BAP1-related signature predicts benefits from immunotherapy over VEGFR/mTOR inhibitors in ccRCC: a retrospective analysis of JAVELIN Renal 101 and checkmate-009/010/025 trials.

In patients with advanced clear cell renal cell carcinoma, despite the undoubted benefits from immune checkpoint inhibitor (ICI)-based therapies over monotherapies of angiogenic/mTOR inhibitors in the intention-to-treat population, approximately a quarter of the patients can scarcely gain advantage from ICIs, prompting the search for predictive biomarkers for patient selection. Clinical and multi-omic data of 2428 ccRCC patients were obtained from The Cancer Genome Atlas (TCGA, n = 537), JAVELIN Renal 101 (avelumab plus axitinib vs. sunitinib, n = 885), and CheckMate-009/010/025 (nivolumab vs. everolimus, n = 1006). BAP1 mutations were associated with large progression-free survival (PFS) benefits from ICI-based immunotherapies over sunitinib/everolimus (pooled estimate of interaction HR = 0.71, 95% CI 0.51-0.99, P = 0.045). Using the top 20 BAP1 mutation-associated differentially expressed genes (DEGs) generated from the TCGA cohort, we developed the BAP1-score, negatively correlated with angiogenesis and positively correlated with multiple immune-related signatures concerning immune cell infiltration, antigen presentation, B/T cell receptor, interleukin, programmed death-1, and interferon. A high BAP1-score indicated remarkable PFS benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors (avelumab plus axitinib vs. sunitinib: HR = 0.55, 95% CI 0.43-0.70, P < 0.001; nivolumab vs. everolimus: HR = 0.72, 95% CI 0.52-1.00, P = 0.045), while these benefits were negligible in the low BAP1-score subgroup (HR = 1.16 and 1.02, respectively). In advanced ccRCCs, the BAP1-score is a biologically and clinically significant predictor of immune microenvironment and the clinical benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors, demonstrating its potential utility in optimizing the personalized therapeutic strategies in patients with advanced ccRCC.

Liu K ，Huang Y ，Xu Y ，Wang G ，Cai S ，Zhang X ，Shi T ... -  《-》

Genomic Biomarkers of a Randomized Trial Comparing First-line Everolimus and Sunitinib in Patients with Metastatic Renal Cell Carcinoma.

Metastatic renal cell carcinoma (RCC) patients are commonly treated with vascular endothelial growth factor (VEGF) inhibitors or mammalian target of rapamycin inhibitors. Correlations between somatic mutations and first-line targeted therapy outcomes have not been reported on a randomized trial. To evaluate the relationship between tumor mutations and treatment outcomes in RECORD-3, a randomized trial comparing first-line everolimus (mTOR inhibitor) followed by sunitinib (VEGF inhibitor) at progression with the opposite sequence in 471 metastatic RCC patients. Targeted sequencing of 341 cancer genes at ∼540× coverage was performed on available tumor samples from 258 patients; 220 with clear cell histology (ccRCC). Associations between somatic mutations and median first-line progression free survival (PFS1L) and overall survival were determined in metastatic ccRCC using Cox proportional hazards models and log-rank tests. Prevalent mutations (≥ 10%) were VHL (75%), PBRM1 (46%), SETD2 (30%), BAP1 (19%), KDM5C (15%), and PTEN (12%). With first-line everolimus, PBRM1 and BAP1 mutations were associated with longer (median [95% confidence interval {CI}] 12.8 [8.1, 18.4] vs 5.5 [3.1, 8.4] mo) and shorter (median [95% CI] 4.9 [2.9, 8.1] vs 10.5 [7.3, 12.9] mo) PFS1L, respectively. With first-line sunitinib, KDM5C mutations were associated with longer PFS1L (median [95% CI] of 20.6 [12.4, 27.3] vs 8.3 [7.8, 11.0] mo). Molecular subgroups of metastatic ccRCC based on PBRM1, BAP1, and KDM5C mutations could have predictive values for patients treated with VEGF or mTOR inhibitors. Most tumor DNA was obtained from primary nephrectomy samples (94%), which could impact correlation statistics. PBRM1, BAP1, and KDM5C mutations impact outcomes of targeted therapies in metastatic ccRCC patients. Large-scale genomic kidney cancer studies reported novel mutations and heterogeneous features among individual tumors, which could contribute to varied clinical outcomes. We demonstrated correlations between somatic mutations and treatment outcomes in clear cell renal cell carcinoma, supporting the value of genomic classification in prospective studies.

