Novel prognostic matrisome-related gene signature of head and neck squamous cell carcinoma

Characterization of macrophages in ischemia-reperfusion injury-induced acute kidney injury based on single-cell RNA-Seq and bulk RNA-Seq analysis

Acute kidney injury (AKI) is a complex disease, with macrophages playing a vital role in its progression. However, the mechanism of macrophage function remains unclear and strategies targeting macrophages in AKI are controversial. To address this issue, we used single-cell RNA-seq analysis to identify macrophage sub-types involved in ischemia-reperfusion-induced AKI, and then screened for associated hub genes using intersecting bulk RNA-seq data. The single-cell and bulk RNA-seq datasets were obtained from the Gene Expression Omnibus (GEO) database. Screening of differentially-expressed genes (DEGs) and pseudo-bulk DEG analyses were used to identify common hub genes. Pseudotime and trajectory analyses were performed to investigate the progression of cell differentiation. CellChat analysis was performed to reveal the crosstalk between cell clusters. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to identify enriched pathways in the cell clusters. Immunofluorescence and RT-PCR were preformed to validate the expression of the identified hub genes. Four hub genes, Vim, S100a6, Ier3, and Ccr1, were identified in the infiltrated macrophages between normal samples and those 3 days after ischemia-reperfusion renal injury (IRI); all were associated with the progression of IRI-induced AKI. Increased expression of Vim, S100a6, Ier3, and Ccr1 in infiltrated macrophages may be associated with inflammatory responses and may mediate crosstalk between macrophages and renal tubular epithelial cells under IRI conditions. Our results reveal that Ier3 may be critical in AKI, and that Vim, S100a6, Ier3, and Ccr1 may act as novel biomarkers and potential therapeutic targets for IRI-induced AKI.

High-Resolution Profiling of Head and Neck Squamous Cells Carcinoma Identifies Specific Biomarkers and Expression Subtypes of Clinically Relevant Vulnerabilities

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) is the seventh most common cancer worldwide. Although there are several options for the treatment of HNSC, there is still a lack of better biomarkers to accurately predict the response to treatment and thus be more able to correctly treat the therapeutic modality.

METHODS

First, we typed cases from the TCGA-HNSC cohort into subtypes by a Bayesian non-negative matrix factorization (BayesNMF)-based consensus clustering approach. Subsequently, genomic and proteomic data from HNSC cell lines were integrated to identify biomarkers of response to targeted therapies and immunotherapies. Finally, associations between HNSC subtypes and CD8 T-cell-associated effector molecules, common immune checkpoint genes, were compared to assess the potential of HNSC subtypes as clinically predictive immune checkpoint blockade therapy.

RESULTS

The 500 HNSC cases from TCGA were put through a consensus clustering approach to identify six HNSC expression subtypes. In addition, subtypes with unique proteomics and dependency profiles were defined based on HNSC cell line histology and proteomics data. Subtype 4 (S4) exhibits hyperproliferative and hyperimmune properties, and S4-associated cell lines show specific vulnerability to ADAT2, EIF5AL1, and PAK2. PD-L1 and CASP1 inhibitors have therapeutic potential in S4, and we have also demonstrated that S4 is more responsive to immune checkpoint blockade therapy.

CONCLUSION

Overall, our HNSC typing approach identified robust tumor-expressing subtypes, and data from multiple screens also revealed subtype-specific biology and vulnerabilities. These HNSC expression subtypes and their biomarkers will help develop more effective therapeutic strategies.

Single-cell sequencing of head and neck carcinoma: Transcriptional landscape and prognostic model based on malignant epithelial cell features

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, and the development of novel therapeutic strategies for HNSCC requires a profound understanding of tumor cells and the tumor microenvironment (TME). Additionally, HNSCC has a poor prognosis, necessitating the use of genetic markers for predicting clinical outcomes in HNSCC. In this study, we performed single-cell sequencing analysis on tumor tissues from seven HNSCC patients, along with one adjacent normal tissue. Firstly, the analysis of epithelial cell clusters revealed two clusters of malignant epithelial cells, characterized by unique gene expression patterns and dysregulated signaling pathways compared to normal epithelial cells. Secondly, the examination of the TME unveiled extensive crosstalk between fibroblasts and malignant epithelial cells, potentially mediated through ligand-receptor interactions such as COL1A1-SDC1, COL1A1-CD44, and COL1A2-SDC1. Furthermore, transcriptional heterogeneity was observed in immune cells present in the TME, including macrophages and dendritic cells. Finally, leveraging the gene expression profiles of malignant epithelial cells, we developed a prognostic model comprising six genes, which we validated using two independent datasets. These findings shed light on the heterogeneity within HNSCC tumors and the intricate interplay between malignant cells and the TME. Importantly, the developed prognostic model demonstrates high efficacy in predicting the survival outcomes of HNSCC patients.

