Molecular Classification of Renal Cell Carcinoma and Its Implication in Future Clinical Practice

Targeting HIF-2α and anemia: A therapeutic breakthrough for clear-cell renal cell carcinoma

Renal cell carcinoma (RCC) is a heterogenous disease which the incidence is increasing worldwide. The identification and understanding of the role of the Von Hipple Lindau (VHP) in regulating the hypoxia-inducible factor signaling pathway has revolutionized the treatment of this disease. Belzutifan is an oral hypoxia-inducible factor (HIF)-2α inhibitor, which has demonstrated efficacy in treating von Hippel-Lindau (VHL) disease and for the treatment of adults with RCC who experienced disease progression after PD-1/PD-L1- and VEGFR-targeted therapies. One of the most common adverse effect of this drug is anemia; however, it is treatment is not well known. This review summarizes role of the VHL-HIF pathway in ccRCC aroused the interest of targeting HIF activity, the history of belzutifan development and their relationship to anemia as well as propose a management algorithm.

Biomarkers in renal cell carcinoma and their targeted therapies: a review

Renal cell carcinoma (RCC) is one of the most life-threatening urinary malignancies displaying poor response to radiotherapy and chemotherapy. Although in the recent past there have been tremendous advancements in using targeted therapies for RCC, despite that it remains the most lethal urogenital cancer with a 5-year survival rate of roughly 76%. Timely diagnosis is still the key to prevent the progression of RCC into metastatic stages as well as to treat it. But due to the lack of definitive and specific diagnostic biomarkers for RCC and its asymptomatic nature in its early stages, it becomes very difficult to diagnose it. Reliable and distinct molecular markers can not only refine the diagnosis but also classifies the tumors into thier sub-types which can escort subsequent management and possible treatment for patients. Potential biomarkers can permit a greater degree of stratification of patients affected by RCC and help tailor novel targeted therapies. The review summarizes the most promising epigenetic [DNA methylation, microRNA (miRNA; miR), and long noncoding RNA (lncRNA)] and protein biomarkers that have been known to be specifically involved in diagnosis, cancer progression, and metastasis of RCC, thereby highlighting their utilization as non-invasive molecular markers in RCC. Also, the rationale and development of novel molecular targeted drugs and immunotherapy drugs [such as tyrosine kinase inhibitors and immune checkpoint inhibitors (ICIs)] as potential RCC therapeutics along with the proposed implication of these biomarkers in predicting response to targeted therapies will be discussed.

Impact of primary resistance to front-line targeted therapy in metastatic renal cell carcinoma on subsequent immune-checkpoint-inhibition

INTRODUCTION

Synergistic effects have been discussed for tyrosine kinase (TKI) and immune checkpoint inhibitors (ICI). Primary resistance to TKI might disturb subsequent ICI effectiveness. The objective was to investigate, if primary resistance to 1st line TKI monotherapy predicts response to ICI in subsequent therapy lines and impacts overall survival (OS) in advanced renal cell carcinoma (aRCC).

MATERIALS AND METHODS

Retrospectively, aRCC patients which received front-line TKI from 2016 to 2019 were analyzed for the outcomes primary resistance (1LR), response to sequential ICI therapy, progression free survival (PFS) and overall survival (OS). Kaplan-Meier-estimates, Cox proportional hazards and logistic regression were used.

RESULTS

Primary resistance to front-line TKI was observed in 27 (53%) of 51 patients. Groups with disease control (DC) and 1st line TKI resistance (1LR) were not different at baseline with regard to clinicopathological features. Median duration on 1st line therapy was significantly shorter in the 1LR (5.1 months) than in the DC (14.7 months) group (p = 0.01). Sequential therapy was started in 21 (75%) and 12 (52%) patients of 1LR and DC groups using nivolumab in 16 (76%) vs. 11 (92%) cases (p > 0.05). Logistic regression revealed that 1LR status, neutrophil-to-lymphocyte ratio < 3, IMDC favorable prognosis and clear cell histology had no significant impact on responsiveness to ICI in subsequent therapy lines. Cox proportional hazards demonstrated no significant association of 1LR status with PFS and OS in patients who received subsequent ICI treatment.

CONCLUSION

Primary TKI resistance of aRCC was neither significantly associated with responsiveness to ICI during sequential therapy nor with PFS and OS. This adds the evidence for ICI based sequential therapy in primary TKI resistant aRCC.

Supervised Learning and Multi-Omics Integration Reveals Clinical Significance of Inner Membrane Mitochondrial Protein (IMMT) in Prognostic Prediction, Tumor Immune Microenvironment and Precision Medicine for Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) accounts for approximately 75% of all renal cancers. The prognosis for patients with metastatic KIRC is poor, with less than 10% surviving five years after diagnosis. Inner membrane mitochondrial protein (IMMT) plays a crucial role in shaping the inner mitochondrial membrane (IMM), regulation of metabolism and innate immunity. However, the clinical relevance of IMMT in KIRC is not yet fully understood, and its role in shaping the tumor immune microenvironment (TIME) remains unclear. This study aimed to investigate the clinical significance of IMMT in KIRC using a combination of supervised learning and multi-omics integration. The supervised learning principle was applied to analyze a TCGA dataset, which was downloaded and split into training and test datasets. The training dataset was used to train the prediction model, while the test and the entire TCGA dataset were used to evaluate its performance. Based on the risk score, the cutoff between the low and high IMMT group was set at median value. A Kaplan-Meier curve, receiver operating characteristic (ROC) curve, principal component analysis (PCA) and Spearman's correlation were conducted to evaluate the prediction ability of the model. Gene Set Enrichment Analysis (GSEA) was used to investigate the critical biological pathways. Immunogenicity, immunological landscape and single-cell analysis were performed to examine the TIME. Databases including Gene Expression Omnibus (GEO), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were employed for inter-database verification. Pharmacogenetic prediction was analyzed via single-guide RNA (sgRNA)-based drug sensitivity screening using Q-omics v.1.30. Low expressions of IMMT in tumor predicted dismal prognosis in KIRC patients and correlated with KIRC progression. GSEA revealed that low expressions of IMMT were implicated in mitochondrial inhibition and angiogenetic activation. In addition, low IMMT expressions had associations with reduced immunogenicity and an immunosuppressive TIME. Inter-database verification corroborated the correlation between low IMMT expressions, KIRC tumors and the immunosuppressive TIME. Pharmacogenetic prediction identified lestaurtinib as a potent drug for KIRC in the context of low IMMT expressions. This study highlights the potential of IMMT as a novel biomarker, prognostic predictor and pharmacogenetic predictor to inform the development of more personalized and effective cancer treatments. Additionally, it provides important insights into the role of IMMT in the mechanism underlying mitochondrial activity and angiogenesis development in KIRC, which suggests IMMT as a promising target for the development of new therapies.

