• AGRN
• AURKA
• carvacrol
• hepatocellular carcinoma
• molecular docking
• network pharmacology

• cancer-associated fibroblasts
• liver cancer
• metastasis
• prognosis
• single-cell

• Cellular senescence
• Gene signature
• Hepatocellular carcinoma
• Pharmacological interventions
• Prognosis
• Subtypes
• Tumor microenvironment

• Immune cell infiltration
• Prognostic signature
• Soft tissue sarcoma
• Tumor microenvironment
• m5C methylation

• Genetic mutation
• Hepatocellular carcinoma
• Heterogeneity
• Hypoxia
• Immunotherapy
• Prognosis
• RNF145

• Aging
• Bioinformatics
• GBM
• Prognosis
• TCGA

• antitumor immunity
• colorectal cancer
• drug sensitivity
• oxidative stress
• prognosis

• LRPPRC
• PD-L1
• anti-tumor immunity
• hepatocellular carcinoma
• immune evasion
• m6A modification
• tumor progression

• CXCL12
• biomarker
• bladder cancer
• tumor immune microenvironment (TIME)
• tumor-infiltrating immune cells (TICs)

• National Natural Science Foundation of China

Evidence proves that integrins affect almost every step of hepatocellular carcinoma (HCC) progression. The current study aimed at constructing an integrin-based signature for prognostic prediction of HCC.

TCGA-LIHC and ICGC-LIRI-JP cohorts were retrospectively analyzed. Integrin genes were analyzed via univariate Cox regression, followed by generation of a prognostic signature with LASSO approach. Independent factors were input into the nomogram. WGCNA was adopted to select this signature-specific genes. Gene Ontology (GO) enrichment together with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the function of the dysregulated genes. The abundance of tumor microenvironment components was estimated with diverse popular computational methods. The relative importance of genes from this signature was estimated through random-forest method.

Eight integrin genes (ADAM15, CDC42, DAB2, ITGB1BP1, ITGB5, KIF14, LIMS2, and SELP) were adopted to define an integrin-based signature. Each patient was assigned the riskScore. High-riskScore subpopulation exhibited worse overall survival, with satisfying prediction efficacy. Also, the integrin-based signature was independent of routine clinicopathological parameters. The nomogram (comprising integrin-based signature, and stage) accurately inferred prognostic outcome, with the excellent net benefit. Genes with the strongest positive interaction to low-riskScore were primarily linked to biosynthetic, metabolic, and catabolic processes and immune pathways; those with the strongest association with high-riskScore were principally associated with diverse tumorigenic signaling. The integrin-based signature was strongly linked with tumor microenvironment components. Among the genes from this signature, LIMS2 possessed the highest importance, and its expression was proven through immunohistochemical staining.

Altogether, our study defined a quantitative integrin-based signature that reliably assessed HCC prognosis and tumor microenvironment features, which possessed the potential as a tool for prognostic prediction.

• Hepatocellular carcinoma
• Long noncoding RNA
• N6-methylandenosine
• Prognosis
• Tumor microenvironment
• ceRNA network

• OLFML2B
• TME
• immune infiltration
• pan-cancer
• prognosis

This study was designed to observe the treatment effects of flavokawain B (FKB) on gastric cancer both in SGC-7901 cells and nude mice. When SGC-7901 cells were exposed to 10 μg/mL FKB, cellular proliferative and apoptotic capacities and cell cycle were detected utilizing CCK-8 and flow cytometry assays. The results showed that FKB treatment induced cell apoptosis and G2/M arrest and suppressed cell proliferation for SGC-7901 cells. Western blot results showed that FKB upregulated proapoptotic proteins as well as downregulated antiapoptotic and cell cycle-related proteins in SGC-7901 cells. SMAD4, TGF-β1, and TSPAN12 proteins were tested in FKB-induced SGC-7901 cells. Following exposure to FKB, SMAD4, TGF-β1, and TSPAN12 expression was augmented in SGC-7901 cells. si-SMAD4 transfection weakened cell apoptosis and accelerated cell proliferation. Furthermore, FKB reversed the change in apoptotic and cell cycle-related proteins induced by si-SMAD4. A nude mouse tumorigenesis model was constructed, which was treated by FKB. In the nude mouse tumorigenesis model, FKB activated the TSPAN12 expression and TGF-β1/SMAD4 pathway. Also, FKB treatment prolonged the survival time of nude mice and lowered tumor weight. iNOS and CD86 expression was significantly enhanced, and Arg-1 and CD206 expression was significantly decreased in THP-1 cells cultured in conditioned media from FKB-treated SGC-7901 cells. Additionally, FKB-treated SGC-7901 cells weakened macrophage migration. Collectively, this evidence suggested that FKB accelerated apoptosis and suppressed the proliferation of gastric cancer cells and attenuated M2 macrophage polarization, thereby exerting an anticancer effect on gastric cancer.

