4.7 Article

A cytokine and angiogenic factor (CAF) analysis in plasma for selection of sorafenib therapy in patients with metastatic renal cell carcinoma

Journal

ANNALS OF ONCOLOGY
Volume 23, Issue 1, Pages 46-52

Publisher

ELSEVIER
DOI: 10.1093/annonc/mdr047

Keywords

CAF profiling; interferon; RCC combinations; renal cell carcinoma; sorafenib

Categories

Funding

  1. U.S. National Cancer Institute
  2. institutional start-up funds
  3. Damon Runyon Cancer Research Foundation [CI 24-04]
  4. Center for Clinical and Translational Sciences
  5. National Institutes of Health from the National Center for Research Resources [KL2 RR0224149]

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Background: We investigated cytokines and angiogenic factors (CAFs) in patients with metastatic renal cell carcinoma (mRCC) treated in a randomized phase II clinical trial of sorafenib versus sorafenib+ interferon-alpha (IFN-alpha) that yielded no differences in progression-free survival (PFS). We aimed to link the CAF profile to PFS and select candidate predictive and prognostic markers for further study. Methods: The concentrations of 52 plasma CAFs were measured pretreatment (n = 69), day 28, and day 56 using multiplex bead arrays and enzyme-linked immunosorbent assay. We investigated the association between baseline levels of CAFs with PFS and posttreatment changes. Results: Unsupervised CAF clustering analysis revealed two distinct mRCC patient groups with elevated proangiogenic or proinflammatory mediators. A six-marker baseline CAF signature [osteopontin, vascular endothelial growth factor (VEGF), carbonic anhydrase 9, collagen IV, VEGF receptor-2, and tumor necrosis factor-related apoptosis-inducing ligand] correlated with PFS benefit (hazard ratio 0.20 versus 2.25, signature negative versus positive, respectively; P = 0.0002). While changes in angiogenic factors were frequently attenuated by the sorafenib+ IFN combination, most key immunomodulatory mediators increased. Conclusions: Using CAF profiling, we identified two mRCC patient groups, a candidate plasma signature for predicting PFS benefit, and distinct marker changes occurring with each treatment. This platform may provide valuable insights into renal cell carcinoma biology and the molecular consequences of targeted therapies.

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