Zhixin Wang

Background Hepatocellular carcinoma (HCC) progression is tightly driven by genomic instability and dysregulated DNA damage repair (DDR) pathways. The replication licensing factor Chromatin Licensing and DNA Replication Factor 1 (CDT1) is frequently overexpressed in HCC tissues; however, the molecular mechanisms by which CDT1 coordinates DDR programs and modulates tumor immune microenvironment remain poorly elucidated. This study aimed to systematically characterize CDT1-centered regulatory networks in HCC, delineate their dual impacts on DDR machinery and immune-related signaling pathways, and validate the clinical translational value of CDT1 as a potential biomarker or therapeutic target. Methods A stable CDT1 knockdown (CDT1-KD) cell model was established in Huh7 HCC cells using lentiviral short hairpin RNA (shRNA), with silencing efficiency verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot analysis. DNA double-strand breaks (DSBs) were quantified via γ-H2AX immunofluorescence staining. RNA sequencing (RNA-seq) was performed to profile CDT1-dependent transcriptional alterations, followed by differential expression analysis using DESeq2, Gene Ontology (GO) functional annotation, and Gene Set Enrichment Analysis (GSEA). Chromatin immunoprecipitation sequencing (ChIP-seq) was employed to map genome-wide CDT1 chromatin occupancy, which was further integrated with the transcriptome data to prioritize direct CDT1 target genes. The involvement of CDT1 in immune regulation was investigated by intersecting CDT1-bound and CDT1-regulated genes with manually curated immune-related gene sets. Finally, the clinical relevance of CDT1 expression in HCC was analyzed using public databases, including The Cancer Genome Atlas (TCGA), UALCAN, and the Human Protein Atlas (HPA). Results CDT1 silencing significantly increased the number of γ-H2AX foci in Huh7 cells, indicating exacerbated accumulation of DNA DSBs. RNA-seq analysis identified 4,581 CDT1-dependent differentially expressed genes (DEGs), including 2,739 upregulated and 1,842 downregulated transcripts. Functional enrichment analysis of downregulated DEGs revealed significant enrichment in biological processes related to DNA replication initiation, homologous recombination (HR), and broader DDR cascades—consistent with GSEA results showing suppressed activity of DDR-related gene sets in CDT1-KD cells. ChIP-seq data demonstrated that CDT1 primarily binds to intergenic and intronic regions of the genome; integration with RNA-seq data identified 328 CDT1-bound DEGs, which were enriched in signal transduction and cell proliferation pathways (e.g., HNRNPD, FBXL4, DROSHA). Intersection with immune gene catalogs yielded 307 immune-related CDT1 target genes; notably, CDT1 knockdown led to reduced expression of key immune regulators such as SEMA3D, CHUK, and PIK3R3, implicating CDT1 in the modulation of HCC immune signaling. Clinically, CDT1 expression was significantly upregulated in HCC tissues compared to adjacent non-tumor tissues, and high CDT1 expression was independently associated with poorer overall survival in HCC patients. Conclusions CDT1 functions as a pivotal oncogenic regulator in HCC by coupling maintenance of DDR proficiency with control of immune-related gene expression. Its dual roles in sustaining DNA replication/repair programs and shaping the tumor immune microenvironment highlight CDT1 as a promising prognostic biomarker and a potential therapeutic target for HCC. Targeting CDT1 may not only disrupt tumor genomic stability but also enhance responsiveness to immunotherapy, thereby addressing the challenge of tumor heterogeneity in HCC treatment.

Background: To explore the evaluation value of systemic immune inflammation index (SII) in the prognosis of patients with alveolar hydatid disease, and establish a nomogram prediction model.Methods: Collect the clinical data of 351 patients undergoing hepatic alveolar hydatid surgery admitted to the Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Qinghai University from January 2015 to December 2020, calculate the SII value, and use the receiver operating characteristic curve (ROC curve) to determine According to the optimal clinical cut-off value of SII, patients were divided into two groups with high SII and low SII, and the relationship between SII and clinicopathological factors and prognosis of patients with alveolar echinococcosis was analyzed. Establish a nomogram prediction model based on independent risk factors for patient prognosis, and evaluate the prediction accuracy and discrimination ability of the nomogram through the consistency index (C-index) and calibration curve. The result is through the use of bootstrapping validation with 1,000 re-sampling Method for internal verification.Results: The ROC curve was used to determine the optimal cut-off value of SII before operation 761.192, and patients were divided into low SII group (n = 184) cases and high SII group (n = 167) cases. The 1, 3, and 5-year survival rates of patients with hepatic alveolar hydatid in the low SII group and the high SII group were 98.90%, 96.90%, 86.50% and 98.20%, 72.50%, 40.30%, respectively. The survival rate of worm disease patients was significantly better than that of the high SII group, and the overall survival rate difference between the two groups was statistically significant (P < 0.001). Multivariate Cox regression model analysis results showed that intraoperative blood loss (HR = 1.810, 95%CI: 1.227–2.668, P = 0.003), SII (HR = 5.011, 95%CI: 3.052–8.228, P < 0.001), Complications (HR = 1.720, 95%CI: 1.162–2.545, P = 0.007) are independent risk factors for the prognosis of patients with alveolar hydatid disease. Draw a nomogram and include statistically significant factors in the multivariate Cox regression model to predict the overall survival rate of patients with alveolar hydatid disease at 1, 3, and 5 years. The survival probability calibration curve is displayed. The nomogram is compared with The actual results have a high degree of agreement. The concordance index (C-index) of the nomogram model in the modeling sample is 0.777, and the C-index in the verification sample is 0.797, indicating that the nomogram model of this study has good accuracy and discrimination.Conclusions: SII has a clear correlation to the prognosis of patients with alveolar echinococcosis. The nomogram prediction model constructed on this basis is beneficial to the clinically individualized analysis of the patient's prognosis.

