Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions.

Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.72, 95% confidence interval 2.23-3.30). In cis-expression quantitative trait locus analyses, 48 variants from 34 regions point toward 83 candidate genes. Enrichment of hypoxia-inducible factor-binding sites underscores the importance of hypoxia-related mechanisms in kidney cancer. Our results advance understanding of the genetic architecture of kidney cancer, provide clues for functional investigation and enable generation of a validated polygenic risk score with an estimated area under the curve of 0.65 (0.74 including risk factors) among European ancestry individuals.

Predicting the recurrence risk of renal cell carcinoma after nephrectomy: potential role of CT-radiomics for adjuvant treatment decisions.

OBJECTIVES: Previous trial results suggest that only a small number of patients with non-metastatic renal cell carcinoma (RCC) benefit from adjuvant therapy. We assessed whether the addition of CT-based radiomics to established clinico-pathological biomarkers improves recurrence risk prediction for adjuvant treatment decisions. METHODS: This retrospective study included 453 patients with non-metastatic RCC undergoing nephrectomy. Cox models were trained to predict disease-free survival (DFS) using post-operative biomarkers (age, stage, tumor size and grade) with and without radiomics selected on pre-operative CT. Models were assessed using C-statistic, calibration, and decision curve analyses (repeated tenfold cross-validation). RESULTS: At multivariable analysis, one of four selected radiomic features (wavelet-HHL_glcm_ClusterShade) was prognostic for DFS with an adjusted hazard ratio (HR) of 0.44 (p = 0.02), along with American Joint Committee on Cancer (AJCC) stage group (III versus I, HR 2.90; p = 0.002), grade 4 (versus grade 1, HR 8.90; p = 0.001), age (per 10 years HR 1.29; p = 0.03), and tumor size (per cm HR 1.13; p = 0.003). The discriminatory ability of the combined clinical-radiomic model (C = 0.80) was superior to that of the clinical model (C = 0.78; p < 0.001). Decision curve analysis revealed a net benefit of the combined model when used for adjuvant treatment decisions. At an exemplary threshold probability of ≥ 25% for disease recurrence within 5 years, using the combined versus the clinical model was equivalent to treating 9 additional patients (per 1000 assessed) who would recur without treatment (i.e., true-positive predictions) with no increase in false-positive predictions. CONCLUSION: Adding CT-based radiomic features to established prognostic biomarkers improved post-operative recurrence risk assessment in our internal validation study and may help guide decisions regarding adjuvant therapy. KEY POINTS: In patients with non-metastatic renal cell carcinoma undergoing nephrectomy, CT-based radiomics combined with established clinical and pathological biomarkers improved recurrence risk assessment. Compared to a clinical base model, the combined risk model enabled superior clinical utility if used to guide decisions on adjuvant treatment.

Cystic Renal Masses: Old and New Paradigms.

Cystic renal masses describe a spectrum of lesions with benign and/or malignant features. Cystic renal masses are most often identified incidentally with the Bosniak classification system stratifying their malignant potential. Solid enhancing components most often represent clear cell renal cell carcinoma yet display an indolent natural history relative to pure solid renal masses. This has led to an increased adoption of active surveillance as a management strategy in those who are poor surgical candidates. This article provides a contemporary overview of historical and emerging clinical paradigms in the diagnosis and management of this distinct clinical entity.

Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity.

Knowledge of the transcriptional programs underpinning the functions of human kidney cell populations at homeostasis is limited. We present a single-cell perspective of healthy human kidney from 19 living donors, with equal contribution from males and females, profiling the transcriptome of 27677 cells to map human kidney at high resolution. Sex-based differences in gene expression within proximal tubular cells were observed, specifically, increased anti-oxidant metallothionein genes in females and aerobic metabolism-related genes in males. Functional differences in metabolism were confirmed in proximal tubular cells, with male cells exhibiting higher oxidative phosphorylation and higher levels of energy precursor metabolites. We identified kidney-specific lymphocyte populations with unique transcriptional profiles indicative of kidney-adapted functions. Significant heterogeneity in myeloid cells was observed, with a MRC1+LYVE1+FOLR2+C1QC+ population representing a predominant population in healthy kidney. This study provides a detailed cellular map of healthy human kidney, and explores the complexity of parenchymal and kidney-resident immune cells.

