Prognostic significance of IFITM1 expression and correlation with microvessel density and epithelial-mesenchymal transition signature in lung adenocarcinoma

Role of interferon-induced transmembrane protein family in cancer progression: a special focus on pancreatic cancer

Human interferon-induced transmembrane protein family (IFITMs) consists of five main proteins. IFITM1, IFITM2, and IFITM3 can be induced by interferon, while IFITM5 and IFITM10 are insensitive to interferon. IFITMs has various functions, including well-researched antiviral effects. As a molecule whose expression is significantly increased by interferon in the immune microenvironment, IFITMs has drawn growing interest in recent years for their role in the cancer progression. Unlike antiviral effects, the role and mechanism of IFITMs in cancer progression have not been clearly studied, especially the role and molecular mechanism of IFITMs in pancreatic cancer are rarely reported in the literature. This article focuses on the role and potential mechanism of IFITMs in pancreatic cancer progression by analyzing the function and mechanism of IFITM1-3 in other cancers and conducting bioinformatics analysis using the databases, so as to provide a new target for pancreatic cancer therapy.

Invasive FoxM1 phosphorylated by PLK1 induces the polarization of tumor-associated macrophages to promote immune escape and metastasis, amplified by IFITM1

BACKGROUND

Understanding the mechanism behind immune cell plasticity in cancer metastasis is crucial for identifying key regulators. Previously we found that mitotic factors regulate epithelial-mesenchymal transition, but how these factors convert to metastatic players in the tumor microenvironment (TME) is not fully understood.

METHODS

The clinical importance of mitotic factors was analyzed by heatmap analysis, a KM plot, and immunohistochemistry in lung adenocarcinoma (LUAD) patients. Immunoprecipitation, LC-MS/MS, kinase assay, and site-directed mutagenesis were performed for the interaction and phosphorylation. A tail-vein injection mouse model, Transwell-based 3D culture, microarray analysis, coculture with monocytes, and chromatin immunoprecipitation assays were used to elucidate the function of phosphorylated FoxM1 in metastasis of TME.

RESULTS

The phosphorylated FoxM1 at Ser25 by PLK1 acquires the reprogramming ability to stimulate the invasive traits in cancer and influence immune cell plasticity. This invasive form of p-FoxM1 upregulates the expression of IL1A/1B, VEGFA, and IL6 by direct activation, recruiting monocytes and promoting the polarization of M2d-like tumor-associated macrophages (TAMs). Upregulation of PD-L1 in LUAD having phosphomimetic FoxM1 facilitates immune evasion. In invasive LUAD with phosphomimetic FoxM1, IFITM1 is the most highly expressed through the activation of the STING-TBK1-IRF3 signaling, which enhances FoxM1-mediated signaling. Clinically, higher expression of FOXM1, PLK1, and IFITM1 is inversely correlated with the survival rate of advanced LUAD patients, providing a promising therapeutic strategy for the treatment of LUAD.

CONCLUSION

FoxM1-based therapy would be a potential therapeutic strategy for LUAD to reduce TAM polarization, immune escape, and metastasis, since FoxM1 functions as a genetic reprogramming factor reinforcing LUAD malignancy in the TME.

Risk prediction for dermatomyositis-associated hepatocellular carcinoma

OBJECTIVE

To explore dermatomyositis signature genes as potential biomarkers of hepatocellular carcinoma and their associated molecular regulatory mechanisms.

METHODS

Based on the mRNA-Seq data of dermatomyositis and hepatocellular carcinoma in public databases, five dermatomyositis signature genes were screened by LASSO regression analysis and support vector machine (SVM) algorithm, and their biological functions in dermatomyositis with hepatocellular carcinoma were investigated, and a nomogram risk prediction model for hepatocellular carcinoma was constructed and its predictive efficiency was initially evaluated. The immune profile in hepatocellular carcinoma was examined based on the CIBERSORT and ssGSEA algorithms, and the correlation between five dermatomyositis signature genes and tumor immune cell infiltration and immune checkpoints in hepatocellular carcinoma was investigated.

