Corresponding Author: Ritesh R. Kotecha, MD, Memorial Sloan Ketter-ing Cancer Center, 1275 York Avenue, New York, NY 10065. Email: firstname.lastname@example.org
Incremental but exciting progress toward the development of a biomarker in metastatic renal cell carcinoma has put precision medicine on the verge of making dramatic changes in detection and surveillance. The utility of circulating tumor DNA is gaining converts to a technology with potential translational impact on clinical practice. But many issues remain to be elucidated before this tool can move beyond the hypothesis-generating stage to becoming integrated into clinical practice.
As new non-invasive tools emerge in the era of precision oncology, the landscape for diagnostic and prognostic markers in renal cell carcinoma (RCC) is dramatically changing. Next-generation sequencing (NGS) platforms, including techniques that analyze tumor tissue for somatic and germline cancer-associated gene alterations, are beginning to have an impact on kidney cancer diagnoses. Potentially - and therein lies the cautionary tale - innovative blood-based tests, also known as liquid biopsies, could begin to change the paradigm of RCC disease management, thereby overcoming issues posed by traditional radiological and histopathological examinations. The need for and the presentation of new research on reliable biomarkers in RCC remains a major focus, yet reliable and confirmatory evidence for such methods continues to be elusive for kidney cancer while substantial progress has been made in other solid tumors which readily employ treatment strategies based on actionable genetic data.
Aside from its non-invasive advantages, other benefits of liquid biopsies include multiple time point testing and its ability to facilitate the diagnosis and monitoring of evolving disease, offering clinicians a potentially contemporary and prognostic marker to effectively track a patient’s clinical course. Liquid biopsies such as circulating tumor DNA (ctDNA) or circulating cell-free DNA (cfDNA) constitute two promising avenues of exploration in the era of precision oncology for RCC.
Circulating cell-free DNA. With a simple blood test, the total quantity of DNA that is released into the peripheral blood circulation and captured comprises circulating cell-free DNA (cfDNA). Since this DNA is released from both normal and tumor cells, isolated DNA fragments in cfDNA are not only from the tumor but include normal cellular DNA that is released from other molecular processes like apoptosis, necrosis, and secretion of genomic DNA fragments.1 The abundance and relative fragmentation of cfDNA has been suggested to be a biomarker for several solid tumors including RCC in numerous studies.2-8 However, additional metrics of cfDNA remain to be clarified and its clinical utility in RCC disease management has yet to be fully elucidated. With each study, differences in patient characteristics, RCC disease characteristics, and most importantly the platform used for cfDNA capture make it challenging to unify conclusions. Although controversy surrounds efforts to validate cfDNA as a clinical biomarker for RCC, recent studies reviewed in this report suggest its utility and promise for it being a non-invasive tool associated with potential high sensitivity and specificity for RCC management.
