Genomic Biomarkers of a Randomized Trial Comparing First-line Everolimus and Sunitinib in Patients with Metastatic Renal Cell Carcinoma

Decoding PTEN regulation in clear cell renal cell carcinoma: Pathway for biomarker discovery and therapeutic insights

Renal cell carcinoma is the most common adult renal solid tumor and the deadliest urological cancer, with clear cell renal cell carcinoma (ccRCC) being the predominant subtype. The PI3K/AKT signaling pathway assumes a central role in ccRCC tumorigenesis, wherein its abnormal activation confers a highly aggressive phenotype, leading to swift resistance against current therapies and distant metastasis. Thus, treatment resistance and disease progression remain a persistent clinical challenge in managing ccRCC effectively. PTEN, an antagonist of the PI3K/AKT signaling axis, emerges as a crucial factor in tumor progression, often experiencing loss or inactivation in ccRCC, thereby contributing to elevated mortality rates in patients. Therefore, understanding the molecular mechanisms underlying PTEN suppression in ccRCC tumors holds promise for the discovery of biomarkers and therapeutic targets, ultimately enhancing patient monitoring and treatment outcomes. The present review aims to summarize these mechanisms, emphasizing their potential prognostic, predictive, and therapeutic value in managing ccRCC.

Exploring necrosis-associated mitochondrial gene signatures: revealing their role in prognosis and immunotherapy of renal clear cell carcinoma

Mitochondrial dysfunction and necrotic apoptosis, pivotal in therapeutic strategies for multiple diseases, lack comprehensive understanding in the context of renal clear cell carcinoma (ccRCC). This study explores their potential as valuable tools for ccRCC prediction, prevention, and personalized medical care. Transcriptomic and clinical datasets were acquired from the Cancer Genome Atlas (TCGA) repository. Mitochondrial and necrosis-associated gene sets were sourced from MitoCarta3.0 and the KEGG Pathway databases, respectively. Six necrosis-related mitochondrial genes (nc-MTGs) with prognostic significance were analyzed and screened, and a prognostic model was constructed. The accuracy of the model was verified using external data (E-MTAB-1980). TISCH was used to explore nc-MTGs at the cellular level. Finally, the expression level of BH3 interacting domain death agonist (BID) in ccRCC cell line was detected by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), and the effect of BID down-regulation on tumor cell migration was verified by transwell assays and wound-healing experiments. We established and validated a prognostic model for clear cell renal cell carcinoma (ccRCC) utilizing six necrosis-related mitochondrial genes (nc-MTGs), affirming its efficacy in evaluating tumor progression. RT-PCR results showed that BID expression was up-regulated in ccRCC tissues compared with controls and exhibited oncogenic effects. In vitro cell function experiments showed that BID may be an important factor affecting the migration of ccRCC. Our study is the first to elucidate the biological functions and prognostic significance of mitochondrial molecules related to necroptosis, providing a new way to evaluate mitochondrial therapeutics in patients with ccRCC.

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

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

Morphological characteristics of SETD2-mutated locally advanced clear cell renal cell carcinoma: Comparison with BAP1-mutated clear cell renal cell carcinoma

SET-domain containing 2 (SETD2) and BRCA1-associated protein 1 (BAP1), both chromatin remodeling genes, are frequently mutated in clear cell renal cell carcinoma (ccRCC) and involved in tumor progression and metastasis. Herein, we studied clinicopathologic features of 7 cases of locally advanced ccRCC with single SETD2 mutation, and compared to 7 cases of locally advanced ccRCC with single BAP1 mutation. SETD2-mutated ccRCC showed high-grade transformation, comprising of enlarged tumor cells with voluminous clear cytoplasm, enlarged irregular nuclei with prominent nucleoli, eosinophilic cytoplasmic granules, arranged in various architectural patterns such as large nested, tubular, tubulopapillary and solid. 71 % (5 of 7 cases) of SETD2-mutated ccRCC showed a rhabdoid morphology. SETD2-mutated ccRCC have striking propensity for invasive growth; all cases have vascular invasion and perirenal (extracapsular) adipose tissue invasion. After nephrectomy, distant metastasis was found in 67 % (4 of 7 cases) of patients with SETD2-mutated ccRCC. The most common metastatic site was the lung (3 cases), followed by precaval lymph nodes (1 case). BAP1-mutated ccRCC also showed a similar high-grade morphology, with rhabdoid and/or sarcomatoid features. Their high-grade features mostly overlapped with those of SETD2-mutated ccRCC, which makes difficult to predict the presence of BAP1 or SETD2 mutation solely from morphology. These findings justify the use of molecular testing to detect these mutations, especially when we encounter high-grade ccRCC. Detecting SETD2 and BAP1 mutation in ccRCC is useful for risk stratification and proper therapeutic strategy.

The m6A demethylase FTO targets POLQ to promote ccRCC cell proliferation and genome stability maintenance

BACKGROUND AND AIM

As the first identified m6A demethylase, FTO has been implicated in the progression of various cancers. However, the specific mechanism of FTO in clear cell renal cell carcinoma (ccRCC) remains incompletely understood. In this study, we aimed to explore the potential molecular mechanisms influencing the progression of ccRCC.

METHODS

We initially assessed the expression of FTO in tumor and adjacent tissues using TCGA database, RT-qPCR, and Western blot. We then conducted CCK-8, cell cycle analysis, and colony formation assay to investigate the impact of FTO on ccRCC cell proliferation. MeRIP-seq and RNA-seq were employed to identify potential downstream targets of FTO in ccRCC, and these findings were further validated through dual-luciferase reporter assays and MeRIP-qPCR. Then, DNA damage and cell death were assessed separately through gammaH2AX immunofluorescence detection and the LIVE/DEAD Fixable Dead Cell Stain assay, respectively. Subsequently, we identified downstream pathways influenced by FTO's regulation of POLQ through TCGA database analysis and GSEA enrichment analysis. Validation was carried out through Western blot.

RESULTS

FTO is highly expressed in ccRCC tissues and cell lines. Furthermore, ROC curve demonstrates that FTO contributes to the diagnosis of ccRCC. FTO modulates m6A modification, consequently influencing the expression of POLQ, thus facilitating cell proliferation and maintaining genome stability in ccRCC.

CONCLUSION

FTO could potentially serve as a diagnostic marker for ccRCC. FTO promotes the progression of ccRCC by regulating m6A modification, making the inhibition of FTO a potential novel therapeutic strategy in ccRCC.

Predictive genomic biomarkers of therapeutic effects in renal cell carcinoma

BACKGROUND

In recent years, there have been great improvements in the therapy of renal cell carcinoma. Nevertheless, the therapeutic effect varies significantly from person to person. To discern the effective treatment for different populations, predictive molecular biomarkers in response to target, immunological, and combined therapies are widely studied.

CONCLUSION

This review summarized those studies from three perspectives (SNPs, mutation, and expression level) and listed the relationship between biomarkers and therapeutic effect, highlighting the great potential of predictive molecular biomarkers in metastatic RCC therapy. However, due to a series of reasons, most of these findings require further validation.

Genetic and Epigenetic Characteristics in Isolated Pancreatic Metastases of Clear-Cell Renal Cell Carcinoma

Isolated pancreatic metastases of renal cell carcinoma (IsPMRCC) are a rare manifestation of metastatic, clear-cell renal cell carcinoma (RCC) in which distant metastases occur exclusively in the pancreas. In addition to the main symptom of the isolated occurrence of pancreatic metastases, the entity surprises with additional clinical peculiarities: (a) the unusually long interval of about 9 years between the primary RCC and the onset of pancreatic metastases; (b) multiple pancreatic metastases occurring in 36% of cases; (c) favourable treatment outcomes with a 75% 5-year survival rate; and (d) volume and growth-rate dependent risk factors generally accepted to be relevant for overall survival in metastatic surgery are insignificant in isPMRCC. The genetic and epigenetic causes of exclusive pancreatic involvement have not yet been investigated and are currently unknown. Conversely, according to the few available data in the literature, the following genetic and epigenetic peculiarities can already be identified as the cause of the protracted course: 1. high genetic stability of the tumour cell clones in both the primary tumour and the pancreatic metastases; 2. a low frequency of copy number variants associated with aggressiveness, such as 9p, 14q and 4q loss; 3. in the chromatin-modifying genes, a decreased rate of PAB1 (3%) and an increased rate of PBRM1 (77%) defects are seen, a profile associated with a favourable course; 4. an increased incidence of KDM5C mutations, which, in common with increased PBRM1 alterations, is also associated with a favourable outcome; and 5. angiogenetic biomarkers are increased in tumour tissue, while inflammatory biomarkers are decreased, which explains the good response to TKI therapy and lack of sensitivity to IT.

