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BACKGROUND: Surgery for renal cell carcinoma (RCC) with venous tumour thrombus (VTT) extension into the renal vein (RV) and/or inferior vena cava (IVC) has high peri-surgical morbidity/mortality. NAXIVA assessed the response of VTT to axitinib, a potent tyrosine kinase inhibitor. METHODS: NAXIVA was a single-arm, multi-centre, Phase 2 study. In total, 20 patients with resectable clear cell RCC and VTT received upto 8 weeks of pre-surgical axitinib. The primary endpoint was percentage of evaluable patients with VTT improvement by Mayo level on MRI. Secondary endpoints were percentage change in surgical approach and VTT length, response rate (RECISTv1.1) and surgical morbidity. RESULTS: In all, 35% (7/20) patients with VTT had a reduction in Mayo level with axitinib: 37.5% (6/16) with IVC VTT and 25% (1/4) with RV-only VTT. No patients had an increase in Mayo level. In total, 75% (15/20) of patients had a reduction in VTT length. Overall, 41.2% (7/17) of patients who underwent surgery had less invasive surgery than originally planned. Non-responders exhibited lower baseline microvessel density (CD31), higher Ki67 and exhausted or regulatory T-cell phenotype. CONCLUSIONS: NAXIVA provides the first Level II evidence that axitinib downstages VTT in a significant proportion of patients leading to reduction in the extent of surgery. CLINICAL TRIAL REGISTRATION: NCT03494816.

Simple Summary We evaluated renal cancer with varying aggressive appearances on histology, using an emerging form of non-invasive metabolic MRI. This imaging technique assesses the uptake and metabolism of a breakdown product of glucose (pyruvate) labelled with hyperpolarized carbon-13. We show that pyruvate metabolism is dependent on the aggressiveness of an individual tumor and we provide a mechanism for this finding from tissue analysis of molecules influencing pyruvate metabolism, suggesting a role for its membrane transporter. Abstract Differentiating aggressive clear cell renal cell carcinoma (ccRCC) from indolent lesions is challenging using conventional imaging. This work prospectively compared the metabolic imaging phenotype of renal tumors using carbon-13 MRI following injection of hyperpolarized [1-13C]pyruvate (HP-13C-MRI) and validated these findings with histopathology. Nine patients with treatment-naïve renal tumors (6 ccRCCs, 1 liposarcoma, 1 pheochromocytoma, 1 oncocytoma) underwent pre-operative HP-13C-MRI and conventional proton (1H) MRI. Multi-regional tissue samples were collected using patient-specific 3D-printed tumor molds for spatial registration between imaging and molecular analysis. The apparent exchange rate constant (kPL) between 13C-pyruvate and 13C-lactate was calculated. Immunohistochemistry for the pyruvate transporter (MCT1) from 44 multi-regional samples, as well as associations between MCT1 expression and outcome in the TCGA-KIRC dataset, were investigated. Increasing kPL in ccRCC was correlated with increasing overall tumor grade (ρ = 0.92, p = 0.009) and MCT1 expression (r = 0.89, p = 0.016), with similar results acquired from the multi-regional analysis. Conventional 1H-MRI parameters did not discriminate tumor grades. The correlation between MCT1 and ccRCC grade was confirmed within a TCGA dataset (p < 0.001), where MCT1 expression was a predictor of overall and disease-free survival. In conclusion, metabolic imaging using HP-13C-MRI differentiates tumor aggressiveness in ccRCC and correlates with the expression of MCT1, a predictor of survival. HP-13C-MRI may non-invasively characterize metabolic phenotypes within renal cancer.

