Trials In Renal Cell Carcinoma Research Articles

Abstract SY41-01: Selection of targeted neoantigens for personalized cancer vaccines

Abstract Neoantigen targeting personalized cancer vaccines (PCV) have the potential to revolutionize cancer treatment. These personalized vaccines rely on accurate epitope prediction and selection. We previously reported phase I trials of neoantigen targeting PCV in melanoma and glioblastoma multiforme (GBM). Recently we concluded a trial in renal cell carcinoma (RCC) where the neoantigen targeting PCV was immunogenic in all patients, targeted cancer drivers, and demonstrated in vitro reactivity to primary patient tumors. The neoantigen selection pipeline at DFCI supporting clinical trials utilizes immunopeptidome-trained epitope prediction algorithms to design synthetic long peptides as vaccine antigens containing predicted HLA Class I neoantigens. We also prioritize highly expressed neoantigens and neoantigens originating from cancer drivers as vaccine epitopes. For future iterations of this pipeline, we aspire to include novel classes of neoantigens originating from endogenous human retroviruses (ERV), fusion epitopes, novel or unannotated open reading frames (nuORFs), and immunopeptidome-identified neoantigens. The neoantigen selection pipeline is currently supporting multiple cancer vaccine trials at DFCI targeting melanoma, GBM, RCC, ovarian cancer, and chronic lymphocytic leukemia (CLL). Citation Format: Derin Keskin. Selection of targeted neoantigens for personalized cancer vaccines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY41-01.

FDA pooled analysis of overall survival according to depth of response as a continuous variable in frontline advanced immuno-oncology renal cell carcinoma trials.

418 Background: Retrospective analyses of individual studies of immune-oncology-containing combinations (IOC) for advanced renal cell carcinoma (aRCC) suggest that depth of response (DepOR; % reduction from baseline in sum of target lesion diameters) is associated with overall survival (OS). However, these analyses are limited by use of DepOR categories with a small number of patients and guarantee-time bias. We therefore sought to investigate the relationship of week 12 DepOR as a continuous variable with OS, hypothesizing not only complete but also deep partial responses might portend favorable longer-term survival. Methods: We pooled data from patients with treatment (tx)-naïve aRCC enrolled in randomized IO-based frontline aRCC trials submitted to FDA that included a Week 12 imaging assessment. We developed 36-month (mo) overall survival (OS) prediction models based on Week 12 DepOR per Independent Review Committee using Cox proportional hazards with natural spline in the IO-TKI combination (IOC) and sunitinib (SUN) groups. To avoid guarantee-time bias, OS was defined from date of an individual patient’s 12-week imaging, among the subset of patients who were alive and in follow-up at the Week 12 scan. Results: Four trials met inclusion criteria (KEYNOTE-426, JAVELIN Renal 100, CheckMate 9ER, CheckMate 214); in total there were 1364 patients in the IOC group and 1267 patients in the SUN group. Eligibility criteria, baseline patient characteristics, and endpoints were similar both between the trials and between tx groups. Deepest response occurred at median 31 weeks (interquartile range [IQR], 18-55) in the IOC group and 29 weeks (IQR range, 17-48) in the SUN group. At Week 12, 34.7% of patients had DepOR of at least 30%; median DepOR was 27.6% (interquartile range [IQR] 8.7 to 43.4%) in the IOC and 13.7% (IQR 2.5 to 26.3%) in the SUN group. DepOR and 36-month OS were correlated throughout the entire range of DepOR in both tx groups; at each DepOR, the IOC group had slightly higher 36-mo OS over SUN. We saw similar results modeling 24-month OS compared to 36-month OS. Conclusions: This pooled exploratory analysis suggests that deeper response is associated with better 36-month OS in patients treated with IOC or SUN and slightly higher probability of 36-month OS for any given DepOR for IOC vs. SUN. We saw no plateau in OS as DepOR approached complete response. However, caution should be used when interpreting DepOR at the tails due to sparse data. Further work characterizing the relationship between DepOR and OS at the trial level may advance understanding of the utility of DepOR as an early endpoint in signal-seeking trials and to facilitate efficient drug development. Additionally, identifying patients with favorable long-term prognosis based on DepOR provides hypotheses for new trial designs.

Assessment of eligibility criteria in renal cell carcinoma trials evaluating systemic therapy.

