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Ovarian cancer (OC) was the fifth leading cause of cancer death and the deadliest gynecological cancer in women. This was largely attributed to its late diagnosis, high therapeutic resistance, and a dearth of effective treatments. Clinical and preclinical studies have revealed that tumor-infiltrating CD8+T cells often lost their effector function, the dysfunctional state of CD8+T cells was known as exhaustion. Our objective was to identify genes associated with exhausted CD8+T cells (CD8TEXGs) and their prognostic significance in OC. We downloaded the RNA-seq and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD8TEXGs were initially identified from single-cell RNA-seq (scRNA-seq) datasets, then univariate Cox regression, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were utilized to calculate risk score and to develop the CD8TEXGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in the risk groups were used to figure out the closely correlated pathways with the risk group. The role of risk score has been further explored in the homologous recombination repair deficiency (HRD), BRAC1/2 gene mutations and tumor mutation burden (TMB). A risk signature with 4 CD8TEXGs in OC was finally built in the TCGA database and further validated in large GEO cohorts. The signature also demonstrated broad applicability across various types of cancer in the pan-cancer analysis. The high-risk score was significantly associated with a worse prognosis and the risk score was proven to be an independent prognostic biomarker. The 1-, 3-, and 5-years ROC values, nomogram, calibration, and comparison with the previously published models confirmed the excellent prediction power of this model. The low-risk group patients tended to exhibit a higher HRD score, BRCA1/2 gene mutation ratio and TMB. The low-risk group patients were more sensitive to Poly-ADP-ribose polymerase inhibitors (PARPi). Our findings of the prognostic value of CD8TEXGs in prognosis and drug response provided valuable insights into the molecular mechanisms and clinical management of OC.
Subject(s)
CD8-Positive T-Lymphocytes , Ovarian Neoplasms , Humans , Female , Ovarian Neoplasms/genetics , CD8-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/metabolism , Prognosis , RNA-Seq/methods , Biomarkers, Tumor/genetics , Single-Cell Analysis/methods , Gene Expression Regulation, Neoplastic , Single-Cell Gene Expression AnalysisABSTRACT
The role of the integrin family in malignancy has received increasing attention. Many studies have confirmed that ITGB4 could activate multiple signal pathways and promote cell migration in various cancers. However, the regulatory role of integrin ß4 (ITGB4) in lung adenocarcinoma (LUAD) is still unclear. Examination of the expression or survival analysis of ITGB4 in cells, pathological samples, and bioinformatics lung adenocarcinoma databases showed ITGB4 was highly expressed in LUAD and significantly associated with poor prognosis. Small interfering RNA and plasmids were performed to investigate the effect of changes in ITGB4 expression on lung adenocarcinoma. Focal adhesion kinase (FAK) inhibitor defactinib was used to further explore the molecular mechanism of ITGB4. The results showed depletion of ITGB4 inhibited migration and activation of FAK signaling pathways in lung adenocarcinoma cells. Moreover, increased ITGB4 expression activated FAK signaling and promoted cell migration, which can be reversed by defactinib. In addition, ITGB4 could interact with FAK in lung adenocarcinoma cells. ITGB4 may promote cell migration of lung adenocarcinoma through FAK signaling pathway and has the potential to be a biomarker for lung adenocarcinoma.
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COVID-19 , Humans , COVID-19/diagnosis , Retrospective Studies , Prognosis , Biomarkers/blood , Male , Female , Middle Aged , SARS-CoV-2 , AgedABSTRACT
Tendon adhesion is a common complication after tendon surgery. The inflammatory phase of tendon healing is characterized by the release of a large number of inflammatory factors, whose mediated excessive inflammatory response is an important cause of tendon adhesion formation. Nonsteroidal anti-inflammatory drugs(NSAIDs) were used to prevent tendon adhesions by reducing the inflammatory response. However, recent studies have shown that the NSAIDs partially impairs tendon healing. Therefore, optimizing the anti-adhesive membrane loaded with NSAIDs to mitigate the effects on tendon healing requires further in-depth study. Amniotic membranes(AM) are natural polymeric semi-permeable membranes from living organisms that are rich in matrix, growth factors, and other active ingredients. In this study, we used electrostatic spinning technology to construct multifunctional nanofiber membranes of the PCL membrane loaded with celecoxib and AM. In vitro cellular assays revealed that celecoxib-loaded PCL membranes significantly inhibited the adhesion and proliferation of fibroblasts with increasing concentrations of celecoxib. In a rabbit tendon repair model, biomechanical tests further confirmed that the PCL membrane loaded with celecoxib had better anti-adhesion effects. Further experimental studies revealed that the PCL/AM membrane improved the inflammatory microenvironment by downregulating the expression of pro-inflammatory factors such as COX-2, IL-1ß, and TNF-α proteins; and inhibiting the synthesis of COL I and COL â ¢. The PCL/AM membrane can continuously release celecoxib to reduce the inflammatory response and deliver growth factors to the damaged area to build a suitable microenvironment for tendon repair, which provides a new direction to improve the repair efficiency of tendon.
