Background: Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes.Methods: Immune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups.Result: A total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, p < 0.01), higher T stage (p < 0.05), higher clinical stage (p < 0.05), higher pathological grade (p < 0.05), low immune cell infiltration (CD4⁺ T cells, B cells, macrophages, neutrophils, and myeloid dendritic cells), low immune checkpoint gene expression, poor response to ICB therapy, and high stemness. Different molecular subtypes and risk groups showed significantly different responses to several chemotherapy drugs, such as doxorubicin (p < 0.001), 5-fluorouracil (p < 0.001), gemcitabine (p < 0.001), and sorafenib (p < 0.01).Conclusion: Our study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC.

Macrophages play important roles in angiogenesis; however, previous studies on macrophage angiogenesis have focused on traditional 2D cultures. In this study, we established a 3D culture system for macrophages using collagen microcarriers and assessed the effect of 3D culture on their angiogenic capabilities. Macrophages grown in 3D culture displayed a significantly different morphology and arrangement under electron microscopy compared to those grown in 2D culture. Tube formation assays and chick embryo chorioallantoic membrane assays further revealed that 3D-cultured macrophages were less angiogenic than those in 2D culture. Whole-transcriptome sequencing showed that nearly 40% of genes were significantly differently expressed, including nine important angiogenic factors of which seven had been downregulated. In addition, the expression of almost all genes related to two important angiogenic pathways was decreased in 3D-cultured macrophages, including the two key angiogenic factors, VEGFA and ANG2. Together, the findings of our study improve our understanding of angiogenesis and 3D macrophage culture in tissues, and provide new avenues and methods for future research on macrophages.

Introduction: Given the poor prognosis associated with hepatocellular carcinoma (HCC), identifying reliable biomarkers is critical to aid in prognostication and customized treatment planning. Objective: This study aimed to develop a prognostic gene signature based on anoikis- and autophagy-related genes (AARGs) to predict HCC prognosis. Methods: We analyzed differentially expressed AARGs associated with HCC prognosis using messenger RNA expression profiles and clinicopathological data from the Cancer Genome Atlas Liver Hepatocellular Carcinoma Database. Validation was performed using data from the International Cancer Genome Consortium. AARG signatures were constructed using univariate Cox regression and the least absolute shrinkage and selection operator method. Results: We identified 13 AARGs, of which nine showed significant associations with overall survival (OS). Three AARGs—baculoviral IAP repeat containing 5, mitogen-activated protein kinase 3, and BRI1-associated kinase 1—were selected to establish the prognostic AARGs signature. Statistical analyses confirmed the prognostic capacity of the model. Gene set enrichment analysis was performed to explore potential molecular mechanisms. Further investigations included assessments of clinical parameters, immune landscape, immune checkpoint blockade response, tumor stemness, and chemotherapy sensitivity. Immunohistochemistry was conducted to compare protein expression between normal and tumor tissues. Patients in the high-risk group exhibited advanced tumor stage, shorter survival time, and poorer prognosis, along with anoikis resistance, elevated autophagy, and immunosuppression. The nomogram incorporating the AARG signature showed strong predictive performance for OS. Conclusion: We developed and validated a new AARGs-based signature that effectively predicts prognosis for HCC patients.

