A genetic basis for sex differences in Xp11 translocation renal cell carcinoma.

Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the transcription factor binding to IGHM enhancer 3 (TFE3) gene on chromosome Xp11.2 and a partner gene on either chromosome X (chrX) or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics constrains somatic chrX alterations and underlies cancer sex differences.

Uncoupled glycerol-3-phosphate shuttle in kidney cancer reveals that cytosolic GPD is essential to support lipid synthesis.

The glycerol-3-phosphate shuttle (G3PS) is a major NADH shuttle that regenerates reducing equivalents in the cytosol and produces energy in the mitochondria. Here, we demonstrate that G3PS is uncoupled in kidney cancer cells where the cytosolic reaction is ∼4.5 times faster than the mitochondrial reaction. The high flux through cytosolic glycerol-3-phosphate dehydrogenase (GPD) is required to maintain redox balance and support lipid synthesis. Interestingly, inhibition of G3PS by knocking down mitochondrial GPD (GPD2) has no effect on mitochondrial respiration. Instead, loss of GPD2 upregulates cytosolic GPD on a transcriptional level and promotes cancer cell proliferation by increasing glycerol-3-phosphate supply. The proliferative advantage of GPD2 knockdown tumor can be abolished by pharmacologic inhibition of lipid synthesis. Taken together, our results suggest that G3PS is not required to run as an intact NADH shuttle but is instead truncated to support complex lipid synthesis in kidney cancer.

A central role for regulated protein stability in the control of TFE3 and MITF by nutrients.

The TFE3 and MITF master transcription factors maintain metabolic homeostasis by regulating lysosomal, melanocytic, and autophagy genes. Previous studies posited that their cytosolic retention by 14-3-3, mediated by the Rag GTPases-mTORC1, was key for suppressing transcriptional activity in the presence of nutrients. Here, we demonstrate using mammalian cells that regulated protein stability plays a fundamental role in their control. Amino acids promote the recruitment of TFE3 and MITF to the lysosomal surface via the Rag GTPases, activating an evolutionarily conserved phospho-degron and leading to ubiquitination by CUL1ß-TrCP and degradation. Elucidation of the minimal functional degron revealed a conserved alpha-helix required for interaction with RagA, illuminating the molecular basis for a severe neurodevelopmental syndrome caused by missense mutations in TFE3 within the RagA-TFE3 interface. Additionally, the phospho-degron is recurrently lost in TFE3 genomic translocations that cause kidney cancer. Therefore, two divergent pathologies converge on the loss of protein stability regulation by nutrients.

TFE3-SLC36A1 axis promotes resistance to glucose starvation in kidney cancer cells.

Higher demand for nutrients including glucose is characteristic of cancer. "Starving cancer" has been pursued to curb tumor progression. An intriguing regime is to inhibit glucose transporter GLUT1 in cancer cells. In addition, during cancer progression, cancer cells may suffer from insufficient glucose supply. Yet, cancer cells can somehow tolerate glucose starvation. Uncovering the underlying mechanisms shall shed insight into cancer progression and benefit cancer therapy. TFE3 is a transcription factor known to activate autophagic genes. Physiological TFE3 activity is regulated by phosphorylation-triggered translocation responsive to nutrient status. We recently reported TFE3 constitutively localizes to the cell nucleus and promotes cell proliferation in kidney cancer even under nutrient replete condition. It remains unclear whether and how TFE3 responds to glucose starvation. In this study, we show TFE3 promotes kidney cancer cell resistance to glucose starvation by exposing cells to physiologically relevant glucose concentration. We find glucose starvation triggers TFE3 protein stabilization through increasing its O-GlcNAcylation. Furthermore, through an unbiased functional genomic study, we identify SLC36A1, a lysosomal amino acid transporter, as a TFE3 target gene sensitive to TFE3 protein level. We find SLC36A1 is overexpressed in kidney cancer, which promotes mTOR activity and kidney cancer cell proliferation. Importantly, SLC36A1 level is induced by glucose starvation through TFE3, which enhances cellular resistance to glucose starvation. Suppressing TFE3 or SLC36A1 significantly increases cellular sensitivity to GLUT1 inhibitor in kidney cancer cells. Collectively, we uncover a functional TFE3-SLC36A1 axis that responds to glucose starvation and enhances starvation tolerance in kidney cancer.