Dual Antigen T Cell Engagers Targeting CA9 as an Effective Immunotherapeutic Modality for Targeting CA9 in Solid Tumors.

Glioblastomas (GBM), the most common malignant primary adult brain tumors, are uniformly lethal and are in need of improved therapeutic modalities. GBM contain extensive regions of hypoxia and are enriched in therapy resistant brain tumor-initiating cells (BTICs). Carbonic anhydrase 9 (CA9) is a hypoxia-induced cell surface enzyme that plays an important role in maintenance of stem cell survival and therapeutic resistance. Here we demonstrate that CA9 is highly expressed in patient-derived BTICs. CA9+ GBM BTICs showed increased self-renewal and proliferative capacity. To target CA9, we developed dual antigen T cell engagers (DATEs) that were exquisitely specific for CA9-positive patient-derived clear cell Renal Cell Carcinoma (ccRCC) and GBM cells. Combined treatment of either ccRCC or GBM cells with the CA9 DATE and T cells resulted in T cell activation, increased release of pro-inflammatory cytokines and enhanced cytotoxicity in a CA9-dependent manner. Treatment of ccRCC and GBM patient-derived xenografts markedly reduced tumor burden and extended survival. These data suggest that the CA9 DATE could provide a novel therapeutic strategy for patients with solid tumors expressing CA9 to overcome treatment resistance. .

High-content CRISPR screening.

CRISPR screens are a powerful source of biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications and species. In pooled CRISPR screens, various genetically encoded perturbations are introduced into pools of cells. The targeted cells proliferate under a biological challenge such as cell competition, drug treatment or viral infection. Subsequently, the perturbation-induced effects are evaluated by sequencing-based counting of the guide RNAs that specify each perturbation. The typical results of such screens are ranked lists of genes that confer sensitivity or resistance to the biological challenge of interest. Contributing to the broad utility of CRISPR screens, adaptations of the core CRISPR technology make it possible to activate, silence or otherwise manipulate the target genes. Moreover, high-content read-outs such as single-cell RNA sequencing and spatial imaging help characterize screened cells with unprecedented detail. Dedicated software tools facilitate bioinformatic analysis and enhance reproducibility. CRISPR screening has unravelled various molecular mechanisms in basic biology, medical genetics, cancer research, immunology, infectious diseases, microbiology and other fields. This Primer describes the basic and advanced concepts of CRISPR screening and its application as a flexible and reliable method for biological discovery, biomedical research and drug development - with a special emphasis on high-content methods that make it possible to obtain detailed biological insights directly as part of the screen.

Establishing a global quality of care benchmark report.

BACKGROUND: The Movember funded TrueNTH Global Registry (TNGR) aims to improve care by collecting and analysing a consistent dataset to identify variation in disease management, benchmark care delivery in accordance with best practice guidelines and provide this information to those in a position to enact change. We discuss considerations of designing and implementing a quality of care report for TNGR. METHODS: Eleven working group sessions were held prior to and as reports were being built with representation from clinicians, data managers and investigators contributing to TNGR. The aim of the meetings was to understand current data display approaches, share literature review findings and ideas for innovative approaches. Preferred displays were evaluated with two surveys (survey 1: 5 clinicians and 5 non-clinicians, 83% response rate; survey 2: 17 clinicians and 18 non-clinicians, 93% response rate). RESULTS: Consensus on dashboard design and three data-display preferences were achieved. The dashboard comprised two performance summary charts; one summarising site's relative quality indicator (QI) performance and another to summarise data quality. Binary outcome QIs were presented as funnel plots. Patient-reported outcome measures of function score and the extent to which men were bothered by their symptoms were presented in bubble plots. Time series graphs were seen as providing important information to supplement funnel and bubble plots. R Markdown was selected as the software program principally because of its excellent analytic and graph display capacity, open source licensing model and the large global community sharing program code enhancements. CONCLUSIONS: International collaboration in creating and maintaining clinical quality registries has allowed benchmarking of process and outcome measures on a large scale. A registry report system was developed with stakeholder engagement to produce dynamic reports that provide user-specific feedback to 132 participating sites across 13 countries.

