Identification of key biomarkers related to epithelial-mesenchymal transition and immune infiltration in ameloblastoma using integrated bioinformatics analysis

Extracellular matrix of ameloblastoma-derived negatively regulates osteogenic differentiation

OBJECTIVE

To investigate the effects of key pathogenic genes involved in the development of jaw ameloblastoma (AB) and its associated extracellular matrix (ECM) on osteogenic differentiation in order to provide a theoretical foundation for future research into bone aggressiveness of AB.

METHODS

The essential genes were identified by five AB patients for whole-exome sequencing and the microarray datasets GES38494 and GES132472. Moreover, the expression of key genes and their encoded proteins in AB tissues was explored. In addition, AB-derived the decellularized ECM (ABdECM) tissues were generated by the decellularization technique. Furthermore, the osteogenic development of periodontal ligament stem cells (PDLSCs) was mimicked by simulating the effects of the AB tumor microenvironment (TME).

RESULTS

The AB essential genes including COL1A2, COL4A2, FBN1, and HPSE were discovered. Among them, the expression of HPSE was down-regulated, while that of COL1A2, COL4A2, and FBN1 was noticeably upregulated in AB compared with normal gingival tissues of the jaws. In vitro osteogenic differentiation of PDLSCs was suppressed by the ABdECM.

CONCLUSIONS

Abnormal ECM proteins encoded by COL4A2, COL1A2, FBN1, and HPSE genes can cause disturbance in the ECM environment of AB and promote bone resorption.

Machine learning and experiments revealed a novel pyroptosis-based classification linked to diagnosis and immune landscape in spinal cord injury

Background

Rising evidence indicates the development of pyroptosis in the initiation and pathogenesis of spinal cord injury (SCI). However, the associated effects of pyroptosis-related genes (PRGs) in SCI are unclear.

Methods

We obtained the gene expression profiles of SCI and normal samples in the GEO.

Database

The R package limma screened for differentially expressed (DE) PRGs and performed functional enrichment analysis. Mechanical learning and PPI analysis helped filter essential PRGs to diagnose SCI. Peripheral blood was collected for validation from ten SCI patients and eight healthy individuals. The association of essential PRGs with immune infiltration was evaluated, and pyroptosis subtypes were recognized in SCI patients by unsupervised cluster analysis. Besides, a SCI model was built for in vivo validation of essential PRGs.

Result

We identified 25 DE-PRGs between SCI and normal controls. Functional enrichment analysis revealed the principal involvement of DE-PRGs in pyroptosis, inflammasome complex, interleukin-1 beta production, etc. Subsequently, three essential PRGs were identified and validated, showing excellent diagnostic efficacy and significant correlation with immune cell infiltration. Additionally, we developed diagnostic nomograms to predict the occurrence of SCI. Two pyroptosis subtypes exhibited distinct biological functions and immune landscapes among SCI patients. Finally, the expression of these essential PRGswas verified in vivo.

Conclusion

The current study described the vital effects of pyroptosis-related genes in SCI, providing a novel direction for effective assessment and management of SCI.

Recurrence and malignant risk of ameloblastoma: A demographic study of 1626 cases from east China

BACKGROUND

Ameloblastoma is characterized by aggressive nature, high recurrence rate, occasional malignant transformation, but recurrence and malignant incidence of ameloblastoma are not yet addressed by a large-scale case series study.

MATERIALS AND METHODS

This study provided a detailed description of the relationship between demographic characteristics and recurrence and malignant cases with different clinical types of ameloblastoma (n = 1626).

RESULTS

The overall incidence of recurrence and malignancy was 17.2 % and 3.4 %, respectively. Notably, we observed that there were multiple recurrent episodes (mean time, 24.3-28.7 months) among ameloblastoma patients. Multivariate analysis revealed that age of > 45 years (odds ratios (OR), 2.10; 95 % confidence interval (CI), 1.17-3.76), male (OR, 3.24; 95 %CI, 1.49-6.99), maxilla (OR, 5.58; 95 %CI, 3.11-10.0), and pre-existing recurrence (OR, 3.79; 95 %CI, 2.05-7.01) as independent factors were associated significantly with increased risk of malignancy.

