | 1797669539183329280 |
|---|---|
| author | Charles G Drake Benjamin Izar Casey R Ager Aleksandar Obradovic Matthew Chaimowitz Catherine Spina Mingxuan Zhang Shruti Bansal Somnath Tagore Collin Jugler Meri Rogava Johannes C Melms Patrick McCann Matthew C Dallos |
| author_facet | Charles G Drake Benjamin Izar Casey R Ager Aleksandar Obradovic Matthew Chaimowitz Catherine Spina Mingxuan Zhang Shruti Bansal Somnath Tagore Collin Jugler Meri Rogava Johannes C Melms Patrick McCann Matthew C Dallos |
| author_sort | Charles G Drake |
| collection | DOAJ |
| description | Current methods for biomarker discovery and target identification in immuno-oncology rely on static snapshots of tumor immunity. To thoroughly characterize the temporal nature of antitumor immune responses, we developed a 34-parameter spectral flow cytometry panel and performed high-throughput analyses in critical contexts. We leveraged two distinct preclinical models that recapitulate cancer immunoediting (NPK-C1) and immune checkpoint blockade (ICB) response (MC38), respectively, and profiled multiple relevant tissues at and around key inflection points of immune surveillance and escape and/or ICB response. Machine learning-driven data analysis revealed a pattern of KLRG1 expression that uniquely identified intratumoral effector CD4 T cell populations that constitutively associate with tumor burden across tumor models, and are lost in tumors undergoing regression in response to ICB. Similarly, a Helios-KLRG1+ subset of tumor-infiltrating regulatory T cells was associated with tumor progression from immune equilibrium to escape and was also lost in tumors responding to ICB. Validation studies confirmed KLRG1 signatures in human tumor-infiltrating CD4 T cells associate with disease progression in renal cancer. These findings nominate KLRG1+ CD4 T cell populations as subsets for further investigation in cancer immunity and demonstrate the utility of longitudinal spectral flow profiling as an engine of dynamic biomarker discovery. |
| first_indexed | 2024-03-11T20:45:52Z |
| format | Article |
| id | doaj.art-e9829ce92dbf4e9c97cb167d068ea152 |
| institution | Directory Open Access Journal |
| issn | 2051-1426 |
| language | English |
| last_indexed | 2024-03-11T20:45:52Z |
| publishDate | 2023-09-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | Journal for ImmunoTherapy of Cancer |
| spelling | doaj.art-e9829ce92dbf4e9c97cb167d068ea1522023-10-01T16:00:06ZengBMJ Publishing GroupJournal for ImmunoTherapy of Cancer2051-14262023-09-0111910.1136/jitc-2023-006782KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy responseCharles G Drake0Benjamin Izar1Casey R Ager2Aleksandar Obradovic3Matthew Chaimowitz4Catherine Spina5Mingxuan Zhang6Shruti Bansal7Somnath Tagore8Collin Jugler9Meri Rogava10Johannes C Melms11Patrick McCann12Matthew C Dallos13Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, New York, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USADepartment of Radiation Oncology, Columbia University Irving Medical Center, New York, New York, USAColumbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, New York, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USAColumbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, New York, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USADepartment of Immunology, Mayo Clinic Arizona, Scottsdale, Arizona, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USAColumbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, New York, USADepartment of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, New York, USACurrent methods for biomarker discovery and target identification in immuno-oncology rely on static snapshots of tumor immunity. To thoroughly characterize the temporal nature of antitumor immune responses, we developed a 34-parameter spectral flow cytometry panel and performed high-throughput analyses in critical contexts. We leveraged two distinct preclinical models that recapitulate cancer immunoediting (NPK-C1) and immune checkpoint blockade (ICB) response (MC38), respectively, and profiled multiple relevant tissues at and around key inflection points of immune surveillance and escape and/or ICB response. Machine learning-driven data analysis revealed a pattern of KLRG1 expression that uniquely identified intratumoral effector CD4 T cell populations that constitutively associate with tumor burden across tumor models, and are lost in tumors undergoing regression in response to ICB. Similarly, a Helios-KLRG1+ subset of tumor-infiltrating regulatory T cells was associated with tumor progression from immune equilibrium to escape and was also lost in tumors responding to ICB. Validation studies confirmed KLRG1 signatures in human tumor-infiltrating CD4 T cells associate with disease progression in renal cancer. These findings nominate KLRG1+ CD4 T cell populations as subsets for further investigation in cancer immunity and demonstrate the utility of longitudinal spectral flow profiling as an engine of dynamic biomarker discovery.https://jitc.bmj.com/content/11/9/e006782.full |
| spellingShingle | Charles G Drake Benjamin Izar Casey R Ager Aleksandar Obradovic Matthew Chaimowitz Catherine Spina Mingxuan Zhang Shruti Bansal Somnath Tagore Collin Jugler Meri Rogava Johannes C Melms Patrick McCann Matthew C Dallos KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response Journal for ImmunoTherapy of Cancer |
| title | KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response |
| title_full | KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response |
| title_fullStr | KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response |
| title_full_unstemmed | KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response |
| title_short | KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response |
| title_sort | klrg1 marks tumor infiltrating cd4 t cell subsets associated with tumor progression and immunotherapy response |
| url | https://jitc.bmj.com/content/11/9/e006782.full |
| work_keys_str_mv | AT charlesgdrake klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT benjaminizar klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT caseyrager klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT aleksandarobradovic klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT matthewchaimowitz klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT catherinespina klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT mingxuanzhang klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT shrutibansal klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT somnathtagore klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT collinjugler klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT merirogava klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT johannescmelms klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT patrickmccann klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse AT matthewcdallos klrg1markstumorinfiltratingcd4tcellsubsetsassociatedwithtumorprogressionandimmunotherapyresponse |