Geospatial Cellular Distribution of Cancer-Associated Fibroblasts Significantly Impacts Clinical Outcomes in Metastatic Clear Cell Renal Cell Carcinoma

• Main Authors: Nicholas H. Chakiryan, Gregory J. Kimmel, Youngchul Kim, Joseph O. Johnson, Noel Clark, Ali Hajiran, Andrew Chang, Ahmet M. Aydin, Logan Zemp, Esther Katende, Jad Chahoud, Meghan C. Ferrall-Fairbanks, Philippe E. Spiess, Natasha Francis, Michelle Fournier, Jasreman Dhillon, Jong Y. Park, Liang Wang, James J. Mulé, Philipp M. Altrock, Brandon J. Manley
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Cancers
• Subjects: metastatic clear cell renal cell carcinoma; cancer associated fibroblasts; Ki-67; spatial analysis; immunohistochemistry
• Online Access: https://www.mdpi.com/2072-6694/13/15/3743

Cancer-associated fibroblasts (CAF) are highly prevalent cells in the tumor microenvironment in clear cell renal cell carcinoma (ccRCC). CAFs exhibit a pro-tumor effect in vitro and have been implicated in tumor cell proliferation, metastasis, and treatment resistance. Our objective is to analyze the geospatial distribution of CAFs with proliferating and apoptotic tumor cells in the ccRCC tumor microenvironment and determine associations with survival and systemic treatment. Pre-treatment primary tumor samples were collected from 96 patients with metastatic ccRCC. Three adjacent slices were obtained from 2 tumor-core regions of interest (ROI) per patient, and immunohistochemistry (IHC) staining was performed for αSMA, Ki-67, and caspase-3 to detect CAFs, proliferating cells, and apoptotic cells, respectively. H-scores and cellular density were generated for each marker. ROIs were aligned, and spatial point patterns were generated, which were then used to perform spatial analyses using a normalized Ripley’s K function at a radius of 25 μm (nK(25)). The survival analyses used an optimal cut-point method, maximizing the log-rank statistic, to stratify the IHC-derived metrics into high and low groups. Multivariable Cox regression analyses were performed accounting for age and International Metastatic RCC Database Consortium (IMDC) risk category. Survival outcomes included overall survival (OS) from the date of diagnosis, OS from the date of immunotherapy initiation (OS-IT), and OS from the date of targeted therapy initiation (OS-TT). Therapy resistance was defined as progression-free survival (PFS) <6 months, and therapy response was defined as PFS >9 months. CAFs exhibited higher cellular clustering with Ki-67⁺ cells than with caspase-3⁺ cells (nK(25): Ki-67 1.19; caspase-3 1.05; <i>p</i> = 0.04). The median nearest neighbor (NN) distance from CAFs to Ki-67⁺ cells was shorter compared to caspase-3⁺ cells (15 μm vs. 37 μm, respectively; <i>p</i> < 0.001). Multivariable Cox regression analyses demonstrated that both high Ki-67⁺ density and H-score were associated with worse OS, OS-IT, and OS-TT. Regarding αSMA+CAFs, only a high H-score was associated with worse OS, OS-IT, and OS-TT. For caspase-3⁺, high H-score and density were associated with worse OS and OS-TT. Patients whose tumors were resistant to targeted therapy (TT) had higher Ki-67 density and H-scores than those who had TT responses. Overall, this ex vivo geospatial analysis of CAF distribution suggests that close proximity clustering of tumor cells and CAFs potentiates tumor cell proliferation, resulting in worse OS and resistance to TT in metastatic ccRCC.