Single-cell protein activity analysis identifies recurrence-associated renal tumor macrophages.

Clear cell renal carcinoma (ccRCC) is a heterogeneous disease with a variable post-surgical course. To assemble a comprehensive ccRCC tumor microenvironment (TME) atlas, we performed single-cell RNA sequencing (scRNA-seq) of hematopoietic and non-hematopoietic subpopulations from tumor and tumor-adjacent tissue of treatment-naive ccRCC resections. We leveraged the VIPER algorithm to quantitate single-cell protein activity and validated this approach by comparison to flow cytometry. The analysis identified key TME subpopulations, as well as their master regulators and candidate cell-cell interactions, revealing clinically relevant populations, undetectable by gene-expression analysis. Specifically, we uncovered a tumor-specific macrophage subpopulation characterized by upregulation of TREM2/APOE/C1Q, validated by spatially resolved, quantitative multispectral immunofluorescence. In a large clinical validation cohort, these markers were significantly enriched in tumors from patients who recurred following surgery. The study thus identifies TREM2/APOE/C1Q-positive macrophage infiltration as a potential prognostic biomarker for ccRCC recurrence, as well as a candidate therapeutic target.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Timing the Landmark Events in the Evolution of Clear Cell Renal Cell Cancer: TRACERx Renal.

Clear cell renal cell carcinoma (ccRCC) is characterized by near-universal loss of the short arm of chromosome 3, deleting several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cell carcinoma. We find hotspots of point mutations in the 5' UTR of TERT, targeting a MYC-MAX-MAD1 repressor associated with telomere lengthening. The most common structural abnormality generates simultaneous 3p loss and 5q gain (36% patients), typically through chromothripsis. This event occurs in childhood or adolescence, generally as the initiating event that precedes emergence of the tumor's most recent common ancestor by years to decades. Similar genomic changes drive inherited ccRCC. Modeling differences in age incidence between inherited and sporadic cancers suggests that the number of cells with 3p loss capable of initiating sporadic tumors is no more than a few hundred. Early development of ccRCC follows well-defined evolutionary trajectories, offering opportunity for early intervention.

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases.

SnapShot: Renal Cell Carcinoma.

This SnapShot summarizes current knowledge about the key features in mutational landscape, major pathways, and tumor evolution and heterogeneity in renal cell carcinoma, as well as the most recent advances in therapeutic development. To view this SnapShot, open or download the PDF.

Geographic variation of mutagenic exposures in kidney cancer genomes.

International differences in the incidence of many cancer types indicate the existence of carcinogen exposures that have not yet been identified by conventional epidemiology make a substantial contribution to cancer burden1. In clear cell renal cell carcinoma, obesity, hypertension and tobacco smoking are risk factors, but they do not explain the geographical variation in its incidence2. Underlying causes can be inferred by sequencing the genomes of cancers from populations with different incidence rates and detecting differences in patterns of somatic mutations. Here we sequenced 962 clear cell renal cell carcinomas from 11 countries with varying incidence. The somatic mutation profiles differed between countries. In Romania, Serbia and Thailand, mutational signatures characteristic of aristolochic acid compounds were present in most cases, but these were rare elsewhere. In Japan, a mutational signature of unknown cause was found in more than 70% of cases but in less than 2% elsewhere. A further mutational signature of unknown cause was ubiquitous but exhibited higher mutation loads in countries with higher incidence rates of kidney cancer. Known signatures of tobacco smoking correlated with tobacco consumption, but no signature was associated with obesity or hypertension, suggesting that non-mutagenic mechanisms of action underlie these risk factors. The results of this study indicate the existence of multiple, geographically variable, mutagenic exposures that potentially affect tens of millions of people and illustrate the opportunities for new insights into cancer causation through large-scale global cancer genomics.

An oncogenic JMJD6-DGAT1 axis tunes the epigenetic regulation of lipid droplet formation in clear cell renal cell carcinoma.