To characterise the restrictiveness of eligibility criteria in contemporary renal cell carcinoma (RCC) trials, using recommendations from the American Society of Clinical Oncology (ASCO)-Friends of Cancer Research (FCR) initiative. vPhase I-III trials assessing systemic therapies in patients with RCC starting between 30 June 2012 and 30 June 2022 were identified. Eligibility criteria regarding brain metastases, prior or concurrent malignancies, hepatitis B virus (HBV) or hepatitis C virus (HCV) infection, and human immunodeficiency virus (HIV) infection were identified and stratified into three groups: exclusion, conditional inclusion, and not reported. Descriptive statistics were used to determine the frequency of eligibility criteria. Fisher's exact test or chi-square test were used to calculate their associations with certain trial characteristics. A total of 423 RCC trials were initially identified of which 112 (26.5%) had sufficient accessible information. Exclusion of patients with HIV infection, HBV/HCV infection, brain metastases, and prior or concurrent malignancies were reported in 74.1%, 53.6%, 33.0%, and 8.0% of trials, respectively. In the context of HIV and HBV/HCV infection, patients were largely excluded from trials evaluating immunotherapy (94.4% and 77.8%, respectively). In addition, brain metastases were excluded in trials assessing targeted therapy (36.4%), combined therapy (33.3%), and immunotherapy (22.2%). Exclusion of patients with prior or concurrent malignancies was less frequently reported, accounting for 9.1%, 8.3%, and 5.6% targeted therapy, combined therapy and immunotherapy trials, respectively. A substantial proportion of RCC trials utilise restrictive eligibility criteria, excluding patients with fairly prevalent comorbidities. Implementing the ASCO-FCR recommendations will ensure resulting data are more inclusive and aligned with patient populations in the real-world.

TNM-based risk eligibility for adjuvant trials in renal cell carcinoma

TNM-based risk eligibility for adjuvant trials in renal cell carcinoma

Biomarker-driven prospective clinical trial in renal cell carcinoma: Developing machine learning models to allocate patients to treatment arms using RNA sequencing.

4525 Background: RNA sequencing has shown promise in defining the biology of individual renal cell carcinoma (RCC) tumors. However, these biomarkers have not yet been translated to the clinic for prospectively assigning optimal treatments to patients. Challenges for RNA-seq biomarker development include translating classifiers across different assays/platforms, normalization of data collected from single patients in the clinic and establishing robust thresholds for assigning prediction groups. We have designed the prospective phase II OPTIC RCC clinical trial (clinicaltrials.gov NCT05361720) to test the utility of an RNA-seq based biomarker in predicting treatment based on biologic drivers relevant to angiogenesis (anti-angiogenesis; TKI) and immune microenvironment (immunotherapy; IO). Here, we will describe the development and optimization of a machine learning model for assigning individual patients to biologically driven clusters in real time to facilitate RNA-seq based biomarker trials. Methods: We have utilized RNA-seq data from the IMmotion 151 trial (ref) to develop a machine learning model. Clusters were grouped into three based on their association to tumor biology and treatment: (1) Cluster 1+2 (angiogenic signature → TKI+IO therapy), (2) Cluster 4+5 (immune/proliferative signature → dual IO therapy), (3) Cluster 3+6 (neither signature → exclude). Random forest classifier was used to train a multi-class model to predict the three groups. The model is evaluated using bootstrapped cross-validation. Results: Our machine learning classifier was built using 188 genes and has a cross-validation accuracy of 85% and sensitivity of >90% in predicting patients into one of the three biological clusters from our training data. Predictions of the classifier are significantly associated with progression-free survival across different treatments within each of the predicted groups. We also observed significant odds ratios when comparing responders (CR/PR/SD) to non-responders (PD) across the treatment groups. The model was then validated in two independent test sets treated with Angio and IO inhibitors: (1) 61 patient renal cell carcinoma cohort (2) 12 patient clear cell renal cell carcinoma cohort. We observed a significant enrichment of responders to Angio+IO treatment for the predicted Cluster_Angio patients compared to IO treatment (p=0.05), highlighting the importance of matching patients to their optimal treatment. Conclusions: We have developed an accurate machine learning model to assign individual patients to RNA-seq clusters in real time. This classifier will facilitate the prospective OPTIC RCC trial. If successful, our biomarker strategy will serve as a proof of concept for selecting optimal treatments for RCC patients.