Genomic Profiling and Molecular Characterization of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) treatment has undergone three major paradigm shifts in recent years, first with the introduction of molecular targeted therapies, then with immune checkpoint inhibitors, and, more recently, with immune-based combinations. However, to date, molecular predictors of response to targeted agents have not been identified for ccRCC. The WHO 2022 classification of renal neoplasms introduced the molecularly defined RCC class, which is a first step in the direction of a better molecular profiling of RCC. We reviewed the literature data on known genomic alterations of clinical interest in ccRCC, discussing their prognostic and predictive role. In particular, we explored the role of VHL, mTOR, chromatin modulators, DNA repair genes, cyclin-dependent kinases, and tumor mutation burden. RCC is a tumor whose pivotal genomic alterations have pleiotropic effects, and the interplay of these effects determines the tumor phenotype and its clinical behavior. Therefore, it is difficult to find a single genomic predictive factor, but it is more likely to identify a signature of gene alterations that could impact prognosis and response to specific treatment. To accomplish this task, the interpolation of large amounts of clinical and genomic data is needed. Nevertheless, genomic profiling has the potential to change real-world clinical practice settings.

Genomic profiles of renal cell carcinoma in a small Chinese cohort

Objectives

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.

Materials and methods

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.

Results

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.

Conclusion

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.

Multi-omics identification of an immunogenic cell death-related signature for clear cell renal cell carcinoma in the context of 3P medicine and based on a 101-combination machine learning computational framework

Background

Clear cell renal cell carcinoma (ccRCC) is a prevalent urological malignancy associated with a high mortality rate. The lack of a reliable prognostic biomarker undermines the efficacy of its predictive, preventive, and personalized medicine (PPPM/3PM) approach. Immunogenic cell death (ICD) is a specific type of programmed cell death that is tightly associated with anti-cancer immunity. However, the role of ICD in ccRCC remains unclear.

Methods

Based on AddModuleScore, single-sample gene set enrichment analysis (ssGSEA), and weighted gene co-expression network (WGCNA) analyses, ICD-related genes were screened at both the single-cell and bulk transcriptome levels. We developed a novel machine learning framework that incorporated 10 machine learning algorithms and their 101 combinations to construct a consensus immunogenic cell death-related signature (ICDRS). ICDRS was evaluated in the training, internal validation, and external validation sets. An ICDRS-integrated nomogram was constructed to provide a quantitative tool for predicting prognosis in clinical practice. Multi-omics analysis was performed, including genome, single-cell transcriptome, and bulk transcriptome, to gain a more comprehensive understanding of the prognosis signature. We evaluated the response of risk subgroups to immunotherapy and screened drugs that target specific risk subgroups for personalized medicine. Finally, the expression of ICD-related genes was validated by qRT-PCR.

Results

We identified 131 ICD-related genes at both the single-cell and bulk transcriptome levels, of which 39 were associated with overall survival (OS). A consensus ICDRS was constructed based on a 101-combination machine learning computational framework, demonstrating outstanding performance in predicting prognosis and clinical translation. ICDRS can also be used to predict the occurrence, development, and metastasis of ccRCC. Multivariate analysis verified it as an independent prognostic factor for OS, progression-free survival (PFS), and disease-specific survival (DSS) of ccRCC. The ICDRS-integrated nomogram provided a quantitative tool in clinical practice. Moreover, we observed distinct biological functions, mutation landscapes, and immune cell infiltration in the tumor microenvironment between the high- and low-risk groups. Notably, the immunophenoscore (IPS) score showed a significant difference between risk subgroups, suggesting a better response to immunotherapy in the high-risk group. Potential drugs targeting specific risk subgroups were also identified.

Conclusion

Our study constructed an immunogenic cell death-related signature that can serve as a promising tool for prognosis prediction, targeted prevention, and personalized medicine in ccRCC. Incorporating ICD into the PPPM framework will provide a unique opportunity for clinical intelligence and new management approaches.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00327-3.

Novel genetically engineered mouse models for clear cell renal cell carcinoma

Genetically engineered mouse models (GEMMs) are important immunocompetent models for research into the roles of individual genes in cancer and the development of novel therapies. Here we use inducible CRISPR-Cas9 systems to develop two GEMMs which aim to model the extensive chromosome p3 deletion frequently observed in clear cell renal cell carcinoma (ccRCC). We cloned paired guide RNAs targeting early exons of Bap1, Pbrm1, and Setd2 in a construct containing a Cas9^D10A (nickase, hSpCsn1n) driven by tetracycline (tet)-responsive elements (TRE3G) to develop our first GEMM. The founder mouse was crossed with two previously established transgenic lines, one carrying the tet-transactivator (tTA, Tet-Off) and one with a triple-mutant stabilized HIF1A-M3 (TRAnsgenic Cancer of the Kidney, TRACK), both driven by a truncated, proximal tubule-specific γ-glutamyltransferase 1 (ggt or γGT) promoter, to create triple-transgenic animals. Our results indicate that this model (BPS-TA) induces low numbers of somatic mutations in Bap1 and Pbrm1 (but not in Setd2), known tumor suppressor genes in human ccRCC. These mutations, largely restricted to kidneys and testis, induced no detectable tissue transformation in a cohort of 13 month old mice (N = 10). To gain insights into the low frequencies of insertions and deletions (indels) in BPS-TA mice we analyzed wild type (WT, N = 7) and BPS-TA (N = 4) kidneys by RNAseq. This showed activation of both DNA damage and immune response, suggesting activation of tumor suppressive mechanisms in response to genome editing. We then modified our approach by generating a second model in which a ggt-driven, cre-regulated Cas9^WT(hSpCsn1) was employed to introduce Bap1, Pbrm1, and Setd2 genome edits in the TRACK line (BPS-Cre). The BPS-TA and BPS-Cre lines are both tightly controlled in a spatiotemporal manner with doxycycline (dox) and tamoxifen (tam), respectively. In addition, whereas the BPS-TA line relies on paired guide RNAs (gRNAs), the BPS-Cre line requires only single gRNAs for gene perturbation. In the BPS-Cre we identified increased Pbrm1 gene-editing frequencies compared to the BPS-TA model. Whereas we did not detect Setd2 edits in the BPS-TA kidneys, we found extensive editing of Setd2 in the BPS-Cre model. Bap1 editing efficiencies were comparable between the two models. Although no gross malignancies were observed in our study, this is the first reported GEMM which models the extensive chromosome 3p deletion frequently observed in kidney cancer patients. Further studies are required (1) to model more extensive 3p deletions, e.g. impacting additional genes, and (2) to increase the cellular resolution, e.g. by employing single-cell RNAseq to ascertain the effects of specific combinatorial gene inactivation.

First-line therapy for adults with advanced renal cell carcinoma: a systematic review and network meta-analysis

BACKGROUND

Since the approval of tyrosine kinase inhibitors, angiogenesis inhibitors and immune checkpoint inhibitors, the treatment landscape for advanced renal cell carcinoma (RCC) has changed fundamentally. Today, combined therapies from different drug categories have a firm place in a complex first-line therapy. Due to the large number of drugs available, it is necessary to identify the most effective therapies, whilst considering their side effects and impact on quality of life (QoL).

OBJECTIVES

To evaluate and compare the benefits and harms of first-line therapies for adults with advanced RCC, and to produce a clinically relevant ranking of therapies. Secondary objectives were to maintain the currency of the evidence by conducting continuous update searches, using a living systematic review approach, and to incorporate data from clinical study reports (CSRs).

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, conference proceedings and relevant trial registries up until 9 February 2022. We searched several data platforms to identify CSRs.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) evaluating at least one targeted therapy or immunotherapy for first-line treatment of adults with advanced RCC. We excluded trials evaluating only interleukin-2 versus interferon-alpha as well as trials with an adjuvant treatment setting. We also excluded trials with adults who received prior systemic anticancer therapy if more than 10% of participants were previously treated, or if data for untreated participants were not separately extractable.

DATA COLLECTION AND ANALYSIS

All necessary review steps (i.e. screening and study selection, data extraction, risk of bias and certainty assessments) were conducted independently by at least two review authors. Our outcomes were overall survival (OS), QoL, serious adverse events (SAEs), progression-free survival (PFS), adverse events (AEs), the number of participants who discontinued study treatment due to an AE, and the time to initiation of first subsequent therapy. Where possible, analyses were conducted for the different risk groups (favourable, intermediate, poor) according to the International Metastatic Renal-Cell Carcinoma Database Consortium Score (IMDC) or the Memorial Sloan Kettering Cancer Center (MSKCC) criteria. Our main comparator was sunitinib (SUN). A hazard ratio (HR) or risk ratio (RR) lower than 1.0 is in favour of the experimental arm.