Characterized by intracellular lipid droplet accumulation, clear cell renal cell carcinoma (ccRCC) is resistant to cytotoxic chemotherapy and is a lethal disease. Through an unbiased siRNA screen of 2-oxoglutarate (2-OG)-dependent enzymes, which play a critical role in tumorigenesis, we identified Jumonji domain-containing 6 (JMJD6) as an essential gene for ccRCC tumor development. The downregulation of JMJD6 abolished ccRCC colony formation in vitro and inhibited orthotopic tumor growth in vivo. Integrated ChIP-seq and RNA-seq analyses uncovered diacylglycerol O-acyltransferase 1 (DGAT1) as a critical JMJD6 effector. Mechanistically, JMJD6 interacted with RBM39 and co-occupied DGAT1 gene promoter with H3K4me3 to induce DGAT1 expression. JMJD6 silencing reduced DGAT1, leading to decreased lipid droplet formation and tumorigenesis. The pharmacological inhibition (or depletion) of DGAT1 inhibited lipid droplet formation in vitro and ccRCC tumorigenesis in vivo. Thus, the JMJD6-DGAT1 axis represents a potential new therapeutic target for ccRCC.

Fumarate inhibits PTEN to promote tumorigenesis and therapeutic resistance of type2 papillary renal cell carcinoma.

Fumarate is an oncometabolite. However, the mechanism underlying fumarate-exerted tumorigenesis remains unclear. Here, utilizing human type2 papillary renal cell carcinoma (PRCC2) as a model, we show that fumarate accumulates in cells deficient in fumarate hydratase (FH) and inhibits PTEN to activate PI3K/AKT signaling. Mechanistically, fumarate directly reacts with PTEN at cysteine 211 (C211) to form S-(2-succino)-cysteine. Succinated C211 occludes tethering of PTEN with the cellular membrane, thereby diminishing its inhibitory effect on the PI3K/AKT pathway. Functionally, re-expressing wild-type FH or PTEN C211S phenocopies an AKT inhibitor in suppressing tumor growth and sensitizing PRCC2 to sunitinib. Analysis of clinical specimens indicates that PTEN C211 succination levels are positively correlated with AKT activation in PRCC2. Collectively, these findings elucidate a non-metabolic, oncogenic role of fumarate in PRCC2 via direct post-translational modification of PTEN and further reveal potential stratification strategies for patients with FH loss by combinatorial AKTi and sunitinib therapy.

Recurrent repeat expansions in human cancer genomes.

Expansion of a single repetitive DNA sequence, termed a tandem repeat (TR), is known to cause more than 50 diseases1,2. However, repeat expansions are often not explored beyond neurological and neurodegenerative disorders. In some cancers, mutations accumulate in short tracts of TRs, a phenomenon termed microsatellite instability; however, larger repeat expansions have not been systematically analysed in cancer3-8. Here we identified TR expansions in 2,622 cancer genomes spanning 29 cancer types. In seven cancer types, we found 160 recurrent repeat expansions (rREs), most of which (155/160) were subtype specific. We found that rREs were non-uniformly distributed in the genome with enrichment near candidate cis-regulatory elements, suggesting a potential role in gene regulation. One rRE, a GAAA-repeat expansion, located near a regulatory element in the first intron of UGT2B7 was detected in 34% of renal cell carcinoma samples and was validated by long-read DNA sequencing. Moreover, in preliminary experiments, treating cells that harbour this rRE with a GAAA-targeting molecule led to a dose-dependent decrease in cell proliferation. Overall, our results suggest that rREs may be an important but unexplored source of genetic variation in human cancer, and we provide a comprehensive catalogue for further study.

