ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma.

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC. We analyzed the expression levels of ERBB2 in various cancers from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA-seq data were analyzed using R packages to identify differentially expressed genes between the high and low ERBB2 expression groups in the TCGA-KIRC dataset. Spearman correlation analysis was performed to determine the correlation between ERBB2 expression and immune cell infiltration, immune checkpoint expression, and PTEN expression. DNA methylation changes and genetic alterations in ERBB2 were assessed using the MethSurv and cBioPortal databases. Logistic regression analysis was performed to determine the correlation between ERBB2 expression and the clinicopathological characteristics of ccRCC patients. The diagnostic and prognostic value of ERBB2 was assessed using Kaplan‒Meier (K‒M) survival curves, diagnostic ROC curves, time-dependent ROC curves, nomogram models, and Cox regression models. The expression level of ERBB2 is lower in tumor tissues of ccRCC patients than in the corresponding control tissues. Differentially expressed genes associated with ERBB2 were significantly enriched in the pathways "BMP2WNT4FOXO1 pathway in primary endometrial stromal cell differentiation" and "AMAN pathway". In ccRCC tissues, ERBB2 expression levels were associated with immune cell infiltration, immune checkpoints, and PTEN. The DNA methylation status of 10 CpG islands in the ERBB2 gene was associated with the prognosis of ccRCC. ERBB2 expression levels in ccRCC tissues were associated with race, sex, T stage, M stage, histological grade, and pathological stage. Cox regression analysis showed that ERBB2 was a potential independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in ccRCC patients. ROC curve analysis showed that the expression level of ERBB2 could accurately distinguish between ccRCC tissue and adjacent normal renal tissue. Our study showed that ERBB2 expression in ccRCC tissues can be of clinical importance as a potential diagnostic and prognostic biomarker.

Ultra-processed food consumption and renal cell carcinoma incidence and mortality: results from a large prospective cohort.

BACKGROUND: Growing evidence shows that ultra-processed food consumption is associated with the risk of cancer. However, prospective evidence is limited on renal cell carcinoma (RCC) incidence and mortality. In this study, we aimed to examine the association of ultra-processed food consumption and RCC incidence and mortality in a large cohort of US adults. METHODS: A population-based cohort of 101,688 participants were included from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Ultra-processed food items were confirmed by using the NOVA food classification system. The consumption of ultra-processed food was expressed as a percentage of total food intake (g/day). Prospective associations were calculated using Cox regression. Restricted cubic spline regression was used to assess nonlinearity. Subgroup analyses were performed to investigate the potential effect modifiers on the incidence and mortality of RCC. RESULTS: A total of 410 participants developed RCC during a total of 899,731 person-years of follow-up (median 9.41 years) and 230 RCC deaths during 1,533,930 person-years of follow-up (median 16.85 years). In the fully adjusted model, participants in the highest compared with the lowest quintiles of ultra-processed food consumption had a higher risk of RCC (HR quartile 4 vs 1:1.42; 95% CI: 1.06-1.91; Ptrend = 0.004) and mortality (HR quartile 4 vs. quartile 1: 1.64; 95% CI: 1.10-2.43; Ptrend = 0.027). Linear dose-response associations with RCC incidence and mortality were observed for ultra-processed food consumption (all Pnonlinearity > 0.05). The reliability of these results was supported by sensitivity and subgroup analyses. CONCLUSION: In conclusion, higher consumption of ultra-processed food is associated with an increased risk of RCC incidence and mortality. Limiting ultra-processed food consumption might be a primary prevention method of RCC.

Predicting the prognosis of patients with renal cell carcinoma based on the systemic immune inflammation index and prognostic nutritional index.

The aim of the study was to analyze and discuss the value of preoperative systemic immune inflammation index (SII) and prognostic nutritional index (PNI) in predicting the prognosis of patients with renal cell carcinoma (RCC) after operation, and to establish a nomogram prediction model for patients with RCC after operation based on SII and PNI. From January 2014 to December 2018, 210 patients with RCC who underwent surgical treatment at the Xuzhou Central Hospital were selected as the research object. The receiver operating characteristic curve (ROC) was used to determine the optimal cut-off value for preoperative SII, PNI, LMR, PLR, NLR and the patients were divided into groups according to the optimal cutoff values. The survival rate of patients was evaluated. The risk factors that affect the prognosis of patients with RCC were determined by LASSO and Cox regression analysis, and a prognostic nomogram was constructed based on this result. The bootstrap method was used for internal verification of the nomogram model. The prediction efficiency and discrimination of the nomogram model were evaluated by the calibration curve and index of concordance (C-index), respectively. The average overall survival (OS) of all patients was 75.385 months, and the 1-, 2-and 3-year survival rates were 95.5%, 86.6% and 77.2%, respectively. The survival curve showed that the 5-year OS rate of low SII group was significantly higher than that of high SII group (89.0% vs. 64.5%; P < 0.05), and low PNI group was significantly lower than those in high PNI group (43.4% vs. 87.9%; p < 0.05). There were significant differences between preoperative SII and CRP, NLR, PLR, LMR, postoperative recurrence, pathological type and AJCC stage (P < 0.05). There were significant differences between preoperative PNI and BMI, platelet, NLR, PLR, LMR, postoperative recurrence, surgical mode and Fuhrman grade (P < 0.05). The ROC curve analysis showed that the AUC of PNI (AUC = 0.736) was higher than that of other inflammatory indicators, followed by the AUC of SII (0.718), and the difference in AUC area between groups was statistically significant (P < 0.05). The results from multivariate Cox regression analysis showed that SII, PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade were independent risk factors for postoperative death of patients with RCC. According to the results of Cox regression analysis, a prediction model for the prognosis of RCC patients was established, and the C-index (0.918) showed that the model had good calibration and discrimination. The subject's operating characteristic curve indicates that the nomogram has good prediction efficiency (the AUC = 0.953). Preoperative SII and PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade are closely related to the postoperative prognosis of patients with renal cell carcinoma. The nomogram model based on SII, PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade has good accuracy, discrimination and clinical prediction efficiency.

Outcomes of laparoscopic, robotic and open nephroureterectomy with bladder cuff excision in patients with T3T4 upper urinary tract urothelial carcinoma: a multi-center retrospective study.

BACKGROUND: Nephroureterectomy with bladder cuff excision is the standard treatment for high-risk upper urinary tract urothelial carcinoma (UTUC). The role of minimally invasive surgery in treating locally advanced UTUC remains controversial. This study aimed to compare the outcomes of open, laparoscopic, and robotic surgeries for managing locally advanced UTUC. METHODS: We retrospectively reviewed 705 patients with locally advanced UTUC from multiple institutions throughout Taiwan. Perioperative outcomes and oncological outcomes, such as cancer-specific survival, overall survival, disease-free survival and bladder-free survival, were compared between the open, laparoscopic and robotic groups. RESULTS: The minimally invasive group had better overall and cancer-specific survival (CSS) rates. The 2-year CSS rates of the open, laparoscopic and robotic groups were 71%, 83%, and 77% respectively (p < 0.001). The robotic group had similar outcomes to the laparoscopic group. (p = 0.061, 0.825, 0.341 for OS, CSS, DFS respectively.) More lymph node dissections were performed and more lymph nodes were harvested in the robotic group (p = 0.009). CONCLUSIONS: Our results demonstrated that minimally invasive surgery, including laparoscopic and robotic surgery, for locally advanced UTUC resulted in oncological outcomes that are non-inferior to those of open surgery.

Crafting and Authenticating Prognostic Nomograms for Overall and Cancer-specific Survival in Pediatric Small Renal Masses: A Comprehensive Two-Decade Cohort Study.

BACKGROUND: The intricate task of diagnosing and managing small renal masses (SRMs) has become progressively convoluted within the realm of clinical practice. Contemporary clinical prediction instruments may succumb to a gradual decay in precision, coupled with an absence of unambiguous guidelines to navigate patient management. METHODS: This investigation was devised to formulate and authenticate nomograms for the overall survival (OS) and cancer- specific survival (CSS) among patients afflicted with SRMs. The study encompassed a cohort of 2558 pediatric patients diagnosed with SRMs over the period of 2000 to 2019. Independent prognostic indicators for OS and CSS, encompassing historical staging, chemotherapy regimens, surgical interventions, and pathological classifications, were ascertained through the employment of multivariate Cox proportional hazards regression analysis and backward stepwise selection. RESULTS: Through the utilization of multivariate Cox regression models, nomograms for OS and CSS were meticulously crafted, demonstrating commendable discrimination and calibration within the training set (OS C-index: 0.762, CSS C-index: 0.779). The validation set further corroborated the exemplary discrimination and calibration of the nomograms. Moreover, these nomograms adeptly differentiated between patient groups at elevated and diminished risk levels. CONCLUSION: The nomograms delineated in this research provide propitious predictive accuracy for overall survival and cancer-specific survival in patients suffering from pediatric SRMs, thereby contributing to refined risk stratification and steering the optimal therapeutic course of action. The necessity for supplementary validation prevails before the translation of these findings into clinical practice.

Prognostic factors and prognostic model of non-metastatic clear cell renal cell carcinoma.

INTRODUCTION: Although there are some established prognostic evaluation models for clear cell renal cell carcinoma (ccRCC), more robust postoperative prognostic evaluation model is urgently needed. Our study intends to explore new clinical and pathological prognostic factors related to non-metastatic ccRCC, which help to establish a better prognostic risk evaluation model in non-metastatic ccRCC. PATIENTS AND METHODS: A retrospective cohort study was conducted in non-metastatic ccRCC patients spanning from 2010 to 2018. Clinical and pathological factors of these patients were collected. Cox regression analysis was employed to assess the relationship between these factors and disease-free survival (DFS), and a nomogram risk prediction model was also constructed. RESULTS: A total of 1467 patients were ultimately included, comprising 994 men (67.8%), with 800 patients aged between 40 and 60 years old (54.5%), and 80 patients (5.5%) experiencing relapse or metastasis of ccRCC within three years after operation. The follow-up duration ranged from 39 to 146 months. Univariate and multivariate Cox regression analysis identified five independent prognostic factors of DFS (P < 0.05) including sex, tumor maximum diameter, T stage, lactate dehydrogenase (LDH), and basophils. Leveraging these five factors, we established a prognostic evaluation model demonstrating good predictive efficacy. CONCLUSION: Male, tumor maximum diameter, T stage, LDH, and basophils serve as prognostic indicators for DFS in patients with non-metastatic ccRCC. Patients with high scores based on our model exhibit an elevated likelihood of recurrence or metastasis, thereby potentially selecting postoperative patients with high risk for adjuvant therapy.

Impact of pretreatment body mass index on clinical outcomes in patients with metastatic renal cell carcinoma receiving first-line immune checkpoint inhibitor-based therapy: A systematic review and meta-analysis.

This study aimed to assess the prognostic role of body mass index (BMI) in patients with metastatic renal cell carcinoma (mRCC) treated with first-line immune checkpoint inhibitor (ICI)-based therapy. We searched for relevant studies in the MEDLINE, Embase, and Cochrane Library databases. The initial search yielded 599 records, of which seven articles (2,517 patients) were selected for analysis. Patients with a high BMI had a favorable overall survival (OS) based on hazard ratio (HR) (crude HR 0.69, 95% confidence interval [CI] 0.57-0.83, p<0.0001; adjusted (a)HR 0.75, 95% CI 0.59-0.95, p=0.02), but not relative risk (RR 0.88, 95% CI 0.67-1.16, p=0.37). In the subgroup analysis, patients with a high BMI had better OS in the ICI with tyrosine kinase inhibitor (TKI) subgroup (aHR 0.71, 95% CI 0.55-0.92, p=0.01), while no significant difference was found in the ICI-only subgroup (aHR 1.02, 95% CI 0.56-1.87, p=0.95). Adjusted statistics for progression-free survival (PFS) were assessable in predominantly ICI-only studies and demonstrated a favorable outcome for patients with a low BMI (aHR 1.67, 95% CI 1.14-2.45, p=0.01). In conclusion, the impact of high BMI varies depending on the treatment type, exhibiting a favorable correlation with OS within ICI with TKI subgroup, but indicating an adverse association with PFS in the ICI-only subgroup. Further research is needed to clarify the influence of BMI by stratifying patients into ICI-only and ICI with TKI treatment to provide more insights.

Adjuvant therapy in renal cell carcinoma: Tyrosine kinase inhibitor versus immune checkpoint inhibitor.

