Objective Lung cancer (LC) is one of the top ten malignant tumors and the first leading cause of cancer-related death among both men and women worldwide. It is imperative to identify immune-related biomarkers for early LC diagnosis and treatment. Methods Three Gene Expression Omnibus (GEO) datasets were selected to acquire the differentially expressed genes(DEGs) between LC and normal lung samples through GEO2R tools of NCBI. To identify hub genes, the DEGs were performed functional enrichment analysis, the protein–protein interaction (PPI) network construction, and Lasso regression. Then, a nomogram was constructed to predict the prognosis of patients with carcinoma based on hub genes. We further evaluated the influence of COL1A1 on clinical prognosis using GSE3141, GSE31210, and TCGA database. Also, the correlations between COL1A1 and cancer immune infiltrates and the B7-CD28 family was investigated via TIMER and GEPIA. Further analysis of immunohistochemistry shown that the COL1A1 expression level is positively correlated with CD276 expression level. Results By difference analysis, there were 340 DEGs between LC and normal lung samples. Then, we picked out seven hub genes, which were identified as components of the risk signature to divide LC into low and high-risk groups. Among them, the expression of COL1A1 is highly correlated with overall survival(OS) and progression-free survival (PFS) (p < 0.05). Importantly, there is a moderate to strong positive relationships between COL1A1 expression level and infiltration level of CD4+ T cells, Macrophage, Neutrophil, and Dendritic cell, as well as CD276 expression level. Conclusion These findings suggest that COL1A1 is correlated with prognosis and immune infiltrating levels, including CD4+ T cells, Macrophage, Neutrophil, and Dendritic cell, as well as CD276 expression level, indicating COL1A1 can be a potential immunity-related biomarker and therapeutic target in LC.

BackgroundThyroid cancer (THCA) is a malignancy affecting the endocrine system, which currently has no effective treatment due to a limited number of suitable drugs and prognostic markers.MethodsThree Gene Expression Omnibus (GEO) datasets were selected to identify differentially expressed genes (DEGs) between THCA and normal thyroid samples using GEO2R tools of National Center for Biotechnology Information. We identified hub gene FN1 using functional enrichment and protein-protein interaction network analyses. Subsequently, we evaluated the importance of gene expression on clinical prognosis using The Cancer Genome Atlas (TCGA) database and GEO datasets. MEXPRESS was used to investigate the correlation between gene expression and DNA methylation; the correlations between FN1 and cancer immune infiltrates were investigated using CIBERSORT. In addition, we assessed the effect of silencing FN1 expression, using an in vitro cellular model of THCA. Immunohistochemical(IHC) was used to elevate the correlation between CD276 and FN1.ResultsFN1 expression was highly correlated with progression-free survival and moderately to strongly correlated with the infiltration levels of M2 macrophages and resting memory CD4+ T cells, as well as with CD276 expression. We suggest promoter hypermethylation as the mechanism underlying the observed changes in FN1 expression, as 20 CpG sites in 507 THCA cases in TCGA database showed a negative correlation with FN1 expression. In addition, silencing FN1 expression suppressed clonogenicity, motility, invasiveness, and the expression of CD276 in vitro. The correlation between FN1 and CD276 was further confirmed by immunohistochemical.ConclusionOur findings show that FN1 expression levels correlate with prognosis and immune infiltration levels in THCA, suggesting that FN1 expression be used as an immunity-related biomarker and therapeutic target in THCA.

N6-methyladenosine (m6A) methylation is the most universal internal modification in eukaryotic mRNA. With elaborate functions executed by m6A writers, erasers, and readers, m6A modulation is involved in myriad physiological and pathological processes. Extensive studies have demonstrated m6A modulation in diverse tumours, with effects on tumorigenesis, metastasis, and resistance. Recent evidence has revealed an emerging role of m6A modulation in tumour immunoregulation, and divergent m6A methylation patterns have been revealed in the tumour microenvironment. To depict the regulatory role of m6A methylation in the tumour immune microenvironment (TIME) and its effect on immune evasion, this review focuses on the TIME, which is characterized by hypoxia, metabolic reprogramming, acidity, and immunosuppression, and outlines the m6A-regulated TIME and immune evasion under divergent stimuli. Furthermore, m6A modulation patterns in anti-tumour immune cells are summarized.