Cytoreductive Nephrectomy and Metastatic Renal Cell Carcinoma: State of the Art and Future Perspectives

In the past decades, several treatments have been proposed for the management of metastatic renal cell carcinoma (mRCC). Among these, cytoreductive nephrectomy (CN) represents a controversial and open issue in the era of targeted therapy and novel immunotherapy with immune checkpoint inhibitors. Two important studies, CARMENA and SURTIME, analyzed therapy with sunitinib with or without CN, and immediate CN followed by sunitinib versus a deferred CN after three cycles of sunitinib, respectively. CARMENA showed the non-inferiority of sunitinib alone versus sunitinib plus CN, whereas SURTIME showed no difference in progression-free survival (PFS), but a better median OS among patients with deferred CN. Therefore, more prospective clinical trials and appropriate patient identification are necessary to support CN in this new scenario. This review provides a snapshot of the current evidence for CN in mRCC, discusses the management strategies, and offers perspectives on the direction of future research.

Acquired Perforating Dermatosis as a Paraneoplastic Feature: A Case Report, Literature Review, and Novel Association

Kyrle's disease is an uncommon form of acquired transepidermal elimination dermatosis frequently associated with diabetes mellitus and chronic kidney disease. An association with malignancy has been sporadically reported in the literature. Here, we describe the clinical course of a diabetic patient with end-stage renal disease who developed this disorder as a herald to a regionally advanced renal cell carcinoma. We provide a focused literature review and rationale for the definitive categorization of acquired perforating dermatosis as a potential paraneoplastic manifestation of systemic malignancies. Clinicopathological correlation and prompt communication among clinicians for occult malignancies are always warranted. Furthermore, we describe a novel association of one of the subtypes of acquired perforating dermatosis with such malignancies.

Can Molecular Classifications Help Tailor First-line Treatment of Metastatic Renal Cell Carcinoma? A Systematic Review of Available Models

Context

The advent of immune check inhibitors (ICIs) has tremendously changed the prognosis of metastatic renal cell carcinoma (mRCC), adding an unseen substantial overall survival benefit. These agents could be administered alone or in combination with anti-vascular endothelial growth factor (anti-VEGF) therapies. So far, treatment allocation is based only on clinical stratification risk models.

Objective

Herein, we aimed to report the different molecular classifications reported in the first-line treatment of mRCC and discuss the awaited clinical implications in terms of treatment selection.

Evidence acquisition

Medline database as well as European Society for Medical Oncology (ESMO)/American Society of Clinical Oncology (ASCO) conference proceedings were searched to identify biomarker studies. Inclusion criteria comprised randomized and nonrandomized clinical trials that included patients treated in the first line of mRCC setting, patients treated with anti-VEGF therapies or ICIs, biological modeling, and available survival outcomes.

Evidence synthesis

Four classification models were identified with subsequent clinical implications: Beuselinck model (34 gene signatures), IMmotion150, Hakimi, and JAVELIN 101 model. Tumor profiling shows distinct outcomes when treated with one or other combination. Patients are clustered into two gene signatures: angiogenic and proinflammatory (as per JAVELIN). The first is more likely to respond to therapy that includes anti-VEGF agents, while the best outcomes are obtained with an ICI combination with the second.

Conclusions

The findings presented here were mostly derived from ancillary registered studies of new drugs in the setting of mRCC. Further validation is needed, which sets new paradigms for investigation in clinical research based on tumor biology for treatment allocation and not only on clinical stratification tools.

Patient summary

First-line treatment of metastatic kidney includes immunotherapy alone or in combination with antiangiogenic therapy. However, clinical practice demonstrated that the "one treatment fits all" strategy might not be the best approach. In fact, recent studies showed that the addition of immunotherapy agents will not benefit all patients equally, and some still respond either equally to or better than anti-vascular endothelial growth factor alone. This review revealed biomarker modeling that impacts treatment selection. Recent tumor profiling into "angiogenic signature" more sensitive to angiogenic agents versus "immune signature" more likely to achieve the best response with immunotherapy should be validated. Tumor biology features might be more powerful than clinical classification for a tailored treatment approach.

NF2-mutated Renal Carcinomas Have Common Morphologic Features Which Overlap With Biphasic Hyalinizing Psammomatous Renal Cell Carcinoma: A Comprehensive Study of 14 Cases

Genetic alterations involving NF2 occur at low frequencies in renal cell carcinoma across all of the major histologic subtypes and have been associated with adverse outcomes. To better characterize tumors harboring these alterations, we identified 14 cases with NF2 mutations that had been previously diagnosed as papillary renal cell carcinoma; renal cell carcinoma, unclassified; or translocation associated renal cell carcinoma. These tumors were characterized by a tubulopapillary architecture, sclerotic stroma, microscopic coagulative necrosis, and psammomatous calcifications. All the cases displayed eosinophilic cytology as well as a high nuclear grade (World Health Organization/International Society of Urological Pathology [WHO/ISUP] grade 3 to 4) in all but 1 case. A subset of cases shared features with the recently described biphasic hyalinizing psammomatous renal cell carcinoma. Next-generation sequencing demonstrated mutations involving NF2 gene in all cases. In 10 cases, this was paired with the loss of chromosome 22. Additional mutations involving PBRM1 were found in 5 cases that were associated with a more solid growth pattern. Eight patients presented with metastatic disease including all 5 with PBRM1 mutations. Despite the aggressive disease course seen in many of the patients in our series, 2 patients exhibited a dramatic response to immunotherapy. Our results support the existence of a distinct group of cases of renal cell carcinoma characterized by distinct although admittedly nonspecific morphology, an aggressive disease course, and NF2 mutations, often paired with the loss of chromosome 22.