Cytosolic GDH1 degradation restricts protein synthesis to sustain tumor cell survival following amino acid deprivation.

The mTORC1 pathway plays key roles in regulating various biological processes, including sensing amino acid deprivation and driving expression of ribosomal protein (RP)-coding genes. In this study, we observed that depletion of glutamate dehydrogenase 1 (GDH1), an enzyme that converts glutamate to α-ketoglutarate (αKG), confers resistance to amino acid deprivation on kidney renal clear cell carcinoma (KIRC) cells. Mechanistically, under conditions of adequate nutrition, GDH1 maintains RP gene expression in a manner dependent on its enzymatic activity. Following amino acid deprivation or mTORC1 inhibition, GDH1 translocates from mitochondria to the cytoplasm, where it becomes ubiquitinated and degraded via the E3 ligase RNF213. GDH1 degradation reduces intracellular αKG levels by more than half and decreases the activity of αKG-dependent lysine demethylases (KDMs). Reduced KDM activity in turn leads to increased histone H3 lysine 9 and 27 methylation, further suppressing RP gene expression and preserving nutrition to support cell survival. In summary, our study exemplifies an economical and efficient strategy of solid tumor cells for coping with amino acid deficiency, which might in the future be targeted to block renal carcinoma progression.

TRIM28 represses renal cell carcinoma cell proliferation by inhibiting TFE3/KDM6A-regulated autophagy.

Autophagy plays a pivotal role in physiology and pathophysiology, including cancer. Mechanisms of autophagy dysregulation in cancer remain elusive. Loss of function of TRIM28, a multifunction protein, is seen in familial kidney malignancy, but the mechanism by which TRIM28 contributes to the etiology of kidney malignancy is unclear. In this study, we show TRIM28 retards kidney cancer cell proliferation through inhibiting autophagy. Mechanistically, we find TRIM28 promotes ubiquitination and proteasome-mediated degradation of transcription factor TFE3, which is critical for autophagic gene expression. Genetic activation of TFE3 due to gene fusion is known to cause human kidney malignancy, but whether and how transcription activation by TFE3 involves chromatin changes is unclear. Here, we find another mode of TFE3 activation in human renal carcinoma. We find that TFE3 is constitutively localized to the cell nucleus in human and mouse kidney cancer, where it increases autophagic gene expression and promotes cell autophagy as well as proliferation. We further uncover that TFE3 interacts with and recruits histone H3K27 demethylase KDM6A for autophagic gene upregulation. We reveal that KDM6A contributes to expression of TFE3 target genes through increasing H3K4me3 rather than demethylating H3K27. Collectively, in this study, we identify a functional TRIM28-TFE3-KDM6A signal axis, which plays a critical role in kidney cancer cell autophagy and proliferation.

l-2-Hydroxyglutarate contributes to tumor radioresistance through regulating the hypoxia-inducible factor-1α signaling pathway.

l-2-Hydroxyglutarate (l-2-HG) has been regarded as a tumor metabolite, and it plays a crucial role in adaptation of tumor cells to hypoxic conditions. However, the role of l-2-HG in tumor radioresistance and the underlying mechanism have not yet been revealed. Here, we found that l-2-HG exhibited to have radioresistance effect on U87 human glioblastoma cells, which could reduce DNA damage and apoptosis caused by irradiation, promote cell proliferation and migration, and impair G2/M phase arrest. Mechanistically, l-2-HG upregulated the protein level of hypoxia-inducible factor-1α (HIF-1α) and the expression levels of HIF-1α downstream target genes. The knockdown of l-2-hydroxyglutarate dehydrogenase (L2HGDH) gene promoted the tumor growth and proliferation of U87 cells in nude mice by increasing HIF-1α expression level in vivo. In addition, the low expression level of L2HGDH gene was correlated with the short survival of patients with glioma or kidney cancer. In conclusion, our study revealed the role and mechanism of l-2-HG in tumor radioresistance and may provide a new perspective for overcoming tumor radioresistance and broaden our comprehension of the role of metabolites in tumor microenvironment.