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[This corrects the article DOI: 10.3389/fonc.2022.986867.].
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Appropriate levels of inflammation are an important part of functional repair of nerve damage. However, excessive inflammation can cause the continuous activation of immune inflammatory cells and degeneration of nerve cells. Regulating the temporal and spatial changes in M1/M2 macrophages can regulate the local inflammatory immune environment of the tissue to promote its transformation to a direction conducive to tissue repair.In the present study, a multi-layer multifunctional nanofiber composite membrane of polycaprolactone(PCL) and amniotic membrane (AM) was constructed using electrospinning. In vitro studies have shown that the PCL/AM composite promoted the axon growth of SH-SY5Y cells and induced their differentiation into neurons. The PCL/AM composite wrapped the nerve stump to form a microenvironment that was conducive to nerve regeneration, blocked the invasion of scar tissue, promoted the recruitment of macrophages and moderate polarization to M2, enhanced the expression of anti-inflammatory factors IL-10 and IL-13, inhibited the expression of pro-inflammatory factors IL-6 and TNF-α, and induced myelin sheath and axon regeneration. By releasing various bioactive substances to regulate the polarization of M2 macrophages and formation of anti-inflammatory factors, the PCL/AM composite can enhance axonal regeneration and improve nerve repair.
Subject(s)
Nanofibers , Neuroblastoma , Humans , Axons , Amnion , Nerve Regeneration , Macrophages/metabolism , Inflammation/metabolism , Tumor MicroenvironmentABSTRACT
Gallbladder neuroendocrine carcinoma (GB-NEC) is a rare, aggressive neuroendocrine carcinoma that arises from the gallbladder. Patients with GB-NEC usually have a poor prognosis. The present study described two cases diagnosed with GB-NEC and reviewed the literature to improve knowledge of GB-NEC. The present study reported on two cases of GB-NEC in male patients aged 65 and 66 years, respectively. Both patients underwent surgical resection. Postoperative pathology confirmed that one case had mixed adeno-neuroendocrine carcinoma and the other had large cell neuroendocrine carcinoma. In addition, both patients had uneventful recoveries following surgery and received cisplatin-etoposide combination chemotherapy. The present study summarized the two cases and reviewed the literature to improve understanding of GB-NEC. The results revealed that radiological findings of GB-NEC are non-specific. The present study demonstrated that surgical resection was still the most effective therapy and that postoperative adjuvant chemotherapy could markedly improve the prognosis of patients with GB-NEC.
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BACKGROUND: Leptomeningeal metastases (LM) were rare in gastric cancer (GC), and GC patients with LM (GCLM) generally suffer from poor prognosis. Nevertheless, the clinical utility of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) was underinvestigated in GCLM. METHODS: We retrospectively studied 15 GCLM patients, and all patients had paired primary tumor tissue samples and post-LM CSF samples while 5 patients also had post-LM plasma samples. All samples were analyzed using next-generation sequencing (NGS), and the molecular and clinical features were correlated with clinical outcomes. RESULTS: CSF had higher mutation allele frequency (P = 0.015), more somatic mutations (P = 0.032), and more copy-number variations (P < 0.001) than tumor or plasma samples. Multiple genetic alterations and aberrant signal pathways were enriched in post-LM CSF, including CCNE1 amplification and cell cycle-related genes, and CCNE1 amplification was significantly associated with patients' overall survival (P = 0.0062). More potential LM progression-related markers were detected in CSF samples than in tumor samples, including PREX2 mutation (P = 0.014), IGF1R mutation (P = 0.034), AR mutation (P = 0.038), SMARCB1 deletion (P < 0.001), SMAD4 deletion (P = 0.0034), and TGF-beta pathway aberration (P = 0.0038). Additionally, improvement in intracranial pressure (P < 0.001), improvement in CSF cytology (P = 0.0038), and relatively low levels of CSF ctDNA (P = 0.0098) were significantly associated with better PFS. Lastly, we reported a GCLM case whose CSF ctDNA dynamic changes were well correlated with his clinical assessment. CONCLUSIONS: CSF ctDNA could more sensitively detect molecular markers and metastasis-related mechanisms than tumor tissues in GCLM patients, and our study sheds light on utilizing CSF ctDNA in prognostic estimation and clinical assessment in GCLM.