Hsieh JJ ，Chen D ，Wang PI ，Marker M ，Redzematovic A ，Chen YB ，Selcuklu SD ，Weinhold N ，Bouvier N ，Huberman KH ，Bhanot U ，Chevinsky MS ，Patel P ，Pinciroli P ，Won HH ，You D ，Viale A ，Lee W ，Hakimi AA ，Berger MF ，Socci ND ，Cheng EH ，Knox J ，Voss MH ，Voi M ，Motzer RJ ... -  《-》

Targeted therapy for metastatic renal cell carcinoma.

Several comparative randomised controlled trials (RCTs) have been performed including combinations of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors since the publication of a Cochrane Review on targeted therapy for metastatic renal cell carcinoma (mRCC) in 2008. This review represents an update of that original review. To assess the effects of targeted therapies for clear cell mRCC in patients naïve to systemic therapy. We performed a comprehensive search with no restrictions on language or publication status. The date of the latest search was 18 June 2020. We included randomised controlled trials, recruiting patients with clear cell mRCC naïve to previous systemic treatment. The index intervention was any TKI-based targeted therapy. Two review authors independently assessed the included studies and extracted data for the primary outcomes: progression-free survival (PFS), overall survival (OS) and serious adverse events (SAEs); and the secondary outcomes: health-related quality of life (QoL), response rate and minor adverse events (AEs). We performed statistical analyses using a random-effects model and rated the certainty of evidence according to the GRADE approach. We included 18 RCTs reporting on 11,590 participants randomised across 18 comparisons. This abstract focuses on the primary outcomes of select comparisons. 1. Pazopanib versus sunitinib Pazopanib may result in little to no difference in PFS as compared to sunitinib (hazard ratio (HR) 1.05, 95% confidence interval (CI) 0.90 to 1.23; 1 study, 1110 participants; low-certainty evidence). Based on the control event risk of 420 per 1000 in this trial at 12 months, this corresponds to 18 fewer participants experiencing PFS (95% CI 76 fewer to 38 more) per 1000 participants. Pazopanib may result in little to no difference in OS compared to sunitinib (HR 0.92, 95% CI 0.80 to 1.06; 1 study, 1110 participants; low-certainty evidence). Based on the control event risk of 550 per 1000 in this trial at 12 months, this corresponds to 27 more OSs (95% CI 19 fewer to 70 more) per 1000 participants. Pazopanib may result in little to no difference in SAEs as compared to sunitinib (risk ratio (RR) 1.01, 95% CI 0.94 to 1.09; 1 study, 1102 participants; low-certainty evidence). Based on the control event risk of 734 per 1000 in this trial, this corresponds to 7 more participants experiencing SAEs (95% CI 44 fewer to 66 more) per 1000 participants. 