FDA analysis of treatment-free survival in frontline advanced immuno-oncology–VEGF TKI renal cell carcinoma trials.

e13602 Background: Treatment-free survival (TFS) with and without (w/o) toxicity are outcome measures that describe health states where patients are experiencing clinically stable disease while off anti-cancer treatment, a clinically meaningful attribute seen with some immune-oncology (IO) regimens. We sought to characterize TFS with and w/o ongoing toxicity in addition to time on protocol therapy (combination and monotherapy) in trials of frontline IO-VEGF tyrosine kinase inhibitor (TKI) combinations in pts with advanced renal cell carcinoma (aRCC). Methods: We pooled randomized trials submitted to FDA evaluating IO-TKI combination in treatment-naïve aRCC with at least 30 months (mos) of median follow-up. OS was partitioned into health states, including TFS, defined as area between Kaplan-Meier curves for 2 time-to-event endpoints originating at randomization: 1) time to all protocol therapy cessation and 2) time to subsequent systemic therapy initiation or death. Health state areas under the curve were estimated by 30-mo restricted mean times. We pooled data by treatment arm. Results: Three trials (KEYNOTE-426, JAVELIN Renal 100, CheckMate 9ER) met criteria for analysis; in total, 1183 pts received IO-TKI vs. 1184 on control arms receiving sunitinib (SUN). IO-TKI and SUN groups spent 9% (2.7 mos [95% confidence interval (CI): 1.8, 3.5]) and 10% (2.9 mos [95% CI: 2.1, 3.8]) of the 30-mo period alive and treatment-free. Mean TFS with grade ≥3 toxicity were 1 and 0.6 mos in the IO-TKI and SUN groups, respectively. Mean TFS w/o grade ≥3 toxicity were 1.7 and 2.3 mos in IO-TKI and SUN groups, respectively. In IO-TKI group, the 30-mo mean time on combination therapy was 13.7 mos (46% of 30-mo period) and 3.9 mos on monotherapy (13% of 30-mo period). Following cessation of one drug in IO-TKI arm, monotherapy duration of TKI was longer than IO: 2.9 and 1 mos, respectively. Conclusions: In this descriptive, exploratory analysis, TFS and TFS w/o toxicity were similar in IO-TKI group compared to SUN group, in contrast to improved TFS in IO-IO vs. SUN seen in published literature. Among pts on IO-TKI, more time was spent on TKI monotherapy than IO monotherapy. These findings may reflect continuation of TKI until progression per protocol design in all trials and discontinuation of IO after 2 years in 2 trials, and may inform individual pt choice of IO-IO vs. IO-TKI. [Table: see text]

FDA pooled analysis of overall survival according to depth of response as a continuous variable in frontline advanced immuno-oncology renal cell carcinoma trials.

e16532 Background: Retrospective analyses of individual studies of immune-oncology-containing combinations (IOC) for advanced renal cell carcinoma (aRCC) suggest that depth of response (DepOR; % reduction from baseline in sum of target lesion diameters) is associated with overall survival (OS). However, these analyses are limited by use of DepOR categories with a small number of patients and guarantee-time bias. We therefore sought to investigate the relationship of week 12 DepOR as a continuous variable with OS, hypothesizing not only complete but also deep partial responses might portend favorable longer-term survival. Methods: We pooled data from patients with treatment (tx)-naïve aRCC enrolled in randomized IO-based frontline aRCC trials submitted to FDA that included a Week 12 imaging assessment. We developed 36-month (mo) overall survival (OS) prediction models based on Week 12 DepOR per Independent Review Committee using Cox proportional hazards with natural spline in the IO-TKI combination (IOC) and sunitinib (SUN) groups. To avoid guarantee-time bias, OS was defined from date of an individual patient’s 12-week imaging, among the subset of patients who were alive and in follow-up at the Week 12 scan. Results: Four trials met inclusion criteria (KEYNOTE-426, JAVELIN Renal 100, CheckMate 9ER, CheckMate 214); in total, there were 1364 patients in the IOC group and 1267 patients in the SUN group. Eligibility criteria, baseline patient characteristics, and endpoints were similar both between the trials and between tx groups. Deepest response occurred at median 31 weeks (interquartile range [IQR], 18-55) in the IOC group and 29 weeks (IQR range, 17-48) in the SUN group. At Week 12, 34.7% of patients had DepOR of at least 30%; median DepOR was 27.6% (interquartile range [IQR] 8.7 to 43.4%) in the IOC and 13.7% (IQR 2.5 to 26.3%) in the SUN group. DepOR and 36-month OS were correlated throughout the entire range of DepOR in both tx groups; at each DepOR, the IOC group had slightly higher 36-mo OS over SUN. We saw similar results modeling 24-month OS compared to 36-month OS. Conclusions: This pooled exploratory analysis suggests that deeper response is associated with better 36-month OS in patients treated with IOC or SUN and slightly higher probability of 36-month OS for any given DepOR for IOC vs. SUN. We saw no plateau in OS as DepOR approached complete response. However, caution should be used when interpreting DepOR at the tails due to sparse data. Further work characterizing the relationship between DepOR and OS at the trial level may advance understanding of the utility of DepOR as an early endpoint in signal-seeking trials and to facilitate efficient drug development. Additionally, identifying patients with favorable long-term prognosis based on DepOR provides hypotheses for new trial designs.