DLK2 Acts as a Potential Prognostic Biomarker for Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common RCC subtype with a high mortality. It has been reported that delta-like 1 homologue (DLK1) participates in the tumor microenvironmental remodeling of ccRCC, but the relationship between delta-like 2 homologue (DLK2, a DLK1 homologue) and ccRCC is still unclear. Thus, this study aims to investigate the role of DLK2 in the biological function and disease prognosis of ccRCC using bioinformatics analysis. The TNMplot database showed that DLK2 was upregulated in ccRCC tissues. From the UALCAN analysis, the overexpression of DLK2 was associated with advanced stage and high grade in ccRCC. Moreover, the Kaplan-Meier plotter (KM Plotter) database showed that DLK2 upregulation was associated with poor survival outcome in ccRCC. By the LinkedOmics analysis, DLK2 signaling may participated in the modulation of ccRCC extracellular matrix (ECM), cell metabolism, ribosome biogenesis, TGF-β signaling and Notch pathway. Besides, Tumor Immune Estimation Resource (TIMER) analysis showed that the macrophage and CD8⁺ T cell infiltrations were associated with good prognosis in ccRCC patients. Finally, DLK2 overexpression was associated with the reduced macrophage recruitments and the M1–M2 polarization of macrophage in ccRCC tissues. Together, DLK2 may acts as a novel biomarker, even therapeutic target in ccRCC. However, this study lacks experimental validation, and further studies are required to support this viewpoint.

Whole-Exome Sequencing Identifies the VHL Mutation (c.262T > C, p.Try88Arg) in Non-Obstructive Azoospermia-Associated Cystic Renal Cell Carcinoma

Von Hippel-Lindau (VHL) genes are intimately involved in renal cell carcinoma (RCC), including clear cell RCC (ccRCC) pathogenesis. However, the contribution of pathogenic VHL mutations to ccRCC remains poorly understood. We report a xanthoderm with non-obstructive azoospermia (NOA)-associated cystic ccRCC, and the missense VHL mutation (c.262T > C, p.Try88Arg). In a 34-year-old patient, a urologic physical examination identified hard epididymis, and imaging tests revealed deferens-associated NOA, as well as multi-organ hydatid cysts, including bilateral epididymal cysts, bilateral testicular cysts, bilateral renal cysts, and pancreatic cysts. Five years later, ccRCC was developed based on clinical and radiologic evidence. Two different prediction models of protein structure and multiple sequence alignment across species were applied to assess the pathological effects of the VHL mutation. The reliability of the assessment in silico was determined by both the cellular location and protein levels of the mutant products, using IF and Western blot, respectively. Our study shows that the missense VHL mutation (c.262T > C, p.Try88Arg) plays a deleterious role in pVHL functions, as predicted by multiple sequence alignment across species. While a structural analysis identified no significant structural alterations in pVHL, the detrimental effects of this mutation were determined by exogenous expression, evidenced by a markedly different spatial distribution and reduced expression of mutant pVHL. This is the first report of the VHL gene mutation (c.475T > C, p.Try88Arg) in a xanthoderm.

Systematic Analysis of the Expression and Prognosis of Fcγ Receptors in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) remains a common malignancy in the urinary system. Although dramatic progress was made in multimodal therapies, the improvement of its prognosis continues to be unsatisfactory. The antibody-binding crystallizable fragment (Fc) γ receptors (FcγRs) are expressed on the surface of leukocytes, to mediate antibody-induced cell-mediated anti-tumor responses when tumor-reactive antibodies are present. FcγRs have been studied extensively in immune cells, but rarely in cancer cells.

Methods

ONCOMINE, UALCAN, GEPIA, TIMER, TISIDB, Kaplan–Meier Plotter, SurvivalMeth, and STRING databases were utilized in this study.

Results

Transcriptional levels of FcγRs were upregulated in patients with ccRCC. There was a noticeable correlation between the over expressions of FCGR1A/B/C, FCGR2A, and clinical cancer stages/tumor grade in ccRCC patients. Besides, higher transcription levels of FcγRs were found to be associated with poor overall survival (OS) in ccRCC patients. Further, high DNA methylation levels of FcγRs were also observed in ccRCC patients, and higher DNA methylation levels of FcγRs were associated with shorter OS. Moreover, we also found that the expression of FcγRs was significantly correlated with immune infiltrates, namely, immune cells (NK, macrophages, Treg, cells) and immunoinhibitor (IL-10, TGFB1, and CTLA-4).

Conclusions

Our study demonstrated that high DNA methylation levels of FcγRs lead to their low mRNA, protein levels, and poor prognosis in ccRCC patients, which may provide new insights into the choice of immunotherapy targets and prognostic biomarkers.

Histologic-Based Tumor-Associated Immune Cells Status in Clear Cell Renal Cell Carcinoma Correlates with Gene Signatures Related to Cancer Immunity and Clinical Outcomes

The three-tier immunophenotype (desert, excluded, and inflamed) and the four-tier immunophenotype (cold, immunosuppressed, excluded, and hot) have been linked to prognosis and immunotherapy response. This study aims to evaluate whether immunophenotypes of clear cell renal cell carcinoma, identified on hematoxylin and eosin-stained slides, correlate with gene expression signatures related to cancer immunity, and clinical outcomes. We evaluated tumor-associated immune cells (TAICs) status using three methodologies: three-tier immunophenotype based on the location of TAICs, four-tier immunophenotype considering both the location and degree of TAICs and inflammation score focusing only on the degree of TAICs, using a localized clear cell renal cell carcinoma cohort (n = 436) and The Cancer Genome Atlas (TCGA)-KIRC cohort (n = 162). We evaluated the association of the TAICs status assessed by three methodologies with CD8 and PD-L1 immunohistochemistry and immune gene expression signatures by TCGA RNA-sequencing data. All three methodologies correlated with immunohistochemical and immune gene expression signatures. The inflammation score and the four-tier immunophenotype showed similarly higher accuracy in predicting recurrence-free survival and overall survival compared to the three-tier immunophenotype. In conclusion, a simple histologic assessment of TIACs may predict clinical outcomes and immunotherapy responses.

Novel emerging biomarkers to immunotherapy in kidney cancer

The treatment of metastatic renal cell carcinoma has significantly evolved in recent years, particularly with the advent of novel immune checkpoint inhibitors (ICI). Despite the striking benefits observed on a population level, outcomes vary and some patients do not respond to ICI-based regimens, ultimately require salvage therapies. An ever deeper understanding of the disease biology mediated by the development of multiple high-throughput molecular omics has led to significant progress in biomarkers discovery. But despite growing insights into the molecular underpinnings of the tumor microenvironment, biomarkers have not been integrated successfully into clinical practice. In this review, we discuss some of the novel emerging predictive biomarkers to ICIs in metastatic renal cell carcinoma.

