Non-clear Renal Cell Carcinoma Research Articles

Characterization of FOLH1 Expression in Renal Cell Carcinoma.

Given the emergence of PSMA-targeted diagnostic agents and therapeutics, we sought to investigate patterns of FOLH1 expression in RCC and their impacts on RCC outcomes. We conducted a pooled multi-institutional analysis of patients with RCC having undergone DNA and RNA next-generation sequencing. FOLH1-high/low expression was defined as the ≥75th/<25th percentile of RNA transcripts per million (TPM). Angiogenic, T-effector, and myeloid expression signatures were calculated using previously defined gene sets. Kaplan-Meier estimates were calculated from the time of tissue collection or therapy start. We included 1,724 patients in the analysis. FOLH1 expression was significantly higher in clear cell (71%) compared to non-clear cell RCC tumors (19.0 versus 3.3 TPM, p < 0.001) and varied by specimen site (45% primary kidney/55% metastasis, 13.6 versus 9.9 TPM, p < 0.001). FOLH1 expression was correlated with angiogenic gene expression (Spearman = 0.76, p < 0.001) and endothelial cell abundance (Spearman = 0.76, p < 0.001). While OS was similar in patients with FOLH1-high versus -low ccRCC, patients with FOLH1-high clear cell tumors experienced a longer time on cabozantinib treatment (9.7 versus 4.6 months, respectively, HR 0.57, 95% CI 0.35-0.93, p < 0.05). We observed differential patterns of FOLH1 expression based on histology and tumor site in RCC. FOLH1 was correlated with angiogenic gene expression, increased OS, and a longer duration of cabozantinib treatment.

Increased level of serum leucine-rich-alpha-2-glycoprotein 1 in patients with clear cell renal cell carcinoma

BackgroundCurrently, no useful serum markers exist for clear cell renal cell carcinoma (ccRCC), making early detection challenging as diagnosis relies solely on imaging tests. Radiation exposure is also a concern due to multiple required CT examinations during treatment. Renal cell carcinoma (RCC) histological types include ccRCC and non-clear cell RCC (non-ccRCC); however, treatment response to medications varies which necessitates accurate differentiation between the two. Therefore, we aimed to identify a novel serum marker of RCC. Increased LRG1 expression in the serum has been demonstrated in multiple cancer types. However, the expression of LRG1 expression in the serum and cancer tissues of patients with RCC has not been reported. Since ccRCC is a hypervascular tumor and LRG1 is capable of accelerating angiogenesis, we hypothesized that the LRG1 levels may be related to ccRCC. Therefore, we examined LRG1 expression in sera from patients with RCC.MethodsUsing an enzyme-linked immunosorbent assay, serum levels of leucine-rich-alpha-2-glycoprotein 1 (LRG1) were measured in 64 patients with ccRCC and 22 patients non-ccRCC who underwent radical or partial nephrectomy, as well as in 63 patients without cancer.ResultsMedian values of serum LRG1 and their inter-quartile ranges were 63.2 (42.8–94.2) µg/mL in ccRCC, 23.4 (17.7–29.6) µg/mL in non-ccRCC, and 36.0 (23.7–56.7) µg/mL in patients without cancer, respectively (ccRCC vs. non-ccRCC or patients without cancer: P < 0.001). C-reactive protein (CRP) levels (P = 0.002), anemia (P = 0.037), hypercalcemia (P = 0.023), and grade (P = 0.031) were independent predictors of serum LRG1 levels in ccRCC. To assess diagnostic performance, the area under the receiver operating characteristic curve of serum LRG1 was utilized to differentiate ccRCC from non-cancer and non-ccRCC, with values of 0.73 (95% CI, 0.64–0.82) and 0.91 (95% CI, 0.82–0.96), respectively.ConclusionsLRG1 served as a serum marker associated with inflammation, indicated by CRP, anemia, hypercalcemia, and malignant potential in ccRCC. Clinically, serum LRG1 levels may assist in differentiating ccRCC from non-ccRCC with excellent diagnostic accuracy.

Prognostic significance of pT3a staging subclassifications in renal cell carcinoma: Not all pT3a are equal

ObjectiveTo examine the prognostic significance of perinephric fat, renal sinus fat, and renal vein invasion in patients with pT3a renal cell carcinoma (RCC) by histologic type. MethodsA population-based retrospective cohort study of patients with pT3aN0M0 RCC was performed using Surveillance, Epidemiology, and End Results (SEER) data for the years 2010 through 2019. Cox proportional hazards models were used to examine the relationship between pT3a subclassification groups and cancer-specific survival (CSS) by histological subtype (clear cell, papillary, chromophobe, and other). ResultsThe cohort consisted of 10,170 patients with pT3a RCC, including 8,446 (83.0%) with clear cell RCC and 1,724 (17.0%) with nonclear cell RCC (nccRCC). Median follow up was 36 months. Differences in CSS by pT3a subclassification groups were observed in all histological subtypes but were most pronounced in nccRCC, specifically papillary RCC. Compared to perinephric fat (PF) invasion only, renal vein (RV) invasion (HR = 4.9, 95%CI: 2.5–9.3, P < 0.01), renal sinus fat invasion (HR = 3.0, 95%CI: 1.4–6.2), RV and PF invasion (HR = 7.5, 95%CI: 3.5–16.0), and combination of all three characteristics (HR = 4.4, 95%CI: 1.2–15.5) were associated with worse CSS in patients with papillary RCC. ConclusionWe examined the prognostic role of pT3a staging subclassifications in RCC by histologic subtype and observed survival differences, particularly in papillary RCC. Our findings highlight the need to refine pT3a staging criteria to help guide individualized, multimodal treatment strategies for locally advanced RCC.

