Washington, DC (UroToday.com) At the kidney cancer session at SUO 2019, Dr. Joshua Lang discussed the future of predictive biomarkers in renal cell carcinoma (RCC). Indeed, this is an evolving therapeutic landscape, with combination therapies as 1st line options for metastatic RCC including nivolumab plus ipilimumab and axitinib plus pembrolizumab. Single-agent options depend on disease risk scores and include cabozantinib and pazopanib.
There are several biomarker categories:
- Diagnostic – identifies the presence of malignancy
- Prognostic – baseline patient or disease characteristics that categorizes patients by degrees of risk for disease recurrence/progression
- Predictive – baseline characteristics that categorize patients by their likelihood for response to a particular treatment
- Pharmacodynamic – dynamic assessment showing a biological response has occurred after a therapeutic intervention
- Discovery – biomarker intended to identify previously unknown alterations that promote tumorigenesis, metastases and resistance
- Surrogate – biomarker intended to substitute for a clinical efficacy endpoint
There are many opportunities in RCC for biomarkers. Risk categorization has some prognostic utility, for example, the IMDC risk groups. However, serum cytokine and angiogenic factors have limited prognostic utility. ctDNA has been found to have a distinct mutation profile in p53 and mTOR, while PD-L1 expression from an archived biopsy has limited predictive capacity. The clinical need for biomarkers is such that we need to ascertain who will respond, why patients develop resistance, what the next/best treatment is, determine how we can combine treatment, assess when we should target resistance, and determining where we’ll find the next generation of drugs.
At the University of Wisconsin, Dr. Lang’s group has developed VERSA technology, which isolates DNA and mRNA, helping the exploration of biomarkers. This has helped show that renal markers, such as CAIX and CAXII, can improve isolation and identification of circulating tumor cells. As such, a higher burden of RCC circulating tumor cells correlates with disease progression. Furthermore, there is phenotypic heterogeneity in RCC circulating tumor cells in that enumeration correlates with scan progression and disease progression (AUC 0.88). Expression of ICI biomarkers have also been assessed on circulating tumor cells – PD-L1 and HLA expression can be reliably detected on circulating tumor cells, and single-cell analysis identifies tumor clones with potential immune escape mechanisms. Higher expression of PD-L1 (AUC 0.77) and HLA (AUC 0.59) is associated with response to ICI.
Dr. Lang concluded his talk with several summary points:
- There is an urgent need for predictive biomarkers
- Single tumor biopsies may not represent the heterogeneity of RCC
- Liquid biopsies may capture the heterogeneity, but it remains to be determined how a single cell protein analysis correlates with primary or metastatic lesions
- Single-cell phenotypic analysis shows early clinical correlations for ICI and TKI therapies
- But ultimately, can we do better than CT scans to identify emerging signs of resistance?
Presented by: Joshua M. Lang, MD, Assistant Professor, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin