High-risk ccRCC Research Articles

Oncologic surveillance after surgical treatment for clinically localized kidney cancer: UroCCR study n. 129.

In 2021, the EAU Guidelines implemented a novel, expert opinion-based follow-up scheme, with a three-risk-category system for clear cell (cc) and non-cc renal cell carcinoma (non-ccRCC) after surgery with curative intent. We aimed to validate the novel follow-up scheme and provide data-driven recurrence estimates according to risk groups, to confirm or implement the oncologic surveillance strategy. We identified 5,320 patients from a prospectively maintained database involving 28 French referral centers. The risk of recurrence, as either loco-regional or distant, was evaluated with the Kaplan-Meier method for each group (low- intermediate- or high-risk) according to ccRCC or non-ccRCC histology. The noncumulative distribution of recurrences was graphically investigated through the LOWESS smoother. Two thousand two hundred ninety-three (58%), 926 (23%), and 738 (19%) had low-, intermediate, and high-risk ccRCC, and 683 (50%), 297 (22%), and 383 (28%) had low-, intermediate, and high-risk non-ccRCC, respectively. Median follow-up for survivors was 46 months. Overall, 661 patients experienced recurrence. Over time, the noncumulative risk of recurrence was approximately 10% for low-risk cc-RCC, non-ccRCC, and intermediate-risk non-ccRCC, with non-significant difference among the three recurrence functions (P=0.9). At 5-year, time point after which imaging should be de-intensified to biennial, the noncumulative risks of recurrence were: for intermediate risk ccRCC and non-ccRCC: 15% and 11%, respectively; for high-risk ccRCC and non-ccRCC: 24% and 8%, respectively. Among high-risk non-ccRCC patients there were 9 recurrences at 3-month. There was no significant difference between the recurrence function of high-risk non-ccRCC patients with negative imaging at 3-month and the one of intermediate-risk ccRCC (P=0.3). Given the relatively low recurrence risk of patients with intermediate-risk non-ccRCC, those individuals could be followed up with a similar strategy to the low-risk category. Similarly, patients with high-risk non-ccRCC with negative imaging at 3-month, could be followed up similarly to intermediate-risk ccRCC after the 3-month time point.

Establishment of a prognostic signature of disulfidptosis-related lncRNAs for predicting survival and immune landscape in clear cell renal cell carcinoma

Abstract Objectives A novel cell death pathway, disulfidptosis, marked by intracellular disulfide build-up, is a recently identified form of cell death. This study developed a dependable model using disulfidptosis-associated lncRNAs to predict outcomes and immune interactions in clear cell renal cell carcinoma (ccRCC) patients. Methods Data from ccRCC patients, including genomic and clinicopathological details, were sourced from The Cancer Genome Atlas database. We employed the least absolute shrinkage and selection operator (LASSO) along with regression analyses to construct a prognostic model consisting of 12 disulfidptosis-related lncRNAs (DRLs). The model’s validity was tested using the RECA-EU and GSE29609 datasets. Results The prognostic model, incorporating 12 DRLs – LINC01671, DOCK9-DT, AL078581.2, SPINT1-AS1, ZNF503-AS1, AL391883.1, AC002070.1, AP001372.2, AC068338.3, AC026401.3, AL355835.1, and AL162377.1 – distinguished high-risk ccRCC patients with diminished survival rates in both the training and validation cohorts. Further analyses through Cox regression confirmed this risk model’s independent prognostic capability regarding overall survival (OS). Functional enrichment analysis indicated significant involvement of differentially expressed genes in immune response mediator production. A prognostic nomogram, integrating DRLs with clinical features, showed strong predictive accuracy as confirmed by receiver operating characteristic curves. Additionally, assessments of immune functionality and tumor mutation burden varied across risk categories in the tumor microenvironment, highlighting potential targets for anticancer drugs. Conclusions The findings suggest the DRLs signature is a potent prognostic indicator and may serve to forecast responses to immunotherapy in ccRCC patients.

