IER3 (IEX‐1) dysregulation serves as a potential prognostic factor in acute myeloid leukemia patients

Ke, Shandong; Zhang, Xin; Xiang, Xiuzhi; Lu, Ye; An, Hongyu

doi:10.1111/ijlh.13749

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Indeed, common HRGs, FBP1, GPI, BGN, PKP1, and NDRG1, have been reported as risk factors in CM [ 23 – 27 ] and are associated with immune cell infiltration in the TME. IER3 is a potential prognostic factor in patients with hepatocellular carcinoma and acute myeloid leukemia [ 28 , 29 ]. B4GALNT2 is down-regulated in colorectal and gastric cancers and elevated in breast cancer [ 30 ], and in CM, we report for the first time that it may act as a risk factor influencing patient prognosis.…”

Section: Discussionmentioning

confidence: 99%

Explore the impact of hypoxia-related genes (HRGs) in Cutaneous melanoma

Cheng

Sun

et al. 2023

BMC Med Genomics

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Background Cutaneous melanoma (CM) has an overall poor prognosis due to a high rate of metastasis. This study aimed to explore the role of hypoxia-related genes (HRGs) in CM. Methods We first used on-negative matrix factorization consensus clustering (NMF) to cluster CM samples and preliminarily analyzed the relationship of HRGs to CM prognosis and immune cell infiltration. Subsequently, we identified prognostic-related hub genes by univariate COX regression analysis and the least absolute shrinkage and selection operator (LASSO) and constructed a prognostic model. Finally, we calculated a risk score for patients with CM and investigated the relationship between the risk score and potential surrogate markers of response to immune checkpoint inhibitors (ICIs), such as TMB, IPS values, and TIDE scores. Results Through NMF clustering, we identified high expression of HRGs as a risk factor for the prognosis of CM patients, and at the same time, increased expression of HRGs also indicated a poorer immune microenvironment. Subsequently, we identified eight gene signatures (FBP1, NDRG1, GPI, IER3, B4GALNT2, BGN, PKP1, and EDN2) by LASSO regression analysis and constructed a prognostic model. Conclusion Our study identifies the prognostic significance of hypoxia-related genes in melanoma and shows a novel eight-gene signature to predict the potential efficacy of ICIs.

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