LIF expression as a predictive biomarker in metastatic renal cell carcinoma.

4548 Background: Clear cell renal cell carcinoma (ccRCC) is biologically heterogeneous, and optimal selection between VEGF-targeted and ICI–based therapies remain an unmet clinical need. Leukemia inhibitory factor (LIF), an IL-6 family cytokine implicated in angiogenesis and immune regulation, is associated with poor prognosis in ccRCC; however, its predictive value for treatment selection has not been defined. Methods: Baseline tumor LIF expression was evaluated in 2,026 patients with metastatic ccRCC across 12 clinical and molecular cohorts, including CheckMate 009/010/025/214, JAVELIN Renal 101, IMmotion150, TCGA-KIRC, CPTAC-3, and institutional datasets. RNA-seq data were batch-corrected, normalized, and immune-deconvoluted (CIBERSORTx). Among 1,306 patients with treatment data, 1,058 with complete clinical covariates were included in treatment-by-biomarker interaction analyses. Results: LIF-high tumors (median cutoff) were associated with younger age (60 vs 63 years, p<0.001) and increased sarcomatoid features (17% vs 8%, p<0.001). A significant treatment-by-LIF interaction was observed for progression-free survival (PFS; interaction p=0.006). High LIF expression predicted inferior PFS on TKI monotherapy (HR 1.26, p<0.001), while this adverse association was absent with ICI-based regimens (monotherapy or combination; HR 0.70, p<0.001). No significant interaction was observed for overall survival. LIF expression discriminated progressive disease from disease control (p<0.001). Immune deconvolution revealed that LIF-high tumors exhibited an inflamed but immunosuppressive microenvironment, characterized by enrichment of macrophages (M0 and M2), neutrophils, and regulatory T cells, with preserved CD8⁺ T-cell infiltration. LIF expression correlated strongly with CXCL8 (R=0.45), and more modestly with FGF2 and VEGFA, consistent with VEGF-independent angiogenic signaling. Conclusions: LIF identifies a biologically distinct subset of metastatic ccRCC characterized by angiogenic and immunosuppressive features and poor outcomes with TKI monotherapy. These data support LIF as a predictive biomarker to inform treatment selection and highlight the LIF/CXCL8 axis as a potential therapeutic target in advanced RCC. Treatment-by-LIF interaction analysis for progression-free survival in metastatic clear cell renal cell carcinoma. Groups N HR 95% CI P-value Full Cohort* 1792 1.09 1.01 – 1.14 0.017 Treatment interaction Model § Main effect (LIF in TKI) 1058 1.26 1.108 - 1.443 <0.001 LIF × IObased (IO and IO+IO) 1058 0.70 0.567 - 0.854 <0.001 LIF × IO+VEGF 1058 0.89 0.73 - 1.079 0.230 LIF × MTORi 1058 0.84 0.689 - 1.035 0.104 Stratified Analyses § : TKI Monotherapy 377 1.27 1.114 - 1.455 <0.001 IO/IO+IO 194 0.87 0.741 - 1.03 0.107 IO+VEGF 364 1.15 0.996 - 1.337 0.057 *Adjusted for IMDC, Age, Sex, Sarcomatoid Features, and Treatment modality. § Adjusted for IMDC, Age, Sex, Sarcomatoid Features.

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Journal
Journal of Clinical Oncology
Published
2026-05-27
DOI
https://doi.org/10.1200/jco.2026.44.16_suppl.4548
Primary Topic
Cytokine Signaling Pathways and Interactions
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article
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article

LIF expression as a predictive biomarker in metastatic renal cell carcinoma.

Chris Labaki, Liliana Ascione, Tarek Baroud, Wassim Daoud Khatoun et al.
Journal of Clinical Oncology
Cytokine Signaling Pathways and Interactions
article

LIF expression as a predictive biomarker in metastatic renal cell carcinoma.