Unveiling pathogenic mutations in BRCA1 and BRCA2 genes across head and neck squamous cell carcinoma patients via next generation sequencing

Head and Neck Squamous Cell Carcinoma (HNSC) presents a formidable challenge in the field of oncology due to its aggressive nature and the limited therapeutic options available. In this study, our primary focus was on the Pakistani HNSC patient population, aiming to investigate germline oncogenic mutations within the BRCA1 and BRCA2 genes via Next Generation Sequencing (NGS) and explore their clinical implications. We sought to understand the functional consequences of these mutations via RT-qPCR and Immunohistochemistry (IHC) techniques. The key discovery of our research lies in the identification of three pathogenic mutations, including two within BRCA1 (p.Cys274Ter and p.Glu272Ter) and one within BRCA2 (p.Met1Val), among Pakistani HNSC patients. These mutations previously associated with an increased risk of various cancers. What sets our study apart is the uniqueness of these pathogenic mutations, absent in HNSC patients from other populations. This suggests a distinct genetic profile in Pakistani HNSC patients, possibly contributing to their susceptibility to this malignancy. Furthermore, our research revealed elevated expression levels of BRCA1 and BRCA2 genes in HNSC samples harboring pathogenic mutations, offering insights into mechanisms driving tumor progression in HNSC. Importantly, we identified significant enrichment of BRCA1/2 genes in pathways related to cancer development within the KEGG database. Finally, in our quest to explore therapeutic avenues, we systematically analyzed drugs targeting up-regulated and mutated BRCA1/2 genes, identifying promising candidates for tailored treatment modalities in HNSC. In conclusion, our study reveals the unique genetic profile of HNSC in Pakistani patients, featuring unique pathogenic mutations in BRCA1 and BRCA2 genes. These mutations offer promise as valuable diagnostic markers and potential therapeutic targets.

Antimicrobial Peptide MPX with Broad-Spectrum Bactericidal Activity Promotes Proper Abscess Formation and Relieves Skin Inflammation

Bacteria have developed antibiotic resistance during the large-scale use of antibiotics, and multidrug-resistant strains are common. The development of new antibiotics or antibiotic substitutes has become an important challenge for humankind. MPX is a 14 amino acid peptide belonging to the MP antimicrobial peptide family. In this study, the antibacterial spectrum of the antimicrobial peptide MPX was first tested. The antimicrobial peptide MPX was tested for antimicrobial activity against the gram-positive bacterium S. aureus ATCC 25923, the gram-negative bacteria E. coli ATCC 25922 and Salmonella enterica serovar Typhimurium CVCC541, and the fungus Candida albicans ATCC 90029. The results showed that MPX had good antibacterial activity against the above four strains, especially against E. coli, for which the MIC was as low as 15.625 μg/mL. The study on the bactericidal mechanism of the antimicrobial peptide revealed that MPX can destroy the integrity of the cell membrane, increase membrane permeability, and change the electromotive force of the membrane, thereby allowing the contents to leak out and mediating bacterial death. A mouse acute infection model was used to evaluate the therapeutic effect of MPX after acute infection of subcutaneous tissue by S. aureus. The study showed that MPX could promote tissue repair in S. aureus infection and alleviate lung damage caused by S. aureus. In addition, skin H&E staining showed that MPX treatment facilitated the formation of appropriate abscesses at the subcutaneous infection site and facilitated the clearance of bacteria by the skin immune system. The above results show that MPX has good antibacterial activity and broad-spectrum antibacterial potential and can effectively prevent the invasion of subcutaneous tissue by S. aureus, providing new ideas and directions for the immunotherapy of bacterial infections.

