A novel molecular signature identifies mixed subtypes in renal cell carcinoma with poor prognosis and independent response to immunotherapy.

BACKGROUND: Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes. For therapy selection, precise subtype identification and individualized prognosis are mandatory, but currently limited. Our aim was to refine subtyping and outcome prediction across main subtypes, assuming that a tumor is composed of molecular features present in distinct pathological subtypes. METHODS: Individual RCC samples were modeled as linear combination of the main subtypes (clear cell (ccRCC), papillary (pRCC), chromophobe (chRCC)) using computational gene expression deconvolution. The new molecular subtyping was compared with histological classification of RCC using the Cancer Genome Atlas (TCGA) cohort (n = 864; ccRCC: 512; pRCC: 287; chRCC: 65) as well as 92 independent histopathologically well-characterized RCC. Predicted continuous subtypes were correlated to cancer-specific survival (CSS) in the TCGA cohort and validated in 242 independent RCC. Association with treatment-related progression-free survival (PFS) was studied in the JAVELIN Renal 101 (n = 726) and IMmotion151 trials (n = 823). CSS and PFS were analyzed using the Kaplan-Meier and Cox regression analysis. RESULTS: One hundred seventy-four signature genes enabled reference-free molecular classification of individual RCC. We unambiguously assign tumors to either ccRCC, pRCC, or chRCC and uncover molecularly heterogeneous tumors (e.g., with ccRCC and pRCC features), which are at risk of worse outcome. Assigned proportions of molecular subtype-features significantly correlated with CSS (ccRCC (P = 4.1E - 10), pRCC (P = 6.5E - 10), chRCC (P = 8.6E - 06)) in TCGA. Translation into a numerical RCC-R(isk) score enabled prognosis in TCGA (P = 9.5E - 11). Survival modeling based on the RCC-R score compared to pathological categories was significantly improved (P = 3.6E - 11). The RCC-R score was validated in univariate (P = 3.2E - 05; HR = 3.02, 95% CI: 1.8-5.08) and multivariate analyses including clinicopathological factors (P = 0.018; HR = 2.14, 95% CI: 1.14-4.04). Heterogeneous PD-L1-positive RCC determined by molecular subtyping showed increased PFS with checkpoint inhibition versus sunitinib in the JAVELIN Renal 101 (P = 3.3E - 04; HR = 0.52, 95% CI: 0.36 - 0.75) and IMmotion151 trials (P = 0.047; HR = 0.69, 95% CI: 0.48 - 1). The prediction of PFS significantly benefits from classification into heterogeneous and unambiguous subtypes in both cohorts (P = 0.013 and P = 0.032). CONCLUSION: Switching from categorical to continuous subtype classification across most frequent RCC subtypes enables outcome prediction and fosters personalized treatment strategies.

Use of Contrast Ultrasound for Renal Mass Evaluation.

An introduction to the expanding modality of contrast-enhanced ultrasound is provided, along with basics on contrast agents and technique. The contrast ultrasound findings of multiple renal tumors are reviewed with examples, including clear cell renal cell carcinoma, papillary renal cell carcinoma, chromophobe renal cell carcinoma, other rare renal cell carcinoma subtypes, oncocytoma, upper tract urothelial carcinoma, lymphoma, and angiomyolipoma, followed also by brief discussions of renal infections and pseudolesions.

The Identification of Immunological Biomarkers in Kidney Cancers.

The recent approval of several agents have revolutionized the scenario of therapeutic management of metastatic renal cell carcinoma (RCC) allowing us to reach important clinical end points with extended patients' survival. Actually, every new drug approved has represented an important step forward to the improvement of patient's survival. On the other hand, we now understand that RCC includes a large group of tumor entities, each of them with different genetic and mutational alterations, but also showing different clinical behavior; a reason behind the needs of subtype specific personalized approach to therapy of RCC. Immunotherapy is gradually becoming a key factor in the therapeutic algorithm for patients with locally advanced or metastatic RCC. Due to the combination of potent treatment success and potentially deadly adverse effects from immune checkpoint inhibitors (ICI), gathering prognostic and predictive information about FDA-indicated tumors seems to be prudent. Robust and reliable biomarkers are crucial for patient's selection of treatments with immunomodulatory drugs. PD-L1 expression is a poor prognostic factor and predictive of better responses from both PD-1 and PD-L1 inhibitors in a variety of tumor types including RCC. Each FDA approved PD-1/PD-L1 drug is paired with a PD-L1 Immunohistochemistry (IHC) assay. Thus, there is need for improved knowledge and application of PD-1/PD-L1 IHC biomarkers in daily practice. IHC staining appears in membranous fashion. The atezolizumab approved IHC assay is unique in that only immune cell staining is quantified for the use of this assay in RCC. A single biomarker for patient selection may not be feasible, given that immune responses are dynamic and evolve over time. Biomarker development for ICI drugs will likely require integration of multiple biologic components like PD-L1 expression, TILs and mutational load. New methodological approaches based on digital pathology may be relevant since they will allow recognition of the biomarker and to objectively quantitate its expression, and therefore might produce objective and reproducible cut-off assessment. Multidisciplinary approach is very much needed to fully develop the current and future value of ICI in clinical practice.

Expression of CD105 cancer stem cell marker in three subtypes of renal cell carcinoma.

BACKGROUND: CD105 is recently described as a cancer stem cell (CSC) marker. OBJECTIVE: The present study was aimed to investigate the expression and prognostic significance of the CSC marker CD105 in different histological subtypes of renal cell carcinoma (RCC). METHODS: Expression of CD105 was evaluated using immunohistochemistry in RCC samples on tissue microarrays including clear cell RCCs (ccRCCs), papillary, and chromophobe RCCs. The association between CD105 expression and clinicopathological features as well as survival outcomes was determined. RESULTS: In ccRCC, increased tumoral cytoplasmic and endothelial expression of CD105 were significantly associated with advanced stage, renal vein invasion, and microvascular invasion (MVI). In addition, MVI was associated with a worse overall survival (OS). Moreover, in multivariate analysis tumor stage and nuclear grade were independent prognostic factors for OS both in case of tumoral cytoplasmic and endothelial CD105 expression. Additionally, CD105 expression was found to be a predictor of worse OS in univariate analysis. However, in papillary and chromophobe RCC, no significant association was found between CD105 expression and clinicopathological parameters or prognosis. CONCLUSIONS: We showed that CD105 expression was associated with more aggressive tumor behavior, more advanced disease, and worse prognosis in ccRCC but not in the other RCC subtypes.