MAIN RESULTS

We included 36 RCTs and 15,177 participants (11,061 males and 4116 females). Risk of bias was predominantly judged as being 'high' or 'some concerns' across most trials and outcomes. This was mainly due to a lack of information about the randomisation process, the blinding of outcome assessors, and methods for outcome measurements and analyses. Additionally, study protocols and statistical analysis plans were rarely available. Here we present the results for our primary outcomes OS, QoL, and SAEs, and for all risk groups combined for contemporary treatments: pembrolizumab + axitinib (PEM+AXI), avelumab + axitinib (AVE+AXI), nivolumab + cabozantinib (NIV+CAB), lenvatinib + pembrolizumab (LEN+PEM), nivolumab + ipilimumab (NIV+IPI), CAB, and pazopanib (PAZ). Results per risk group and results for our secondary outcomes are reported in the summary of findings tables and in the full text of this review. The evidence on other treatments and comparisons can also be found in the full text. Overall survival (OS) Across risk groups, PEM+AXI (HR 0.73, 95% confidence interval (CI) 0.50 to 1.07, moderate certainty) and NIV+IPI (HR 0.69, 95% CI 0.69 to 1.00, moderate certainty) probably improve OS, compared to SUN, respectively. LEN+PEM may improve OS (HR 0.66, 95% CI 0.42 to 1.03, low certainty), compared to SUN. There is probably little or no difference in OS between PAZ and SUN (HR 0.91, 95% CI 0.64 to 1.32, moderate certainty), and we are uncertain whether CAB improves OS when compared to SUN (HR 0.84, 95% CI 0.43 to 1.64, very low certainty). The median survival is 28 months when treated with SUN. Survival may improve to 43 months with LEN+PEM, and probably improves to: 41 months with NIV+IPI, 39 months with PEM+AXI, and 31 months with PAZ. We are uncertain whether survival improves to 34 months with CAB. Comparison data were not available for AVE+AXI and NIV+CAB. Quality of life (QoL) One RCT measured QoL using FACIT-F (score range 0 to 52; higher scores mean better QoL) and reported that the mean post-score was 9.00 points higher (9.86 lower to 27.86 higher, very low certainty) with PAZ than with SUN. Comparison data were not available for PEM+AXI, AVE+AXI, NIV+CAB, LEN+PEM, NIV+IPI, and CAB. Serious adverse events (SAEs) Across risk groups, PEM+AXI probably increases slightly the risk for SAEs (RR 1.29, 95% CI 0.90 to 1.85, moderate certainty) compared to SUN. LEN+PEM (RR 1.52, 95% CI 1.06 to 2.19, moderate certainty) and NIV+IPI (RR 1.40, 95% CI 1.00 to 1.97, moderate certainty) probably increase the risk for SAEs, compared to SUN, respectively. There is probably little or no difference in the risk for SAEs between PAZ and SUN (RR 0.99, 95% CI 0.75 to 1.31, moderate certainty). We are uncertain whether CAB reduces or increases the risk for SAEs (RR 0.92, 95% CI 0.60 to 1.43, very low certainty) when compared to SUN. People have a mean risk of 40% for experiencing SAEs when treated with SUN. The risk increases probably to: 61% with LEN+PEM, 57% with NIV+IPI, and 52% with PEM+AXI. It probably remains at 40% with PAZ. We are uncertain whether the risk reduces to 37% with CAB. Comparison data were not available for AVE+AXI and NIV+CAB.

AUTHORS' CONCLUSIONS

Findings concerning the main treatments of interest comes from direct evidence of one trial only, thus results should be interpreted with caution. More trials are needed where these interventions and combinations are compared head-to-head, rather than just to SUN. Moreover, assessing the effect of immunotherapies and targeted therapies on different subgroups is essential and studies should focus on assessing and reporting relevant subgroup data. The evidence in this review mostly applies to advanced clear cell RCC.

BAP1-related signature predicts benefits from immunotherapy over VEGFR/mTOR inhibitors in ccRCC: a retrospective analysis of JAVELIN Renal 101 and checkmate-009/010/025 trials

BACKGROUND

In patients with advanced clear cell renal cell carcinoma, despite the undoubted benefits from immune checkpoint inhibitor (ICI)-based therapies over monotherapies of angiogenic/mTOR inhibitors in the intention-to-treat population, approximately a quarter of the patients can scarcely gain advantage from ICIs, prompting the search for predictive biomarkers for patient selection.

METHODS

Clinical and multi-omic data of 2428 ccRCC patients were obtained from The Cancer Genome Atlas (TCGA, n = 537), JAVELIN Renal 101 (avelumab plus axitinib vs. sunitinib, n = 885), and CheckMate-009/010/025 (nivolumab vs. everolimus, n = 1006).

RESULTS

BAP1 mutations were associated with large progression-free survival (PFS) benefits from ICI-based immunotherapies over sunitinib/everolimus (pooled estimate of interaction HR = 0.71, 95% CI 0.51-0.99, P = 0.045). Using the top 20 BAP1 mutation-associated differentially expressed genes (DEGs) generated from the TCGA cohort, we developed the BAP1-score, negatively correlated with angiogenesis and positively correlated with multiple immune-related signatures concerning immune cell infiltration, antigen presentation, B/T cell receptor, interleukin, programmed death-1, and interferon. A high BAP1-score indicated remarkable PFS benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors (avelumab plus axitinib vs. sunitinib: HR = 0.55, 95% CI 0.43-0.70, P < 0.001; nivolumab vs. everolimus: HR = 0.72, 95% CI 0.52-1.00, P = 0.045), while these benefits were negligible in the low BAP1-score subgroup (HR = 1.16 and 1.02, respectively).

CONCLUSION

In advanced ccRCCs, the BAP1-score is a biologically and clinically significant predictor of immune microenvironment and the clinical benefits from ICI-based immunotherapies over angiogenic/mTOR inhibitors, demonstrating its potential utility in optimizing the personalized therapeutic strategies in patients with advanced ccRCC.

A Nomogram for Relapse/Death and Contemplating Adjuvant Therapy for Parathyroid Carcinoma

Parathyroid carcinoma (PC) is a rare endocrine malignancy with an increased incidence in the last decade. There is no reliable prognostic staging system for PC. Several hosts, tumors, and tumor microenvironment factors have been negatively correlated with survival in the last decade. Surgical resection with negative margins is still the standard of treatment in PC. Chemo and radiotherapy have no proven beneficial effect. A new promising approach with molecular profiling could lead to adjuvant therapies.

The expanding role of BAP1 in clear cell renal cell carcinoma

Mutations drive renal cell carcinoma biology and tumor growth. The BRCA1-associated protein-1 (BAP1) gene is frequently mutated in clear cell renal cell carcinoma (ccRCC) and has emerged as a prognostic and putative predictive biomarker. In this review, we discuss the role of BAP1 as a signature event of a subtype of ccRCC marked by aggressiveness, inflammation, and possibly a heightened response to immunotherapy.

Sunitinib resistance in renal cell carcinoma: From molecular mechanisms to predictive biomarkers

Currently, renal cell carcinoma (RCC) is the most prevalent type of kidney cancer. Targeted therapy has replaced radiation therapy and chemotherapy as the main treatment option for RCC due to the lack of significant efficacy with these conventional therapeutic regimens. Sunitinib, a drug used to treat gastrointestinal tumors and renal cell carcinoma, inhibits the tyrosine kinase activity of a number of receptor tyrosine kinases, including vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), c-Kit, rearranged during transfection (RET) and fms-related receptor tyrosine kinase 3 (Flt3). Although sunitinib has been shown to be efficacious in the treatment of patients with advanced RCC, a significant number of patients have primary resistance to sunitinib or acquired drug resistance within the 6-15 months of therapy. Thus, in order to develop more efficacious and long-lasting treatment strategies for patients with advanced RCC, it will be crucial to ascertain how to overcome sunitinib resistance that is produced by various drug resistance mechanisms. In this review, we discuss: 1) molecular mechanisms of sunitinib resistance; 2) strategies to overcome sunitinib resistance and 3) potential predictive biomarkers of sunitinib resistance.

RNA mis-splicing drives viral mimicry response after DNMTi therapy in SETD2-mutant kidney cancer

Tumors with mutations in chromatin regulators present attractive targets for DNA hypomethylating agent 5-aza-2'-deoxycytidine (DAC) therapy, which further disrupts cancer cells' epigenomic fidelity and reactivates transposable element (TE) expression to drive viral mimicry responses. SETD2 encodes a histone methyltransferase (H3K36me3) and is prevalently mutated in advanced kidney cancers. Here, we show that SETD2-mutant kidney cancer cells are especially sensitive in vitro and in vivo to DAC treatment. We find that the viral mimicry response are direct consequences of mis-splicing events, such as exon inclusions or extensions, triggered by DAC treatment in an SETD2-loss context. Comprehensive epigenomic analysis reveals H3K9me3 deposition, rather than DNA methylation dynamics, across intronic TEs might contribute to elevated mis-splicing rates. Through epigenomic and transcriptomic analyses, we show that SETD2-deficient kidney cancers are prone to mis-splicing, which can be therapeutically exacerbated with DAC treatment to increase viral mimicry activation and provide synergy with combinatorial immunotherapy approaches.