Genome-wide Screening Identifies SFMBT1 as an Oncogenic Driver in Cancer with VHL Loss.

von Hippel-Lindau (VHL) is a critical tumor suppressor in clear cell renal cell carcinomas (ccRCCs). It is important to identify additional therapeutic targets in ccRCC downstream of VHL loss besides hypoxia-inducible factor 2α (HIF2α). By performing a genome-wide screen, we identified Scm-like with four malignant brain tumor domains 1 (SFMBT1) as a candidate pVHL target. SFMBT1 was considered to be a transcriptional repressor but its role in cancer remains unclear. ccRCC patients with VHL loss-of-function mutations displayed elevated SFMBT1 protein levels. SFMBT1 hydroxylation on Proline residue 651 by EglN1 mediated its ubiquitination and degradation governed by pVHL. Depletion of SFMBT1 abolished ccRCC cell proliferation in vitro and inhibited orthotopic tumor growth in vivo. Integrated analyses of ChIP-seq, RNA-seq, and patient prognosis identified sphingosine kinase 1 (SPHK1) as a key SFMBT1 target gene contributing to its oncogenic phenotype. Therefore, the pVHL-SFMBT1-SPHK1 axis serves as a potential therapeutic avenue for ccRCC.

Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor.

Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer and has very few mutations that are shared between different patients. To better understand the intratumoral genetics underlying mutations of ccRCC, we carried out single-cell exome sequencing on a ccRCC tumor and its adjacent kidney tissue. Our data indicate that this tumor was unlikely to have resulted from mutations in VHL and PBRM1. Quantitative population genetic analysis indicates that the tumor did not contain any significant clonal subpopulations and also showed that mutations that had different allele frequencies within the population also had different mutation spectrums. Analyses of these data allowed us to delineate a detailed intratumoral genetic landscape at a single-cell level. Our pilot study demonstrates that ccRCC may be more genetically complex than previously thought and provides information that can lead to new ways to investigate individual tumors, with the aim of developing more effective cellular targeted therapies.

Unconventional mechanism of action and resistance to rapalogs in renal cancer.

mTORC1 is aberrantly activated in renal cell carcinoma (RCC) and is targeted by rapalogs. As for other targeted therapies, rapalogs clinical utility is limited by the development of resistance. Resistance often results from target mutation, but mTOR mutations are rarely found in RCC. As in humans, prolonged rapalog treatment of RCC tumorgrafts (TGs) led to resistance. Unexpectedly, explants from resistant tumors became sensitive both in culture and in subsequent transplants in mice. Notably, resistance developed despite persistent mTORC1 inhibition in tumor cells. In contrast, mTORC1 became reactivated in the tumor microenvironment (TME). To test the role of the TME, we engineered immunocompromised recipient mice with a resistance mTOR mutation (S2035T). Interestingly, TGs became resistant to rapalogs in mTORS2035T mice. Resistance occurred despite mTORC1 inhibition in tumor cells and could be induced by coculturing tumor cells with mutant fibroblasts. Thus, enforced mTORC1 activation in the TME is sufficient to confer resistance to rapalogs. These studies highlight the importance of mTORC1 inhibition in nontumor cells for rapalog antitumor activity and provide an explanation for the lack of mTOR resistance mutations in RCC patients.

Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease.

BACKGROUND: Mutations within the Von Hippel-Lindau (VHL) tumor suppressor gene are known to cause VHL disease, which is characterized by the formation of cysts and tumors in multiple organs of the body, particularly clear cell renal cell carcinoma (ccRCC). A major challenge in clinical practice is determining tumor risk from a given mutation in the VHL gene. Previous efforts have been hindered by limited available clinical data and technological constraints. METHODS: To overcome this, we initially manually curated the largest set of clinically validated VHL mutations to date, enabling a robust assessment of existing predictive tools on an independent test set. Additionally, we comprehensively characterized the effects of mutations within VHL using in silico biophysical tools describing changes in protein stability, dynamics and affinity to binding partners to provide insights into the structure-phenotype relationship. These descriptive properties were used as molecular features for the construction of a machine learning model, designed to predict the risk of ccRCC development as a result of a VHL missense mutation. RESULTS: Analysis of our model showed an accuracy of 0.81 in the identification of ccRCC-causing missense mutations, and a Matthew's Correlation Coefficient of 0.44 on a non-redundant blind test, a significant improvement in comparison to the previous available approaches. CONCLUSION: This work highlights the power of using protein 3D structure to fully explore the range of molecular and functional consequences of genomic variants. We believe this optimized model will better enable its clinical implementation and assist guiding patient risk stratification and management.