Pathogenic Roles for RNASET2 in Clear Cell Renal Cell Carcinoma.

A specific splicing isoform of RNASET2 is associated with worse oncologic outcomes in clear cell renal cell carcinoma (ccRCC). However, the interplay between wild-type RNASET2 and its splice variant and how this might contribute to the pathogenesis of ccRCC remains poorly understood. We sought to better understand the relationship of RNASET2 in the pathogenesis of ccRCC and the interplay with a pathogenic splicing isoform (RNASET2-SV) and the tumor immune microenvironment. Using data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, we correlated clinical variables to RNASET2 expression and the presence of a specific RNASET2-SV. Immunohistochemical staining with matched RNA sequencing of ccRCC patients was then utilized to understand the spatial relationships of RNASET2 with immune cells. Finally, in vitro studies were performed to demonstrate the oncogenic role of RNASET2 and highlight its potential mechanisms. RNASET2 gene expression is associated with higher grade tumors and worse overall survival in The Cancer Genome Atlas cohort. The presence of the RNASET2-SV was associated with increased expression of the wild-type RNASET2 protein and epigenetic modifications of the gene. Immunohistochemical staining revealed increased intracellular accumulation of RNASET2 in patients with increased RNA expression of RNASET2-SV. In vitro experiments reveal that this accumulation results in increased cell proliferation, potentially from altered metabolic pathways. RNASET2 exhibits a tumor-promoting role in the pathogenesis of ccRCC that is increased in the presence of a specific RNASET2-SV and associated with changes in the cellular localization of the protein.

Advances in non-clear cell renal cell carcinoma management: From heterogeneous biology to treatment options.

Non-clear cell renal cell carcinoma (nccRCC) makes up nearly one quarter of all RCC subtypes, commonly impacts younger patients, and is often metastatic at presentation. Compared to clear-cell RCC (ccRCC), nccRCC typically has a worse prognosis in the metastatic setting, with overall survival durations that are ~10 months shorter. The nccRCC consists of a wide range of different histological subtypes, the majority of which are composed of papillary, chromophobe, renal medullary carcinoma, translocation RCC, collecting duct carcinoma and unclassified RCC. Most clinical trials have either excluded or only included small numbers of patients with nccRCC; owing to the lack of prospective studies focusing on this population, data on response rates and survival outcomes are lacking. NccRCC treatment is a nascent field with various therapeutic modalities and combinations under investigation, often based on data extrapolated from therapeutic studies in ccRCC. We herein review the use and outcomes of cytotoxic chemotherapy, various combination modalities of tyrosine kinase inhibitors and immune checkpoint inhibitors, and targeted agents. We discuss active ongoing clinical trials for patients with nccRCC and future directions in the treatment of this rare disease. Historically, treatment for nccRCC has been adopted from the standard of care for patients with ccRCC, although these treatments are less effective in the nccRCC population. As we begin to understand the underlying biology of these tumors, clinical trials have been able to slowly accrue and include more patients with various subtypes of nccRCC. There remains much room for improvement in this area of need, but there is hope on the horizon.

Proteogenomics in Nephrology: A New Frontier in Nephrological Research.

Proteogenomics represents a transformative intersection in nephrology, uniting genomics, transcriptomics, and proteomics to unravel the molecular intricacies of kidney diseases. This review encapsulates the methodological essence of proteogenomics and its profound implications in chronic kidney disease (CKD) research. We explore the proteogenomic pipeline, highlighting the integrated analysis of genomic, transcriptomic, and proteomic data and its pivotal role in enhancing our understanding of kidney pathologies. Through case studies, we showcase the application of proteogenomics in clear cell renal cell carcinoma (ccRCC) and Autosomal Recessive Polycystic Kidney Disease (ARPKD), emphasizing its potential in personalized treatment strategies and biomarker discovery. The review also addresses the challenges in proteogenomic analysis, including data integration complexities and bioinformatics limitations, and proposes solutions for advancing the field. Ultimately, this review underscores the prospective future of proteogenomics in nephrology, particularly in advancing personalized medicine and providing novel therapeutic insights.