BACKGROUND: Application of the MSKCC and IMDC models is recommended for prognostication in metastatic renal cell cancer (mRCC). Patient classification in MSKCC and IMDC risk groups in real-world observational studies is often hampered by missing data on required pre-treatment characteristics. OBJECTIVE: To evaluate the effect of application of easy-to-use logical, or deductive, imputation on MSKCC and IMDC risk classification in an observational study setting. PATIENTS AND METHODS: We used data on 713 mRCC patients with first-line sunitinib treatment from our observational European multi-centre study EuroTARGET. Pre-treatment characteristics and follow-up were derived from medical files. Hospital-specific cut-off values for laboratory measurements were requested. The effect of logical imputation of missing data and consensus versus hospital-specific cut-off values on patient classification and the subsequent models’ predictive performance for progression-free and overall survival (OS) was evaluated. RESULTS: 45% of the patients had missing data for≥1 pre-treatment characteristic for either model. Still, 72% of all patients could be unambiguously classified using logical imputation. Use of consensus instead of hospital-specific cut-offs led to a shift in risk group for 12% and 7% of patients for the MSKCC and IMDC model, respectively. Using logical imputation or other cut-offs did not influence the models’ predictive performance. These were in line with previous reports (c-statistic ∼0.64 for OS) CONCLUSIONS: Logical imputation leads to a substantial increase in the proportion of patients that can be correctly classified into poor and intermediate MSKCC and IMDC risk groups in observational studies and its use in the field should be advocated.

Additional file 3.

Additional file 2.

Additional file 1: Supplementary Table 1. Time-to-events by LOT. Supplementary Table 2. Adverse events by LOT. Supplementary Figure 1. Treatment pathways for patients receiving systemic therapies. Supplementary Figure 2. Overall survival from 2LOT stratified by key baseline characteristics. Supplementary Figure 3. Overall survival by LOT in patients receiving interleukin-2/interferon-alpha at any LOT

This study introduces the use of 'error-category mapping' in the interpretation of pharmacokinetic (PK) model parameter results derived from dynamic contrast-enhanced (DCE-) MRI data. Eleven patients with metastatic renal cell carcinoma were enrolled in a multiparametric study of the treatment effects of bevacizumab. For the purposes of the present analysis, DCE-MRI data from two identical pre-treatment examinations were analysed by application of the extended Tofts model (eTM), using in turn a model arterial input function (AIF), an individually-measured AIF and a sample-average AIF. PK model parameter maps were calculated. Errors in the signal-to-gadolinium concentration ([Gd]) conversion process and the model-fitting process itself were assigned to category codes on a voxel-by-voxel basis, thereby forming a colour-coded 'error-category map' for each imaged slice. These maps were found to be repeatable between patient visits and showed that the eTM converged adequately in the majority of voxels in all the tumours studied. However, the maps also clearly indicated sub-regions of low Gd uptake and of non-convergence of the model in nearly all tumours. The non-physical condition ve ≥ 1 was the most frequently indicated error category and appeared sensitive to the form of AIF used. This simple method for visualisation of errors in DCE-MRI could be used as a routine quality-control technique and also has the potential to reveal otherwise hidden patterns of failure in PK model applications.

Additional file 6: Figure S6. cumulative incidence of disease recurrence of patients with PRCC recruited into ASSURE according to UISS, Leibovich Score 2018 and VENUSS group.

Additional file 3: Figure S3. Estimated restricted cubic spline function for tumour size versus the log hazard for tumour recurrence.

Additional file 1: Table S1. Clinicopathological variables of the PRCC patients enrolled in ASSURE.

Additional file 2: Table S2. Competing risks models for VENUSS score, VENUSS, group TNM group and Leibovich group.

Additional file 5: Figure S5. Calibration and decision curve analysis of the VENUSS score, VENUSS group, UISS, TNM and Leibovich group in the ASSURE dataset.

Additional file 4: Figure S4. Non-smoothed decision curves of VENUSS and other risk definitions predicting PRCC recurrence.