Integration of NRP1, RGS5, and FOXM1 expression, and tumour necrosis, as a postoperative prognostic classifier based on molecular subtypes of clear cell renal cell carcinoma

Molecular mechanisms of progression of clear cell renal cell carcinoma (ccRCC) have been proven with recent genomic or transcriptional analyses. However, it is still difficult to apply these analyses to daily clinical practice owing to economical and practical issues. Here, we established a pathology-based, postoperative prognostic classification based on the well-validated transcriptional classifier, ClearCode34, in ccRCC. A total of 342 cases with available tissue were identified and randomly allocated into a discovery cohort (n = 138) and a validation cohort (n = 204). Levels of mRNA were quantified using a nCounter Digital Analyzer, and the ccA/ccB subtypes were determined. Histological and immunohistochemistry (IHC) analyses were subsequently performed to establish a pathology-based classification based on the mRNA levels. Finally, the prognostic ability of the new classifier was evaluated in both the discovery and validation cohorts. Of 138 cases in the discovery cohort, 78 (56.5%) and 60 (43.5%) were assigned to the ccA and ccB subtypes, respectively. Proangiogenic genes, neuropilin 1 (NRP1) and regulator of G protein signalling 5 (RGS5), were especially overexpressed in all ccRCC samples and were enriched in ccA-assigned tumours. Histologically, tumour necrosis and the sarcomatoid feature were associated with the ccB subtype. In IHC analyses, expression of NRP1, RGS5, and forkhead box M1 (FOXM1), an epithelial-mesenchymal transition-related factor, significantly correlated with the ccA/ccB subtypes. Combining these three IHC factors and tumour necrosis, we developed the IHC/histology-based classifier, which showed good concordance with the ClearCode34 classifier with an accuracy of 0.80. The established classification significantly stratified relapse-free, cancer-specific, and overall survival rates in both the discovery and validation cohorts. The novel molecular pathology classifier integrating NRP1, RGS5, FOXM1, and tumour necrosis may enable the stratification of oncological outcomes for patients with ccRCC undergoing resection surgery.

The Hypoxic Microenvironment Induces Stearoyl-CoA Desaturase-1 Overexpression and Lipidomic Profile Changes in Clear Cell Renal Cell Carcinoma

Simple Summary

Clear cell renal cell carcinoma (ccRCC) is characterized by a high rate of cell proliferation and an extensive accumulation of lipids. Uncontrolled cell growth usually generates areas of intratumoral hypoxia that define the tumor phenotype. In this work, we show that, under these microenvironmental conditions, stearoyl-CoA desaturase-1 is overexpressed. This enzyme induces changes in the cellular lipidomic profile, increasing the oleic acid levels, a metabolite that is essential for cell proliferation. This work supports the idea of considering stearoyl-CoA desaturase-1 as an exploitable therapeutic target in ccRCC.

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cell carcinoma (RCC). It is characterized by a high cell proliferation and the ability to store lipids. Previous studies have demonstrated the overexpression of enzymes associated with lipid metabolism, including stearoyl-CoA desaturase-1 (SCD-1), which increases the concentration of unsaturated fatty acids in tumor cells. In this work, we studied the expression of SCD-1 in primary ccRCC tumors, as well as in cell lines, to determine its influence on the tumor lipid composition and its role in cell proliferation. The lipidomic analyses of patient tumors showed that oleic acid (18:1n-9) is one of the major fatty acids, and it is particularly abundant in the neutral lipid fraction of the tumor core. Using a ccRCC cell line model and in vitro-generated chemical hypoxia, we show that SCD-1 is highly upregulated (up to 200-fold), and this causes an increase in the cellular level of 18:1n-9, which, in turn, accumulates in the neutral lipid fraction. The pharmacological inhibition of SCD-1 blocks 18:1n-9 synthesis and compromises the proliferation. The addition of exogenous 18:1n-9 to the cells reverses the effects of SCD-1 inhibition on cell proliferation. These data reinforce the role of SCD-1 as a possible therapeutic target.

Quantitative Proteomics Identifies Secreted Diagnostic Biomarkers as well as Tumor-Dependent Prognostic Targets for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the third most common and most malignant urological cancer, with a 5-year survival rate of 10% for patients with advanced tumors. Here, we identified 10,160 unique proteins by in-depth quantitative proteomics, of which 955 proteins were significantly regulated between tumor and normal adjacent tissues. We verified four putatively secreted biomarker candidates, namely, PLOD2, FERMT3, SPARC, and SIRPα, as highly expressed proteins that are not affected by intratumor and intertumor heterogeneity. Moreover, SPARC displayed a significant increase in urine samples of patients with ccRCC, making it a promising marker for the detection of the disease in body fluids. Furthermore, based on molecular expression profiles, we propose a biomarker panel for the robust classification of ccRCC tumors into two main clusters, which significantly differed in patient outcome with an almost three times higher risk of death for cluster 1 tumors compared with cluster 2 tumors. Moreover, among the most significant clustering proteins, 13 were targets of repurposed inhibitory FDA-approved drugs. Our rigorous proteomics approach identified promising diagnostic and tumor-discriminative biomarker candidates which can serve as therapeutic targets for the treatment of ccRCC. IMPLICATIONS: Our in-depth quantitative proteomics analysis of ccRCC tissues identifies the putatively secreted protein SPARC as a promising urine biomarker and reveals two molecular tumor phenotypes.

Review of Prognostic Expression Markers for Clear Cell Renal Cell Carcinoma

Context: The number of prognostic markers for clear cell renal cell carcinoma (ccRCC) has been increasing regularly over the last 15 years, without being integrated and compared. Objective: Our goal was to perform a review of prognostic markers for ccRCC to lay the ground for their use in the clinics. Evidence Acquisition: PubMed database was searched to identify RNA and protein markers whose expression level was reported as associated with survival of ccRCC patients. Relevant studies were selected through cross-reading by two readers. Evidence Synthesis: We selected 249 studies reporting an association with prognostic of either single markers or multiple-marker models. Altogether, these studies were based on a total of 341 distinct markers and 13 multiple-marker models. Twenty percent of these markers were involved in four biological pathways altered in ccRCC: cell cycle, angiogenesis, hypoxia, and immune response. The main genes (VHL, PBRM1, BAP1, and SETD2) involved in ccRCC carcinogenesis are not the most relevant for assessing survival. Conclusion: Among single markers, the most validated markers were KI67, BIRC5, TP53, CXCR4, and CA9. Of the multiple-marker models, the most famous model, ClearCode34, has been highly validated on several independent datasets, but its clinical utility has not yet been investigated. Patient Summary: Over the years, the prognosis studies have evolved from single markers to multiple-marker models. Our review highlights the highly validated prognostic markers and multiple-marker models and discusses their clinical utility for better therapeutic care.

