Background

Next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) has emerged as a powerful complement to tissue NGS, offering a noninvasive and serially conductible test. Its application holds promise in enhancing the assessment of spatial and temporal molecular tumor heterogeneity, thus providing valuable insights into cancer progression and treatment response. In this study, we explore the mutational landscape of renal cell carcinoma (RCC) patients through comprehensive profiling of mutations in ctDNA and matched tissue samples, aiming to elucidate the concordance and clinical significance of molecular alterations detected in both circulating and tissue-derived DNA.

Methods

From the Tempus multimodal database, we retrospectively analyzed de-identified NGS data from patients with RCC that had dual tissue (Tempus xT, 648 genes) and ctDNA testing (Tempus xF, 105 genes). Patients with matched samples (collected +/- 90 days of one another) were included. We evaluated socio-demographic and clinical characteristics and select pathogenic somatic short variants (PSSV) and copy number variants [(amplifications and deletions, two copy number losses (CNL)]. Concordance analyses were restricted to the 105 genes tested on the ctDNA panel and further restricted to short variants, with the exception of amplifications and CNL detected by both xF and xT. Analysis was further stratified by metastatic status (n=260, metastatic, n=120 non-metastatic) prior to collection of both xT and xF.

Results

Among all patients (n=393), the median age was 61 years, and 71% were male. The patient cohort comprised a diverse population based on race, with 75% white, 12% African American, 4.8% Asian and 8% others. The median time from tissue to blood collection was 21 days (IQR, 7, 39). 67% (n=265) and 68% (n=266) had metastatic disease at the time of tissue and blood collection, respectively. The most common tissue sites were kidney (49%, n=189), bone (11%, n=43), lung (9%, n=34), lymph node (8%, n=29), liver (6%, n=23), and brain/CNS (4%, n=17). Genes harboring the most common PSSV in tissue included VHL (59% n=232), PBRM1 (31%, n=123), SETD2 (23%, n=91), TP53 (14%, n=54), BAP1 (12%, n=46) and TERT (11%, n=45). Genes with common PSSV in ctDNA included TP53 (23%, n=91), VHL (18%, n=69), BAP1 (6%, n=23), PBRM1 (5%, n=21), PTEN (4%, n=15), KRAS (4%, n=14) and NF2 (4%, n=14). The combination of tissue and ctDNA testing increased the detection of mutations (Table 1). There was higher concordance between somatic alterations in select genes among patients with metastases vs. non-metastases, including BAP1 (55.9% vs. 9.1%), TP53 (36.8% vs. 9.1%), VHL (32.3% vs. 12.5%), ARID1A (25% vs. 16.7%), and ATM (25% vs. 0%).

Conclusions

The analysis conducted in this study highlights the complementary nature of ctDNA profiling alongside tissue-based NGS in RCC, demonstrating an increased detection of mutations. Particularly, we observed a higher concordance between ctDNA and tissue profiling in individuals with metastatic disease, suggesting the potential utility of ctDNA analysis in advanced stages of RCC. Further research is warranted to elucidate how longitudinal ctDNA analysis can delineate biomarkers of response and resistance at both the mutation and ctDNA fraction levels. Understanding these dynamics could offer valuable insights into disease progression and guide personalized treatment strategies for RCC patients.

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