Hospital-level Effects Contribute to Variations in Prostate Cancer Quality of Care.

A paucity of real-world data exists highlighting whether variations in prostate cancer quality of care occur at a hospital level, independent of differences in case mix. To overcome this knowledge gap, we benchmarked hospital-level quality (n = 1245 hospitals) across a broad multidisciplinary panel of previously reported disease-specific, expert-defined quality indicators (QIs), adjusting for differences in patient case mix by indirect standardization. A composite measure of prostate cancer quality-the prostate cancer quality score (PC-QS)-was derived, and associations between PC-QS and hospital volume, academic status, and location as well as patient all-cause mortality were determined. After adjusting for the case mix, of the total of 1245 hospitals evaluated, 2-37% were identified as those performing significantly below the national average for a given QI. Hospitals with a higher PC-QS displayed larger patient volumes, were more commonly academic affiliated, and had lower overall mortality. Collectively, our data-driven benchmarking analysis reveals that widespread hospital-level variations exist in prostate cancer quality of care after adjusting for differences in case mix, with the PC-QS serving as a novel, validated, quality benchmarking tool. PATIENT SUMMARY: Our statistical benchmarking method shows that the quality of prostate cancer care varies between hospitals, after accounting for differences in patient characteristics. The prostate cancer quality score is a novel, validated, quality benchmarking tool.

Functional genomic landscape of cancer-intrinsic evasion of killing by T cells.

The genetic circuits that allow cancer cells to evade destruction by the host immune system remain poorly understood1-3. Here, to identify a phenotypically robust core set of genes and pathways that enable cancer cells to evade killing mediated by cytotoxic T lymphocytes (CTLs), we performed genome-wide CRISPR screens across a panel of genetically diverse mouse cancer cell lines that were cultured in the presence of CTLs. We identify a core set of 182 genes across these mouse cancer models, the individual perturbation of which increases either the sensitivity or the resistance of cancer cells to CTL-mediated toxicity. Systematic exploration of our dataset using genetic co-similarity reveals the hierarchical and coordinated manner in which genes and pathways act in cancer cells to orchestrate their evasion of CTLs, and shows that discrete functional modules that control the interferon response and tumour necrosis factor (TNF)-induced cytotoxicity are dominant sub-phenotypes. Our data establish a central role for genes that were previously identified as negative regulators of the type-II interferon response (for example, Ptpn2, Socs1 and Adar1) in mediating CTL evasion, and show that the lipid-droplet-related gene Fitm2 is required for maintaining cell fitness after exposure to interferon-γ (IFNγ). In addition, we identify the autophagy pathway as a conserved mediator of the evasion of CTLs by cancer cells, and show that this pathway is required to resist cytotoxicity induced by the cytokines IFNγ and TNF. Through the mapping of cytokine- and CTL-based genetic interactions, together with in vivo CRISPR screens, we show how the pleiotropic effects of autophagy control cancer-cell-intrinsic evasion of killing by CTLs and we highlight the importance of these effects within the tumour microenvironment. Collectively, these data expand our knowledge of the genetic circuits that are involved in the evasion of the immune system by cancer cells, and highlight genetic interactions that contribute to phenotypes associated with escape from killing by CTLs.

Systematic mapping of genetic interactions for de novo fatty acid synthesis identifies C12orf49 as a regulator of lipid metabolism.