Histone methyltransferase SETD2: An epigenetic driver in clear cell renal cell carcinoma

SET domain-containing 2 (SETD2) is a lysine methyltransferase that catalyzes histone H3 lysine36 trimethylation (H3K36me3) and has been revealed to play important roles in the regulation of transcriptional elongation, RNA splicing, and DNA damage repair. SETD2 mutations have been documented in several cancers, including clear cell renal cell carcinoma (ccRCC). SETD2 deficiency is associated with cancer occurrence and progression by regulating autophagy flux, general metabolic activity, and replication fork speed. Therefore, SETD2 is considered a potential epigenetic therapeutic target and is the subject of ongoing research on cancer-related diagnosis and treatment. This review presents an overview of the molecular functions of SETD2 in H3K36me3 regulation and its relationship with ccRCC, providing a theoretical basis for subsequent antitumor therapy based on SETD2 or H3K36me3 targets.

KDM5 Lysine Demethylases in Pathogenesis, from Basic Science Discovery to the Clinic

The histone lysine demethylase 5 (KDM5) family proteins are Fe2+ and α-ketoglutarate-dependent dioxygenases, with jumonji C (JmjC) domain as their catalytic core and several plant homeodomains (PHDs) to bind different histone methylation marks. These enzymes are capable of demethylating tri-, di- and mono-methylated lysine 4 in histone H3 (H3K4me3/2/1), the key epigenetic marks for active chromatin. Thus, this H3K4 demethylase family plays critical roles in cell fate determination during development as well as malignant transformation. KDM5 demethylases have both oncogenic and tumor suppressive functions in a cancer type-dependent manner. In solid tumors, KDM5A/B are generally oncogenic, whereas KDM5C/D have tumor suppressive roles. Their involvement in de-differentiation, cancer metastasis, drug resistance, and tumor immunoevasion indicated that KDM5 family proteins are promising drug targets for cancer therapy. Significant efforts from both academia and industry have led to the development of potent and selective KDM5 inhibitors for preclinical experiments and phase I clinical trials. However, a better understanding of the roles of KDM5 demethylases in different physiological and pathological conditions is critical for further developing KDM5 modulators for clinical applications.

Semantic Computed Tomography Features for Predicting BRCA1-associated Protein 1 and/or Tumor Protein p53 Gene Mutation Status in Clear Cell Renal Cell Carcinoma

PURPOSE

The purpose of this study was to explore the semantic computed tomography (CT) features associated with BRCA1-associated protein 1 (BAP1) and/or tumor protein p53 (TP53) mutation in clear cell renal cell carcinoma (ccRCC).

METHODS AND MATERIALS

Clinical characteristics and gene mutation information of 336 ccRCC patients were retrieved from The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma database (TCGA-KIRC). Kaplan-Meier analysis was performed to examine prognosis by gene mutation. The CT imaging data and gene mutation information of 156 ccRCC patients treated between January 2019 and January 2021 (the training cohort) were retrospectively analyzed. The CT imaging information and gene mutation data of 123 patients with ccRCC were downloaded from The Cancer Imaging Archive and The Cancer Genome Atlas database (the external validation cohort). Univariate Chi-square test and multivariate binary logistic regression analysis were performed to determine predictors of gene mutation; a nomogram was developed using these predictors. Receiver operating characteristic curve analysis and the Hosmer-Lemeshow test were performed to evaluate the performance of the nomogram.

RESULTS

Kaplan-Meier analysis showed that BAP1 and/or TP53 mutation was significantly correlated with worse survival outcome. Multivariate binary logistic regression analysis indicated ill-defined margin (P = .001), spiculated margin (P = .018), renal vein invasion (P = .002), and renal pelvis invasion (P = .001) were independent predictors of BAP1 and/or TP53 mutation. A nomogram containing these 4 semantic CT features was constructed; the area under the receiver operating characteristic curves was 0.872 (95% CI, 0.809-0.920). The Hosmer-Lemeshow test showed acceptable goodness-of-fit for the nomogram (X² = 1.194, P = .742). The nomogram was validated in the validation cohort; it showed good accuracy (area under the receiving operating characteristic curve = 0.819, 95% CI, 0.740-0.883) and was well calibrated (X² = 3.934, P = .559).

CONCLUSIONS

Semantic CT features are a potential and promising method for predicting BAP1 and/or TP53 mutation status in ccRCC patients.

Tumors masquerading as type 2 papillary renal cell carcinoma: pathologists' ever-expanding differential diagnosis for a heterogeneous group of entities

Although papillary renal cell carcinoma has historically been classified as either type 1 or type 2, data from The Cancer Genome Atlas (TCGA) has demonstrated significant genomic heterogeneity in tumors classified as "type 2 papillary renal cell carcinoma" (T2PRCC). Papillary renal cell carcinoma is expected to have a favorable clinical course compared to clear cell renal cell carcinoma (CCRCC). However, tumors with poor outcome more similar to CCRCC were included in the T2PRCC cohort studied by the TCGA. The differential diagnosis for T2PRCC includes a variety of other renal tumors, including aggressive entities such as TFE3 translocation-associated renal cell carcinoma, TFEB-amplified renal cell carcinoma, fumarate hydratase-deficient renal cell carcinoma, high-grade CCRCC, and collecting duct carcinoma. Accurate classification of these tumors is important for prognostication and selection of therapy.

Development of a SETD2-related immune prognostic signature in clear cell renal cell carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is a malignant tumor of urinary system, and clear cell RCC (ccRCC) is the major pathological subtype. A high-frequency mutation in SETD2 gene is related to the occurrence, development, and poor prognosis of RCC.

OBJECTIVE

The research of immune-related genes (IRGs) is important to the success of immunotherapy in RCC. The aim of this study was to develop SETD2-related immune prognostic signature (IPS) potentially useful in the prognosis prediction of ccRCC.

METHODS

The expression profile, mutation profile, and clinical data related to ccRCC were obtained from the TCGA (Cancer Genome Atlas) and cBioPortal databases. The data of IRGs were downloaded from the ImmPort database.

RESULTS

An IPS with 5 genes (PDIA2, PAEP, AMELX, GREM2, and INHA) was constructed by analyzing the correlation between prognosis data and IRGs associated with ccRCC patients with wild type and mutant SETD2 genes. The clinical utility of the IPS and its relationship with immune microenvironment were also studied.

CONCLUSIONS

According to the results of this study, the IPS can be a promising biomarker of ccRCC to guide its prognosis and treatment.

Exploring synthetic lethal network for the precision treatment of clear cell renal cell carcinoma

The emerging targeted therapies have revolutionized the treatment of advanced clear cell renal cell carcinoma (ccRCC) over the past 15 years. Nevertheless, lack of personalized treatment limits the development of effective clinical guidelines and improvement of patient prognosis. In this study, large-scale genomic profiles from ccRCC cohorts were explored for integrative analysis. A credible method was developed to identify synthetic lethality (SL) pairs and a list of 72 candidate pairs was determined, which might be utilized to selectively eliminate tumors with genetic aberrations using SL partners of specific mutations. Further analysis identified BRD4 and PRKDC as novel medical targets for patients with BAP1 mutations. After mapping these target genes to the comprehensive drug datasets, two agents (BI-2536 and PI-103) were found to have considerable therapeutic potentials in the BAP1 mutant tumors. Overall, our findings provided insight into the overview of ccRCC mutation patterns and offered novel opportunities for improving individualized cancer treatment.

Clinical Benefit of Niraparib to TKI/mTORi-Resistance Metastatic ccRCC With BAP1-Frame Shift Mutation: Case Report and Literature Review

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. The top four mutant genes affecting the occurrence and progression of ccRCC are VHL, PBRM1, BAP1, and SETD2, respectively. Tyrosine kinase/mammalian target of rapamycin inhibitors (TKI/mTORis) with or without immunotherapy are the standard and effective therapy to metastatic ccRCC. Once TKI/mTORis fail to ccRCC, there is still a lack of other effective therapies. In this study, we reported a case in which a metastatic ccRCC patient (T2aN1M1) presented resistance after a 28-month treatment by sorafenib–axitinib–everolimus (TKI-TKI-mTORi). Subsequently, a frame shift pathogenic mutation, c.799_800del (p.Q267fs) in the exon10 of BAP1 in ccRCC, was revealed by targeted sequencing. Oral administration of nilapanib (PARP inhibitor) was further given, which may provide a new therapy for TKI/mTORi-resistance metastatic ccRCC. Fortunately, a partial response has been achieved and lasted for 5 months. Since the frequency of BAP1 mutations in ccRCC patients was approximately 10%–20%, as reported previously, we also tried to explore the potential mechanisms benefitting from the nilapanib. Moreover, the literature concerning BAP1 mutation and associated cancers including ccRCC is reviewed.