Radiogenomics and Texture Analysis to Detect von Hippel-Lindau (VHL) Mutation in Clear Cell Renal Cell Carcinoma.

Radiogenomics, a burgeoning field in biomedical research, explores the correlation between imaging features and genomic data, aiming to link macroscopic manifestations with molecular characteristics. In this review, we examine existing radiogenomics literature in clear cell renal cell carcinoma (ccRCC), the predominant renal cancer, and von Hippel-Lindau (VHL) gene mutation, the most frequent genetic mutation in ccRCC. A thorough examination of the literature was conducted through searches on the PubMed, Medline, Cochrane Library, Google Scholar, and Web of Science databases. Inclusion criteria encompassed articles published in English between 2014 and 2022, resulting in 10 articles meeting the criteria out of 39 initially retrieved articles. Most of these studies applied computed tomography (CT) images obtained from open source and institutional databases. This literature review investigates the role of radiogenomics, with and without texture analysis, in predicting VHL gene mutation in ccRCC patients. Radiogenomics leverages imaging modalities such as CT and magnetic resonance imaging (MRI), to analyze macroscopic features and establish connections with molecular elements, providing insights into tumor heterogeneity and biological behavior. The investigations explored diverse mutations, with a specific focus on VHL mutation, and applied CT imaging features for radiogenomic analysis. Moreover, radiomics and machine learning techniques were employed to predict VHL gene mutations based on CT features, demonstrating promising results. Additional studies delved into the relationship between VHL mutation and body composition, revealing significant associations with adipose tissue distribution. The review concludes by highlighting the potential role of radiogenomics in guiding targeted and selective therapies.

In Silico and In Vitro Study of Isoquercitrin against Kidney Cancer and Inflammation by Triggering Potential Gene Targets.

Kidney cancer has emerged as a major medical problem in recent times. Multiple compounds are used to treat kidney cancer by triggering cancer-causing gene targets. For instance, isoquercitrin (quercetin-3-O-ß-d-glucopyranoside) is frequently present in fruits, vegetables, medicinal herbs, and foods and drinks made from plants. Our previous study predicted using protein-protein interaction (PPI) and molecular docking analysis that the isoquercitrin compound can control kidney cancer and inflammation by triggering potential gene targets of IGF1R, PIK3CA, IL6, and PTGS2. So, the present study is about further in silico and in vitro validation. We performed molecular dynamic (MD) simulation, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, cytotoxicity assay, and RT-PCR and qRT-PCR validation. According to the MD simulation (250 ns), we found that IGF1R, PIK3CA, and PTGS2, except for IL6 gene targets, show stable binding energy with a stable complex with isoquercitrin. We also performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the final targets to determine their regulatory functions and signaling pathways. Furthermore, we checked the cytotoxicity effect of isoquercitrin (IQ) and found that 5 µg/mL and 10 µg/mL doses showed higher cell viability in a normal kidney cell line (HEK 293) and also inversely showed an inhibition of cell growth at 35% and 45%, respectively, in the kidney cancer cell line (A498). Lastly, the RT-PCR and qRT-PCR findings showed a significant decrease in PTGS2, PIK3CA, and IGF1R gene expression, except for IL6 expression, following dose-dependent treatments with IQ. Thus, we can conclude that isoquercitrin inhibits the expression of PTGS2, PIK3CA, and IGF1R gene targets, which in turn controls kidney cancer and inflammation.

Genomic ancestry in kidney cancer: Correlations with clinical and molecular features.