The Therapeutic Landscape of Renal Cell Carcinoma: From the Dark Age to the Golden Age

Oncologic treatments for renal cell carcinoma (RCC) have undergone a major revolution in the past 2 decades, moving away from the pre-2004 Dark Age during which interleukin 2 and interferon-α were the only therapeutic options and induced treatment responses in only 5% to 10% of patients with metastatic disease. The development of anti-angiogenic tyrosine kinase inhibitors against vascular endothelial growth factor receptor 2 and inhibitors of mammalian target of rapamycin complex 1 in 2005 introduced the Modern Age with better overall and progression-free survival and a greater number of patients (30%-40%) responding to and (∼80%) benefiting from these targeted therapeutic agents. The coming of age of the immuno-oncology era with the use of immune checkpoint inhibitors (ICIs) have ushered us into the Golden Age of metastatic RCC care, in which combined administrations of two ICIs (anti-programmed cell death protein 1/programmed death-ligand 1 and anti-cytotoxic T-lymphocyte-associated protein 4 or one tyrosine kinase inhibitor plus one ICI (anti-programmed cell death protein 1/programmed death-ligand 1) have recast the treatment landscape of clear cell RCC, the most common RCC subtype, with an approximately 60% response rate and an approximately 90% disease control rate that further improves metastatic RCC survival. Exciting clinical trials are in the pipeline investigating complementary/synergistic molecular mechanisms, based on studies investigating the biology, pathology, and genomics of renal carcinoma and the respective treatment outcome. This will enable us to enter the Diamond Age of precision medicine in which a specific treatment can be tailored to the specific biological and pathologic circumstance of an individual kidney tumor to offer more effective yet less toxic therapy.

Current Advance of Immune Evasion Mechanisms and Emerging Immunotherapies in Renal Cell Carcinoma

Renal cell carcinoma is a highly heterogeneous cancer group, and the complex microenvironment of the tumor provides appropriate immune evasion opportunities. The molecular mechanism of immune escape in renal cell carcinoma is currently a hot issue, focusing primarily on the major complex of histocompatibility, immunosuppressive cells, their secreted immunosuppressive cytokines, and apoptosis molecule signal transduction. Immunotherapy is the best treatment option for patients with metastatic or advanced renal cell carcinoma and combination immunotherapy based on a variety of principles has shown promising prospects. Comprehensive and in-depth knowledge of the molecular mechanism of immune escape in renal cell carcinoma is of vital importance for the clinical implementation of effective therapies. The goal of this review is to address research into the mechanisms of immune escape in renal cell carcinoma and the use of the latest immunotherapy. In addition, we are all looking forward to the latest frontiers of experimental combination immunotherapy.

Identification of subtype specific biomarkers of clear cell renal cell carcinoma using random forest and greedy algorithm

Suitable biomarkers can be good indicator for cancer subtype. To find biomarkers that can accurately distinguish clear cell renal cell carcinoma (ccRCC) subtypes, we first determined ccRCC subtypes based on the expression of mRNA, miRNA and lncRNA, named clear cell type 1 (ccluster1) and 2 (ccluster2), using three unsupervised clustering algorithms. Besides being associated with the expression pattern derived from the single type of RNA, the differences between subtypes are relevant to the interactions between RNAs. Then, based on ceRNA network, the optimal combination features are selected using random forest and greedy algorithm. Further, in survival-related sub-ceRNA, competing gene pairs centering on miR-106a, miR-192, miR-193b, miR-454, miR-32, miR-98, miR-143, miR-145, miR-204, miR-424 and miR-1271 can also well identify ccluster1 and ccluster2 with prediction accuracy over 92%. These subtype-specific features potentially enhance the accuracy with which machine learning methods predict specific ccRCC subtypes. Simultaneously, the changes of miR-106 and OIP5-AS1 affect cell proliferation and the prognosis of ccluster1. The changes of miR-145 and FAM13A-AS1 in ccluster2 have an effect on cell invasion, apoptosis, migration and metabolism function. Here miR-192 displays a unique characteristic in both subtypes. Two subtypes also display notable differences in diverse pathways. Tumors belonging to ccluster1 are characterized by Fc gamma R-mediated phagocytosis pathway that affects tissue remodeling and repair, whereas those belonging to ccluster2 are characterized by EGFR tyrosine kinase inhibitor resistance pathway that participates in regulation of cell homeostasis. In conclusion, identifying these gene pairs can shed light on therapeutic mechanisms of ccRCC subtypes.

In Situ Metabolomics Expands the Spectrum of Renal Tumours Positive on 99mTc-sestamibi Single Photon Emission Computed Tomography/Computed Tomography Examination

Background

Definite noninvasive characterisation of renal tumours positive on ^99mTc-sestamibi single photon emission computed tomography/computed tomography (SPECT/CT) examination including renal oncocytomas (ROs), hybrid oncocytic chromophobe tumours (HOCTs), and chromophobe renal cell carcinoma (chRCC) is currently not feasible.

Objective

To investigate whether combined ^99mTc-sestamibi SPECT/CT and in situ metabolomic profiling can accurately characterise renal tumours exhibiting ^99mTc-sestamibi uptake.

Design, setting, and participants

A tissue microarray analysis of 33 tumour samples from 28 patients was used to investigate whether their in situ metabolomic status correlates with their features on ^99mTc-sestamibi SPECT/CT examination. In order to validate emerging data, an independent cohort comprising 117 tumours was subjected to matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI MSI).

Outcome measurements and statistical analysis

MALDI MSI data analysis and image generation were facilitated by FlexImaging v. 4.2, while k-means analysis by SCiLS Lab software followed by R-package CARRoT analysis was used for assessing the highest predictive power in the differential of RO versus chRCC. Heatmap-based clustering, sparse partial least-squares discriminant analysis, and volcano plots were created with MetaboAnalyst 3.0.

