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

Deciphering the interplay between SETD2 mediated H3K36me3 and RNA N6-methyladenosine in clear cell renal cell carcinoma (ccRCC)

RNA N6-methyladenosine (m6A) plays diverse roles in RNA metabolism and its deregulation contributes to tumor initiation and progression. Clear cell renal cell carcinoma (ccRCC) is characterized by near ubiquitous loss of VHL followed by mutations in epigenetic regulators PBRM1, SETD2, and BAP1. Mutations in SETD2, a histone H3 lysine 36 trimethylase (H3K36me3), are associated with reduced survival, greater metastatic propensity, and metabolic reprogramming. While m6A and H3K36me3 deregulation are separately implicated in renal tumorigenesis, H3K36me3 may participate directly in m6A targeting, but the m6A-H3K36me3 interplay has not been investigated in the context of ccRCC. Using RCC-relevant SETD2 isogenic knockout and rescue cell line models, we demonstrate a dynamic redistribution of m6A in the SETD2 depleted transcriptome, with a subset of transcripts involved in metabolic reprogramming demonstrating SETD2 dependent m6A and expression level changes. Using a panel of six histone modifications we show that m6A redistributes to regions enriched in gained active enhancers upon SETD2 inactivation. Finally, we demonstrate a reversal of transcriptomic programs involved in SETD2 loss mediated metabolic reprogramming, and reduced cell viability through pharmacologic inhibition or genetic ablation of m6A writer METTL3 specific to SETD2 deficient cells. Thus, targeting m6A may represent a novel therapeutic vulnerability in SETD2 mutant ccRCC.

A war on many fronts: cross disciplinary approaches for novel cancer treatment strategies

Cancer is a disease characterized by uncontrolled cellular growth where cancer cells take advantage of surrounding cellular populations to obtain resources and promote invasion. Carcinomas are the most common type of cancer accounting for almost 90% of cancer cases. One of the major subtypes of carcinomas are adenocarcinomas, which originate from glandular cells that line certain internal organs. Cancers such as breast, prostate, lung, pancreas, colon, esophageal, kidney are often adenocarcinomas. Current treatment strategies include surgery, chemotherapy, radiation, targeted therapy, and more recently immunotherapy. However, patients with adenocarcinomas often develop resistance or recur after the first line of treatment. Understanding how networks of tumor cells interact with each other and the tumor microenvironment is crucial to avoid recurrence, resistance, and high-dose therapy toxicities. In this review, we explore how mathematical modeling tools from different disciplines can aid in the development of effective and personalized cancer treatment strategies. Here, we describe how concepts from the disciplines of ecology and evolution, economics, and control engineering have been applied to mathematically model cancer dynamics and enhance treatment strategies.

SETD2 loss in renal epithelial cells drives epithelial-to-mesenchymal transition in a TGF-β-independent manner

Histone-lysine N-methyltransferase SETD2 (SETD2), the sole histone methyltransferase that catalyzes trimethylation of lysine 36 on histone H3 (H3K36me3), is often mutated in clear cell renal cell carcinoma (ccRCC). SETD2 mutation and/or loss of H3K36me3 is linked to metastasis and poor outcome in ccRCC patients. Epithelial-to-mesenchymal transition (EMT) is a major pathway that drives invasion and metastasis in various cancer types. Here, using novel kidney epithelial cell lines isogenic for SETD2, we discovered that SETD2 inactivation drives EMT and promotes migration, invasion, and stemness in a transforming growth factor-beta-independent manner. This newly identified EMT program is triggered in part through secreted factors, including cytokines and growth factors, and through transcriptional reprogramming. RNA-seq and assay for transposase-accessible chromatin sequencing uncovered key transcription factors upregulated upon SETD2 loss, including SOX2, POU2F2 (OCT2), and PRRX1, that could individually drive EMT and stemness phenotypes in SETD2 wild-type (WT) cells. Public expression data from SETD2 WT/mutant ccRCC support the EMT transcriptional signatures derived from cell line models. In summary, our studies reveal that SETD2 is a key regulator of EMT phenotypes through cell-intrinsic and cell-extrinsic mechanisms that help explain the association between SETD2 loss and ccRCC metastasis.

A Novel Cuproptosis-Related Prognostic Model and the Hub Gene FDX1 Predict the Prognosis and Correlate with Immune Infiltration in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common malignancy of the urological system with poor prognosis. Cuproptosis is a recently discovered novel manner of cell death, and the hub gene FDX1 could promote cuproptosis. However, the potential roles of cuproptosis-related genes (CRGs) and FDX1 for predicting prognosis, the immune microenvironment, and therapeutic response have been poorly studied in ccRCC. In the present study, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data were downloaded. CRGs were subjected to prognosis analysis, and three of them were used to construct the prognostic model by least absolute shrinkage and selection operator (LASSO) regression. The CRGs prognostic model showed excellent performance. Moreover, based on the risk score of the model, the nomogram was developed to predict 1-year, 3-year, and 5-year survival. Furthermore, the hub gene of cuproptosis, FDX1, was an independent prognostic biomarker in multivariate Cox regression analysis. The pan-cancer analysis showed that FDX1 was significantly downregulated and closely related to prognosis in ccRCC among 33 cancer types. Lower FDX1 was also correlated with worse clinicopathologic features. The lower expression of FDX1 in ccRCC was verified in the external database and our own database, which may be caused by DNA methylation. We further demonstrated that the tumor mutational burden (TMB) and immune cell infiltration were related to the expression of FDX1. Immune response and drug sensitivity analysis revealed that immunotherapy or elesclomol may have a favorable treatment effect in the high FDX1 expression group and sunitinib or axitinib may work better in the low FDX1 expression group. In conclusion, we constructed a CRGs prognostic model and revealed that FDX1 could serve as a prognostic biomarker and predict therapeutic response in ccRCC. The study will provide a novel, precise, and individual treatment strategy for ccRCC patients.

Recent Insight on Regulations of FBXW7 and Its Role in Immunotherapy

SCF^FBXW7 E3 ubiquitin ligase complex is a crucial enzyme of the ubiquitin proteasome system that participates in variant activities of cell process, and its component FBXW7 (F-box and WD repeat domain–containing 7) is responsible for recognizing and binding to substrates. The expression of FBXW7 is controlled by multiple pathways at different levels. FBXW7 facilitates the maturity and function maintenance of immune cells via functioning as a mediator of ubiquitination-dependent degradation of substrate proteins. FBXW7 deficiency or mutation results in the growth disturbance and dysfunction of immune cell, leads to the resistance against immunotherapy, and participates in multiple illnesses. It is likely that FBXW7 coordinating with its regulators and substrates could offer potential targets to improve the sensitivity and effects of immunotherapy. Here, we review the mechanisms of the regulation on FBXW7 and its tumor suppression role in immune filed among various diseases (mostly cancers) to explore novel immune targets and treatments.