Objective Costimulatory molecules have been demonstrated to exert essential roles in multiple cancers. However, their role in lung cancer remains elusive. Here, we sought to identify costimulatory molecule-related lncRNAs in non-small cell lung cancer (NSCLC) and establish a prognostic signature to predict the prognosis of patients with NSCLC. Methods A total of 535 lung adenocarcinoma (LUAD) and 502 lung squamous cell carcinoma (LUSC) patients from the cancer genome atlas (TCGA) database were recruited. A novel costimulatory molecule-based lncRNA prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival. The Homo_sapiens.GRCh38 data set was set as a reference file for probe annotation. Results A total of 593 costimulatory molecule-related lncRNAs were extracted. After analysis, six costimulatory molecule-related lncRNAs (AC084859.1, AC079949.2, HSPC324, LINC01150, LINC01150, and AC090617.5) were screened. A prognostic model based on the six lncRNAs was established using systematic bioinformatics analyses. The prognostic model had a prognostic value in NSCLC patients. Furthermore, a prognostic nomogram was established based on clinical parameters and a risk-score model. Patients with different risk scores had considerably different tumor-infiltrating immune cells, somatic mutational loading, clinical outcomes, signaling pathways, and immunotherapy efficacy. In addition, LINC01137 was associated with unfavorable disease outcomes and fueled tumor progression in NSCLC. Conclusion Taken together, our study demonstrated that a costimulatory molecule-related lncRNA model could be a potential prognostic biomarker in NSCLC. Moreover, LINC01137 could facilitate the proliferation and invasion of lung cancer.

Background mRNA vaccines are emerging as new targets for cancer immunotherapy. However, the potential tumor antigens for mRNA vaccine design in hepatocellular carcinoma (HCC) remain to be elucidated. Methods Genetic and RNA-Seq data were obtained from TCGA and ICGC. Tumor-specific antigens (TSAs) were identified by differential expression, mutation status, HLA binding, antigen-presenting cell (APC) correlation, immune checkpoint (ICP) relevance and prognosis. Consensus clustering was used for patient classification. The molecular and immune status of TSAs and clustered patients, including prognostic ability, tumor microenvironment, tumor-related signature and tumor immune dysfunction and exclusion (TIDE), were further characterized. Results Five dysregulated and mutated TSAs were identified in HCC (TSA5): FXYD6, JAM2, GALNT16, C7, and CCDC146. Seven immune gene modules and five immune subtypes (IS1-IS5) of HCC were identified. The immune subtypes and TSA5-related modules showed distinct molecular, cellular and clinical characteristics. According to our study, IS1 patients may be suitable for vaccination.

Dear Editor, Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide. Currently, the overall response rate of immune checkpoint blockade (ICB) is only 15%–20% in HCC patients, suggesting the critical need to overcome this barrier via a comprehensive examination of the mechanisms underlying local and systemic antitumour immune responses.1 Here, we explored the association between flavin mono-oxygenase enzyme 4 (FMO4) and immuno-metabolic signatures in HCC. Our results indicate that FMO4 may be a useful prognostic biomarker and therapeutic target for HCC. FMO4 expression was decreased in tumour tissues relative to normal tissues inmultiple HCC cohorts (Figure 1A). Overall survival (OS) and progression-free interval were significantly reduced in FMO4low tumours when using median value as cut-off (Figure 1B). FMO4low remained a significant predictive factor for survival in HCC patients after multivariate analysis (Figure S1C). In addition, FMO4low group’s genomic landscape was substantially different from that of the FMO4high group (Figure 1C, Figure S1F,G). FMO4low HCCs were linked with increased expression of members of the APOBEC3 genes (Figure 1D), which contribute to cancer heterogeneity. A negative correlation between FMO4 and tumour burdern or microsatellite instability was observed, indicating that FMO4low HCCs are more immunogenic2 (Figure 1E). Next, co-expression and cluster analysis clearly revealed two clusters of differentially expressed genes (DEGs) associated with FMO4 status (Figure 1F). Using the LASSO method to identify the top candidate DEGs (FMO4-related signature, FRS; Figure S2F–H), patients with a low FRS had a substantially longer OS and survival probability in various HCC cohorts (Figure 1G, Tables S1 and S2).This re-validated the conclusion that FMO4 was a prognostic biomarker in HCC. Metabolic alterations are one of the hallmarks of cancer.3 We next investigated the configuration of the

Basic leucine zipper and W2 domain 2 (BZW2), also known as 5MP1, is a protein related to translation regulation. Evidence from previous studies indicates that BZW2 is involved in tumorigenesis in several cancers. However, little is known about the role of BZW2 in hepatocellular carcinoma (HCC). In this study, we first analyzed the gene expression profile of BZW2 in multiple HCC datasets. Next, we explored the biological effects of BZW2 in HCC cell lines. BZW2 was overexpressed in different HCC cohorts. Multivariate analysis confirmed that increased BZW2 expression is an independent prognostic indicator of shorter overall survival. BZW2 coexpressed genes were mainly enriched in the biological processes of ribonucleoprotein complex biogenesis, rRNA metabolism, translational initiation, and negative regulation of metabolic processes. BZW2 depletion reduced proliferation, clonality, and invasion and increased apoptosis in MHCC97-H cells. Furthermore, BZW2 overexpression or knockdown enhanced or impaired c-Myc expression, respectively. Overall, these findings identified BZW2 as a biomarker of HCC and provided novel insight that the effect of BZW2 on the translatome is a potential mechanism that promotes HCC progression via the c-Myc pathway.