Objective: This study aimed to investigate the clinical characteristics and risk factors of patients with hepatocellular carcinoma (HCC) with extrahepatic metastases (EHM) and to establish an effective predictive nomogram.Methods: Clinical and pathological data from 607 patients with hepatocellular carcinoma admitted to the Affiliated Hospital of Qinghai University between 1 January 2015 and 31 May 2018 were documented, as well as demographics, clinical pathological characteristics, and tumor-related parameters to clarify clinical risk factors for HCC EHM. These risks were selected to build an R-based clinical prediction model. The predictive accuracy and discriminating ability of the model were determined by the concordance index (C-index) and the calibration curve. The results were validated with a bootstrap resample and 151 patients from 1 June 2018 to 31 December 2019 at the same facility.Results: In multivariate analysis, independent factors for EHM were neutrophils, prothrombin time, tumor number, and size, all of which were selected in the model. The C-index in the EHM prediction model was 0.672 and in the validation cohort was 0.694. In the training cohort and the validation cohort, the calibration curve for the probability of EHM showed good agreement between the nomogram prediction and the actual observation.Conclusion: The extrahepatic metastasis prediction model of hepatocellular carcinoma constructed in this study has some evaluation capability.

Background: Microwave ablation (MWA) is a popular therapy for liver malignant tumor in recent years. Few studies have been conducted on its use in the treatment of hepatic alveolar echinococcosis (HAE). The study aims to evaluate the efficacy and safety of MWA in the treatment of HAE.Methods: This study analyzed the data of 45 patients (mean age, 38 ± 2 years; 24 males) diagnosed with HAE and underwent MWA treatment between June 2014 to December 2019. The patients after MWA were examined by CT or MRI [follow-up: 32 months (IQR 23–48.5)] to determine whether the lesions were relapsed and to evaluate the therapeutic effect of MWA. The safety of MWA was evaluated by monitoring postoperative complications. Clinical data, such as patient demographics, imaging features of the lesions, relevant findings of laboratory tests before and after ablation, and information related to ablation, were collected and analyzed. Paired-sample t tests and paired-sample Wilcoxon signed-rank tests were used to compare relevant laboratory indicators before and after MWA.Results: MWA was applied to 57 HAE lesions in 45 patients. The median size of lesions was 3.42 cm (IQR2.85–4.41). The rate of complete ablation was 100% (57/57). The median follow-up time was 32 months (IQR 23–48.5). The recurrence rate was 13% (6/45), and the median time of recurrence was 22 months. The rate of minor complications was 11.1% (5/45), and there were no major complications and deaths. Compared to preoperative, ALB, RBC, HBG, and PLT were decreased (p < 0.001); ALT, TB, DB, and WBC were increased (p < 0.001); and no statistically difference in PT, APTT, and INR (p > 0.05).Conclusions: MWA might be a safe and effective way to cure HAE. Meanwhile, it provides a new option and a new way of thinking about treatment for patients with HAE.

Background: To explore the relationship between the preoperative immune inflammation index (SII) and the prognostic nutritional index (PNI) and the overall survival rate (OS) of patients with alveolar hydatid disease.Methods: The clinical data of patients with hepatic alveolar echinococcosis treated by surgery in the Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Qinghai University from January 2015 to January 2019 were analyzed retrospectively, and the SII, PNI, PLR and NLR were calculated. Spearman correlation analysis was utilized to analyze the correlation among SII, PNI, PLR and NLR. Receiver operating characteristic curve (ROC) was utilized to determine the best intercept values of SII, PNI, PLR and NLR, and Chi-square test was used to evaluate the relationship between SII, PNI and various clinicopathological features in patients with hepatic alveolar echinococcosis. The kaplan-Meier method was used to draw survival curves and analyze the relationship between them and the total survival time of patients. A cox regression model was used to analyze the relationship between SII, PNI and the prognosis of patients with hepatic alveolar echinococcosis. Finally, ROC curve was used to estimate the predictive efficacy of SII, PNI and COSII-PNI for the prognosis of patients with hepatic alveolar echinococcosis.Results: A total of 242 patients were included, including 96 males and 146 females, aged 11.0-67.0 (36.6 ± 11.7) years. The values of SII, PNI, PLR and NLR are calculated, and the best truncation values of SII, PNI, PLR and NLR are given in ROC curve. The kaplan-Meier survival curve was used to analyze the relationship between SII, PNI, PLR, NLR and the overall survival time of patients with hepatic alveolar echinococcosis. The results showed that the median follow-up time was 45 months (95%CI: 39.484-50.516), and the average survival time was 49 months (95%CI: 47.300-51.931), which was low pvs 71.6%; pvs 24.3%; pvs 28.8%; p<0.001). Cox unifoliate analysis showed that SII, PNI, PLR and NLR were important prognostic factors related to OS. Cox multivariate analysis showed that SII(HR=4.678, 95% CI: 2.581-8.480, P<0.001) and PNI(HR=0.530, 95%CI: 0.305-0.920, P<0.05) were identified as independent risk indicators of OS, while NL was identified as independent risk indicators of OS ROC curve analysis showed that AUC of SII, PNI, PLR, NLR and COSII-PNI were 0.670(95%CI: 0.601-0.738), 0.638(95%CI: 0.561-0.716) and 0.618(95% CI: 0.541-0.694), respectively COSII-PNI is superior to SII and PNI in evaluating prognosis (P < 0.05).Conclusions: SII and PNI can be regarded as independent risk factors reflecting the prognosis of patients with hepatic alveolar echinococcosis. The lower SII and the higher PNI before operation, the better the prognosis of patients, and the combined application of SII and PNI before operation can improve the accuracy of prediction.