Patient-reported outcomes in metastatic renal cell carcinoma trials using combinations versus sunitinib as first-line treatment.

Over the past 5 years, several new immunotherapy treatments have been tested for metastatic renal cell carcinoma (mRCC). Clinical trials assessing combinations of different immunotherapies, or of an immunotherapy with a tyrosine kinase inhibitor (TKI), have reported improved clinical outcomes compared with the standard of care - that is, treatments using TKIs alone. However, to understand the holistic impact of new treatments on patients, physicians must also consider effects on health-related quality of life (HRQoL). As patient-reported outcome measures (PROMs) on HRQoL are often treated as a secondary outcome in clinical trials, their collection and reporting are non-standardized and, therefore, difficult to compare and interpret. However, results from six clinical trials indicate that two immunotherapy treatments overwhelmingly outperform sunitinib in HRQoL measurements: nivolumab plus cabozantinib (CheckMate 9ER) and atezolizumab plus bevacizumab (IMmotion151). An additional two treatments generally outperform sunitinib: nivolumab plus ipilimumab (CheckMate 214) and lenvatinib plus pembrolizumab (CLEAR). Of three studies that reported no difference from sunitinib, two suffered design flaws that might have obscured HRQoL benefits (JAVELIN Renal 101and KEYNOTE-426). To ensure future HRQoL data are of the highest quality and comparable across trials, future studies should adopt best practices for the design, analysis and reporting of PROMs.

Evaluation of eligibility criteria in contemporary renal cell carcinoma based on ASCO-FCR recommendations.

612 Background: A consensus statement from the American Society of Clinical Oncology (ASCO) and Friends of Cancer Research (FCR) collaboration highlights the importance of expanding eligibility criteria in cancer trials to more accurately reflect the real-world population (Kim et al., Clin Cancer Res 2021). We sought to characterize use of overly restrictive eligibility criteria in renal cell carcinoma (RCC) trials in the context of ASCO-FCR recommendations. Methods: Studies containing the MeSH terms “(metastatic OR advanced OR stage IV or unresectable) AND (kidney cancer OR renal cell carcinoma OR renal cell cancer)” from June 30, 2012 to June 30, 2022 were identified on the ClinicalTrials.gov platform. Our search query’s inclusion criteria identified international studies examining adult patients aged ≥ 18 in phase I-III trials. Exclusion criteria comprised pan-cancer studies, trials involving localized treatments, radiation therapy, and prognostic tools. Descriptive statistics were used to characterize the frequency of restrictive eligibility criteria across studies, while Fisher’s exact test or chi-square test were utilized to determine the association between treatment type and exclusion criteria. Results: The content of 423 RCC trials were analyzed, of which 112 (26.5%) had adequate data available. 48 (42.9%), 44 (39.3%) and 18 (16.1%) studies examined combination therapy, targeted therapy, and immunotherapy, respectively. The presence of HIV positivity, HBV/HCV positivity, brain metastases, and concurrent malignancies accounted for the most frequently cited exclusionary criteria, seen in 83/112 (74.1%), 60/112 (53.6%), 37/112 (33.0%), and 9/112 (8.0%) studies respectively. Differences in the use of HIV positivity (p<0.001) and HBV/HCV positivity (p<0.001) as eligibility criteria were observed across classes of therapy (see Table). Conclusions: A significant proportion of RCC studies utilize overly restrictive eligibility criteria as highlighted by the ASCO-FCR joint statement. Appropriate broadening of eligibility criteria to incorporate patient populations mirroring a real-world setting will provide more useful data going forward. [Table: see text]

Chimeric Antigen Receptor (CAR) T-cell Treatment in Renal Cell Carcinoma: Current Clinical Trials and Future Directions

Renal cell carcinoma (RCC) has long been found to be responsive to immunotherapy. While high dose interleukin-2 resulted in some durable remissions, this treatment has largely been replaced by immune checkpoint inhibitor therapy, due to the safer toxicity profile and emerging evidence for long term remissions. However, the majority of patients continue to face disease progression and death from metastatic RCC. Chimeric antigen receptor T-cells (CAR T) represent the next step in immunotherapy for this malignancy and hold promise for a higher rate of durable remissions. The realization of this therapeutic strategy for RCC will require identification of the best tumor antigen and T cell modifications and will depend on achieving remissions with an acceptable toxicity profile. This review summarizes current CAR T-cell treatment targets and clinical trials for metastatic RCC, highlighting the potential therapeutic impact as well as obstacles to successful development.

Evolving Role of Adjuvant Systemic Therapy for Kidney and Urothelial Cancers.