The de novo synthesis of fatty acids has emerged as a therapeutic target for various diseases, including cancer. Because cancer cells are intrinsically buffered to combat metabolic stress, it is important to understand how cells may adapt to the loss of de novo fatty acid biosynthesis. Here, we use pooled genome-wide CRISPR screens to systematically map genetic interactions (GIs) in human HAP1 cells carrying a loss-of-function mutation in fatty acid synthase (FASN), whose product catalyses the formation of long-chain fatty acids. FASN-mutant cells show a strong dependence on lipid uptake that is reflected in negative GIs with genes involved in the LDL receptor pathway, vesicle trafficking and protein glycosylation. Further support for these functional relationships is derived from additional GI screens in query cell lines deficient in other genes involved in lipid metabolism, including LDLR, SREBF1, SREBF2 and ACACA. Our GI profiles also identify a potential role for the previously uncharacterized gene C12orf49 (which we call LUR1) in regulation of exogenous lipid uptake through modulation of SREBF2 signalling in response to lipid starvation. Overall, our data highlight the genetic determinants underlying the cellular adaptation associated with loss of de novo fatty acid synthesis and demonstrate the power of systematic GI mapping for uncovering metabolic buffering mechanisms in human cells.

Constructing inverse probability weights for institutional comparisons in healthcare.

In comparing quality of care between hospitals, disease-specific quality indicators measure structural, process, or outcome elements related to the care of a particular condition. Such comparisons can be framed in terms of causal contrasts, answering the question of whether a patient (or a population of patients on average) would receive different care if treated at the care level of a different hospital. Fair comparisons have to be adjusted for patient case-mix, which is equivalent to controlling for confounding by the patient-level factors, including demographic factors, comorbidities, and disease progression. The methodological choice for such comparisons is usually between direct and indirect standardization methods. In this article, we discuss the alternative of inverse probability weighting as a tool for standardization in hospital comparisons. This involves fitting multinomial logistic hospital assignment models and using these to construct the inverse probability weights. The challenge in the present context is the presence of large number of hospitals being compared, many of which have a small patient volume. We propose methods to include small categories in the weighted analysis, as well as metrics and visualizations for checking the positivity/overlap and covariate balance in constructing such weights. The methods are illustrated in a running example using linked administrative data on surgical treatment of kidney cancer patients in Ontario.

Causal variance decompositions for institutional comparisons in healthcare.

There is increasing interest in comparing institutions delivering healthcare in terms of disease-specific quality indicators (QIs) that capture processes or outcomes showing variations in the care provided. Such comparisons can be framed in terms of causal models, where adjusting for patient case-mix is analogous to controlling for confounding, and exposure is being treated in a given hospital, for instance. Our goal here is to help identify good QIs rather than comparing hospitals in terms of an already chosen QI, and so we focus on the presence and magnitude of overall variation in care between the hospitals rather than the pairwise differences between any two hospitals. We consider how the observed variation in care received at patient level can be decomposed into that causally explained by the hospital performance adjusting for the case-mix, the case-mix itself, and residual variation. For this purpose, we derive a three-way variance decomposition, with particular attention to its causal interpretation in terms of potential outcome variables. We propose model-based estimators for the decomposition, accommodating different link functions and either fixed or random effect models. We evaluate their performance in a simulation study and demonstrate their use in a real data application.

Causal Mediation Analysis for Standardized Mortality Ratios.

Indirectly standardized mortality ratios (SMR) are often used to compare patient outcomes between health care providers as indicators of quality of care. Observed differences in the outcomes raise the question of whether these could be causally attributable to earlier processes or outcomes in the pathway of care that the patients received. Such pathways can be naturally addressed in a causal mediation analysis framework. Adopting causal mediation models allows the total provider effect on outcome to be decomposed into direct and indirect (mediated) effects. This in turn enables quantification of the improvement in patient outcomes due to a hypothetical intervention on the mediator. We formulate the effect decomposition for the indirectly standardized SMR when comparing to a health care system-wide average performance, propose novel model-based and semiparametric estimators for the decomposition, study the properties of these through simulations, and demonstrate their use through application to Ontario kidney cancer data.

