TNF Patterns and Tumor Microenvironment Characterization in Head and Neck Squamous Cell Carcinoma

Identification of fatty acid anabolism patterns to predict prognosis and immunotherapy response in gastric cancer

Gastric cancer (GC), one of the most common and heterogeneous malignancies, is the second leading cause of cancer death worldwide and is closely related to dietary habits. Fatty acid is one of the main nutrients of human beings, which is closely related to diabetes, hypertension and other diseases. However, the correlation between fatty acid metabolism and the development and progression of GC remains largely unknown. Here, we profiled the genetic alterations of fatty acid anabolism-related genes (FARGs) in gastric cancer samples from the TCGA cohort and GEO database to evaluate the possible relationships and their internal regulatory mechanism. Through consistent clustering and functional enrichment analysis, three distinct fatty acid anabolism clusters and three gene subtypes were identified to participate in different biological pathways, and correlated with the characteristics of immune cell infiltration and clinical prognosis. Importantly, a distinctive FA-score was constructed through the principal component analysis to quantify the characteristics of fatty acid anabolism in each GC patient. Further analysis showed patients grouped in the high FA-score group were characterized with greater tumor mutational burden (TMB) and higher microsatellite stability (MSI-H), which may be more aeschynomenous to immunotherapy and had a favorable prognosis. Altogether, our bioinformatics analysis based on FARGs uncovered the potential roles of fatty acid metabolism in GC, and may provide newly prognostic information and novel approaches for promoting individualized immunotherapy in patients with GC.

drexml: A command line tool and Python package for drug repurposing

We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.

Identification and analysis of a cell communication prognostic signature for oral squamous cell carcinoma at bulk and single-cell levels

Head and neck squamous cancer (HNSC) is a heterogenous malignant tumour disease with poor prognosis and has become the current major public health concern worldwide. Oral squamous cell carcinoma (OSCC) is the majority of HNSC. It is still in lack of comprehensive tumour immune microenvironment analysis and prognostic model development for OSCC's clinic practice. Single-cell sequencing data analysis was conducted to identify immune cell subtypes and illustrate cell-cell interaction status in OSCC via R package 'Seurat', 'Harmony', 'elldex' and 'CellChat'. Base on the bulk sequencing data, WGCNA analysis was employed to identify the CD8+ T cell related gene module. XGBoost was used to construct the gene prognostic model for OSCC. Validation sets and immunotherapy data sets were analysed to further evaluate the model's effectiveness and immunotherapy responsiveness predicting potential. siRNA was used to down regulate FCRL4 expression. Real-time PCR and Western blot were used to validate target gene expression. The effects of FCRL4 on OSCC cells were detected by wound healing, Trans well and clone formation assays. Communication between epithelial cells and tissue stem cells may be the potential key regulators for OSCC progression. By integrating single-cell sequencing data analysis and bulk sequencing data analysis, we constructed a novel immune-related gene prognostic model. The model can effectively predict the prognosis and immunotherapy responsiveness of OSCC patients. In addition, the effects of FCRL4 on OSCC cells were validated. We comprehensively interpreted the immune microenvironment pattern of OSCC based on the single-cell sequencing data and bulk sequencing data analysis. A robust immune feature-based prognostic model was developed for the precise treatment and prognosis evaluation of OSCC.

Small extracellular vesicles in plasma carry luminal cytokines that remain undetectable by antibody-based assays in cancer patients and healthy donors

Background

Small (30-150nm) extracellular vesicles (sEV), also known as exosomes, play a key role in cell-to-cell signaling. They are produced by all cells, circulate freely and are present in all body fluids. Evidence indicates that cytokines are present on the surface and/or in the lumen of sEV. The contribution of intravesicular cytokines to cytokine levels in plasma are unknown.

Methods

sEV were isolated by ultrafiltration/size exclusion chromatography from pre-cleared plasma obtained from patients with head and neck squamous cell carcinoma (HNSCC) and healthy donors (HDs). Multiplex immunoassays were used to measure cytokine levels in paired untreated and detergent-treated (0.5% Triton X-100) plasma and plasma-derived detergent-treated sEV. Non-parametric tests were used to assess differences in cytokine levels.

Results

The presence of cytokines in sEV isolated from patients' and HDs' plasma was confirmed by immunoblots and on-bead flow cytometry. sEV-associated cytokines were functional in various in vitro assays. Levels of cytokines in sEV varied among the HNSCC patients and were generally significantly higher than the levels observed in sEV from HDs. Compared to untreated plasma, levels for the majority (40/51) of the evaluated proteins were significantly higher in detergent-treated plasma (P<0.0001-0.03). In addition, levels of 24/51 proteins in sEV, including IL6, TNFRII, IL-17a, IFNa and IFNg, were significantly positively correlated with the difference between levels detected in detergent-treated plasma and untreated plasma.