The role of adjuvant therapy in renal cell carcinoma and urothelial carcinoma is rapidly evolving. To date, the U.S. Food and Drug Administration has approved sunitinib and pembrolizumab in the adjuvant setting for renal cell carcinoma and nivolumab for urothelial carcinoma based on disease-free survival benefit. The U.S. Food and Drug Administration held a joint workshop with the National Cancer Institute and the Society of Urologic Oncology in 2017 to harmonize design elements, including eligibility and radiologic assessments across adjuvant trials in renal cell carcinoma and urothelial carcinoma. Considerations from the discussion at these workshops led the U.S. Food and Drug Administration to draft guidances to help inform subsequent adjuvant trial design for renal cell carcinoma and urothelial carcinoma. Patient-centered decision-making is crucial when determining therapeutic choices in the adjuvant setting; utility functions can be used to help quantify each patient's goals, values, and risk/benefit trade-offs to ensure that the decision regarding adjuvant therapy is informed by their preferences and the evolving outcomes data.

HLA-A*03 and response to immune checkpoint blockade in cancer: an epidemiological biomarker study.

Predictive biomarkers could allow more precise use of immune checkpoint inhibitors (ICIs) in treating advanced cancers. Given the central role of HLA molecules in immunity, variation at the HLA loci could differentially affect the response to ICIs. The aim of this epidemiological study was to determine the effect of HLA-A*03 as a biomarker for predicting response to immunotherapy. In this epidemiological study, we investigated the clinical outcomes (overall survival, progression free survival, and objective response rate) after treatment for advanced cancer in eight cohorts of patients: three observational cohorts of patients with various types of advanced tumours (the Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets [MSK-IMPACT] cohort, the Dana-Farber Cancer Institute [DFCI] Profile cohort, and The Cancer Genome Atlas) and five clinical trials of patients with advanced bladder cancer (JAVELIN Solid Tumour) or renal cell carcinoma (CheckMate-009, CheckMate-010, CheckMate-025, and JAVELIN Renal 101). In total, these cohorts included 3335 patients treated with various ICI agents (anti-PD-1, anti-PD-L1, and anti-CTLA-4 inhibitors) and 10 917 patients treated with non-ICI cancer-directed therapeutic approaches. We initially modelled the association of HLA amino-acid variation with overall survival in the MSK-IMPACT discovery cohort, followed by a detailed analysis of the association between HLA-A*03 and clinical outcomes in MSK-IMPACT, with replication in the additional cohorts (two further observational cohorts and five clinical trials). HLA-A*03 was associated in an additive manner with reduced overall survival after ICI treatment in the MSK-IMPACT cohort (HR 1·48 per HLA-A*03 allele [95% CI 1·20-1·82], p=0·00022), the validation DFCI Profile cohort (HR 1·22 per HLA-A*03 allele, 1·05-1·42; p=0·0097), and in the JAVELIN Solid Tumour clinical trial for bladder cancer (HR 1·36 per HLA-A*03 allele, 1·01-1·85; p=0·047). The HLA-A*03 effect was observed across ICI agents and tumour types, but not in patients treated with alternative therapies. Patients with HLA-A*03 had shorter progression-free survival in the pooled patient population from the three CheckMate clinical trials of nivolumab for renal cell carcinoma (HR 1·31, 1·01-1·71; p=0·044), but not in those receiving control (everolimus) therapies. Objective responses were observed in none of eight HLA-A*03 homozygotes in the ICI group (compared with 59 [26·6%] of 222 HLA-A*03 non-carriers and 13 (17·1%) of 76 HLA-A*03 heterozygotes). HLA-A*03 was associated with shorter progression-free survival in patients receiving ICI in the JAVELIN Renal 101 randomised clinical trial for renal cell carcinoma (avelumab plus axitinib; HR 1·59 per HLA-A*03 allele, 1·16-2·16; p=0·0036), but not in those receiving control (sunitinib) therapy. Objective responses were recorded in one (12·5%) of eight HLA-A*03 homozygotes in the ICI group (compared with 162 [63·8%] of 254 HLA-A*03 non-carriers and 40 [55·6%] of 72 HLA-A*03 heterozygotes). HLA-A*03 was associated with impaired outcome in meta-analysis of all 3335 patients treated with ICI at genome-wide significance (p=2·01 × 10-8) with no evidence of heterogeneity in effect (I2 0%, 95% CI 0-0·76) INTERPRETATION: HLA-A*03 is a predictive biomarker of poor response to ICI. Further evaluation of HLA-A*03 is warranted in randomised trials. HLA-A*03 carriage could be considered in decisions to initiate ICI in patients with cancer. National Institutes of Health, Merck KGaA, and Pfizer.

