Molecular changes in advanced clear cell renal cell carcinoma (ccRCC) pre- and post-immunotherapy.

W Wadih Issa (Department of Internal Medicine, Division of Hematology/Oncology, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX) N Navneet Kaur A Andrew DeVilbiss (UT Southwestern Medical Center, Dallas, TX) Z Ze Yu (State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Molecular Recognition and Biosensing, Frontiers Science Center for New Organic Matter, College of Chemistry) A Aleksandra Weronika Nielsen (UT Southwestern Medical Center, Dallas, TX) H Hua Zhong (Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Republic of Singapore) D Damla Günenç Q Qinhan Zhou J Jay Jasti P Payal Kapur S Satwik Rajaram C Chao Xing L Liwei Jia A Andrew Zhuang Wang (Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX) T Tian Zhang (Division of Hematology‐Oncology, Department of Internal Medicine University of Texas Southwestern Medical Center Dallas Texas USA)

Abstract

e16533 Background: Whileimmunotherapy (IO) has improved outcomes for advanced ccRCC, biomarkers for IO response or resistance are lacking. Evaluating molecular alterations pre- and post-IO may identify biomarkers to improve IO treatment selection for RCC. Methods: We identified 18 patients (pts) with advanced ccRCC who had undergone cytoreductive nephrectomy (Nx) after IO, with matched pre-IO tissue controls (5 with IO-IO, 9 with IO-tyrosine kinase inhibitors (TKI), and 4 with IO monotherapy). Pre-treatment biopsies and post-treatment Nx samples were profiled using the Nanostring GeoMx platform. We selected 4-12 regions of interest (ROIs) per sample and profiled each ROI. Pathway enrichment was assessed with Gene Set Enrichment Analysis (GSEA) using Reactome and Hallmark gene sets. Deep learning algorithms analyzedH&E slides for angiogenic and immune gene signatures. Tumor response was assessed using RECIST 1.1. Results: All post-IO samples (median 5 cycles) had residual disease (2 ypT1, 4 ypT2 and 12 ypT3). Comparing tumor profiles between pre- and post-treatment, 1027 differentially expressed genes were found in the IO-IO group,181 in the IO-TKI, and 934 in the IO mono group (adj. p < 0.05). In IO/IO pts with stable disease (SD), residual tumors were positively enriched for “myc variant targets” and “response to hypoxia: Hif1α targets”, whereas these pathways were not enriched in partial response (PR) pts. Protein translation pathways were enriched in SD tumors, while collagen and extracellular matrix remodeling pathways were enriched in PR tumors. In the IO-TKI treated group, enrichment of the “Cell cycle progression: E2F targets” and “Cell cycle progression: G2/M checkpoint” pathways were found in 7/9 (78%) and 6/9 (67%) tumors, respectively. In pts treated with pembrolizumab and lenvatinib, 4/6 (67% in IO-TKI group) showed “mTORC1 signaling” enrichment. The IO-mono cohort was depleted for “epithelial to mesenchymal transition” pathway in all (4/4) pts. Regardless of therapy, 83% of all pts (15/18) were positively enriched in “myc variant targets”, suggesting myc signaling may be crucial for residual tumor survival. Finally, using digital pathology, most pre-IO samples had moderate to high immune infiltration; post-IO, immune infiltration increased while angiochanges decreased in a subset of samples. Conclusions: Molecular gene expression changes in RCC after IO-based therapy found MYC signaling and a number of critical tumorigenesis pathways enriched in residual tumors. The heterogeneity in RCC emphasizes the need for individualized tumor profiling to predict IO therapy outcomes. Ongoing analyses include spatial proteomics, with further validation in larger cohorts.

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (15)

W

Wadih Issa

Department of Internal Medicine, Division of Hematology/Oncology, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX

N

Navneet Kaur

A

Andrew DeVilbiss

UT Southwestern Medical Center, Dallas, TX

Z

Ze Yu

State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Molecular Recognition and Biosensing, Frontiers Science Center for New Organic Matter, College of Chemistry

A

Aleksandra Weronika Nielsen

UT Southwestern Medical Center, Dallas, TX

H

Hua Zhong

Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Republic of Singapore

D

Damla Günenç

Q

Qinhan Zhou

J

Jay Jasti

P

Payal Kapur

S

Satwik Rajaram

C

Chao Xing

L

Liwei Jia

A

Andrew Zhuang Wang

Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX

T

Tian Zhang

Division of Hematology‐Oncology, Department of Internal Medicine University of Texas Southwestern Medical Center Dallas Texas USA