Circulating tumor DNA. Next generation sequencing (NGS) of circulating tumor DNA (ctDNA) is an attractive alternative to traditional tissue sequencing because it circumvents the need for repeated, invasive tissue biopsies to gain a contemporary mutational profile. In addition, ctDNA analyses may also provide a more comprehensive assessment of the total tumor as ctDNA is shed from separate heterogeneous tumor sites.9 While the role of ctDNA in other diseases like lung cancer and colorectal cancer is well established, studies of ctDNA in metastatic RCC (mRCC) are only hypothesis-generating to date. In contrast to cfDNA, ctDNA is derived from the tumor itself and usually represents a smaller fraction of cfDNA. ctDNA is thought to be shed into circulation by apoptotic and necrotic tumor cells in patients with cancer,10,11 highly prevalent in most advanced solid tumors except for brain tumors,12 and has a half-life ranging from sixteen minutes to a few hours.13-15 Because advanced tumors, either pre-treated or at tumor progression, have a higher mitotic index and undergo more rapid cell cycling compared with normal tissue or earlier stage tumors, ctDNA constitutes a larger proportion of cfDNA in metastatic disease.16,17 Patients with high tumor burdens and aggressive disease have higher proportions of ctDNA, which may rise above 90% of cfDNA.18 The presence of multiple alterations in ctDNA may also represent selective treatment pressures and/or tumor heterogeneity, though, which complicate interpretation of identified variants. Ultimately, the goal of ctDNA is to derive actionable genomic information from a peripheral source to make real-time, personalized cancer treatment decisions.19
Investigational Uses of cfDNA and ctDNA: Potential Implications
Although the clinical utility of these assays is not ready for “prime time”, especially since integral biomarkers are not currently used to guide targeted therapy or immunotherapy in mRCC, a review of recent literature offers a glimpse of how these techniques can be applied as they move forward from the bench to the bedside. In a study by Wan et al.,20 for example, results demonstrate how cfDNA may play a potential role in monitoring patients with RCC after nephrectomy. The objective of this and other such studies is to extend to RCC the significance of plasma/serum cfDNA identified post-surgically as studied in other solid tumors. Wan and colleagues focused on whether a quantitative analysis—before and after nephrectomy—could play an important role in monitoring patients during follow-up for detection of a recurrence in clear cell RCC (ccRCC). The pretreatment level of plasma cfDNA in patients with metastatic ccRCC (6.04 ± 0.72) was significantly higher than those with localized ccRCC (5.29 ± 0.53, p=0.017) or controls (0.65 ± 0.29, p < 0.001). Of patients with localized ccRCC, those with disease recurrence had a significantly higher plasma cfDNA level than those without (p=0.024). Further, patients with a high plasma cfDNA level had a significantly higher recurrence rate than those with a low plasma cfDNA level before and after nephrectomy (p= 0.018).
Although the follow-up was relatively short (36 months), the results from Wan et al. highlight potentially a “minimal residual disease” state which would be helpful in monitoring ccRCC patients after surgery. Traditional nomograms which currently help predict recurrence include variables like disease stage, high Fuhrman grade or large tumor size, and adding serum testing after surgery to characterize this biological disease state may add predictive power. Several observations suggest the potential value of cfDNA in this setting: there was a significant difference of plasma cfDNA levels between low and high Fuhrman grade; patients with high disease stage (T3) and large tumor size (>3 cm) had significantly higher plasma cfDNA levels than those with lower stage and smaller tumors. Also, the average cfDNA level was significantly higher in metastatic tumors (N+ and/or M+) than in localized tumors before nephrectomy.
One of the challenges with ctDNA studies in RCC has been uncovered in large pan-cancer studies, which show a relatively low recovered ctDNA quantity in patients with kidney cancers when compared to other solid tumors. In an analysis of 21,807 patients with treated, late-stage cancers across more than 50 cancer types, the recovered ctDNA for renal cancer is much less robust (Figure 1).10 Understanding why ctDNA loads remain low for this cancer may help fuel new RCC-specific methods to improve ctDNA detection. Nevertheless, several recent reports are capturing the narrative of how ctDNA can be used for clinical care.
Figure 1. In an analysis of 21,807 patients with treated, late-stage cancers across more than 50 cancer types, the recovered ctDNA for renal cancer is much less robust. (Adapted from reference 19.)
One report by Hahn and colleagues21 assessed whether genomic alterations detected by ctDNA NGS are truly representative of those alterations detected in tumor tissues. Are these NGS platforms interchangeable or complementary? Understanding this key distinction impacts how and when to integrate ctDNA testing during clinical care. In this first report to correlate ctDNA with matched tumor tissue NGS, there is mixed news. When the study controlled for genes tested by both platforms, the median mutation rate for ctDNA was similar to tissue (median 3.0 vs 1.0) but the concordance rate between the two platforms was only 8.6%. This result is comparable to findings in other solid tumors on concordance. The “take-home” message from this study is that ctDNA NGS offers the advantage of a decreased risk for sample collection and an improved ease of repetitive testing over tumor tissue NGS, and that these two platforms may be used in concert with each other rather than as a substitute. Since this avenue of investigation is still in the preliminary stage, appropriate use of ctDNA in this context remains an area of active research.