Results and limitations

We identified a discriminatory metabolomic signature for ^99mTc-sestamibi SPECT/CT–positive Birt-Hogg-Dubè–associated HOCTs versus other renal oncocytic tumours. Metabolomic differences were also evident between ^99mTc-sestamibi–positive and ^99mTc-sestamibi–negative chRCCs, prompting additional expert review; two of three ^99mTc-sestamibi–positive chRCCs were reclassified as low-grade oncocytic tumours (LOTs). Differences were identified between distal-derived tumours from those of proximal tubule origin, including differences between ROs and chRCCs.

Conclusions

The current study expands the spectrum of ^99mTc-sestamibi SPECT/CT–positive renal tumours, encompassing ROs, HOCTs, LOTs, and chRCCs, and supports the feasibility of in situ metabolomic profiling in the diagnostics and classification of renal tumours.

Patient summary

For preoperative evaluation of solid renal tumours, ^99mTc-sestamibi single photon emission computed tomography/computed tomography (SPECT/CT) is a novel examination method. To increase diagnostic accuracy, we propose that ^99mTc-sestamibi–positive renal tumours should be biopsied and followed by a combined histometabolomic analysis.

The Pan-Omics Landscape of Renal Cell Carcinoma and Its Implication on Future Clinical Practice

Renal cell carcinoma has traditionally been classified based on histological features. Contemporary studies have identified genomic, transcriptomic, epigenomic, and metabolomic signatures that correspond to or even transcend histological subtypes. Much remains to be learned about improving the algorithm of pan-omics integration for precision oncology, which will not only advance our understanding of RCC pathobiology and treatment response but also result in novel therapeutic opportunities. Accordingly, this review focuses on recent RCC multi-omics literature. Encouragingly, a few reports on omics integration into routinely employed prognostic risk models have shown early promise that could lay the foundation for future development of precision kidney cancer therapies. Hence, this article serves as a primer on what we have learned and how we might better realize the clinical potential of the burgeoning pan-omics data.

Combination drug regimens for metastatic clear cell renal cell carcinoma

Renal cell carcinomas (RCC) make up about 90% of kidney cancers, of which 80% are of the clear cell subtype. About 20% of patients are already metastatic at the time of diagnosis. Initial treatment is often cytoreductive nephrectomy, but systemic therapy is required for advanced RCC. Single agent targeted therapies are moderately toxic and only somewhat effective, leading to development of immunotherapies and combination therapies. This review identifies limitations of monotherapies for metastatic renal cell carcinoma, discusses recent advances in combination therapies, and highlights therapeutic options under development. The goal behind combining various modalities of systemic therapy is to potentiate a synergistic antitumor effect. However, combining targeted therapies may cause increased toxicity. The initial attempts to create therapeutic combinations based on inhibition of the vascular endothelial growth factor or mammalian target of rapamycin pathways were largely unsuccessful in achieving a profile of increased synergy without increased toxicity. To date, five combination therapies have been approved by the U.S. Food and Drug Administration, with the most recently approved therapies being a combination of checkpoint inhibition plus targeted therapy. Several other combination therapies are under development, including some in the phase 3 stage. The new wave of combination therapies for metastatic RCC has the potential to increase response rates and improve survival outcomes while maintaining tolerable side effect profiles.

The induction of AMPK-dependent autophagy leads to P53 degradation and affects cell growth and migration in kidney cancer cells

The most common subtype of renal cell carcinoma (RCC) is the clear cell RCC (ccRCC) that accounts for 70-80% of cases. The fate of ccRCC is linked to alterations of genes that regulate TP53. The dysfunction of p53 affects several processes including autophagy, which is increased in different advanced carcinomas and could be associated with cancer progression. We report that different kidney cancer cell lines show higher levels of autophagy than control cells. The increased autophagy is associated with the upregulation of miR501-5p, which stimulates mTOR-independent autophagy by the activation of AMP kinase. AMPK activation occurs through the decrease of ATP generation caused by the downregulation of the mitochondrial calcium uniporter (MCU) that leads to the reduction of mitochondrial calcium uptake. Autophagy induction promotes the degradation of p53 through the autophagolysosomal machinery. Consistently, the inhibition of autophagy reduces both cell proliferation and migration enhancing the expression of p53, p21 and E-Cadherin as well as decreasing Vimentin synthesis. Taken together, these findings indicate that autophagy is involved in the progression of kidney cancer. Therefore, the pharmacological targeting of this process could be considered an interesting option for the treatment of advanced renal carcinoma.

Resistance to cancer immunotherapy in metastatic renal cell carcinoma

The prognosis of metastatic clear cell renal cell carcinoma (mccRCC) has changed dramatically over the years with the emergence of immune checkpoint inhibitors (ICI) used alone, or in combination with another ICI, or with vascular endothelial growth factor receptor tyrosine kinase inhibitor. Although major response rates have been observed with ICI, many patients do not respond, reflecting primary resistance, and durable responses remain exceptional, reflecting secondary resistance. Factors contributing to primary and acquired resistance are manifold, including patient-intrinsic factors, tumor cell-intrinsic factors and factors associated with the tumoral microenvironment (TME). While some mechanisms of resistance are common to several tumor types, others are specific to mccRCC. Predictive biomarkers and alternative strategies are needed to overcome this resistance. This review provides an overview of the major ICI resistance mechanisms, highlights the potential of the TME to induce resistance to ICI, and discusses the predictive biomarkers available to guide therapeutic choice.

Exploiting the circuit breaker cancer evolution model in human clear cell renal cell carcinoma

The incessant interactions between susceptible humans and their respective macro/microenvironments registered throughout their lifetime result in the ultimate manifestation of individual cancers. With the average lifespan exceeding 50 years of age in humans since the beginning of 20th century, aging - the "time" factor - has played an ever-increasing role alongside host and environmental factors in cancer incidences. Cancer is a genetic/epigenetic disease due to gain-of-function mutations in cancer-causing genes (oncogene; OG) and/or loss-of-function mutations in tumor-suppressing genes (tumor suppressor genes; TSG). In addition to their integral relationship with cancer, a timely deployment of specific OG and/or TSG is in fact needed for higher organisms like human to cope with respective physiological and pathological conditions. Over the past decade, extensive human kidney cancer genomics have been performed and novel mouse models recapitulating human kidney cancer pathobiology have been generated. With new genomic, genetic, mechanistic, clinical and therapeutic insights accumulated from studying clear cell renal cell carcinoma (ccRCC)-the most common type of kidney cancer, we conceived a cancer evolution model built upon the OG-TSG signaling pair analogous to the electrical circuit breaker (CB) that permits necessary signaling output and at the same time prevent detrimental signaling overdrive. Hence, this viewpoint aims at providing a step-by-step mechanistic explanation/illustration concerning how inherent OG-TSG CBs intricately operate in concert for the organism's wellbeing; and how somatic mutations, the essential component for genetic adaptability, inadvertently triggers a sequential outage of specific sets of CBs that normally function to maintain and protect and individual tissue homeostasis.