Deeply integrating latent consistent representations in high-noise multi-omics data for cancer subtyping.

Cancer is a complex and high-mortality disease regulated by multiple factors. Accurate cancer subtyping is crucial for formulating personalized treatment plans and improving patient survival rates. The underlying mechanisms that drive cancer progression can be comprehensively understood by analyzing multi-omics data. However, the high noise levels in omics data often pose challenges in capturing consistent representations and adequately integrating their information. This paper proposed a novel variational autoencoder-based deep learning model, named Deeply Integrating Latent Consistent Representations (DILCR). Firstly, multiple independent variational autoencoders and contrastive loss functions were designed to separate noise from omics data and capture latent consistent representations. Subsequently, an Attention Deep Integration Network was proposed to integrate consistent representations across different omics levels effectively. Additionally, we introduced the Improved Deep Embedded Clustering algorithm to make integrated variable clustering friendly. The effectiveness of DILCR was evaluated using 10 typical cancer datasets from The Cancer Genome Atlas and compared with 14 state-of-the-art integration methods. The results demonstrated that DILCR effectively captures the consistent representations in omics data and outperforms other integration methods in cancer subtyping. In the Kidney Renal Clear Cell Carcinoma case study, cancer subtypes were identified by DILCR with significant biological significance and interpretability.

Effect of HLA Genotype on Anti-PD-1 Antibody Treatment for Advanced Renal Cell Carcinoma in the SNiP-RCC Study.

Immune checkpoint blockade therapies are widely used for cancer treatment, including advanced renal cell carcinoma (RCC). This study aimed to investigate the impact of zygosity in HLA genes and individual HLA genotypes on the efficacy of an anti-PD-1 Ab, nivolumab, in treating advanced RCC. Patient enrollment was conducted across 23 institutions in Japan from August 19, 2019, to September 30, 2020, with follow-up concluding on March 31, 2021. HLA genotype imputation of HLA-A, B, and C, DQB1, and DRB1 loci was performed. Among 222 patients, the presence of at least one homozygosity of the HLA-II allele significantly improved the best objective response (hazard ratio, 0.34; 95% confidence interval, 0.21-0.96; p = 0.042). The HLA evolutionary divergence (HED) of the HLA-A and HLA-B loci was higher than the HLA-C (p < 0.0001 and p < 0.0001, respectively), with high HED of the HLA-B locus correlating to clinical benefits in nivolumab treatment (hazard ratio, 0.44; 95% confidence interval, 0.21-0.90; p = 0.024) and improving cancer-specific survival compared with the low group (p = 0.0202). Additionally, high HED of the HLA-B locus was correlated with the number of infiltrated CD8+ cells in the tumor microenvironment (correlation coefficient, 0.4042). These findings indicate that the diversity of the HLA-B locus plays a significant role in the anti-tumor effect of nivolumab treatment in advanced RCC, potentially offering insights for improved risk stratification in nivolumab treatment and leading to better medical management of advanced RCC.

The Immunogenomic Landscape of Peripheral High-Dose IL-2 Pharmacodynamics in Patients with Metastatic Renal Cell Carcinoma: A Benchmark for Next-Generation IL-2-Based Immunotherapies.