RESULTS

The expression levels of five dermatomyositis signature genes were significantly altered in hepatocellular carcinoma and showed good diagnostic efficacy for hepatocellular carcinoma, suggesting that they may be potential predictive targets for hepatocellular carcinoma, and the risk prediction model based on five dermatomyositis signature genes showed good risk prediction efficacy for hepatocellular carcinoma and has good potential for clinical application. In addition, we also found that the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through integrin-mediated activation, which in turn regulates the development and progression of hepatocellular carcinoma.

CONCLUSION

LY6E, IFITM1, GADD45A, MT1M, and SPP1 are potential predictive targets for new-onset hepatocellular carcinoma in patients with dermatomyositis, and the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through the mediation of integrins to promote the development and progression of hepatocellular carcinoma.

Integrated bioinformatics analysis of IFITM1 as a prognostic biomarker and investigation of its immunological role in prostate adenocarcinoma

Introduction

Prostate adenocarcinoma (PRAD) is a highly aggressive malignancy with high mortality and poor prognosis, and its potential mechanism remains unclear. Our study aimed to identify novel markers for the prognosis of PRAD using bioinformatics technology.

Methods

The GSE32571 dataset was downloaded from the GEO database, and analyzed via the limma R package to identify differentially expressed genes (DEGs) and differentially expressed immune score-related genes (DEISRGs). The immune-related genes (IRGs) were further obtained by overlapping DEISRGs and DEGs, and the core gene was identified via survival analysis. Furthermore, the expression level, prognostic value, and potential functions of the core gene were evaluated via multiple bioinformatics databases.

Results

A total of 301 IRGs were identified from the GSE32571 dataset, and IFITM1 was a down-regulated gene in several types of cancer, including PRAD. Besides, low expression of IFITM1 was associated with a poor prognosis in PRAD. GSEA indicated that the vital pathways of IFITM1-associated genes were mainly enriched in primary immunodeficiency, Th17 cell differentiation, Th1, and Th2 cell differentiation, natural killer cell-mediated cytotoxicity, myeloid dendritic cell activation, regulation of leukocyte activation, etc. Furthermore, IFITM1 was closely correlated with 22 types of tumor-infiltrating immune cells.

Discussion

IFITM1 was a prognostic biomarker for PRAD patients, and it can be acted as a potential immune therapy target in PRAD.

IFITM protein regulation and functions: Far beyond the fight against viruses

Interferons (IFNs) are important cytokines that regulate immune responses through the activation of hundreds of genes, including interferon-induced transmembrane proteins (IFITMs). This evolutionarily conserved protein family includes five functionally active homologs in humans. Despite the high sequence homology, IFITMs vary in expression, subcellular localization and function. The initially described adhesive and antiproliferative or pro-oncogenic functions of IFITM proteins were diluted by the discovery of their antiviral properties. The large set of viruses that is inhibited by these proteins is constantly expanding, as are the possible mechanisms of action. In addition to their beneficial antiviral effects, IFITM proteins are often upregulated in a broad spectrum of cancers. IFITM proteins have been linked to most hallmarks of cancer, including tumor cell proliferation, therapeutic resistance, angiogenesis, invasion, and metastasis. Recent studies have described the involvement of IFITM proteins in antitumor immunity. This review summarizes various levels of IFITM protein regulation and the physiological and pathological functions of these proteins, with an emphasis on tumorigenesis and antitumor immunity.

Comprehensive analysis to identify GNG7 as a prognostic biomarker in lung adenocarcinoma correlating with immune infiltrates

Background: G Protein Subunit Gamma 7 (GNG7), an important regulator of cell proliferation and cell apoptosis, has been reported to be downregulated in a variety of tumors including lung adenocarcinoma (LUAD). However, the correlation between low expression of GNG7 and prognosis of LUAD as well as the immune infiltrates of LUAD remains unclear.

Methods: The samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). R software was performed for statistical analysis. GNG7 expression and its prognostic value in LUAD were assessed through statistically analyzing the data from different databases. A nomogram was constructed to predict the impact of GNG7 on prognosis. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analyses GSEA (ssGSEA) were employed to determine the potential signal pathways and evaluated the immune cell infiltration regulated by GNG7. The prognostic significance of GNG7 expression associated with immune cell infiltration was investigated using the Tumor Immune Estimation Resource 2.0 (TIMER2.0) and the Kaplan-Meier plotter database. The UALCAN, cBio Cancer Genomics Portal (cBioPortal) and MethSurv database were used to analyze the correlation between the methylation of GNG7 and its mRNA expression as well as prognostic significance.

