Predicting cancer-specific mortality in T1/2 hepatocellular carcinoma after radiofrequency ablation by competing risk nomogram: A population-based analysis.

BACKGROUND: Radiofrequency ablation (RFA) is one of the primary treatment methods for T1/2 hepatocellular carcinoma (HCC), but the risk factors after RFA remain controversial. This study aims to identify the key factors associated with cancer-specific mortality (CSM) in patients with T1/2 HCC after RFA using competing risk analysis and to establish a prognostic nomogram for improved clinical management. METHODS: A total of 2,135 T1/2 HCC patients treated with RFA were obtained from the Surveillance, Epidemiology, and End Results (SEER) database and randomly categorized into training and validation sets. Univariate and multivariable competing risk analyses were performed to identify risk factors associated with CSM and construct a competing risk nomogram. Receiver operating characteristic (ROC) curves, concordance indices (C-indexes), calibration plots, and decision curve analysis (DCA) were conducted to evaluate the predictive efficiency and clinical applicability of the nomogram in the training and validation sets. Patients were stratified according to their nomogram score, and the different risk groups were compared using cumulative incidence function (CIF) curves and Gray's validation . RESULTS: The 5-year CSM rate for HCC patients treated with RFA was 30.1 %. Grade, tumor size, tumor number, cirrhosis, and AFP level were identified as independent risk factors for CSM. A prognostic nomogram was developed based on these risk factors. The time-dependent C-indexes (0.65) were greater than those of the AJCC stage model (0.55) during the 12 to 60 months of follow-up. The calibration plots of the competing risk nomograms demonstrated excellent consistency between actual survival and nomogram predictions. ROC analyses showed that the 1-, 3-, and 5-year AUC values in both the training and validation cohorts were all greater than 0.63 and exceeded those of the AJCC stage model. DCA demonstrated the clinical usefulness of the nomogram. Patients were classified into low-, moderate-, and high-risk groups based on the nomogram scores, with the high-risk group showing significantly higher CSM rates after RFA compared to the other two groups. CONCLUSIONS: We identified Grade, AFP, cirrhosis, tumor size, and tumor number as independent risk factors associated with CSM. The competing risk nomogram exhibited high performance in predicting the probability of CSM for HCC patients undergoing RFA.

Comprehensive bioinformatics analysis reveals the crosstalk genes and immune relationship between the systemic lupus erythematosus and venous thromboembolism.

Background: It is well known that patients with systemic lupus erythematosus (SLE) had a high risk of venous thromboembolism (VTE). This study aimed to identify the crosstalk genes between SLE and VTE and explored their clinical value and molecular mechanism initially. Methods: We downloaded microarray datasets of SLE and VTE from the Gene Expression Omnibus (GEO) dataset. Differential expression analysis was applied to identify the crosstalk genes (CGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the shared genes. The shared diagnostic biomarkers of the two diseases were further screened from CGs using least absolute shrinkage and selection operator (Lasso) regression. Two risk scores for SLE and VTE were constructed separately to predict the likelihood of illness according to the diagnostic biomarkers using a logical regression algorithm. The immune infiltration levels of SEL and VTE were estimated via the CIBERSORT algorithm and the relationship of CGs with immune cell infiltration was investigated. Finally, we explored potential phenotype subgroups in SLE and VTE based on the expression level of CGs through the consensus clustering method and studied immune cell infiltration in different subtypes. Result: A total of 171 CGs were obtained by the intersection of differentially expressed genes (DEGs) between SLE and VTE cohorts. The functional enrichment shown these CGs were mainly related to immune pathways. After screening by lasso regression, we found that three hub CGs (RSAD2, HSP90AB1, and FPR2) were the optimal shared diagnostic biomarkers for SLE and VTE. Based on the expression level of RSAD2 and HSP90AB1, two risk prediction models for SLE and VTE were built by multifactor logistic regression and systemically validated in internal and external validation datasets. The immune infiltration results revealed that CGs were highly correlated with multiple infiltrated immunocytes. Consensus clustering was used to respectively regroup SLE and VTE patients into C1 and C2 clusters based on the CGs expression profile. The levels of immune cell infiltration and immune activation were higher in C1 than in C2 subtypes. Conclusion: In our study, we further screen out diagnostic biomarkers from crosstalk genes SLE and VTE and built two risk scores. Our findings reveal a close relationship between CGs and the immune microenvironment of diseases. This provides clues for further exploring the common mechanism and interaction between the two diseases.

