Identification of ATIC as a Novel Target for Chemoradiosensitization

Liu, Xiangfei; Paila, Uma Devi; Teraoka, Sharon N.; Wright, James R.; Huang, Xin; Quinlan, Aaron R.; Gatti, Richard A.; Concannon, Patrick

doi:10.1016/j.ijrobp.2017.08.033

Cited by 26 publications

(27 citation statements)

References 44 publications

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“…Moreover, a study found by exome sequencing conducted on radiosensitive cell line derived from patients suspected of having ataxia‐telangiectasia and Lesch‐Nyhan spectrum disorders, a heterozygous complex frameshift mutation c.[130dup;131_132insA] in the ATIC gene, of unknown significance 15 . This variation is also carried by eight heterozygous Europeans in gnomAD, while neither c.130dup nor c.131_132insA alone is reported.…”

Section: Discussionmentioning

confidence: 99%

AICA‐ribosiduria due to ATIC deficiency: Delineation of the phenotype with three novel cases, and long‐term update on the first case

Ramond

Rio

Héron

et al. 2020

J of Inher Metab Disea

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5-Amino-4-imidazolecarboxamide-ribosiduria (AICA)-ribosiduria is an exceedingly rare autosomal recessive condition resulting from the disruption of the bifunctional purine biosynthesis protein PURH (ATIC), which catalyzes the last two steps of de novo purine synthesis. It is characterized biochemically by the accumulation of AICA-riboside in urine. AICA-ribosiduria had been reported in only one individual, 15 years ago. In this article, we report three novel cases of AICA-ribosiduria from two independent families, with two novel pathogenic variants in ATIC. We also provide a clinical update on the first patient. Based on the phenotypic features shared by these four patients, we define AICA-ribosiduria as the syndromic association of severe-to-profound global neurodevelopmental impairment, severe visual impairment due to

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Section: Discussionmentioning

confidence: 99%

AICA‐ribosiduria due to ATIC deficiency: Delineation of the phenotype with three novel cases, and long‐term update on the first case

Ramond

Rio

Héron

et al. 2020

J of Inher Metab Disea

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“…Previous studies have reported that ATIC is a bifunctional protease that catalyzes the last two steps in the purine biosynthesis pathway. Depletion of ATIC or suppression of its transformylase activity significantly decreased the survival rate of cells in clonogenic survival assays, which indicates that ATIC may promote the proliferation and migration in cancer cell lines [33]. Indeed, suppression of ATIC expression significantly inhibited the ability of HCC cells to proliferate and migrate through the regulation of the AMPK-mTOR-S6K1 signaling pathway.…”

Section: Discussionmentioning

confidence: 94%

Identification of an autophagy-related gene signature that can improve prognosis of hepatocellular carcinoma patients

Huo

Huang

et al. 2020

BMC Cancer

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Background: Autophagy is a programmed cell degradation mechanism that has been associated with several physiological and pathophysiological processes, including malignancy. Improper induction of autophagy has been proposed to play a pivotal role in the progression of hepatocellular carcinoma (HCC). Methods: Univariate Cox regression analysis of overall survival (OS) was performed to identify risk-associated autophagy-related genes (ARGs) in HCC data set from The Cancer Genome Atlas (TCGA). Multivariate cox regression was then performed to develop a risk prediction model for the prognosis of 370 HCC patients. The multi-target receiver operating characteristic (ROC) curve was used to determine the model's accuracy. Besides, the relationship between drug sensitivity and ARGs expression was also examined. Results: A total of 62 differentially expressed ARGs were identified in HCC patients. Univariate and multivariate regression identified five risk-associated ARGs (HDAC1, RHEB, ATIC, SPNS1 and SQSTM1) that were correlated with OS in HCC patients. Of importance, the risk-associated ARGs were independent risk factors in the multivariate risk model including clinical parameters such as malignant stage (HR = 1.433, 95% CI = 1.293-1.589, P < 0.001). In addition, the area under curve for the prognostic risk model was 0.747, which indicates the high accuracy of the model in prediction of HCC outcomes. Interestingly, the risk-associated ARGs were also correlated with drug sensitivity in HCC cell lines. Conclusion: We developed a novel prognostic risk model by integrating the molecular signature and clinical parameters of HCC, which can effectively predict the outcomes of HCC patients.

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“…Previous studies have reported that ATIC is a bifunctional protease that catalyzes the last two steps in the purine biosynthesis pathway. Depletion of ATIC or suppression of its transformylase activity significantly decreased the survival rate of cells in clonogenic survival assays, which indicates that ATIC may promote the proliferation and migration in cancer cell lines [32]. Indeed, suppression of ATIC expression significantly inhibited the ability of HCC cells to proliferate and migrate through the regulation of the AMPK-mTOR-S6K1 signaling pathway.…”

Section: Discussionmentioning

confidence: 94%

Identification of an Autophagy-Related Gene Signature that Can Improve Prognosis of Hepatocellular Carcinoma Patients

Huo

Huang

et al. 2020

Preprint

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Background: Autophagy is a programmed cell degradation mechanism that has been associated with several physiological and pathophysiological processes, including malignancy. Improper induction of autophagy has been proposed to play a pivotal role in the progression of hepatocellular carcinoma (HCC).Methods: Univariate Cox regression analysis of overall survival (OS) was performed to identify risk-associated autophagy-related genes (ARGs) in HCC data set from The Cancer Genome Atlas (TCGA). Multivariate cox regression was then performed to develop a risk prediction model for the prognosis of 370 HCC patients. The multi-target receiver operating characteristic (ROC) curve was used to determine the model’s accuracy. Besides, the relationship between drug sensitivity and ARGs expression was also examined. Results: A total of 62 differentially expressed ARGs were identified in HCC patients. Univariate and multivariate regression identified five risk-associated ARGs ( HDAC1, RHEB , ATIC, SPNS1 and SQSTM1 ) that were correlated with OS in HCC patients. Of importance, the risk-associated ARGs were independent risk factor s in the multivariate risk model including clinical parameters such as malignant stage (HR=1.433, 95% CI=1.293-1.589, P<0.001). In addition, the area under curve for the prognostic risk model was 0.747, which indicates the high accuracy of the model in prediction of HCC outcomes. Interestingly, the risk-associated ARGs were also correlated with drug sensitivity in HCC cell lines.Conclusions: We developed a novel prognostic risk model by integrating the molecular signature and clinical parameters of HCC, which can effectively predict the outcomes of HCC patients.

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Identification of ATIC as a Novel Target for Chemoradiosensitization

Cited by 26 publications

References 44 publications

AICA‐ribosiduria due to ATIC deficiency: Delineation of the phenotype with three novel cases, and long‐term update on the first case

AICA‐ribosiduria due to ATIC deficiency: Delineation of the phenotype with three novel cases, and long‐term update on the first case

Identification of an autophagy-related gene signature that can improve prognosis of hepatocellular carcinoma patients

Identification of an Autophagy-Related Gene Signature that Can Improve Prognosis of Hepatocellular Carcinoma Patients

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