Leveraging the Heterogeneity of Adaptive Immune Cells Within the Tumor-Ecosystem to Better Describe Clear Cell Renal Cell Carcinoma Biologically and Clinically - Beyond the Abstract

Renal cell carcinoma ranks seventh and tenth among the most diagnosed cancers among men and women in the US, respectively, accounting for 3.8% of all cancer cases and 2.5% of all cancer death. The most common type of renal cell carcinoma is clear cell renal cell carcinoma (ccRCC). Metastatic ccRCC has been one of the first malignancies successfully treated with immune-modulating systemic therapy, using interleukin-2 and interferon-α. Immune checkpoint inhibitors (ICI) such as nivolumab, ipilimumab, pembrolizumab, and avelumab, have emerged as part of the first line in therapy for metastatic ccRCC. These ICI are often administered in combination or with a targeted therapeutic agent. The success of these novel options in clinical practice can vary greatly. Some of this variation is now understood to originate from between-patient differences in the tumor microenvironment. To better integrate ICI into successful treatment plans, we must improve our understanding of this complex tumor ecosystem.

The tumor microenvironment (TME) is the environment within and around a tumor. The description of the TME typically includes blood vessels, immune cells, fibroblasts (cells of the connective tissue), signaling molecules, and extracellular matrix (ECM). There is a constant flow of interactions between the TME and the tumor. We now understand that a normal (healthy) TME can function to suppress tumor onset. But once this suppression fails, which can occur for several reasons, part of the TME can be co-opted for the benefit of tumor growth and spread. The interactions of this unwanted evolutionary and ecological process, in which cancer and immune cell populations act as the evolving entities that form a joint ecosystem, can lead to vast cancer heterogeneity that impacts treatment success and survival. In an integrative, multi-disciplinary study, Ferrall-Fairbanks and colleagues now assessed the tumor-infiltrating T-cell and B-cell diversity in clear cell renal cell carcinoma. The study advances our understanding of tumor-immune system interactions and links the tumor immune ecology with important clinical properties such as tumor pathology, aggressiveness, and patient survival.

The team hypothesized that adaptive immune cell receptor-sequence diversity recapitulates important features of tumor biology. Such important features are tumor origin, its environment-driven evolution, and the risk of progression. The team of researchers leveraged properties of a measure that, so far, has commonly been applied in ecology and evolution, to quantify immune cell receptor-sequence diversity. As a result, they were able to assess whether and how this specific adaptive immune cell diversity is associated with important clinicopathologic outcomes in clear cell renal cell carcinoma. To this end, the team retrospectively investigated genomic sequencing data from three important clinical cohorts: a Moffitt cohort under the Total Cancer Care (TCC) protocol, the Clinical Proteomic Tumor Analysis Consortium (CPTAC-3 cohort), and the Total Cancer Genome Atlas (TCGA-KIRC cohort). Specifically, the recovery of adaptive immune receptor recombination reads from bulk RNAseq was obtained via PCR amplification of adaptive immune receptors—a procedure that is also called the immune repertoire approach. This allowed them to quantify tumor-immune infiltration (of T-and B-cells) across the different patient cohorts using complementarity determining region-3 (CDR3) sequence recovery counts from tumor-infiltrating lymphocytes. To identify statistical associations and differences among patients and cohorts, the team applied a generalized diversity index (GDI) for deep “ecological characterization” of these CDR3 sequence distributions.

The findings suggest that individuals with more advanced disease have increased richness in tumor recovered CDR3 sequences. In the Moffitt TCC cohort, the immune receptor profiles of sarcomatoid tumors were particularly interesting since sarcomatoid histology has been associated with a very favorable response to ICI. Also, the researchers found a significant increase in richness in left-sided tumors, which could explain some of the host-related factors associated with left-sided tumors that have been associated with poorer clinical outcomes compared to right-sided tumors. Many of the TCC-established associations were validated in similar comparisons with the CPTAC-3 cohort analyses. Another interesting finding was that B-cell CDR3 recoveries dominated in the TCC cohort, accounting for an average of 93.41% (ranging from at least 53.24% to 99.95%). This contrasted with the CPTAC-3 renal cell carcinoma cohort, which contains generally less aggressive tumors, with only 40.9% of the cohort respectively comprised of stage 3 or 4 tumors.

The results demonstrate that increased richness of the tumor-infiltrating immune cell receptors is indicative of larger and more advanced clear cell renal cell carcinoma tumors. In contrast, the evenness of these distributions segregated patients based on survival. Hereby, richness characterizes genetic sample distributions which measure the overall number of distinct sequences regardless of their abundances, whereas evenness characterizes the homogeneity of these abundant receptors. For example, a distribution of 5 unique sequences is richer than one of 3 unique sequences, and a sample with a frequency distribution of (1/3,1/3,1/3) is more even than (1/2,1/3,1/6). In the latter, we would say that the sequence found in 1/2 of the cells is dominant. In a cross-validation cut-point analysis, patients with higher T-cell receptor α (TRA) evenness had a significantly improved overall survival compared to individuals with lower TRA evenness. This result indicates that patients’ TRA evenness, not richness, may be a possible prognostic biomarker and could have direct therapeutic consequences for response to systemic agents that elicit their effect in the tumor microenvironment.

This study brought together researchers with backgrounds in applied mathematics, biomedical engineering, immunology, data science, oncology, pathology, as well as surgery, to show that different point estimates that emerge from a spectrum of scales of heterogeneity, can reveal unique information about tumors and patients. For example, increased richness in TRA and B-cell immunoglobulin lambda light chain  (IGL) diversity inform the size and aggressiveness of a tumor. The dominance of the most abundant sequence segregates patients based on prognosis. The study identifies a novel way to measure evenness among immune receptor subtypes that accurately classified patients’ overall survival in the investigated cohorts. The study also found important differences in receptor subtype contributions based on patient demographics, such as race and gender. Thus, the team of researchers identified a new statistical approach to help stratify patient-based differences in immune infiltration diversity and further guide precision oncology.

Written by: Meghan C. Ferrall-Fairbanks,1,2,3 Brandon J. Manley,3,4 Philipp M. Altrock3,5


  1. J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
  2. University of Florida Health Cancer Center, University of Florida, Gainesville, FL, USA
  3. Department of Mathematical Oncology, Moffitt Cancer Center, Tampa, FL, USA
  4. Department of Genitourinary Oncology, Moffitt Cancer Center, Tampa, FL, USA
  5. Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, D-24306 Ploen, Germany


  1. Article in press (online first): Meghan C Ferrall-Fairbanks, Nicholas Chakiryan, Boris I Chobrutskiy, Youngchul Kim, Jamie K Teer, Anders Berglund, James J Mulé, Michelle Fournier, Erin M Siegel, Jasreman Dhillon, Seyed Shayan Ahmad Falasiri, Juan F Arturo, Esther N Katende, George Blanck, Brandon J Manley, Philipp M Altrock. Quantification of T-and B-cell immune receptor distribution diversity characterizes immune cell infiltration and lymphocyte heterogeneity in clear cell renal cell carcinoma. Cancer Research, 2022. PMID: 35031572 DOI: 10.1158/0008-5472.CAN

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