Discussion

The data indicate that sEV-associated cytokines account for the differences in cytokine levels measured in detergent-treated versus untreated plasma. Ab-based assays using untreated plasma detect only soluble cytokines and miss cytokines carried in the lumen of sEV. Permeabilization of sEV with a mild detergent allows for Ab-based detection of sEV-associated and soluble cytokines in plasma. The failure to detect cytokines carried in the sEV lumen leads to inaccurate estimates of cytokine levels in body fluids.

Advances in the role of gut microbiota in the regulation of the tumor microenvironment (Review)

As a protector of human health, the gut microbiota plays an important role in the development of the immune system during childhood, and the regulation of dietary habits, metabolism and immune system during adulthood. Dysregulated gut flora is not pathogenic, but it can weaken the protective effect of the immune system and cause various diseases. The tumor microenvironment is a physiological environment formed during tumor growth, which provides nutrients and growth factors necessary for tumor growth. As an important factor affecting the tumor microenvironment, the intestinal microflora affects the development of tumors through the mechanisms of gut and microflora metabolites, gene toxins and signaling pathways. The present article aimed to review the components and mechanisms of action, clinical applications, and biological targets of gut microbiota in the regulation of the tumor microenvironment. The present review provides novel insights for the future use of intestinal flora, to regulate the tumor microenvironment, to intervene in the occurrence, development, treatment and prognosis of tumors.

Pyroptosis patterns influence the clinical outcome and immune microenvironment characterization in HPV-positive head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous tumor with diverse molecular pathological profiles. Recent studies have suggested the vital role of pyroptosis in tumor microenvironment. However, the expression patterns of pyroptosis in HPV-positive HNSCC are still unclear.

METHODS

Unsupervised clustering analysis was used to identify the pyroptosis patterns based on the RNA-sequencing data of 27 pyroptosis-related genes (PRGs) in HPV-positive HNSCC samples. Random forest classifier and artificial neural network were performed to screen the signature genes associated with pyroptosis, which were verified in two independent external cohorts and qRT-PCR experiment. Principal component analysis was used to develop a scoring system, namely Pyroscore.

RESULTS

The expression variations of 27 PRGs in HPV-positive HNSCC patients were analyzed from genomic and transcriptional domains. Two pyroptosis-related subtypes with distinct clinical outcomes, enrichment pathways and immune characteristics were identified. Next, six signature genes (GZMB, LAG3, NKG7, PRF1, GZMA and GZMH) associated with pyroptosis were selected for prognostic prediction. Further, a Pyroscore system was constructed to determine the level of pyroptosis in each patient. A low Pyroscore was featured by better survival time, increased immune cell infiltration, higher expression of immune checkpoint molecules and T cell-inflamed genes, as well as elevated mutational burden. The Pyroscore was also related to the sensitivity of chemotherapeutic agents.

CONCLUSIONS

The pyroptosis-related signature genes and Pyroscore system may be reliable predictors of prognosis and serve as mediators of immune microenvironment in patients with HPV-positive HNSCC.

Tumor-derived extracellular vesicles delivering TNF-α promotes colorectal cancer metastasis via the NF-kB/LAMB3/AKT axis by targeting SNAP23

Accumulating evidence have demonstrated that cytokines are enriched in tumor-derived extracellular vesicles (EVs) and widely involved in tumorigenesis of various types of carcinomas, including colorectal cancer (CRC). Nevertheless, the functions of cytokines in EVs secreted from colorectal cancer cells remain largely unknown. In the present study, we found that TNF-α was elevated in EVs from CRC patient serum samples and CRC cell lines, of which the expression was associated with aggressive features of colorectal cancer. EV TNF-α secretion is dependent on synaptosome-associated protein 23 (SNAP23). Functional experiments revealed that EV TNF-α promotes CRC cell metastasis via the NF-κB pathway by targeting SNAP23. Mechanistically, SNAP23 was transcriptionally upregulated by EV TNF-α/NF-κB axis to enhance the expression of laminin subunit beta-3 (LAMB3), thereby activating the PI3K/AKT signaling pathway and consequently facilitate CRC progression. Based on our findings, we could conclude that EV TNF-α plays an oncogenic role in CRC progression through SNAP23, which in turn promotes EV TNF-α secretion, suggesting that EV TNF-α/SNAP23 axis may serve as a diagnostic biomarker and potential therapeutic target for CRC.