Results: GNG7 was demonstrated to be down-regulated in LUAD and its low expression was associated with poor prognosis. A clinical reliable prognostic-predictive model was constructed. Pathway enrichment showed that GNG7 was highly related to the B cell receptor signaling pathway. Further analysis showed that GNG7 was positively associated with B cell infiltration and low levels of B cell infiltration tended to associate with worse prognosis in patients with low GNG7 expression. Moreover, methylation analysis suggested hypermethylation may contribute to the low expression of GNG7 in LUAD.

Conclusion: Decreased expression of GNG7 at least partly caused by hypermethylation of the GNG7 promoter is closely associated with poor prognosis and tumor immune cell infiltration (especially B cells) in LUAD. These results suggest that GNG7 may be a promising prognostic biomarker and a potential immunotherapeutic target for LUAD, which provides new insights into immunotherapy for LUAD.

Comprehensive Analysis of Ferroptosis- and Immune-Related Signatures to Improve the Prognosis and Diagnosis of Kidney Renal Clear Cell Carcinoma

Background

Almost 40% of patients with kidney renal clear cell carcinoma (KIRC) with advanced cancers eventually develop to metastases, and their 5-year survival rates are approximately 10%. Aberrant DNA methylations are significantly associated with the development of KIRC. The aim of our present study was to identify suitable ferroptosis- and immune-related (FI) biomarkers correlated with aberrant methylations to improve the prognosis and diagnosis of KIRC.

Methods

ChAMP and DESeq2 in R (3.6.2) were used to screen the differentially expressed methylation probes and differentially expressed genes, respectively. Univariate and multivariate Cox regression were used to identify the overall survival (OS)-related biomarkers.

Results

We finally identified five FI biomarkers (CCR4, CMTM3, IFITM1, MX2, and NR3C2) that were independently correlated with the OS of KIRC. The area under the curve value of the receiver operating characteristic value of prognosis model was 0.74, 0.68, and 0.72 in the training, validation, and entire cohorts, respectively. The sensitivity and specificity of the diagnosis model were 0.8698 and 0.9722, respectively. In addition, the prognosis model was also significantly correlated with several immune cells and factors.

Conclusion

Our present study suggested that these five FI-DEGs (CCR4, CMTM3, IFITM1, MX2, and NR3C2) could be used as prognosis and diagnosis biomarkers for patients with KIRC, but further cross-validation clinical studies are still needed to confirm them.

Development and Validation of a Combined Glycolysis and Immune Prognostic Model for Melanoma

Background

Glycolytic effects and immune microenvironments play important roles in the development of melanoma. However, reliable biomarkers for prognostic prediction of melanoma as based on glycolysis and immune status remain to be identified.

Methods

Glycolysis-related genes (GRGs) were obtained from the Molecular Signatures database and immune-related genes (IRGs) were downloaded from the ImmPort dataset. Prognostic GRGs and IRGs in the TCGA (The Cancer Genome Atlas) and GSE65904 datasets were identified. Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression were used for model construction. Glycolysis expression profiles and the infiltration of immune cells were analyzed and compared. Finally, in vitro experiments were performed to assess the expression and function of these CIGI genes.

Results

Four prognostic glycolysis- and immune-related signatures (SEMA4D, IFITM1, KIF20A and GPR87) were identified for use in constructing a comprehensive glycolysis and immune (CIGI) model. CIGI proved to be a stable, predictive method as determined from different datasets and subgroups of patients and served as an independent prognostic factor for melanoma patients. In addition, patients in the high-CIGI group showed increased levels of glycolytic gene expressions and exhibited immune-suppressive features. Finally, SEMA4D and IFITM1 may function as tumor suppressor genes, while KIF20A and GPR87 may function as oncogenes in melanoma as revealed from results of in vitro experiments.

Conclusion

In this report we present our findings on the development and validation of a novel prognostic classifier for use in patients with melanoma as based on glycolysis and immune expression profiles.