Immune infiltration and clinical significance analyses of the coagulation-related genes in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common types of cancers and a global health challenge with a low early diagnosis rate and high mortality. The coagulation cascade plays an important role in the tumor immune microenvironment (TME) of HCC. In this study, based on the coagulation pathways collected from the KEGG database, two coagulation-related subtypes were distinguished in HCC patients. We demonstrated the distinct differences in immune characteristics and prognostic stratification between two coagulation-related subtypes. A coagulation-related risk score prognostic model was developed in the Cancer Genome Atlas (TCGA) cohort for risk stratification and prognosis prediction. The predictive values of the coagulation-related risk score in prognosis and immunotherapy were also verified in the TCGA and International Cancer Genome Consortium cohorts. A nomogram was also established to facilitate the clinical use of this risk score and verified its effectiveness using different approaches. Based on these results, we can conclude that there is an obvious correlation between the coagulation and the TME in HCC, and the risk score could serve as a robust prognostic biomarker, provide therapeutic benefits for chemotherapy and immunotherapy and may be helpful for clinical decision making in HCC patients.

Development and Validation of TACE Refractoriness-Related Diagnostic and Prognostic Scores and Characterization of Tumor Microenvironment Infiltration in Hepatocellular Carcinoma.

Background: Transcatheter arterial chemoembolization LIHC, Liver hepatocellular carcinoma; (TACE) is a valid therapeutic method for hepatocellular carcinoma (HCC). However, many patients respond poorly to TACE, thus leading to an adverse outcome. Therefore, finding new biomarkers for forecasting TACE refractoriness occurrence and prognosis becomes one of the current research priorities in the field of HCC treatment. Materials and Methods: Based on microarray datasets and a high-throughput sequencing dataset, the TACE refractoriness-related genes (TRGs) were identified by differential expression analysis. LASSO and Cox regression were applied to construct TACE refractoriness diagnostic score (TRD score) and prognostic score (TRP score) and validated their accuracy in external datasets. Functional correlation of TRP score was analyzed by gene set variation analysis and Gene Ontology. CIBERSORT and IMMUNCELL AI algorithms were performed to understand the correlation between the two scores and immune activity. We further carried out the efficacy analysis of immunotherapy and targeted drugs in the different TRP score groups. Furthermore, a nomogram was built by integrating various independent prognostic factors and validated its effectiveness in different datasets. Results: We identified 487 TRGs combined with GSE104580 and TCGA datasets. Then four novel TRGs (TTK, EPO, SLC7A11, and PON1) were screened out to construct TRD score and TRP score models, and both two scores had good predictive ability in external datasets. Tumors with high TRP score show an immunosuppressive phenotype with more infiltrations of regulatory T cells and macrophages. Immunotherapy and chemotherapy response evaluation revealed patients with a high TRP score demonstrated well reactions to immune checkpoint inhibitors (ICIs) and sorafenib. TRP score, TNM stage, and cancer type were brought into the combined nomogram with optimum prediction. Conclusions: Our research provided dependable and simplified methods for patients with HCC to assess tumors' susceptibility to TACE refractoriness and prognosis and guide patients' clinical therapy choices.

Construction and Validation of Two Hepatocellular Carcinoma-Progression Prognostic Scores Based on Gene Set Variation Analysis.