Papillary Renal Cell Carcinoma: Outcomes for Patients Receiving First-line Immune-based Combinations or Tyrosine Kinase Inhibitors from the ARON-1 Study

Background and objectivePapillary renal cell carcinoma (pRCC) is the most frequent histological subtype of non-clear cell RCC (nccRCC). Owing to the heterogeneity of nccRCC, patients are often excluded from large phase 3 trials focused on clear cell RCC, so treatment options for nccRCC remain limited. Our aim was to investigate the efficacy of first-line treatment with tyrosine kinase inhibitors (TKIs) or immuno-oncology (IO)-based combinations in patients with pRCC. MethodsWe performed a multicenter retrospective analysis of real-world data collected for patients with advanced pRCC treated in 40 centers in 12 countries as part of the ARON-1 project (NCT05287464). The primary endpoints were overall survival (OS), progression-free survival (PFS), the overall response rate (ORR), and time to second progression (PFS2). OS, PFS, and PFS2 were estimated using the Kaplan-Meier method and results were compared between the treatment groups using a log-rank test. Univariate and multivariable analyses were carried out using Cox proportional-hazard models. Key findings and limitationsWe included 200 patients with metastatic pRCC, of whom 73 were treated with IO-based combinations and 127 with TKIs. Median OS was 22.5 mo in the TKI group 28.8 mo in the IO group (p = 0.081). Median PFS was 6.4 mo in the TKI group and 17.4 mo in the IO group (p < 0.001). The ORR was higher in the IO group than in the TKI group (41% vs 27%; p = 0.037). Conclusions and clinical implicationsOur results show that IO-based combinations have superior efficacy outcomes to TKIs for first-line treatment of metastatic pRCC. Patient summaryThe ARON-1 project collects clinical data for patients with kidney cancer treated in multiple centers worldwide to assess outcomes in the real-world setting. We analyzed data for patients with metastatic kidney cancer of a specific subtype to evaluate the efficacy of different first-line treatments. Patients treated with immune-based combinations had better outcomes than patients treated with tyrosine kinase inhibitors.

Cancer-specific mortality in non-metastatic T1a renal cell carcinoma treated with radiotherapy versus partial nephrectomy.

Radiotherapy (RT) represents a treatment option for small renal masses with proven feasibility and tolerability. However, it has never been directly compared to partial nephrectomy (PN) with cancer-specific mortality (CSM) as an endpoint. Within the Surveillance, Epidemiology, and End Results database (2004-2020), we identified T1aN0M0 renal cell carcinoma (RCC) patients treated with RT or PN. We relied on 1:1 propensity score matching (PSM) for age, tumor size and histology. Subsequently, cumulative incidence plots and multivariable competing risks regression (CRR) models were fitted. The same methodology was then re-applied to a subset of patients with tumor size 21-40mm. Of 40,355 patients with T1aN0M0 RCC, 40,262 underwent PN (99.8%) vs 93 underwent RT (0.2%). RT patients were older (median age 72 vs 60years, p < 0.001) and harbored larger tumor size (median size 28 vs 25mm, p < 0.001) and a higher proportion of non-clear cell RCC (49% vs 22%, p < 0.001). After 1:1 PSM (92 RT versus 92 PN patients), cumulative incidence plots' derived CSM was 21.3 vs 4%, respectively. In multivariable CRR models, RT independently predicted higher CSM (hazard ratio (HR) 4.3, p < 0.001). In the subgroup with tumor size 21-40mm, after 1:1 PSM (72 RT versus 72 PN patients), cumulative incidence plots derived CSM was 21.3% vs 4%, respectively. In multivariable CRR models, RT also independently predicted higher CSM (HR 4.7, p = 0.001). In T1aN0M0 RCC patients, relative to PN, RT is associated with significantly higher absolute and relative CSM, even in patients with tumor size 21-40mm.