Benchmarking quality for renal cancer surgery: Canadian Kidney Cancer information system (CKCis) perspective.

INTRODUCTION: There is a lack of validated quality metrics to evaluate the care of patients receiving surgery for renal cell carcinoma (RCC). To address this, the Kidney Cancer Research Network of Canada defined a list of quality indicators (QI) to assess hospital-level performance. We have case-mix adjusted these QIs to benchmark RCC surgical care at Canadian academic centres. METHODS: The Canadian Kidney Cancer information system (CKCis) was used to measure six QIs: laparoscopic approach proportion (LA), partial nephrectomy proportion (PN), partial nephrectomy in patients with chronic kidney disease (CKDPN), positive margin rate (PMR), partial nephrectomy complication rate (PNCx), and warm ischemia time (WIT). To benchmark performance, indirect standardization (observed-to-expected ratio) methodology was employed using multivariate regression models. RESULTS: Multivariate models for LA, PN, and CKDPN demonstrated good discrimination and were used for benchmarking. National averages of 74% (70-78%), 73% (70-75%), and 70% (67-74%) for the LA, PN, and CKDPN QIs, respectively, were determined and used to benchmark individual hospital performance. Overall, three (23%), two (15%), and two (15%) hospitals performed below expected for LA, PN, and CKDPN, respectively. Hospital identity was an independent predictor of LA, PN, and CKDPN (p<0.001). CONCLUSIONS: Significant variability between CKCis hospitals for three RCC surgical QIs exists. Using the CKCis infrastructure may provide a framework for institution-level audit feedback for quality improvement. Greater CKCis capture rates and further data supporting the construct validity of these QIs are required to extend the use of this dataset to real-world quality initiatives.

The Impact of Quality Variations on Patients Undergoing Surgery for Renal Cell Carcinoma: A National Cancer Database Study.

BACKGROUND: Despite efforts to define metrics assessing hospital-level quality for renal cell carcinoma (RCC) surgical care there remains a paucity of real-world data validating their ability to benchmark performance. Consequently, whether poor performance on hospital-level quality indicators is associated with inferior patient outcomes remains unknown. OBJECTIVES: To determine hospital-level variations in RCC surgical quality after adjusting for differences in patient- and tumor-specific factors. Further, to determine associations between hospital-level quality performance and surgical volume, academic affiliation, and patient mortality. DESIGN, SETTING, AND PARTICIPANTS: RCC patients undergoing surgery in the USA and Puerto Rico (2004-2014) were identified from the National Cancer Database. OUTCOME MEASURES AND STATISTICAL ANALYSIS: Hospital-level quality of care was assessed according to disease-specific process and outcome quality indicators. Case-mix adjusted hospital benchmarking was performed using indirect standardization methodology and multivariable regression models. A composite measure of quality, the Renal Cancer Quality Score (RC-QS), was subsequently derived and associations between RC-QS and surgical volume, academic affiliation, and patient mortality were determined. RESULTS AND LIMITATIONS: Over 1100 hospitals were benchmarked for quality, with 10-31% identified as providing poor care for a given quality indicator. Lower RC-QS hospitals had smaller referral volumes and were less academic compared with higher RC-QS hospitals (p<0.001). Higher RC-QS was independently associated with lower 30-d, 90-d, and overall mortality (adjusted odds ratio [confidence interval]: 0.92 [0.90-0.95], odds ratio: 0.94 [0.91-0.96], hazard ratio: 0.97 [0.96-0.98] per unit increase, respectively). These data are retrospective and it is unknown whether improvement in the RC-QS improves outcomes. CONCLUSIONS: Widespread hospital-level variations in RCC surgical quality exist, as captured by the RC-QS. Superior quality is associated with improved patient outcomes, including mortality benefit. The RC-QS serves as a benchmarking tool for RCC quality that can provide audit level feedback to hospitals and policymakers for quality improvement. PATIENT SUMMARY: We benchmarked hospital performance across quality indicators for kidney cancer surgical care. Overall, large variations in quality exist, with high volume academic hospitals demonstrating superior performance and improved patient survival. These data can inform hospitals and policymakers for quality improvement initiatives.

