Downregulated METTL14 accumulates BPTF that reinforces super-enhancers and distal lung metastasis via glycolytic reprogramming in renal cell carcinoma

Abstract

Background: Methyltransferase-like 14 (METTL14) participates in tumorigenesis in several malignancies, but how METTL14 mediates the metastasis of renal cell carcinoma (RCC) has never been reported. Methods: Western blotting, quantitative real-time PCR, and immunohistochemistry were used to determine the mRNA and protein levels of relevant genes. Methylated RNA immunoprecipitation sequencing and RNA sequencing were utilized to screen potential targets of METTL14. Chromatin immunoprecipitation sequencing and assay for transposase-accessible chromatin sequencing were performed to investigate epigenetic alterations. The biological roles and mechanisms of METTL14/BPTF in promoting lung metastasis were confirmed in vitro and in vivo using cell lines, patient samples, xenograft models, and organoids. Results: Utilizing the TCGA-KIRC and Ruijin-RCC datasets, we found low expression of METTL14 in mRCC samples, which predicted poor prognosis. METTL14 deficiency promoted RCC metastasis in vitro and in vivo . Mechanistically, METTL14-mediated m 6 A modification negatively regulated the mRNA stability of bromodomain PHD finger transcription factor (BPTF) and depended on BPTF to drive lung metastasis. Accumulated BPTF in METTL14-deficient cells remodeled the enhancer landscape to reinforce several oncogenic crosstalk. Particularly, BPTF constituted super-enhancers that activate downstream targets like enolase 2 and SRC proto-oncogene nonreceptor tyrosine kinase, leading to glycolytic reprogramming of METTL14 -/- cells. Finally, we determined the efficacy of the BPTF inhibitor AU1 in suppressing mRCC of patient-derived cells, mRCC-derived organoids (MDOs), and orthotopic xenograft models. Conclusions: Our study is the first to investigate the essential role of m 6 A modification and the METTL14/BPTF axis in the epigenetic and metabolic remodeling of mRCC, highlighting AU1 as a vital therapeutic candidate.

TRIM38 triggers the ubiquitination and degradation of glucose transporter type 1 (GLUT1) to restrict tumor progression in bladder cancer

“…The key characteristic of cancer cell metabolism is the efficiency to obtain essential nutrients from microenvironment and adopt the nutrients to maintain cell viability and create new biomass. Aerobic glycolysis, also named as the Warburg effect, is considered to be a prominent hallmark in tumor cells, which is depicted by elevated glucose uptake and lactate production in the normal oxygen conditions [ 26 ]. As well documented, the high glycolytic flux in tumor cells relys on glycolysis-associated signature, including GLUT3, SRC-3, hexokinase 1 (HK1), as well as lactic dehydrogenase A (LDHA), leading to production of pyruvate, alanine, and lactate [ 27 , 28 ].…”

Oncogenic Chromatin Modifier KAT2A Activates MCT1 to Drive the Glycolytic Process and Tumor Progression in Renal Cell Carcinoma

“…How to identify novel biomarkers and therapeutic targets are promising to optimize the current treatment of RCC. It has been well-known that loss-of-function mutations and abnormal expressions of epigenetic drivers could result in tumorigenesis and progression of RCC ( Nargund et al, 2017 ; Zhang et al, 2021a , b ). Apart from aberrant classical chromatin regulator genes like VHL , PBRM1 , BAP1 , and SETD2 , the existence of other epigenetic vulnerability in RCC remains unclear.…”

A comprehensive investigation of m6A regulators prognostic value and associated molecular pathways in breast invasive cancer

“…Furthermore, expression level and function variation of m 6 A genes among the cancer types may imply the tumor type-specific roles of this pathway. As an example, METTL14 can act as a tumor-suppressor as in colorectal cancer [73], renal cell carcinoma [74] and breast cancer [75], or oncogene as in pancreatic cancer [76] which might be due to the target RNA composition specific to cancer types. Therefore, as performed in this study, analysis of these genes using the comprehensive datasets would be more informative to approximate the exact function of the genes across the possible multiple roles of m 6 A pathway components in investigated cancers.…”