Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
[Preprint]. 2025 Aug 22:2025.05.28.656673.
doi: 10.1101/2025.05.28.656673.

OGDHL regulates tumor growth, neuroendocrine marker expression, and nucleotide abundance in prostate cancer

Affiliations

OGDHL regulates tumor growth, neuroendocrine marker expression, and nucleotide abundance in prostate cancer

Matthew J Bernard et al. bioRxiv. .

Abstract

As cancer cells evade therapeutic pressure and adopt alternate lineage identities not commonly observed in the tissue of origin, they likely adopt alternate metabolic programs to support their evolving demands. Targeting these alternative metabolic programs in distinct molecular subtypes of aggressive prostate cancer may lead to new therapeutic approaches to combat treatment-resistance. We identify the poorly studied metabolic enzyme Oxoglutarate Dehydrogenase-Like (OGDHL), named for its structural similarity to the tricarboxylic acid (TCA) cycle enzyme Oxoglutarate Dehydrogenase (OGDH), as an unexpected regulator of tumor growth, treatment-induced lineage plasticity, and DNA Damage in prostate cancer. While OGDHL has been described as a tumor-suppressor in various cancers, we find that its loss impairs prostate cancer cell proliferation and tumor formation. Loss of OGDHL profoundly alters Androgen Receptor inhibition-induced plasticity, including suppressing the neuroendocrine markers DLL3 and HES6, induces accumulation of the DNA damage response marker ƔH2AX, and reduces nucleotide synthesis. Our data suggest that OGDHL has minimal impact on TCA cycle activity, and that mitochondrial localization is not required for its regulation of prostate cancer plasticity and nucleotide metabolism. Finally, we demonstrate that OGDHL expression is tightly correlated with neuroendocrine differentiation in clinical prostate cancer. These findings underscore the importance of investigating poorly characterized metabolic genes as potential regulators of distinct molecular subtypes of aggressive cancer.