Tumour heterogeneity leads to the development of multiple resistance mechanisms during targeted therapies. Identifying the dominant driver(s) is critical for treatment decision. We studied the relative dynamics of multiple oncogenic drivers in longitudinal plasma of 50 EGFR‐mutant non‐small‐cell lung cancer patients receiving gefitinib and hydroxychloroquine. We performed digital PCR and targeted sequencing on samples from all patients and shallow whole‐genome sequencing on samples from three patients who underwent histological transformation to small‐cell lung cancer. In 43 patients with known EGFR mutations from tumour, we identified them accurately in plasma of 41 patients (95%, 41/43). We also found additional mutations, including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%) and PTEN (4/50, 8%). Patients with both TP53 and EGFR mutations before treatment had worse overall survival than those with only EGFR. Patients who progressed without T790M had worse PFS during TKI continuation and developed alternative alterations, including small‐cell lung cancer‐associated copy number changes and TP53 mutations, that tracked subsequent treatment responses. Longitudinal plasma analysis can help identify dominant resistance mechanisms, including non‐druggable genetic information that may guide clinical management., EMBO Molecular Medicine, 10 (6), ISSN:1757-4676, ISSN:1757-4684

PURPOSE: To test the hypothesis that cytoreductive nephrectomy (CN) improves overall survival (OS) of patients with synchronous metastatic renal cell carcinoma (mRCC), who subsequently receive targeted therapies (TT). METHODS: We identified 261 patients who received TT for synchronous mRCC with or without prior CN. To achieve balance in baseline characteristics between groups, we used the inverse probability of treatment weighting (IPTW) method. We conducted OS analyses, including IPTW-adjusted Kaplan-Meier curves, Cox regression models, interaction term, and landmark and sensitivity analyses. RESULTS: Of the 261 patients, 97 (37.2%) received CN and 164 (62.8%) did not. IPTW-adjusted analyses showed a statistically significant OS benefit for patients treated with CN (HR 0.63, 95% CI 0.46-0.83, P = 0.0015). While there was no statistically significant difference in OS at 3 months (P = 0.97), 6 months (P = 0.67), and 12 months (P = 0.11) from diagnosis, a benefit for the CN group was noted at 18 months (P = 0.005) and 24 months (P = 0.004). On interaction term analyses, the beneficial effect of CN increased with better performance status (P = 0.06), in women (P = 0.03), and in patients with thrombocytosis (P = 0.01). CONCLUSIONS: IPTW-adjusted analysis of our patient cohort suggests that CN improves OS of patients with synchronous mRCC treated with TT. On the whole, the survival difference appears after 12 months. Specific subgroups may particularly benefit from CN, and these subgroups warrant further investigation in prospective trials.

Background: Cell-free tumor-derived DNA (ctDNA) allows non-invasive monitoring of cancers, but its utility in renal cell cancer (RCC) has not been established. Methods: Here, a combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n = 91) with various renal tumor subtypes, were used to determine ctDNA content in plasma and urine. Results: Our data revealed lower plasma ctDNA levels in RCC relative to other cancers of similar size and stage, with untargeted detection in 27.5% of patients from both cohorts. A sensitive personalized approach, applied to plasma and urine from select patients (n = 22) improved detection to ~ 50%, including in patients with early-stage disease and even benign lesions. Detection in plasma, but not urine, was more frequent amongst patients with larger tumors and in those patients with venous tumor thrombus. With data from one extensively characterized patient, we observed that plasma and, for the first time, urine ctDNA may better represent tumor heterogeneity than a single tissue biopsy. Furthermore, in a subset of patients (n = 16), longitudinal sampling revealed that ctDNA can track disease course and may pre-empt radiological identification of minimal residual disease or disease progression on systemic therapy. Additional datasets will be required to validate these findings. Conclusions: These data highlight RCC as a ctDNA-low malignancy. The biological reasons for this are yet to be determined. Nonetheless, our findings indicate potential clinical utility in the management of patients with renal tumors, provided improvement in isolation and detection approaches.