Abstract 1846: Integrative histopathologic, proteomic, phosphoproteomic, genomic, and transcriptomic characterization of renal cell carcinoma

Abstract Although histologically defined subtypes exist, renal cell carcinoma (RCC) is a heterogenous disease, resulting in various treatment outcomes and prognosis. Here, we conduct comprehensive profiling of RCC with histopathologic, proteomic, phosphoproteomic, genomic, and transcriptomic analyses on tumor and paired adjacent normal tissues from 113 patients. RCC tumors are distinctly separated from corresponding normal tissues through multi-omics clustering, a distinction further supported by pathway analysis. In addition, various hallmarks of cancer were differentially observed at the individual patient level, highlighting the intertumoral heterogeneity of RCC. Proteomic subtyping classifies RCC tumors into four subtypes (C1-4) with distinct phosphoproteomic, genomic, and transcriptomic characteristics with prognostic and predictive implications. Among these subtypes, C1-3 were almost composed of clear cell RCC (ccRCC; 96.8%), whereas C4 was composed of non-clear cell RCC (nccRCC) or other types of cancer (100.0%). Among each subtype, C1 (N=37) exhibits the strongest adaptive immune response and angiogenesis with favorable prognosis after surgical resection. C2 (N=39) was characterized with enrichment in DNA repair pathways and alteration in VHL (100.0%) along with BAP1 (24.0%) genes. C3 (N=19) was associated with enrichment in inflammatory response with dismal prognosis and therapeutic resistance to tyrosine kinase inhibitors targeting vascular endothelial growth factor receptors. C4 (N=18) was exclusively enriched with nccRCC with active mitochondrial and oxidation phosphorylation. Transglutaminase 2 (TGM2), a crosslinking enzyme, is identified as a potential marker with therapeutic implication for ccRCC. Collectively, this study reports a large-scale multi-omics-based approach of RCC, providing insights into biologic underpinning and evidence for rational treatment selection as well as linking the multi-omics-derived phenotypes to clinical outcomes of ccRCC. Citation Format: Woo Sun Kwon, Chang Gon Kim, Harim Koo, Woo Kyun Bae, Eu Chang Hwang, Won Sik Ham, Nam Hoon Cho, Jason K. Sa, Jong Bae Park, Sun Young Rha. Integrative histopathologic, proteomic, phosphoproteomic, genomic, and transcriptomic characterization of renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1846.

Metastasis suppressor kisspeptin (KISS1) in serum of patients with renal cell carcinoma

Background. The most important problems in improvement of treatment outcomes in patients with renal cell carcinoma (RCC) are search and validation of molecular markers for its early diagnosis and prognosis. Genes suppressing distant metastasizing but not affecting the primary tumor are called metastasis suppressors. Study of these genes and their products not only improves understanding of the mechanisms of tumor progression, but has practical value for diagnosis, prognosis, and establishment of new molecular targets for antitumor therapy. One of such genes is KISS1 with its product kisspeptin (KISS1) protein.Aim: comparative evaluation of KISS1 concentration in blood serum of practically healthy persons and patients with renal cancer; analysis of correlations between the marker’s level and clinical and morphological characteristics of the disease.Materials and methods. 140 patients with RCC (88 men, 52 women) aged between 29 and 82 years were included in the study. Among them, clear cell RCC was diagnosed in 84 patients, papillary in 38, chromophobe in 18. The control group was comprised of 40 healthy persons of matched age and sex. Pre-treatment KISS1 concentration in blood serum was measured using a direct enzyme immunoassay kit (Kisspeptin 1 – KISS1, Cloud-Clone Corp., USA).Results. Median serum KISS1 concentration in the control group was 51.7 pg/mL which was significantly lower than in the total RCC patient group – 243.6 pg/mL (p &lt;0.0001). ROC analysis of diagnostic value of serum KISS1 level was performed both for the total RCC group and for each of its three histological types. In the total group the sensitivity of the test was 75 %, specificity – 80 % (AUC 0.877; 95 % confidence interval (CI) 0.827–0.927; optimal cut-off level 130.8 pg/mL; р &lt;0.0001). For clear cell RCC, both sensitivity and specificity were 85 % (AUC 0.941; 95 % CI 0.902– 0.979; cut-off 141.8 pg/mL; p &lt;0.0001). In non-clear cell RCC types, sensitivity of this marker was only 58 % while the specificity remained 80 % (for papillary RCC AUC 0.787; 95 % CI 0.684–0.889; cut-off level 135.5 pg/mL; p &lt;0.0001, and for chromophobe RCC AUC 0.774; 95 % CI 0.617–0.929; cut-off level 132.1 pg/mL; p &lt;0.001). KISS1 level increased with disease progression: it is significantly higher at more advanced stages above stage I, and in patients with distant metastases compared to those without metastases. Higher serum KISS1 level is also observed in patients with poorly differentiated high-grade (per Furhman) clear cell RCC and papillary RCC (G3–G4) than in those with well differentiated low-grade (G1–G2) tumors.Conclusion. KISS1 level is significantly increased in patients with RCC compared to healthy controls and is a stagedependent marker of this disease. It has relatively high diagnostic sensitivity and specificity (both 85 %) for the most frequent histological type of RCC – clear cell RCC. Thus, clinical significance of kisspeptin in RCC requires further investigation.

Predicting recurrence and survival in patients with non-metastatic renal-cell carcinoma after nephrectomy: a prospective population-based study with multicenter validation.