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Cell-Free Nucleic Acids , Lung Neoplasms , Meningeal Neoplasms , Stomach Neoplasms , Humans , Stomach Neoplasms/genetics , Retrospective Studies , Meningeal Neoplasms/genetics , Mutation/genetics , Genomics , Biomarkers, Tumor/genetics , Lung Neoplasms/pathologyABSTRACT
Introduction: It is believed that ovarian cancer (OC) is the most deadly form of gynecological cancer despite its infrequent occurrence, which makes it one of the most salient public health concerns. Clinical and preclinical studies have revealed that intratumoral CD4+ T cells possess cytotoxic capabilities and were capable of directly killing cancer cells. This study aimed to identify the CD4+ conventional T cells-related genes (CD4TGs) with respect to the prognosis in OC. Methods: We obtained the transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD4TGs were first identified from single-cell datasets, then univariate Cox regression was used to screen prognosis-related genes, LASSO was conducted to remove genes with coefficient zero, and multivariate Cox regression was used to calculate riskscore and to construct the CD4TGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), decision curve analysis (DCA), nomogram, and calibration were made to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. The role of riskscore has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy. A risk signature with 11 CD4TGs in OC was finally established in the TCGA database and furtherly validated in several GEO cohorts. Results: High riskscore was significantly associated with a poorer prognosis and proven to be an independent prognostic biomarker by multivariate Cox regression. The 1-, 3-, and 5-year ROC values, DCA curve, nomogram, and calibration results confirmed the excellent prediction power of this model. Compared with the reported risk models, our model showed better performance. The patients were grouped into high-risk and low-risk subgroups according to the riskscore by the median value. The low-risk group patients tended to exhibit a higher immune infiltration, immune-related gene expression and were more sensitive to immunotherapy and chemotherapy. Discussion: Collectively, our findings of the prognostic value of CD4TGs in prognosis and immune response, provided valuable insights into the molecular mechanisms and clinical management of OC.
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Ovarian Neoplasms , Humans , Female , Prognosis , Ovarian Neoplasms/genetics , Nomograms , CD4-Positive T-Lymphocytes , Calibration , Tumor Microenvironment/geneticsABSTRACT
According to statistics, breast cancer (BC) has replaced lung cancer as the most common cancer in the world. Therefore, specific detection markers and therapeutic targets need to be explored as a way to improve the survival rate of BC patients. We first identified m6A/m5C/m1A/m7G-related long noncoding RNAs (MRlncRNAs) and developed a model of 16 MRlncRNAs. Kaplan-Meier survival analysis was applied to assess the prognostic power of the model, while univariate Cox analysis and multivariate Cox analysis were used to assess the prognostic value of the constructed model. Then, we constructed a nomogram to illustrate whether the predicted results were in good agreement with the actual outcomes. We tried to use the model to distinguish the difference in sensitivity to immunotherapy between the two groups and performed some analyses such as immune infiltration analysis, ssGSEA and IC50 prediction. To explore the novel anti-tumor drug response, we reclassified the patients into two clusters. Next, we assessed their response to clinical treatment by the R package pRRophetic, which is determined by the IC50 of each BC patient. We finally identified 11 MRlncRNAs and based on them, a risk model was constructed. In this model, we found good agreement between calibration plots and prognosis prediction. The AUC of ROC curves was 0.751, 0.734, and 0.769 for 1-year, 2-year, and 3-year overall survival (OS), respectively. The results showed that the IC50 was significantly different between the risk groups, suggesting that the risk groups can be used as a guide for systemic treatment. We regrouped patients into two clusters based on 11 MRlncRNAs expression. Next, we conducted immune scores for 2 clusters, which showed that cluster 1 had higher stromal scores, immune scores and higher estimated (microenvironment) scores, demonstrating that TME of cluster 1 was different from cluster 2. The results of this study support that MRlncRNAs can predict tumor prognosis and help differentiate patients with different sensitivities to immunotherapy as a basis for individualized treatment for BC patients.