BACKGROUND: Cell-free tumor-derived DNA (ctDNA) allows non-invasive monitoring of cancers, but its utility in renal cell cancer (RCC) has not been established. METHODS: Here, a combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n = 91) with various renal tumor subtypes, were used to determine ctDNA content in plasma and urine. RESULTS: Our data revealed lower plasma ctDNA levels in RCC relative to other cancers of similar size and stage, with untargeted detection in 27.5% of patients from both cohorts. A sensitive personalized approach, applied to plasma and urine from select patients (n = 22) improved detection to ~ 50%, including in patients with early-stage disease and even benign lesions. Detection in plasma, but not urine, was more frequent amongst patients with larger tumors and in those patients with venous tumor thrombus. With data from one extensively characterized patient, we observed that plasma and, for the first time, urine ctDNA may better represent tumor heterogeneity than a single tissue biopsy. Furthermore, in a subset of patients (n = 16), longitudinal sampling revealed that ctDNA can track disease course and may pre-empt radiological identification of minimal residual disease or disease progression on systemic therapy. Additional datasets will be required to validate these findings. CONCLUSIONS: These data highlight RCC as a ctDNA-low malignancy. The biological reasons for this are yet to be determined. Nonetheless, our findings indicate potential clinical utility in the management of patients with renal tumors, provided improvement in isolation and detection approaches.

Background: Cell-free tumor-derived DNA (ctDNA) allows non-invasive monitoring of cancers, but its utility in renal cell cancer (RCC) has not been established. Methods: Here, a combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n = 91) with various renal tumor subtypes, were used to determine ctDNA content in plasma and urine. Results: Our data revealed lower plasma ctDNA levels in RCC relative to other cancers of similar size and stage, with untargeted detection in 27.5% of patients from both cohorts. A sensitive personalized approach, applied to plasma and urine from select patients (n = 22) improved detection to ~ 50%, including in patients with early-stage disease and even benign lesions. Detection in plasma, but not urine, was more frequent amongst patients with larger tumors and in those patients with venous tumor thrombus. With data from one extensively characterized patient, we observed that plasma and, for the first time, urine ctDNA may better represent tumor heterogeneity than a single tissue biopsy. Furthermore, in a subset of patients (n = 16), longitudinal sampling revealed that ctDNA can track disease course and may pre-empt radiological identification of minimal residual disease or disease progression on systemic therapy. Additional datasets will be required to validate these findings. Conclusions: These data highlight RCC as a ctDNA-low malignancy. The biological reasons for this are yet to be determined. Nonetheless, our findings indicate potential clinical utility in the management of patients with renal tumors, provided improvement in isolation and detection approaches.

Table S1. Summary of patient characteristics of the DIAMOND cohort. Table S2. Summary of patient characteristics of the MonReC cohort. Table S3. Summary of filters applied to somatic single nucleotide variants (SNV) calls from Mutect2, for mutation calling of DIAMOND tissue samples. Table S4. Genes targeted for open reading frame sequencing. Table S5. Summary of samples with detected ctDNA at baseline of the MonReC cohort. Table S6. Mutations identified in tissue of in VHL, PTEN, TP53, SETD2, PBRM1, and BAP1 of patients subsequently analyzed with INVAR-TAPAS (n = 29). Table S7. Mutations identified at baseline in the MonReC cohort using a QIASeq custom panel targeting 10 frequently mutated genes in RCC. Fig. S1. Clinical records of select DIAMOND patients. Fig. S2. Schematic explaining the INVAR-TAPAS approach. Fig. S3. Summary of SCNA observed in matched tumor tissue from select DIAMOND patients. Fig. S4. tMAD - interrogation of plasma and urine data. Fig. S5. Assessment of SCNA landscape of matched tumor tissue supports their classification as oncocytoma. Fig. S6. Improved detection of SCNA by in silico size selection. Fig. S7. Comparison of the distribution of ichorCNA tumor fraction and tMAD score at baseline, and assessment of ichorCNA scores between cancer types from the MonReC cohort. Fig. S8. Summary of tumor tissue WES of the DIAMOND patients. Fig. S9. Tumor heterogeneity in RCC. Fig. 10. Summary of global ctDNA levels relative to informative reads in INVAR-TAPAS data from patient plasma and urine. Fig. S11. Correlation of tumor size and ctDNA detection. Fig. S12. Correlation of venous tumor thrombus and cell proliferation rates with ctDNA detection. Fig. S13. Confirmation of pathological classification as oncocytoma. Fig. S14. Application of a fragmentation feature based random forest model to predict patients with detected ctDNA. Fig. S15. Summary of ctDNA detection in all patients and all biofluids. Fig. S16. Comparison of z-score distribution at baseline, during treatment and when progression occurred. Fig. S17. Longitudinal monitoring of mutations detected with the QIAseq custom panel and ichorCNA tumor fractions. Fig. S18. Comparison of imaging data and ctDNA levels (as predicted by INVAR.TAPAS and tMAD). Fig. S19. Comparison of SCNA landscape of matched tumor tissue, normal adjacent tissue, and longitudinal plasma samples from DIAMOND patient 5634. Fig. S20. Comparison of imaging data and ctDNA levels (as predicted by INVAR.TAPAS and tMAD). Fig. S21. Tumor map of patient 5842. Fig. S22. Comparison between mAF and mutation representation in tumor lesions. Fig. S23. Representation of private mutations in the baseline plasma and USN samples of patient 5842. Fig. S24. Representation of mutations private to tumor regions in plasma and urine. Fig. S25. Distribution of mAF of patient specific mutations in plasma and urine from patient 5842. Fig. S26. Assessment of tumor heterogeneity representation in plasma from patient 5634.

