Tracing Clonal Dynamics Reveals that Two- and Three-dimensional Patient-derived Cell Models Capture Tumor Heterogeneity of Clear Cell Renal Cell Carcinoma

Abstract

Background: Extensive DNA sequencing has led to an unprecedented view of the diversity of individual genomes and their evolution among patients with clear cell renal cell carcinoma (ccRCC). Objective: To understand subclonal architecture and dynamics of patient-derived two-dimensional (2D) and three-dimensional (3D) ccRCC models in vitro, in order to determine whether they mirror ccRCC inter-and intratumor heterogeneity. Design, setting, and participants: We have established a comprehensive platform of living renal cancer cell models from ccRCC surgical specimens. Outcome measurements and statistical analysis: We confirmed the concordance of 2D and 3D patient-derived cell (PDC) models with the original tumor tissue in terms of histology, biomarker expression, cancer driver mutations, and copy number alterations. We addressed inter-and intrapatient heterogeneity by analyzing clonal dynamics during serial passaging. Results and limitations: In-depth genetic characterization verified the presence of heterogeneous cell populations, and revealed a high degree of similarity between subclonal compositions of monolayer and organoid cell cultures and the corresponding parental ccRCCs. Clonal dynamics were evident during serial passaging of cells in vitro, suggesting that PDC cultures can offer insights into evolutionary potential and treatment susceptibility of ccRCC subclones in vivo. Proof-of-concept drug profiling using selected ccRCC-targeted therapy agents highlighted patient-specific vulnerabilities in PDC models that could not be anticipated by interrogating commercially available cell lines. Conclusions: We demonstrate that PDC models mirror inter-and intratumor heterogeneity of ccRCC in vitro. Based on our findings, we envision that the use of these models will advance our understanding of the trajectories that cause genetic diversity and their consequences for treatment on an individual level. Patient summary: In this study, we developed two-and three-dimensional patient-derived models from clear cell renal cell carcinoma (ccRCC) as "mini-tumors in a dish." We show that these cell models retain important features of the human ccRCCs such as the profound tumor heterogeneity, thus highlighting their importance for cancer research and precision medicine.

Inhibiting WNT and NOTCH in renal cancer stem cells and the implications for human patients

“…Two other methods to culture ccRCC organoids have recently been described 56,57 . The first yielded organoids with a limited expansion capacity and a low rate of success.…”

A brief history of organoids

“…In addition, primary breast cancer organoids have been reported to faithfully recapitulate the corresponding parent tumors in morphology, histopathology, hormone receptor status, and mutational landscape ( 112 ). Organoids of other cancer types have also been subsequently established, including gastric ( 78 , 90 , 93 , 126 ), prostate ( 39 ), ovarian ( 69 ), brain ( 22 ), bladder ( 74 ), kidney ( 15 ), lung ( 114 ), and esophageal cancers ( 77 ).…”

“…Large-scale genomic and functional analysis from various studies have shown that tumor-derived organoids can faithfully recapitulate the phenotypic and genomic features of the primary tumors both in vitro and in vivo after transplantation ( 14 , 39 , 73 , 112 , 150 ). Importantly, the tumor heterogeneity and clonal dynamics were preserved after serial passaging of PDOs, indicating that these “mini-tumors” are genetically stable with enormous clinical applicability ( 15 ). With increasing interest in the use of organoids for disease modeling, biobanking can soon be extended beyond cancer, such as intestinal and lung organoids for cystic fibrosis patients and liver organoids for patients with various metabolic diseases.…”

Prediction of best features in heterogeneous Lung adenocarcinoma samples using Least Absolute Shrinking and Selection Operator

“…Genetic mutations, cancer microenvironment, immune, and therapeutic selection pressures all dynamically contribute to tumor heterogeneity. Heterogeneity may lead to cells with a differential molecular signature within single tumor tissue, and in some cases, it may contribute to therapy resistance [3]. Therefore, deciphering LUAD heterogeneity will have a significant impact in designing precision medicine strategy.…”