BACKGROUND: To date, no meta-analysis has been conducted to compare the effectiveness and safety of adjuvant tyrosine kinase inhibitors (TKIs) and adjuvant immunotherapies (IMTs) in renal cell carcinoma (RCC) patients using reconstructed individual patient data (IPD). This study aims to fill that gap by assessing the efficacy and safety profiles of these treatments in such patients. METHODS: This study employed a systematic approach for identifying relevant literature from the PubMed and EMBASE databases. We included articles published in English from the inception of these databases until November 11, 2023, focusing specifically on appropriate phase III randomized controlled trials (RCTs). To reconstruct survival curves, we utilized a semiautomated tool, WebPlotDigitizer, in conjunction with a novel shiny application integrated with R software. For adverse events (AEs), the summary measures were incidences, expressed as a 95% confidence interval (CI), calculated using a random-effects model with a logit transformation. RESULTS: The analysis included 8 RCTs with a total of 9119 patients. Compared to adjuvant TKIs, adjuvant IMTs showed a similar disease-free survival (DFS) (hazard ratio [HR] 1.03, 95% CI [0.98-1.09], P = .281). However, the overall survival (OS) rates between the 2 groups couldn't be directly compared due to unmatched control groups in the IMT and TKI studies. Against placebo, adjuvant IMTs demonstrated superior DFS (HR 0.82, 95% CI [0.71-0.94], P = .004) but comparable OS (HR 0.79, 95% CI [0.59-1.06], P = .120). Against placebo, adjuvant TKIs showed superior DFS (HR 0.85, 95% CI [0.79-0.92], P < .0001) and marginally better OS (HR 0.89, 95% CI [0.80-0.996], P = .042). Regarding severe AEs and discontinuation rates due to AEs, adjuvant IMTs had a significantly lower incidence of severe AEs (25% [320/1282] vs 59% [2192/3716], odds ratio [OR] 0.23, 95% CI [0.20-0.27], P < .0001) and a markedly better discontinuation rate (39% [499/1282] vs 52% [2068/4018], OR 0.60, 95% CI [0.53-0.68], P < .0001) compared to TKIs. CONCLUSION: This paper presents a thorough analysis of DFS, OS, and treatment-related AEs across various groups in RCC patients, offering a valuable resource for clinicians in everyday practice. Our findings indicate that while adjuvant IMTs and adjuvant TKIs demonstrate similar DFS, IMTs are notably superior in terms of safety and compliance.

Identification of a novel PANoptosis-related gene signature for predicting the prognosis in clear cell renal cell carcinoma.

PANoptosis has been shown to play an important role in tumorigenesis and gain more attention. Yet, the prognostic significance of PANoptosis-related genes has not been investigated more in clear cell renal cell carcinoma (ccRCC). The aim of this research was designed to identify and create a signature of PANoptosis-related genes which was expected to predict prognosis of ccRCC more effectively. The transcriptome data and clinical information were collected from The Cancer Genome Atlas database and the Gene Expression Omnibus database. Optimal differentially expressed PANoptosis-related genes, which were closely associated with prognosis and employed to construct a risk score, were extracted by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression and multivariate Cox analysis. We performed Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curves to complete this process. By adopting univariate and multivariate analysis, the constructed risk score was assessed to verify whether it could be taken as an independent contributor for prognosis. Moreover, we created a nomogram in order to predict overall survival (OS) of ccRCC. Five differentially expressed PANoptosis-related genes were screened out and used to construct a risk score. Our results showed that ccRCC patients with high risk score had a poor prognosis and shorter OS. The results of Kaplan-Meier curves and the area under the receiver operating characteristic curves of 1-, 3-, and 5-year OS indicated that the prediction performance was satisfactory. Additionally, the risk model could be taken as an independent prognostic factor in training and validation cohorts. The nomogram exhibited excellent reliability in predicting OS, which was validated by calibration curves. We identified 5 PANoptosis-related genes, which were used to construct a risk score and a nomogram for prognostic prediction with reliable predictive capability. The present study may provide new potential therapeutic targets and precise treatment strategies for ccRCC.

Transcriptome analysis revealed a novel nine-gene prognostic risk score of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) continues to pose a significant global health concern, with rising incidence and high mortality rate. Accordingly, identifying molecular alternations associated with ccRCC is crucial to boost our understanding of its onset, persistence, and progression as well as developing prognostic biomarkers and novel therapies. Bulk RNA sequencing data and its associated clinicopathological variables of ccRCC were obtained from The Cancer Genome Atlas Program. Atypical differential gene expression analysis of advanced disease states using the extreme categories of staging and grading components was performed. Upregulated differentially expressed genes shared across the aforementioned components were selected. The risk-score construction pipeline started with univariate Cox logistic regression analysis, least absolute shrinkage and selection operator, and multivariate Cox logistic regression analysis in sequence. The generated risk score classified patients into low- vs high-risk groups. The predictive power of the constructed risk score was assessed using Kaplan-Meier curves analysis, multivariate Cox logistic regression analysis, and receiver operator curve of the overall survival. External validation of the risk score was performed using the E-MTAB-1980 cohort. The analysis work scheme established a novel nine-gene prognostic risk score composed of the following genes: ZIC2, TNNT1, SAA1, OTX1, C20orf141, CDHR4, HOXB13, IGFL2, and IGFN1. The high-risk group was associated with shortened overall survival and possessed an independent predictive power (hazard ratio: 1.942, 95% CI: 1.367-2.758, P < .0001, area under the curve = 0.719). In addition, the high-risk score was associated with advance clinicopathological parameters. The same pattern was observed within the external validation dataset (E-MTAB-1980 cohort), in which the high-risk score held a poor prognostic signature as well as independent predictive potential (hazard ratio: 5.121, 95% CI: 1.412-18.568, P = .013, area under the curve = 0.787). In the present work, a novel nine-gene prognostic risk score was constructed and validated. The risk score correlated with tumor immune microenvironment, somatic mutation patterns, and altered molecular pathways involved in tumorigenesis. Further experimental data are warranted to expand the work.

