Clinical outcome following checkpoint therapy in renal cell carcinoma is associated with a burst of activated CD8 T cells in blood
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ..
PURPOSE: Checkpoint therapy is now the cornerstone of treatment for patients with renal cell carcinoma (RCC) with advanced disease, but biomarkers are lacking to predict which patients will benefit. This study proposes potential immunological biomarkers that could developed for predicting therapeutic response in patients with RCC.
METHODS: Using flow cytometry, RNA sequencing, and T-cell receptor (TCR) sequencing, we investigated changes in T cells in the peripheral blood of patients with advanced RCC after receiving immunotherapy. We used immunofluorescence (IF) imaging and flow cytometry to investigate how intratumoral T cells in patients' tumors (resected months/years prior to receiving checkpoint therapy) predicted patient outcomes after immunotherapy.
RESULTS: We found that a small proportion of CD4 and CD8 T cells in the blood activate following checkpoint therapy, expressing the proliferation marker Ki67 and activation markers HLA-DR and CD38. Patients who had the highest increase in these HLA-DR +CD38+CD8 T cells after treatment had the best antitumor immune response and experienced clinical benefit. Using RNA sequencing, we found that while these cells expanded in most patients, their phenotype did not drastically change during treatment. However, when we analyzed the TCR repertoire of these HLA-DR +CD38+CD8+T cells, we found that only patients who clinically benefitted had a burst of new clonotypes enter this pool of activated cells. Finally, we found that abundant T cells in the untreated tumors predicted clinical benefit to checkpoint therapy on disease progression.
CONCLUSIONS: Together, these data suggest that having a strong pre-existing immune response and immediate peripheral T-cell activation after checkpoint therapy is a predictor of clinical benefit in patients with RCC.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Journal for immunotherapy of cancer - 10(2022), 7 vom: 25. Juli |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Carlisle, Jennifer Wilkinson [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 25.07.2022 Date Revised 15.11.2023 published: Print Citation Status MEDLINE |
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| doi: |
10.1136/jitc-2022-004803 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM343838168 |
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| 100 | 1 | |a Carlisle, Jennifer Wilkinson |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Clinical outcome following checkpoint therapy in renal cell carcinoma is associated with a burst of activated CD8 T cells in blood |
| 264 | 1 | |c 2022 | |
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| 500 | |a Date Completed 25.07.2022 | ||
| 500 | |a Date Revised 15.11.2023 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a PURPOSE: Checkpoint therapy is now the cornerstone of treatment for patients with renal cell carcinoma (RCC) with advanced disease, but biomarkers are lacking to predict which patients will benefit. This study proposes potential immunological biomarkers that could developed for predicting therapeutic response in patients with RCC | ||
| 520 | |a METHODS: Using flow cytometry, RNA sequencing, and T-cell receptor (TCR) sequencing, we investigated changes in T cells in the peripheral blood of patients with advanced RCC after receiving immunotherapy. We used immunofluorescence (IF) imaging and flow cytometry to investigate how intratumoral T cells in patients' tumors (resected months/years prior to receiving checkpoint therapy) predicted patient outcomes after immunotherapy | ||
| 520 | |a RESULTS: We found that a small proportion of CD4 and CD8 T cells in the blood activate following checkpoint therapy, expressing the proliferation marker Ki67 and activation markers HLA-DR and CD38. Patients who had the highest increase in these HLA-DR +CD38+CD8 T cells after treatment had the best antitumor immune response and experienced clinical benefit. Using RNA sequencing, we found that while these cells expanded in most patients, their phenotype did not drastically change during treatment. However, when we analyzed the TCR repertoire of these HLA-DR +CD38+CD8+T cells, we found that only patients who clinically benefitted had a burst of new clonotypes enter this pool of activated cells. Finally, we found that abundant T cells in the untreated tumors predicted clinical benefit to checkpoint therapy on disease progression | ||
| 520 | |a CONCLUSIONS: Together, these data suggest that having a strong pre-existing immune response and immediate peripheral T-cell activation after checkpoint therapy is a predictor of clinical benefit in patients with RCC | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Biomarkers, Tumor | |
| 650 | 4 | |a CD8-Positive T-Lymphocytes | |
| 650 | 4 | |a Immunotherapy | |
| 650 | 4 | |a Kidney Neoplasms | |
| 650 | 4 | |a Lymphocytes, Tumor-Infiltrating | |
| 650 | 7 | |a HLA-DR Antigens |2 NLM | |
| 650 | 7 | |a Immune Checkpoint Inhibitors |2 NLM | |
| 650 | 7 | |a Receptors, Antigen, T-Cell |2 NLM | |
| 700 | 1 | |a Jansen, Caroline S |e verfasserin |4 aut | |
| 700 | 1 | |a Cardenas, Maria Andrea |e verfasserin |4 aut | |
| 700 | 1 | |a Sobierajska, Ewelina |e verfasserin |4 aut | |
| 700 | 1 | |a Reyes, Adriana Moon |e verfasserin |4 aut | |
| 700 | 1 | |a Greenwald, Rachel |e verfasserin |4 aut | |
| 700 | 1 | |a Del Balzo, Luke |e verfasserin |4 aut | |
| 700 | 1 | |a Prokhnevska, Nataliya |e verfasserin |4 aut | |
| 700 | 1 | |a Kucuk, Omer |e verfasserin |4 aut | |
| 700 | 1 | |a Carthon, Bradley C |e verfasserin |4 aut | |
| 700 | 1 | |a Mullane, Patrick Connor |e verfasserin |4 aut | |
| 700 | 1 | |a Osunkoya, Adeboye |e verfasserin |4 aut | |
| 700 | 1 | |a Baumgarten, Deborah |e verfasserin |4 aut | |
| 700 | 1 | |a Hosseinzadeh, Fares |e verfasserin |4 aut | |
| 700 | 1 | |a Wilkinson, Scott |e verfasserin |4 aut | |
| 700 | 1 | |a Lake, Ross |e verfasserin |4 aut | |
| 700 | 1 | |a Sowalsky, Adam G |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Yuan |e verfasserin |4 aut | |
| 700 | 1 | |a Master, Viraj A |e verfasserin |4 aut | |
| 700 | 1 | |a Bilen, Mehmet A |e verfasserin |4 aut | |
| 700 | 1 | |a Kissick, Haydn |e verfasserin |4 aut | |
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