Immunomodulatory response to neoadjuvant nivolumab in non-metastatic clear cell renal cell carcinoma

Novel perioperative strategies are needed to reduce recurrence rates in patients undergoing nephrectomy for high-risk, non-metastatic clear cell renal cell carcinoma (ccRCC). We conducted a prospective, phase I trial of neoadjuvant nivolumab prior to nephrectomy in 15 evaluable patients with non-metastatic ccRCC. We leveraged tissue from that cohort to elucidate the effects of PD-1 inhibition on immune cell populations in ccRCC and correlate the evolving immune milieu with anti-PD-1 response. We found that nivolumab durably induces a pro-inflammatory state within the primary tumor, and baseline immune infiltration within the primary tumor correlates with nivolumab responsiveness. Nivolumab increases CTLA-4 expression in the primary tumor, and subsequent nephrectomy increases circulating concentrations of sPD-L1, sPD-L3 (sB7-H3), and s4-1BB. These findings form the basis to consider neoadjuvant immune checkpoint inhibition (ICI) for high-risk ccRCC while the tumor remains in situ and provide the rationale for perioperative strategies of novel ICI combinations.

Post-Metastasectomy Adjuvant Therapy in Patients with Renal Cell Carcinoma: A Systematic Review.

Pembrolizumab is established as adjuvant therapy for patients with high-risk clear cell renal cell carcinoma (ccRCC) after resection. Patients with completely resected metastatic disease (M1 NED) seem to have greater benefit from adjuvant pembrolizumab in both disease-free survival (DFS) and overall survival (OS); yet, with other agents, adjuvant therapy has not been shown to improve survival. As newer therapies evolve, it is important to understand the efficacy of systemic agents in this patient population. We aimed to systematically review available trials investigating adjuvant therapy after metastasectomy in RCC. Following PRISMA guidelines, we performed a systematic literature search using PubMed and Embase through January 2024. For inclusion, studies were required to include completely resected patients with known metastatic RCC. Patients with only locally advanced and/or regional nodal involvement (N1) alone were excluded. Titles and abstracts were screened to identify articles for full-text, and then a descriptive review was performed. A total of 149 articles were initially identified. Ultimately 9 articles published before the end of January 2024 met our inclusion criteria and were included in the analysis. Data were extracted and organized to reflect the role of adjuvant treatment - both targeted therapies as well as immunotherapy in patients who had undergone metastasectomy and rendered M1 NED. With the exception of pembrolizumab, adjuvant therapy in M1 NED was not found to be associated with improved survival. Pembrolizumab appears to benefit M1 NED ccRCC patients after resection even more than other high-risk ccRCC patients. Yet, this same benefit has not been seen with other agents. Future research should focus on trying to establish which M1 NED patients benefit from adjuvant treatment.

High risk clear cell renal cell carcinoma microenvironments contain protumour immunophenotypes lacking specific immune checkpoints

Perioperative immune checkpoint inhibitor (ICI) trials for intermediate high-risk clear cell renal cell carcinoma (ccRCC) have failed to consistently demonstrate improved patient outcomes. These unsuccessful ICI trials suggest that the tumour infiltrating immunophenotypes, termed here as the immune cell types, states and their spatial location within the tumour microenvironment (TME), were unfavourable for ICI treatment. Defining the tumour infiltrating immune cells may assist with the identification of predictive immunophenotypes within the TME that are favourable for ICI treatment. To define the immunophenotypes within the ccRCC TME, fresh para-tumour (pTME, n = 2), low-grade (LG, n = 4, G1-G2) and high-grade (HG, n = 4, G3-G4) tissue samples from six patients with ccRCC presenting at a tertiary referral hospital underwent spatial transcriptomics sequencing (ST-seq). Within the generated ST-seq datasets, immune cell types and states, termed here as exhausted/pro-tumour state or non-exhausted/anti-tumour state, were identified using multiple publicly available single-cell RNA and T-cell receptor sequencing datasets as references. HG TMEs revealed abundant exhausted/pro-tumour immune cells with no consistent increase in expression of PD-1, PD-L1 and CTLA4 checkpoints and angiogenic genes. Additional HG TME immunophenotype characteristics included: pro-tumour tissue-resident monocytes with consistently increased expression of HAVCR2 and LAG3 checkpoints; an exhausted CD8+ T cells sub-population with stem-like progenitor gene expression; and pro-tumour tumour-associated macrophages and monocytes within the recurrent TME with the expression of TREM2. Whilst limited by a modest sample size, this study represents the largest ST-seq dataset on human ccRCC. Our study reveals that high-risk ccRCC TMEs are infiltrated by exhausted/pro-tumour immunophenotypes lacking specific checkpoint gene expression confirming that HG ccRCC TME are immunogenic but not ICI favourable.

