Background: Hepatocellular carcinoma (HCC) is among malignancies with the highest fatality toll globally and minimal therapeutic options. Necroptosis is a programmed form of necrosis or inflammatory cell death, which can affect prognosis and microenvironmental status of HCC. Therefore, we aimed to explore the prognostic value of necroptosis-related lncRNAs (NRLs) in HCC and the role of the tumor microenvironment (TME) in immunotherapy.Methods: The RNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). NRLs were identified by Pearson correlation analysis. The signature was constructed using the LASSO–Cox regression analysis and evaluated using the receiver operating characteristic curve (ROC) and the area under the Kaplan–Meier curve. The nomogram was built based on clinical information and risk score. Gene set enrichment analysis (GSEA), immunoassay, half-maximum inhibitory concentration (IC50) analysis of the risk group, and the HCC subtype identification based on NRLs were also carried out. Finally, we detected the expression of lncRNAs in HCC tissues and cell lines in vitro.Results: A total of 508 NRLs were screened out, and seven NRLs were constructed as a risk stratification system to classify patients into distinct low- and high-risk groups. Patients in the high-risk group had a significantly lower overall survival (OS) than those in the low-risk group. Using multivariate Cox regression analysis, we found that the risk score was an independent predictor of OS. Functional analysis showed that the immune status of different patients was different. The IC50 analysis of chemotherapy demonstrated that patients in the high-risk group were more sensitive to commonly prescribed drugs. qRT-PCR showed that three high-risk lncRNAs were upregulated in drug-resistant cells, and the expression in HCC tissues was higher than that in adjacent tissues.Conclusion: The prediction signature developed in this study can be used to assess the prognosis and microenvironment of HCC patients, and serve as a new benchmark for HCC treatment selection.
The aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to March 2022, 156 patients were admitted to the Affiliated Hospital of Nantong University, and from September 2017 to March 2022, 116 patients were retrospectively collected from the Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine. These patients were divided into a training group and an external test group. A radiomics nomogram was established using multivariate logistics regression analysis using the radiomics score and clinical data, including the ultrasound feature scoring terms from the thyroid imaging reporting and data system (TI-RADS). The radiomics nomogram incorporated the correlated predictors, and compared with the clinical model (training set AUC: 0.795; test set AUC: 0.783) and radiomics model (training set AUC: 0.774; test set AUC: 0.740), had better discrimination performance and correction effects in both the training set (AUC: 0.866) and the test set (AUC: 0.866). Both the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical application value. The nomogram constructed based on TI-RADS and radiomics features had good results in predicting and distinguishing benign and malignant TNs < 1 cm.
Background. Transarterial chemoembolization (TACE) is a first-line treatment for patients with unresectable hepatocellular carcinoma (HCC). Owing to differences in its efficacy across individuals, determining the indicators of patient response to TACE and finding approaches to reversing nonresponse thereto are necessary. Methods. Transcriptome data were obtained from the GSE104580 dataset, in which patients were marked as having TACE response or nonresponse. We identified differentially expressed genes (DEGs) and performed Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. We screened genes with a prognostic value for TACE in the HIF-1 signaling pathway by univariate regression analysis. By using least absolute shrinkage and selection operator (LASSO) Cox regression, we established a multigene signature in GSE14520, which we verified using a drug sensitivity test. The Connectivity Map (CMap) database was used to find potential drugs to reverse nonresponse to TACE. Results. We constructed a prognostic signature consisting of three genes (erythropoietin (EPO), heme oxygenase 1 (HMOX1), and serine protease inhibitor 1 (SERPINE1)) that we validated by drug sensitivity test. After dividing patients treated with TACE into high- and low-risk groups based on this new signature, we showed that overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group and that the risk score was an independent predictor of OS in patients treated with TACE. Based on our CMap findings, we speculated that PD-184352, an inhibitor of mitogen-activated protein kinase (MEK), had potential as a drug treatment to reverse nonresponse to TACE. We confirmed this speculation by using PD-184352 in a cell promotion experiment in a TACE environment. Conclusion. We constructed a TACE-specific three-gene signature that could be used to predict HCC patients’ responses to and prognosis after TACE treatment. PD-184352 might have potential as a drug to improve TACE efficacy.
ObjectiveTo explore the prognostic value of radiological features and serum indicators in patients treated with postoperative adjuvant transarterial chemoembolization (PA-TACE) and develop a prognostic model to predict the overall survival (OS) of patients with hepatocellular carcinoma (HCC) treated with PA-TACE.MethodWe enrolled 112 patients (75 in the training cohort and 37 in the validation cohort) with HCC treated with PA-TACE after surgical resection at the Affiliated Hospital of Nantong University between January 2012 and June 2015. The independent OS predictors were determined using univariate and multivariate regression analyses. Decision curve analyses and time-dependent receiver operating characteristic curve analysis was used to verify the prognostic performance of the different models; the best model was selected to establish a multi-dimensional nomogram for predicting the OS of HCC patients treated with PA-TACE.ResultMultivariate regression analyses indicated that rim-like arterial phase enhancement (IRE), peritumor capsule (PTC), and alanine aminotransferase to hemoglobin ratio (AHR) were independent predictors of OS after PA-TACE. The combination of AHR had the best clinical net benefit and we constructed a prognostic nomogram based on IRE, PTC, and AHR. The calibration curve showed good fit between the predicted nomogram’s curve and the observed curve.ConclusionOur preliminary study confirmed the prognostic value of AHR, PTC, and IRE and established a nomogram that can predict the OS after PA-TACE treatment in patients with HCC.
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