Accurate prognostication of oncological outcomes is crucial for the optimal management of patients with renal cell carcinoma (RCC) after surgery. Previous prediction models were developed mainly based on retrospective data in the Western populations, and their predicting accuracy remains limited in contemporary, prospective validation. We aimed to develop contemporary RCC prognostic models for recurrence and overall survival (OS) using prospective population-based patient cohorts and compare their performance with existing, mostly utilized ones. In this prospective analysis and external validation study, the development set included 11 128 consecutive patients with non-metastatic RCC treated at a tertiary urology center in China between 2006 and 2022, and the validation set included 853 patients treated at 13 medical centers in the USA between 1996 and 2013. The primary outcome was progression-free survival (PFS), and the secondary outcome was OS. Multivariable Cox regression was used for variable selection and model development. Model performance was assessed by discrimination [Harrell's C-index and time-dependent areas under the curve (AUC)] and calibration (calibration plots). Models were validated internally by bootstrapping and externally by examining their performance in the validation set. The predictive accuracy of the models was compared with validated models commonly used in clinical trial designs and with recently developed models without extensive validation. Of the 11 128 patients included in the development set, 633 PFS and 588 OS events occurred over a median follow-up of 4.3 years [interquartile range (IQR) 1.7-7.8]. Six common clinicopathologic variables (tumor necrosis, size, grade, thrombus, nodal involvement, and perinephric or renal sinus fat invasion) were included in each model. The models demonstrated similar C-indices in the development set (0.790 [95% CI 0.773-0.806] for PFS and 0.793 [95% CI 0.773-0.811] for OS) and in the external validation set (0.773 [0.731-0.816] and 0.723 [0.731-0.816]). A relatively stable predictive ability of the models was observed in the development set (PFS: time-dependent AUC 0.832 at 1 year to 0.760 at 9 years; OS: 0.828 at 1 year to 0.794 at 9 years). The models were well calibrated and their predictions correlated with the observed outcome at 3, 5, and 7 years in both development and validation sets. In comparison to existing prognostic models, the present models showed superior performance, as indicated by C-indices ranging from 0.722 to 0.755 (all P <0.0001) for PFS and from 0.680 to 0.744 (all P <0.0001) for OS. The predictive accuracy of the current models was robust in patients with clear-cell and non-clear-cell RCC. Based on a prospective population-based patient cohort, the newly developed prognostic models were externally validated and outperformed the currently available models for predicting recurrence and survival in patients with non-metastatic RCC after surgery. The current models have the potential to aid in clinical trial design and facilitate clinical decision-making for both clear-cell and non-clear-cell RCC patients at varying risk of recurrence and survival.

The incidence, pathogenesis, and management of non-clear cell renal cell carcinoma.

Renal cell carcinoma (RCC) is the most common type of kidney cancer and is divided into two distinct subtypes, clear cell renal cell carcinoma (ccRCC) and non-clear cell renal cell carcinoma (nccRCC). Although many treatments exist for RCC, these are largely based on clinical trials performed in ccRCC and there are limited studies on the management of nccRCC. Non-clear cell RCC consists of multiple histological subtypes: papillary, chromophobe, translocation, medullary, collecting duct, unclassified, and other rare histologies. Due to variations in pathogenesis and therapeutic response, therapy should be tailored to specific variant histologies. For patients with localized nccRCC, surgical resection remains the gold standard. In the metastatic setting, the standard of care has yet to be clearly defined, and most guidelines recommend clinical trial participation. General therapeutic options include immunotherapy, either as monotherapy or in combination, targeted therapies such as vascular endothelial growth factor tyrosine kinase inhibitors and MET inhibitors, and chemotherapy in certain subtypes. Here we present a review of the incidence and pathogenesis of the various subtypes, as well as available clinical data to support therapeutic recommendations for these subtypes. We also highlight currently available clinical trials in nccRCC and future directions in investigating novel treatment modalities tailored to patients with variant histology.

Comprehensive analyses of immune tumor microenvironment in papillary renal cell carcinoma

BackgroundPapillary renal cell carcinoma (pRCC) is the most common non-clear cell RCC, and associated with poor outcomes in the metastatic setting. In this study, we aimed to comprehensively evaluate the...

Real-World Treatment Patterns and Clinical Outcomes Among Patients With Advanced Renal Cell Carcinoma

BackgroundNearly 30% of new renal cell carcinoma (RCC) cases are diagnosed at an advanced or metastatic stage. Recent approvals of immunotherapies (IO) have significantly impacted patient care, but real-world outcomes of these treatments have not been widely evaluated. MethodsEligible physicians abstracted demographic and clinical data from patient medical records for patients with advanced clear and non-clear cell RCC (aRCC) who initiated treatment between January 1, 2018, and December 31, 2020. Overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier method. A multivariate Cox regression model was developed to assess the impact of treatment category on clinical outcomes while controlling for International Metastatic RCC Database Consortium (IMDC) risk category, histology, and other patient characteristics. ResultsA total of 498 patients were included (201 from US, 62 from Canada, 58 from UK, 59 from France, 58 from Germany, 60 from Spain). Of these, 250 received tyrosine kinase inhibitor (TKI) monotherapy, 197 received immunotherapy (IO) combination (119 IO+TKI, 78 IO+IO), and 32 received IO monotherapy as first-line treatment for aRCC; 19 patients received various other regimens. 16% of patients had a favorable IMDC risk score. Based on results of multivariable Cox regression, PFS (hazard ratio [HR] [95% confidence interval (CI)]: 0.50 [0.36-0.72]) (P < .001) and time to next treatment (TTNT) were significantly longer (HR [95% CI]: 0.54 [0.39-0.73]) (P < .001) for patients treated with IO combination versus TKI monotherapy. IO combination had a numerically reduced, but statistically insignificant, risk of death versus TKI monotherapy (HR: 0.66; P = .114). IO+TKI combination was associated with significantly longer PFS and reduced risk of progression (HR: 0.52; P = .04) versus IO+IO combination; similar results were observed for TTNT (HR: 0.57; P = .03). ConclusionOur evaluation of real-world treatment outcomes in aRCC revealed that IO + TKI combination is associated with improved PFS and prolonged TTNT compared with TKI monotherapy and IO+IO combination.

