The multifaceted role of EGLN family prolyl hydroxylases in cancer: going beyond HIF regulation

Strocchi, Silvia; Reggiani, Francesca; Gobbi, Giulia; Ciarrocchi, Alessia; Sancisi, Valentina

doi:10.1038/s41388-022-02378-8

Cited by 9 publications

(7 citation statements)

References 127 publications

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“…Here, we demonstrated that 41 α-KG-dependent dioxygenase-encoding genes can function as surrogate indicators for IDH mutation. Among them, EGLN1 and EGLN3, two α-KG-dependent dioxygenases of the EglN prolyl-4-hydroxylase family ( 21 ), were upregulated in IDH mutant LGG patients and served as favorable indicators for LGG prognosis, which is consistent with previous studies proving that 2-HG specifically increased the activity of EglN enzymes in human astrocytes ( 22 ) and that overexpression of EGLN3 could suppress tumor progression of glioma models by normalized glioma capillary architecture and tightly associated with hypoxic environment ( 23 , 24 ). As the main component of the extracellular matrix, collagen can modify tumor cell behavior and promote tumor development ( 25 ).…”

Section: Discussionsupporting

confidence: 88%

Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles

et al. 2022

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The inhibition of alpha-ketoglutarate (α-KG)-dependent dioxygenases is thought to contribute to isocitrate dehydrogenase (IDH) mutation-derived malignancy. Herein, we aim to thoroughly investigate the expression pattern and prognostic significance of genes encoding α-KG-dependent enzymes for lower-grade glioma (LGG) patients. In this retrospective study, a total of 775 LGG patients were enrolled. The generalized linear model, least absolute shrinkage and selection operator Cox regression, and nomogram were applied to identify the enzyme-based signature. With the use of gene set enrichment analysis and Gene Ontology, the probable molecular abnormalities underlying high-risk patients were investigated. By comprehensively analyzing mRNA data, we observed that 41 genes were differentially expressed between IDHMUT and IDHWT LGG patients. A risk signature comprising 10 genes, which could divide samples into high- and low-risk groups of distinct prognoses, was developed and independently validated. This enzyme-based signature was indicative of a more malignant phenotype. The nomogram model incorporating the risk signature, molecular biomarkers, and clinicopathological parameters proved the incremental utility of the α-KG-dependent signature by achieving a more accurate prediction impact. Our study demonstrates that the α-KG-dependent enzyme-encoding genes were differentially expressed in relation to the IDH phenotype and may serve as a promising indicator for clinical outcomes of LGG patients.

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Section: Discussionsupporting

confidence: 88%

Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles

et al. 2022

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“…Finally, we compared sample-level signature scores between prognostic groups to evaluate the associations between existing prognostic prostate cancer signatures with our multi- omics signatures. Results suggested that signature 1 high-risk patients had significantly higher signature scores for a 28-gene hypoxia-related signature developed by Yang et al (Yang et al, 2018) (p=0.014), confirming the role of EGLN3 in hypoxia (Strocchi et al, 2022). However, high-risk patients of signature 2 exhibited low signature scores for Talantov(Talantov et al, 2010) (p = 0.005) and Planche (Planche et al, 2011) signatures (p=0.035).…”

Section: Resultssupporting

confidence: 63%

Multi-omics biomarkers aid prostate cancer prognostication

Omar

Benedetti

et al. 2022

Preprint

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Effective biomarkers and diagnostic tools are urgently needed in clinical settings for improved management of prostate cancer patients, especially to reduce over-treatment of indolent tumors and for early identification of aggressive disease. Gene expression signatures are currently the "gold standard" to provide guide clinical decision, however their clinical utility and interpretability is questionable. Multi-modal molecular profiling provides an holistic approach to systematically unravel the biological complexity underlying cancer pathogenesis, hence biomarkers developed using such an integrated approach hold the potential to more accurately capture cancer-driving alterations than signatures based on a single omics modality. Currently, however, robust and reproducible multi-omics biomarkers are still lacking for prostate cancer. In this study, we analyzed transcriptomics and metabolomics profiles jointly in a prostate cancer cohort and identified two prognostic signatures with high statistical powers (signature1: EGLN3, succinate, trans-4-hydroxyprolin; and signature2: IL6, SLC22A2, histamine). Our approach leveraged a priori biological knowledge of the cellular metabolism and gene circuitry, enabling the identification of dysregulated network modules. Functional bioinformatics analyses suggest that these signatures can capture relevant molecular alterations in prostate cancer tissues, including dysregulations of cellular signaling, cell cycle progression, and immune system modulation, stratifying patients in distinct risk groups. Next, we trained two gene expression signatures as a proxy for the multi-omics ones, extending our investigation to publicly available data, further confirming their prognostic values in independent patient cohorts. In summary, the analysis of multi-modal molecular grounded in cellular network biology represents a promising approach for the development of robust prognostic biomarkers of detecting and discriminating high grade disease.

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“…Egl-9 family hypoxia inducible factor 1 ( EglN1 ) is a proline hydroxylase acting as an oxygen sensor that regulates the degradation of hypoxia-inducible factor α (HIFα). Under normal oxygen concentration, EglN1 hydroxylates Akt1 on Pro125/Pro313 and promotes the binding of pVHL, in turn leading to inhibiting Akt activity through ubiquitination manner [ 28 , 29 ]. Under hypoxic conditions, EglN1 is incapable of hydroxylating Akt, which facilitates pVHL -mediated enrollment of PP2A to dephosphorylate Akt-T308, thereby leading to activation of Akt [ 12 ].…”

Section: Posttranslational Regulation Of Aktmentioning

confidence: 99%

Akt: a key transducer in cancer

et al. 2022

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Growth factor signaling plays a pivotal role in diverse biological functions, such as cell growth, apoptosis, senescence, and migration and its deregulation has been linked to various human diseases. Akt kinase is a central player transmitting extracellular clues to various cellular compartments, in turn executing these biological processes. Since the discovery of Akt three decades ago, the tremendous progress towards identifying its upstream regulators and downstream effectors and its roles in cancer has been made, offering novel paradigms and therapeutic strategies for targeting human diseases and cancers with deregulated Akt activation. Unraveling the molecular mechanisms for Akt signaling networks paves the way for developing selective inhibitors targeting Akt and its signaling regulation for the management of human diseases including cancer.

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The multifaceted role of EGLN family prolyl hydroxylases in cancer: going beyond HIF regulation

Cited by 9 publications

References 127 publications

Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles

Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles

Multi-omics biomarkers aid prostate cancer prognostication

Akt: a key transducer in cancer

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