Chris Labaki, Liliana Ascione, Tarek Baroud, Wassim Daoud Khatoun, Marc Machaalani, Harry Kane, Mustafa Saleh, Kevin Meli, Eliezer Mendel Van Allen, Ro Malik, Pablo Barrios, Emre Yekeduz, Toni K. Choueiri, Sabina Signoretti, David A. Braun, Renee Maria Saliby, Alexander Gusev, Jad El Masri, Eddy Saad
article en

Abstract

4548 Background: Clear cell renal cell carcinoma (ccRCC) is biologically heterogeneous, and optimal selection between VEGF-targeted and ICI–based therapies remain an unmet clinical need. Leukemia inhibitory factor (LIF), an IL-6 family cytokine implicated in angiogenesis and immune regulation, is associated with poor prognosis in ccRCC; however, its predictive value for treatment selection has not been defined. Methods: Baseline tumor LIF expression was evaluated in 2,026 patients with metastatic ccRCC across 12 clinical and molecular cohorts, including CheckMate 009/010/025/214, JAVELIN Renal 101, IMmotion150, TCGA-KIRC, CPTAC-3, and institutional datasets. RNA-seq data were batch-corrected, normalized, and immune-deconvoluted (CIBERSORTx). Among 1,306 patients with treatment data, 1,058 with complete clinical covariates were included in treatment-by-biomarker interaction analyses. Results: LIF-high tumors (median cutoff) were associated with younger age (60 vs 63 years, p<0.001) and increased sarcomatoid features (17% vs 8%, p<0.001). A significant treatment-by-LIF interaction was observed for progression-free survival (PFS; interaction p=0.006). High LIF expression predicted inferior PFS on TKI monotherapy (HR 1.26, p<0.001), while this adverse association was absent with ICI-based regimens (monotherapy or combination; HR 0.70, p<0.001). No significant interaction was observed for overall survival. LIF expression discriminated progressive disease from disease control (p<0.001). Immune deconvolution revealed that LIF-high tumors exhibited an inflamed but immunosuppressive microenvironment, characterized by enrichment of macrophages (M0 and M2), neutrophils, and regulatory T cells, with preserved CD8⁺ T-cell infiltration. LIF expression correlated strongly with CXCL8 (R=0.45), and more modestly with FGF2 and VEGFA, consistent with VEGF-independent angiogenic signaling. Conclusions: LIF identifies a biologically distinct subset of metastatic ccRCC characterized by angiogenic and immunosuppressive features and poor outcomes with TKI monotherapy. These data support LIF as a predictive biomarker to inform treatment selection and highlight the LIF/CXCL8 axis as a potential therapeutic target in advanced RCC. Treatment-by-LIF interaction analysis for progression-free survival in metastatic clear cell renal cell carcinoma. Groups N HR 95% CI P-value Full Cohort* 1792 1.09 1.01 – 1.14 0.017 Treatment interaction Model § Main effect (LIF in TKI) 1058 1.26 1.108 - 1.443 <0.001 LIF × IObased (IO and IO+IO) 1058 0.70 0.567 - 0.854 <0.001 LIF × IO+VEGF 1058 0.89 0.73 - 1.079 0.230 LIF × MTORi 1058 0.84 0.689 - 1.035 0.104 Stratified Analyses § : TKI Monotherapy 377 1.27 1.114 - 1.455 <0.001 IO/IO+IO 194 0.87 0.741 - 1.03 0.107 IO+VEGF 364 1.15 0.996 - 1.337 0.057 *Adjusted for IMDC, Age, Sex, Sarcomatoid Features, and Treatment modality. § Adjusted for IMDC, Age, Sex, Sarcomatoid Features.

Journal of Clinical OncologyVol. 44(16_suppl)
Brigham and Women's Hospital (US), Beth Israel Deaconess Medical Center (US), Yale Cancer Center (US), Dana-Farber Cancer Institute (US)
Reduced inequalities
Openalex Percentile: Top 12%
Cytokine Signaling Pathways and Interactions
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