Glioma is a common malignant tumor of the central nervous system with extremely poor prognosis. An efficient molecular marker for diagnosis and treatment is urgently needed. Fatty acid binding protein 7(FABP7), which regulates intracellular lipid metabolism, is highly expressed in nervous system tumors, but its prognostic value remains undetermined. The present study investigated the relationship between FABP7 expression and prognosis in glioma patients by bioinformatics analysis, as well as immunohistochemically evaluating the effect of FABP7 expression on the efficacy of antiangiogenic drugs.

Gene expression and clinical data on patients with glioma were collected from the China Glioma Genome Atlas (CGGA) database, The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases. Levels of FABP7 expression and their association with the clinicopathologic characteristics of glioma patients were analyzed in the CGGA database. The relationships between FABP7 expression and clinical findings, such as survival and prognostic, were determined and used for nomogram construction. Mechanisms of action of FABP7 were assessed using GSEA software. FABP7 expression in the tissues of glioma patients treated with apatinib was evaluated immunohistochemically.

FABP7 was highly expressed in glioma samples, with higher FABP7 expression associated with poorer patient prognosis and more advanced clinicopathological features. Bioinformatics analysis, including survival, receiver operating characteristic curve, and univariate and multivariate Cox analyses, showed that FABP7 was independently prognostic of outcomes in glioma patients. GSEA analysis showed that FABP7 was associated with angiogenesis, with FABP7 having correlation coefficients > 0.4 with seven factors in the angiogenic pathway, POSTN, TIMP1, PDGFA, FGFR1, S100A4, COL5A2, and STC1, and the expression of these factors related to patient prognosis. Immunohistochemistry showed that FABP7 expression was higher in glioma patients with poor survival after apatinib treatment.

High FABP7 expression is associated with poor prognosis in glioma patients. FABP7, which is important for glioma angiogenesis, may serve as an independent prognostic predictor in glioma patients.

The tumor-adipose microenvironment (TAME) is a universal microecosystem, that is characterized by the dysfunction of lipid metabolism, such as excessive free fatty acids (FFAs). Macrophages are the most abundant immune cell type within TAME, although their diversity in the TAME is not clear. We first reveal that infiltration of M2-like macrophages in the TAME is associated with poor survival in breast cancer. To explore lipid-associated alterations in the TAME, we also detected the levels of FFAs transporters including fatty acid binding proteins (FABPs) and fatty acid transport protein 1 (FATP1). The results indicated that expression of fatty acid transporters in the TAME is tightly linked to the function of macrophages and predicts survival in breast cancer. To explore the impact of FFAs transporters on the function of macrophages, we performed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics. Consequently, we identified a special subpopulation of macrophages defined as lipid-associated macrophages (LAMs), highly expressed macrophage markers (CD163, SPP1 and C1QC), genes involved in lipid metabolism (FABP3, FABP4, FABP5, LPL and LIPA) and some lipid receptors (LGALS3 and TREM2). Functionally, LAMs were characterized by a canonical functional signature of M2-like macrophages, lipid accumulation and enhancing phagocytosis, and they were mostly distributed in tumor-adipose junctional regions. Finally, the allograft cancer mouse models confirmed that LAMs depletion in the TAME synergizes the antitumorigenic effects of anti-PD1 therapy. In summary, we defined a novel subtype of macrophages in the TAME, that has unique features and clinical outcomes.

• breast cancer
• lipid-associated macrophage
• tumor-adipose microenvironment

Helicobacter pylori (H. pylori) infection is the strongest causative factor of gastric cancer. Growing evidence suggests that the complex crosstalk of H. pylori and the tumor microenvironment (TME) exerts a profound influence on gastric cancer progression. Hence, there is emerging interest to in-depth comprehension of the mechanisms of interplay between H. pylori and the TME. This review discusses the regulatory mechanisms underlying the crosstalk between H. pylori infection and immune and stromal cells, including tumor-associated macrophages (TAMs), neutrophils, dendritic cells, myeloid-derived suppressor cells (MDSCs), natural killer (NK) cells, B and T cells, cancer associated fibroblasts (CAFs), and mesenchymal stem cells (MSCs), within the TME. Such knowledge will deepen the understanding about the roles of H. pylori in the immune evasion mechanism in gastric cancer and contribute to the development of more effective treatment regimens against H. pylori-induced gastric cancer.

