Corrigendum: CDT1 is a Novel Prognostic and Predictive Biomarkers for Hepatocellular Carcinoma

Cai, Chenhui; Zhang, Ying; Hu, Xu Guang; Hu, Wenhui; Yang, Sizhen; Qiu, H.; Chu, Tongwei

doi:10.3389/fonc.2021.801970

Cited by 1 publication

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“…Despite encouraging progress being achieved in the detection, treatment, and prevention of HCC, it remains a prevalent and malignant disease with a high mortality rate and a poor prognosis, resulting in over 500,000 deaths annually ( 18 , 19 ). HCC represents 90% of all kind of liver cancers, and its 5-year survival rate is only 18% ( 1 , 20 ).…”

Section: Discussionmentioning

confidence: 99%

Disulfidptosis-related genes of prognostic signature and immune infiltration features in hepatocellular carcinoma supported by bulk and single-cell RNA sequencing data

Wang,

Yuan,

Zhu

et al. 2024

J Gastrointest Oncol

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Background Disulfidptosis is a new type of cellular death triggered in response to disulfide stress and is strongly linked to the progression of malignancies. Hepatocellular carcinoma (HCC) is a very common malignancy. Some reports have suggested a link between disulfidptosis-related genes (DRGs) and cancer; however, further research needs to be conducted. Methods In this study, HCC data from the Cancer Genome Atlas–Liver Hepatocellular Carcinoma and Gene Expression Omnibus data sets were collected and analyzed. A univariate Cox regression analysis, least absolute shrinkage and selection operator, and multivariate Cox regression analysis were conducted to identify the hub DRGs signature for prognosis. The HCC patients were allocated to high- and low-risk groups based on their disulfidptosis risk scores. The model was validated with a high degree of precision using both internal and external validation data sets. “ESTIMATE” and “CIBERSORT” packages were employed to assess the immunological landscapes and immune cell infiltration. The IMvigor210 cohort was chosen to validate the immunotherapy results. A drug sensitivity analysis was conducted to identify targeted medications. The expression of the hub DRGs in the HCC cells was confirmed using cytological techniques. Results The bioinformatic analysis revealed that 16 genes showed differential expression. A prognostic model was developed based on four genes: RPN1, SLC2A1, SLC2A4 , and SLC7A11 . A notable difference in prognosis was observed between the two risk groups. Based on the results of the immune microenvironment, tumor mutation burden, immunotherapy, and drug screening analyses, the DRGs signature can be employed in HCC immunotherapy decision making. Further, the expression levels of the hub DRGs were significantly upregulated in the HCC cells. Conclusions Our four-DRGs signature could be used to predict HCC prognosis. Further, this study showed that the hub DRGs could serve as biomarkers for immunotherapy prediction and could potentially guide targeted therapies.

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