Repurposing Sunitinib with Oncolytic Reovirus as a Novel Immunotherapeutic Strategy for Renal Cell Carcinoma.

PURPOSE: In addition to their direct cytopathic effects, oncolytic viruses are capable of priming antitumor immune responses. However, strategies to enhance the immunotherapeutic potential of these agents are lacking. Here, we investigated the ability of the multi-tyrosine kinase inhibitor and first-line metastatic renal cell carcinoma (RCC) agent, sunitinib, to augment the antitumor immune response generated by oncolytic reovirus. EXPERIMENTAL DESIGN: In vitro, oncolysis and chemokine production were assessed in a panel of human and murine RCC cell lines after exposure to reovirus, sunitinib, or their combination. In vivo, the RENCA syngeneic murine model of RCC was employed to determine therapeutic and tumor-specific immune responses after treatment with reovirus (intratumoral), sunitinib, or their combination. Parallel investigations employing the KLN205 syngeneic murine model of lung squamous cell carcinoma (NSCLC) were conducted for further validation. RESULTS: Reovirus-mediated oncolysis and chemokine production was observed following RCC infection. Reovirus monotherapy reduced tumor burden and was capable of generating a systemic adaptive antitumor immune response evidenced by increased numbers of tumor-specific CD8+ IFNγ-producing cells. Coadministration of sunitinib with reovirus further reduced tumor burden resulting in improved survival, decreased accumulation of immune suppressor cells, and the establishment of protective immunity upon tumor rechallenge. Similar results were observed for KLN205 tumor-bearing mice, highlighting the potential broad applicability of this approach. CONCLUSIONS: The ability to repurpose sunitinib for augmentation of reovirus' immunotherapeutic efficacy positions this novel combination therapy as an attractive strategy ready for clinical testing against a range of histologies, including RCC and NSCLC. Clin Cancer Res; 22(23); 5839-50. ©2016 AACR.

Assessment of antibiotic prophylaxis prescribing patterns for TURP: A need for Canadian guidelines?

BACKGROUND: While antibiotic prophylaxis is recommended to all patients undergoing transurethral resection of prostate (TURP), little data exist regarding prescribing patterns of urologists prior to this procedure. Here, we sought to determine real-world antibiotic prophylaxis prescribing patterns at a high volume Canadian institution and determine compliance rates to recommendations put forth by the American Urological Association's (AUA) Best Practice Statement (BPS) on antimicrobial prophylaxis. METHODS: A retrospective chart review of 488 patients undergoing TURP was conducted. Electronic medical records were reviewed to determine antibiotics prescribed 3 hours preoperatively and 24 hours postoperatively. For patients without a catheter, compliance was defined as those receiving an antibiotic prior to TURP. In patients with an indwelling catheter, compliance was defined as those receiving antibiotics from two different classes prior to surgery. RESULTS: Overall, a total of 30 antibiotic regimens were utilized. The most common single antibiotic regimens prescribed were ciprofloxacin (32%), cefazolin (25%) and gentamicin (3%). In those patients with indwelling Foley catheters prior to TURP, a significant increase in gentamicin, as well as combination antibiotic regimens, was noted. The compliance rate with the AUA BPS in patients without a preoperative catheter was 81%, while the compliance rate for patients with an indwelling catheter prior to TURP was 37%. INTERPRETATION: Collectively, our results demonstrate that prescribing patterns vary significantly prior to TURP, with compliance to AUA BPS being lower than anticipated. Overall, these results support educational efforts in this area, and the development of Canadian recommendations to improve uptake by practicing urologists.