INTRODUCTION: Genetic ancestry (GA) refers to population hereditary patterns that contribute to phenotypic differences seen among race/ethnicity groups, and differences among GA groups may highlight unique biological determinants that add to our understanding of health care disparities. METHODS: A retrospective review of patients with renal cell carcinoma (RCC) was performed and correlated GA with clinicopathologic, somatic, and germline molecular data. All patients underwent next-generation sequencing of normal and tumor DNA using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets, and contribution of African (AFR), East Asian (EAS), European (EUR), Native American, and South Asian (SAS) ancestry was inferred through supervised ADMIXTURE. Molecular data was compared across GA groups by Fisher exact test and Kruskal-Wallis test. RESULTS: In 953 patients with RCC, the GA distribution was: EUR (78%), AFR (4.9%), EAS (2.5%), SAS (2%), Native American (0.2%), and Admixed (12.2%). GA distribution varied by tumor histology and international metastatic RCC database consortium disease risk status (intermediate-poor: EUR 58%, AFR 88%, EAS 74%, and SAS 73%). Pathogenic/likely pathogenic germline variants in cancer-predisposition genes varied (16% EUR, 23% AFR, 8% EAS, and 0% SAS), and most occurred in CHEK2 in EUR (3.1%) and FH in AFR (15.4%). In patients with clear cell RCC, somatic alteration incidence varied with significant enrichment in BAP1 alterations (EUR 17%, AFR 50%, SAS 29%; p = .01). Comparing AFR and EUR groups within The Cancer Genome Atlas, significant differences were identified in angiogenesis and inflammatory pathways. CONCLUSION: Differences in clinical and molecular data by GA highlight population-specific variations in patients with RCC. Exploration of both genetic and nongenetic variables remains critical to optimize efforts to overcome health-related disparities.

2018 Leibovich prognostic model for renal cell carcinoma: Performance in a large population with special consideration of Black race.

BACKGROUND: The 2018 Leibovich prognostic model for nonmetastatic renal cell carcinoma (RCC) combines clinical, surgical, and pathologic factors to predict progression-free survival (PFS) and cancer-specific survival (CSS) for patients with clear cell (ccRCC), papillary (pRCC), and chromophobe (chRCC) histology. Despite high accuracy, <1% of the original cohort was Black. Here, the authors examined this model in a large population with greater Black patient representation. METHODS: By using a prospectively maintained RCC institutional database, patients were assigned Leibovich model risk scores. Survival outcomes included 5-year and 10-year PFS and CSS. Prognostic accuracy was determined using area under the curve (AUC) analysis and calibration plots. Black patient subanalyses were conducted. RESULTS: In total, 657 (29%) of 2295 patients analyzed identified as Black. Declines in PFS and CSS were observed as scores increased. Discrimination for ccRCC was strong for PFS (AUC: 5-year PFS, 0.81; 10-year PFS, 0.78) and for CSS (AUC: 5-year CSS, 0.82; 10-year CSS, 0.74). The pRCC AUC for PFS was 0.74 at 5 years and 0.71 at 10 years; and the AUC for CSS was 0.74 at 5 years and 0.70 at 10 years. In chRCC, better performance was observed for CSS (AUC at 5 years, 0.75) than for PFS (AUC: 0.66 at 5 years; 0.55 at 10 years). Black patient subanalysis revealed similar-to-improved performance for ccRCC at 5 years (AUC: PFS, 0.79; CSS, 0.87). For pRCC, performance was lower for PFS (AUC at 5 years, 0.63) and was similar for CSS (AUC at 5 years, 0.77). Sample size limited Black patient 10-year and chRCC analyses. CONCLUSIONS: The authors externally validated the 2018 Leibovich RCC prognostic model and found optimal performance for ccRCC, followed by pRCC, and then chRCC. Importantly, the results were consistent in this large representation of Black patients. PLAIN LANGUAGE SUMMARY: In 2018, a model to predict survival in patients with renal cell carcinoma (kidney cancer) was introduced by Leibovich et al. This model has performed well; however, Black patients have been under-represented in examination of its performance. In this study, 657 Black patients (29%) were included, and the results were consistent. This work is important for making sure the model can be applied to all patient populations.