Adjuvant therapy for renal cell carcinoma in 2023: hopes and disappointments.

It is known that 30% of clear cell renal cell carcinomas (ccRCC) will develop progressive disease after surgical treatment. These patients with high-risk ccRCC require adjuvant therapy after nephrectomy or resection of metastases. The article presents an overview of the results of recent studies in adjuvant therapy. We analyzed the results of randomized trials of targeted therapy and checkpoint inhibitors in high-risk ccRCC patients. Targeted therapy did not significantly reduce this risk or/and did not affect overall survival. Three randomized studies investigating nivolumab, ipilimumab, and atezolizumab in the adjuvant setting also failed without improving disease-free survival. Pembrolizumab had a significant impact on the disease-free survival in the entire population, with the greatest effect in patients after metastasectomy, but mature overall survival data are not yet available. In conclusion, it must be noted that, at present, it has not been possible to achieve magnificent success in adjuvant therapy of RCC in patients at high risk of relapse after surgical treatment. There remains hope for adjuvant pembrolizumab, which has been used for high-risk population including patients with removed metastases who may benefit more from therapy.

PD24-11 HOT CLEAR CELL RENAL CELL CARCINOMA IMMUNE STATUS: ILLUSION OR REALITY?

You have accessJournal of UrologyCME1 Apr 2023PD24-11 HOT CLEAR CELL RENAL CELL CARCINOMA IMMUNE STATUS: ILLUSION OR REALITY? Yi Lu and Hongjun Li Yi LuYi Lu More articles by this author and Hongjun LiHongjun Li More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003302.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The drivers and resistors of the anti-tumor response remain incompletely elucidated. High tumor mutation burden (TMB) and increased infiltration by T cells are associated with the answer to immune checkpoint inhibitors ICIs. We conducted the bioinfomatic study to better understand immunotherapy resistance in clear cell renal cell carcinoma (ccRCC). METHODS: The patients and sequencing data were selected from The Cancer Genome Atlas KIRC (TCGA-KIRC), and a clinical trial dataset. To classify worse-survival ccRCC resistant to immunotherapy, immune prognosis model (IPM) risk score classifier was constructed with prognostic costimulatory molecule genes through survival analysis and validated as well. For function analysis, ESTIMATE, ImmuCellAI, TIDE, and Gene Oncology (GO) were used. RESULTS: The 366 Co-expressed genes (CEGs) correlated with IPM risk score were enriched with p<0.05 and correlation |R-value|>0.5. GO analysis indicated CEGs were enriched within immune-associated gene sets, such as T cell homeostasis. TIDE algorithm predicted all the patients' response to ICIs, and non-responders were enriched in higher IPM risk scores and a real-world ICIs-treated ccRCC cohort validated it with a consistent finding with p=0.028 in chi-square test. ESTIMATE algorithm showed the ESTIMATE, and immune scores of high-risk patients, markedly increased compared with low-risk patients. Nevertheless, tumor purity was thinner than low-risk patients. Besides, TMB and cytolytic activity were higher in high-risk patients. ImmuCellAI algorithm revealed the levels of CD8+ T cells, CD4+ T cells, dendritic cells, and MAIT, together with macrophages, increased in the tumor microenvironment of high-risk patients. The TIDE T cell function estimate was used to test the T cell dysfunction of high-risk patients, which was markedly worse compared with low-risk patients. Meanwhile, immune inhibiting cells, namely exhausted T cells, nTreg cells, iTreg cells, and cancer associated fibroblast (CAF), had an increased fraction in high-risk ccRCC. Remarkably, the microsatellite instability (MSI) score was lower in high-risk ccRCC. Interestingly, IPM risk level was independent from MSI level in prognostic influence. CONCLUSIONS: We found a subtype of refractory ccRCC (IPM high risk), and subsequent function analysis indicated the reason for its insensitivity to immune blockades was T cell dysfunction. In IPM high-risk ccRCC, T cells' high infiltration, hot immune status, is an illusion. The reality is the increased infiltration of dysfunctional CD8+ and CD4+ T cells, immunosuppressive cells (i.e., iT-regs, nT-regs, and CAFs) as well as low MSI. Source of Funding: This work is supported by the grant from National Population Health Science Data Sharing Service Platform Clinical Medical Science Data Center (NCMI-ABD02-201906) to Hongjun Li © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e727 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yi Lu More articles by this author Hongjun Li More articles by this author Expand All Advertisement PDF downloadLoading ...