Given the poor prognosis of patients with hepatocellular carcinoma (HCC), it is crucial to investigate possible new biomarkers to aid in prognostication and customised treatment. Accordingly, we analysed differentially expressed anoikis- and autophagy-related genes (DE-AARGs) associated with poor outcomes in actual cases of HCC. Analysis of differentially expressed genes (DEGs) was performed based on mRNA expression patterns and clinicopathological information found in the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database. Further validation of TCGA results was performed using the International Cancer Genome Consortium database. AARGs signatures were constructed by applying Univariate COX regression and the Least Absolute Shrinkage and Selection Operator method. We identified 13 AARGs, of which 9 showed significant associations with overall survival. Three AARGs (BIRC5, MAPK3, and BAK1) were selected to establish an AARGs signature. We assessed the prognostic capacity of the AARGs signature through various statistical methods. The molecular mechanisms underpinning this phenomenon were further studied using Gene Set Enrichment Analyses (GSEA). The prognostic ability of the signature was also examined in terms of clinical characteristics, immune landscape, immune checkpoint-blocking response, stemness, and chemotherapy response. Immunohistochemical staining was used to compare the protein expression levels of AARGs between normal liver tissue and HCC tissues. The high-risk group had higher tumour staging, shorter survival time, and worse prognosis than the low-risk group. In addition, high-risk patients showed inhibition of anoikis, a high autophagy index, and a suppressed immune system. The nomogram showed a strong prognostic capability for predicting overall survival in patients with HCC. With this study, a new AARGs-based signature has been developed to reliably predict patient prognosis for HCC.

Background and purpose: Colorectal cancer (CRC) is one of the most common malignant tumors with the highest mortality globally. At present, there is no exact biomarker to predict the prognosis and clinicopathological monitoring of CRC patients. Recent studies on the relationship of Karyopherin α 2 (KPNA2) expression and the prognosis of CRC has gradually become a hot spot while the results are still controversial. The aim of this study was to analyze and assess the prognostic role of KPNA2 in CRC patients. Methods: PubMed, Web of Science, Medline, EMBASE, CNKI, Wanfang, VIP, and Chinese Medical Database were systematically searched. The cohort study of high-level expression of KNPA2 and low-level expression of KPNA2 in CRC patients was included, the relevant data were extracted and the literature quality was evaluated. At the same time, the relationship between KPNA2 expression level and the overall survival (OS), the clinicopathological stage of CRC patients was studied. Meta-analysis was carried out by Stata MP 17.0 (Stata Corporation, College Station, TX, USA) software. Results: A total of 7 cohort studies involving 1166 patients were included. The analysis results showed that higher KPNA2 expression was significantly associated with higher tumor stage (OR=1.90, 95% CI 1.42–2.54), higher degree of tumor invasion (OR=2.14，95% CI 1.55-2.94), more lymph node metastasis (OR=2.20, 95% CI 1.68-2.88) and more distant metastasis (OR=3.66，95% CI 1.81-7.40). Moreover, higher KPNA2 expression was significantly associated with the shorter OS (HR=2.31, 95%CI 1.46-3.68).Conclusion: KPNA2 overexpression is an unfavorable prognostic factor for CRC patients. It could serve as a prognostic biomarker and as a potential therapeutic target for CRC.

BACKGROUND Accumulating evidence suggests that insulin resistance (IR) is closely linked to colorectal cancer (CRC). Some studies have revealed that IR may be associated with metabolites in colonocytes and may play a proto-oncogenic role. OBJECTIVE This study aims to investigate the relationship between colorectal adenoma and insulin resistance and its associated VCAM-1. METHOD 49 patients diagnosed with intestinal polyps between June 2019 and September 2021 at the Shandong Cancer Hospital were recruited in this study. Fasting insulin (Fins), fasting blood glucose (FBG), HOMA-IR, and polyp’s VCAM-1 mRNA levels were determined in these patients. Univariate and multivariate logistic regression analysis to identify independent predictors of the aggressive clinical behavior of polyps. RESULTS Patients with adenomatous polyps had significant higher levels of fasting insulin (Fins), fasting blood glucose (FBG), HOMA-IR, and polyp’s VCAM-1 mRNA than those with inflammatory polyps. Multivariate binary logistic regression analysis indicated that HOMA-IR was an independent predictive factor for adenomatous polyps. Cross-tabulation and Pearson’s chi-square tests identified that adenomatous polyps had higher levels of VCAM-1 than inflammatory polyps. CONCLUSION Colorectal adenoma is positively associated with insulin resistance and polyp’s VCAM-1 expression, suggesting an important role of insulin resistance in the formation and progression of intestinal tumor.