Impact of smoking status on clinical outcomes in patients with metastatic renal cell carcinoma treated with first-line immune checkpoint inhibitor-based regimens.

BACKGROUND: Current tobacco smoking is independently associated with decreased overall survival (OS) among patients with metastatic renal cell carcinoma (mRCC) treated with targeted monotherapy (VEGF-TKI). Herein, we assess the influence of smoking status on the outcomes of patients with mRCC treated with the current first-line standard of care of immune checkpoint inhibitor (ICI)-based regimens. MATERIALS AND METHODS: Real-world data from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) were collected retrospectively. Patients with mRCC who received either dual ICI therapy or ICI with VEGF-TKI in the first-line setting were included and were categorized as current, former, or nonsmokers. The primary outcomes were OS, time to treatment failure (TTF), and objective response rate (ORR). OS and TTF were compared between groups using the log-rank test and multivariable Cox regression models. ORR was assessed between the 3 groups using a multivariable logistic regression model. RESULTS: A total of 989 eligible patients were included in the analysis, with 438 (44.3%) nonsmokers, 415 (42%) former, and 136 (13.7%) current smokers. Former smokers were older and included more males, while other baseline characteristics were comparable between groups. Median follow-up for OS was 21.2 months. In the univariate analysis, a significant difference between groups was observed for OS (P = .027) but not for TTF (P = .9), with current smokers having the worse 2-year OS rate (62.8% vs 70.8% and 73.1% in never and former smokers, respectively). After adjusting for potential confounders, no significant differences in OS or TTF were observed among the 3 groups. However, former smokers demonstrated a higher ORR compared to never smokers (OR 1.45, P = .02). CONCLUSION: Smoking status does not appear to independently influence the clinical outcomes to first-line ICI-based regimens in patients with mRCC. Nonetheless, patient counseling on tobacco cessation remains a crucial aspect of managing patients with mRCC, as it significantly reduces all-cause mortality.

Long-Term Survival in Patients With Relapsed/Refractory Advanced Renal Cell Carcinoma Treated With Tivozanib: Analysis of the Phase III TIVO-3 Trial.

BACKGROUND: Tivozanib is an oral vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitor (TKI) with efficacy in advanced renal cell carcinoma (RCC). Long-term exploratory analyses from the TIVO-3 trial in relapsed/refractory (R/R) RCC including patients (26%) with prior immuno-oncology (IO) therapy are reported. METHODS: Patients with R/R advanced RCC that progressed with 2 or 3 prior systemic therapies (≥1 VEGFR TKI) were randomized to tivozanib 1.5 mg QD or sorafenib 400 mg BID, stratified by IMDC risk and previous therapy. Safety, investigator-assessed long-term progression-free survival (LT-PFS), and serial overall survival (OS) were assessed. RESULTS: Mean time on treatment was 11.0 months with tivozanib (n = 175) and 6.3 months with sorafenib (n = 175). Fewer grade ≥3 treatment-related adverse events occurred with tivozanib (46%) than sorafenib (55%). Dose modification rates were lower with tivozanib than sorafenib across age/prior IO subgroups; prior IO therapy did not impact dose reductions or discontinuations in either arm. Landmark LT-PFS rates were higher with tivozanib (3 years: 12.3% vs 2.4%; 4 years: 7.6% vs 0%). After 22.8 months mean follow-up, the OS HR was 0.89 (95% CI, 0.70-1.14); when conditioned on 12-month landmark PFS, tivozanib showed significant OS improvement over sorafenib (HR, 0.45; 95% CI, 0.22-0.91; 2-sided P = .0221). CONCLUSIONS: Tivozanib demonstrated a consistent safety profile and long-term survival benefit in patients with R/R advanced RCC who were alive and progression free at 12 months. These post hoc exploratory analyses of LT-PFS and conditional OS support a clinically meaningful improvement with tivozanib versus sorafenib in this advanced RCC population.

