Circulating kidney injury molecule-1 (KIM-1) in association with kidney injury biomarkers and outcomes in metastatic renal cell carcinoma.

C Clara Steiner (University Hospital Leipzig, Leipzig, Germany) E Eddy Saad R Renee Maria Saliby (Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT) M Marc Eid (Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA) K Karl Semaan (Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA) M Marc Machaalani E Emre Yekedüz J Jack T. Horst (Dana-Farber Cancer Institute, Boston, MA) J Jasmine Lee (Dana-Farber Cancer Institute, Boston, MA) N Noa Phillips (Dana-Farber Cancer Institute, Boston, MA) R Rachel Trowbridge (Dana-Farber Cancer Institute, Boston, MA) M Marta Pirovano (Dana-Farber Cancer Institute, Boston, MA) C Carolina Saldanha Neves Horta Lima (Brigham and Women's Hospital, Boston, MA) S Shruti Gupta (Department of Anatomy and Cell Biology, The George Washington University) G Gwo-Shu Mary Lee (Dana-Farber Cancer Institute, Boston, MA) Y Yehonatan Elon (Oncohost Ltd, Binyamina, Israel) A Adam P. Dicker J Joseph Bonventre (Brigham and Women's Hospital, Boston, MA) T Toni K. Choueiri (Department of Medical Oncology Dana‐Farber Cancer Institute Boston Massachusetts USA) W Wenxin Xu (Department of Medical Oncology Dana‐Farber Cancer Institute Boston Massachusetts USA)

Abstract

582 Background: Kidney injury molecule-1 (KIM-1) is overexpressed in clear cell and papillary renal cell carcinoma (RCC) and in proximal tubular kidney injury. While circulating KIM-1 is a minimally invasive biomarker for RCC, it is unknown whether kidney disease, a common comorbidity among RCC patients, impacts the association of KIM-1 with RCC outcomes. We evaluated the association between KIM-1 and outcomes in metastatic RCC after adjustment for multiple kidney injury biomarkers using plasma proteomics. Methods: Plasma samples from patients with metastatic clear cell and papillary RCC were obtained prior to 1 st line systemic therapy. Samples were analyzed using a high-throughput aptamer-based proteomics assay (SomaLogic), and results were log-transformed for analysis. Clinical and laboratory data, as well as cancer outcomes, were retrospectively curated. Spearman’s ρ was used to evaluate correlations between circulating KIM-1 and kidney injury biomarkers (cystatin C, TNFR1, TNFR2, eGFR). Cox regression analyses were used to evaluate the association between KIM-1 as a continuous variable and overall survival (OS) and progression-free survival (PFS), after adjusting for kidney injury biomarkers. Performance of KIM-1 tertiles versus IMDC risk groups for prognosticating OS was evaluated using the C-index. Results: Among 210 patients, higher baseline KIM-1 was associated with worse PFS (p = 0.004) and OS (p < 0.001) in univariate Cox regression analysis (Table). The prognostic value of KIM-1 was consistent across clear cell and papillary RCC (p-value for interaction = 0.98). KIM-1 remained prognostic for PFS (p = 0.01) and OS (p < 0.001) after multivariable adjustment for kidney injury biomarkers and eGFR (Table). Median follow-up was 22.1 months. Kidney injury biomarkers (cystatin C, TNFR1, TNFR2, eGFR) were correlated with each other but not with plasma KIM-1. KIM-1 tertiles (high/medium/low) were more prognostic for OS than the IMDC risk groups (C-index, KIM-1 0.63 vs. IMDC groups 0.58) and the addition of KIM-1 to the IMDC model improved its performance (C-index, KIM-1 + IMDC groups 0.64). Conclusions: Plasma KIM-1 was associated with PFS and OS in metastatic clear cell and papillary RCC. Plasma KIM-1 was not correlated with kidney injury biomarkers, suggesting that at least in metastatic RCC, circulating KIM-1 derives predominantly from tumor rather than benign kidney. The addition of KIM-1 improves IMDC model performance and may be useful for risk prognostication in RCC. Association of KIM-1 with PFS and OS in metastatic RCC. Multivariable models are adjusted for kidney injury markers (cystatin C, TNFR1, TNFR2) and eGFR. log KIM-1 HR (95% CI) p-value OS (univariate) 1.4 (1.2 – 1.7) <0.001*** PFS (univariate) 1.2 (1.1 – 1.4) 0.004** OS (multivariate) 1.4 (1.2 – 1.6) <0.001*** PFS (multivariate) 1.2 (1.1 – 1.3) 0.01**

Article Details

Volume / Issue Vol. 43, Issue 5_suppl
Published February 10, 2025
Pages 582-582
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (20)

C

Clara Steiner

University Hospital Leipzig, Leipzig, Germany

E

Eddy Saad

R

Renee Maria Saliby

Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT

M

Marc Eid

Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA

K

Karl Semaan

Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA

M

Marc Machaalani

E

Emre Yekedüz

J

Jack T. Horst

Dana-Farber Cancer Institute, Boston, MA

J

Jasmine Lee

Dana-Farber Cancer Institute, Boston, MA

N

Noa Phillips

Dana-Farber Cancer Institute, Boston, MA

R

Rachel Trowbridge

Dana-Farber Cancer Institute, Boston, MA

M

Marta Pirovano

Dana-Farber Cancer Institute, Boston, MA

C

Carolina Saldanha Neves Horta Lima

Brigham and Women's Hospital, Boston, MA

S

Shruti Gupta

Department of Anatomy and Cell Biology, The George Washington University

G

Gwo-Shu Mary Lee

Dana-Farber Cancer Institute, Boston, MA

Y

Yehonatan Elon

Oncohost Ltd, Binyamina, Israel

A

Adam P. Dicker

J

Joseph Bonventre

Brigham and Women's Hospital, Boston, MA

T

Toni K. Choueiri

Department of Medical Oncology Dana‐Farber Cancer Institute Boston Massachusetts USA

W

Wenxin Xu

Department of Medical Oncology Dana‐Farber Cancer Institute Boston Massachusetts USA