Multi-omics Analysis of Renal Cell Carcinoma Mechanisms; Drug Sensitivity Testing in Patient-Derived Cell-based Microtumors

Multi-omics Analysis of Renal Cell Carcinoma Mechanisms; Drug Sensitivity Testing in Patient-Derived Cell-based Microtumors

This is a research study aiming to better understand a type of kidney cancer called Renal Cell Carcinoma (RCC). Doctors have observed that inside some larger RCC tumors, there are multiple smaller nodules. This study wants to find out if these nodules are different from each other and how they might be related.

To do this, researchers will study tumor tissue samples from 10 patients with RCC who are having surgery. From each tumor, several nodules will be analyzed using advanced laboratory techniques. These techniques will create very detailed maps of the genes and cells within each nodule. At the same time, tiny 3D tumor models (called microtumors) will be grown from these samples in the lab to test how they respond to different cancer drugs.

The main goal is to combine these two types of information to see how the differences in genes and cells between nodules might explain why some tumors stop responding to treatment (become resistant). We hope this study will lead to a deeper understanding of how RCC grows and spreads, and help find new ways to diagnose and treat it in the future.

Background and Rationale: Renal Cell Carcinoma (RCC) frequently exhibits intratumoral morphological heterogeneity, often presenting as distinct multiple nodules within a single tumor mass on cross-section. The biological and clinical significance of this multinodular architecture remains poorly understood. It is hypothesized that these nodules may represent clonal subpopulations with unique genomic, transcriptomic, and functional profiles, potentially driving tumor progression and therapy resistance. This study leverages integrated multi-omics and functional drug testing to systematically decipher the inter-nodular heterogeneity and evolutionary relationships within RCC.

Primary Objectives:

To delineate the cellular and genomic landscape of different intratumoral nodules in RCC using single-cell RNA sequencing (scRNA-seq), whole-exome sequencing (WES), and spatial transcriptomics.

To infer the potential clonal evolutionary relationships and driver-subordinate dynamics between coexisting nodules.

To characterize the differential drug sensitivity profiles of patient-derived microtumor (PTC) models established from distinct nodules.

To integrate multi-omics data with drug response data to explore underlying mechanisms of drug resistance.

Study Design and Methods: This is a single-center, prospective, basic science study. We will enroll 10 treatment-naïve patients with locally advanced RCC (tumor diameter ≥7 cm, with regional lymph node metastasis but no distant metastasis) scheduled for radical nephrectomy. Intraoperatively or immediately post-resection, each grossly multinodular tumor will be sectioned. Three dominant nodules (labeled T1, T2, T3 by size) will be identified from each specimen. From each nodule, four matched samples will be collected for: 1) scRNA-seq, 2) WES, 3) spatial transcriptomics, and 4) generation of 3D patient-derived tumor cell (PTC) microtumor models.

Analyses: Bioinformatic integration of scRNA-seq, WES, and spatial data will be performed to construct maps of cellular composition, genetic alterations, and their spatial distribution across nodules. Pseudotime trajectory analysis will be applied to infer potential evolutionary sequences. PTC models will undergo ex vivo drug sensitivity testing (e.g., against axitinib, pembrolizumab, and their combination). Differential response data will be correlated with omics-derived features (e.g., specific mutant alleles, cell subtype abundances, pathway activities) to identify candidate resistance mechanisms.

Significance: This is the first study to systematically investigate intratumoral nodular heterogeneity in RCC at a multi-omics level coupled with functional validation. Findings are expected to provide novel insights into RCC tumorigenesis and progression, potentially revealing new biomarkers for prognosis and therapeutic targets to overcome resistance.

Inclusion Criteria:

• Histologically confirmed renal cell carcinoma with regional lymph node metastasis.
• Primary tumor with a maximum diameter ≥ 7 cm.
• Tumor exhibits a multinodular distribution pattern on cross-section (assessed via intraoperative or postoperative gross specimen).
• Age > 18 years.
• Ability to understand the study and voluntarily provide written informed consent.

Exclusion Criteria:

• Presence of distant metastasis (M1 stage).
• Prior receipt of any targeted therapy or immunotherapy for renal cell carcinoma before surgery.
• History of other active malignancies besides RCC (except cured basal cell carcinoma of the skin or carcinoma in situ of the cervix).
• Any psychiatric, neurological, or legal condition that may compromise the ability to understand the informed consent or to comply with study procedures.