Advantages of multi-arm non-randomised sequentially allocated cohort designs for Phase II oncology trials

BackgroundEfficient trial designs are required to prioritise promising drugs within Phase II trials. Adaptive designs are examples of such designs, but their efficiency is reduced if there is a delay in assessing patient responses to treatment.MethodsMotivated by the WIRE trial in renal cell carcinoma (NCT03741426), we compare three trial approaches to testing multiple treatment arms: (1) single-arm trials in sequence with interim analyses; (2) a parallel multi-arm multi-stage trial and (3) the design used in WIRE, which we call the Multi-Arm Sequential Trial with Efficient Recruitment (MASTER) design. The MASTER design recruits patients to one arm at a time, pausing recruitment to an arm when it has recruited the required number for an interim analysis. We conduct a simulation study to compare how long the three different trial designs take to evaluate a number of new treatment arms.ResultsThe parallel multi-arm multi-stage and the MASTER design are much more efficient than separate trials. The MASTER design provides extra efficiency when there is endpoint delay, or recruitment is very quick.ConclusionsWe recommend the MASTER design as an efficient way of testing multiple promising cancer treatments in non-comparative Phase II trials.

Adherence to oral therapies among patients with renal cell carcinoma: Post hoc analysis of the ECOG-ACRIN E2805 trial.

BackgroundAs use of oral cancer therapies increases, patient adherence has become critical when evaluating the effectiveness of therapy. In a phase III trial for renal cell carcinoma, we: (a) characterized adherence to sorafenib, sunitinib, and/or placebo and (b) identified factors associated with non‐adherence.MethodsECOG‐ACRIN E2805 was a double‐blind, placebo‐controlled, randomized trial comparing adjuvant sorafenib or sunitinib in patients with resected primary renal cell carcinoma at high risk for recurrence. We used patient‐completed pill diaries to measure adherence as the number of pills taken divided by the number of pills prescribed. Log‐binomial regression was used to identify correlates of non‐adherence (<80% of prescribed pills reported as taken).ResultsMean adherence was 90.7% among those assigned to sunitinib (n = 613) and 84.8% among those assigned to sorafenib (n = 616). Among those assigned to placebo, mean adherence was 94.9% and 92.4% to sunitinib and sorafenib placebo, respectively. Non‐adherence was associated with race/ethnicity (non‐Hispanic Black: prevalence ratio [PR] 2.22, 95% CI 1.63, 3.01; Hispanic: PR 1.54, 95% CI 1.05, 2.26), high volume enrollment (≥10 patients: PR 1.30, 95% CI 1.03, 1.64), treatment group (sunitinib: PR 2.24, 95% CI 1.66, 3.02; sorafenib: PR 2.37, 95% CI 1.74, 3.22), and skin rash (PR 1.36, 95% CI 1.03, 1.80).ConclusionAmong patients participating in a randomized clinical trial, adherence to oral cancer therapies was lower compared to placebo. Adherence was also worse in racial/ethnic minorities, those experiencing toxicities, and high volume enrolling sites. Our findings highlight several challenges to address in clinical practice as use of oral therapies continues to increase.Clinical trial registration numberThis trial is registered with ClinicalTrials.gov, number NCT00326898.

Prevalence and Landscape of Actionable Genomic Alterations in Renal Cell Carcinoma

Abstract Purpose: We report our experience with next-generation sequencing to characterize the landscape of actionable genomic alterations in renal cell carcinoma (RCC). Experimental Design: A query of our institutional clinical sequencing database (MSK-IMPACT) was performed that included tumor samples from 38,468 individuals across all cancer types. Somatic variations were annotated using a precision knowledge database (OncoKB) and the available clinical data stratified by level of evidence. Alterations associated with response to immune-checkpoint blockade (ICB) were analyzed separately; these included DNA mismatch repair (MMR) gene alterations, tumor mutational burden (TMB), and microsatellite instability (MSI). Data from The Cancer Genome Atlas (TCGA) consortium as well as public data from several clinical trials in metastatic RCC were used for validation purposes. Multiregional sequencing data from the TRAcking Cancer Evolution through Therapy (TRACERx) RENAL cohort were used to assess the clonality of somatic mutations. Results: Of the 753 individuals with RCC identified in the MSK-IMPACT cohort, 115 showed evidence of targetable alterations, which represented a prevalence of 15.3% [95% confidence interval (CI), 12.7%–17.8%). When stratified by levels of evidence, the alterations identified corresponded to levels 2 (11.3%), 3A (5.2%), and 3B (83.5%). A low prevalence was recapitulated in the TCGA cohort at 9.1% (95% CI, 6.9%–11.2%). Copy-number variations predominated in papillary RCC tumors, largely due to amplifications in the MET gene. Notably, higher rates of actionability were found in individuals with metastatic disease (stage IV) compared with those with localized disease (OR, 2.50; 95% CI, 1.16–6.16; Fisher's P = 0.01). On the other hand, the prevalence of alterations associated with response to ICB therapy was found to be approximately 5% in both the MSK-IMPACT and TCGA cohorts and no associations with disease stage were identified (OR, 1.35; 95% CI, 0.46–5.40; P = 0.8). Finally, multiregional sequencing revealed that the vast majority of actionable mutations occurred later during tumor evolution and were only present subclonally in RCC tumors. Conclusions: RCC harbors a low prevalence of clinically actionable alterations compared with other tumors and the evidence supporting their clinical use is limited. These aberrations were found to be more common in advanced disease and seem to occur later during tumor evolution. Our study provides new insights on the role of targeted therapies for RCC and highlights the need for additional research to improve treatment selection using genomic profiling.