Outcomes of Patients With Advanced Renal Cell Carcinoma With Non-Clear Cell Histology Treated With Systemic Therapy

BackgroundPatients with nonclear cell renal cell carcinoma (RCC) and RCC with sarcomatoid differentiation have been under-represented in clinical trials. This study evaluates the outcomes and treatment patterns of patients with non-clear cell RCC and RCC with sarcomatoid features compared to those with clear cell RCC receiving systemic therapy. MethodsA single-center retrospective analysis of patients with advanced or metastatic RCC receiving systemic therapy was conducted. Patients were divided into groups based on histology: nonclear cell RCC, clear cell RCC, and RCC with and without sarcomatoid features. The primary endpoint was overall survival (OS) for each group calculated from the date of diagnosis of advanced or metastatic RCC to the date of last follow-up or death. Additionally, an exploratory analysis was conducted by nonclear cell type and type of first-line treatment. ResultsOverall, 251 patients were included, with most treated before 2018. First-line therapies included vascular endothelial growth factor monotherapy (68.5%), immunotherapy monotherapy (7.6%), immunotherapy combination therapy (16.7%), or other treatments (7.2%). Overall survival was shorter for patients with nonclear cell RCC compared to clear cell RCC (39.2 months vs. 81.1 months, hazard ratio (HR), 1.60, 95% Confidence Interval 1.0, 2.6, P = .04). Additionally, OS for patients with sarcomatoid differentiation was shorter compared to patients without sarcomatoid differentiation (43.4 vs. 75.0 months, HR 1.5, 95% CI 0.8, 2.6, P = .20). ConclusionWe demonstrate inferior outcomes among patients with advanced or metastatic nonclear cell RCC and RCC with sarcomatoid differentiation receiving systemic treatment. Further prospective studies are warranted testing immunotherapy combinations and novel treatments in patients with nonclear cell RCC.

Efficacy and safety evaluation of immunotherapy combined with targeted therapy as second-line treatment in patients with metastatic non-clear cell renal cell carcinoma

Objective: This study aimed to evaluate the efficacy and safety of programmed death-1 (PD-1) inhibitor combined tyrosine kinase inhibitor (TKI) therapy versus TKI monotherapy as the second-line regimen for patients with metastatic non-clear cell renal carcinoma (nccRCC) who failed first-line TKI therapy. Methods: The clinicopathological data of 67 patients with metastatic nccRCC who failed first-line TKI therapy between October 2011 and September 2020 were retrospectively analyzed, including 22 patients who received TKI monotherapy and 45 patients who received TKI plus PD-1 inhibitor as the second-line therapy. The efficacy was assessed according to Response Evaluation Criteria in Solid Tumors version 1.0/1.1 (RECIST 1.0/1.1), the Kaplan-Meier method was used to plot the survival curves, and the Log rank test was used to analyze the differences in the survival between the two groups. Treatment-related adverse events (AEs) after treatment were observed in both groups. Results: The overall objective response rate (ORR) and disease control rate (DCR) were 37.3% (25/67) and 56.7% (38/67), respectively. The overall second-line progression-free survival (PFS) was 7.7 months and Overall Survival (OS) was 25.2 months. The ORR and DCR of patients in the combination therapy group were 48.9% (22/45) and 71.1% (32/45), respectively, which were significantly improved compared with the TKI monotherapy group [13.6% (3/22) and 27.3% (6/22), respectively] (P=0.007 and P=0.001, respectively). The median PFS of 9.2 months for second-line treatment was longer in patients in the combination therapy group than in the TKI monotherapy group (5.2 months, P=0.001), but the median OS was not statistically different between the two groups (28.2 months vs 20.8 months, P=0.068). Common treatment-related AEs included hypertension, diarrhea, fatigue, stomatitis, hand-foot syndrome, and hypothyroidism. The incidence of hypothyroidism was higher in the combination therapy group [40.0% (18/45)] than in the TKI monotherapy group [22.7% (5/22), P=0.044]; the incidence of other treatment-related AEs between the two groups were not statistically significant (all P>0.05). Conclusion: Immune-targeted combination therapy was more effective than TKI monotherapy alone and was well tolerated in the treatment of metastatic nccRCC patients who failed first-line TKIs.

