Diagnostic and therapeutic values of PMEPA1 and its correlation with tumor immunity in pan-cancer

Prognostic model based on B cell marker genes for NSCLC patients under neoadjuvant immunotherapy by integrated analysis of single-cell and bulk RNA-sequencing data

BACKGROUND

Neoadjuvant immunotherapy has evolved as an effective option to treat non-small cell lung cancer (NSCLC). B cells play essential roles in the immune system as well as cancer progression. However, the repertoire of B cells and its association with clinical outcomes remains unclear in NSCLC patients receiving neoadjuvant immunotherapy.

METHODS

Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data for LUAD samples were accessed from the TCGA and GEO databases. LUAD-related B cell marker genes were confirmed based on comprehensive analysis of scRNA-seq data. We then constructed the B cell marker gene signature (BCMGS) and validated it. In addition, we evaluated the association of BCGMS with tumor immune microenvironment (TIME) characteristics. Furthermore, we validated the efficacy of BCGMS in a cohort of NSCLC patients receiving neoadjuvant immunotherapy.

RESULTS

A BCMGS was constructed based on the TCGA cohort and further validated in three independent GSE cohorts. In addition, the BCMGS was proven to be significantly associated with TIME characteristics. Moreover, a relatively higher risk score indicated poor clinical outcomes and a worse immune response among NSCLC patients receiving neoadjuvant immunotherapy.

CONCLUSIONS

We constructed an 18-gene prognostic signature derived from B cell marker genes based on scRNA-seq data, which had the potential to predict the prognosis and immune response of NSCLC patients receiving neoadjuvant immunotherapy.

Prognostic Values of METTL3 and Its Roles in Tumor Immune Microenvironment in Pan-Cancer

Background: N6-methyladenosine (m⁶A) is among the most prevalent RNA modifications regulating RNA metabolism. The roles of methyltransferase-like 3 (METTL3), a core catalytic subunit, in various cancers remain unclear. Methods: The expression levels of METTL3 in pan-cancer were profiled and their prognostic values were examined. We assessed the relationships between METTL3 expression levels and tumor immune infiltration levels, immune checkpoint gene expression, immune neoantigens, tumor mutation burden, microsatellite instability, and DNA mismatch repair gene expression. Furthermore, a protein-protein interaction network was drawn, and gene set enrichment analysis was conducted to explore the functions of METTL3. Results: METTL3 expression levels were elevated in most cancers, with high expression associated with poorer overall and disease-free survival. METTL3 levels were significantly related to immune cell infiltration, tumor mutation burden, microsatellite instability, mismatch repair genes, and immune checkpoint gene levels. METTL3 was enriched in pathways related to RNA modification and metabolism and correlated with epithelial-mesenchymal transition. Conclusions: METTL3 serves as an oncogene in most cancer types and shows potential as a prognostic biomarker. Additionally, our comprehensive pan-cancer analysis suggested that METTL3 is involved in regulating the tumor immune microenvironments and epithelial-mesenchymal transition via modulating RNA modification and metabolism, making it a potential therapeutic target.

RNA Sequencing of Idiopathic Subglottic Stenosis Tissues Uncovers Putative Profibrotic Mechanisms and Identifies a Prognostic Biomarker

Idiopathic subglottic stenosis (iSGS) is a localized airway disease that almost exclusively affects females. Understanding the molecular mechanisms involved may provide insights leading to therapeutic interventions. Next-generation sequencing was performed on tissue sections from patients with iSGS (n = 22), antineutrophil cytoplasmic antibody-associated vasculitis (AAV; n = 5), and matched controls (n = 9) to explore candidate genes and mechanisms of disease. Gene expression changes were validated, and selected markers were identified by immunofluorescence staining. Epithelial-mesenchymal transition (EMT) and leukocyte extravasation pathways were the biological mechanisms most relevant to iSGS pathogenesis. Alternatively activated macrophages (M2) were abundant in the subepithelium and perisubmucosal glands of the airway in iSGS and AAV. Increased expression of the mesenchymal marker S100A4 and decreased expression of the epithelial marker epithelial cell adhesion molecule (EPCAM) further supported a role for EMT, but to different extents, in iSGS and antineutrophil cytoplasmic antibody-associated subglottic stenosis. In patients with iSGS, high expression of prostate transmembrane protein, androgen induced 1 (PMEPA1), an EMT regulator, was associated with a shorter recurrence interval (25 versus 116 months: hazard ratio = 4.16; P = 0.041; 95% CI, 1.056-15.60). Thus, EMT is a key pathogenetic mechanism of subglottic stenosis in iSGS and AAV. M2 macrophages contribute to the pathogenesis of both diseases, suggesting a shared profibrotic mechanism, and PMEPA1 may be a biomarker for predicting disease recurrence in iSGS.

Identification of a TGF-β signaling-related gene signature for prediction of immunotherapy and targeted therapy for lung adenocarcinoma

BACKGROUND

Transforming growth factor (TGF)-β signaling functions importantly in regulating tumor microenvironment (TME). This study developed a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical outcome of patients with lung adenocarcinoma (LUAD).

METHODS

TGF-β signaling-related genes came from The Molecular Signature Database (MSigDB). LUAD prognosis-related genes were screened from all the genes involved in TGF-β signaling using least absolute shrinkage and selection operator (LASSO) Cox regression analysis and then used to establish a risk score model for LUAD. ESTIMATE and CIBERSORT analyzed infiltration of immune cells in TME. Immunotherapy response was analyzed by the TIDE algorithm.