Expression of GOT2 Is Epigenetically Regulated by DNA Methylation and Correlates with Immune Infiltrates in Clear-Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (KIRC) is the most common and highly malignant pathological type of kidney cancer, characterized by a profound metabolism dysregulation. As part of aspartate biosynthesis, mitochondrial GOT2 (glutamic-oxaloacetic transaminase 2) is essential for regulating cellular energy production and biosynthesis, linking multiple pathways. Nevertheless, the expression profile and prognostic significance of GOT2 in KIRC remain unclear. This study comprehensively analyzed the transcriptional levels, epigenetic regulation, correlation with immune infiltration, and prognosis of GOT2 in KIRC using rigorous bioinformatics analysis. We discovered that the expression levels of both mRNA and protein of GOT2 were remarkably decreased in KIRC tissues in comparison with normal tissues and were also significantly related to the clinical features and prognosis of KIRC. Remarkably, low GOT2 expression was positively associated with poorer overall survival (OS) and disease-free survival (DFS). Further analysis revealed that GOT2 downregulation is driven by DNA methylation in the promoter-related CpG islands. Finally, we also shed light on the influence of GOT2 expression in immune cell infiltration, suggesting that GOT2 may be a potential prognostic marker and therapeutic target for KIRC patients.

Clinicopathological and Prognostic Value of Necroptosis-Associated lncRNA Model in Patients with Kidney Renal Clear Cell Carcinoma

Background. Necroptosis, a recently identified type of programmed necrotic cell death, is closely related to the tumorigenesis and development of cancer. However, it remains unclear whether necroptosis-associated long noncoding RNAs (lncRNAs) can be used to predict the prognosis of kidney renal clear cell carcinoma (KIRC). This work was designed to probe the possible prognostic worth of necroptosis-associated lncRNAs along with their impact on the tumor microenvironment (TME) in KIRC. Methods. The Cancer Genome Atlas (TCGA) database was used to extract KIRC gene expression and clinicopathological data. Pearson correlation analysis was used to evaluate necroptosis-associated lncRNAs against 159 known necroptosis-associated genes. To define molecular subtypes, researchers used univariate Cox regression analysis and consensus clustering, as well as clinical significance, TME, and tumor immune cells in each molecular subtype. We develop the necroptosis-associated lncRNA prognostic model using univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Patients were divided into high- and low-risk groups according to prognostic model. Moreover, comprehensive analyses, including prognostic value, gene set enrichment analysis (GSEA), immune infiltration, and immune checkpoint gene expression, were performed between the two risk groups. Finally, anticancer drug sensitivity analyses were employed for assessing associations for necroptosis-associated lncRNA expression profile and anticancer drug chemosensitivity. Results. Through univariate analysis, sixty-nine necroptosis-associated lncRNAs were found to have a significant relationship with KIRC prognosis. Two molecular clusters were identified, and significant differences were found with respect to clinicopathological features and prognosis. The segregation of patients into two risk groups was done by the constructed necroptosis-associated lncRNA model. The survival prognosis, clinical features, degree of immune cell infiltration, and expression of immune checkpoint genes of high-risk and low-risk groups were all shown to vary. Conclusions. Our study identified a model of necroptosis-associated lncRNA signature and revealed its prognostic role in KIRC. It is expected to provide a reference for the screening of KIRC prognostic markers and the evaluation of immune response.

Immune Checkpoint Blockade via PD-L1 Potentiates More CD28-Based than 4-1BB-Based Anti-Carbonic Anhydrase IX Chimeric Antigen Receptor T Cells

The complete regression of clear cell renal cell carcinoma (ccRCC) obtained pre-clinically with anti-carbonic anhydrase IX (CAIX) G36 chimeric antigen receptor (CAR) T cells in doses equivalent to ≅10⁸ CAR T cells/kg renewed the potential of this target to treat ccRCC and other tumors in hypoxia. The immune checkpoint blockade (ICB) brought durable clinical responses in advanced ccRCC and other tumors. Here, we tested CD8α/4-1BB compared to CD28-based anti-CAIX CAR peripheral blood mononuclear cells (PBMCs) releasing anti-programmed cell death ligand-1 (PD-L1) IgG4 for human ccRCC treatment in vitro and in an orthotopic NSG mice model in vivo. Using a ≅10⁷ CAR PBMCs cells/kg dose, anti-CAIX CD28 CAR T cells releasing anti-PD-L1 IgG highly decrease both tumor volume and weight in vivo, avoiding the occurrence of metastasis. This antitumoral superiority of CD28-based CAR PBMCs cells compared to 4-1BB occurred under ICB via PD-L1. Furthermore, the T cell exhaustion status in peripheral CD4 T cells, additionally to CD8, was critical for CAR T cells efficiency. The lack of hepatotoxicity and nephrotoxicity upon the administration of a 10⁷ CAR PMBCs cells/kg dose is the basis for carrying out clinical trials using anti-CAIX CD28 CAR PBMCs cells releasing anti-PD-L1 antibodies or anti-CAIX 4-1BB CAR T cells, offering exciting new prospects for the treatment of refractory ccRCC and hypoxic tumors.

The RBPJ/DAPK3/UBE3A signaling axis induces PBRM1 degradation to modulate the sensitivity of renal cell carcinoma to CDK4/6 inhibitors

Renal cell carcinoma (RCC) is a kind of malignant tumor originating from the renal tubular epithelium. Approximately 30% of patients with renal cancer are found to have metastasis when first diagnosed. Exploring other effective treatment methods in addition to surgery is an urgent need in the research field of renal cell carcinoma. Polybromo 1 (PBRM1) is the second most mutated gene in RCC, with a mutation rate of ~40%. Notably, the posttranscriptional modification of PBRM1 in RCC is unclear. In this study, we performed unbiased mass spectrometry of PBRM1 and identified ubiquitin-protein ligase E3A (UBE3A), an extensively studied E3 ligase that can bind with PBRM1 and regulate the stability of PBRM1 in renal cancer cells. We further found that RBPJ/DAPK3 modulated the E3 ligase activity of UBE3A by interfering with the PKA phosphorylation of UBE3A. Finally, we demonstrated that the RBPJ/DAPK3/UBE3A/PBRM1/p21 axis contributed to the sensitivity of renal cancer cells to CDK4/6 inhibitors. In addition, in combination with RBPJ inhibitors, CDK4/6 inhibitors showed synergistically enhanced effects on renal cancer cells. In summary, we not only revealed a novel RBPJ/DAPK3/UBE3A/PBRM1/p21 signaling axis but also identified a combination strategy for overcoming the resistance of renal cancer cells to CDK4/6 inhibitors.

Reshaping Treatment Paradigms for Advanced Renal Cell Cancer Patients and Improving Patient Management : Optimal Management for Renal Cell Cancer Patients

OPINION STATEMENT

The treatment of renal cell carcinoma (RCC) is one of the great success stories in the field of oncology, which was revolutionized with the development of therapies aimed at disrupting crucial pathways. Tumor biology of RCC has provided insight into the disease through elucidation of the role of vascular endothelial growth-factor (VEGF) and the mammalian target of rapamycin (mTOR). Targeted agents against VEGF and mTOR, as well as agents targeting relevant immunomodulatory pathways, have shown clinical benefit for advanced disease. The targeted agents are highly effective in achieving a response and survival, particularly in high-risk patients. These include the vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitors (TKIs) axitinib and cabozantinib, and programmed cell death 1 protein (PD-1) immune checkpoint inhibitors (ICI) nivolumab and pembrolizumab. There is a wealth of evidence investigating different therapeutic options and combinations for first-line treatment of advanced RCC including the CheckMate 214 study, KEYNOTE-426, JAVELIN Renal 101, and CheckMate 9ER. Dual ICI and combination agents targeting the programmed cell death protein 1/programmed cell death protein ligand 1 (PD1/PDL1) and VEGF, began to demonstrate superiority over previously accepted standards in advanced clear-cell RCC. Data from a number of clinical studies are available to help physicians with evidence-based decisions for the sequence of second-line and future treatments for patients with progressive RCC. In this review, we focus on essentials for clinicians treating patients with clear-cell RCC.