High-dose (HD) IL-2 was the first immuno-oncology agent approved for treating advanced renal cell carcinoma and metastatic melanoma, but its use was limited because of substantial toxicities. Multiple next-generation IL-2 agents are being developed to improve tolerability. However, a knowledge gap still exists for the genomic markers that define the target pharmacology for HD IL-2 itself. In this retrospective observational study, we collected PBMC samples from 23 patients with metastatic renal cell carcinoma who were treated with HD IL-2 between 2009 and 2015. We previously reported the results of flow cytometry analyses. In this study, we report the results of our RNA-sequencing immunogenomic survey, which was performed on bulk PBMC samples from immediately before (day 1), during (day 3), and after treatment (day 5) in cycle 1 and/or cycle 2 of the first course of HD IL-2. As part of a detailed analysis of immunogenomic response to HD IL-2 treatment, we analyzed the changes in individual genes and immune gene signatures. By day 3, most lymphoid cell types had transiently decreased, whereas myeloid transcripts increased. Although most genes and/or signatures generally returned to pretreatment expression levels by day 5, certain ones representative of B cell, NK cell, and T cell proliferation and effector functions continued to increase, along with B cell (but not T cell) oligoclonal expansion. Regulatory T cells progressively expanded during and after treatment. They showed strong negative correlation with myeloid effector cells. This detailed RNA-sequencing immunogenomic survey of IL-2 pharmacology complements results of prior flow cytometry analyses. These data provide valuable pharmacological context for assessing PBMC gene expression data from patients dosed with IL-2-related compounds that are currently in development.

LncRNA-SERB promotes vasculogenic mimicry (VM) formation and tumor metastasis in renal cell carcinoma.

A growing body of evidence shows that vasculogenic mimicry (VM) is closely related to the invasion and metastasis of many tumor cells. Although the estrogen receptor (ER) can promote initiation and progression of renal cell carcinoma (RCC), how the downstream biomolecules are involved, and the detailed mechanisms of how ER expression is elevated in RCC remain to be further elucidated. Here, we discovered that long noncoding RNA (LncRNA)-SERB is highly expressed in tumor cells of RCC patients. We used multiple RCC cells and an in vivo mouse model for our study, and results indicated that LncRNA-SERB could boost RCC VM formation and cell invasion in vitro and in vivo. Although a previous report showed that ERß can affect the VM formation in RCC, it is unclear which factor could upregulate ERß. This is the first study to show LncRNA-SERB can be the upstream regulator of ERß to control RCC progression. Mechanistically, LncRNA-SERB may increase ERß via binding to the promoter area, and ERß functions through transcriptional regulation of zinc finger E-box binding homeobox 1 (ZEB1) to regulate VM formation. These results suggest that LncRNA-SERB promotes RCC cell VM formation and invasion by upregulating the ERß/ZEB1 axis and that therapeutic targeting of this newly identified pathway may better inhibit RCC progression.

Genomic features of renal cell carcinoma developed during end-stage renal disease and dialysis.

Patients with end-stage renal disease (ESRD) or receiving dialysis have a much higher risk for renal cell carcinoma (RCC), but carcinogenic mechanisms and genomic features remain little explored and undefined. This study's goal was to identify the genomic features of ESRD RCC and characterize them for associations with tumor histology and dialysis exposure. In this study, we obtained 33 RCCs, with various histological subtypes, that developed in ESRD patients receiving dialysis and performed whole-genome sequencing and transcriptome analyses. Driver events, copy-number alteration (CNA) analysis and mutational signature profiling were performed using an analysis pipeline that integrated data from germline and somatic SNVs, Indels and structural variants as well as CNAs, while transcriptome data were analyzed for differentially expressed genes and through gene set enrichment analysis. ESRD related clear cell RCCs' driver genes and mutations mirrored those in sporadic ccRCCs. Longer dialysis periods significantly correlated with a rare mutational signature SBS23, whose etiology is unknown, and increased mitochondrial copy number. All acquired cystic disease (ACD)-RCCs, which developed specifically in ESRD patients, showed chromosome 16q amplification. Gene expression analysis suggests similarity between certain ACD-RCCs and papillary RCCs and in TCGA papillary RCCs with chromosome 16 gain identified enrichment for genes related to DNA repair, as well as pathways related to reactive oxygen species, oxidative phosphorylation and targets of Myc. This analysis suggests that ESRD or dialysis could induce types of cellular stress that impact some specific types of genomic damage leading to oncogenesis.