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma.

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort. Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package "Seurat" was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the "ssGSEA" algorithm. In order to develop possible medications for patients with high-risk ccRCC, the "pRRophetic" package is employed. Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature's biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications. Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient's prognosis for ccRCC and reflect the disease's complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

Adjuvant immunotherapy for patients with renal cell carcinoma at increased risk of recurrence following resection: A National Cancer Database analysis.

649 Background: Radical nephrectomy is the standard management for locoregional renal cell carcinoma (RCC); however, patients with adverse pathological features are at increased risk of recurrence. IMmotion010 and KeyNote 564 trials investigated the adjuvant role of immune checkpoint inhibitors (ICI) for high-risk clear cell RCC (ccRCC) and have yielded conflicting results. We aimed to investigate real-world survival outcomes associated with the adjuvant use of ICI in high-risk ccRCC using the National Cancer Database Methods: In this nationwide contemporary cohort study, patients with newly diagnosed non-metastatic high-risk clear cell RCC undergoing radical nephrectomy between 2015-2019 were included. High-risk RCC was defined as cT2 with Fuhrman grade 4 or cT3a with Fuhrman grade 3/4 or cT3b/T3c/T4 with any grade, or TxN+ any grade. Patients receiving adjuvant ICI were classified as Group A and patients who did not receive adjuvant ICI were classified as Group B. Inverse probability weighting (IPW)-adjusted Kaplan Meier curves were utilized to compare overall survival (OS) between the groups and cox proportional hazard models were utilized to identify the predictors for OS. Results: Overall, 768 patients met the inclusion criteria; 270 patients in Group A and 498 patients in Group B. The mean age was 60.5(10.6) years, and 70.8% of patients were males (Table). The use of ICI in the adjuvant setting for high-risk RCC increased from 17.4% in 2015 to 61.8% in 2019. The unadjusted and IPW-adjusted Kaplan Meier 5-year overall survival was similar in the two groups [Unadjusted: 36.8% in Group A vs 50.1% in Group B, p=0.30 and adjusted: 39.5% in Group A vs 47.9% in Group B, p=0.17]. The use of adjuvant ICI did not appear to be an independent predictor for OS on multivariable cox regression analysis (HR=1.14, p=0.31) Conclusions: Adjuvant ICI therapy in non-metastatic high-risk ccRCC might not be associated with a benefit in overall survival. [Table: see text]

Immunomodulatory response to neoadjuvant nivolumab in non-metastatic clear cell renal cell carcinoma.

708 Background: Novel perioperative strategies are needed to reduce recurrence rates in patients undergoing nephrectomy for high-risk, non-metastatic clear cell renal cell carcinoma (ccRCC). We sought to (1) elucidate the effects of PD-1 inhibition on primary tumor-infiltrating and circulating immune cell populations in ccRCC and (2) correlate tumor microenvironment and circulating immune cell compositions with response to anti-PD-1 therapy. Methods: We conducted a prospective, phase I trial of neoadjuvant nivolumab prior to nephrectomy in 15 evaluable patients with non-metastatic ccRCC. We leveraged tissue from this cohort to elucidate the effects of PD-1 inhibition on immune cell populations in ccRCC and correlate the evolving immune milieu with anti-PD-1 response using fluorescence-activated cell sorting, bulk RNA sequencing with protein activity inference, and enzyme-linked immunosorbent assay for circulating cytokines. Results: We found that nivolumab durably promotes a pro-inflammatory state within the primary tumor, as evidenced by a sustained increase in the effector T cell phenotype and decreased representation of regulatory T cell subsets. Baseline immune infiltration within the primary tumor including T effector and myeloid enrichment along with angiogenic depletion correlates with nivolumab responsiveness. Nivolumab increases CTLA-4 expression in the primary tumor, and subsequent nephrectomy increases circulating concentrations of sPD-L1, sPD-L3 (sB7-H3), and s4-1BB. Conclusions: Our findings form the basis to consider neoadjuvant immune checkpoint inhibition (ICI) for high-risk ccRCC while the tumor remains in situ and provide the rationale for perioperative strategies of novel ICI combinations. Clinical trial information: NCT02575222 .

Prognostic role of the innate immune signature CD163 and "eat me" signal calreticulin in clear cell renal cell carcinoma.