The genomic landscape of metastatic clear cell renal cell carcinoma after systemic therapy

Primary clear cell renal cell carcinoma (ccRCC) has been previously characterized, but the genomic landscape of metastatic ccRCC is largely unexplored. Here, we performed whole exome sequencing (WES) in 68 samples from 44 patients with ccRCC, including 52 samples from a metastatic site. SETD2, PBRM1, APC and VHL were the most frequently mutated genes in the metastatic ccRCC cohort. RBM10 and FBXW7 were also among the 10 most frequently mutated genes in metastatic tissues. Recurrent somatic copy number variations (CNV) were observed at the previously identified regions 3p25, 9p21 and 14q25, but also at 6p21 (CDKN1A) and 13q14 (RB1). No statistically significant differences were found between samples from therapy‐naïve and pretreated patients. Clonal evolution analyses with multiple samples from 13 patients suggested that early appearance of CNVs at 3p25, 9p21 and 14q25 may be associated with rapid clinical progression. Overall, the genomic landscapes of primary and metastatic ccRCC seem to share frequent CNVs at 3p25, 9p21 and 14q25. Future work will clarify the implication of RBM10 and FBXW7 mutations and 6p21 and 13q14 CNVs in metastatic ccRCC.

Identification and validation of a cigarette smoke-related five-gene signature as a prognostic biomarker in kidney renal clear cell carcinoma

Cigarette smoking greatly promotes the progression of kidney renal clear cell carcinoma (KIRC), however, the underlying molecular events has not been fully established. In this study, RCC cells were exposed to the tobacco specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK, nicotine-derived nitrosamine) for 120 days (40 passages), and then the soft agar colony formation, wound healing and transwell assays were used to explore characteristics of RCC cells. RNA-seq was used to explore differentially expressed genes. We found that NNK promoted RCC cell growth and migration in a dose-dependent manner, and RNA-seq explored 14 differentially expressed genes. In TCGA-KIRC cohort, Lasso regression and multivariate COX regression models screened and constructed a five-gene signature containing ANKRD1, CYB5A, ECHDC3, MT1E, and AKT1S1. This novel gene signature significantly associated with TNM stage, invasion depth, metastasis, and tumor grade. Moreover, when compared with individual genes, the gene signature contained a higher hazard ratio and therefore had a more powerful value for the prognosis of KIRC. A nomogram was also developed based on clinical features and the gene signature, which showed good application. Finally, AKT1S1, the most crucial component of the gene signature, was significantly induced after NNK exposure and its related AKT/mTOR signaling pathway was dramatically activated. Our findings supported that NNK exposure would promote the KIRC progression, and the novel cigarette smoke-related five-gene signature might serve as a highly efficient biomarker to identify progression of KIRC patients, AKT1S1 might play an important role in cigarette smoke exposure-induced KIRC progression.

The Next Paradigm Shift in the Management of Clear Cell Renal Cancer: Radiogenomics—Definition, Current Advances, and Future Directions

With improved molecular characterization of clear cell renal cancer and advances in texture analysis as well as machine learning, diagnostic radiology is primed to enter personalized medicine with radiogenomics: the identification of relationships between tumor image features and underlying genomic expression. By developing surrogate image biomarkers, clinicians can augment their ability to non-invasively characterize a tumor and predict clinically relevant outcomes (i.e., overall survival; metastasis-free survival; or complete/partial response to treatment). It is thus important for clinicians to have a basic understanding of this nascent field, which can be difficult due to the technical complexity of many of the studies. We conducted a review of the existing literature for radiogenomics in clear cell kidney cancer, including original full-text articles until September 2021. We provide a basic description of radiogenomics in diagnostic radiology; summarize existing literature on relationships between image features and gene expression patterns, either computationally or by radiologists; and propose future directions to facilitate integration of this field into the clinical setting.

Molecular Characterization of m6A Modifications in Non-Clear Cell Renal Cell Carcinoma and Potential Relationship with Pathological Types

Background

N6-Methyladenosine (m6A) modification is a eukaryotic mRNA modification that modulates the fate of modified RNA and, therefore, the expression of proteins. m6A modifications are associated with important roles in several cancers. Most studies related to m6A modification are based on clear cell renal cell carcinoma (ccRCC) and little is known about its role in non-ccRCC.

Methods

We summarized the molecular features of different m6A modification patterns in non-ccRCC based on The Cancer Genome Atlas database and correlated them with phenotypes such as immune patterns and prognosis. We also computed the m6Ascore and assessed its prognostic value using multivariate Cox regression analysis.

Results

We found the immune-excluded phenotype to be predominant in non-ccRCC patients. We also found that in non-clear cell carcinoma, different m6A modification profiles determine different immune patterns and are associated with different prognosis. m6AgeneCluser typing strongly associated with pathological status. Based on our findings, we suggest that the m6Ascore can be used as an independent prognostic value for prognostic assessment in non-ccRCC.

Conclusion

This study confirms the important role of m6A modifications in non-ccRCC, reveals the heterogeneity of tumor immunity, and highlights the promise of non-ccRCC therapy.

Case Report: TFE3 Positive Xp11.2 Translocation Renal Cell Carcinoma (TRCC) – A Case Study and Review of the Literature

Microphthalmia-associated transcription factor renal cell cancer, also known as translocation renal cell cancer, belongs to the group of extremely rare non-clear-cell kidney neoplasms. Their incidence is lower in adulthood than in childhood. The only known risk factor for the development of this tumor is prior chemotherapy. In the operable stage of the disease, the prognosis depends on the status of regional lymph nodes. Interestingly lymph node positivity worsens the prognosis only in the adult patient population. Radical surgical excision is the best therapy in the early stage. The optimal treatment strategy for locally advanced and metastatic disease has not been established, given the lack of evidence in such a rare disease. We present the case of a patient with an aggressive course of this neoplasm treated with temsirolimus, who achieved 10-month control of this neoplasm accompanied by a discussion on other therapeutic possibilities.

M2-Polarization-related CNTNAP1 gene might be a novel immunotherapeutic target and biomarker for clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common malignancies, characterized by high mortality rate in urology. Unfortunately, reliable biomarkers for ccRCC diagnosis and prognosis remain lacking. Contactin Associated Protein 1 (CNTNAP1) has yet to be thoroughly investigated in cancer, especially its relationship with immune infiltration or clinical outcomes of ccRCC. Here, we explored the Cancer Genome Atlas Kidney Clear Cell Carcinoma database (TCGA-KIRC) for prognostic significance, differential expression, and probable mechanism of CNTNAP1. The aberrant CNTNAP1 expression was also validated by international Cancer Genome Consortium (ICGC) and ccRCC clinic samples. We used Database for Annotation, Visualization, and Integrated Discovery (DAVID) to performed the GO & KEGG enrichment. TIMER database was further utilized to assess its correlation with immune infiltration in ccRCC. The the CellMiner database was used to analyse the relationship between CNTNAP1 expression and drug sensitivity. Results showed CNTNAP1 was upregulated in TCGA-KIRC, ICGC and clinic samples. And CNTNAP1 expression was positively related to infiltration levels of cancer-associated fibroblast, regulatory T cells, and Myeloid-derived suppressor cells, while negatively related to eosinophils. Furthermore, we observed CNTNAP1 was appreciably positively associated with alternatively activated macrophage (M2) in ccRCC. Finally, high CNTNAP1 expression was negatively correlated with Nilotinib, Crizotinib, Eribulin mesylate, and Vinorelbine. Collectively, these results strongly suggest that CNTNAP1 might act as an immunotherapeutic target and a promising novel biomarker for ccRCC.

Molecular mechanisms in governing genomic stability and tumor suppression by the SETD2 H3K36 methyltransferase

Epigenetic dysregulation is an important contributor to carcinogenesis. This is not surprising, as chromatin-genomic DNA organized around structural histone scaffolding-serves as the template on which occurs essential nuclear processes, such as transcription, DNA replication and DNA repair. Histone H3 lysine 36 (H3K36) methyltransferases, such as the SET-domain 2 protein (SETD2), have emerged as critical tumor suppressors. Previous work on mammalian SETD2 and its counterpart in model organisms, Set2, has highlighted the role of this protein in governing genomic stability through transcriptional elongation and splicing, as well as in DNA damage response processes and cell cycle progression. A compendium of SETD2 mutations have been documented, garnered from sequenced cancer patient genome data, and these findings underscore the cancer-driving properties of SETD2 loss-of-function. In this review, we consolidate the molecular mechanisms regulated by SETD2/Set2 and discuss evidence of its dysregulation in tumorigenesis. Insight into the genetic interactions that exist between SETD2 and various canonical intracellular signaling pathways has not only empowered pharmacological intervention by taking advantage of synthetic lethality but underscores SETD2 as a druggable target for precision cancer therapy.