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Breast Neoplasms , Lung Neoplasms , RNA, Long Noncoding , Humans , Female , Breast Neoplasms/genetics , RNA, Long Noncoding/genetics , ROC Curve , Tumor MicroenvironmentABSTRACT
Objective: To evaluate the safety of the combination of pegylated liposomal doxorubicin and docetaxel in neoadjuvant therapy for breast cancer (BC) with axillary lymph nodes metastasis. Methods: In this single-arm study, 91 patients with clinical stage IIA-IIIc BC received 6 cycles of pegylated liposomal doxorubicin plus docetaxel as neoadjuvant chemotherapy (NAC). Trastuzumab was allowed in patients with human epidermal growth factor receptor 2-positive tumors. The effects of new anthracycline-polyethylene glycol liposomal doxorubicin on the patients' hearts were studied. The changes in left ventricular ejection fraction (LVEF) before and after treatment were evaluated by echocardiography, and the levels of cardiac-specific biomarker troponin I (cTnI) and N terminal B natriuretic peptide (NT-pro-BNP) were noted before and after treatment. Result: In our study, 88 patients completed 6 cycles of neoadjuvant chemotherapy. LVEF was within normal range; average LVEF was 67% at baseline, 66% after NAC. The difference was not statistically significant. However, LVEF decreased by more than 10% in 44.4% of patients. There was no significant difference in troponin I or NT-pro-BNP levels before or after treatment. No cardiac events with clinical symptoms were reported. Conclusion: The combination of polyethylene glycol liposome adriamycin and docetaxel in neoadjuvant chemotherapy in patients with early BC with axillary lymph node metastasis has certain cardiac safety. And in the human epidermal growth factor receptor-2 (HER-2) positive population, polyethylene glycol liposome adriamycin combined with docetaxel and trastuzumab also has certain cardiac safety.
Subject(s)
Breast Neoplasms , Humans , Female , Breast Neoplasms/drug therapy , Docetaxel/therapeutic use , Neoadjuvant Therapy/adverse effects , Liposomes/therapeutic use , Lymphatic Metastasis , Stroke Volume , Troponin I , Taxoids/adverse effects , Ventricular Function, Left , Doxorubicin/adverse effects , Trastuzumab/adverse effects , Polyethylene Glycols/therapeutic useABSTRACT
PURPOSE: Previous studies have shown that an inversed albumin-to-globulin ratio (IAGR) is a predictor of the prognosis of many cancers. However, the prognostic value of an IAGR for patients with hepatocellular carcinoma (HCC) who undergo transarterial chemoembolization (TACE) is still unclear. This study aims to evaluate the predictive value of an IAGR for the prognosis of those patients. METHODS: This study retrospectively analyzed 396 patients with HCC who received TACE. Using a cut-off value of 1.0 for the albumin-to-globulin ratio, patients were divided into a normal albumin-to-globulin ratio (NAGR) (≥1) and an IAGR (<1) group. Univariate and multivariate analyses and time-dependent receiver operating characteristic analyses were performed to identify risk factors of overall survival (OS) and cancer-specific survival (CSS). Survival nomograms were constructed based on the multivariable analysis results and further evaluated using the consistency index (C-index) and calibration curve. RESULTS: A total of 396 patients were included in the final analysis and were divided into the NAGR group (n = 298, 75.3%) and the IAGR (n = 98, 24.7%) group. The median OS and CSS were significantly worse in the IAGR group than in the NAGR group (OS: 8 vs. 26 months, CSS: 10 vs. 41 months, both P < 0.001). Multivariate analyses demonstrated that an IAGR was an independent risk factor for predicting worse OS [hazard ratio (HR), 2.024; 95% confidence interval (CI): 1.460-2.806] and CSS (HR: 2.439; 95% CI: 1.651-3.601). The nomogram-based model-related C-indexes for OS and CSS prediction were 0.715 (95% CI: 0.697-0.733) and 0.750 (95% CI: 0.729-0.771), and the calibration of the nomogram showed good consistency. CONCLUSION: The IAGR along with underlying liver disease severity were the useful prognostic predictors of OS and CSS among patients with HCC undergoing TACE and might be useful to identify high-risk patients.
