Background: N6-methyladenosine (m6A) methylation and ferroptosis assist long noncoding RNAs (lncRNAs) in promoting immune escape in hepatocellular carcinoma (HCC). However, the predictive value of m6A- and ferroptosis-related lncRNAs (mfrlncRNAs) in terms of immune efficacy remains unknown.Method: A total of 365 HCC patients with complete data from The Cancer Genome Atlas (TCGA) database were used as the training cohort, and half of them were randomly selected as the validation cohort. A total of 161 HCC patients from the International Cancer Genome Consortium (ICGC) database were used as external validation (ICGC cohort).Results: We first identified a group of specific lncRNAs associated with both m6A regulators and ferroptosis-related genes and then constructed prognosis-related mfrlncRNA pairs. Based on this, the mfrlncRNA signature was constructed using the least absolute shrinkage and selection operator (LASSO) analysis and Cox regression. Notably, the risk score of patients was proven to be an independent prognostic factor and was better than the TNM stage and tumor grade. Moreover, patients with high-risk scores had lower survival rates, higher infiltration of immunosuppressive cells (macrophages and Tregs), lower infiltration of cytotoxic immune cells (natural killer cells), poorer immune efficacy (both immunophenoscore and score of tumor immune dysfunction and exclusion), higher IC₅₀, and enrichment of the induced Treg pathway, which confirmed that the mfrlncRNA signature contributed to survival prediction and risk stratification of patients with HCC.Conclusions: The mfrlncRNA signature, which has great prognostic value, provides new clues for identifying “cold” and “hot” tumors and might have crucial implications for individualized therapy to improve the survival rate of patients with HCC.

Annexin A2 promotion of hepatocellular carcinoma tumorigenesis via the immune microenvironment

Cardiomyocyte apoptosis in response to inflammation is a primary cause of myocardial ischemia-reperfusion injury (IRI). Nuclear factor erythroid 2 like 2 (Nrf2) reportedly plays an important role in myocardial IRI, but the underlying mechanism remains obscure. Expression data from the normal heart tissues of mice or heart tissues treated with reperfusion for 6 h after ischemia (IR6h) were acquired from the GEO database; changes in biological function and infiltrating immune cells were analyzed. The binding between the molecules was verified by chromatin immunoprecipitation sequencing. Based on confirmation that early myocardial ischemia-reperfusion (myocardial ischemia/reperfusion for 6 hours, IR6h) promoted myocardial apoptosis and inflammatory response, we found that Nrf2, cooperating with Programmed Cell Death 4, promoted transcription initiation of C-C Motif Chemokine Ligand 3 (Ccl3) in myocardial tissues of mice treated with IR6h. Moreover, Ccl3 contributed to the high signature score of C-C motif chemokine receptor 1 (Ccr1)-positive macrophages. The high signature score of Ccr1-positive macrophages leads to the release of pro-inflammatory factors interleukin 1 beta and interleukin 6. This study is the first to elucidate the damaging effect of Nrf2 via remodeling of the immune microenvironment in early myocardial ischemia-reperfusion, which provides us with new perspectives and treatment strategies for myocardial ischemia-reperfusion.

Background: Lung adenocarcinoma (LUAD) is one of the tumor‐related diseases with high morbidity worldwide. Epigenetic modifications such as DNA methylation changes may involve in tumorigenesis. This study aimed to explore new biomarkers that have prognostic significance of LUAD.Methods: First, we downloaded the gene expression and methylation data set from Gene Expression Omnibus. R software was then used to identify abnormally methylated differentially expressed genes (MDEGs). Next, R package Cluster Profiler was used to analyze the enrichment and pathway of the MDEGs. Analysis using STRING revealed the protein–protein interaction network. The result was then visualized by Cytoscape and obtained 10 hub genes. Afterward, they were further verified by The Cancer Genome Atlas to select candidate genes. Moreover, quantitative real‐time polymerase chain reaction (qRT‐PCR) and immunohistochemistry were used to verify the expression and prognostic value of candidate genes in LUAD patients.Results: The results showed that the expressions of ADCY5 and PRKCB are indeed related to LUAD. The clinical relevance to PRKCB was confirmed by its clinical correlation analysis. Gene set enrichment analysis (GSEA) and tumor immune estimation resource (TIMER) tumor immune correlations showed that PRKCB is involved in the cancer‐related Kyoto Encyclopedia of Genes and Genomes pathway and is involved in immune infiltration. It was also verified by qRT‐PCR and immunohistochemistry that PRKCB was lowly expressed in LUAD patients and correlated with prognosis.Conclusions: PRKCB is relevant to prognosis of LUAD through methylation and immune infiltration.