PubMed Disclaimer

Figures

Figure 1:
Figure 1:. OGDHL supports proliferation of Enzalutamide-resistant prostate cancer cells in vitro and in vivo
(A and B) 18F-FDG PET signal (A) or 18F-BnTP PET signal (B) in MDA PCa 180-30 CRPC tumors treated with Enza or Vehicle for 14 Days. (C) RNA expression of Canonical TCA cycle genes in Enza-Resistant (EnzaR) 16D Cells relative to Enza-naïve cells. (D) Western Blot of changes in OGDHL, PSA and OGDH in response to acquisition of Enza-resistance in 16DCRPC cells. (E and F) Western Blot of elevated OGDHL expression in MDA PCa 180-30 derived xenografts (E), and quantification of in vivo western blot (F). (G) Relative change in cell viability over 48 hours with OGDHL overexpression. Plotted as change in viability relative to control cells. Data from 5 (16D, LNCaP) or 6 (PC3) technical replicates. (H) Relative change in cell viability over 48 hours with shRNA-mediated knockdown of OGDHL in Enza-Maintained 16D cells. Plotted as change in viability relative to control. Data from 3 biological replicate experiments with 5 technical replicates each. (I) Measured tumoroid diameter of Enza-maintained 16D cells after 2 weeks of 3D culture. Data from 3 biological replicate experiments, >50 tumoroids measured per replicate. (J) Representative images of control (shScrambled) and OGDHL knockdown (shOGDHL) tumoroids generated from Enza-Maintained 16D Cells. Scale Bar = 50 μm. (K and L) Image of tissues recovered 4 weeks after implantation in vivo from Enza-maintained 16DCRPC cells with control (Scrambled) or OGDHL knockdown. Scale Bar = 1.0 cm. (K) Measured weights of tissues recovered 4 weeks after implantation in vivo from Enza-maintained 16D Cells with control (Scrambled) or OGDHL knockdown (L). Error bars represent +/− SEM. P-value calculated by unpaired t-test with Welch’s Correction.
Figure 2:
Figure 2:. Loss of OGDHL in CRPC cells alters transcription of cell stress and cell cycle associated pathways in vitro and in vivo
(A) RNA expression of Canonical TCA cycle genes in OGDHL knockdown Enza-maintained 16DCRPC cells in vitro normalized to control knockdown values. Data represented as 3 technical replicates each from 2 shRNAs. (B) Volcano Plot of Differentially Expressed Genes in shOGDHL Enza-maintained 16DCRPC cells relative to control. Color indicates FDR < 0.05 (C) Heatmap of isolated proliferation and cell stress genes in control and OGDHL knockdown cells, with technical replicates shown. (D-F) Average expression of genes in Hallmark: G2M Checkpoint, E2F Targets, and Myc Targets v1 with Enza-Maintained 16DCRPC cells with acute knockdown of OGDHL in vitro (D), in OGDHL CRISPR knockout cell lines in vitro (E), and in tumors formed from OGDHL knockout cells (F). Data shown is average Z scores from 3 control replicates and 6 knockdown/knockout replicates in vitro or 5 control and 4 knockout replicates in vivo. Error bars represent +/− SEM. Adjusted P values were calculated by applying the Benjamini-Hochberg procedure for multiple hypothesis testing to p-values corresponding to 2-tailed t-tests.
Figure 3:
Figure 3:. OGDHL loss perturbs nucleotide pools and glucose incorporation into nucleotides
(A) Schematic of heavy-isotope (U-13C Glucose or U-13C Glutamine) nutrient tracing into TCA cycle and nucleotide metabolic intermediates. (B) M + 2 labeled ɑ-ketoglutarate from U-13C glucose in control or OGDHL knockdown Enza-maintained 16DCRPC cells. Data represent 3 technical replicate experiments for each of 2 shRNAs. (C) Volcano Plot of differentially abundant metabolites from metabolic profiling of Enza-maintained 16DCRPC cells with OGDHL or control knockdown. Highlighted metabolites are nucleotide synthesis intermediates. Line indicates FDR = 0.05. (D) Heatmap of nucleotide phosphate abundance in OGDHL knockdown and control knockdown Enza-maintained 16DCRPC cells. Data represented as row z scores from 3 technical replicates from each of 3 biological replicate lines. (E and F) Relative abundance of nucleotide synthesis intermediates Phosphoribosyl pyrophosphate (PRPP) (E) and Dihydroorotate (F) from metabolic profiling in control and OGDHL knockdown Enza-maintained 16DCRPC cells. Data from 2 biological replicate experiments (PRPP) or 3 biological replicates (Dihydroorotate) each with 3 technical replicates. (G) M + 5 labeling of pyrimidine phosphates derived from U-13C glucose in control and OGDHL knockdown Enza-maintained 16DCRPC cells. Error bars represent +/− SEM. Adjusted P values were calculated by applying the Benjamini-Hochberg procedure for multiple hypothesis testing to p-values corresponding to 2-tailed t-tests.
Figure 4:
Figure 4:. OGDHL Loss reduces nucleotide synthesis gene expression and induces DNA damage in vitro and in vivo