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Carcinoma, Hepatocellular , Chemoembolization, Therapeutic , Globulins , Liver Neoplasms , Humans , Carcinoma, Hepatocellular/therapy , Carcinoma, Hepatocellular/pathology , Prognosis , Liver Neoplasms/therapy , Liver Neoplasms/pathology , Retrospective Studies , Chemoembolization, Therapeutic/methods , Patient Acuity , AlbuminsABSTRACT
As an important element in regulating the tumor microenvironment (TME), integrin plays a key role in tumor progression. This study aimed to establish prognostic signatures to predict the overall survival and identify the immune landscape of patients with lung adenocarcinoma based on integrins. The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus datasets were used to obtain information on mRNA levels and clinical factors (GSE72094). The least absolute shrinkage and selection operator (LASSO) model was used to create a prediction model that included six integrin genes. The nomogram, risk score, and time-dependent receiver operating characteristic analysis all revealed that the signatures had a good prognostic value. The gene signatures may be linked to carcinogenesis and TME, according to a gene set enrichment analysis. The immunological and stromal scores were computed using the ESTIMATE algorithm, and the data revealed, the low-risk group had a higher score. We discovered that the B lymphocytes, plasma, CD4+ T, dendritic, and mast cells were much higher in the group with low-risk using the CiberSort. Inflammatory processes and several HLA family genes were upregulated in the low-risk group. The low-risk group with a better prognosis is more sensitive to immune checkpoint inhibitor medication, according to immunophenoscore (IPS) research. We found that the patients in the high-risk group were more susceptible to chemotherapy than other group patients, according to the prophetic algorithm. The gene signatures could accurately predict the prognosis, identify the immune status of patients with lung adenocarcinoma, and provide guidance for therapy.
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Adenocarcinoma of Lung , Lung Neoplasms , Humans , Tumor Microenvironment , Carcinogenesis , IntegrinsSubject(s)
COVID-19 , Humans , COVID-19/epidemiology , Triage , Incidence , Endoscopy, Gastrointestinal , Polymerase Chain Reaction , COVID-19 TestingABSTRACT
Introduction: Post-hepatectomy liver failure (PHLF) is one of the most serious complications and causes of death in patients with hepatocellular carcinoma (HCC) after hepatectomy. This study aimed to develop a novel machine learning (ML) model based on the light gradient boosting machines (LightGBM) algorithm for predicting PHLF. Methods: A total of 875 patients with HCC who underwent hepatectomy were randomized into a training cohort (n=612), a validation cohort (n=88), and a testing cohort (n=175). Shapley additive explanation (SHAP) was performed to determine the importance of individual variables. By combining these independent risk factors, an ML model for predicting PHLF was established. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, and decision curve analyses (DCA) were used to evaluate the accuracy of the ML model and compare it to that of other noninvasive models. Results: The AUCs of the ML model for predicting PHLF in the training cohort, validation cohort, and testing cohort were 0.944, 0.870, and 0.822, respectively. The ML model had a higher AUC for predicting PHLF than did other non-invasive models. The ML model for predicting PHLF was found to be more valuable than other noninvasive models. Conclusion: A novel ML model for the prediction of PHLF using common clinical parameters was constructed and validated. The novel ML model performed better than did existing noninvasive models for the prediction of PHLF.