Lactate is an end product of glycolysis. As a critical energy source for mitochondrial respiration, lactate also acts as a precursor of gluconeogenesis and a signaling molecule. We briefly summarize emerging concepts regarding lactate metabolism, such as the lactate shuttle, lactate homeostasis, and lactate-microenvironment interaction. Accumulating evidence indicates that lactate-mediated reprogramming of immune cells and enhancement of cellular plasticity contribute to establishing disease-specific immunity status. However, the mechanisms by which changes in lactate states influence the establishment of diverse functional adaptive states are largely uncharacterized. Posttranslational histone modifications create a code that functions as a key sensor of metabolism and are responsible for transducing metabolic changes into stable gene expression patterns. In this review, we describe the recent advances in a novel lactate-induced histone modification, histone lysine lactylation. These observations support the idea that epigenetic reprogramming-linked lactate input is related to disease state outputs, such as cancer progression and drug resistance.

Background and Aims Great efforts have been made towards increasing our understanding of the pathogenesis involved in hepatocellular carcinoma (HCC), but the rapid growth inherent to such tumor development remains to be explored. Methods We identified distinct gene coexpression modes upon liver tumor growth using weighted gene coexpression network analysis. Modeling of tumor growth as signaling activity was employed to understand the main cascades responsible for the growth. Hub genes in the modules were determined, examined in vitro, and further assembled into the growth signature. Results We revealed modules related to the different growth states in HCC, especially the fastest growth module, which is preserved among different HCC cohorts. Moreover, signaling flux in the cell cycle pathway was found to act as a driving force for rapid growth. Twenty hub genes in the module were identified and assembled into the growth signature, and two genes (NCAPH, and RAD54L) were tested for their growth potential in vitro. Genetic alteration of the growth signature affected the global gene expression. The activity of the signature was associated with tumor metabolism and immunity in HCC. Finally, the prognosis effect of the growth signature was reproduced in nine cancers. Conclusions These results collectively demonstrate the molecule organization of rapid tumor growth in HCC, which is a highly synergistic process, with implications for the future management of patients.

Background: Concanavalin A (ConA)-induced liver damage of mice is a well-established murine model mimicking the human autoimmune hepatitis (AIH). However, the pathogenic genes of the liver injury remain to be revealed. Methods: Using time-series liver transcriptome, top dynamic genes were inferred from a set of segmented regression models, and cross-checked by weighted correlation network analysis (WGCNA). AIH murine models created by ConA were used to verify the in vivo effect of these genes. Results: We identified 115 top dynamic genes, of which most were overlapped with the hub genes determined by WGCNA. The expression of several top dynamic genes including Cd63, Saa3, Slc10a1, Nrxn1, Ugt2a3, were verified in vivo. Further, Cluster determinant 63 (Cd63) knockdown in mice treated with ConA showed significantly less liver pathology and inflammation as well as higher survival rates than the corresponding controls. Conclusion: We have identified the top dynamic genes related to the process of acute liver injury, and highlighted a targeted strategy for Cd63 might have utility for the protection of hepatocellular damage.

Background: Flavin mono-oxygenase enzyme (FMO) reportedly possesses the function of detoxification and/or bioactivation of xenobiotics in vivo, nevertheless its role in hepatocellular carcinoma (HCC) remains unclear. Methods: We performed a systematic analysis of high expression of FMO4 (FMO4high) and low expression of FMO4 (FMO4low) in HCC using multidimensional data from The Cancer Genome Atlas (TCGA) and GEO datasets. Results: In two independent cohorts of HCC patients, compared to FMO4high, FMO4low group was significantly associated with adverse biomarkers and outcomes. Multivariable analyses adjusting for known factors confirmed FMO4low as a high risk factor. Multiple omics analysis revealed aberrant alterations of genomics and epigenetics were significantly associated with FMO4 expression, including biochemical metabolism and signaling pathways in HCC were greatly reconfigured with FOM4 dysregulation. Next, FMO4low cases were distinguished by the loss of hepatocytes. Macrophages, and CD8+ T cells, etc., were mutually associated and enriched in FMO4low cases. Further, FOM4 alteration induced abnormal immune cell infiltration and disturbed global immune profile. In particular, FMO4 expression is highly correlated with the expression of immune checkpoint genes, and affects the prognosis when combined with these markers. Interpretation: Low expression of FMO4 in HCC patients is related to adverse biomarkers and outcomes .Funding Statement: This research was funded by the National Natural Science Foundation of China (81772520), Zhejiang Provincial Natural Science Foundation (LGF19H030004), and Zhejiang medical and health technology project (2018PY039). Declaration of Interests: The authors declare that they have no competing interests.

Nonalcoholic fatty liver disease (NAFLD)-related hepatocellular carcinoma (HCC) shows growing tendency across the world, thus requiring the convenient mice models mimic the pathology and pathogenesis of human disease to accelerate the findings of this disease. Herein, we summarized the mice model of NAFLD-HCC recently developed. *Correspondence to: Jin Yang, Translational Medicine Center, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, 310015, China, E-mail: hz_zhiy@163.com