Clinical features and response to immune combinations in patients with renal cell carcinoma and sarcomatoid de-differentiation (ARON-1 study).

Metastatic renal cell carcinoma (mRCC) carrying sarcomatoid features (sRCC) has aggressive biology and poor prognosis. First-line immunotherapy (IO)-based combinations have improved the outcome of clear cell RCC patients, including that of sRCC. Real-world data confirming the adequate first-line management of sRCC is largely lacking. We investigated the clinical features and the outcome of sRCC patients treated with IO-based combinations within the ARON-1 study population (NCT05287464). The primary objective was to define the incidence and baseline clinical characteristics of sRCC compared with non-sRCC patients. The secondary objective was to describe the outcome of sRCC patients based on type of first-line treatment (IO + IO vs. IO + tyrosin kinase inhibitor [TKI]). We identified 1362 mRCC patients with IMDC intermediate or poor risk, 226 sRCC and 1136 non-sRCC. These two subgroups did not differ in terms of baseline characteristics. The median overall survival (OS) was 26.8 months (95%CI 21.6-44.2) in sRCC and 35.3 months (95%CI 30.2-40.4) in non-sRCC patients (p = .013). The median progression-free survival (PFS) was longer in non-sRCC patients compared to sRCC (14.5 vs. 12.3 months, p = .064). In patients treated with first-line IO + TKI the median OS was 34.4 months compared to 26.4 months of those who received IO + IO (p = .729). The median PFS was 12.4 months with IO + TKI and 12.3 months with IO + IO (p = .606). In conclusion, we confirm that sRCC are aggressive tumors with poor prognosis. IO-based combinations improve survival outcomes of sRCC patients, regardless from the type of strategy (IO + IO versus IO + TKI) adopted.

Global burden of benign prostatic hyperplasia, urinary tract infections, urolithiasis, bladder cancer, kidney cancer, and prostate cancer from 1990 to 2021.

BACKGROUND: The burden of common urologic diseases, including benign prostatic hyperplasia (BPH), urinary tract infections (UTI), urolithiasis, bladder cancer, kidney cancer, and prostate cancer, varies both geographically and within specific regions. It is essential to conduct a comprehensive and precise assessment of the global burden of urologic diseases. METHODS: We obtained data on incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) for the aforementioned urologic diseases by age, sex, location, and year from the Global Burden of Disease (GBD) 2021. We analyzed the burden associated with urologic diseases based on socio-demographic index (SDI) and attributable risk factors. The trends in burden over time were assessed using estimated annual percentage changes (EAPC) along with a 95% confidence interval (CI). RESULTS: In 2021, BPH and UTI were the leading causes of age-standardized incidence rate (ASIR) and age-standardized prevalence rate (ASPR), with rates of 5531.88 and 2782.59 per 100,000 persons, respectively. Prostate cancer was the leading cause of both age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR), with rates of 12.63 and 217.83 per 100,000 persons, respectively. From 1990 to 2021, there was an upward trend in ASIR, ASPR, ASMR, and ASDR for UTI, while urolithiasis showed a downward trend. The middle and low-middle SDI quintile levels exhibited higher incidence, prevalence, mortality, and DALYs related to UTI, urolithiasis, and BPH, while the high and high-middle SDI quintile levels showed higher rates for the three cancers. The burden of these six urologic diseases displayed diverse age and sex distribution patterns. In 2021, a high body mass index (BMI) contributed to 20.07% of kidney cancer deaths worldwide, while smoking accounted for 26.48% of bladder cancer deaths and 3.00% of prostate cancer deaths. CONCLUSIONS: The global burden of 6 urologic diseases presents a significant public health challenge. Urgent international collaboration is essential to advance the improvement of urologic disease management, encompassing the development of effective diagnostic screening tools and the implementation of high-quality prevention and treatment strategies.

Effect of radiation after surgery on the prognosis of children with Wilms tumor.