CONCLUSION

Identification of the clinical factors responsible for increased risk of malignancy provides better insight in management planning for ameloblastoma.

FN1 mediated activation of aspartate metabolism promotes the progression of triple-negative and luminal a breast cancer

BACKGROUND

Breast cancer (BC) is regarded as one of the most common cancers diagnosed among the female population and has an extremely high mortality rate. It is known that Fibronectin 1 (FN1) drives the occurrence and development of a variety of cancers through metabolic reprogramming. Aspartic acid is considered to be an important substrate for nucleotide synthesis. However, the regulatory mechanism between FN1 and aspartate metabolism is currently unclear.

METHODS

We used RNA sequencing (RNA seq) and liquid chromatography-mass spectrometry to analyze the tumor tissues and paracancerous tissues of patients. MCF7 and MDA-MB-231 cells were used to explore the effects of FN1-regulated aspartic acid metabolism on cell survival, invasion, migration and tumor growth. We used PCR, Western blot, immunocytochemistry and immunofluorescence techniques to study it.

RESULTS

We found that FN1 was highly expressed in tumor tissues, especially in Lumina A and TNBC subtypes, and was associated with poor prognosis. In vivo and in vitro experiments showed that silencing FN1 inhibits the activation of the YAP1/Hippo pathway by enhancing YAP1 phosphorylation, down-regulates SLC1A3-mediated aspartate uptake and utilization by tumor cells, inhibits BC cell proliferation, invasion and migration, and promotes apoptosis. In addition, inhibition of FN1 combined with the YAP1 inhibitor or SLC1A3 inhibitor can effectively inhibit tumor growth, of which inhibition of FN1 combined with the YAP1 inhibitor is more effective.

CONCLUSION

Targeting the "FN1/YAP1/SLC1A3/Aspartate metabolism" regulatory axis provides a new target for BC diagnosis and treatment. This study also revealed that intratumoral metabolic heterogeneity plays an important role in the progression of different subtypes of breast cancer.

Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response

Osteosarcoma (OS) is a highly heterogeneous malignant bone tumor, and its tendency to metastasize leads to a poor prognosis. TGFβ is an important regulator in the tumor microenvironment and is closely associated with the progression of various types of cancer. However, the role of TGFβ-related genes in OS is still unclear. In this study, we identified 82 TGFβ DEGs based on RNA-seq data from the TARGET and GETx databases and classified OS patients into two TGFβ subtypes. The KM curve showed that the Cluster 2 patients had a substantially poorer prognosis than the Cluster 1 patients. Subsequently, a novel TGFβ prognostic signatures (MYC and BMP8B) were developed based on the results of univariate, LASSO, and multifactorial Cox analyses. These signatures showed robust and reliable predictive performance for the prognosis of OS in the training and validation cohorts. To predict the three-year and five-year survival rate of OS, a nomogram that integrated clinical features and risk scores was also developed. The GSEA analysis showed that the different subgroups analyzed had distinct functions, particularly, the low-risk group was associated with high immune activity and a high infiltration abundance of CD8 T cells. Moreover, our results indicated that low-risk cases had higher sensitivity to immunotherapy, while high-risk cases were more sensitive to sorafenib and axitinib. scRNA-Seq analysis further revealed that MYC and BMP8B were strongly expressed mainly in tumor stromal cells. Finally, in this study, we confirmed the expression of MYC and BMP8B by performing qPCR, WB, and IHC analyses. To conclude, we developed and validated a TGFβ-related signature to accurately predict the prognosis of OS. Our findings might contribute to personalized treatment and making better clinical decisions for OS patients.

Potential involvement of polycystins in the pathogenesis of ameloblastomas: Analysis based on bioinformatics and immunohistochemistry

OBJECTIVE

To perform an integrated analysis in identifying novel hub genes that could facilitate the diagnosis and targeted therapy of ameloblastoma.