CtDNA and Checkpoint Inhibitor Therapy
A key question in this era of precision medicine is to what extent ctDNA might be applied to correlate with response to immune checkpoint inhibitors. Recently, Khagi et al.22 studied whether hypermutated ctDNA correlated with immune checkpoint inhibitor response in solid tumors. In this study of 69 patients with various malignancies including melanoma, lung cancer, and head and neck cancer, 63 patients (91% of the cohort) had at least one ctDNA alteration detected. Characterizing these alterations further, the authors found many patients with “variants of unknown significance (VUS)”, which refers to a variant identified through genetic testing whose significance on disease remains unknown. The authors found an association between ctDNA VUS on progression-free survival (PFS) and overall survival (OS) with immune checkpoint blockade therapy. For example, at two months, landmark survival analyses of responder’s versus non-responders to checkpoint inhibitor therapy with VUS >3 showed a median PFS of 23 versus 2.3 months (p=0.004). The preliminary conclusions from this study – still investigational - is that tissue tumor mutational burden as determined by liquid biopsy could also have a role in predicting response to immunotherapy.
A closely related case report by Dizman et al.23 of ctDNA changes in a patient with metastatic RCC who achieved an exceptional response to nivolumab therapy adds personalized context to the clinical utility of ctDNA in metastatic RCC. In this case, the patient’s disease had progressed after treatment with bevacizumab and subsequently cabozantinib. In addition to several genomic alterations from a tissue-based assessment, unique alterations were noted in ctDNA at baseline. After 4 weeks of therapy with nivolumab, the patient had a significant clinical response to immune checkpoint blockade therapy. Interval ctDNA analysis during nivolumab therapy showed no alterations, highlighting paralleled changes in ctDNA with therapy response.
An additional metric highlighted from this case report is whether the rate of ctDNA change, termed ctDNA velocity, may be used as a surrogate for therapy response. In this case report, 6 distinct genomic alterations were identified. Although this is not a clear surrogate for mutational burden, Dizman et al.23 refer to other reports that link the presence of increased mutational load with response to checkpoint inhibition. Additionally, timing of ctDNA changes seen during therapy may represent markers for cell turnover and therefore surrogates of treatment response. As prior research has demonstrated differences in radiographic tumor burden with ctDNA (Figure 2),24 dynamic measurements which incorporate serial changes in ctDNA like velocity could have significant implications particularly in challenging scenarios like pseudoprogression.
Figure 2. Difference in sum of the longest dimension (SLD) of tumor in patients with detectable and non-detectable ctDNA. Mean SLD in was 8.81 cm in patients with detectable ctDNA, as compared to 4.49 in patients with non-detectable ctDNA (p = 0.04 by unpaired t-test). (Adapted from reference 24.
Single-Time Point and Evolutionary Changes in ctDNA
A new generation of studies extending the above efforts into large cohorts of treated RCC patients provides additional insights into the utility of ctDNA as a tool which may capture evolving disease with therapy. In a large cohort of 220 patients with metastatic RCC, Pal et al.25 assessed ctDNA profiles of patients treated with first-line and later lines of therapy. In their cohort, the most frequent identified alterations included TP53 (35%), VHL (23%), EGFR (17%), NF1 (16%), and ARID1A (12%). This cohort of patients remains the largest assessment of ctDNA sequencing in metastatic RCC to date. Variations seen across first-line and refractory settings suggests underlying mechanisms for therapeutic resistance (Figure 3), e.g. TP53 mutations), as well as identification of alterations which may prompt non-conventional therapy selection for certain patients.
