Background: Hepatocellular carcinoma (HCC) is among the deadliest forms of cancer. While RNA-binding proteins (RBPs) have been shown to be key regulators of oncogenesis and tumor progression, their dysregulation in the context of HCC remains to be fully characterized. Methods: Data from the Cancer Genome Atlas - liver HCC (TCGA-LIHC) database were downloaded and analyzed in order to identify RBPs that were differentially expressed in HCC tumors relative to healthy normal tissues. Functional enrichment analyses of these RBPs were then conducted using the GO and KEGG databases to understand their mechanistic roles. Central hub RBPs associated with HCC patient prognosis were then detected through Cox regression analyses, and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, univariate and multivariate Cox regression analyses, and nomograms. Lastly, the relationship between individual hub RBPs and HCC patient overall survival (OS) was evaluated using Kaplan-Meier curves. Finally, find protein-coding genes (PCGs) related to hub RBPs were used to construct a hub RBP-PCG co-expression network. Results: In total, we identified 81 RBPs that were differentially expressed in HCC tumors relative to healthy tissues (54 upregulated, 27 downregulated). Seven prognostically-relevant hub RBPs (SMG5, BOP1, LIN28B, RNF17, ANG, LARP1B, and NR0B1) were then used to generate a prognostic model, after which HCC patients were separated into high- and low-risk groups based upon resultant risk score values. In both the training and test datasets, we found that high-risk HCC patients exhibited decreased OS relative to low-risk patients, with time-dependent area under the ROC curve values of 0.801 and 0.676, respectively. This model thus exhibited good prognostic performance. We additionally generated a prognostic nomogram based upon these seven hub RBPs and found that four other genes were significantly correlated with OS. Conclusion: We herein identified a seven RBP signature that can reliably be used to predict HCC patient OS, underscoring the prognostic relevance of these genes.

Background: The prognosis of lower-grade glioma (LGG) is highly variable, and more accurate predictors are still needed. The aim of our study was to explore the prognostic value of ferroptosis-related long non-coding RNAs (lncRNAs) in LGG and to develop a novel risk signature for predicting survival with LGG. Methods: We first integrated multiple datasets to screen for prognostic ferroptosis-related lncRNAs in LGG. A least absolute shrinkage and selection operator (LASSO) analysis was then utilized to develop a risk signature for prognostic prediction. Based on the results of multivariate Cox analysis, a prognostic nomogram model for LGG was constructed. Finally, functional enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), immunity, and m6A correlation analyses were conducted to explore the possible mechanisms by which these ferroptosis-related lncRNAs affect survival with LGG. Results: A total of 11 ferroptosis-related lncRNAs related to the prognosis of LGG were identified. Based on prognostic lncRNAs, a risk signature consisting of 8 lncRNAs was constructed and demonstrated good predictive performance in both the training and validation cohorts. Correlation analysis suggested that the risk signature was closely linked to clinical features. The nomogram model we constructed by combining the risk signature and clinical parameters proved to be more accurate in predicting the prognosis of LGG. In addition, there were differences in the levels of immune cell infiltration, immune-related functions, immune checkpoints, and m6A-related gene expression between the high- and low-risk groups. Conclusion: In summary, our ferroptosis-related lncRNA signature exhibits good performance in predicting the prognosis of LGG. This study may provide useful insight into the treatment of LGG.

Purpose: This study aimed to identify independent risk factors for non-classic radiation-induced liver disease (ncRILD) in hepatocellular carcinoma (HCC) patients treated with intensity-modulated radiation therapy (IMRT) and to construct a predictive nomogram. Patients and Methods: We retrospectively analyzed 177 primary HCC patients treated with IMRT between 2013 and 2021. Univariate and multivariate analyses were conducted to identify risk factors for ncRILD. A nomogram was developed based on significant variables. Dosimetric parameters were also assessed across different fractionation doses. Results: Multivariate analysis identified tumor number ≥ 2, mean liver dose ≥ 1371.4 cGy, and normal liver volume < 700 mL as independent risk factors for ncRILD. A nomogram was established using logistic regression. In patients receiving ≥ 4 Gy per fraction, ncRILD was significantly associated with Vs5–Vs40 (p < 0.05), but not with V5–V40. No such associations were found for 2 Gy and 3 Gy groups. Conclusion: Patients with multifocal tumor, lower normal liver volume and higher mean liver dose are at increased risk of developing radiation-induced liver injury. These findings suggest that dosimetric parameters, especially at higher fraction doses, may play a critical role in the occurrence of ncRILD.

Original Article Molecular subtyping and IMScore based on immune-related pathways, oncogenic pathways, and DNA damage repair pathways for guiding immunotherapy in hepatocellular carcinoma patients Zeyan Yu, Olivier Vyungura, Yinnong Zhao

This study assesses the effect of postoperative radiotherapy on survival outcomes in patients diagnosed with stage pIIIA-N2 non-small cell lung cancer (NSCLC) after sublobar resection. Data of patients with stage pIIIA-N2 NSCLC who underwent sublobar resection were extracted from the Surveillance, Epidemiology, and End Results database spanning from 2000 to 2020. Patients were divided into 2 groups: postoperative radiotherapy and observation. Cancer-specific survival (CSS) and overall survival (OS) were analyzed and compared between the 2 groups. A total of 444 patients were included in the study, with 210 (47.3%) receiving postoperative radiotherapy and 234 (52.7%) with observation. The CSS (hazard ratio [HR] = 0.99, 95% confidence interval [CI]: 0.78–1.26; P = .926) and OS (HR = 0.93, 95% CI: 0.75–1.15; P = .512) did not show significant differences between the postoperative radiotherapy and observation groups. Subgroup analysis of patients receiving postoperative chemotherapy revealed comparable CSS (HR = 1.24, 95% CI: 0.89–1.71; P = .203) and OS (HR = 1.12, 95% CI: 0.85–1.49; P = .425) between the 2 groups. Similarly, for patients without postoperative chemotherapy, CSS (HR = 1.11, 95% CI: 0.66–1.84; P = .699) and OS (HR = 1.08, 95% CI: 0.68–1.71; P = .740) were not significantly different between the 2 groups. Postoperative radiotherapy does not improve survival in patients with stage pIIIA-N2 NSCLC following sublobar resection.