Abstract 3173: Clinical significance of Fanconi anemia complementation group E(FANCE)DNA repair-related gene expression in hepatocellular carcinoma

Author(s):  
Junichi Takahashi ◽  
Takaaki Masuda ◽  
Yosuke Kuroda ◽  
Akihiro Kitagawa ◽  
Yushi Motomura ◽  
...  
Oncology ◽  
2021 ◽  
Author(s):  
Junichi Takahashi ◽  
Takaaki Masuda ◽  
Akihiro Kitagawa ◽  
Taro Tobo ◽  
Yusuke Nakano ◽  
...  

Introduction: Fanconi anemia complementation group E (FANCE) is a Fanconi anemia (FA) pathway gene that regulates DNA repair. We evaluated the clinical relevance of FANCE expression in hepatocellular carcinoma (HCC). Methods: First, the associations between the expression of FA pathway genes including FANCE and clinical outcomes in HCC patients were analyzed in two independent cohorts: The Cancer Genome Atlas (TCGA, n = 373) and our patient cohort (n = 53). Localization of FANCE expression in HCC tissues was observed by immunohistochemical staining. Gene set enrichment analysis (GSEA) and gene network analysis (SiGN_BN) were conducted using the TCGA dataset. Next, an in vitro proliferation assay was performed using FANCE-knockdown HCC cell lines (HuH7 and HepG2). The association between mRNA expression of FANCE and that of DNA damage response genes in HCC was analyzed using TCGA and Cancer Cell Line Encyclopedia datasets. Finally, the association between FANCE mRNA expression and overall survival (OS) in various digestive carcinomas was analyzed using TCGA data. Results: FANCE was highly expressed in HCC cells. Multivariate analysis indicated that high FANCE mRNA expression was an independent factor predicting poor OS. GSEA revealed a positive relationship between enhanced FANCE expression and E2F and MYC target gene expression in HCC tissues. FANCE knockdown attenuated the proliferation of HCC cells, as well as reduced cdc25A expression and elevated histone H3 pSer10 expression. SiGN_BN revealed that FANCE mRNA expression was positively correlated with DNA damage response genes (H2AFX and CHEK1) in HCC tissues. Significant effects of high FANCE expression on OS were observed in hepatobiliary pancreatic carcinomas, including HCC. Conclusions: FANCE may provide a potential therapeutic target and biomarker of poor prognosis in HCC, possibly by facilitating tumor proliferation, which is mediated partly by cell cycle signaling activation.


2005 ◽  
Vol 37 (9) ◽  
pp. 958-963 ◽  
Author(s):  
Amom Ruhikanta Meetei ◽  
Annette L Medhurst ◽  
Chen Ling ◽  
Yutong Xue ◽  
Thiyam Ramsing Singh ◽  
...  

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Hyuk Soo Eun ◽  
Sang Yeon Cho ◽  
Jong Seok Joo ◽  
Sun Hyung Kang ◽  
Hee Seok Moon ◽  
...  

2021 ◽  
Author(s):  
Lingyu Zhang ◽  
Yu Li ◽  
Yibei Dai ◽  
Danhua Wang ◽  
Xuchu Wang ◽  
...  

Abstract Metabolic pattern reconstruction is an important element in tumor progression. The metabolism of tumor cells is characterized by the abnormal increase of anaerobic glycolysis, regardless of the higher oxygen concentration, resulting in a large accumulation of energy from glucose sources, and contributes to rapid cell proliferation and tumor growth which is further referenced as the Warburg effect. We tried to reconstruct the metabolic pattern in the progression of cancer to screen which genetic changes are specific in cancer cells. A total of 12 common types of solid tumors were enrolled in the prospective study. Gene set enrichment analysis (GSEA) was implemented to analyze 9 glycolysis-related gene sets, which are closely related to the glycolysis process. Univariate and multivariate analyses were used to identify independent prognostic variables for the construction of a nomogram based on clinicopathological characteristics and a glycolysis-related gene prognostic index (GRGPI). The prognostic model based on glycolysis genes has the highest area under the curve (AUC) in LIHC (Liver hepatocellular carcinoma). 8-gene signatures (AURKA, CDK1, CENPA, DEPDC1, HMMR, KIF20A, PFKFB4, STMN1) were related to overall survival (OS) and recurrence-free survival (RFS). Further analysis demonstrates that the prediction model can accurately distinguish between high- and low-risk cancer patients among patients in different clusters in LIHC. A nomogram with a well-fitted calibration curve based on gene expression profiles and clinical characteristics improves discrimination in internal and external cohorts. Furthermore, the altering expression of metabolic genes related to glycolysis may contribute to the reconstruction of the tumor-related microenvironment.


Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3760-3760
Author(s):  
W. Clark Lambert ◽  
Monique M. Brown ◽  
Santiago A. Centurion

Abstract One of us (WCL) has previously proposed a mathematical model, Co-Recessive Inheritance, for inherited diseases associated with DNA repair deficiencies (Lambert WC, Lambert MW: Mutat. Res., 1985;145:227–234; Lambert WC: Keynote Address, 21st Anniversary Celebration, MRC Cell Mutation Unit, University of Sussex, UK. Mutat. Res., 1992;273:179–102). The model is also applicable to diseases associated with defective cell cycle modulation following specific types of DNA damage, such as Fanconi Anemia, with or without additional defects in DNA repair. The model proposes that in some complementation groups of these diseases defective alleles at more than one locus are required for the disease phenotype to be expressed. It follows from the model (A readily understandable derivation will be presented.) that the carrier frequencies of the genes involved are very much higher than would be predicted based on classical population genetics. This may impact on recent observations of higher than expected co-inheritance of defective alleles of Fanconi Anemia and Bloom Syndrome genes along with BRCA genes in certain populations (e.g., Koren-Michowitz, M, et al.: Am. J. Hematol., 2005;78:203–206), and provides an explanation for the lower than expected incidence of cancer in these individuals. It also provides an explanation for finding biallelic defects in the same DNA repair genes in more than one complementation group of Fanconi Anemia (Howlett NG, et al.: Science, 2002;297:606–609). The Co-Recessive Model predicts that other findings of this nature are to be expected, and provides some guidelines that may be helpful in the process of gene discovery in Fanconi Anemia. Among the more important of these are 1) that the search for defective genes in each complementation group should not cease when one such gene is found, even if one or more patients in the group is homozygous or compound heterozygous for defective alleles of that gene, and 2) that carrier frequencies for some Fanconi Anemia genes may be much higher than would otherwise be anticipated, with a significant proportion of the normal population being carriers. If the latter hypothesis is correct, it follows that the relevance of these rare diseases and their associated genes to disease, including bone marrow failure, in the general population is dramatically greater than has been generally believed.


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