BACKGROUND: To explore the association between radiation after surgery and the 5-year overall survival (OS) and 5-year cancer-specific survival (CSS) in patients with Wilms tumor. METHODS: In this cohort study, 1564 participants were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The univariate and multivariable COX proportional risk model as well as competitive risk model were used to explore the covariates associated with 5-year OS and 5-year CSS of patients with Wilms tumor and the correlation between radiation after surgery and 5-year OS or 5-year CSS of patients with Wilms tumor, respectively. The Kaplan-Meier curves of participants were plotted. RESULTS: The median follow-up was 126.00 (84.00, 178.00) months. Patients receiving surgery had higher 5-year survival probability than those not receiving surgery, while participants receiving radiation after surgery showed poor 5-year survival than those not. After adjusting for covariates including age and SEER stage, increased risk of 5-year overall mortality in patients with Wilms tumor [hazard ratio (HR) = 1.62, 95% confidence interval (CI): 1.10-2.41). After the adjustment for confounding factors including age, SEER stage and ethnicity, increased risk of 5-year cancer-specific mortality of patients with Wilms tumor was observed in those receiving radiation after surgery (HR = 1.77, 95%CI: 1.13-2.79). CONCLUSION: Radiation after surgery was associated with poor prognosis of patients with Wilms tumor, which indicated that the clinicians should assess whether the patient was suitable for using radiation after surgery.

Temporary treatment cessation compared with continuation of tyrosine kinase inhibitors for adults with renal cancer: the STAR non-inferiority RCT.

Background: There is interest in using treatment breaks in oncology, to reduce toxicity without compromising efficacy. Trial design: A Phase II/III multicentre, open-label, parallel-group, randomised controlled non-inferiority trial assessing treatment breaks in patients with renal cell carcinoma. Methods: Patients with locally advanced or metastatic renal cell carcinoma, starting tyrosine kinase inhibitor as first-line treatment at United Kingdom National Health Service hospitals. Interventions: At trial entry, patients were randomised (1 : 1) to a drug-free interval strategy or a conventional continuation strategy. After 24 weeks of treatment with sunitinib/pazopanib, drug-free interval strategy patients took up a treatment break until disease progression with additional breaks dependent on disease response and patient choice. Conventional continuation strategy patients continued on treatment. Both trial strategies continued until treatment intolerance, disease progression on treatment, withdrawal or death. Objective: To determine if a drug-free interval strategy is non-inferior to a conventional continuation strategy in terms of the co-primary outcomes of overall survival and quality-adjusted life-years. Co-primary outcomes: For non-inferiority to be concluded, a margin of ≤ 7.5% in overall survival and ≤ 10% in quality-adjusted life-years was required in both intention-to-treat and per-protocol analyses. This equated to the 95% confidence interval of the estimates being above 0.812 and -0.156, respectively. Quality-adjusted life-years were calculated using the utility index of the EuroQol-5 Dimensions questionnaire. Results: Nine hundred and twenty patients were randomised (461 conventional continuation strategy vs. 459 drug-free interval strategy) from 13 January 2012 to 12 September 2017. Trial treatment and follow-up stopped on 31 December 2020. Four hundred and eighty-eight (53.0%) patients [240 (52.1%) vs. 248 (54.0%)] continued on trial post week 24. The median treatment-break length was 87 days. Nine hundred and nineteen patients were included in the intention-to-treat analysis (461 vs. 458) and 871 patients in the per-protocol analysis (453 vs. 418). For overall survival, non-inferiority was concluded in the intention-to-treat analysis but not in the per-protocol analysis [hazard ratio (95% confidence interval) intention to treat 0.97 (0.83 to 1.12); per-protocol 0.94 (0.80 to 1.09) non-inferiority margin: 95% confidence interval ≥ 0.812, intention to treat: 0.83 > 0.812 non-inferior, per-protocol: 0.80 < 0.812 not non-inferior]. Therefore, a drug-free interval strategy was not concluded to be non-inferior to a conventional continuation strategy in terms of overall survival. For quality-adjusted life-years, non-inferiority was concluded in both the intention-to-treat and per-protocol analyses [marginal effect (95% confidence interval) intention to treat -0.05 (-0.15 to 0.05); per-protocol 0.04 (-0.14 to 0.21) non-inferiority margin: 95% confidence interval ≥ -0.156]. Therefore, a drug-free interval strategy was concluded to be non-inferior to a conventional continuation strategy in terms of quality-adjusted life-years. Limitations: The main limitation of the study is the fewer than expected overall survival events, resulting in lower power for the non-inferiority comparison. Future work: Future studies should investigate treatment breaks with more contemporary treatments for renal cell carcinoma. Conclusions: Non-inferiority was shown for the quality-adjusted life-year end point but not for overall survival as pre-defined. Nevertheless, despite not meeting the primary end point of non-inferiority as per protocol, the study suggested that a treatment-break strategy may not meaningfully reduce life expectancy, does not reduce quality of life and has economic benefits. Although the treating clinicians' perspectives were not formally collected, the fact that clinicians recruited a large number of patients over a long period suggests support for the study and provides clear evidence that a treatment-break strategy for patients with renal cell carcinoma receiving tyrosine kinase inhibitor therapy is feasible. Trial registration: This trial is registered as ISRCTN06473203. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment Programme (NIHR award ref: 09/91/21) and is published in full in Health Technology Assessment; Vol. 28, No. 45. See the NIHR Funding and Awards website for further award information.