The effects of the innate immune status on patients with clear cell renal cell carcinoma (ccRCC) currently remain unknown. We herein provided more extensive information about the inner landscape of immunobiology of ccRCC. In total, 260 ccRCC samples from three different cohorts consisting of 213 primary tumors and 47 metastases were obtained. We focused on five representative innate immune signatures, CD68, CD163, the "eat me" signal calreticulin, the "don't eat me" signal CD47, and signal regulatory protein α, and examined the role of each signature by quantitative immunohistochemistry. We then conducted an integrated genome mutation analysis by next-generation sequencing. Among the five markers, high CD163 and low calreticulin expression levels were prognostic in ccRCC. The application of a new risk model based on CD163 and calreticulin levels, named the innate immune risk group (high risk: high-CD163/low calreticulin, intermediate risk: high-CD163/high calreticulin or low CD163/low calreticulin, low risk: low-CD163/high calreticulin), enabled the sequential stratification of patient prognosis and malignancy. Although organ-specific differences were observed, metastases appeared to have a higher innate immune risk, particularly in the lungs, with 50% of ccRCC metastases being classified into the high-risk group according to our risk score. An analysis of genomic alterations based on the innate immune risk group revealed that alterations in the TP53/Cell cycle pathway were highly prevalent in high-risk ccRCC patients according to two innate immune signatures CD163 and calreticulin. The present results provide insights into the immune-genomic biology of ccRCC tumors for innate immunity and will contribute to future therapies focused on the innate immune system in solid cancers.

Identification and Validation of Cuproptosis-Related LncRNA Signatures in the Prognosis and Immunotherapy of Clear Cell Renal Cell Carcinoma Using Machine Learning.

(1) Objective: We aimed to mine cuproptosis-related LncRNAs with prognostic value and construct a corresponding prognostic model using machine learning. External validation of the model was performed in the ICGC database and in multiple renal cancer cell lines via qPCR. (2) Methods: TCGA and ICGC cohorts related to renal clear cell carcinoma were included. GO and KEGG analyses were conducted to determine the biological significance of differentially expressed cuproptosis-related LncRNAs (CRLRs). Machine learning (LASSO), Kaplan-Meier, and Cox analyses were conducted to determine the prognostic genes. The tumor microenvironment and tumor mutation load were further studied. TIDE and IC50 were used to evaluate the response to immunotherapy, a risk model of LncRNAs related to the cuproptosis genes was established, and the ability of this model was verified in an external independent ICGC cohort. LncRNAs were identified in normal HK-2 cells and verified in four renal cell lines via qPCR. (3) Results: We obtained 280 CRLRs and identified 66 LncRNAs included in the TCGA-KIRC cohort. Then, three hub LncRNAs (AC026401.3, FOXD2-AS1, and LASTR), which were over-expressed in the four ccRCC cell lines compared with the human renal cortex proximal tubule epithelial cell line HK-2, were identified. In the ICGC database, the expression of FOXD2-AS1 and LASTR was consistent with the qPCR and TCGA-KIRC. The results also indicated that patients with low-risk ccRCC-stratified by tumor-node metastasis stage, sex, and tumor grade-had significantly better overall survival than those with high-risk ccRCC. The predictive algorithm showed that, according to the three CRLR models, the low-risk group was more sensitive to nine target drugs (A.443654, A.770041, ABT.888, AG.014699, AMG.706, ATRA, AP.24534, axitinib, and AZ628), based on the estimated half-maximal inhibitory concentrations. In contrast, the high-risk group was more sensitive to ABT.263 and AKT inhibitors VIII and AS601245. Using the CRLR models, the correlation between the tumor immune microenvironment and cancer immunotherapy response revealed that high-risk patients are more likely to respond to immunotherapy than low-risk patients. In terms of immune marker levels, there were significant differences between the high- and low-risk groups. A high TMB score in the high-risk CRLR group was associated with worse survival, which could be a prognostic factor for KIRC. (4) Conclusions: This study elucidates the core cuproptosis-related LncRNAs, FOXD2-AS1, AC026401.3, and LASTR, in terms of potential predictive value, immunotherapeutic strategy, and outcome of ccRCC.

