FPR1 mediates the tumorigenicity of human cervical cancer cells

Cervical extracellular matrix hydrogel optimizes tumor heterogeneity of cervical squamous cell carcinoma organoids

Cervical cancer, primarily squamous cell carcinoma, is the most prevalent gynecologic malignancy. Organoids can mimic tumor development in vitro, but current Matrigel inaccurately replicates the tissue-specific microenvironment. This limitation compromises the accurate representation of tumor heterogeneity. We collected para-cancerous cervical tissues from patients diagnosed with cervical squamous cell carcinoma (CSCC) and prepared uterine cervix extracellular matrix (UCEM) hydrogels. Proteomic analysis of UCEM identified several tissue-specific signaling pathways including human papillomavirus, phosphatidylinositol 3-kinase-AKT, and extracellular matrix receptor. Secreted proteins like FLNA, MYH9, HSPA8, and EEF1A1 were present, indicating UCEM successfully maintained cervical proteins. UCEM provided a tailored microenvironment for CSCC organoids, enabling formation and growth while preserving tumorigenic potential. RNA sequencing showed UCEM-organoids exhibited greater similarity to native CSCC and reflected tumor heterogeneity by exhibiting CSCC-associated signaling pathways including virus protein-cytokine, nuclear factor κB, tumor necrosis factor, and oncogenes EGR1, FPR1, and IFI6. Moreover, UCEM-organoids developed chemotherapy resistance. Our research provides insights into advanced organoid technology through native matrix hydrogels.

The role of NF-κB in carcinogenesis of cervical cancer: opportunities and challenges

The nuclear factor-κB (NF-κB) family, consisting of several transcription factors, has been implicated in the regulation of cell proliferation and invasion, as well as inflammatory reactions and tumor development. Cervical cancer (CC) results from long-term interactions of multiple factors, among which persistent high-risk human papillomavirus (hrHPV) infection is necessary. During different stages from early to late after HPV infection, the activity of NF-κB varies and plays various roles in carcinogenesis and progress of CC. As the center of the cell signaling transduction network, NF-κB can be activated through classical and non-classical pathways, and regulate the expression of downstream target genes involved in regulating the tumor microenvironment and acquiring hallmark traits of CC cells. Targeting NF-κB may help treat CC and overcome the resistance to radiation and chemotherapy. Even though NF-κB inhibitors have not been applied in clinical treatment as yet, due to limitations such as dose-restrictive toxicity and poor tumor-specificity, it is still considered to have significant therapeutic potential and application prospects. In this review, we focus on the role of NF-κB in the process of CC occurrence and hallmark capabilities acquisition. Finally, we summarize relevant NF-κB-targeted treatments, providing ideas for the prevention and treatment of CC.

Construction of monocyte-related prognosis model based on comprehensive analysis of bulk RNA-seq and single-cell RNA-seq in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is a common subtype of ovarian cancer with high mortality. Finding a new biomarker is useful for the diagnosis and treatment of HGSOC. The scRNA and bulk RNA data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The monocyte-related clusters were identified and annotated by Seruat and SingleR package. The Kaplan-Meier and receiver operating characteristic curve was used to determine the prognosis. The differentially expressed genes were determined by limma. The single sample Gene Set Enrichment Analysis, Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes were used for the enrichment function. The correlation between drug activity and gene expression was assessed by rcellminer and rcellminer Data package. We identified 9 cell types and obtained 37 differentially expressed marker genes of monocyte. A2M, CD163, and FPR1 were screened out as hub genes and used to construct risk model in HGSOC through univariate and multivariate cox analysis. Single sample Gene Set Enrichment Analysis showed risk score was related to B cell and T cell signal pathways, and further analysis showed most immune checkpoint genes expressions were upregulated in high-risk score group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis exhibited that hub gene related genes were involved in signal receptor binding and cytokine-cytokine interaction. Low A2M expression and high expression of CD163 and FPR1 were associated with poor prognosis. Gene Set Enrichment Analysis revealed that A2M promoted tumor development through enhancing immune cell related signal pathways, while CD163 and FPR1 inhibited tumor development through activated carcinogenic signal pathways. Drug sensitivity analysis revealed that these hub genes could be potential therapeutic targets for the treatment of HGSOC. We constructed a risk model for the overall survival and explored the potential mechanism of monocyte in HGSOC.

Formyl peptide receptor 1 is involved in surgery-induced neuroinflammation and dysfunction of learning and memory in mice

Postoperative cognitive dysfunction (POCD) is a common complication after surgery. Peripheral immune cells may contribute to the development of POCD. However, molecules that are important for this contribution are not known. We hypothesize that formyl peptide receptor 1 (FPR1), a molecule critical for the migration of the monocytes and neutrophils into the brain after brain ischemia, is central to the development of postoperative neuroinflammation and dysfunction of learning and memory. Male C57BL/6 (wild-type) mice and FPR1-/- mice received right carotid artery exposure surgery. Some wild-type mice received cFLFLF, an FPR1 antagonist. Mouse brains were harvested 24 h after the surgery for biochemical analysis. Mice were subjected to the Barnes maze and fear conditioning tests to determine their learning and memory from 2 weeks after the surgery. We found that surgery increased FPR1 in the brain and proinflammatory cytokines in the blood and brain of wild-type mice. Surgery also impaired their learning and memory. cFLFLF attenuated these effects. Surgery did not induce an increase in the proinflammatory cytokines and impairment of learning and memory in FPR1-/- mice. These results suggest that FPR1 is important for the development of neuroinflammation and dysfunction of learning and memory after surgery. Specific interventions that inhibit FPR1 may be developed to reduce POCD.

