Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma
Introduction: Treatment with Sunitinib, a potent multitargeted receptor tyrosine kinase inhibitor (TKI) has increased the progression-free survival (PFS) and overall-survival (OS) of patients with metastasized renal cell carcinoma (mRCC). With modest OS improvement and variable response and toxicity...
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Elsevier
2025-02-01
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| Series: | Neoplasia: An International Journal for Oncology Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1476558624001490 |
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| author | Jeannette C. Oosterwijk-Wakka Liesbeth Houkes Loes F.M. van der Zanden Lambertus A.L.M. Kiemeney Kerstin Junker Anne Y Warren Tim Eisen Ulrich Jaehde Marius T Radu Rob Ruijtenbeek Egbert Oosterwijk |
| author_facet | Jeannette C. Oosterwijk-Wakka Liesbeth Houkes Loes F.M. van der Zanden Lambertus A.L.M. Kiemeney Kerstin Junker Anne Y Warren Tim Eisen Ulrich Jaehde Marius T Radu Rob Ruijtenbeek Egbert Oosterwijk |
| author_sort | Jeannette C. Oosterwijk-Wakka |
| collection | DOAJ |
| description | Introduction: Treatment with Sunitinib, a potent multitargeted receptor tyrosine kinase inhibitor (TKI) has increased the progression-free survival (PFS) and overall-survival (OS) of patients with metastasized renal cell carcinoma (mRCC). With modest OS improvement and variable response and toxicity predictive and/or prognostic biomarkers are needed to personalize patient management: Prediction of individual TKI therapy response and resistance will increase successful treatment outcome while reducing unnecessary drug use and expense. The aim of this study was to investigate whether kinase activity analysis can predict sunitinib response and/or toxicity using tissue samples obtained from primary clear cell RCC (ccRCC) from a cohort of clinically annotated patients with mRCC receiving sunitinib as first-line treatment. Materials and Methods: EuroTARGET partners collected ccRCC and matched normal kidney tissue samples immediately after surgery, snap-frozen and stored at -80°C until use. Phosphotyrosine-activity profiling was performed using PamChip® peptide microarrays (144 peptides derived from known phosphorylation sites in Protein Tyrosine Kinase substrates) of lysed tissue samples (5 µg protein input) of 163 mRCC patients. Evolve software Was used to analyze kinome profiles and Bionavigator was used for unsupervised and supervised clustering. The kinexus kinase predictor (www.phosphonet.ca) was used to analyze the peptide lists within the clusters. Results: Kinome data was available from 94 patients who received sunitinib as 1st-line treatment and had complete follow-up of their clinical data (PFS, OS and toxicity) for at least 6 months. Matched normal tissue was available from 14 mRCC patients. Supervised clustering of basal kinome activity could correctly classify mRCC patients with PFS >9 months versus PFS<9 months with an accuracy of 61 %. Unsupervised hierarchical clustering revealed 3 major clusters related to immune signaling, VEGF pathway, and immune signaling/cell adhesion. Basal kinase activity levels of patients with short PFS were substantially higher compared to patients who experienced extended PFS. Discussion/Conclusion: Based on kinase levels ccRCC tumors can be subdivided into 3 clusters which may reflect the aggressiveness of these tumors. The accuracy of response prediction of 61 % based on basal kinase levels is too low to justify implementation. STK assays may help to predict sunitinib toxicity and guide clinical management. Additionally, it is possible that mRCC patients with an immune kinase signature are better checkpoint inhibitor candidates, but this needs to be studied. |
| format | Article |
| id | doaj-art-34569442762947d7a1b56e4a2d8e1477 |
| institution | Kabale University |
| issn | 1476-5586 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neoplasia: An International Journal for Oncology Research |