Zanzalintinib in combination with immune checkpoint inhibitors: Design of the renal cell carcinoma expansion stage cohorts in STELLAR-002

Abstract Background: Zanzalintinib (XL092) is a novel, potent, orally bioavailable small molecule inhibitor of several receptor tyrosine kinases, including VEGFR2, MET, and the TAM kinases AXL, and MER. These receptor tyrosine kinases are implicated in several oncogenic processes, including tumor angiogenesis, proliferation, invasion, and metastasis. MET and AXL are known to play important roles in the development of resistance to antiangiogenic therapies. In addition, drugs targeting the TAM kinases are thought to promote an immune-permissive environment, potentially enhancing responses to immune checkpoint inhibitors (ICIs). This hypothesis has been confirmed in preclinical murine tumor models in which zanzalintinib in combination with an anti–PD-1 agent showed significantly greater antitumor and immunomodulatory activity, as well as a greater survival benefit, when compared with either agent alone (Hsu J, et al. Mol Cancer Ther 2023). In a phase 1 first-in-human study, zanzalintinib alone or in combination with atezolizumab showed a manageable safety profile and a half-life of 16–22 hours for zanzalintinib supporting once-daily dosing. The combination also showed promising clinical activity in patients with advanced or metastatic solid tumors, including renal cell carcinoma (RCC; Sharma MR, et al. ESMO 2022:Abs 481P). The encouraging preclinical and clinical activity support the evaluation of zanzalintinib in combination with ICIs in clinical studies, including STELLAR-304 (NCT05678673), a randomized study that is exploring the efficacy and safety of zanzalintinib in combination with nivolumab in patients with non-clear cell RCC (nccRCC). STELLAR-002 (NCT05176483) is another ongoing study assessing the safety and preliminary efficacy of zanzalintinib in multiple ICI combinations in patients with advanced solid tumors. Presented here is the study design of the cohort-expansion stage for patients with RCC in STELLAR-002. Methods: STELLAR-002 is a multicenter, open-label, phase 1b trial consisting of a dose-escalation stage and a tumor-specific cohort-expansion stage. The study is enrolling adults who have a cytologically or histologically confirmed solid tumor that is unresectable, locally advanced, or metastatic. In addition, patients with RCC enrolled in the expansion phase must have measurable disease per RECIST v1.1 as assessed by the investigator. The recommended doses of zanzalintinib plus nivolumab, zanzalintinib plus nivolumab and ipilimumab, and zanzalintinib plus nivolumab and relatlimab are being established in the dose-escalation stage of the study. The study includes three dose-expansion cohorts for patients with RCC: first-line clear cell RCC (ccRCC; Cohort 1), second-line ccRCC after 1 prior ICI-based combination therapy (Cohort 2), and first-line nccRCC (Cohort 6). The following regimens are available options for randomization at the recommended dose depending on the cohort: single-agent zanzalintinib (Regimen A), zanzalintinib plus nivolumab (Regimen B), zanzalintinib plus nivolumab and ipilimumab (Regimen C), or zanzalintinib plus nivolumab and relatlimab (Regimen D). Patients in Cohort 1 may be randomized to Regimens B, C, or D, patients in Cohort 2 to Regimens A, B, or D, and patients in Cohort 6 to Regimens A or B. The primary objectives of the cohort-expansion stage are objective response rate per RECIST v1.1 (as assessed by the investigator) and incidence and severity of adverse events, including serious and immune-mediated events. The trial is ongoing and enrolling patients from 13 countries in North America, Europe, and the Asia-Pacific region.

Abstract B010: Germline susceptibility to renal cell carcinoma and implications for genetic screening

Abstract Background: Genetic susceptibility to renal cell carcinoma (RCC) remains poorly understood and limited to specific hereditary cancer syndromes. Whereas few studies have investigated rare germline variants in specific populations, the majority of them have not taken into account differences between histological subtypes of RCC. Objective: To identify common risk-genes for RCC within the Canadian population, investigate their association to clinical annotations and outcomes, and compare gene-burden among RCC patients from various countries. Methods: We conducted targeted DNA sequencing of 19 RCC-related and 27 cancer predisposition genes for 960 RCC patients (759 with clear cell and 201 with non-clear cell RCC) from Canada. We identified genes enriched in rare germline pathogenic variants (PVs) in RCC compared to a cancer-free control population (gnomAD, n=118148). Gene associations to RCC subtypes and clinical annotations were examined using Firth’s logistic regression models and Fisher’s exact tests, respectively. In addition, we compared prevalence of PVs in Canadian patients to those in previous studies from Japan (n=1632), the UK (n=1336) and the USA (n=254). Furthermore, we evaluated the performance of current criteria for RCC genetic screening for including patients with PVs in Canada, the US, and the UK. Results: We identified 39 germline PVs in 56 RCC patients from the Canadian cohort. Compared to cancer-free controls, PVs in MITF (OR: 212.3, 95% CI: 4.0-6.8, p= 1.44 × 10−9), CHEK2 (OR: 4.8, 95% CI: 1.0-2.1, p=3.94 × 10−5), and ATM (OR: 4.5, 95% CI: 0.7-2.2, p=0.016) genes were significantly enriched in patients with clear cell RCC, whereas PVs in FH (OR: 215.1, 95% CI: 4.2-6.4, p=6.14 × 10−9) were enriched in patients with non-clear cell RCC. We observed an association between PVs in DNA repair genes BRCA1, BRCA2 and ATM with the presence of metastasis in ccRCC (p=0.004) and RCC overall (p=0.003). Comparisons of gene-burden to other populations showed an enrichment for TP53 in RCC patients from Japan, while RCC patients from Canada showed an enrichment for CHEK2 and ATM. RCC patients from the US showed an enrichment for germline PVs in FH in comparison to Canadians. Notably, our analysis reveals that current criteria for referral to genetic screening for hereditary renal cancer fail to include the majority (73%) of patients harboring rare germline PVs in risk genes for RCC, both in Canada and globally. Conclusions: MITF, CHEK2, ATM, and FH were identified as risk-genes for RCC within the Canadian population, while germline mutations in BRCA1/2 and ATM are associated with risk of metastasis. Globally, clinical guidelines for genetic screening in RCC fail to identify up to 80% of patients with rare germline PVs. Citation Format: Kate I. Glennon, Mikiko Endo, Yoshiaki Usui, Yusuke Iwasaki, Rodney H. Breau, Anil Kapoor, Simon Tanguay, Yukihide Momozawa, Yasser Riazalhosseini. Germline susceptibility to renal cell carcinoma and implications for genetic screening [abstract]. In: Proceedings of the AACR Special Conference: Advances in Kidney Cancer Research; 2023 Jun 24-27; Austin, Texas. Philadelphia (PA): AACR; Cancer Res 2023;83(16 Suppl):Abstract nr B010.