Integrated bioinformatics analysis of differentially expressed genes in the temporomandibular joint internal derangement

OBJECTIVES

This study aimed to identify significant mechanisms and potential treatments for temporomandibular joint internal derangement (TMJD) through integrated bioinformatics analysis.

MATERIALS AND METHODS

Gene expression data sets (GSE66864) from the Gene Expression Omnibus (GEO) database were downloaded. Differentially expressed genes (DEGs) were identified both in the treatment groups and in controls by R packages. Network analysis of protein-protein interaction (PPI) and Human Protein Atlas was used to explore DEGs' potential function. DGIdb database was utilized to gain potential drug targets.

RESULTS

In conclusion, 126 DEGs were selected for TMJD through bioinformatics analysis. Both GO and Kyoto Encyclopedia of Genes and Genomes analyses combined showed the pathways involved in TMJD. A PPI network was constructed to select the top 10 hub genes, of which five hub genes were chosen for further investigation. Moreover, the microenvironment of immune cells related to hub genes was evaluated by R packages. Macrophages play an important role in inflammation and oral-related tumors. The Human Protein Atlas analysis indicated that the five hub genes are highly related to head and neck cancer. Finally, eight potential drugs were selected for two genes using the DGIdb database.

CONCLUSION

Our integrated bioinformatics analysis identified DEGs in TMJD and provided potential ideas for further research and treatment approaches. However, experimental validation of the hub genes and potential drug targets is still needed. The key mechanisms of the identified genes and their potential roles as biomarkers or drug targets in TMJD require further investigation.

Papillary Thyroid Carcinoma Landscape and Its Immunological Link With Hashimoto Thyroiditis at Single-Cell Resolution

The tumor microenvironment heterogeneity of papillary thyroid cancer (PTC) is poorly characterized. The relationship between PTC and Hashimoto thyroiditis (HT) is also in doubt. Here, we used single-cell RNA sequencing to map the transcriptome landscape of PTC from eight PTC patients, of which three were concurrent with HT. Predicted copy number variation in epithelial cells and mesenchymal cells revealed the distinct molecular signatures of carcinoma cells. Carcinoma cells demonstrated intertumoral heterogeneity based on BRAF V600E mutation or lymph node metastasis, and some altered genes were identified to be correlated with disease-free survival in The Cancer Genome Atlas datasets. In addition, transcription factor regulons of follicular epithelial cells unveil the different transcription activation state in PTC patients with or without concurrent HT. The immune cells in tumors exhibited distinct transcriptional states, and the presence of tumor-infiltrating B lymphocytes was predominantly linked to concurrent HT origin. Trajectory analysis of B cells and plasma cells suggested their migration potential from HT adjacent tissues to tumor tissues. Furthermore, we revealed diverse ligand–receptor pairs between non-immune cells, infiltrating myeloid cells, and lymphocytes. Our results provided a single-cell landscape of human PTC. These data would deepen the understanding of PTC, as well as the immunological link between PTC and HT.

Annexin A1 as a Regulator of Immune Response in Cancer

Annexin A1 is a 37 kDa phospholipid-binding protein that is expressed in many tissues and cell types, including leukocytes, lymphocytes and epithelial cells. Although Annexin A1 has been extensively studied for its anti-inflammatory activity, it has been shown that, in the cancer context, its activity switches from anti-inflammatory to pro-inflammatory. Remarkably, Annexin A1 shows pro-invasive and pro-tumoral properties in several cancers either by eliciting autocrine signaling in cancer cells or by inducing a favorable tumor microenvironment. Indeed, the signaling of the N-terminal peptide of AnxA1 has been described to promote the switching of macrophages to the pro-tumoral M2 phenotype. Moreover, AnxA1 has been described to prevent the induction of antigen-specific cytotoxic T cell response and to play an essential role in the induction of regulatory T lymphocytes. In this way, Annexin A1 inhibits the anti-tumor immunity and supports the formation of an immunosuppressed tumor microenvironment that promotes tumor growth and metastasis. For these reasons, in this review we aim to describe the role of Annexin A1 in the establishment of the tumor microenvironment, focusing on the immunosuppressive and immunomodulatory activities of Annexin A1 and on its interaction with the epidermal growth factor receptor.

An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

To explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.

Combination of Immune-Related Genomic Alterations Reveals Immune Characterization and Prediction of Different Prognostic Risks in Ovarian Cancer

With the highest case-fatality rate among women, the molecular pathological alterations of ovarian cancer (OV) are complex, depending on the diversity of genomic alterations. Increasing evidence supports that immune infiltration in tumors is associated with prognosis. Therefore, we aim to assess infiltration in OV using multiple methods to capture genomic signatures regulating immune events to identify reliable predictions of different outcomes. A dataset of 309 ovarian serous cystadenocarcinoma patients with overall survival >90 days from The Cancer Genome Atlas (TCGA) was analyzed. Multiple estimations and clustering methods identified and verified two immune clusters with component differences. Functional analyses pointed out immune-related alterations underlying internal genomic variables potentially. After extracting immune genes from a public database, the LASSO Cox regression model with 10-fold cross-validation was used for selecting genes associated with overall survival rate significantly, and a risk score model was then constructed. Kaplan-Meier survival and Cox regression analyses among cohorts were performed systematically to evaluate prognostic efficiency among the risk score model and other clinical pathological parameters, establishing a predictive ability independently. Furthermore, this risk score model was compared among identified signatures in previous studies and applied to two external cohorts, showing better prediction performance and generalization ability, and also validated as robust in association with immune cell infiltration in bulk tissues. Besides, a transcription factor regulation network suggested upper regulatory mechanisms in OV. Our immune risk score model may provide gyneco-oncologists with predictive values for the prognosis and treatment management of patients with OV.

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

BACKGROUND

Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV.

METHODS

Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored.

RESULTS

A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8).

CONCLUSION

The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.