Debulking surgery for malignant tumors: the current status, evidence and future perspectives.

Debulking surgery, also called cytoreductive surgery, is a resection of the tumor as much as possible and an intended incomplete resection for unresectable malignant tumors. Since the most important principle in surgical oncology is complete R0 resection, debulking surgery goes against the basic principle and obscures the concept of operability. However, debulking surgery has been advocated for various types of advanced malignant tumors, including gynecological cancers, urological cancers, gastrointestinal cancers, breast cancers and other malignancies, with or without adjuvant therapy. Positive data from randomized trials have been shown in subsets of ovarian cancer, renal cell carcinoma, colorectal cancer and breast cancer. However, recent trials for renal cell carcinoma, colorectal cancer and breast cancer have tended to show controversial results, mainly according to the survival improvement of nonsurgical systemic therapy alone. On the other hand, debulking surgery still has a therapeutic role for slow-growing and borderline malignant tumors, such as pseudomyxoma peritonei and thymomas. The recent understanding of tumor heterogeneity and clonal evolution responsible for malignancy and drug resistance indicates that select patients may obtain prolonged survival by the synergistic effect of debulking surgery and novel systemic therapy. This review aimed to describe the current status and evidence of debulking surgery in a cross-organ manner and to discuss future perspectives in the current era with advances in systemic therapy.

PROSPER: Phase III RandOmized Study Comparing PERioperative nivolumab versus observation in patients with renal cell carcinoma (RCC) undergoing nephrectomy (ECOG-ACRIN EA8143).

TPS4596 Background: There is no standard adjuvant systemic therapy that increases overall survival (OS) over surgery alone for non-metastatic RCC. Anti-PD-1 nivolumab (nivo) improves OS in metastatic RCC and is well tolerated. In mouse models, priming the immune system prior to surgery with anti-PD-1 results in superior OS compared to adjuvant dosing. Remarkable pathologic responses have been seen with neoadjuvant PD-1 in multiple ph 2 studies in bladder, lung and breast cancers. Phase 2 neoadjuvant RCC trials of nivo show preliminary feasibility and safety with no surgical delays. PROSPER RCC seeks to improve clinical outcomes by priming the immune system with neoadjuvant nivo prior to nephrectomy followed by continued immune system engagement with adjuvant blockade in patients (pts) with high risk RCC compared to standard of care surgery alone. Methods: This global, unblinded, phase 3 National Clinical Trials Network study is accruing pts with clinical stage ≥T2 or TanyN+ RCC of any histology planned for radical or partial nephrectomy. Select oligometastatic disease is permitted if the pt can be rendered ‘no evidence of disease’ within 12 weeks of nephrectomy (≤3 metastases; no brain, bone or liver). In the investigational arm, nivo is administered 480mg IV q4 weeks with 1 dose prior to surgery followed by 9 adjuvant doses. The control arm is nephrectomy followed by standard of care surveillance. There is no placebo. Baseline tumor biopsy is required only in the nivo arm but encouraged in both. Randomized pts are stratified by clinical T stage, node positivity, and M stage. 805 pts provide 84.2% power to detect a 14.4% absolute benefit in recurrence-free survival at 5 years assuming the ASSURE historical control of ̃56% to 70% (HR = 0.70). The study is powered to evaluate a significant increase in OS (HR 0.67). Critical perioperative therapy considerations such as safety, feasibility, and quality of life metrics are integrated. PROSPER RCC embeds a wealth of translational studies to examine the contribution of the baseline immune milieu and neoadjuvant priming with anti-PD-1 on clinical outcomes. As of February 10, 2021, 704 patients have been enrolled (N = 805). Clinical trial information: NCT03055013.

