(UroToday.com) The 2025 American Society of Clinical Oncology (ASCO) Genitourinary (GU) Annual Symposium held in San Francisco, CA was host to a session on the current state and future directions of biomarkers and adjuvant therapy for renal cell carcinoma (RCC). Dr. Samra Turajlic discussed the future of biomarkers in RCC.
Why do we need biomarkers in RCC? There are various settings in RCC where these may help with answering important clinical questions and addressing treatment decision-making processes:
- Small renal masses
- What is the risk of progression?
- Should patients undergo surgery, ablation, or surveillance?
- Resected pT2G4 and pT≥3 disease
- What is the risk of relapse?
- Should these patients receive adjuvant therapy?
- Metastatic disease, including solitary, oligometastases, and widespread metastatic disease spread
- Is there any indication for surgery (cytoreductive/consolidative nephrectomy)?
- Can we defer systemic therapy? If not, what regimen should these patients receive?
- Is there a role for metastasectomy?
- How can we sequence regimens?
The 1st step in developing genetic biomarkers for RCC is acknowledging that combinations of mutations, as opposed to one binary mutation, are key to clinical behaviour.
Motivated by this framework, Vasudev et al. evaluated mutational combinations to optimise selection for adjuvant therapy. Using a cohort of RCC patients that would have been eligible for KEYNOTE-564 (adjuvant pembrolizumab), the study investigators risk stratified patients by the number of driver mutations:
- VHL alone
- VHL + 1 additional driver mutation
- VHL + 2
- VHL +3
As seen in the Kaplan Meier curves below, patients with an increasing number of driver mutations had progressively worse disease-free survival outcomes.1
Based on these results, Vasudev et al proposed a treatment algorithm for these patients based on the genomic classifier results, whereby patients with a VHL-only mutation would be potentially spared adjuvant therapy, those with a VHL + additional driver mutation would be appropriately counseled, and those with two or three additional mutations would be prioritized for adjuvant therapy.
The second step is to go beyond gene mutations and evaluate the burden of copy number alterations. The weighted genome instability index (WGII) is a measurement of chromosomal instability in tumor samples. It estimates the proportion of a genome with abnormal copy numbers compared to the median ploidy. WGII is a prognostic biomarker that separates kidney cancer patients into high- and low-risk subgroups.
Given the pervasive intra-tumoral heterogeneity, both with regards to mutations and copy number alterations/aneuploidy, sampling error is a concern that increases with tumor size and stage and is a frequent reason for failure of biomarker validation. Solutions for capturing genetic changes include:
- Multi-regional sampling
- This is costly and labor intensive
- Liquid biopsy
- Ideal, but associated with low sensitivity, especially for earlier stage and aneuploidy detection
Thus, innovation to overcome this limitation is needed. To this end, Dr. Turajlic’s team used a novel approach, whereby ‘left over’ tumoral tissue, after pathologic evaluation was completed, was collated and homogenized and then sorted by Fixed-FACS to create a representative sample.
The 4th step is to use histology to predict genetic alterations. An example of this is the use of histologic features in patients with PBRM1 mutations alone, who have different pathologic features, compared to those who gain additional driver mutations, as demonstrated below:
Step 5 is to use radiology, via radiomics, to predict genetic alterations. Dr. Turajlic noted that while promising, radiomics approaches are challenging given that they require a large number of well-annotated data:
Step 6 is context dependency – consider the phenotype, as well as the genotype. Phenotype accounts for the genotype in the context of environmental factors, which is difficult to measure in situ.
What are the spatial features of metastasizing populations? Genetic mutations and copy number alterations are typically enriched in the center of the tumors (i.e., interior), where maximal tumor hypoxia occurs, and are associated with necrosis and an immunosuppressive tumor microenvironment (TME).
But Dr. Turajlic argued that this is a paradoxical observation, given that aneuploidy, through chromosomal instability, should stimulate antigen presenting cells (APCs) to produce an anti-tumor response. It appears that this phenotypic immunosuppression observed is secondary to increased expression of ENPP1 and SLC19A that suppress the cGAS/STINg pathway responsible for the immune activation.
