Photo Credit: Nemes Laszlo
Physician’s Weekly reviewed renal cell carcinoma (RCC)-targeted research presented at the 2024 ESMO annual meeting.
Using Minimal Residual Disease as a Prognostic Marker
Clear cell RCC (ccRCC) is a highly lethal urological cancer with substantial tumor heterogeneity, making reliable biomarkers essential for prognosis. The role of Minimal Residual Disease (MRD) as a prognostic marker in ccRCC is still uncertain. One study analyzed MRD using a customized panel based on whole exome sequencing (WES) of tumor tissue to identify clonal mutations, which were then tracked in blood samples taken preoperatively and at several postoperative intervals.
There were 70 patients with ccRCC examined, with a significant portion of mutated genes found to be unique to individual patients. Tumor-informed MRD demonstrated higher accuracy than standard panel-based MRD. Preoperative MRD positivity correlated with tumor stage, showing 39.1% in stage pT1-2, 72.2% in stage pT3, and 100% in stage pT4. The negative predictive value (NPV) of MRD was 100%, indicating reliable recurrence prediction. However, the positive predictive value (PPV) was 42.9%, indicating less certainty in predicting recurrence. Early findings suggest tumor-informed MRD’s potential for predicting ccRCC recurrence and metastasis, emphasizing the need for ongoing MRD monitoring to improve long-term prognosis assessment.
Epigenomic Profiling of Cell-Free DNA in tRCC
Translocation RCC (tRCC) is an aggressive kidney cancer subtype, typically driven by TFE3 gene fusions, and is often misclassified due to histologic similarities with other RCC types. Accurate diagnostic methods for this distinct molecular subtype are urgently needed. This study explored epigenomic profiling of cell-free DNA (cfDNA) from blood plasma as a method to detect tRCC and distinguish it from clear cell RCC (ccRCC).
Researchers analyzed gene expression, methylation, and regulatory elements (REs) specific to tRCC and ccRCC in cell lines. Plasma samples from metastatic patients with tRCC and ccRCC, as well as healthy controls, underwent various epigenomic profiling techniques, including cfChIP-seq for H3K4me3 and H3K27ac markers. Results showed that H3K27ac and H3K4me3 signals were significantly elevated in tRCC compared to healthy samples, with H3K27ac also distinguishing tRCC from ccRCC (P<10^-4, AUROC=0.95). Methylation profiling alone was ineffective for discrimination.
The findings suggest that cfChIP-seq is a promising tool for identifying tRCC and differentiating it from ccRCC and healthy plasma, highlighting its potential for non-invasive diagnosis and informing targeted therapies.
Plasma Proteomic Model to Help Detect Treatment Benefits
PROphetNSCLC, a plasma proteomic model designed to predict benefit from PD-(L)1 inhibitor-based therapy in metastatic non-small cell lung cancer (NSCLC), was evaluated for its predictive value in RCC. This study analyzed pre-treatment plasma samples and clinical data from 201 RCC patients treated with either VEGFR TKI inhibitors, immune checkpoint inhibitors (ICI), or a combination of both.
Patients were categorized as PROphet-positive or PROphet-negative based on plasma proteomic profiles. Kaplan-Meier and Cox analyses showed that PROphet-positive RCC patients (n=143) had significantly improved overall survival (OS) compared to PROphet-negative patients (n=58), with a median OS of 57.5 versus 18.4 months (HR=0.22, P<0.0001). This OS advantage held after adjusting for treatment type and other risk factors (HR=0.21, P<0.0001). PROphet-positive patients also showed better progression-free survival (PFS) than PROphet-negative patients (median PFS 15.6 vs. 8.3 months, HR=0.59, P=0.01).
These findings suggest that proteomic features predictive of outcomes may be shared across cancer types, supporting the utility of PROphetNSCLC in RCC. Ongoing research aims to clarify proteomic markers linked to specific responses to VEGFR TKI versus ICI therapies in RCC.