The 2022 Updated European Association of Urology Guidelines on the Use of Adjuvant Immune Checkpoint Inhibitor Therapy for Renal Cell Carcinoma

In KEYNOTE-564, adjuvant pembrolizumab, a PD-1 antibody, significantly improved disease-free survival (DFS) in localised clear-cell renal cell carcinoma (ccRCC) with a high risk of relapse. In 2021, the European Association of Urology RCC Guidelines Panel issued a weak recommendation for adjuvant pembrolizumab for high-risk ccRCC as defined by the trial until final overall survival data and results from other trials were available. Meanwhile, the primary DFS endpoints were not met for adjuvant atezolizumab (PD-L1 inhibitor; IMmotion010), adjuvant nivolumab plus ipilimumab (CheckMate 914), or perioperative nivolumab (PROSPER). Owing to heterogeneity, a meta-analysis is not recommended. Pembrolizumab remains the only immune checkpoint inhibitor currently recommended in this setting. Overall survival data are immature and biomarkers to predict outcome are lacking. Uncertainty exists and overtreatment is occurring. Treatment decisions should be made with caution and with the involvement of each patient. Patient summaryNew results from three trials of immunotherapy after surgery for kidney cancer to reduce the risk of recurrence showed no improvement with these treatments. These results are in contrast to an earlier study that showed that the antibody pembrolizumab did extend the time before kidney cancer recurrence, even though it is not yet clear if overall survival is longer. Thus, we cautiously recommend pembrolizumab as additional treatment in high-risk kidney cancer after surgery, but patient preference should be carefully considered and the risk of overtreatment should be discussed.

A novel inflammation-associated prognostic signature for clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) are typically situated in a complex inflammatory and immune microenvironment, which has been reported to contribute to the unfavorable prognosis of patients with ccRCC. There would be beneficial clinical implications for elucidating the roles of its molecular characteristics in the inflammatory microenvironment. This is because it would facilitate the development of reliable biomarkers for pre-stratification prior to the designation of individualized treatment strategies. In the present study, RNA-sequencing data from 607 patients were retrospectively analyzed to elucidate the profile of inflammatory molecules. Based on this, an inflammatory prognostic signature (IPS) was developed and further validated using clinical ccRCC samples. Subsequently, the associated mechanisms in terms of the immune microenvironment and molecular pathways were then investigated. This proposed IPS was found to exhibit superior accuracy compared with the criterion of a good prognostic model for the prediction of patient prognosis from ccRCC [area under the receiver operating characteristic curve (AUC)=0.811] in addition to being an independent factor for prognostic risk stratification [hazard ratio: 11.73 (95% CI, 26.98-5.10); log-rank test, P<0.001]. Pathologically, ccRCC cells identified as high-risk according to their IPS presented with a more malignant tumor structure, including voluminous eosinophilic cytoplasm, acinar/lamellar/tubular growth patterns and atypic nuclei. High-risk ccRCC also exhibited higher infiltration levels by four types of immune cells, including T regulatory cells, but lower infiltration levels by mast cells. Pathways associated with immune-inflammation interaction, including the IL-17 pathway, were found to be upregulated in IPS-identified high-risk ccRCC. Furthermore, by combining the IPS with clinical factors, an integrated prognostic index was developed and validated for increasing the accuracy of patient risk-stratification for ccRCC (AUC=0.911). In conclusion, the complex regulatory mechanisms and molecular characteristics involved in ccRCC-inflammation interaction, coupled with their prognostic potential, were systematically elucidated in the present study. This may have important implications in furthering the understanding into the molecular mechanisms underlying this ccRCC-inflammation interaction, which can in turn be exploited for identifying high-risk patients with ccRCC prior to designing their clinical treatment strategy.

Abstract 4017: Defining cell type-specific pathways in both cancer and tumor-microenvironment cells that impact survival of clear cell renal carcinoma patients

Abstract Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, with 5-year mortality of 25%. The molecular landscape of ccRCC has been elucidated by a number of next generation sequencing studies and complemented by recent global proteome and phosphoproteome results. However, a limitation of such studies is the mixture of signals from distinct cell populations, presenting challenges to subsequent interpretation. As a remedy, single nuclei RNA-seq (snRNA-seq) is able to dissect distinct cell populations and map their differential expression patterns. Using snRNA-seq from 30 ccRCC tumor samples, we identified distinct genetic pathways associated with survival in the TCGA patient cohort (525 patients) in multiple cell types, including immune and stromal components. Prognostic value of pathways was confirmed in an independent cohort with 130 patients. Multiple cancer cell-specific pathways were related to metabolism, suggesting that certain metabolites are less abundant in high-risk tumors. Using data from two independent large-scale metabolism ccRCC studies, we found metabolites’ levels changing in accordance with our predictions, when comparing low-risk to high-risk ccRCC tumors. Citation Format: Ilya Strunilin, Yige Wu, Ruiyang Liu, Wagma Caravan, Feng Chen, Li Ding. Defining cell type-specific pathways in both cancer and tumor-microenvironment cells that impact survival of clear cell renal carcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4017.

