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MTHFD2 links RNA methylation to metabolic reprogramming in renal cell carcinoma.

ABSTRACT: One-carbon metabolism plays a central role in a broad array of metabolic processes required for the survival and growth of tumor cells. However, the molecular basis of how one-carbon metabolism may influence RNA methylation and tumorigenesis remains largely unknown. Here we show MTHFD2, a mitochondrial enzyme involved in one-carbon metabolism, contributes to the progression of renal cell carcinoma (RCC) via a novel epitranscriptomic mechanism that involves HIF-2α. We found that expression of MTHFD2 was significantly elevated in human RCC tissues, and MTHFD2 knockdown strongly reduced xenograft tumor growth. Mechanistically, using an unbiased methylated RNA immunoprecipitation sequencing (meRIP-Seq) approach, we found that MTHFD2 plays a critical role in controlling global N⁶-methyladenosine (m⁶A) methylation levels, including the m⁶A methylation of HIF-2α mRNA, which results in enhanced translation of HIF-2α. Enhanced HIF-2α translation, in turn, promotes the aerobic glycolysis, linking one-carbon metabolism to HIF-2α-dependent metabolic reprogramming through RNA methylation. Our findings also suggest that MTHFD2 and HIF-2α form a positive feedforward loop in RCC, promoting metabolic reprograming and tumor growth. Taken together, our results suggest that MTHFD2 links RNA methylation status to the metabolic state of tumor cells in RCC.

SUBMITTER: Green NH

PROVIDER: S-EPMC8040069 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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MTHFD2 links RNA methylation to metabolic reprogramming in renal cell carcinoma.

Green Nathanael H NH Galvan Daniel L DL Badal Shawn S SS Chang Benny H BH LeBleu Valerie S VS Long Jianyin J Jonasch Eric E Danesh Farhad R FR

Oncogene 20190709 34

One-carbon metabolism plays a central role in a broad array of metabolic processes required for the survival and growth of tumor cells. However, the molecular basis of how one-carbon metabolism may influence RNA methylation and tumorigenesis remains largely unknown. Here we show MTHFD2, a mitochondrial enzyme involved in one-carbon metabolism, contributes to the progression of renal cell carcinoma (RCC) via a novel epitranscriptomic mechanism that involves HIF-2α. We found that expression of MTH ...[more]

PMID: 31289360

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Project description:Renal cell carcinoma (RCC) is the most common type of cancer in kidney and is often diagnosed in advanced stages. Until now, there is no reliable biomarker to assess tumor prognosis during histopathological diagnosis. The Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) overexpression has been suggested as prognostic indicator for RCC, however, its protein profile needs to be clarified. This study investigated the MTHFD2 expression in different RCC cohorts, associating it with tumor characteristics and prognostic factors. Gene expression comparisons between non-neoplastic (NN) and tumor samples, as well as patients' survival analysis, were assessed using KM-Plotter tool. MTHFD2 protein pattern was evaluated in 117 RCC by immunohistochemistry and associations with prognosis, clinical and pathological data were investigated. The tumors exhibited higher MTHFD2 transcript levels than NN, being even higher in the metastatic group. Opposite gene expression patterns were found among clear cell renal cell carcinoma (ccRCC) and pappilary renal cell carcinoma (pRCC) subtypes, showing higher and lower expressions compared to NN samples respectively. Overexpression was associated with shorter overall survival for ccRCC and pRCC subtypes, and shorter recurrence-free survival for pRCC. The immunolabeling profile varied according to tumor subtypes, with lower intensity and expression scores in ccRCC compared to pRCC and to chromophobe renal cell carcinoma (chRCC). MTHFD2 protein expression was associated with larger tumors and higher Fuhrman grades. Although prognostic value of protein immunostaining was not confirmed, patients with higher MTHFD2 tended to have lower survival rates in the pRCC group. The results highlight MTHFD2 different patterns according to RCC histological subtypes, revealing marked variations at both the genetic and protein levels. The mRNA indicated tumor prognosis, and greater expression in the tumor samples. Although MTHFD2 immunolabeling suggests tumor aggressiveness, it needs to be validated in other cohorts as potential prognostic factor.