Sunitinib increases the cancer stem cells and vasculogenic mimicry formation via modulating the lncRNA-ECVSR/ERβ/Hif2-α signaling

Sunitinib is the first-line drug for treating renal cell carcinoma (RCC), and it functions mainly through inhibition of tumor angiogenesis. However, the patients may become insensitive or develop resistance toward sunitinib treatment, but the underlying mechanisms have not yet been fully elucidated. Herein, it was found that sunitinib could have adverse effects of promoting RCC progression by increasing vascular mimicry (VM) formation of RCC cells. Mechanism dissection revealed that sunitinib can increase the expression of a long non-coding RNA (lncRNA), lncRNA-ECVSR, thereby enhancing the stability of estrogen receptor β (ERβ) mRNA. Subsequently, the increased ERβ expression can then function via transcriptional up-regulation of Hif2-α. Notably, sunitinib-increased lncRNA-ECVSR/ERβ/Hif2-α signaling resulted in an increased cancer stem cell (CSC) phenotype, thereby promoting VM formation. Furthermore, the sunitinib/lncRNA-ECVSR-increased ERβ expression can transcriptionally regulate lncRNA-ECVSR expression via a positive-feedback loop. Supportively, preclinical studies using RCC mouse xenografts demonstrated that combining sunitinib with the small molecule anti-estrogen PHTPP can increase sunitinib efficacy with reduced VM formation. Collectively, the findings of this study may aid in the development of potential biomarker(s) and novel therapies to better monitor and suppress RCC progression.

BRCA1-Associated Protein 1 (BAP-1) as a Prognostic and Predictive Biomarker in Clear Cell Renal Cell Carcinoma: A Systematic Review

BACKGROUND: The gene that encodes BRCA1-associated protein 1 (BAP1) has been reported to be dysregulated in several human cancers such as uveal melanoma, malignant pleural mesothelioma, hepatocellular carcinoma, thymic epithelial tumors, and clear-cell renal cell carcinoma (ccRCC). The gene is located on the human chromosome 3p21.3, encoding a deubiquitinase and acts as a classic two-hit tumor suppressor gene. BAP1 predominantly resides in the nucleus, where it interacts with several chromatin-associated factors, as well as regulates calcium signaling in the cytoplasm. As newer therapies continue to evolve for the management of RCC, it is important to understand the role of BAP1 mutation as a prognostic and predictive biomarker. OBJECTIVE: We aimed to systematically evaluate the role of BAP1 mutations in patients with RCC in terms of its impact on prognosis and its role as a predictive biomarker. METHODS: Following PRISMA guidelines, we performed a systematic literature search using PubMed and Embase through March 2021. Titles and abstracts were screened to identify articles for full-text and then a descriptive review was performed. RESULTS: A total of 490 articles were initially identified. Ultimately 71 articles that met our inclusion criteria published between 2012–2021 were included in the analysis. Data were extracted and organized to reflect the role of BAP1 alterations as a marker of prognosis as well as a marker of response to treatments, such as mTOR inhibitors, VEGF tyrosine kinase inhibitors, and immune checkpoint inhibitors. CONCLUSIONS: Alterations in BAP1 appear to be uniformly associated with poor prognosis in patients with RCC. Knowledge gaps remain with regard to the predictive relevance of BAP1 alterations, especially in the context of immunotherapy. Prospective studies are required to more precisely ascertain the predictive value of BAP1 alterations in RCC.

Screening Novel Drug Candidates for Kidney Renal Clear Cell Carcinoma Treatment: A Study on Differentially Expressed Genes through the Connectivity Map Database

OBJECTIVE

Kidney renal clear cell carcinoma (KIRC) is a common cancer with high morbidity and mortality in renal cancer. Thus, the transcriptome data of KIRC patients in The Cancer Genome Atlas (TCGA) database were analyzed and drug candidates for the treatment of KIRC were explored through the connectivity map (CMap) database.

METHODS

The transcriptome data of KIRC patients were downloaded from TCGA database, and KIRC-associated hub genes were screened out through differential analysis and protein-protein interaction (PPI) network analysis. Afterward, the CMap database was used to select drug candidates for KIRC treatment, and the drug-targeted genes were obtained through the STITCH database. A PPI network was constructed by combining drug-targeted genes with hub genes that affected the pathogenesis of KIRC to obtain final hub genes. Finally, combining hub genes and KIRC-associated hub genes, the pathways affected by drugs were explored by pathway enrichment analysis.

RESULTS

A total of 2,312 differentially expressed genes were found in patients, which were concentrated in immune cell activity, cytokine, and chemokine secretion pathways. Drug screening disclosed 5 drug candidates for KIRC treatment: fedratinib, Ly344864, geldanamycin, AS-605240, and luminespib. Based on drug-targeted genes and KIRC-associated hub genes, 16 hub genes were screened out. Pathway enrichment analysis revealed that drugs mainly affected pathways such as neuroactive ligand pathways, cell adhesion, and chemokines.

CONCLUSION

The above results indicated that fedratinib, LY 344864, geldanamycin, AS-605240, and luminespib could be used as candidates for KIRC therapy. The findings from this study will make contributions to the treatment of KIRC in the future.

Overexpressing IFITM family genes predict poor prognosis in kidney renal clear cell carcinoma

Background

The interferon-inducible transmembrane (IFITM) proteins are localized in the endolysosomal and plasma membranes, conferring cellular immunity to various infections. However, the relationship with carcinogenesis remains poorly elucidated. In the present study, we investigated the role of IFITM in kidney renal clear cell carcinoma (KIRC).

Methods

We utilized the online databases of Oncomine, UALCAN and Human Protein Atlas to analyze the expression of IFITMs and validate their levels in human KIRC cells by qPCR and western blot. Furthermore, we evaluated prognostic significance with the Gene Expression Profiling Interactive Analysis tool (Kaplan-Meier (KM) Plotter) and delineated the immune cell infiltration profile related to IFITMs with the TIMER2.0 database.

Results

IFITMs were overexpressed in KIRC and varied in subtypes and tumor grades. High expression of IFITMs indicated a poor prognosis and more immune cell infiltration, especially endothelial cells and cancer-associated fibroblasts. IFITMs were associated with immune genes, which correlated with poor prognosis of renal clear cell carcinoma. We also explored the enriched network of IFITMs co-occurrence genes and their targeted transcription factors and miRNA. The expression of IFITMs correlated with hub mutated genes of KIRC.

Conclusions

IFITMs play a crucial role in the oncogenesis of KIRC and could be a potential surrogate marker for treatment response to targeted therapies.

Risk Scores Based on Six Survival-Related RNAs in a Competing Endogenous Network Composed of Differentially Expressed RNAs Between Clear Cell Renal Cell Carcinoma Patients Carrying Wild-Type or Mutant Von Hippel-Lindau Serve Well to Predict Malignancy and Prognosis

Clear cell renal cell carcinoma (ccRCC) carrying wild-type Von Hippel–Lindau (VHL) tumor suppressor are more invasive and of high morbidity. Concurrently, competing endogenous RNA (ceRNA) network has been suggested to play an important role in ccRCC malignancy. In order to understand why the patients carrying wild-type VHL gene have high degrees of invasion and morbidity, we applied bioinformatics approaches to identify 861 differentially expressed RNAs (DE-RNAs) between patients carrying wild-type and patients carrying mutant VHL from The Cancer Genome Atlas (TCGA) database, established a ceRNA network including 122 RNAs, and elected six survival-related DE-RNAs including Linc00942, Linc00858, RP13_392I16.1, hsa-miR-182-5p, hsa-miR-183-5p, and PAX3. Examining clinical samples from our hospital revealed that patients carrying wild-type VHL had significantly higher levels of all six RNAs than those carrying mutant VHL. Patients carrying wild-type VHL had significantly higher risk scores, which were calculated based on expression levels of all six RNAs, than those carrying mutant VHL. Patients with higher risk scores had significantly shorter survival times than those with lower risk scores. Therefore, the risk scores serve well to predict malignancy and prognosis.

Natural history of Von Hippel-Lindau disease-associated and sporadic clear cell renal cell carcinoma: a comparative study

PURPOSE

To compare the tumor growth kinetics between sporadic clear cell renal cell carcinoma (ccRCC) and Von Hippel-Lindau disease-associated renal cell carcinoma (VHL-associated RCC). To analyze predictive markers for the growth rate of these two types of RCC.

METHODS

The clinical data of patients with renal tumors who received active surveillance were collected retrospectively. Immunohistochemical staining was utilized to analyze the expression levels of VHL, PBRM1, H3K36me3, and BAP1 in the postoperative specimens.

RESULTS

The age of the VHL group was significantly younger than that of the sporadic group (P < 0.0001). The mean linear growth rate (LGR) was significantly faster in the sporadic group (P = 0.0004). The tumors of those in the sporadic group tended to have a higher histologic grade (P = 0.0011). In the sporadic group, tumor histologic grade was an independent predictor for rapid mean LGR (P = 0.0022). In the VHL group, initial maximal tumor diameter (MTD) was the only independent predictor for rapid mean LGR (P < 0.0001). Tumors with low VHL expression and negative PBRM1 expression showed a faster growth rate in the sporadic group (P = 0.001 and P = 0.008, respectively). The expression levels of the four biomarkers showed no impact on the tumor growth rate in the VHL group.

CONCLUSION

Sporadic ccRCC grew faster than VHL-associated RCC. High histologic grade, low VHL expression and negative PBRM1 expression were predictors of faster growth in sporadic ccRCC. A large initial MTD was a predictor of faster growth for VHL-associated RCC.