Treatment breaks in cancer are of significant interest to patients and health professionals. Renal cell carcinoma is the most common type of kidney cancer. Sunitinib and pazopanib are both targeted treatments. They were commonly used to treat advanced kidney cancer but often cause side effects, sometimes requiring use of a reduced dose or even stopping treatment. The STAR trial was designed to see whether planned treatment breaks made patients with advanced kidney cancer being treated with sunitinib and pazopanib feel better, without substantially affecting how well the treatment worked. After 24 weeks of treatment, patients took sunitinib and pazopanib either as they normally would or in the alternative way with planned treatment breaks. Treating patients in this way was continued until drug-related side effects stopped treatment, patients' disease worsened while taking treatment or the patient died. The trial compared how well the different treatment strategies worked in terms of how long patients lived and their quality of life over that time. This trial is the largest United Kingdom trial in advanced renal cell carcinoma. Patients took part from 60 United Kingdom centres between 2012 and 2017. It was funded by the National Institute for Health and Care Research Health Technology Assessment Programme and run by the Leeds Clinical Trials Research Unit. In total, 920 patients took part. Four hundred and sixty-one patients were allocated to continue treatment and 459 were allocated to start at least one treatment break. Treatment breaks lasted on average 87 days. The length of time patients lived in both arms of the trial appeared similar, but this cannot be concluded due to insufficient information. Being allocated to have treatment breaks rather than continuing treatment did not negatively impact a patient's quality of life. Additionally, allocating patients to have treatment breaks was shown to have significant cost savings compared to just continuing treatment. Importantly planned treatment breaks were shown to be feasible.

Radiomics predicts the prognosis of patients with clear cell renal cell carcinoma by reflecting the tumor heterogeneity and microenvironment.

PURPOSE: We aimed to develop and externally validate a CT-based deep learning radiomics model for predicting overall survival (OS) in clear cell renal cell carcinoma (ccRCC) patients, and investigate the association of radiomics with tumor heterogeneity and microenvironment. METHODS: The clinicopathological data and contrast-enhanced CT images of 512 ccRCC patients from three institutions were collected. A total of 3566 deep learning radiomics features were extracted from 3D regions of interest. We generated the deep learning radiomics score (DLRS), and validated this score using an external cohort from TCIA. Patients were divided into high and low-score groups by the DLRS. Sequencing data from the corresponding TCGA cohort were used to reveal the differences of tumor heterogeneity and microenvironment between different radiomics score groups. What's more, univariate and multivariate Cox regression were used to identify independent risk factors of poor OS after operation. A combined model was developed by incorporating the DLRS and clinicopathological features. The SHapley Additive exPlanation method was used for interpretation of predictive results. RESULTS: At multivariate Cox regression analysis, the DLRS was identified as an independent risk factor of poor OS. The genomic landscape of different radiomics score groups was investigated. The heterogeneity of tumor cell and tumor microenvironment significantly varied between both groups. In the test cohort, the combined model had a great predictive performance, with AUCs (95%CI) for 1, 3 and 5-year OS of 0.879(0.868-0.931), 0.854(0.819-0.899) and 0.831(0.813-0.868), respectively. There was a significant difference in survival time between different groups stratified by the combined model. This model showed great discrimination and calibration, outperforming the existing prognostic models (all p values < 0.05). CONCLUSION: The combined model allowed for the prognostic prediction of ccRCC patients by incorporating the DLRS and significant clinicopathologic features. The radiomics features could reflect the tumor heterogeneity and microenvironment.

Prognostic significance of immune evasion-related genes in clear cell renal cell carcinoma immunotherapy.

Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignancy of the urinary system. Despite the integration of immune checkpoint inhibitors (ICIs) into the treatment paradigm for advanced RCC, resistance to immunotherapy has emerged as a pivotal determinant impacting the clinical outlook of ccRCC. Accumulating evidence underscores the pivotal role of immune evasion-related genes and pathways in enabling tumor escape from host immune surveillance, consequently influencing patients' responsiveness to immunotherapy. Nonetheless, the clinical relevance of immune evasion-related genes in ccRCC patients undergoing immunotherapy remains inadequately understood. In this study, we aggregated RNA sequencing and clinical data from ccRCC patients across three cohorts: the Cancer Genome Atlas (TCGA), CheckMate cohorts, and the JAVELIN Renal 101 trial. Leveraging a curated immune evasion-related gene set from Lawson et al., we employed the LASSO algorithm and Cox regression analysis to identify eight genes (LPAR6, RGS5, NFYC, PCDH17, CENPW, CNOT8, FOXO3, SNRPB) significantly associated with immune therapy prognosis (HR, 3.57; 95 % CI, 2.38-5.35; P<0.001). A predictive algorithm developed utilizing these genes exhibited notable accuracy in forecasting patients' progression-free survival in the training set (AUC, 0.835). Furthermore, stratification of patients by risk score revealed discernible differences in immunotherapy response and tumor microenvironment. In summary, we present a prognostic model intricately linked with immune status and treatment response. For ccRCC patients undergoing immunotherapy, this approach holds promise in aiding clinical decision-making by providing more precise and tailored treatment recommendations.

Clinical application of radiomics for the prediction of treatment outcome and survival in patients with renal cell carcinoma: a systematic review.

PURPOSE: The management of renal cell carcinoma (RCC) relies on clinical and histopathological features for treatment decisions. Recently, radiomics, which involves the extraction and analysis of quantitative imaging features, has shown promise in improving RCC management. This review evaluates the current application and limitations of radiomics for predicting treatment and oncological outcomes in RCC. METHODS: A systematic search was conducted in Medline, EMBASE, and Web of Science databases or studies that used radiomics to predict response to treatment and survival outcomes in patients with RCC. The study quality was assessed using the Radiomics Quality Score (RQS) tools. RESULTS: The systematic review identified a total of 27 studies, examining 6,119 patients. The most used imaging modality was contrast-enhanced abdominal CT. The reviewed studies extracted between 19 and 3376 radiomics features, including Histogram, Texture, Filter, or transformation method. Radiomics-based risk stratification models provided valuable insights into treatment response and oncological outcomes. All developed signatures demonstrated at least modest accuracy (AUC range: 0.55-0.99). The studies included in this analysis reported heterogeneous results regarding radiomics methods. The range of Radiomics Quality Score (RQS) was from - 5 to 20, with a mean RQS total of 9.15 ± 7.95. CONCLUSION: Radiomics has emerged as a promising tool in the management of RCC. It offers the potential for improved risk stratification and response assessment. However, future trials must demonstrate the generalizability of findings to prospective cohorts before progressing towards clinical translation.

A systematic investigation of clear cell renal cell carcinoma using meta-analysis and systems biology approaches.

Renal cell carcinoma with clear cells (ccRCC) is the most frequent kind; it accounts for almost 70% of all kidney cancers. A primary objective of current research was to find genes that may be used in ccRCC gene therapy to understand better the molecular pathways underlying the disease. Based on PubMed microarray searches and meta-analyses, we compared overall survival and recurrence-free survival rates in ccRCC patients with those in healthy samples. The technique was followed by a KEGG pathway and Gene Ontology (GO) function analyses, both performed in conjunction with the approach. Tumor immune estimate and multi-gene biomarkers validation for clinical outcomes were performed at the molecular and clinical cohort levels. Our analysis included fourteen GEO datasets based on inclusion and exclusion criteria. A meta-analysis procedure, network construction using PPIs, and four significant gene identification standard algorithms indicated that 11 genes had the most important differences. Ten genes were upregulated, and one was downregulated in the study. In order to analyze RFS and OS survival rates, 11 genes expressed in the GEPIA2 database were examined. Nearly nine of eleven significant genes have been found to beinvolved in tumor immunity. Furthermore, it was found that mRNA expression levels of these genes were significantly correlated with experimental literature studies on ccRCCs, which explained these findings. This study identified eleven gene panels associated with ccRCC growth and metastasis, as well as their immune system infiltration.

Understanding m6A changes in chromophobe renal cell carcinoma and predicting patient outcomes survival.

N6-methyladenosine (m6A) is a prevalent mRNA modification known for its implications in various cancer types, yet its role in chromophobe renal cell carcinoma (chRCC) remains largely unexplored. In this study, we performed m6A-SEAL-seq and RNA-seq analyses on tissues from three chRCC subjects, aiming to uncover m6A alterations in chRCC. Our findings revealed reduced expression levels of four m6A regulators in chRCC tissues and highlighted differences in m6A levels compared to normal tissues. Furthermore, we identified specific genes and cancer-related pathways affected by these differences, including notable candidates like NOTCH1 and FGFR1, implicated in chRCC development. Additionally, we developed a predictive model based on the expression level of m6A associated genes, demonstrating promising prognostic capabilities for patient survival prediction. Overall, our study provides valuable insights into the role of m6A in chRCC and its potential as a prognostic indicator.