• RNA-seq
• TMAO
• database reanalysis
• hepatocellular carcinoma
• inflammatory
• microbial metabolite

• National Key Research and Development Program of China
• Natural Science Foundation of Shanghai

• Adenocarcinoma of Lung/metabolism
• Adenocarcinoma of Lung/pathology
• Cell Proliferation/genetics
• Genes, Homeobox
• Homeodomain Proteins/metabolism
• Humans
• Lung Neoplasms/metabolism
• Lung Neoplasms/pathology
• Oxidative Stress
• Transcription Factors/metabolism

Objective: Experimental and clinical evidence suggests that atherosclerosis is a chronic inflammatory disease. Our study was conducted for uncovering the roles of immune-associated genes during atherosclerotic plaque progression.

Methods: Gene expression profiling of GSE28829, GSE43292, GSE41571, and GSE120521 datasets was retrieved from the GEO database. Three machine learning algorithms, least absolute shrinkage, and selection operator (LASSO), random forest, and support vector machine–recursive feature elimination (SVM-RFE) were utilized for screening characteristic genes among atherosclerotic plaque progression- and immune-associated genes. ROC curves were generated for estimating the diagnostic efficacy. Immune cell infiltrations were estimated via ssGSEA, and immune checkpoints were quantified. CMap analysis was implemented to screen potential small-molecule compounds. Atherosclerotic plaque specimens were classified using a consensus clustering approach.

Results: Seven characteristic genes (TNFSF13B, CCL5, CCL19, ITGAL, CD14, GZMB, and BTK) were identified, which enabled the prediction of progression of atherosclerotic plaques. Higher immune cell infiltrations and immune checkpoint expressions were found in advanced-stage than in early-stage atherosclerotic plaques and were positively linked to characteristic genes. Patients could clinically benefit from the characteristic gene-based nomogram. Several small molecular compounds were predicted based on the characteristic genes. Two subtypes, namely, C1 immune subtype and C2 non-immune subtype, were classified across atherosclerotic plaques. The characteristic genes presented higher expression in C1 than in C2 subtypes.

Conclusion: Our findings provide several promising atherosclerotic plaque progression- and immune-associated genes as well as immune subtypes, which might enable to assist the design of more accurately tailored cardiovascular immunotherapy.

• atherosclerosis
• atherosclerotic plaque
• characteristic genes
• immune subtype
• immune-associated genes

Salvianolic acid B (Sal B) has been demonstrated to be a potential chemoprevention agent for several cancers. Herein, we investigated the pharmacological function of Sal B on non-small-cell lung cancer (NSCLC) metastasis.

Two NSCLC cell lines (NCI-H2030 and NCI-H1650) were disposed of by 200 μM Sal B or 10 μM PKM2 agonist TEPP-46. Wound healing and transwell experiments were implemented for analyzing migratory and invasive capacities. Epithelial-to-mesenchymal transition (EMT) markers β-catenin and E-cadherin were measured via western blotting. Cellular bioenergetics were evaluated with glucose uptake, lactate production, enolase activity, cellular ATP levels, as well as seahorse-based oxygen consumption rate (OCR), extracellular acidification rate (ECAR) analysis. Metabolic reprogramming markers PKM2, LDHA, and GLUT1 were detected via western blotting and immunofluorescence.

The results showed that Sal B disposal weakened the migration and invasion of NCI-H2030 and NCI-H1650 cells and inactivated the EMT process according to downregulation of β-catenin and upregulation of E-cadherin. Sal B-treated NSCLC cells displayed decreased glucose uptake, lactate production, enolase activity, cellular ATP levels, OCR, and ECAR, indicating a reduction in metabolic reprogramming. Additionally, Sal B downregulated the expression of PKM2, LDHA, and GLUT1. TEPP-46 may reverse the inhibitory effect of Sal B on metastasis as well as metabolic reprogramming.

Our findings provide evidence that Sal B enables to weaken NSCLC metastasis through PKM2-independent metabolic reprogramming, which sheds light on the promising therapeutic usage of Sal B in treating NSCLC.