Comprehensive Analysis of the Butyrate-Metabolism-Related Gene Signature in Tumor Microenvironment-Infiltrating Immune Cells in Clear Cell Renal Cell Carcinoma.

A wealth of experimental evidence has validated that butyrate is capable of inhibiting tumorigenesis, while the potential role of butyrate metabolism in the tumor immune microenvironment (TIME) has been rarely explored. This study aims to explore the potential of butyrate-metabolism-related genes as prognostic biomarkers and their correlations with immune infiltrates in clear cell renal cell carcinoma (ccRCC) patients. Based on The Cancer Genome Atlas dataset (TCGA; n = 539), a total of 22 differentially expressed genes (DEGs) related with butyrate metabolism in ccRCC and normal samples were identified. Among them, a prognostic signature involving six butyrate-metabolism-related genes was created (Bu-Meta-GPS) in the training set (n = 271) and validation set (n = 268), and risk scores were calculated based on them. ccRCC patients with high-risk scores exhibited an unfavorable prognosis, high immunoscore, upregulated immuno-oncological targets (PD1, PD-L1, CTLA4, and CD19), and distinct immune-cell infiltration than those with low-risk scores. High-risk ccRCC patients without radiotherapy had a better survival rate than radiotherapy-treated patients. The negative regulation of cytokine production and cytokine-mediated signaling pathways was remarkably enriched in ccRCC patients with high-risk scores. A nomogram was then formulated to assess the overall survival (OS) of ccRCC patients. In summary, we illuminated the key role of butyrate metabolism in ccRCC TIME. The developed Bu-Meta-GPS was a sensitive predictive biomarker for the prognosis of ccRCC, which also provided new perspectives in improving immunotherapeutic efficacy.

2021 Updated European Association of Urology Guidelines on the Use of Adjuvant Pembrolizumab for Renal Cell Carcinoma

Adjuvant treatment of nonmetastatic high-risk renal cell carcinoma is an unmet medical need. In the past, several tyrosine kinase inhibitor trials have failed to demonstrate an improvement of disease-free survival (DFS) in this setting. Only one trial (S-TRAC) provided evidence for improved DFS with sunitinib but without an overall survival (OS) signal. Keynote-564 is the first trial of an immune checkpoint inhibitor that significantly improved DFS with adjuvant pembrolizumab, a programmed death receptor-1 antibody, in clear cell renal cell carcinoma with a high risk of relapse. The intention-to-treat population, which included a group of patients after metastasectomy and no evidence of disease (M1 NED), had a significant DFS benefit. The OS data are not mature as yet. The Renal Cell Carcinoma Guideline Panel issues a weak recommendation for the adjuvant use of pembrolizumab for high-risk clear cell renal carcinoma, as defined by the trial until final OS data are available. However, the trial reilluminates the discussion on when and in whom metastasectomy should be performed. Here, caution is necessary not to perform metastasectomy in patients with poor prognostic features and rapid progressive disease, which must be excluded by a confirmatory scan of disease status prior to planned metastasectomy. Patient summaryNew data from the adjuvant immune checkpoint inhibitor trial with pembrolizumab (a programmed death receptor-1 antibody) for the treatment of high-risk clear cell renal cell carcinoma (ccRCC) after surgery showed that the drug prolonged the period of being cancer free significantly, although whether it prolonged survival remained uncertain. Consequently, pembrolizumab is cautiously recommended as additional (ie, adjuvant) treatment in high-risk ccRCC after kidney cancer surgery.