BACKGROUND:Cell-free tumor-derived DNA (ctDNA) allows non-invasive monitoring of cancers, but its utility in renal cell cancer (RCC) has not been established. METHODS:Here, a combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n = 91) with various renal tumor subtypes, were used to determine ctDNA content in plasma and urine. RESULTS:Our data revealed lower plasma ctDNA levels in RCC relative to other cancers of similar size and stage, with untargeted detection in 27.5% of patients from both cohorts. A sensitive personalized approach, applied to plasma and urine from select patients (n = 22) improved detection to ~ 50%, including in patients with early-stage disease and even benign lesions. Detection in plasma, but not urine, was more frequent amongst patients with larger tumors and in those patients with venous tumor thrombus. With data from one extensively characterized patient, we observed that plasma and, for the first time, urine ctDNA may better represent tumor heterogeneity than a single tissue biopsy. Furthermore, in a subset of patients (n = 16), longitudinal sampling revealed that ctDNA can track disease course and may pre-empt radiological identification of minimal residual disease or disease progression on systemic therapy. Additional datasets will be required to validate these findings. CONCLUSIONS:These data highlight RCC as a ctDNA-low malignancy. The biological reasons for this are yet to be determined. Nonetheless, our findings indicate potential clinical utility in the management of patients with renal tumors, provided improvement in isolation and detection approaches.