DESIGN

The expression profiling dataset, GSE38494, was obtained from the Gene Expression Omnibus database. Differentially expressed genes were identified through GEO2R online tool and characterised via Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The protein-protein interaction network and hub genes were screened using the STRING database and Cytoscape software. Subsequently, an upregulated gene was selected for further validation using the GSE132472 dataset. Further, immunohistochemistry was performed to assess the expression of the selected gene in ameloblastomas, odontogenic keratocysts, dentigerous cysts, and gingival tissues. The diagnostic and therapeutic utility of the selected hub genes were further verified by receiver operating characteristic analysis and the DGIdb database.

RESULTS

We identified six hub genes in ameloblastoma, among which the upregulated gene PKD2 and its related gene PKD1 were further validated. GO functional annotation revealed that PKD2 is involved in cell-cell junction, extracellular exosome, cytoplasm, endoplasmic reticulum, and calcium ion transport. The immunohistochemical analysis showed that the expression of polycystin-1 and polycystin-2, encoded by the PKD1 and PKD2 genes, respectively, was upregulated in ameloblastoma. PKD1 and PKD2 had a high diagnostic utility for ameloblastoma, and allopurinol interacted with the PKD2 gene.

CONCLUSION

Our research indicates that polycystins are highly expressed in ameloblastoma and might be involved in the oncogenesis of ameloblastoma, thus offering a new perspective on the molecular mechanisms and targeted therapies on ameloblastoma.

Comprehensive landscape of immune-based classifier related to early diagnosis and macrophage M1 in spinal cord injury

Numerous studies have documented that immune responses are crucial in the pathophysiology of spinal cord injury (SCI). Our study aimed to uncover the function of immune-related genes (IRGs) in SCI. Here, we comprehensively evaluated the transcriptome data of SCI and healthy controls (HC) obtained from the GEO Database integrating bioinformatics and experiments. First, a total of 2067 DEGs were identified between the SCI and HC groups. Functional enrichment analysis revealed substantial immune-related pathways and functions that were abnormally activated in the SCI group. Immune analysis revealed that myeloid immune cells were predominantly upregulated in SCI patients, while a large number of lymphoid immune cells were dramatically downregulated. Subsequently, 51 major IRGs were screened as key genes involved in SCI based on the intersection of the results of WGCNA analysis, DEGs, and IRGs. Based on the expression profiles of these genes, two distinct immune modulation patterns were recognized exhibiting opposite immune characteristics. Moreover, 2 core IRGs (FCER1G and NFATC2) were determined to accurately predict the occurrence of SCI via machine learning. qPCR analysis was used to validate the expression of core IRGs in an external independent cohort. Finally, the expression of these core IRGs was validated by sequencing, WB, and IF analysis in vivo. We found that these two core IRGs were closely associated with immune cells and verified the co-localization of FCER1G with macrophage M1 via IF analysis. Our study revealed the key role of immune-related genes in SCI and contributed to a fresh perspective for early diagnosis and treatment of SCI.

Conventional Ameloblastoma. A Case Report with Microarray and Bioinformatic Analysis

Ameloblastoma is a rare benign epithelial odontogenic neoplasm, but with great clinical implications, as despite its benignity and slow growth, most cases are locally aggressive with a significant recurrence rate. Histological, cellular, or molecular analyses of its pathogenesis have confirmed the complexity of this neoplasm. We present the case of a 20-year-old patient with a suggestive clinical and radiographic diagnosis of ameloblastoma. An incisional biopsy was obtained confirming the diagnosis of conventional ameloblastoma. Left hemimandibulectomy and plate reconstruction were performed. Histopathological analysis of the surgical specimen confirmed the conventional ameloblastoma with a plexiform pattern and significant areas of cystic degeneration and amyloid-like-like deposits. Additionally, a microarray was carried out with bioinformatic analysis for the enrichment, protein interaction, and determination of eight hub genes (CRP, BCHE, APP, AKT1, AGT, ACTC1, ADAM10, and APOA2) related to their pathogenesis.