Figure 3. Notable differences in genomic alteration (GA) frequency in patients documented as receiving first-line therapy versus post first-line therapy (p values were as follows: TP53: p = 0.02; NF1: p = 0.01; VHL: p = 0.26; EGFR: p = 0.6; PIK3CA: p = 0.3. (Adapted from reference 25.)
As noted above, the excitement for ctDNA to guide targeted therapy in RCC has started to gain traction. For instance, inhibition of the MET pathway remains an active area of investigation, and evidence for MET alteration identification across solid tumors is increasing. To investigate this further, Ikeda et al.26 performed ctDNA digital sequencing (using a 54-70 gene panel) in a pan-cancer cohort of 438 patients, 263 of whom had tissue sequencing for comparison. MET alterations were seen in 7.1% of patients which correlated with presence of bone metastases; TP53 and PTEN abnormalities were also found to be correlated as well. Importantly, MET alterations were detected at a lower frequency in tissue (1.14%) compared to ctDNA (7.1%), again highlighting that ctDNA analyses complement standard tissue sequencing.
To further characterize the complexities of applying ctDNA as a biomarker for metastatic RCC, we performed a large cohort analysis incorporating a comparative genomics approach with matched primary tissues at Memorial Sloan Kettering Cancer Center.27 In our cohort, 110 metastatic ccRCC patients underwent a single-time point collection for ctDNA, and the median time between ctDNA collection and previously collected tissue used for comparison was 24 months. Although the mutational profiles were similar between these two tissue platforms – with VHL and PBRM1 alterations recovered with the highest frequency in both blood and tissue, there remained discordance between the total number of alterations recovered. For instance, the majority of VHL and PBRM1 alterations were only identified in primary tissue and not in ctDNA. Alterations of these genes found in ctDNA, though, were always found in the matched primary tissue. In sum, investigating other methodologies which use an enriched RCC specific gene-set panel or higher sequencing depth may improve and enhance ctDNA detection and concordance in this patient population.
With the focus on ctDNA undergoing closer scrutiny, application of this tool in varied disease stages has been explored and presented at scientific symposia. A report by Correa et al.28 of a cohort of 42 patients with stage I-IV RCC who underwent complete surgical resection demonstrated the impact of ctDNA on prognosis. At baseline, for example, ctDNA was detected in 41% off patients and was significantly associated with increased tumor size, advanced tumor stage, and poorly differentiated tumors. Postoperatively, 8 of 8 ctDNA-positive patients relapsed while only 16 of 33 ctDNA-negative patients relapsed. This report concludes that ctDNA values have the potential to be used as a prognostic marker across multiple disease settings.
Looking ahead, future studies need to address a wide range of issues to determine the translational impact of ctDNA in RCC. A few notable areas of exploration include:
Robust ctDNA testing with matched tissues NGS data to provide reliable sensitivity, specificity and positive/negative predictive metrics.
Studies to “benchmark” each assay, delineating how each of these platforms work and how they can be used in clinical practice.
An improved understanding of which relevant alterations need to be identified and their relationship to a disease stage (e.g. prognostic or predictive power, understanding genomic changes and their relationship to therapeutic resistance).
Correlation of clinical variables like disease sites or treatment effects with ctDNA variables like ctDNA velocity or load to improve upon clinical significance during assay development.
Discovery of disease states like “minimal residual disease” after curative intent surgeries, or responding/progressive disease states for systemic therapy monitoring.
Cell free and circulating tumor DNA assessments are non-invasive tools which can provide pertinent and serial genomic tumor assessments. Although the experience of ctDNA has not advanced to the stage where it can be considered an actionable routine part of clinical practice for RCC disease management, all signs point toward it becoming integrated as a complementary tool to current tissue sequencing efforts. As new technology emerges on the forefront – including integration of epigenomics or analyses of other circulating substances like exosome-derived DNA, ensuring that these assays are benchmarked and robustly tested in the RCC population remains crucial. Studies such as these can propel the use of these innovative tools and usher in a new era of precision testing for patients with kidney cancers.
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