RESULTS

A LUAD prognostic 5-gene signature was developed based on 54 TGF-β signaling-related genes. Prognosis of high-risk patients was significantly worse than low-risk patients. Both internal validation and external dataset validation confirmed a high precision of the risk model in predicting the clinical outcomes of LUAD patients. Multivariate Cox analysis demonstrated the model independence in OS prediction of LUAD. The risk model was significantly related to the infiltration of 9 kinds of immune cells, matrix, and immune components in TME. Low-risk patients tended to respond more actively to anti-PD-1 treatment, while high-risk patients were more sensitive to chemotherapy and targeted therapy.

CONCLUSIONS

The 5-gene signature based on TGF-β signaling-related genes showed potential for LUAD management.

PMEPA1 Serves as a Prognostic Biomarker and Correlates with Immune Infiltrates in Cervical Cancer

Emerging studies have demonstrated that Prostate transmembrane protein androgen induced 1 (PMEPA1) plays crucial roles in the carcinogenesis of many developing human tumors. However, the clinical significance of PMEPA1 expression in cervical cancer (CC) and its contribution to cancer immunity have not been investigated. In this study, we identified PMEPA1 as a survival-related gene in CC based on TCGA datasets. Univariate and multivariate analysis showed that PMEPA1 expression was an independent predictor for overall survival in CC patients. We could observe a strong negative correlation between PMEPA1 expression and PMEPA1 methylation. Two CpG sites of PMEPA1 were associated with overall survival, and one CpG site of PMEPA1 was associated with progression-free survival. The low level of PMEPA1 methylation was associated with advanced clinical stage of CC patients. KEGG assays revealed the genes associated with PMEPA1 expression were mainly enriched in several tumor-related pathways. Increased PMEPA1 expressions were observed to be positively related to high immune infiltration levels in several immune cells. Finally, the pan-cancer assays revealed that PMEPA1 expression was associated with the overall survival of UVM, PAAD, LUSC, BLCA, CESC, and LUAD. Taken together, PMEPA1 is a prognosis-related biomarker for multiple cancer types, especially CC. PMEPA1 is involved in tumor immunity, suggesting PMEPA1 may be a potential immunotherapeutic target in CC.

Integrative Pan-Cancer Analysis of KIF15 Reveals Its Diagnosis and Prognosis Value in Nasopharyngeal Carcinoma

Background

KIF15 plays a vital role in many biological processes and has been reported to influence the occurrence and development of certain human cancers. However, there are few systematic evaluations on the role of KIF15 in human cancers, and the role of KIF15 in the diagnosis and prognosis of nasopharyngeal carcinoma (NPC) also remains unexplored. Therefore, this study aimed to conduct a pan-cancer analysis of KIF15 and evaluate its diagnostic and prognostic potential in NPC.

Methods

The expression pattern, prognostic value, molecular function, tumor mutation burden, microsatellite instability, and immune cell infiltration of KIF15 were examined based on public databases. Next, the diagnostic value of KIF15 in NPC was analyzed using the Gene Expression Omnibus (GEO) database and immunohistochemistry (IHC). Kaplan–Meier curves, Cox regression analyses, and nomograms were used to evaluate the effects of KIF15 expression on NPC prognosis. Finally, the effect of KIF15 on NPC was explored by in vitro experiments.

Results

The expression of KIF15 was significantly upregulated in 20 out of 33 cancer types compared to adjacent normal tissue. Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG) analysis showed that KIF15 could participate in several cancer-related pathways. The increased expression level of KIF15 was correlated with worse clinical outcomes in many types of human cancers. Additionally, KIF15 expression was related to cancer infiltration of immune cells, tumor mutation burden, and microsatellite instability. In the analysis of NPC, KIF15 was significantly upregulated based on the GEO database and immunohistochemistry. A high expression of KIF15 was negatively associated with the prognosis of patients with NPC. A nomogram model integrating clinical characteristics and KIF15 expression was established, and it showed good predictive ability with an area under the curve value of 0.73. KIF15 knockdown significantly inhibited NPC cell proliferation and migration.

Conclusions

Our findings revealed the important and functional role of KIF15 as an oncogene in pan-cancer. Moreover, high expression of KIF15 was found in NPC tissues, and was correlated with poor prognosis in NPC. KIF15 may serve as a potential therapeutic target in NPC treatment.

Elevated Ras related GTP binding B (RRAGB) expression predicts poor overall survival and constructs a prognostic nomogram for colon adenocarcinoma

Currently, no articles have explored the roles of RRAGB gene in the occurrence and development of cancer. By means of The Cancer Genome Atlas (TCGA) data mining, we found that this gene might be a novel prognostic predictor for colon adenocarcinoma (COAD). Hence, this article was carried out to explore its roles in COAD and associations with immunity. RRAGB single-gene expression matrix and corresponding clinical information were extracted from TCGA database. Univariate/multivariate cox regression analyses and gene set enrichment analysis (GSEA) were utilized to identify independent prognostic factors and RRAGB related pathways, respectively. Relationships between RRAGB and immunity were also analyzed. Boxplot and K-M survival analysis indicated that RRAGB was not only differently expressed in COAD (P < 0.05), but also significantly associated with overall survival (OS; P < 0.05). Univariate and multivariate Cox hazard regression analyses indicated that RRAGB could serve as an independent prognostic factor for COAD (both P < 0.05). GSEA identified five signaling pathways significantly enriched in the high-RRAGB expression phenotype. Moreover, a RRAGB-based nomogram was successfully constructed and displayed a satisfactory performance. In addition, RRAGB expression was found to be significantly associated with microsatellite instability (MSI), tumor mutational burden (TMB) and immunity. Our results revealed that RRAGB could be a prognostic biomarker for COAD in terms of OS and markedly related to MSI, TMB, and immunity. We also constructed an RRAGB-based nomogram with a satisfactory performance. Further researches should be carried out to validate our findings.