Deciphering the Roles of IFITM1 in Tumors

Interferon (IFN)-induced transmembrane protein 1 (IFITM1), a member of the IFN-induced transmembrane protein family, is reported to be highly expressed in tumor tissues as well as cancer cell lines, and it is an independent prognostic biomarker for patients with certain tumor types, such as gallbladder carcinoma, esophageal adenocarcinoma, colorectal cancer, and gastric cancer. Moreover, overexpression of IFITM1 promotes tumor cell proliferation, invasion, metastasis, angiogenesis, and therapeutic resistance, including endocrine therapy, chemotherapy, and radiotherapy resistance. Due to these diverse functions of IFITM1 in tumors, targeting IFITM1 may provide a novel strategy for cancer treatment and be highly desirable to improve cancer patient outcomes. Herein, we decipher the role of IFITM1 in cancer in detail.

Development of an Oncogenic Driver Alteration Associated Immune-Related Prognostic Model for Stage I-II Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) needs to be stratified for its heterogeneity. Oncogenic driver alterations such as EGFR mutation, ALK translocation, ROS1 translocation, and BRAF mutation predict response to treatment for LUAD. Since oncogenic driver alterations may modulate immune response in tumor microenvironment that may influence prognosis in LUAD, the effects of EGFR, ALK, ROS1, and BRAF alterations on tumor microenvironment remain unclear. Immune-related prognostic model associated with oncogenic driver alterations is needed. In this study, we performed the Cox-proportional Hazards Analysis based on the L1-penalized (LASSO) Analysis to establish an immune-related prognostic model (IPM) in stage I-II LUAD patients, which was based on 3 immune-related genes (PDE4B, RIPK2, and IFITM1) significantly enriched in patients without EGFR, ALK, ROS1, and BRAF alterations in The Cancer Genome Atlas (TCGA) database. Then, patients were categorized into high-risk and low-risk groups individually according to the IPM defined risk score. The predicting ability of the IPM was validated in GSE31210 and GSE26939 downloaded from the Gene Expression Omnibus (GEO) database. High-risk was significantly associated with lower overall survival (OS) rates in 3 independent stage I-II LUAD cohorts (all P < 0.05). Moreover, the IPM defined risk independently predicted OS for patients in TCGA stage I-II LUAD cohort (P = 0.011). High-risk group had significantly higher proportions of macrophages M1 and activated mast cells but lower proportions of memory B cells, resting CD4 memory T cells and resting mast cells than low-risk group (all P < 0.05). In addition, the high-risk group had a significantly lower expression of CTLA-4, PDCD1, HAVCR2, and TIGIT than the low-risk group (all P < 0.05). In summary, we established a novel IPM that could provide new biomarkers for risk stratification of stage I-II LUAD patients.

Development and validation of a 4-gene combination for the prognostication in lung adenocarcinoma patients

Objective: To identify a multi-gene prognostic factor in patients with lung adenocarcinoma (LUAD).

Materials and methods Prognosis-related genes were screened in the TCGA-LUAD cohort. Then, patients in this cohort were randomly separated into training set and test set. Least absolute shrinkage and selection operator (LASSO) regression was performed to the penalized the Cox proportional hazards regression (CPH) model on the training set, and a prognostication combination based on the result of LASSO analysis was developed. By performing Kaplan-Meier curve analysis, univariate and multivariable CPH model on the overall survival (OS) as well as recurrence free survival (RFS), the prognostication performance of the multigene combination were evaluated. Moreover, we constructed a nomogram and performed decision curve analysis to evaluate the clinical application of the multigene combination.

Results We obtained 99 prognosis-related genes and screened out a 4-gene combination (including CIDEC, ZFP3, DKK1, and USP4) according to the LASSO analysis. The results of survival analyses suggested that patients in the 4-gene combination low-risk group had better OS and RFS than those in the 4-gene combination high-risk group. The 4-gene mentioned was demonstrated to be independent prognostic factor of patients with LUAD in the training set(OS, HR=11.962, P<0.001; RFS, HR=9.281, P<0.001) and test set (OS, HR=5.377, P=0.003; RFS, HR=2.949, P=0.104). More importantly, its prognosis performance was well in the validation set (OS, HR=0.955, P=0.002; RFS, HR=1.042, P<0.001).

Conclusions We introduced a 4-gene combination which could predict the survival of LUAD patients and might be an independent prognostic factor in LUAD.