l-2-Hydroxyglutarate remodeling of the epigenome and epitranscriptome creates a metabolic vulnerability in kidney cancer models
Anirban Kundu, … , Jason M. Tennessen, Sunil Sudarshan
Anirban Kundu, … , Jason M. Tennessen, Sunil Sudarshan
Published May 14, 2024
Citation Information: J Clin Invest. 2024;134(13):e171294. https://doi.org/10.1172/JCI171294.
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Research Article Metabolism Oncology

l-2-Hydroxyglutarate remodeling of the epigenome and epitranscriptome creates a metabolic vulnerability in kidney cancer models

Abstract

Tumor cells are known to undergo considerable metabolic reprogramming to meet their unique demands and drive tumor growth. At the same time, this reprogramming may come at a cost with resultant metabolic vulnerabilities. The small molecule l-2-hydroxyglutarate (l-2HG) is elevated in the most common histology of renal cancer. Similarly to other oncometabolites, l-2HG has the potential to profoundly impact gene expression. Here, we demonstrate that l-2HG remodels amino acid metabolism in renal cancer cells through combined effects on histone methylation and RNA N6-methyladenosine. The combined effects of l-2HG result in a metabolic liability that renders tumors cells reliant on exogenous serine to support proliferation, redox homeostasis, and tumor growth. In concert with these data, high–l-2HG kidney cancers demonstrate reduced expression of multiple serine biosynthetic enzymes. Collectively, our data indicate that high–l-2HG renal tumors could be specifically targeted by strategies that limit serine availability to tumors.

Authors

Anirban Kundu, Garrett J. Brinkley, Hyeyoung Nam, Suman Karki, Richard Kirkman, Madhuparna Pandit, EunHee Shim, Hayley Widden, Juan Liu, Yasaman Heidarian, Nader H. Mahmoudzadeh, Alexander J. Fitt, Devin Absher, Han-Fei Ding, David K. Crossman, William J. Placzek, Jason W. Locasale, Dinesh Rakheja, Jonathan E. McConathy, Rekha Ramachandran, Sejong Bae, Jason M. Tennessen, Sunil Sudarshan

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Figure 3

l-2HG promotes mRNA m6A methylation in RCC.

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l-2HG promotes mRNA m6A methylation in RCC. (A and B) m6A dot blot of 1...
(A and B) m6A dot blot of 100 ng mRNA isolated from 786-O (A) and 769p (B) cells (n = 3, biological replicates) stably expressing control vector or L2HGDH (WT). Methylene blue blot serves as loading control. (C) Quantification of m6A normalized to methylene blue as shown in A and B. Data are shown as mean ± SD from n = 3 biological replicates. (D) LC-MS/MS analysis of m6A levels in mRNA from RXF-393 cells stably expressing control vector or L2HGDH. Data are presented as ratio of m6A to unmodified adenosine (m6A/A). Data are shown as mean ± SD from n = 4 biological replicates. (E) m6A dot blot of mRNA isolated from RXF-393 cells stably expressing control vector, L2HGDH WT, or L2HGDH mutant (A241G). (F) In vitro ALKBH5 activity with increasing concentration of l-2HG. Each data point represents mean ± error values of n = 2 technical replicates. (G) 786-O cells stably transduced with L2HGDH cDNA were transiently treated with scramble siRNA (Scr) or siRNAs targeting ALKBH5 and FTO (52 hours). mRNA was harvested and assessed for m6A via dot blot. (H) Volcano plot of m6A-Seq demonstrating relative changes in m6A peaks in mRNAs isolated from high–l-2HG control versus low–l-2HG (L2HGDH-transduced) 786-O cells n = 1 each. Red denotes higher m6A levels in high l-2HG levels. Blue denotes lower m6A levels in high l-2HG levels. (I) m6A-Seq analysis of the PSAT1 mRNA from 786-O control (high–l-2HG) and L2HGDH (low–l-2HG) cells. For each condition, enrichment is displayed as RNA m6A-immunoprecipitated (RIP) normalized to the corresponding input. (J) m6A immunoprecipitation RT-qPCR was used to assess m6A enrichment in the PSAT1 3′-UTR from 786-O cells stably transduced with the indicated vector. PSAT1-1F/1R primer pair was used. Data are represented as mean ± SD from n = 3 biological replicates.