Table S1. Summary of patient characteristics of the DIAMOND cohort. Table S2. Summary of patient characteristics of the MonReC cohort. Table S3. Summary of filters applied to somatic single nucleotide variants (SNV) calls from Mutect2, for mutation calling of DIAMOND tissue samples. Table S4. Genes targeted for open reading frame sequencing. Table S5. Summary of samples with detected ctDNA at baseline of the MonReC cohort. Table S6. Mutations identified in tissue of in VHL, PTEN, TP53, SETD2, PBRM1, and BAP1 of patients subsequently analyzed with INVAR-TAPAS (n = 29). Table S7. Mutations identified at baseline in the MonReC cohort using a QIASeq custom panel targeting 10 frequently mutated genes in RCC. Fig. S1. Clinical records of select DIAMOND patients. Fig. S2. Schematic explaining the INVAR-TAPAS approach. Fig. S3. Summary of SCNA observed in matched tumor tissue from select DIAMOND patients. Fig. S4. tMAD - interrogation of plasma and urine data. Fig. S5. Assessment of SCNA landscape of matched tumor tissue supports their classification as oncocytoma. Fig. S6. Improved detection of SCNA by in silico size selection. Fig. S7. Comparison of the distribution of ichorCNA tumor fraction and tMAD score at baseline, and assessment of ichorCNA scores between cancer types from the MonReC cohort. Fig. S8. Summary of tumor tissue WES of the DIAMOND patients. Fig. S9. Tumor heterogeneity in RCC. Fig. 10. Summary of global ctDNA levels relative to informative reads in INVAR-TAPAS data from patient plasma and urine. Fig. S11. Correlation of tumor size and ctDNA detection. Fig. S12. Correlation of venous tumor thrombus and cell proliferation rates with ctDNA detection. Fig. S13. Confirmation of pathological classification as oncocytoma. Fig. S14. Application of a fragmentation feature based random forest model to predict patients with detected ctDNA. Fig. S15. Summary of ctDNA detection in all patients and all biofluids. Fig. S16. Comparison of z-score distribution at baseline, during treatment and when progression occurred. Fig. S17. Longitudinal monitoring of mutations detected with the QIAseq custom panel and ichorCNA tumor fractions. Fig. S18. Comparison of imaging data and ctDNA levels (as predicted by INVAR.TAPAS and tMAD). Fig. S19. Comparison of SCNA landscape of matched tumor tissue, normal adjacent tissue, and longitudinal plasma samples from DIAMOND patient 5634. Fig. S20. Comparison of imaging data and ctDNA levels (as predicted by INVAR.TAPAS and tMAD). Fig. S21. Tumor map of patient 5842. Fig. S22. Comparison between mAF and mutation representation in tumor lesions. Fig. S23. Representation of private mutations in the baseline plasma and USN samples of patient 5842. Fig. S24. Representation of mutations private to tumor regions in plasma and urine. Fig. S25. Distribution of mAF of patient specific mutations in plasma and urine from patient 5842. Fig. S26. Assessment of tumor heterogeneity representation in plasma from patient 5634.

PURPOSE The 2003 Leibovich score guides prognostication and selection to adjuvant clinical trials for patients with locally advanced renal cell carcinoma (RCC) after nephrectomy. We provide a robust external validation of the 2003 Leibovich score using contemporary data from SORCE, an international, randomized trial of sorafenib after excision of primary RCC. METHODS Data used to derive the 2003 Leibovich score were compared with contemporary data from SORCE. Discrimination and calibration of the metastasis-free survival outcome were assessed in data from patients with clear-cell RCC, using Cox proportional hazards regression, Kaplan-Meier curves, and calculation of Harrell's c indexes. Secondary analyses involved three important SORCE groups: patients with any non–clear-cell subtype, papillary, and chromophobe carcinomas. RESULTS Four hundred seven recurrences occurred in 982 patients in the Leibovich cohort and 520 recurrences were recorded in 1,445 patients in the primary SORCE cohort. Clear discrimination between intermediate-risk and high-risk SORCE cohorts was shown; hazard ratio 2.74 (95% CI, 2.29 to 3.28), c-index 0.63 (95% CI, 0.61 to 0.65). A hazard ratio of 0.61 (95% CI, 0.53 to 0.70) confirmed poor calibration of the two cohorts. Discrimination was observed in secondary populations, with c-indexes of 0.64 (95% CI, 0.59 to 0.69) for non–clear-cell RCC, 0.63 (95% CI, 0.56 to 0.69) for papillary RCC, and 0.65 (95% CI, 0.55 to 0.76) for chromophobe RCC. CONCLUSION The 2003 Leibovich score discriminates between intermediate-risk and high-risk clear-cell and non–clear-cell RCC groups in contemporary data, supporting its use for risk stratification in adjuvant clinical trials. Over time, metastasis-free survival for patients with locally advanced RCC has improved. Contemporary data from adjuvant RCC trials should be used to improve prognostication for patients with RCC.