Identification of fatty acid metabolism-related clusters and immune infiltration features in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a type of liver cancer which is characterized by inflammation-associated tumor. The unique characteristics of tumor immune microenvironment in HCC contribute to hepatocarcinogenesis. It was also clarified that aberrant fatty acid metabolism (FAM) might accelerate tumor growth and metastasis of HCC. In this study, we aimed to identify fatty acid metabolism-related clusters and establish a novel prognostic risk model in HCC. Gene expression and corresponding clinical data were searched from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) portal. From the TCGA database, by unsupervised clustering method, we determined three FAM clusters and two gene clusters with distinct clinicopathological and immune characteristics. Based on 79 prognostic genes identified from 190 differentially expressed genes (DEGs) among three FAM clusters, five prognostic DEGs (CCDC112, TRNP1, CFL1, CYB5D2, and SLC22A1) were determined to construct risk model by least absolute shrinkage and selection operator (LASSO) and multivariate cox regression analysis. Furthermore, the ICGC dataset was used to validate the model. In conclusion, the prognostic risk model constructed in this study exhibited excellent indicator performance of overall survival, clinical feature, and immune cell infiltration, which has the potential to be an effective biomarker for HCC immunotherapy.

Cuproptosis-related modification patterns depict the tumor microenvironment, precision immunotherapy, and prognosis of kidney renal clear cell carcinoma

BACKGROUND

Due to the different infiltration abundance of immune cells in tumor, the efficacy of immunotherapy varies widely among individuals. Recently, growing evidence suggested that cuproptosis has impact on cancer immunity profoundly. However, the comprehensive roles of cuproptosis-related genes in tumor microenvironment (TME) and in response to immunotherapy are still unclear.

METHODS

Based on 43 cuproptosis-related genes, we employed unsupervised clustering to identify cuproptosis-related patterns and single-sample gene set enrichment analysis algorithm to build a cuproptosis signature for individual patient's immune cell infiltration and efficacy of immune checkpoint blockade (ICB) evaluation. Then, the cuproptosis-related genes were narrowed down using univariate Cox regression model and least absolute shrinkage and selection operator algorithm. Finally, a cuproptosis risk score was built by random survival forest based on these narrowed-down genes.

RESULTS

Two distinct cuproptosis-related patterns were developed, with cuproptosis cluster 1 showing better prognosis and higher enrichment of immune-related pathways and infiltration of immune cells. For individual evaluation, the cuproptosis signature that we built could be used not only for predicting immune cell infiltration in TME but also for evaluating an individual's sensitivity to ICBs. Patients with higher cuproptosis signature scores exhibited more activated cancer immune processes, higher immune cell infiltration, and better curative efficacy of ICBs. Furthermore, a robust cuproptosis risk score indicated that patients with higher risk scores showed worse survival outcomes, which could be validated in internal and external validation cohorts. Ultimately, a nomogram which combined the risk score with the prognostic clinical factors was developed, and it showed excellent prediction accuracy for survival outcomes.

CONCLUSION

Distinct cuproptosis-related patterns have significant differences on prognosis and immune cell infiltration in kidney renal clear cell carcinoma (KIRC). Cuproptosis signature and risk score are able to provide guidance for precision therapy and accurate prognosis prediction for patients with KIRC.

The Assessment of Serum Cytokines in Oral Squamous Cell Carcinoma Patients: An Observational Prospective Controlled Study

Background: The oral squamous cell carcinoma (OSCC) tumor microenvironment (TME) is a complex interweb of cells and mediators balancing carcinogenesis, inflammation, and the immune response. However, cytokines are not only secreted within the TME but also released by a variety of other cells that do not comprise the TME; therefore, a thorough assessment of humoral changes in OSCC should include the measurement of serum cytokines. Methods: We assessed the role of various serum cytokines in the evolution of OSCC, before and after treatment, versus a control group. We measured the serum concentrations of MIP-1α, IL-1β, IL-4, IL-6, IL-8, IL-10, and TNF-α. Results: Significantly higher values (p < 0.01) were noted for IL-1β, IL-6, IL-8, IL-10, and TNF-α in the OSCC group before treatment (n = 13) compared with the control group (n = 14), and the increased concentrations persisted after treatment (n = 11). Furthermore, the variations in the values of MIP-1α, IL-1β, IL-10, and TNF-α are correlated both before and after treatment (p < 0.01). In the pretherapeutic group, IL-6 and IL-8 concentrations also correlate with IL-1β and IL-10 serum levels (p < 0.01), while in the posttherapeutic group, IL-4 varies with MIP-1α and TNF-α (p < 0.01). Conclusion: In OSCC patients, serum cytokine levels are significantly higher compared with control, but they are not significantly altered by treatment, therefore implying that they are also influenced by systemic factors. The interactions between all involved cytokines and the various pathways they regulate warrant further studies to clarify their definitive roles.