Gut Bacteria Composition Drives Primary Resistance to Cancer Immunotherapy in Renal Cell Carcinoma Patients

BACKGROUND

The development of immune checkpoint blockade (ICB) has revolutionized the clinical outcome of renal cell carcinoma (RCC). Nevertheless, improvement of durability and prediction of responses remain unmet medical needs. While it has been recognized that antibiotics (ATBs) decrease the clinical activity of ICB across various malignancies, little is known about the direct impact of distinct intestinal nonpathogenic bacteria (commensals) on therapeutic outcomes of ICB in RCC.

OBJECTIVE

To evaluate the predictive value of stool bacteria composition for ICB efficacy in a cohort of advanced RCC patients.

DESIGN, SETTING, AND PARTICIPANTS

We prospectively collected fecal samples from 69 advanced RCC patients treated with nivolumab and enrolled in the GETUG-AFU 26 NIVOREN microbiota translational substudy phase 2 trial (NCT03013335) at Gustave Roussy. We recorded patient characteristics including ATB use, prior systemic therapies, and response criteria. We analyzed 2994 samples of feces from healthy volunteers (HVs). In parallel, preclinical studies performed in RCC-bearing mice that received fecal transplant (FMT) from RCC patients resistant to ICB (NR-FMT) allowed us to draw a cause-effect relationship between gut bacteria composition and clinical outcomes for ICB. The influence of tyrosine kinase inhibitors (TKIs) taken before starting nivolumab on the microbiota composition has also been assessed.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Metagenomic data (MG) from whole genome sequencing (WGS) were analyzed by multivariate and pairwise comparisons/fold ratio to identify bacterial fingerprints related to ATB or prior TKI exposure and patients' therapeutic response (overall response and progression-free survival), and compared with the data from cancer-free donors.

RESULTS AND LIMITATIONS

Recent ATB use (n = 11; 16%) reduced objective response rates (from 28% to 9%, p < 0.03) and markedly affected the composition of the microbiota, facilitating the dominance of distinct species such as Clostridium hathewayi, which were also preferentially over-represented in stools from RCC patients compared with HVs. Importantly, TKIs taken prior to nivolumab had implications in shifting the microbiota composition. To establish a cause-effect relationship between gut bacteria composition and ICB efficacy, NR-FMT mice were successfully compensated with either FMT from responding RCC patients or beneficial commensals identified by WGS-MG (Akkermansia muciniphila and Bacteroides salyersiae).

CONCLUSIONS

The composition of the microbiota is influenced by TKIs and ATBs, and impacts the success of immunotherapy. Future studies will help sharpen the role of these specific bacteria and their potential as new biomarkers.

PATIENT SUMMARY

We used quantitative shotgun DNA sequencing of fecal microbes as well as preclinical models of fecal or bacterial transfer to study the association between stool composition and (pre)clinical outcome to immune checkpoint blockade. Novel insights into the pathophysiological relevance of intestinal dysbiosis in the prognosis of kidney cancer may lead to innovative therapeutic solutions, such as supplementation with probiotics to prevent primary resistance to therapy.

Identifying BAP1 Mutations in Clear-Cell Renal Cell Carcinoma by CT Radiomics: Preliminary Findings

To evaluate the potential application of computed tomography (CT) radiomics in the prediction of BRCA1-associated protein 1 (BAP1) mutation status in patients with clear-cell renal cell carcinoma (ccRCC). In this retrospective study, clinical and CT imaging data of 54 patients were retrieved from The Cancer Genome Atlas–Kidney Renal Clear Cell Carcinoma database. Among these, 45 patients had wild-type BAP1 and nine patients had BAP1 mutation. The texture features of tumor images were extracted using the Matlab-based IBEX package. To produce class-balanced data and improve the stability of prediction, we performed data augmentation for the BAP1 mutation group during cross validation. A model to predict BAP1 mutation status was constructed using Random Forest Classification algorithms, and was evaluated using leave-one-out-cross-validation. Random Forest model of predict BAP1 mutation status had an accuracy of 0.83, sensitivity of 0.72, specificity of 0.87, precision of 0.65, AUC of 0.77, F-score of 0.68. CT radiomics is a potential and feasible method for predicting BAP1 mutation status in patients with ccRCC.

Molecular characterization and diagnostic criteria of renal cell carcinoma with emphasis on liquid biopsies

Introduction: Over the past 6 years, important genomic and transcriptomic studies performed on RCC reported a comprehensive molecular description of RCC pathogenic alterations. Such molecular findings pave the way for an integrated classification, based on histopathology aspects and molecular alterations in order to personalize the clinical management of RCC.Areas covered: The aim of this review is to evaluate the current knowledge and the potential value of liquid biopsy in RCC. Studies on presence and analysis of circulating tumor DNA (ctDNA), circulating RNA, specific microRNA, long non-coding RNA, and circulating tumor cells are reported for each phase of disease, from the diagnostic setting to the localized disease and, lastly, in the metastatic stage.Expert opinion: Advantages of liquid biopsies compared to serial tissue sampling are numerous. However, some limitations must be addressed before considering liquid biopsy as a noninvasive biomarker of clinical utility. The suboptimal sensitivity depends on the assessment technique and genetic platforms used, the tumor organ, the tumor stage, tumor heterogeneity, and clonality. The rate of discordance with tumor tissue genotyping may depends on temporal heterogeneity, spatial heterogeneity, and/or assay error (false-negative or false-positive genotyping).

Harnessing the Genomic Landscape of the Small Renal Mass to Guide Clinical Management

CONTEXT

Small renal masses (SRMs; tumors <4 cm) encompass a diagnostic and therapeutic challenge. Genomic profiling has the potential to improve risk stratification and personalize treatment selection.