• AQP9
• Immune microenvironment
• Immune-related genes
• Laryngeal cancer
• Prognosis
• Progression
• ZAP70

• Hepatocellular carcinoma
• Neural network
• Personalized medicine
• Prognostic scoring system
• Random forest

Gastric cancer (GC) is one of the most common cancers worldwide with a poor prognosis. The tumor microenvironment (TME) serves a pivotal role in affecting the prognosis and efficacy of immunotherapy. Given the poor prognosis of GC patients and the limitation of immunotherapy, we urged to identify new prognostic and immunotherapeutic biomarkers.

The transcriptome data were downloaded from the TCGA, GEO, and GEPIA databases, and performed differential analysis of AFF3 in tumor samples and normal samples. The UALCAN, Kaplan–Meier plotter and GEPIA databases were employed to assess the correlation of AFF3 with clinicopathological characteristics and prognosis. The potential mechanism of AFF3 was explored by the GO and KEGG enrichment. The potential role of AFF3 on tumor‐infiltrating immune cells (TIICs) was explored by TIMER2.0 and TISIDB. TIMER2.0 and SangerBox3.0 databases were, respectively, used to determine the correlation of AFF3 with immune checkpoint (ICs), tumor mutational burden (TMB), and microsatellite instability (MSI) in GC.

We found significant downregulation of AFF3 in GC tissues as compared with normal tissues. However, GC patients having a higher expression of AFF3 were found to have worse clinicopathological characteristics and prognosis. Moreover, the GO enrichment analysis illustrated that AFF3 might regulate the immune cells in the TME. In addition, the AFF3 was positively correlated with TIICs, ICs, TMB, and MSI.

Here, we conclude that AFF3 may be a promising potential marker for the diagnosis and prognosis of GC patients, and may influence response to ICIs by affecting TIICs and ICs expression in the TME.

• AFF3
• bioinformatic analysis
• gastric cancer
• immunotherapy
• prognosis

Low-grade glioma (LGG) mainly threatens the elderly population, with undesirable prognoses. This study uncovered the immune cell infiltration (ICI) landscape in LGG.

RNA-seq profiles of LGG were retrieved from TCGA and CGGA databases. CIBERSORTx and ESTIMATE algorithms were employed to characterize the ICI landscape in LGG tissues. Through unsupervised clustering analysis, ICI subtypes were clustered. ICI scores were computed via principal component analysis (PCA). The differences in survival, tumor-infiltrating immune cells, stromal scores, immune scores, immune checkpoint genes, immune activity genes, and tumor mutation burden (TMB) were assessed between high and low ICI score groups.

Three ICI subtypes were constructed in LGG, with distinct survival outcomes, PD-L1 expression, and infiltration levels of immune cells. Furthermore, ICI scores were developed. Both in TCGA and CGGA datasets, low ICI scores were indicative of undesirable outcomes. High ICI scores were significantly correlated to increased infiltration levels of memory B cells, CD8 T cells, CD4 naïve T cells, T follicular helper cells, macrophages M0, and eosinophils, while low ICI scores were characterized by increased infiltration levels of naïve B cells, plasma cells, CD4 memory resting T cells, Tregs, resting NK cells, macrophages M2, and activated dendritic cells. High ICI scores exhibited correlations with lower immune activity genes and immune checkpoint genes. Furthermore, TMB was distinctly reduced in the high ICI score group.

The ICI scores may serve as a promising prognostic index and predictive indicator for immunotherapies, extending our understanding of immune microenvironment in LGG.

Long noncoding RNAs (lncRNAs) participate in cancer immunity. We characterized the clinical significance of an immune-related lncRNA model and evaluated its association with immune infiltrations and chemosensitivity in bladder cancer. Transcriptome data of bladder cancer specimens were employed from The Cancer Genome Atlas. Dysregulated immune-related lncRNAs were screened via Pearson correlation and differential expression analyses, followed by recognition of lncRNA pairs. Then, a LASSO regression model was constructed, and receiver operator characteristic curves of one-, three- and five-year survival were established. Akaike information criterion (AIC) value of one-year survival was determined as the cutoff of high- and low-risk subgroups. The differences in survival, clinical features, immune cell infiltrations and chemosensitivity were compared between subgroups. Totally, 90 immune-related lncRNA pairs were identified, 15 of which were screened for constructing the prognostic model. The area under the curves of one-, three- and five-year survival were 0.806, 0.825 and 0.828, confirming the favorable predictive performance of this model. According to the AIC value, we clustered patients into high- and low-risk subgroups. High-risk score indicated unfavorable outcomes. The risk model was related to survival status, age, stage and TNM. Compared with conventional clinicopathological characteristics, the risk model displayed higher predictive efficacy and served as an independent predictor. Also, it could well characterize immune cell infiltration landscape and predict immune checkpoint expression and sensitivity to cisplatin and methotrexate. Collectively, the model conducted by paring immune-related lncRNAs regardless of expressions exhibits a favorable efficacy in predicting prognosis, immune landscape and chemotherapeutic response in bladder cancer.