PurposeRheumatoid arthritis (RA) is a chronic autoimmune disease (AD) characterized by persistent synovial inflammation, bone erosion and progressive joint destruction. This research aimed to elucidate the potential roles and molecular mechanisms of N6-methyladenosine (m6A) methylation regulators in RA.MethodsAn array of tissues from 233 RA and 126 control samples was profiled and integrated for mRNA expression analysis. Following quality control and normalization, the cohort was split into training and validation sets. Five distinct machine learning feature selection methods were applied to the training set and validated in validation sets.ResultsAmong the six models, the LASSO_λ-1se model not only performed better in the validation sets but also exhibited more stringent performance. Two m6A methylation regulators were identified as significant biomarkers by consensus feature selection from all four methods. IGF2BP3 and YTHDC2, which are differentially expressed in patients with RA and controls, were used to predict RA diagnosis with high accuracy. In addition, IGF2BP3 showed higher importance, which can regulate the G2/M transition to promote RA-FLS proliferation and affect M1 macrophage polarization.ConclusionThis consensus of multiple machine learning approaches identified two m6A methylation regulators that could distinguish patients with RA from controls. These m6A methylation regulators and their target genes may provide insight into RA pathogenesis and reveal novel disease regulators and putative drug targets.

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The deubiquitinating enzyme USP1 (ubiquitin-specific protease 1) plays a role in the progression of various tumors, emerging as a potential therapeutic target. This study aimed to determine the role of USP1 as a therapeutic target in hepatocellular carcinoma (HCC). We detected USP1 expression in the tumor and adjacent tissues of patients with HCC using immunohistochemical staining. We evaluated the effect of the USP1 inhibitor ML-323 on HCC cell proliferation and cell cycle using a CCK-8 cell-counting kit and plate cloning assays, and propidium iodide, respectively. Apoptosis was detected by annexin V-FITC/Propidium Iodide (PI) staining and caspase 3 (casp3) activity. Transmission electron microscopy and LC3B immunofluorescence were used to detect autophagy. Western blotting was used to detect the accumulation of ubiquitinated proteins, the expression of endoplasmic reticulum (ER) stress-related proteins, and the AMPK-ULK1/ATG13 signaling pathway. We demonstrated that ML-323 inhibits the growth of HCC cells and induces G1 phase cell cycle arrest by regulating cyclin expression. ML-323 treatment resulted in the accumulation of ubiquitinated proteins, induced ER stress, and triggered Noxa-dependent apoptosis, which was regulated by the Activating Transcription Factor 4(ATF4). Moreover, active ER stress induces protective autophagy by increasing AMPK phosphorylation; therefore, we inhibited ER stress using 4-Phenylbutyric acid (4-PBA), which resulted in ER stress reduction, apoptosis, and autophagy in ML-323-treated HCC cells. In addition, blocking autophagy using the AMPK inhibitor compound C (CC), chloroquine (CQ), or bafilomycin A1 (BafA1) enhanced the cytotoxic effect of ML-323. Our findings revealed that targeting USP1 may be a potential strategy for the treatment of HCC.

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Background: Fatty acid transporters (FATPs) family play an important role in the uptake and metabolism regulation of long-chain fatty acids, which influence the occurrence and developing of multiple tumors. Fatty acid transporter 5(FATP5), a member of FATPs family, participates in fatty acid transport and lipid metabolism and is related to tumor development, whose mechanism in colorectal cancer (CRC) remains unclear.Methods: In this study, we comprehensively utilized a range of relevant bioinformatic tools along with multiple databases to analyze the expression of FATPs family and investigate the biological function and prognostic value of FATP5 in CRC. Besides, cell proliferation and cell cycle distribution analysis, western blotting and immunohistochemistry (IHC) further validated the conclusion of bioinformatics analysis.Results: FATP5 is the only member of FATPs family which was overexpressed in CRC. In the survival analysis based on the GSE39582 databases, the low expression of FATP5 predicts poor prognosis in CRC. Similar results were also observed in GSE17536, GSE28814 and TCGA colon cohorts. The potential function of DNA methylation regulated the abnormal expression of FATP5 in CRC. In addition, enrichment analysis indicated that FATP5 also participates in the regulation of cell cycle. Furthermore, Gene Set Enrichment Analysis (GSEA) showed a strong negative correlation between FATP5 and cell growth, implying that it may participate in regulating cancer cell proliferation by the regulation of cell cycle G2/M transition. At last, we identified that FATP5 was overexpressed in colorectal carcinoma tissues through immunohistochemistry staining, and played an important role in cell cycle by cell proliferation and cell cycle distribution analysis.Conclusion: This study suggested that FATP5 was overexpression in colorectal carcinoma and predicted favorable prognosis, indicating it as a novel appealing prognostic marker for CRC.