Identification of S1PR4 as an immune modulator for favorable prognosis in HNSCC through machine learning

G protein-coupled receptors (GPCRs) are the largest family of membrane proteins and play a critical role as pharmacological targets. An improved understanding of GPCRs' involvement in tumor microenvironment may provide new perspectives for cancer therapy. This study used machine learning to classify head and neck squamous cell carcinoma (HNSCC) patients into two GPCR-based subtypes. Notably, these subtypes showed significant differences in prognosis, gene expression, and immune microenvironment, particularly CD8+ T cell infiltration. S1PR4 emerged as a key regulator distinguishing the subtypes, positively correlated with CD8+ T cell proportion and cytotoxicity in HNSCC. It was predominantly expressed in CX3CR1+CD8+ T cells among T cells. Upregulation of S1PR4 enhanced T cell function during CAR-T cell therapy, suggesting its potential in cancer immunotherapy. These findings highlight S1PR4 as an immune modulator for favorable prognosis in HNSCC, and offer a potential GPCR-targeted therapeutic option for HNSCC treatment.

The value of basement membrane-associated genes in the prognosis and immune regulation of glioma

Gliomas have a high incidence rate in central nervous tumors. Although many breakthroughs have been made in the pathogenesis and treatment of glioma, the recurrence and metastasis rates of patients have not been improved based on the uniqueness of glioma. Glioma destroys the surrounding basement membrane (BM), leading to local infiltration, resulting in the corresponding clinical and neurological symptoms. Therefore, exploring the biological roles played by BM associated genes in glioma is particularly necessary for a comprehensive understanding of the biological processes of glioma and its treatment. Differential expression and univariate COX regression analyses were used to identify the basement membrane genes (BMGs) to be included in the model. LASSO regression was used to construct the BMG model. The Kaplan-Meier (KM) survival analysis model was used to assess the prognosis discrimination between training sets, validation sets, and clinical subgroups. Receiver-operating characteristic (ROC) analysis was used to test the prognostic efficacy of the model. Use calibration curves to verify the accuracy of nomograms. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and gene set enrichment analysis (GSEA) were used to analyze the function and pathway enrichment among the model groups. ESTIMATE and other 7 algorithms including CIBERSORT were used to evaluate the immune microenvironment. "pRRophetic" was used to evaluate drug sensitivity. This study demonstrated that high-risk genes (LAMB4, MMP1, MMP7) promote glioma progression and negatively correlate with patient prognosis. In the tumor microenvironment (TME), high-risk genes have increased scores of macrophages, neutrophils, immune checkpoints, chemokines, and chemokine receptors. This study suggests that BMGs, especially high-risk-related genes, are potential sites for glioma therapy, a new prospect for comprehensively understanding the molecular mechanism of glioma.

Circadian rhythm-related genes index: A predictor for HNSCC prognosis, immunotherapy efficacy, and chemosensitivity

Background

Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer and is highly aggressive and heterogeneous, leading to variable prognosis and immunotherapy outcomes. Circadian rhythm alterations in tumourigenesis are of equal importance to genetic factors and several biologic clock genes are considered to be prognostic biomarkers for various cancers. The aim of this study was to establish reliable markers based on biologic clock genes, thus providing a new perspective for assessing immunotherapy response and prognosis in patients with HNSCC.

Methods

We used 502 HNSCC samples and 44 normal samples from the TCGA-HNSCC dataset as the training set. 97 samples from GSE41613 were used as an external validation set. Prognostic characteristics of circadian rhythm-related genes (CRRGs) were established by Lasso, random forest and stepwise multifactorial Cox. Multivariate analysis revealed that CRRGs characteristics were independent predictors of HNSCC, with patients in the high-risk group having a worse prognosis than those in the low-risk group. The relevance of CRRGs to the immune microenvironment and immunotherapy was assessed by an integrated algorithm.

Results

6-CRRGs were considered to be strongly associated with HNSCC prognosis and a good predictor of HNSCC. The riskscore established by the 6-CRRG was found to be an independent prognostic factor for HNSCC in multifactorial analysis, with patients in the low-risk group having a higher overall survival (OS) than the high-risk group. Nomogram prediction maps constructed from clinical characteristics and riskscore had good prognostic power. Patients in the low-risk group had higher levels of immune infiltration and immune checkpoint expression and were more likely to benefit from immunotherapy.

Conclusion

6-CRRGs play a key predictive role for the prognosis of HNSCC patients and can guide physicians in selecting potential responders to prioritise immunotherapy, which could facilitate further research in precision immuno-oncology.