Chromophobe renal cell carcinoma

Chromophobe renal cell carcinoma (ChRCC) is the second most common variant histology (non-clear cell) RCC. ChRCC is distinct from clear cell RCC (ccRCC) in terms of genetics, genomics, metabolism, cell of origin, and response to targeted and immune therapies. The pathogenesis of ChRCC remains unclear, but current data suggest two potential mechanisms: mTORC1 hyperactivation through PTEN pathway mutations and mitochondrial dysfunction leading to oxidative stress. There are no specific approved treatments for ChRCC, although some responses to tyrosine kinase and mTOR inhibitors have been observed. Response to immunotherapy is generally limited. Targetable pathways involving innate lymphoid cells/IL-15 and cysteine homeostasis/ferroptosis have recently been identified.

The genomic and transcriptomic landscape of advanced renal cell cancer for individualized treatment strategies

Differences in the clinical course and treatment responses in individual patients with advanced renal cell carcinoma (RCC) can largely be explained by the different genomics of this disease. To improve the personalized treatment strategy and survival outcomes for patients with advanced RCC, the genomic make-up in patients with advanced RCC was investigated to identify putative actionable variants and signatures. In this prospective multicenter study (NCT01855477), whole-genome sequencing (WGS) data of locally advanced and metastatic tissue biopsies and matched whole-blood samples were collected from 91 patients with histopathologically confirmed RCC. WGS data were analyzed for small somatic variants, copy-number alterations and structural variants. For a subgroup of patients, RNA sequencing (RNA-Seq) data could be analyzed. RNA-Seq data were clustered on immunogenic and angiogenic gene expression patterns according to a previously developed angio-immunogenic gene signature. In all patients with papillary and clear cell RCC, putative actionable drug targets were detected by WGS, of which 94% were on-label available. RNA-Seq data of clear cell and papillary RCC were clustered using a previously developed angio-immunogenic gene signature. Analyses of driver mutations and RNA-Seq data revealed clear differences among different RCC subtypes, showing the added value of WGS and RNA-Seq over clinicopathological data. By improving both histological subtyping and the selection of treatment according to actionable targets and immune signatures, WGS and RNA-Seq may improve therapeutic decision making for most patients with advanced RCC, including patients with non-clear cell RCC for whom no standard treatment is available to data. Prospective clinical trials are needed to evaluate the impact of genomic and transcriptomic diagnostics on survival outcome for advanced RCC patients.

Second malignant tumors and non-tumor causes of death for patients with localized and regional kidney cancer after diagnosis

BackgroundTo evaluate the second malignant tumors (SMTs) and non-tumor causes of death among patients diagnosed with localized and regional kidney cancer.MethodsPatients diagnosed with kidney cancer between 2000 and 2017 in the Surveillance, Epidemiology, and End Results (SEER) program database were identified. All causes of death for patients during the follow-up and standardized mortality ratio (SMR) were analyzed.Result113,734 patients with localized kidney cancer with 30,390 cases of death were analyzed. 60.4% of the death cases were due to non-tumor caused and 23.6% were second malignant tumors (SMTs). Main SMTs included cancers of lung and bronchus [n = 1,283, SMR: 1.00 (0.95–1.06)] and pancreas [n = 393, SMR: 1.27 (1.15–1.41)]. Causes of death for non-tumor mainly included heart diseases [n = 6,161, SMR: 1.25 (1.21–1.28)] and chronic obstructive pulmonary disease (COPD) [n = 1,185, SMR: 0.99 (0.94–1.05)]. 14,437 of 29,602 patients with regional kidney cancer died. 14.6% of all deaths were due to SMTs and 23.6% due to non-tumor causes. Main SMTs contained bladder cancer [n = 371, SMR: 10.90 (9.81–12.06)] and lung and bronchus cancer [n = 346, SMR: 1.21 (1.08–1.34)]. The main non-tumor death was heart disease [n = 1,424, SMR: 1.26 (1.2–1.33)]. When stratified by pathological types, patients with clear cell renal cell carcinoma (RCC) did not have increased mortality risks of bladder cancer and lung cancer but patients with non-clear cell RCC did.ConclusionSMTs and non-tumor diseases including lung and bronchus cancer, bladder cancer, pancreas cancer, diseases of heart, COPD, and cerebrovascular diseases are the leading causes of death besides kidney cancer and should be paid more attention during patients’ survival period.