(A and B) Relative RNA abundance of nucleotide synthesis genes in tumors formed from 16DCRPC cells with genetic knockout of OGDHL (n =4) or a control (n = 5) (A) or OGDHL knockout cells grown in vitro (B). Data from 3 technical replicates each from 2 gRNAs. (C) Average Expression of genes in the KEGG: Pyrimidine metabolism gene set in 16DCRPC cells with genetic knockout of OGDHL. Data shown is average Z scores from 3 control replicates and 6 knockout replicates in vitro. (D and E) Average expression of genes in the Hallmark: Apoptosis (D) and Hallmark: DNA Repair (E) gene sets with acute knockdown of OGDHL. Data shown is average Z scores from 3 control replicates and 6 knockdown replicates in vitro. (F-H) Western blot of the DNA damage marker ƔH2AX and OGDHL expression in control and OGDHL knockdown cells in vitro (F), in cells recovered 4 days after implantation in vivo (G) and in cells recovered 4 weeks after implantation in vivo (H). Error bars represent +/− SEM. Adjusted P values were calculated by applying the Benjamini-Hochberg procedure for multiple hypothesis testing to p-values corresponding to 2-tailed t-tests.
Figure 5:
Figure 5:. OGDHL mediates lineage plasticity phenotypes and NE marker expression in prostate cancer
(A-C) Average expression of genes in Gene Ontology Biological Pathway Gene Set: Axon Guidance (A), Hallmark: Epithelial Mesenchymal Transition (B) and Hallmark: Androgen Response (C) gene sets in 16DCRPC cells with CRISPR-Cas9 mediated genetic knockout of OGDHL allowed to adapt to enzalutamide for 6 weeks in vitro. Data shown is average Z scores from 3 control replicates (+/− Enza) and 6 knockout replicates (+Enza) in vitro. (D) mRNA expression of NEPC gene HES6 in 16DCRPC cells with genetic knockout of OGDHL cultured in vitro. (E and F) mRNA expression of NEPC genes HES6 (E) and DLL3 (F) in tumors formed from 16DCRPC cells with genetic knockout of OGDHL (n =4) or control cells (n = 5). (G) Average expression of HES6 target genes in tumors formed from 16DCRPC cells with genetic knockout of OGDHL (n =4) or control (n = 5). (H) Western blot of DLL3 and HES6 in control and OGDHL knockdown cell lines cells recovered 4 days after implantation in vivo. Error bars represent +/− SEM. P-value calculated by unpaired t-test with Welch’s Correction.
Figure 6:
Figure 6:. Mitochondrial localization of OGDHL is not required to regulate lineage and nucleotide phenotypes
(A) Schematic of CRISPR-resistant Full Length (FL) and mitochondrial targeting sequence deletion (ΔMTS) OGDHL variants and validation of protein expression. (B) Immunofluorescence validation of OGDHL subcellular localization in 16DCRPC cells with CRISPR-Cas9 mediated genetic knockout of OGDHL and expression of knockout-resistant FL and ΔMTS variants. (C) Representative image of subcellular localization of endogenous OGDHL in enza-maintained 16DCRPC cells. (D and E) Quantification of mitochondrial (D) and nuclear (E) localization of OGDHL. Data represented as % of OGDHL signal overlapping with the mitochondrial marker TUFM (D) or the nuclear stain DAPI (E). Each data point represents a single cell. (F-H) Average expression of genes in the KEGG: Pyrimidine Metabolism (F) and HES6 Target Gene Set (G) and Hallmark: Myc Targets v1 (H) gene sets in 16DCRPC cells with CRISPR-Cas9 mediated genetic knockout of OGDHL or reintroduction of knockout-resistant FL and ΔMTS variants. Data show average Z scores or TPM values from 3 technical replicates each. (I) M + 5 labeling of Uridine phosphates derived from U-13C glucose in enza-maintained 16DCRPC cells with genetic knockdown of OGDHL and expression of knockdown-resistant FL and ΔMTS variants. Data represent 3 technical replicates each. Error bars represent +/− SEM. P-value calculated by unpaired t-test with Welch’s Correction.
Figure 7:
Figure 7:. OGDHL expression is elevated in Neuroendocrine Prostate Cancer
(A) Volcano plot of differentially expressed genes correlated with disease progression in the Ku et al. GEMM data set. Highlighted genes correspond to an FDR < 0.05. Names of the top 10 differentially regulated TCA cycle genes are displayed. (B and C) OGDHL mRNA expression in a GEMM model (B) of prostate adenocarcinoma (pten-null (SKO)) (n=4) and NEPC (pten;Rb1;TP53-null (TKO)) (n = 6) or in patients (C) with Adenocarcinoma (CRPC-Adeno) or NEPC (From Beltran et al.). (D-F) OGDHL mRNA in clinical metastatic CRPC specimens (D), surgically resected tissue from patients who died from metastatic CRPC (E), and in Patient Derived Xenograft models of CRPC based on AR expression and NE features,. (G) OGDHL mRNA expression in Circulating Tumor Cells (CTCs) from metastatic CRPC based on profiled subtype from the Sharifi et al. dataset. Error bars represent +/− SEM. P-value calculated by unpaired t-test with Welch’s Correction.

References

    1. Finley L. W. S. What is cancer metabolism? Cell 186, 1670–1688 (2023). - PMC - PubMed
    1. Kinnaird A., Zhao S., Wellen K. E. & Michelakis E. D. Metabolic control of epigenetics in cancer. Nat. Rev. Cancer 16, 694–707 (2016). - PubMed
    1. Shapira S. N. & Christofk H. R. Metabolic Regulation of Tissue Stem Cells. Trends Cell Biol. 30, 566–576 (2020). - PMC - PubMed
    1. DeBerardinis R. J. & Chandel N. S. Fundamentals of cancer metabolism. Sci. Adv. 2, e1600200 (2016). - PMC - PubMed
    1. Faubert B., Solmonson A. & DeBerardinis R. J. Metabolic reprogramming and cancer progression. Science 368, eaaw5473 (2020). - PMC - PubMed

Publication types