As such, the sixth step could be considering the phenotype and genotype by combining aneuploidy and STING status:
The seventh step is to consider the therapeutic mechanism of action. Special challenges in RCC included:
- The absence of oncogenic targets
- Tumor microenvironment targets: angiogenesis and immune infiltration
- The complex interplay between the tumor, tumor microenvironment, and host which are subject to dynamic changes
- Combinations are thus largely used empirically
Which of these well-described biological processes in RCC matter the most in a biomarker context? One way to go about this is to define biological end points in clinical trials. An example of this is the APREDICT study, presented at this meeting, which evaluated sample changes to axitinib, in vivo, while on treatment.
The ‘holy grail’ is the biomarker-driven clinical trial. BIONIKK is a biomarker-driven randomized phase II trial, whereby patients with previously untreated metastatic ccRCC were randomly assigned to receive either nivolumab or nivolumab + ipilimumab (ccrcc1 and ccrcc4 groups), or either a VEGFR-TKI or nivolumab + ipilimumab (ccrcc2 and ccrcc3 groups), with the four ccRCC subgroups defined using a 35-gene expression classifier.2
The main findings were as follows:
- High efficacy of TKIs as well as nivo + ipi in ccRCC2 tumors
- Higher efficacy of nivo +/- ipi in ccRCC4 tumors compared to ccRCC1.
Another example of such an approach is the RNA-seq-based biomarker approach being prospectively evaluated in the prospective OPTIC RCC trial:
This is based on recent seminal work by Motzer et al. from the phase III IMmotion151 trial of atezolizumab + bevacizumab versus sunitinib that identified seven different RCC molecular clusters. Two notable clusters were the angiogenic clusters (1 and 2) and the immunogenic/cell proliferative T-effector and cell cycle clusters. Patients in the 1st cluster fared well with sunitinib, whereas those in the immunogenic/cell proliferative cluster had a much better response with atezolizumab + bevacizumab,3 thus creating the framework for the OPTIC RCC trial.
The ninth step is studying exceptional responders within the context of standard-of-care studies.
The future (10th step) is multimodal within the incorporation of multiple biomarkers in both real-world and clinical trial settings:
Dr. Turajlic concluded by asking – how can we do better?
- Harmonize and collaborate sample acquisition, profiling, data sharing
- Embrace technology
- Consider implementation in advanced path to translation, practicalities
- Leverage research infrastructure, large-scale initiatives
- Industry and patient advocates are key stakeholders and partners in the future of biomarkers
- It takes a village!
Presented by: Samra Turajlic, MD, PhD, Professor, Medical Oncologist, The Royal Marsden NHS Foundation Trust, The Francis Crick Institute, London, UK
Written by: Rashid K. Sayyid, MD, MSc – Robotic Urologic Oncology Fellow at The University of Southern California, @rksayyid on Twitter during the 2025 Genitourinary (GU) American Society of Clinical Oncology (ASCO) Annual Meeting, San Francisco, CA, Thurs, Feb 13 – Sat, Feb 15, 2025.
References:
- Vasudev NS, Riazalhosseini Y, Minarikova L, et al. Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma. Clin Cancer Res. 2023; 29(7):1220-1230.
- Vano YA, Elaidi R, Bennamoun M, et al. Nivolumab, nivolumab–ipilimumab, and VEGFR-tyrosine kinase inhibitors as first-line treatment for metastatic clear-cell renal cell carcinoma (BIONIKK): a biomarker-driven, open-label, non-comparative, randomised, phase 2 trial. Lancet Oncology. 2022; 23(5):612-624
- Motzer RJ, Banchereau R, Hamidi H, et al. Molecular Subsets in Renal Cancer Determine Outcome to Checkpoint and Angiogenesis Blockade. Cancer Cell. 2020; 38(6):803-817.