Project description:Renal cell carcinoma (RCC) is frequently infiltrated by immune cells, a process which is governed by chemokines. CD8+ T cells in the RCC tumor microenvironment (TME) may be exhausted which most likely influence therapy response and survival. The aim of this study was to evaluate chemokine-driven T cell recruitment, T cell exhaustion in the RCC TME, as well as metabolic processes leading to their functional anergy in RCC. Eight publicly available bulk RCC transcriptome collectives (n=1819) and a single cell RNAseq dataset (n=12) were analyzed. Immunodeconvolution, semi-supervised clustering, gene set variation analysis and Monte Carlo-based modeling of metabolic reaction activity were employed. Among 28 chemokine genes available, CXCL9/10/11/CXCR3, CXCL13/CXCR5 and XCL1/XCR1 mRNA expression were significantly increased in RCC compared to normal kidney tissue and also strongly associated with tumor-infiltrating effector memory and central memory CD8+ T cells in all investigated collectives. M1 TAMs, T cells, NK cells as well as tumor cells were identified as the major sources of these chemokines, whereas T cells, B cells and dendritic cells were found to predominantly express the cognate receptors. The cluster of RCCs characterized by high chemokine expression and high CD8+ T cell infiltration displayed a strong activation of IFN/JAK/STAT signaling with elevated expression of multiple T cell exhaustion-associated transcripts. Chemokinehigh RCCs were characterized by metabolic reprogramming, in particular by downregulated OXPHOS and increased IDO1-mediated tryptophan degradation. None of the investigated chemokine genes was significantly associated with survival or response to immunotherapy. We propose a chemokine network that mediates CD8+ T cell recruitment and identify T cell exhaustion, altered energy metabolism and high IDO1 activity as key mechanisms of their suppression. Concomitant targeting of exhaustion pathways and metabolism may pose an effective approach to RCC therapy.

Project description:BackgroundMetabolism reprogramming is a hallmark that associates tumor growth, metastasis, progressive, and poor prognosis. However, the metabolism-related molecular patterns and mechanism in clear cell renal cell carcinoma (ccRCC) remain unclear. Herein, the purpose of this study was to identify metabolism-related molecular pattern and to investigate the characteristics and prognostic values of the metabolism-related clustering.MethodsWe comprehensively analyzed the differentially expressed genes (DEGs), and metabolism-related genes (MAGs) in ccRCC based on the TCGA database. Consensus clustering was used to construct a metabolism-related molecular pattern. Then, the biological function, molecular characteristics, Estimate/immune/stomal scores, immune cell infiltration, response to immunotherapy, and chemotherapy were analyzed. We also identified the DEGs between subclusters and constructed a poor signature and risk model based on LASSO regression cox analysis and univariable and multivariable cox regression analyses. Then, a predictive nomogram was constructed and validated by calibration curves.ResultsA total of 1942 DEGs (1004 upregulated and 838 downregulated) between ccRCC tumor and normal samples were identified, and 254 MRGs were screened out from those DEGs. Then, 526 ccRCC patients were divided into two subclusters. The 7 metabolism-related pathways enriched in cluster 2. And cluster 2 with high Estimate/immune/stomal scores and poor survival. While, cluster 1 with higher immune cell infiltrating, expression of the immune checkpoint, IFN, HLA, immune activation-related genes, response to anti-CTLA4 treatment, and chemotherapy. Moreover, we identified 295 DEGs between two metabolism-related subclusters and constructed a 15-gene signature and 9 risk factors. Then, a risk score was calculated and the patients into high- and low-risk groups in TCGA-KIRC and E-MTAB-1980 datasets. And the prediction viability of the risk score was validated by ROC curves. Finally, the clinicopathological characteristics (age and stage), risk score, and molecular clustering, were identified as independent prognostic variables, and were used to construct a nomogram for 1-, 3-, 5-year overall survival predicting. The calibration curves were used to verify the performance of the predicted ability of the nomogram.ConclusionOur finding identified two metabolism-related molecular subclusters for ccRCC, which facilitates the estimation of response to immunotherapy and chemotherapy, and prognosis after treatment.

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MTHFD2 links RNA methylation to metabolic reprogramming in renal cell carcinoma.

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MTHFD2 links RNA methylation to metabolic reprogramming in renal cell carcinoma.

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