KPNA2 promotes renal cell carcinoma proliferation and metastasis via NPM

Karyopherin α2 (KPNA2), involved in nucleocytoplasmic transport, has been reported to be up‐regulated in tumorigenesis. However, comprehensive studies of KPNA2 functions in renal cell carcinoma (RCC) are still lacking. In this study, we aim to investigate the roles of KPNA2 in kidney tumour development. Our results showed that down‐regulation of KPNA2 inhibited the proliferation and invasion of kidney tumour cell cells in vitro, while the cell cycle arrest and cellular apoptosis were induced once KPNA2 was silenced. Repression of KPNA2 was proved to be efficient to repress tumorigenesis and development of kidney tumour in in nude mice. Furthermore, one related participator, NPM, was identified based on Co‐IP/MS and bioinformatics analyses. The up‐regulation of NPM attenuates the efficiency of knockdown KPNA2. These results indicated that KPNA2 may regulate NPM to play a crucial role for kidney tumour development.

[Biomarkers for renal cell tumours]

During the last three decades, renal tumours have become increasingly well differentiated on the basis of their histopathological and molecular features. This subtyping has increasingly impacted clinical practice because more therapeutic options are available in organ-confined and metastatic renal cell tumours. The knowledge of the underlying molecular alterations is essential to develop molecular targeted therapies and to select the most effective systemic therapy for each patient. This manuscript gives an overview of the molecular differentiation on the one hand, and on diagnostic, prognostic and predictive biomarkers on the other hand.

Prevalence and Landscape of Actionable Genomic Alterations in Renal Cell Carcinoma

PURPOSE

We report our experience with next-generation sequencing to characterize the landscape of actionable genomic alterations in renal cell carcinoma (RCC).

EXPERIMENTAL DESIGN

A query of our institutional clinical sequencing database (MSK-IMPACT) was performed that included tumor samples from 38,468 individuals across all cancer types. Somatic variations were annotated using a precision knowledge database (OncoKB) and the available clinical data stratified by level of evidence. Alterations associated with response to immune-checkpoint blockade (ICB) were analyzed separately; these included DNA mismatch repair (MMR) gene alterations, tumor mutational burden (TMB), and microsatellite instability (MSI). Data from The Cancer Genome Atlas (TCGA) consortium as well as public data from several clinical trials in metastatic RCC were used for validation purposes. Multiregional sequencing data from the TRAcking Cancer Evolution through Therapy (TRACERx) RENAL cohort were used to assess the clonality of somatic mutations.

RESULTS

Of the 753 individuals with RCC identified in the MSK-IMPACT cohort, 115 showed evidence of targetable alterations, which represented a prevalence of 15.3% [95% confidence interval (CI), 12.7%-17.8%). When stratified by levels of evidence, the alterations identified corresponded to levels 2 (11.3%), 3A (5.2%), and 3B (83.5%). A low prevalence was recapitulated in the TCGA cohort at 9.1% (95% CI, 6.9%-11.2%). Copy-number variations predominated in papillary RCC tumors, largely due to amplifications in the MET gene. Notably, higher rates of actionability were found in individuals with metastatic disease (stage IV) compared with those with localized disease (OR, 2.50; 95% CI, 1.16-6.16; Fisher's P = 0.01). On the other hand, the prevalence of alterations associated with response to ICB therapy was found to be approximately 5% in both the MSK-IMPACT and TCGA cohorts and no associations with disease stage were identified (OR, 1.35; 95% CI, 0.46-5.40; P = 0.8). Finally, multiregional sequencing revealed that the vast majority of actionable mutations occurred later during tumor evolution and were only present subclonally in RCC tumors.

CONCLUSIONS

RCC harbors a low prevalence of clinically actionable alterations compared with other tumors and the evidence supporting their clinical use is limited. These aberrations were found to be more common in advanced disease and seem to occur later during tumor evolution. Our study provides new insights on the role of targeted therapies for RCC and highlights the need for additional research to improve treatment selection using genomic profiling.

Detection of von Hippel-Lindau gene mutation in circulating cell-free DNA for clear cell renal cell carcinoma

The therapeutic landscape of metastatic clear cell renal cell carcinoma (ccRCC) has rapidly expanded, and there is an urgent need to develop noninvasive biomarkers that can select an optimal therapy or evaluate the response in real time. To evaluate the clinical utility of circulating tumor DNA (ctDNA) analysis in ccRCC, we established a highly sensitive assay to detect mutations in von Hippel‐Lindau gene (VHL) using a combination of digital PCR and multiplex PCR–based targeted sequencing. The unique assay could detect VHL mutations with a variant allele frequency (VAF) <1.0%. Further, we profiled the mutation status of VHL in 76 cell‐free DNA (cfDNA) and 50 tumor tissues from 56 patients with ccRCC using the assay. Thirteen VHL mutations were identified in cfDNA from 12 (21.4%) patients with a median VAF of 0.78% (range, 0.13%‐4.20%). Of the 28 patients with VHL mutations in matched tumor tissues, eight (28.6%) also had VHL mutation in cfDNA with a median VAF of 0.47% (range, 0.13%‐2.88%). In serial ctDNA analysis from one patient, we confirmed that the VAF of VHL mutation changed consistent with tumor size by radiographic imaging during systemic treatment. In conclusion, VHL mutation in cfDNA was detected only in a small number of patients even using the highly sensitive assay; nevertheless, we showed the potential of ctDNA analysis as a novel biomarker in ccRCC.

The Molecular Characteristics of Non-Clear Cell Renal Cell Carcinoma: What's the Story Morning Glory?

Non-clear cell renal cell carcinomas are a miscellaneous group of tumors that include different histological subtypes, each one characterized by peculiarity in terms of genetic alteration, clinical behavior, prognosis, and treatment response. Because of their low incidence and poor enrollment in clinical trials, alongside their heterogeneity, additional efforts are required to better unveil the pathogenetic mechanisms and, consequently, to improve the treatment algorithm. Nowadays, tyrosine kinase inhibitors, mTOR and MET inhibitors, and even cisplatin-based chemotherapy and immunotherapy are potential weapons that are still under evaluation in this setting. Various biomarkers have been evaluated for detecting progression and monitoring renal cell carcinoma, but more studies are necessary to improve this field. In this review, we provide an overview on the molecular characteristics of this group of tumors and the recently published trials, giving an insight into what might become the future therapeutic standard in this complex world of non-clear cell kidney cancers.

Gene Expression Signature Correlates with Outcomes in Metastatic Renal Cell Carcinoma Patients Treated with Everolimus Alone or with a Vascular Disrupting Agent

Everolimus monotherapy use for metastatic renal cell carcinoma (mRCC) has diminished due to recent approvals of immune checkpoint and VEGF inhibitors. We hypothesized that gene expression associated with everolimus benefit may provide rationale to select appropriate patients. To address this hypothesis, tumors from a phase I/II trial that compared everolimus alone or with BNC105P, a vascular disrupting agent, were profiled using Nanostring as a discovery cohort. A phase III trial (CheckMate 025) was used for validation. Clinical benefit (CB) was defined as response or stable disease for ≥6 months. A propensity score covariate adjustment was used, and model discrimination performance was assessed using the area under the ROC curve (AUC). In a discovery cohort of 82 patients, 35 (43%) were treated with everolimus alone and 47 (57%) received everolimus + BNC105P. Median PFS (mPFS) was 4.9 (95% CI, 2.8-6.2) months. A four-gene signature (ASXL1, DUSP6, ERCC2, and HSPA6) correlated with CB with everolimus ± BNC105P [AUC, 86.9% (95% CI, 79.2-94.7)]. This was validated in 130 patients from CheckMate 025 treated with everolimus [AUC, 60.2% (95% CI, 49.7-70.7)]. Among 43 patients (52.4%) with low expression of an 18-gene signature, everolimus + BNC105P was associated with significantly longer mPFS compared with everolimus alone (10.4 vs. 6.9 months; HR, 0.49; 95% CI, 0.24-1.002; P = 0.047). These signatures warrant further validation to select patients who may benefit from everolimus alone or with a vascular disrupting agent.

Making Patient-Specific Treatment Decisions Using Prognostic Variables and Utilities of Clinical Outcomes

We argue that well-informed patient-specific decision-making may be carried out as three consecutive tasks: (1) estimating key parameters of a statistical model, (2) using prognostic information to convert these parameters into clinically interpretable values, and (3) specifying joint utility functions to quantify risk-benefit trade-offs between clinical outcomes. Using the management of metastatic clear cell renal cell carcinoma as our motivating example, we explain the role of prognostic covariates that characterize between-patient heterogeneity in clinical outcomes. We show that explicitly specifying the joint utility of clinical outcomes provides a coherent basis for patient-specific decision-making.