Background: Liver hepatocellular carcinoma (LIHC) remains a global health challenge with a low early diagnosis rate and high mortality. Therefore, finding new biomarkers for diagnosis and prognosis is still one of the current research priorities. Methods: Based on the variation of gene expression patterns in different stages, the LIHC-development genes (LDGs) were identified by differential expression analysis. Then, prognosis-related LDGs were screened out to construct the LIHC-unfavorable gene set (LUGs) and LIHC-favorable gene set (LFGs). Gene set variation analysis (GSVA) was conducted to build prognostic scoring models based on the LUGs and LFGs. ROC curve analysis and univariate and multivariate Cox regression analysis were carried out to verify the diagnostic and prognostic utility of the two GSVA scores in two independent datasets. Additionally, the key LCGs were identified by the intersection analysis of the PPI network and univariate Cox regression and further evaluated their performance in expression level and prognosis prediction. Single-sample GSEA (ssGSEA) was performed to understand the correlation between the two GSVA enrichment scores and immune activity. Result: With the development of LIHC, 83 LDGs were gradually upregulated and 247 LDGs were gradually downregulated. Combining with LIHC survival analysis, 31 LUGs and 32 LFGs were identified and used to establish the LIHC-unfavorable GSVA score (LUG score) and LIHC-favorable GSVA score (LFG score). ROC curve analysis and univariate/multivariate Cox regression analysis suggested the LUG score and LFG score could be great indicators for the early diagnosis and prognosis prediction. Four genes (ESR1, EHHADH, CYP3A4, and ACADL) were considered as the key LCGs and closely related to good prognosis. The frequency of TP53 mutation and copy number variation (CNV) were high in some LCGs. Low-LFG score patients have active metabolic activity and a more robust immune response. The high-LFG score patients characterized immune activation with the higher infiltration abundance of type I T helper cells, DC, eosinophils, and neutrophils, while the high-LUG score patients characterized immunosuppression with the higher infiltration abundance of type II T helper cells, TRegs, and iDC. The high- and low-LFG score groups differed significantly in immunotherapy response scores, immune checkpoints expression, and IC50 values of common drugs. Conclusion: Overall, the LIHC-progression characteristic genes can be great diagnostic and prognostic signatures and the two GSVA score systems may become promising indices for guiding the tumor treatment of LIHC patients.

Effective Disease Control After Combinatorial Treatment with a PD-1 Antibody and an mTOR Inhibitor for Recurrent Ovarian Clear Cell Carcinomas: A Case Report and Literature Review.

Ovarian clear cell carcinoma (OCCC) is a rare type of epithelial ovarian cancer characterized by a chemoresistant phenotype and high-grade tumor. Conventional therapies for OCCC include surgery and chemotherapy. However, these OCCC treatment approaches are characterized by a high risk of relapse and drug resistance resulting in poor prognosis. Therefore, alternative therapeutic approaches are required to achieve better outcomes. In this study, a PIK3CA p.R88Q mutation and PD-L1 expression with a tumor proportion score of 10% was explored in a patient who presented with rapid recurrence after surgery and unsuccessful postoperative chemotherapy. Based on the clinical condition and the patient preference, she was administered a novel combinatorial therapy comprising mTOR inhibitor everolimus, which is a well-known and potent inhibitor of the PI3K/AKT signaling pathway, and the anti-PD-1 antibody toripalimab. Treatment with this combinatorial therapy showed good prognosis, with more than eight months of disease control, and no severe adverse events were observed. The findings of this study provide a novel and effective strategy for OCCC patients. To the best of our knowledge, this is the first study to report a new combination regimen of immunotherapy (everolimus plus toripalimab) for solid tumors. Everolimus is not only an antitumor targeted drug but also an immunosuppressant; it's combination with immunotherapy is controversial. This is the first report to demonstrate that it has a synergistic effect.

The Association of High Resolution Cervical Auscultation Signal Features With Hyoid Bone Displacement During Swallowing.

Recent publications have suggested that high-resolution cervical auscultation (HRCA) signals may provide an alternative non-invasive option for swallowing assessment. However, the relationship between hyoid bone displacement, a key component to safe swallowing, and HRCA signals is not thoroughly understood. Therefore, in this work we investigated the hypothesis that a strong relationship exists between hyoid displacement and HRCA signals. Videofuoroscopy data was collected for 129 swallows, simultaneously with vibratory/acoustic signals. Horizontal, vertical and hypotenuse displacements of the hyoid bone were measured through manual expert analysis of videofluoroscopy images. Our results showed that the vertical displacement of both the anterior and posterior landmarks of the hyoid bone was strongly associated with the Lempel-Ziv complexity of superior-inferior and anterior-posterior vibrations from HRCA signals. Horizontal and hypotenuse displacements of the posterior aspect of the hyoid bone were strongly associated with the standard deviation of swallowing sounds. Medial-Lateral vibrations and patient characteristics such as age, sex, and history of stroke were not significantly associated with the hyoid bone displacement. The results imply that some vibratory/acoustic features extracted from HRCA recordings can provide information about the magnitude and direction of hyoid bone displacement. These results provide additional support for using HRCA as a non-invasive tool to assess physiological aspects of swallowing such as the hyoid bone displacement.