| spelling | doaj-art-34569442762947d7a1b56e4a2d8e14772025-02-03T04:16:33ZengElsevierNeoplasia: An International Journal for Oncology Research1476-55862025-02-0160101108Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell CarcinomaJeannette C. Oosterwijk-Wakka0Liesbeth Houkes1Loes F.M. van der Zanden2Lambertus A.L.M. Kiemeney3Kerstin Junker4Anne Y Warren5Tim Eisen6Ulrich Jaehde7Marius T Radu8Rob Ruijtenbeek9Egbert Oosterwijk10Radboud University Medical Center, 6525 GA, Nijmegen, the Netherlands; Corresponding author.PamGene International B.V., 5211 HH 's-Hertogenbosch, the NetherlandsRadboud University Medical Center, 6525 GA, Nijmegen, the NetherlandsRadboud University Medical Center, 6525 GA, Nijmegen, the NetherlandsClinic of Urology and Paediatric Urology, Saarland University, 66424 Homburg, GermanyDepartment of Oncology, Cambridge University Hospitals NHS Foundation Trust and Cambridge Biomedical Research Centre, Cambridge CB2 0QQ, UKDepartment of Histopathology, Cambridge University Hospitals NHS Foundation Trust and Cambridge Biomedical Campus, Cambridge CB2 0QQ, UKCESAR Central Office, CESAR Central European Society for Anticancer Drug Research-EWIV, 1010, Vienna, AustriaUniversity of Medicine and Pharmacy Carol Davila 050474, Bucharest, RomaniaPamGene International B.V., 5211 HH 's-Hertogenbosch, the NetherlandsRadboud University Medical Center, 6525 GA, Nijmegen, the NetherlandsIntroduction: Treatment with Sunitinib, a potent multitargeted receptor tyrosine kinase inhibitor (TKI) has increased the progression-free survival (PFS) and overall-survival (OS) of patients with metastasized renal cell carcinoma (mRCC). With modest OS improvement and variable response and toxicity predictive and/or prognostic biomarkers are needed to personalize patient management: Prediction of individual TKI therapy response and resistance will increase successful treatment outcome while reducing unnecessary drug use and expense. The aim of this study was to investigate whether kinase activity analysis can predict sunitinib response and/or toxicity using tissue samples obtained from primary clear cell RCC (ccRCC) from a cohort of clinically annotated patients with mRCC receiving sunitinib as first-line treatment. Materials and Methods: EuroTARGET partners collected ccRCC and matched normal kidney tissue samples immediately after surgery, snap-frozen and stored at -80°C until use. Phosphotyrosine-activity profiling was performed using PamChip® peptide microarrays (144 peptides derived from known phosphorylation sites in Protein Tyrosine Kinase substrates) of lysed tissue samples (5 µg protein input) of 163 mRCC patients. Evolve software Was used to analyze kinome profiles and Bionavigator was used for unsupervised and supervised clustering. The kinexus kinase predictor (www.phosphonet.ca) was used to analyze the peptide lists within the clusters. Results: Kinome data was available from 94 patients who received sunitinib as 1st-line treatment and had complete follow-up of their clinical data (PFS, OS and toxicity) for at least 6 months. Matched normal tissue was available from 14 mRCC patients. Supervised clustering of basal kinome activity could correctly classify mRCC patients with PFS >9 months versus PFS<9 months with an accuracy of 61 %. Unsupervised hierarchical clustering revealed 3 major clusters related to immune signaling, VEGF pathway, and immune signaling/cell adhesion. Basal kinase activity levels of patients with short PFS were substantially higher compared to patients who experienced extended PFS. Discussion/Conclusion: Based on kinase levels ccRCC tumors can be subdivided into 3 clusters which may reflect the aggressiveness of these tumors. The accuracy of response prediction of 61 % based on basal kinase levels is too low to justify implementation. STK assays may help to predict sunitinib toxicity and guide clinical management. Additionally, it is possible that mRCC patients with an immune kinase signature are better checkpoint inhibitor candidates, but this needs to be studied.http://www.sciencedirect.com/science/article/pii/S1476558624001490Renal Cell CarcinomaTKIbiomarkerkinase activity |
| spellingShingle | Jeannette C. Oosterwijk-Wakka Liesbeth Houkes Loes F.M. van der Zanden Lambertus A.L.M. Kiemeney Kerstin Junker Anne Y Warren Tim Eisen Ulrich Jaehde Marius T Radu Rob Ruijtenbeek Egbert Oosterwijk Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma Neoplasia: An International Journal for Oncology Research Renal Cell Carcinoma TKI biomarker kinase activity |
| title | Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma |
| title_full | Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma |
| title_fullStr | Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma |
| title_full_unstemmed | Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma |
| title_short | Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma |
| title_sort | kinomic profiling to predict sunitinib response of patients with metastasized clear cell renal cell carcinoma |
| topic | Renal Cell Carcinoma TKI biomarker kinase activity |
| url | http://www.sciencedirect.com/science/article/pii/S1476558624001490 |
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