2. Sunitinib versus avelumab and axitinib Sunitinib probably reduces PFS as compared to avelumab plus axitinib (HR 1.45, 95% CI 1.17 to 1.80; 1 study, 886 participants; moderate-certainty evidence). Based on the control event risk of 550 per 1000 in this trial at 12 months, this corresponds to 130 fewer participants experiencing PFS (95% CI 209 fewer to 53 fewer) per 1000 participants. Sunitinib may result in little to no difference in OS (HR 1.28, 95% CI 0.92 to 1.79; 1 study, 886 participants; low-certainty evidence). Based on the control event risk of 890 per 1000 in this trial at 12 months, this would result in 29 fewer OSs (95% CI 78 fewer to 8 more) per 1000 participants. Sunitinib may result in little to no difference in SAEs (RR 1.01, 95% CI 0.93 to 1.10; 1 study, 873 participants; low-certainty evidence). Based on the control event risk of 705 per 1000 in this trial, this corresponds to 7 more SAEs (95% CI 49 fewer to 71 more) per 1000 participants.  3. Sunitinib versus pembrolizumab and axitinib Sunitinib probably reduces PFS as compared to pembrolizumab plus axitinib (HR 1.45, 95% CI 1.19 to 1.76; 1 study, 861 participants; moderate-certainty evidence). Based on the control event risk of 590 per 1000 in this trial at 12 months, this corresponds to 125 fewer participants experiencing PFS (95% CI 195 fewer to 56 fewer) per 1000 participants. Sunitinib probably reduces OS (HR 1.90, 95% CI 1.36 to 2.65; 1 study, 861 participants; moderate-certainty evidence). Based on the control event risk of 880 per 1000 in this trial at 12 months, this would result in 96 fewer OSs (95% CI 167 fewer to 40 fewer) per 1000 participants. Sunitinib may reduce SAEs as compared to pembrolizumab plus axitinib (RR 0.90, 95% CI 0.81 to 1.02; 1 study, 854 participants; low-certainty evidence) although the CI includes the possibility of no effect. Based on the control event risk of 604 per 1000 in this trial, this corresponds to 60 fewer SAEs (95% CI 115 fewer to 12 more) per 1000 participants.  4. Sunitinib versus nivolumab and ipilimumab Sunitinib may reduce PFS as compared to nivolumab plus ipilimumab (HR 1.30, 95% CI 1.11 to 1.52; 1 study, 847 participants; low-certainty evidence). Based on the control event risk of 280 per 1000 in this trial at 30 months' follow-up, this corresponds to 89 fewer PFSs (95% CI 136 fewer to 37 fewer) per 1000 participants. Sunitinib reduces OS (HR 1.52, 95% CI 1.23 to 1.89; 1 study, 847 participants; high-certainty evidence). Based on the control event risk 600 per 1000 in this trial at 30 months, this would result in 140 fewer OSs (95% CI 219 fewer to 67 fewer) per 1000 participants. Sunitinib probably increases SAEs (RR 1.37, 95% CI 1.22 to 1.53; 1 study, 1082 participants; moderate-certainty evidence). Based on the control event risk of 457 per 1000 in this trial, this corresponds to 169 more SAEs (95% CI 101 more to 242 more) per 1000 participants. Based on the low to high certainty of evidence, several combinations of immune checkpoint inhibitors appear to be superior to single-agent targeted therapy in terms of PFS and OS, and with a favourable AE profile. Some single-agent targeted therapies demonstrated a similar or improved oncological outcome compared to others; minor differences were observed for AE within this group. The certainty of evidence was variable ranging from high to very low and all comparisons were based on single trials.

