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Chengkai Yang,1 Xiaoya Wu,2 Jianyong Liu,3 Huaxiang Wang,1 Yi Jiang,3 Zhihong Wei,3 Qiucheng Cai3 1The Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, 350025, People’s Republic of China; 2Eastern Hospital Affiliated to Xiamen University, Fuzhou, 350025, People’s Republic of China; 3Department of Hepatobiliary Surgery, 900 Hospital of The Joint Logistics Team, Fuzhou, 350025, People’s Republic of ChinaCorrespondence: Qiucheng Cai; Zhihong Wei, Department of Hepatobiliary Surgery, 900 Hospital of The Joint Logistics Team, No. 156 The Second West Ring Road, Fuzhou, Fujian, 350025, People’s Republic of China, Tel +86 13514072408 ; +86 18059055977, Email caiqiucheng2211@163.com; 779349357@qq.comPurpose: In this study, we developed a nomogram based on the platelet–albumin–bilirubin (PALBI) score to predict recurrence-free survival (RFS) after curative resection in alpha-fetoprotein (AFP)-negative (≤ 20 ng/mL) hepatocellular carcinoma (HCC) patients.Patients and Methods: A total of 194 pathologically confirmed AFP-negative HCC patients were retrospectively analyzed. Univariate and multivariate Cox regression analyses were performed to screen the independent risk factors associated with RFS, and a nomogram prediction model for RFS was established according to the independent risk factors. The receiver operating characteristic (ROC) curve and the C-index were used to evaluate the accuracy and the efficacy of the model prediction. The correction curve was used to assess the calibration of the prediction model, and decision curve analysis was performed to evaluate the clinical application value of the prediction model.Results: PALBI score, MVI, and tumor size were independent risk factors for postoperative tumor recurrence (P < 0.05). A nomogram prediction model based on the independent predictive factors was developed to predict RFS, and it achieved a good C-index of 0.704 with an area under the ROC curve of 0.661 and the sensitivity was 73.2%. Patients with AFP-negative HCC could be divided into the high-risk group or the low-risk group by the risk score calculated by the nomogram, and there was a significant difference in RFS between the two groups (P < 0.05). Decision curve analysis (DCA) showed that the nomogram increased the net benefit in predicting the recurrence of AFP-negative HCC and exhibited a wider range of threshold probabilities than the independent risk factors (PALBI score, MVI, and tumor size) by risk stratification.Conclusion: The nomogram based on the PALBI score can predict RFS after curative resection in AFP-negative HCC patients and can help clinicians to screen out high-risk patients for early intervention.Keywords: hepatocellular carcinoma, platelet–albumin–bilirubin score, alpha-fetoprotein-negative, recurrence-free survival, nomogram

High recurrence rate in HCC is the primary cause of the poor prognosis after hepatectomy. Therefore, in this study, we aimed to construct a gene signature for predicting the recurrence rate in HCC. The mRNA expression profiles and clinical information of HCC patients from GEO and TCGA databases were used, and ferroptosis-related gene list was obtained from the FerrDb database. We identified 39 ferroptosis-related genes (FDEGs) that were differentially expressed between HCC samples and normal tissues from the GSE14520 dataset. The univariate and multivariate Cox regression analyses were employed to construct a prognostic signature. Seven FDEGs (MAPK9, SLC1A4, PCK2, ACSL3, STMN1, CDO1, and CXCL2) were included to construct a risk model, which was validated in the TCGA dataset. Patients in high-risk groups exhibited a significantly poor prognosis compared with patients in low-risk groups in both the training set (GSE14520 cohort) and the validation set (TCGA cohort). Multivariate cox regression analyses demonstrated that the 7-gene signature was an independent risk factor for RFS in HCC patients. KEGG analysis showed that FDEGs were mainly enriched in Ferroptosis, Hepatocellular carcinoma pathway, and MAPK signaling pathway. GSEA analysis suggested that the high-risk group was correlated with multiple oncogenic signatures and invasive-related pathways. These results indicated that this risk model can accurately predict recurrence after hepatectomy and offer novel research directions for personalized treatment in HCC patients.

Additional file 1 Supplementary figures S1-S8.

Additional file 4 Review history.

In the paper, the effect of niobium addition on the microstructure, mechanical properties and wear resistance of high chromium cast iron has been studied. The results show that the microstructure of the heat-treated alloys is composed of M7C3 and M23C6 types primary carbide, eutectic carbide, secondary carbide and a matrix of martensite and retained austenite. NbC particles appear both inside and on the edge of the primary carbides. The hardness of the studied alloys maintains around 66 HRC, not significantly affected by the Nb content within the selected range of 0.48%-0.74%. The impact toughness of the alloys increases with increasing niobium content. The wear resistance of the specimens presents little variation in spite of the increase of Nb content under a light load of 40 N. However, when heavier loads of 70 and 100 N are applied, the wear resistance increases with increasing Nb content.