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Objective: To develop a nomogram for predicting post-hepatectomy liver failure (PHLF) in patients with resectable hepatocellular carcinoma (HCC) based on portal hypertension, the extent of resection, ALT, total bilirubin, and platelet count. Methods: Patients with HCC hospitalized from January 2015 to December 2020 were included in a retrospective cohort study. 595 HCC patients were divided into a training cohort (n=416) and a validation cohort (n=179) by random sampling. Univariate and multivariable analyses were performed to identify the independent variables to predict PHLF. The nomogram models for predicting the overall risk of PHLF and the risk of PHLF B+C were constructed based on the independent variables. Comparisons were made by using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) with traditional models, such as FIB-4 score, APRI score, CP class (Child-Pugh), MELD score (model of end-stage liver disease), and ALBI score (albumin-bilirubin) to analyze the accuracy and superiority of the nomogram. Results: We discovered that portal hypertension (yes vs no) (OR=1.677,95% CI:1.817-4.083, p=0.002), the extent of liver resection (OR=1.872,95% CI:3.937-47.096, p=0.001), ALT (OR=1.003,95% CI:1.003-1.016, P=0.003), total bilirubin (OR=1.036,95% CI:1.031-1.184, p=0.005), and platelet count (OR= 1.004, 95% CI:0.982-0.998, p=0.020) were independent risk factors for PHLF using multifactorial analysis. The nomogram models were constructed using well-fit calibration curves for each of these five covariates. When compared to the FIB4, ALBI, MELD, and CP score, our nomogram models have a better predictive value for predicting the overall risk of PHLF or the risk of PHLF B+C. The validation cohort's results were consistent. DCA also confirmed the conclusion. Conclusion: Our models, in the form of static nomogram or web application, were developed to predict PHLF overall risk and PHLF B+C risk in patients with HCC, with a high prediction sensitivity and specificity performance than other commonly used scoring systems.
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Purpose: To determine the predictive value of portal hypertension (PH) for the development of post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). Patients and methods: This study enrolled a total of 659 patients with HCC that received hepatectomy as a first-line therapy. PH was classified as grade 0, 1, and 2 according to whether the indirect criteria for PH were met: 1) patients had obvious varicose veins and 2) splenomegaly was present and platelet count < 100 × 109/L. The effects of each variable on the occurrence of PHLF were assessed using univariate and multivariate analyses. Results: PH grade 2 (odds ratio [OR] = 2.222, p = 0.011), higher age (OR = 1.031, p = 0.003), hepatitis C infection (OR = 3.711, p = 0.012), open surgery (OR = 2.336, p < 0.001), portal flow blockage (OR = 1.626, p = 0.023), major hepatectomy (OR = 2.919, p = 0.001), hyperbilirubinemia (≥ 17.2 µmol/L, OR = 2.113, p = 0.002), and high levels of alpha-fetoprotein (> 400n g/ml, OR = 1.799, p = 0.008) were significantly associated with PHLF occurrence. We performed a subgroup analysis of liver resection and found that the extent of liver resection and PH grade were good at distinguishing patients at high risk for PHLF, and we developed an easy-to-view roadmap. Conclusion: PH is significantly related to the occurrence of PHLF in patients who underwent hepatectomy. Noninvasively assessing PH grade can predict PHLF risk.
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Data on safety and immunogenicity of coronavirus disease 2019 (COVID-19) vaccinations in hepatocellular carcinoma (HCC) patients are limited. In this multicenter prospective study, HCC patients received two doses of inactivated whole-virion COVID-19 vaccines. The safety and neutralizing antibody were monitored. Totally, 74 patients were enrolled from 10 centers in China, and 37 (50.0%), 25 (33.8%), and 12 (16.2%) received the CoronaVac, BBIBP-CorV, and WIBP-CorV, respectively. The vaccines were well tolerated, where pain at the injection site (6.8% [5/74]) and anorexia (2.7% [2/74]) were the most frequent local and systemic adverse events. The median level of neutralizing antibody was 13.5 (interquartile range [IQR]: 6.9-23.2) AU/ml at 45 (IQR: 19-72) days after the second dose of vaccinations, and 60.8% (45/74) of patients had positive neutralizing antibody. Additionally, lower γ-glutamyl transpeptidase level was related to positive neutralizing antibody (odds ratio = 1.022 [1.003-1.049], p = 0.049). In conclusion, this study found that inactivated COVID-19 vaccinations are safe and the immunogenicity is acceptable or hyporesponsive in patients with HCC. Given that the potential benefits may outweigh the risks and the continuing emergences of novel severe acute respiratory syndrome coronavirus 2 variants, we suggest HCC patients to be vaccinated against COVID-19. Future validation studies are warranted.