TIGIT expression in renal cell carcinoma infiltrating T cells is variable and inversely correlated with PD-1 and LAG3.

PURPOSE: Immune checkpoint inhibitors have revolutionized the treatment of renal cell carcinoma (RCC), but many patients do not respond to therapy and the majority develop resistant disease over time. Thus, there is increasing need for alternative immunomodulating agents. The co-inhibitory molecule T-cell immunoglobulin and ITIM domain (TIGIT) may play a role in resistance to approved immune checkpoint inhibitors and is being investigated as a potential therapeutic target. The purpose of this study was to quantify TIGIT positivity in tumor-infiltrating T cells in RCC. METHODS: We employed tissue microarrays containing specimens from primary RCC tumors, adjacent normal renal tissue, and RCC metastases to quantify TIGIT within tumor-infiltrating CD3+ T cells using quantitative immunofluorescent analysis. We also compared these results to TIGIT+ CD3+ levels in four other tumor types (melanoma, non-small cell lung, cervical, and head and neck cancers). RESULTS: We did not observe significant differences in TIGIT positivity between primary RCC tumors and patient-matched metastatic samples. We found that the degree of TIGIT positivity in RCC is comparable to that in lung cancer but lower than that in melanoma, cervical, and head and neck cancers. Correlation analysis comparing TIGIT positivity to previously published, patient-matched spatial proteomic data by our group revealed a negative association between TIGIT and the checkpoint proteins PD-1 and LAG3. CONCLUSION: Our findings support careful evaluation of TIGIT expression on T cells in primary or metastatic RCC specimens for patients who may be treated with TIGIT-targeting antibodies, as increased TIGIT positivity might be associated with a greater likelihood of response to therapy.

Limitations of Parenchymal Volume Analysis for Estimating Split Renal Function and New Baseline Glomerular Filtration Rate After Radical Nephrectomy.

PURPOSE: Accurately predicting new baseline glomerular filtration rate (NBGFR) after radical nephrectomy (RN) can improve counseling about RN vs partial nephrectomy. Split renal function (SRF)-based models are optimal, and differential parenchymal volume analysis (PVA) is more accurate than nuclear renal scans (NRS) for this purpose. However, there are minimal data regarding the limitations of PVA. Our objective was to identify patient-/tumor-related factors associated with PVA inaccuracy. MATERIALS AND METHODS: Five hundred and ninety-eight RN patients (2006-2021) with preoperative CT/MRI were retrospectively analyzed, with 235 also having NRS. Our SRF-based model to predict NBGFR was: 1.25 × (GlobalGFRPre-RN × SRFContralateral), where GFR indicates glomerular filtration rate, with SRF determined by PVA or NRS, and with 1.25 representing the median renal functional compensation in adults. Accuracy of predicted NBGFR within 15% of observed was evaluated in various patient/tumor cohorts using multivariable logistic regression analysis. RESULTS: PVA and NRS accuracy were 73%/52% overall, and 71%/52% in patients with both studies (n = 235, P < .001), respectively. PVA inaccuracy independently associated with pyelonephritis, hydronephrosis, renal vein thrombosis, and infiltrative features (all P < .03). Ipsilateral hydronephrosis and renal vein thrombosis associated with PVA underprediction, while contralateral hydronephrosis and increased age associated with PVA overprediction (all P < .01). NRS inaccuracy was more common and did not associate with any of these conditions. Even among cohorts where PVA inaccuracy was observed (22% of our patients), there was no significant difference in the accuracies of NRS- and PVA-based predictions. CONCLUSIONS: PVA was more accurate for predicting NBGFR after RN than NRS. Inaccuracy of PVA correlated with factors that distort the parenchymal volume/function relationship or alter renal functional compensation. NRS inaccuracy was more common and unpredictable, likely reflecting the inherent inaccuracy of NRS. Awareness of cohorts where PVA is less accurate can help guide clinical decision-making.

Decisional Conflict Among Patients Newly Diagnosed With Clinical T1 Renal Masses: A Prospective Study.