Background: Stratification of tumors is necessary to achieve better clinical outcomes. Hepatocellular carcinoma (HCC) is commonly associated with mutation of the TP53 gene and heterogeneity in immune cell content. However, TP53 mutation-associated immunotype of HCC has not been reported yet. This study aimed to identify the TP53 mutation-associated immunotype in HCC. Methods: The mutation annotation format (MAF) document, mRNA expression data, and clinical data of HCC patients were downloaded from the publicly available The Cancer Genome Atlas (TCGA) data portal. Data from 332 HCC patients were analyzed in this study. Infiltrating immune cells were evaluated by the well-known CIBERSORT method. Additional mutation data of HCC patients were downloaded from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. Results: The TP53 gene harbored the highest frequency of mutations in HCC patients. Consequently, five lethal features, including TP53 mutations, were screened by least absolute shrinkage and selector operation (LASSO)-COX regression, according to TP53 mutations and 22 infiltrating immune cells. Two distinct subgroups of HCC were identified, namely, immunotypes A and B. Furthermore, the expression levels of co-inhibitory immune checkpoints were significantly upregulated, and the gene ontology (GO) terms or pathways to boost immune responses were found to be inhibited in the immunotype B subgroup compared to that in the immunotype A subgroup. Finally, we proved immunotype to be an independent adverse prognostic factor that contributed to improvement in the predictive accuracy of the immunotype-based model and helped in avoiding excessive medical treatment. Conclusions: Two distinct immunotypes of HCC, in terms of prognosis, phenotype, and function, were identified and the traditional understanding of intratumoralCD8⁺ T cells was subverted. Moreover, the identified immunotypes contributed to improving the predictive accuracy of the immunotype-based model and helped in avoiding excessive medical treatment in some HCC patients.

Immune checkpoint blockade has revolutionized immunotherapy of lung squamous cell carcinoma (LUSC), but the effective rate is less than 30% attributing to no effective and reliable method for predicting immune response. However, the clinical value of N6‐methyladenosine (m⁶A) and immune‐related lncRNA (mirlncRNA) concerning immune efficacy remains unknown. First, we identified a packet of specific mirlncRNA. Based on this, patients with LUSC were optimally divided into mirlncRNA clusters A, B, and C. The mirlncRNA cluster A was categorized as an immune‐inflamed phenotype distinguished by infiltration of numerous immune cells such as tumor‐infiltrating lymphocyte cells and highlighted by pathways such as regulation of myeloid leukocyte differentiation, while clusters B and C were found to correspond to immune‐desert and immune‐excluded phenotypes, respectively. Furthermore, the immune‐inflamed phenotype was shown to possess the highest immune infiltration, the lowest chromatin accessibility, survival rates, half inhibitory concentration (IC₅₀), and the best immune efficacy. Finally, risk scores derived from the mirlncRNA signature helped identify subgroups of patients who could significantly benefit from immunotherapy. Encouragingly, in the population with poor response to the three targeted drugs, the immune response of patients with low drug sensitivity is significantly improved, indicating the vitality of combined therapy. The mirlncRNA signature not only identifies molecular typing and distinguishes chromatin accessibility, but also further highlights the immune efficacy and drug sensitivity, which might contribute to developing a new strategy for immunotherapy‐based individualized treatment.