Predicting Disease Recurrence, Early Progression, and Overall Survival Following Surgical Resection for High-risk Localized and Locally Advanced Renal Cell Carcinoma

BackgroundRisk stratification for localized renal cell carcinoma (RCC) relies heavily on retrospective models, limiting their generalizability to contemporary cohorts. ObjectiveTo introduce a contemporary RCC prognostic model, developed using prospective, highly annotated data from a phase III adjuvant trial. Design, setting, and participantsThe model utilizes outcome data from the ECOG-ACRIN 2805 (ASSURE) RCC trial. Outcome measurements and statistical analysisThe primary outcome for the model is disease-free survival (DFS), with overall survival (OS) and early disease progression (EDP) as secondary outcomes. Model performance was assessed using discrimination and calibration tests. Results and limitationsA total of 1735 patients were included in the analysis, with 887 DFS events occurring over a median follow-up of 9.6 yr. Five common tumor variables (histology, size, grade, tumor necrosis, and nodal involvement) were included in each model. Tumor histology was the single most powerful predictor for each model outcome. The C-statistics at 1 yr were 78.4% and 81.9% for DFS and OS, respectively. Degradation of the DFS, DFS validation set, and OS model's discriminatory ability was seen over time, with a global c-index of 68.0% (95% confidence interval or CI [65.5, 70.4]), 68.6% [65.1%, 72.2%], and 69.4% (95% CI [66.9%, 71.9%], respectively. The EDP model had a c-index of 75.1% (95% CI [71.3, 79.0]). ConclusionsWe introduce a contemporary RCC recurrence model built and internally validated using prospective and highly annotated data from a clinical trial. Performance characteristics of the current model exceed available prognostic models with the added benefit of being histology inclusive and TNM agnostic. Patient summaryImportant decisions, including treatment protocols, clinical trial eligibility, and life planning, rest on our ability to predict cancer outcomes accurately. Here, we introduce a contemporary renal cell carcinoma prognostic model leveraging high-quality data from a clinical trial. The current model predicts three outcome measures commonly utilized in clinical practice and exceeds the predictive ability of available prognostic models.

Health-related quality-of-life outcomes from a phase II open-label trial of two different starting doses of lenvatinib in combination with everolimus for treatment of renal cell carcinoma following one prior VEGF-targeted treatment.

314 Background: Renal cell carcinoma (RCC) is the most common type of kidney cancer, constituting 80% to 85% of primary renal neoplasms. Preserving health-related quality of life (HRQOL) is an important goal during RCC treatment, but HRQOL analyses in prospective clinical trials in RCC are limited. We report changes in HRQOL, a secondary endpoint of this phase II trial. Methods: HRQOL data were collected during a multicenter, randomized, open-label phase II study comparing the safety and efficacy of two different starting doses of lenvatinib (18 mg vs. 14 mg daily [QD]) in combination with everolimus (5 mg QD), following one prior vascular endothelial growth factor–targeted treatment (NCT03173560). HRQOL was measured using three different instruments, including the FKSI-DRS, EORTC QLQ-C30, and EQ-5D-3L. Change from baseline HRQOL was assessed using linear mixed-effects models. Deterioration events for time to deterioration (TTD) analyses were defined using established thresholds for minimally important differences in the change from baseline for each scale (i.e., 10 points for EORTC, 3 points for FKSI-DRS, 0.08 points for EQ-5D index, and 10 points for EQ-VAS). The distribution of TTD and median TTD for each treatment arm were estimated using the Kaplan-Meier method. Results: Baseline characteristics, including baseline scores of the 343 participants randomly assigned to 14 mg QD lenvatinib (n = 172) and 18 mg QD lenvatinib (n = 171), were well balanced. The average scores for the 18 mg QD group were generally higher, with lower symptom severity than the 14 mg QD group. The least squares mean estimates for change from baseline were favorable for the 18 mg QD group over the 14 mg QD group for the FKSI-DRS and most EORTC QLQ-C30 scales; however, the differences between treatments did not exceed the minimally important difference for clinical significance. Both study arms showed an increase diarrhea severity. Median TTD was longer among participants in the 18 mg QD group than those in the 14 mg QD group for most scales. Conclusions: In most scales, participants who received an 18 mg QD lenvatinib starting dose had better HRQOL and longer time to deterioration than those who received a 14 mg QD starting dose. These findings suggest that the approved treatment regimen of an 18 mg starting dose of lenvatinib in combination with everolimus remains favorable for RCC treatment, following one prior vascular endothelial growth factor–targeted treatment. Clinical trial information: NCT03173560 .

Abstract NG13: Metabolomic adaptations and correlates of survival to immune checkpoint blockade

Abstract NG13: Metabolomic adaptations and correlates of survival to immune checkpoint blockade