Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The “Estimation of STromal and Immune cells in MAlignant Tumors using Expression data” algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain FABP3, GALNT5, GPR84, ITGB6, MYEOV, PLEKHS1, and STRA6 and may be candidate biomarkers for HCC prognosis.

Background. The prognosis of pancreatic adenocarcinoma (PAAD) is extremely poor and has not been improved. Thus, an effective method to assess the prognosis of patients must be established to improve their survival rate. Method. This study investigated immune‐related genes that could be used as potential therapeutic targets for PAAD. Level 3 gene expression data from the PAAD cohort and the relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. For validation, other PAAD datasets (DSE62452) were downloaded from the Gene Expression Omnibus (GEO) database. The PAAD datasets from TCGA and GEO were used to screen immune‐related genes through the Molecular Signatures Database using gene set enrichment analysis. Then, the overlapping immune‐related genes of the two datasets were identified. Coexpression networks of the immune‐related genes were constructed. Results. A signature of three immune‐related genes (CKLF, ERAP2, and EREG) was identified in patients with PAAD. The signature could be used to divide the patients with PAAD into high‐ and low‐risk groups based on their median risk score. Multivariate Cox regression analysis was performed to determine the independent prognostic factors of PAAD. Time‐dependent receiver operating characteristic (ROC) curve analysis was conducted to assess the prediction accuracy of the prognostic signature. Last, a nomogram was established to assess the individualized prognosis prediction model based on the clinical characteristics and risk score of the TCGA PAAD dataset. The accuracy of the prognostic signature was further evaluated through functional evaluation and principal component analysis. Conclusions. The results indicated that the signature of three immune‐related genes had excellent predictive value for PAAD. These findings might help improve personalized treatment and medical decisions.

Background: Associating liver partition with portal vein ligation for staged liver resection (ALPPS) has been used in the treatment of patients with advanced or massive liver cancer without sufficient future liver remnant, but concerns remain regarding tumor outcomes and surgical safety. This study aims to evaluate the efficacy and safety of a new procedure, hepatic artery restriction operation combined with ALPPS (HARO-ALPPS), in the treatment of hepatocellular carcinoma (HCC) patients especially with severe fibrosis. Methods: This retrospective study analyzed 8 patients who underwent HARO-ALPPS for HCC and compared their outcomes with 64 patients who underwent conventional ALPPS. The primary outcomes assessed were liver regeneration ability (measured by relative and absolute kinetic growth rates), postoperative complications, and mortality. The secondary outcomes included overall survival and disease-free survival. Results: HARO-ALPPS significantly restricted the blood supply of the hepatic artery. One week after surgery, the blood flow of the right hepatic artery dropped to 62.1%. At the same time, HARO-ALPPS shows superior liver regeneration ability, which is particularly prominent in the background of liver fibrosis. No serious complications occurred after HARO-ALPPS. The overall survival rate of HARO-ALPPS was 75%, which was higher than that of ALPPS (64%, P=0.816). Conclusion: Compared to conventional ALPPS, HARO-ALPPS exhibits a better liver regeneration ability, and favorable long-term outcomes. Further prospective studies are needed to validate these findings and evaluate the long-term oncologic outcomes of this novel procedure.

The present study was aimed at identifying the potential prognostic biomarkers of the immune‐related long noncoding RNA (IRL) signature for patients with hepatocellular carcinoma (HCC). RNA‐sequencing data and clinical information about HCC were obtained from The Cancer Genome Atlas. The IRLs were determined with regard to the coexpression of immune‐related genes and differentially expressed lncRNAs. The survival IRLs were obtained using the univariate Cox analysis. Subsequently, the prognosis model was constructed via the multivariate Cox analysis. Subsequently, functional annotation was conducted using Gene Set Enrichment Analysis (GSEA) and principal component analysis (PCA). In total, 341 IRLs were identified, and 6 IRLs were found to have a highly significant association with the prognosis of patients with HCC. The immune prognosis model was constructed with these 6 IRLs (AC099850.4, negative regulator of antiviral response, AL031985.3, PRRT3‐antisense RNA1, AL365203.2, and long intergenic nonprotein coding RNA 1224) using the multivariate Cox regression analysis. In addition, immune‐related prognosis signatures were confirmed as an independent prognostic factor. The association between prognostic signatures and immune infiltration indicated that the 6 lncRNAs could reflect the immune status of the tumor. Collectively, the present study demonstrates that six‐lncRNA signatures may be potential biomarkers to predict the prognosis of patients with HCC.

Background: Hypoxia is a key factor in the development of hepatocellular carcinoma (HCC), which is the most common primary liver cancer with poor prognosis. The current study aimed to identify the potential prognostic biomarkers of the hypoxia-associated gene signature in patients with HCC, and to further explore the relationship between hypoxia and immune infiltration. Methods: After the determination of differentially expressed genes (DEGs) using the HCC transcriptome data of The Cancer Genome Atlas database and hypoxia-related gene set, the prognosis-associated genes were identified using univariate Cox regression analysis. Then, the hypoxia prognosis model was established via multivariate Cox regression analysis, with functional annotation conducted using Gene Set Enrichment Analysis. CIBERSORT was utilized to analyze the degree of tumor immune invasion, and an International Cancer Genome Consortium cohort to verify the reliability of the prognosis model. Expression levels of hypoxia-associated genes were detected by real-time quantitative polymerase chain reaction in HCC samples. Results: 3 genes (ENO1, SAP30, and STC2) constructed the hypoxia prognosis model. The patients were subdivided into 2 groups based on median risk score, with a high hypoxic score indicating poor prognosis of HCC. The hypoxia signature could be employed as an independent prognostic factor in HCC. In addition, the proportion of macrophages was higher in the high-risk group. Conclusion: The hypoxia-associated signature could be a potential prognostic marker of HCC and provides a different perspective for immunotherapy of HCC.