Funder: NIHR Cambridge Biomedical Research Centre, Funder: Addenbrooke’s Charitable Trust, Funder: National Institute for Health Research (NIHR), Funder: Mark Foundation For Cancer Research, Funder: Cambridge Commonwealth, European and International Trust, Funder: Cancer Research UK, Funder: Cambridge Clinical Trials Unit, Funder: Cancer Research UK Cambridge Centre, Funder: Engineering and Physical Sciences Research Council Cancer Imaging Centre in Cambridge and Manchester, Funder: Cambridge Experimental Cancer Medicine Centre, PURPOSE: To detect early response to sunitinib treatment in metastatic clear cell renal cancer (mRCC) using multiparametric MRI. METHOD: Participants with mRCC undergoing pre-surgical sunitinib therapy in the prospective NeoSun clinical trial (EudraCtNo: 2005-004502-82) were imaged before starting treatment, and after 12 days of sunitinib therapy using morphological MRI sequences, advanced diffusion-weighted imaging, measurements of R2* (related to hypoxia) and dynamic contrast-enhanced imaging. Following nephrectomy, participants continued treatment and were followed-up with contrast-enhanced CT. Changes in imaging parameters before and after sunitinib were assessed with the non-parametric Wilcoxon signed-rank test and the log-rank test was used to assess effects on survival. RESULTS: 12 participants fulfilled the inclusion criteria. After 12 days, the solid and necrotic tumor volumes decreased by 28% and 17%, respectively (p = 0.04). However, tumor-volume reduction did not correlate with progression-free or overall survival (PFS/OS). Sunitinib therapy resulted in a reduction in median solid tumor diffusivity D from 1298x10-6 to 1200x10-6mm2/s (p = 0.03); a larger decrease was associated with a better RECIST response (p = 0.02) and longer PFS (p = 0.03) on the log-rank test. An increase in R2* from 19 to 28s-1 (p = 0.001) was observed, paralleled by a decrease in Ktrans from 0.415 to 0.305min-1 (p = 0.01) and a decrease in perfusion fraction from 0.34 to 0.19 (p

Funder: AstraZeneca (GB), Background: Window-of-opportunity trials, evaluating the engagement of drugs with their biological target in the time period between diagnosis and standard-of-care treatment, can help prioritise promising new systemic treatments for later-phase clinical trials. Renal cell carcinoma (RCC), the 7th commonest solid cancer in the UK, exhibits targets for multiple new systemic anti-cancer agents including DNA damage response inhibitors, agents targeting vascular pathways and immune checkpoint inhibitors. Here we present the trial protocol for the WIndow-of-opportunity clinical trial platform for evaluation of novel treatment strategies in REnal cell cancer (WIRE). Methods: WIRE is a Phase II, multi-arm, multi-centre, non-randomised, proof-of-mechanism (single and combination investigational medicinal product [IMP]), platform trial using a Bayesian adaptive design. The Bayesian adaptive design leverages outcome information from initial participants during pre-specified interim analyses to determine and minimise the number of participants required to demonstrate efficacy or futility. Patients with biopsy-proven, surgically resectable, cT1b+, cN0���1, cM0���1 clear cell RCC and no contraindications to the IMPs are eligible to participate. Participants undergo diagnostic staging CT and renal mass biopsy followed by treatment in one of the treatment arms for at least 14 days. Initially, the trial includes five treatment arms with cediranib, cediranib + olaparib, olaparib, durvalumab and durvalumab + olaparib. Participants undergo a multiparametric MRI before and after treatment. Vascularised and de-vascularised tissue is collected at surgery. A ��� 30% increase in CD8+ T-cells on immunohistochemistry between the screening and nephrectomy is the primary endpoint for durvalumab-containing arms. Meanwhile, a reduction in tumour vascular permeability measured by Ktrans on dynamic contrast-enhanced MRI by ���30% is the primary endpoint for other arms. Secondary outcomes include adverse events and tumour size change. Exploratory outcomes include biomarkers of drug mechanism and treatment effects in blood, urine, tissue and imaging. Discussion: WIRE is the first trial using a window-of-opportunity design to demonstrate pharmacological activity of novel single and combination treatments in RCC in the pre-surgical space. It will provide rationale for prioritising promising treatments for later phase trials and support the development of new biomarkers of treatment effect with its extensive translational agenda. Trial registration: ClinicalTrials.gov: NCT03741426 / EudraCT: 2018���003056-21.