Genomic profiles of renal cell carcinoma in a small Chinese cohort.

Our aim was to describe the molecular characteristics of Renal Cell Carcinoma (RCC) and develop a small panel of RCC-associated genes from a large panel of cancer-related genes. Clinical data of 55 patients with RCC diagnosed in four hospitals from September 2021 to August 2022 were collected. Among the 55 patients, 38 were diagnosed with clear cell RCC (ccRCC), and the other 17 were diagnosed with non-clear cell RCC (nccRCC), including 10 cases of papillary renal cell carcinoma, 2 cases of hereditary leiomyomatosis and RCC syndrome (HLRCC), 1 eosinophilic papillary RCC, 1 tubular cystic carcinoma, 1 TFE3 gene fusion RCC, and 2 RCC with sarcomatoid differentiation. For each patient, 1123 cancer-related genes and 79 RCC-associated genes were analyzed. The most frequent mutations in a large panel of 1123 cancer-related genes in the overall population of RCC patients were VHL (51%), PBRM1 (35%), BAP1 (16%), KMT2D (15%), PTPRD (15%), and SETD2 (15%). For ccRCC patients, mutations in VHL, PBRM1, BAP1, and SERD2 can reach 74%, 50%, 24%, and 18%, respectively, while for nccRCC patients, the most frequent mutation was FH (29%), MLH3 (24%), ARID1A (18%), KMT2D (18%), and CREBBP (18%). The germline mutation rate in all 55 patients reached 12.7% (five with FH, one with ATM, and one with RAD50). The small panel containing only 79 RCC-associated genes demonstrated that mutations of VHL, PBRM1, BAP1, and SETD2 in ccRCC patients were 74%, 50%, 24%, and 18% respectively, while for the nccRCC cohort, the most frequent mutations were FH (29%), ARID1A (18%), ATM (12%), MSH6 (12%), BRAF (12%), and KRAS (12%). For ccRCC patients, the spectrum of mutations by large and small panels was almost the same, while for nccRCC patients, the mutation spectrum showed some differences. Even though the most frequent mutations (FH and ARID1A) in nccRCC were both demonstrated by large panels and small panels, other less frequent mutations such as MLH3, KMT2D, and CREBBP were not shown by the small panel. Our study revealed that nccRCC is more heterogeneous than ccRCC. For nccRCC patients, the small panel shows a more clear profile of genetic characteristics by replacing MLH3, KMT2D, and CREBBP with ATM, MSH6, BRAF, and KRAS, which may help predict prognosis and make clinical decisions.

Using the “2 standard deviations” rule with Dixon MRI to differentiate renal cell carcinoma types

BackgroundClear cell and non-clear cell renal cell carcinoma (RCC) are distinguishable based on microscopic fat, detectable by chemical shift MRI. However, these assessments are often subjective. Conversely, Dixon MRIs and the “2 standard deviations” rule (2SDR) are quantitative methods that may decrease diagnostic subjectivity. Therefore, this study assessed the value of the 2SDR for detecting microscopic fat and thus differentiating clear cell and non-clear cell RCC using Dixon MRI. MethodsThis retrospective study included patients with RCC who underwent preoperative Dixon MRI. The patients were grouped based on tumor type: clear cell RCC and non-clear cell RCC. The 2SDR value was calculated based on in-phase and opposed-phase images and then compared between the two groups. 2SDR values >0 indicated clear cell RCCs, whereas values <0 indicated non-clear cell RCC. ResultsWe included 151 patients; 114 patients had clear cell RCC, of which 106 had a 2SDR value >0. Furthermore, 37 patients had non-clear cell RCC, of which 3 had a 2SDR value >0. The 2SDR value was significantly higher in the clear cell RCC group than in the non-clear cell RCC group (p = 0.000). Overall, 93.0% (106/114) and 8.1% (3/37) of patients with clear cell and non-clear cell RCC, respectively, had microscopic fat. The evaluation indices for this 2SDR method were: accuracy: 92.72%, sensitivity: 92.98%, specificity: 91.89%, positive predictive value: 97.25%, and negative predictive value: 80.95%. Conclusions2SDR values calculated from Dixon magnetic resonance images can differentiate clear cell from non-clear cell RCCs by detecting microscopic fat. PrecisThe “2 standard deviations” rule value calculated from Dixon MR images differentiates clear cell from non-clear cell renal cell carcinoma with high efficiency by detecting microscopic fat.