OBJECTIVE

Herein, we review the evidence regarding the utility, challenges, and potential implications of genomic profiling in the management of SRMs.

EVIDENCE ACQUISITION

Pertinent publications available on PubMed database pertaining to kidney cancer, tumor size, genomics, and clinical management were reviewed.

EVIDENCE SYNTHESIS

Compared with larger tumors, SRMs range from benign to lethal, necessitating strategies for improved treatment selection. Recent advances in the molecular characterization of renal cell carcinoma have improved our understanding of the disease; however, utility of these tools for the management of SRMs is less clear. While intratumoral heterogeneity (ITH) reduces the accuracy and reliability of sequencing, relative genomic uniformity of SRMs somewhat lessens the impact of ITH. Therefore, renal mass biopsy of SRMs represents an appealing opportunity to evaluate how incorporation of molecular profiles may improve management strategies.

CONCLUSIONS

Ongoing research into the genomic landscape of SRMs has advanced our understanding of the spectrum of disease aggressiveness and may hold promise in matching disease biology to treatment intensity.

PATIENT SUMMARY

Small renal masses are a clinical challenge, as they range from benign to lethal. Genomic profiling may eventually improve treatment selection, but more research is needed.

Chromosome 3p Loss-Orchestrated VHL, HIF, and Epigenetic Deregulation in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma subtype, and metastatic ccRCC is associated with 5-year survival rates of 10% to 20%. Genetically, ccRCC originates from sequential losses of multiple tumor suppressor genes. Remarkably, chromosome 3p loss occurs in more than 90% of sporadic ccRCCs. This results in concurrent one-copy loss of four tumor suppressor genes that are also mutated individually at high frequency in ccRCC (ie, VHL, 80%; PBRM1, 29% to 46%; BAP1, 6% to 19%; and SETD2, 8% to 30%). Pathogenically, 3p loss probably represents the first genetic event that occurs in sporadic ccRCC and the second genetic event in VHL-mutated hereditary ccRCC. VHL constitutes the substrate recognition module of the VCB-Cul2 E3 ligase that degrades HIF1/2α, whereas PBRM1, BAP1, and SETD2 are epigenetic modulators that regulate gene transcription. Because 3p loss and VHL inactivation are nearly universal truncal events in ccRCC, the resulting HIF1/2 signaling overdrive and accompanied tumor hypervascularization probably underlie the therapeutic benefits observed with vascular endothelial growth factor receptor inhibitors, including sorafenib, sunitinib, pazopanib, axitinib, bevacizumab, cabozantinib, and lenvatinib. Furthermore, recent marked advances in ccRCC genomics, transcriptomics, proteomics, metabolomics, molecular mechanisms, mouse models, prognostic and predictive biomarkers, and clinical trials have rendered invaluable translational insights concerning precision kidney cancer therapeutics. With an armamentarium encompassing 13 drugs that exploit seven unique therapeutic mechanisms (ie, cytokines, vascular endothelial growth factor receptor, mTORC1, cMET/AXL, fibroblast growth factor receptor, programmed cell death-1 and programmed death-ligand 1, and cytotoxic T-cell lymphocyte associated-4) to treat metastatic renal cell carcinoma, one of the imminent clinical questions concerning care of patients with metastatic ccRCC is how a personalized treatment strategy, through rationally combining and sequencing different therapeutic modalities, can be formulated to offer the best clinical outcome for individual patients. Here, we attempt to integrate recent discoveries of immediate translational impacts and discuss future translational challenges and opportunities.

Genomic classifications of renal cell carcinoma: a critical step towards the future application of personalized kidney cancer care with pan-omics precision

Over the past 20 years, classifications of kidney cancer have undergone major revisions based on morphological refinements and molecular characterizations. The 2016 WHO classification of renal tumors recognizes more than ten different renal cell carcinoma (RCC) subtypes. Furthermore, the marked inter- and intra-tumor heterogeneity of RCC is now well appreciated. Nevertheless, contemporary multi-omics studies of RCC, encompassing genomics, transcriptomics, proteomics, and metabolomics, not only highlight apparent diversity but also showcase and underline commonality. Here, we wish to provide an integrated perspective concerning the future 'functional' classification of renal cancer by bridging gaps among morphology, biology, multi-omics, and therapeutics. This review focuses on recent progress and elaborates the potential value of contemporary pan-omics approaches with a special emphasis on cancer genomics unveiled through next-generation sequencing technology, and how an integrated multi-omics approach might impact precision-based personalized kidney cancer care in the near future. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Molecular Subtypes of Clear Cell Renal Cell Carcinoma Are Associated With Outcome During Pazopanib Therapy in the Metastatic Setting

BACKGROUND

We previously described 4 molecular subtypes of metastatic clear cell renal cell carcinoma (mccRCC), named ccrcc1-4 (Beuselinck et al, 2015). These have both prognostic and predictive value for patients treated with first-line sunitinib, with distinctive objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). The ccrcc2 and ccrcc3 tumors have the best outcomes, followed by ccrcc1 and then ccrcc4. We hypothesized that these molecular subtypes would show similar outcomes with first-line pazopanib treatment.

PATIENTS AND METHODS

We classified 28 mccRCC tumors treated with pazopanib as first-line therapy, as described previously. The primary endpoints were PFS and OS from the start of pazopanib. A secondary endpoint was ORR. Because there were only 2 ccrcc3 tumors, they were pooled with the ccrcc2 tumors for outcome analysis.

RESULTS

PFS was 9 months for the ccrcc2 and ccrcc3 tumors, 5 months for ccrcc1 tumors, and 3 months for the ccrcc4 tumors (P = .011). The corresponding OS duration was 69, 19, and 5 months (P = .003). The corresponding ORR was 50%, 33%, and 0%. The corresponding mean tumor size decreased by 34%, 6%, and 2% (P = .032). The ccrcc1-4 classification was a stronger predictor of outcome than the International Metastatic Renal Cell Carcinoma Database Consortium score on univariate analysis (P = .011 vs. P = .094 for PFS and P = .003 vs. .013 for OS). Both remained independent on bivariate analysis.

CONCLUSION

The molecular subtypes of mccRCC are associated with outcome on pazopanib as first-line therapy. The prognostic and predictive value of the ccrcc1-4 molecular classification requires validation in prospective trials.