Potential Biomarkers and Signaling Pathways Associated with the Pathogenesis of Primary Ameloblastoma: A Systems Biology Approach

Objective

Ameloblastoma is a benign odontogenic tumor that may lead to ameloblastic carcinoma. This study aimed to determine potential signaling pathways and biological processes, critical genes and their regulating transcription factors (TFs), and miRNAs, as well as protein kinases involved in the etiology of primary ameloblastoma.

Methods

The dataset GSE132472 was obtained from the GEO database, and multivariate statistical analyses were applied to identify differentially expressed genes (DEGs) in primary ameloblastoma tissues compared to the corresponding normal gingiva samples. A protein-protein interaction (PPI) map was built using the STRING database. The Cytoscape software identified significant modules and the hub genes within the PPI network. Gene Ontology annotation and signaling pathway analyses were executed by employing the DAVID and Reactome databases, respectively. Significant TFs and miRNAs acting on the hub genes were identified using the iRegulon plugin and MiRWalk 2.0 database, respectively. A protein kinase enrichment analysis was conducted using the online Kinase Enrichment Analysis 2 (KEA2) web server. The approved drugs acting on the hub genes were also found.

Results

A total of 1,629 genes were differentially expressed in primary ameloblastoma (P value <0.01 and |Log2FC| > 1). HRAS, CDK1, MAPK3, ERBB2, COL1A1, CYCS, and BRCA1 demonstrated high degree and betweenness centralities in the PPI network. E2F4 was the most significant TF acting on the hub genes. BTK was the protein kinase significantly enriched by the TFs. Cholesterol biosynthesis was considerably involved in primary ameloblastoma.

Conclusions

This study provides an intuition into the potential mechanisms involved in the etiology of ameloblastoma.

Expression of lactate-related signatures correlates with immunosuppressive microenvironment and prognostic prediction in ewing sarcoma

Objectives: Ewing sarcoma (EWS) is an aggressive tumor of bone and soft tissue. Growing evidence indicated lactate as a pivotal mediator of crosstalk between tumor energy metabolism and microenvironmental regulation. However, the contribution of lactate-related genes (LRGs) in EWS is still unclear.

Methods: We obtained the transcriptional data of EWS patients from the GEO database and identified differentially expressed-LRGs (DE-LRGs) between EWS patient samples and normal tissues. Unsupervised cluster analysis was utilized to recognize lactate modulation patterns based on the expression profile of DE-LRGs. Functional enrichment including GSEA and GSVA analysis was conducted to identify molecular signaling enriched in different subtypes. ESTIMATE, MCP and CIBERSORT algorithm was used to explore tumor immune microenvironment (TIME) between subtypes with different lactate modulation patterns. Then, lactate prognostic risk signature was built via univariate, LASSO and multivariate Cox analysis. Finally, we performed qPCR analysis to validate candidate gene expression.

Result: A total of 35 DE-LRGs were identified and functional enrichment analysis indicated that these LRGs were involved in mitochondrial function. Unsupervised cluster analysis divided EWS patients into two lactate modulation patterns and we revealed that patients with Cluster 1 pattern were linked to poor prognosis and high lactate secretion status. Moreover, TIME analysis indicated that the abundance of multiple immune infiltrating cells were dramatically elevated in Cluster 1 to Cluster 2, including CAFs, endothelial cells, Macrophages M2, etc., which might contribute to immunosuppressive microenvironment. We also noticed that expression of several immune checkpoint proteins were clearly increased in Cluster 1 to Cluster 2. Subsequently, seven genes were screened to construct LRGs prognostic signature and the performance of the resulting signature was validated in the validation cohort. Furthermore, a nomogram integrating LRGs signature and clinical characteristics was developed to predict effectively the 4, 6, and 8-year prognosis of EWS patients.

Conclusion: Our study revealed the role of LRGs in immunosuppressive microenvironment and predicting prognosis in EWS and provided a robust tool to predict the prognosis of EWS patients.