PURPOSE: Because multiple management options exist for clinical T1 renal masses, patients may experience a state of uncertainty about the course of action to pursue (ie, decisional conflict). To better support patients, we examined patient, clinical, and decision-making factors associated with decisional conflict among patients newly diagnosed with clinical T1 renal masses suspicious for kidney cancer. MATERIALS AND METHODS: From a prospective clinical trial, participants completed the Decisional Conflict Scale (DCS), scored 0 to 100 with < 25 associated with implementing decisions, at 2 time points during the initial decision-making period. The trial further characterized patient demographics, health status, tumor burden, and patient-centered communication, while a subcohort completed additional questionnaires on decision-making. Associations of patient, clinical, and decision-making factors with DCS scores were evaluated using generalized estimating equations to account for repeated measures per patient. RESULTS: Of 274 enrollees, 250 completed a DCS survey; 74% had masses ≤ 4 cm in size, while 11% had high-complexity tumors. Model-based estimated mean DCS score across both time points was 17.6 (95% CI 16.0-19.3), though 50% reported a DCS score ≥ 25 at least once. On multivariable analysis, DCS scores increased with age (+2.64, 95% CI 1.04-4.23), high- vs low-complexity tumors (+6.50, 95% CI 0.35-12.65), and cystic vs solid masses (+9.78, 95% CI 5.27-14.28). Among decision-making factors, DCS scores decreased with higher self-efficacy (-3.31, 95% CI -5.77 to -0.86]) and information-seeking behavior (-4.44, 95% CI -7.32 to -1.56). DCS scores decreased with higher patient-centered communication scores (-8.89, 95% CI -11.85 to -5.94). CONCLUSIONS: In addition to patient and clinical factors, decision-making factors and patient-centered communication relate with decisional conflict, highlighting potential avenues to better support patient decision-making for clinical T1 renal masses.

Perioperative Complications and In-Hospital Mortality in Partial and Radical Nephrectomy Patients with Heart-Valve Replacement.

BACKGROUND: In-hospital mortality and complication rates after partial and radical nephrectomy in patients with history of heart-valve replacement are unknown. PATIENTS AND METHODS: Relying on the National Inpatient Sample (2000-2019), kidney cancer patients undergoing partial or radical nephrectomy were stratified according to presence or absence of heart-valve replacement. Multivariable logistic and Poisson regression models addressed adverse hospital outcomes. RESULTS: Overall, 39,673 patients underwent partial nephrectomy versus 94,890 radical nephrectomy. Of those, 248 (0.6%) and 676 (0.7%) had a history of heart-valve replacement. Heart-valve replacement patients were older (median partial nephrectomy 69 versus 60 years; radical nephrectomy 71 versus 63 years), and more frequently exhibited Charlson comorbidity index ≥ 3 (partial nephrectomy 22 versus 12%; radical nephrectomy 32 versus 23%). In partial nephrectomy patients, history of heart-valve replacement increased the risk of cardiac complications [odds ratio (OR) 4.33; p < 0.001), blood transfusions (OR 2.00; p < 0.001), intraoperative complications (OR 1.53; p = 0.03), and longer hospital stay [rate ratio (RR) 1.25; p < 0.001], but not in-hospital mortality (p = 0.5). In radical nephrectomy patients, history of heart-valve replacement increased risk of postoperative bleeding (OR 4.13; p < 0.001), cardiac complications (OR 2.72; p < 0.001), intraoperative complications (OR 1.53; p < 0.001), blood transfusions (OR 1.27; p = 0.02), and longer hospital stay (RR 1.12; p < 0.001), but not in-hospital mortality (p = 0.5). CONCLUSIONS: History of heart-valve replacement independently predicted four of twelve adverse outcomes in partial nephrectomy and five of twelve adverse outcomes in radical nephrectomy patients including intraoperative and cardiac complications, blood transfusions, and longer hospital stay. Conversely, no statistically significant differences were observed in in-hospital mortality.