Hofmann F ，Hwang EC ，Lam TB ，Bex A ，Yuan Y ，Marconi LS ，Ljungberg B ... -  《Cochrane Database of Systematic Reviews》

Genomically annotated risk model for advanced renal-cell carcinoma: a retrospective cohort study.

The Memorial Sloan Kettering Cancer Center (MSKCC) risk model is an established prognostic tool for metastatic renal-cell carcinoma that integrates clinical and laboratory data, but is agnostic to tumour genomics. Several mutations, including BAP1 and PBRM1, have prognostic value in renal-cell carcinoma. Using two independent clinical trial datasets of patients with metastatic renal-cell carcinoma, we aimed to study whether the addition of the mutation status for several candidate prognostic genes to the MSKCC model could improve the model's prognostic performance. In this retrospective cohort study, we used available formalin-fixed paraffin-embedded tumour tissue and clinical outcome data from patients with metastatic renal-cell carcinoma assigned to treatment with tyrosine kinase inhibitors in the COMPARZ trial (training cohort; n=357) and RECORD-3 trial (validation cohort; n=258). Eligible patients in both trials were treatment-naive; had histologically confirmed, advanced, or metastatic renal-cell carcinoma; and a Karnofsky performance status score of at least 70. For each cohort, data from patients in all treatment groups (sunitinib and pazopanib in the training cohort, and everolimus and sunitinib in the validation cohort) were pooled for this analysis. In the training cohort, tumour tissue was used to evaluate somatic mutations by next-generation sequencing, and the association between cancer-specific outcomes (overall survival, progression-free survival, and overall response) and the mutation status of six genes of interest (BAP1, PBRM1, TP53, TERT, KDM5C, and SETD2) was tested. Only those genes with prognostic value in this setting were added to the MSKCC risk model to create a genomically annotated version. The validation cohort was used to independently test the prognostic value of the annotated model compared with the original MSKCC risk model. 357 (32%) of 1110 patients assigned to protocol treatment in the COMPARZ study between August, 2008, and September, 2011, were evaluable for mutation status and clinical outcomes in the training cohort. The independent validation cohort included 258 (55%) of 471 evaluable patients, enrolled between October, 2009, and June, 2011, on the RECORD-3 study. In the training cohort, the presence of any mutation in BAP1 or TP53, or both, and absence of any mutation in PBRM1 were prognostic in terms of overall survival (TP53wt/BAP1mut, TP53mut/BAP1wt o TP53mut/BAP1mut vs TP53wt/BAP1wt hazard ratio [HR] 1·57, 95% CI 1·21-2·04; p=0·0008; PBRM1wt vs PBRMmut, HR 1·58, 1·16-2·14; p=0·0035). The mutation status for these three prognostic genes were added to the original MSKCC risk model to create a genomically annotated version. Distribution of participants in the training cohort into the three risk groups of the original MSKCC model changed from 87 (24%) of 357 patients deemed at favourable risk, 217 (61%) at intermediate risk, and 53 (15%) at poor risk, to distribution across four risk groups in the genomically annotated risk model, with 36 (10%) of 357 deemed at favourable risk, 77 (22%) at good risk, 108 (30%) at intermediate risk, and 136 (38%) at poor risk. Addition of genomic information improved model performance for predicting overall survival (C-index: original model, 0·595 [95% CI 0·557-0·634] vs new model, 0·637 [0·595-0·679]) and progression-free survival (0·567 [95% CI 0·529-0·604] vs 0·602 [0·560-0·643]) with adequate discrimination of the proportion of patients who achieved an objective response (Cochran-Armitage one-sided p=0·0014). Analyses in the validation cohort confirmed the superiority of the genomically annotated risk model over the original version. The mutation status of BAP1, PBRM1, and TP53 has independent prognostic value in patients with advanced or metastatic renal-cell carcinoma treated with first-line tyrosine kinase inhibitors. Improved stratification of patients across risk groups by use of a genomically annotated model including the mutational status of these three genes warrants further investigation in prospective trials and could be of use as a model to stratify patients with metastatic renal-cell carcinoma in clinical trials. Novartis Pharmaceuticals Corporation, MSKCC Support Grant/Core Grant, and the J Randall & Kathleen L MacDonald Research Fund.

Voss MH ，Reising A ，Cheng Y ，Patel P ，Marker M ，Kuo F ，Chan TA ，Choueiri TK ，Hsieh JJ ，Hakimi AA ，Motzer RJ ... -  《-》

Improvement in survival end points of patients with metastatic renal cell carcinoma through sequential targeted therapy.

Survival of patients with metastatic renal cell carcinoma (mRCC) has improved since the advent of targeted therapy. Approved agents include the multi-targeted tyrosine kinase inhibitors (TKIs) sunitinib, sorafenib, axitinib, pazopanib, cabozantinib, and lenvatinib (approved in combination with everolimus), the anti-VEGF monoclonal antibody bevacizumab, the mammalian target of rapamycin (mTOR) inhibitors everolimus and temsirolimus, and the programmed death-1 (PD-1) targeted immune checkpoint inhibitor nivolumab. The identification of predictive and prognostic factors of survival is increasing, and both clinical predictive factors and pathology-related prognostic factors are being evaluated. Serum-based biomarkers and certain histologic subtypes of RCC, as well as clinical factors such as dose intensity and the development of some class effect adverse events, have been identified as predictors of survival. Expression levels of microRNAs, expression of chemokine receptor 4, hypermethylation of certain genes, VEGF polymorphisms, and elevation of plasma fibrinogen or d-dimer have been shown to be prognostic indicators of survival. In the future, prognosis and treatment of patients with mRCC might be based on genomic classification, especially of the 4 most commonly mutated genes in RCC (VHL, PBRM1, BAP1, and SETD2). Median overall survival has improved for patients treated with a first-line targeted agent compared with survival of patients treated with first-line interferon-α, and results of clinical trials have shown a survival benefit of sequential treatment with targeted agents. Prognosis of patients with mRCC will likely improve with optimization and individualization of current sequential treatment with targeted agents.

Calvo E ，Schmidinger M ，Heng DY ，Grünwald V ，Escudier B ... -  《-》