Renal cell carcinoma (RCC) makes up 2-3% of adult cancers. The introduction of tyrosine kinase inhibitors (TKIs) and mammalian target of rapamycin inhibitors in the mid-2000s radically changed the management of RCC. These targeted treatments superseded immunotherapy with interleukin-2 and interferon. The pendulum now appears to be shifting back towards immunotherapy, with the evidence of prolonged overall survival of patients with metastatic RCC on treatment with the anti-programmed cell death 1 ligand monoclonal antibody, nivolumab. Clinical prognostic criteria aid prediction of relapse risk for resected localised disease. Unfortunately, for patients at high risk of relapse, no adjuvant treatment has yet shown benefit, although further trials are yet to report. Clinical prognostic models also have a role in the management of advanced disease; now there is a pressing need for predictive biomarkers to direct therapy. Treatment selection for metastatic disease is currently based on histology, prognostic group and patient preference based on side effect profile. In this article, we review the current medical and surgical management of localised, oligometastatic and advanced RCC, including side effect management and the evidence base for management of poor-risk and non-clear cell disease. We discuss recent results from clinical trials and how these are likely to shape future practice and a renaissance of immunotherapy for renal cell cancer.

BACKGROUND: Relative telomere length in peripheral blood leukocytes has been evaluated as a potential biomarker for renal cell carcinoma (RCC) risk in several studies, with conflicting findings. OBJECTIVE: We performed an analysis of genetic variants associated with leukocyte telomere length to assess the relationship between telomere length and RCC risk using Mendelian randomization, an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. DESIGN, SETTING, AND PARTICIPANTS: Genotypes from nine telomere length-associated variants for 10 784 cases and 20 406 cancer-free controls from six genome-wide association studies (GWAS) of RCC were aggregated into a weighted genetic risk score (GRS) predictive of leukocyte telomere length. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) relating the GRS and RCC risk were computed in individual GWAS datasets and combined by meta-analysis. RESULTS AND LIMITATIONS: Longer genetically inferred telomere length was associated with an increased risk of RCC (OR=2.07 per predicted kilobase increase, 95% confidence interval [CI]:=1.70-2.53, p0.5) with GWAS-identified RCC risk variants (rs10936599 and rs9420907) from the telomere length GRS; despite this exclusion, a statistically significant association between the GRS and RCC risk persisted (OR=1.73, 95% CI=1.36-2.21, p

BACKGROUND: Lung cancer screening using low-dose CT (LDCT) was shown to reduce lung cancer mortality by 20% in the National Lung Screening Trial.METHODS: The pilot UK Lung Cancer Screening (UKLS) is a randomised controlled trial of LDCT screening for lung cancer versus usual care. A population-based questionnaire was used to identify high-risk individuals. CT screen-detected nodules were managed by a pre-specified protocol. Cost effectiveness was modelled with reference to the National Lung Cancer Screening Trial mortality reduction.RESULTS: 247 354 individuals aged 50-75 years were approached; 30.7% expressed an interest, 8729 (11.5%) were eligible and 4055 were randomised, 2028 into the CT arm (1994 underwent a CT). Forty-two participants (2.1%) had confirmed lung cancer, 34 (1.7%) at baseline and 8 (0.4%) at the 12-month scan. 28/42 (66.7%) had stage I disease, 36/42 (85.7%) had stage I or II disease. 35/42 (83.3%) had surgical resection. 536 subjects had nodules greater than 50 mm(3) or 5 mm diameter and 41/536 were found to have lung cancer. One further cancer was detected by follow-up of nodules between 15 and 50 mm(3) at 12 months. The baseline estimate for the incremental cost-effectiveness ratio of once-only CT screening, under the UKLS protocol, was £8466 per quality adjusted life year gained (CI £5542 to £12 569).CONCLUSIONS: The UKLS pilot trial demonstrated that it is possible to detect lung cancer at an early stage and deliver potentially curative treatment in over 80% of cases. Health economic analysis suggests that the intervention would be cost effective-this needs to be confirmed using data on observed lung cancer mortality reduction.TRIAL REGISTRATION: ISRCTN 78513845.