AGAP2-AS1 as a prognostic biomarker in low-risk clear cell renal cell carcinoma patients with progressing disease

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer and one of the most common cancers. While survival for localized ccRCC is good, the survival of metastatic disease is not, and thirty percent of patients with ccRCC develop metastases during follow-up. Although current scoring methods accurately identify patients at low progression risk, a small subgroup of those patients still experience metastasis. We therefore aimed to identify ccRCC progression biomarkers in “low-risk” patients who were potentially eligible for adjuvant treatments or more intensive follow-up.MethodsWe assembled a cohort of ccRCC patients (n = 443) and identified all “low-risk” patients who later developed progressing tumors (n = 8). Subsequently, we performed genome-wide expression profiling from formalin-fixed samples obtained at initial surgery from these “low-risk” patients and 16 matched patients not progressing to recurrence with metastasis. The patients were matched for Leibovich sore, creatinine, age, sex, tumor size and tumor stage. Key results were confirmed with qPCR and external data from The Cancer Genome Atlas.ResultsPrincipal component analysis indicated that systematic transcriptomic differences were already detectable at the time of initial surgery. One thousand one hundred sixty-seven genes, mainly associated with cancer and immune-related pathways, were differentially expressed between progressors and nonprogressors. A search for a classifier revealed that overexpression of AGAP2-AS1, an antisense long noncoding RNA, correctly classified 23 of 24 samples, years (4.5 years average) in advance of the discovery of metastasis and without requiring larger gene panels. Subsequently, we confirmed AGAP2-AS1 gene overexpression by qPCR in the same samples (p < 0.05). Additionally, in external data from The Cancer Genome Atlas, overexpression of AGAP2-AS1 is correlated with overall unfavorable survival outcome in ccRCC, irrespective of other prognostic predictors (p = 2.44E−7).ConclusionAGAP2-AS1 may represent a novel biomarker identifying high-risk ccRCC patients currently classified as “low risk” at the time of surgery.

Identification of a Four Hypoxia-Associated Long Non-Coding RNA Signature and Establishment of a Nomogram Predicting Prognosis of Clear Cell Renal Cell Carcinoma

To identify novel hypoxia-associated long non-coding RNAs (lncRNAs) as potential biomarkers, we developed a risk stratification signature and constructed a prognosis prediction nomogram of clear cell renal cell carcinoma (ccRCC). Hypoxia-related lncRNAs were identified through Pearson correlation analysis between the expression profiles of hypoxia-related differentially expressed genes and lncRNAs from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Then, a signature of four key lncRNAs (COMETT, EMX2OS, AC026462.3, and HAGLR) was developed. The four lncRNAs were downregulated in high-grade, advanced stage, and high-risk ccRCC. The signature had an independent and long-standing prognosis prediction ability up to a 10-year follow-up. Notably, the risk score was significantly positively correlated with the infiltration abundances of six immune cells from the Tumor IMmune Estimation Resource (TIMER). The gene set enrichment analysis (GSEA) also suggested that the signature was involved in metabolism and tumorigenesis, which were closely related to the hypoxic tumor microenvironment. Ultimately, a nomogram of signature, age, stage, and grade, was built to predict the individual long-term survival possibility. Finally, the expressions of four lncRNAs were validated by quantitative real-time PCR (qRT-PCR). Our study identified a four-lncRNA signature and established a prognostic nomogram that reliably predicts survival in ccRCC. The findings may be beneficial to therapeutic customization and medical decision-making.

An eleven metabolic gene signature-based prognostic model for clear cell renal cell carcinoma

In this study, we performed bioinformatics and statistical analyses to investigate the prognostic significance of metabolic genes in clear cell renal cell carcinoma (ccRCC) using the transcriptome data of 539 ccRCC and 72 normal renal tissues from TCGA database. We identified 79 upregulated and 45 downregulated (n=124) metabolic genes in ccRCC tissues. Eleven prognostic metabolic genes (NOS1, ALAD, ALDH3B2, ACADM, ITPKA, IMPDH1, SCD5, FADS2, ACHE, CA4, and HK3) were identified by further analysis. We then constructed an 11-metabolic gene signature-based prognostic risk score model and classified ccRCC patients into high- and low-risk groups. Overall survival (OS) among the high-risk ccRCC patients was significantly shorter than among the low-risk ccRCC patients. Receiver operating characteristic (ROC) curve analysis of the prognostic risk score model showed that the areas under the ROC curve for the 1-, 3-, and 5-year OS were 0.810, 0.738, and 0.771, respectively. Thus, our prognostic model showed favorable predictive power in the TCGA and E-MTAB-1980 ccRCC patient cohorts. We also established a nomogram based on these eleven metabolic genes and validated internally in the TCGA cohort, showing an accurate prediction for prognosis in ccRCC.