• DEHP
• Environmental endocrine disruptor
• Metabolism
• Prepubertal testis
• RNA-seq
• Toxic

• Animals
• Diethylhexyl Phthalate/toxicity
• Gene Expression Profiling
• Male
• Mice
• Rats, Sprague-Dawley
• Testis
• Transcriptome
• Rats

• 82071632 national natural science foundation of china

• hepatocellular carcinoma
• immune infiltration level
• immune related genes
• prognostic biomarker
• tumor microenvironment

• PLA2G2D
• cervical squamous cell carcinoma
• immune infiltration
• metabolism
• multiplex immunohistochemistry
• tumor immune microenvironment

Osteosarcoma (OS) is a type of primary malignant tumor, and increasing evidence shows the clinical benefits of immunotherapy in treating OS. However, the lack of comprehensive studies on the complex OS immune microenvironment hinders the application of immunotherapy. Thus, this study aimed to systematically explore the immune characteristics of OS and identify novel biomarkers for OS treatment.

We systematically studied the immune score and proportions of infiltrating immune cells in OS in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases using the ESTIMATE and CIBERSORT algorithms. Differential expression and functional analyses were used to identify dysregulated genes and explore their functions. Survival and Cox regression analyses were applied to establish an immune-related prognostic signature. Additionally, qPCR and immunohistochemistry were performed to validate the results.

A total of 103 differentially expressed immune genes (DEIGs) were found in the TARGET-OS and GSE39058 databases, and these DEIGs were mainly enriched in leukocyte proliferation, leukocyte differentiation, osteoclast differentiation, natural killer (NK) cell-mediated cytotoxicity, and the adaptive immune system. A predictive signature was constructed based on the survival analysis, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.65. Moreover, we found that mitogen-activated protein kinase kinase kinase 15 (MAP3K15) can predict the prognosis of patients with OS and is closely related to CD4⁺ T cells and macrophages. The OS patients with high MAP3K15 expression had a significantly poorer prognosis.

Our study found that MAP3K15, whose expression level is closely related to immune activity in tumors, is a critical immune-related biomarker, and our findings may provide a basis for OS immunotherapy.

• Mitogen-activated protein kinase kinase kinase 15 (MAP3K15)
• bioinformatics
• immune infiltrates
• osteosarcoma (OS)
• prognosis

• Asian
• CIBERSORT
• ESTIMATE
• hepatocellular carcinoma
• non-Asian
• tumor microenvironment

FAM83D has been demonstrated to contribute to tumorigenesis. However, its immune effects in hepatocellular carcinoma (HCC) have not been reported. This study aimed to identify the immune role of FAM83D in HCC. FAM83D was over-expressed in HCC and contributed to poor prognosis according to the results of data analysis based on The Cancer Genome Atlas (TCGA). Afterward, the levels of immune cells infiltration were found to be correlated with the expression level of FAM83D in HCC. Through TISIDB and cBioPortal network tools, a total of 82 FAM83D-associated genes were screened out, including 12 immunoinhibitors, 20 immunostimulators and 50 tightly co-expressed genes. TCGA cohort was divided into train set and test set on the basis of the proportion of 7:3. According to FAM83D-associated immunomodulators, a four gene predicted model was established using train set via the Cox regression analysis. Survival analysis demonstrated that the overall survival (OS) of high-risk HCC patients was poor compared with the patients in low-risk group. The reliability and predicted power of the risk-score model were identified by a receiver operating characteristic (ROC) curve. A risk-score based nomogram as well as a calibration curve, which were created could be used to anticipate patient’s 1-year, 3-year and 5-year survival probabilities. The test set was used to validate these results. Our findings showed that the FAM83D gene was related with HCC immunity. The immune marker chosen could be a promising biomarker for HCC prognosis.

• FAM83D
• HCC
• immune cells
• nomogram
• prognosis

• Immune microenvironment
• Lung adenocarcinoma
• Prognosis
• ceRNA (competitive endogenous RNAs)

• READ
• gene signature
• m6A
• prognostic prediction
• risk score