Characterization of the relationship between FLI1 and immune infiltrate level in tumour immune microenvironment for breast cancer

Integrated analysis reveals FLI1 regulates the tumor immune microenvironment via its cell-type-specific expression and transcriptional regulation of distinct target genes of immune cells in breast cancer

BACKGROUND

Immunotherapy is a practical therapeutic approach in breast cancer (BRCA), and the role of FLI1 in immune regulation has gradually been unveiled. However, the specific role of FLI1 in BRCA was conflicted; thus, additional convincing evidence is needed.

METHODS

We explored the upstream regulation of FLI1 expression via summary data-based Mendelian randomization (SMR) analysis and ncRNA network construction centering on FLI1 using BRCA genome-wide association study (GWAS) summary data with expression quantitative trait loci (eQTLs) and DNA methylation quantitative trait loci (mQTLs) from the blood and a series of in silico analyses, respectively. We illuminated the downstream function of FLI1 in immune regulation by integrating a series of analyses of single-cell RNA sequence data (scRNA-seq).

RESULTS

We verified a causal pathway from FLI1 methylation to FLI1 gene expression to BRCA onset and demonstrated that FLI1 was downregulated in BRCA. FLI1, a transcription factor, served as myeloid and T cells' communication regulator by targeting immune-related ligands and receptor transcription in BRCA tissues. We constructed a ceRNA network centering on FLI1 that consisted of three LncRNAs (CKMT2-AS1, PSMA3-AS1, and DIO3OS) and a miRNA (hsa-miR-324-5p), and the expression of FLI1 was positively related to a series of immune-related markers, including immune cell infiltration, biomarkers of immune cells, and immune checkpoints.

CONCLUSION

Low-methylation-induced or ncRNA-mediated downregulation of FLI1 is associated with poor prognosis, and FLI1 might regulate the tumor immune microenvironment via a cell-type-specific target genes manner in BRCA.

Identification of Mir-182-3p/FLI-1 Axis as a Key Signaling in Immune Response in Cervical Cancer: A Comprehensive Bioinformatic Analysis

miRNAs modulate gene expression and play critical functions as oncomiRs or tumor suppressors. The miR-182-3p is important in chemoresistance and cancer progression in breast, lung, osteosarcoma, and ovarian cancer. However, the role of miR-182-3p in cervical cancer (CC) has not been elucidated.

AIM

To analyze the role of miR-182-3p in CC through a comprehensive bioinformatic analysis.

METHODS

Gene Expression Omnibus (GEO) databases were used for the expression analysis. The mRNA targets of miR-182-3p were identified using miRDB, TargetScanHuman, and miRPathDB. The prediction of island CpG was performed using the MethPrimer program. The transcription factor binding sites in the FLI-1 promoter were identified using ConSite+, Alibaba2, and ALGGEN-PROMO. The protein-protein interaction (PPI) analysis was performed in STRING 11.5.

RESULTS

miR-182-3p was significantly overexpressed in CC patients and has potential as a diagnostic. We identified 330 targets of miR-182-3p including FLI-1, which downregulates its expression in CC. Additionally, the aberrant methylation of the FLI-1 promoter and Ap2a transcription factor could be involved in downregulating FLI1 expression. Finally, we found that FLI-1 is a possible key gene in the immune response in CC.

CONCLUSIONS

The miR-182-3p/FLI-1 axis plays a critical role in immune response in CC.

Identification of Novel m6A-Related Long Non-Coding RNA Signatures for Cholangiocarcinoma Using Integrated Bioinformatics Analyses

Traditional methods used to treat cholangiocarcinoma are less effective, and the identification of new CHOL signature genes can help in the early clinical diagnosis and intervention of cholangiocarcinoma. In this work, we used integrated bioinformatics analysis to find new m6a-associated lncRNA signatures in cholangiocarcinoma. Pearson correlation test was used to identify m6A-lncRNAs by co-expression analysis of m6A-mrna and lncRNAs. we then selected m6A-lncRNAs co-expressed with METTL3 and METTL14 genes and screened for DEm6A-lncRNAs by comparing expression differences. we then used R package of Spearman coefficient correlation analysis to investigate the relevance of m6A-lncrna expression in CHOL. To determine the relative levels of immune cell infiltration, we performed ssGSEA analysis on all samples using the R package, and then we used graphs to illustrate the differences in immune cell infiltration between the CHOL and NC groups. The results of this study will help to identify new CHOL-causing biosignatures, which are important for the early clinical detection and management of CHOL.

Transcription factor Fli-1 as a new target for antitumor drug development

The transcription factor Friend leukemia virus integration 1 (Fli-1) belonging to the E26 Transformation-Specific (ETS) transcription factor family is not only expressed in normal cells such as hematopoietic stem cells and vascular endothelial cells, but also abnormally expressed in various malignant tumors including Ewing sarcoma, Merkel cell sarcoma, small cell lung carcinoma, benign or malignant hemangioma, squamous cell carcinoma, adenocarcinoma, bladder cancer, leukemia, and lymphoma. Fli-1 binds to the promoter or enhancer of the target genes and participates in a variety of physiological and pathological processes of tumor cells, including cell growth, proliferation, differentiation, and apoptosis. The expression of Fli-1 gene is related to the specific biological functions and characteristics of the tissue in which it is located. In tumor research, Fli-1 gene is used as a specific marker for the occurrence, metastasis, efficacy, and prognosis of tumors, thus, a potential new target for tumor diagnosis and treatment. These studies indicated that Fli-1 may be a specific candidate for antitumor drug development. Recent studies identified small molecules regulating Fli-1 thanks to our screened strategy of natural products and their derivatives. Therefore, in this review, the advanced research on Fli-1 as a target for antitumor drug development is analyzed in different cancers. The inhibitors and agonists of Fli-1 that regulate its expression are introduced and their clinical applications in the treatment of cancer, thus providing new therapeutic strategies.

Tumor-Associated Macrophages: Critical Players in Drug Resistance of Breast Cancer

Drug resistance is one of the most critical challenges in breast cancer (BC) treatment. The occurrence and development of drug resistance are closely related to the tumor immune microenvironment (TIME). Tumor-associated macrophages (TAMs), the most important immune cells in TIME, are essential for drug resistance in BC treatment. In this article, we summarize the effects of TAMs on the resistance of various drugs in endocrine therapy, chemotherapy, targeted therapy, and immunotherapy, and their underlying mechanisms. Based on the current overview of the key role of TAMs in drug resistance, we discuss the potential possibility for targeting TAMs to reduce drug resistance in BC treatment, By inhibiting the recruitment of TAMs, depleting the number of TAMs, regulating the polarization of TAMs and enhancing the phagocytosis of TAMs. Evidences in our review support it is important to develop novel therapeutic strategies to target TAMs in BC to overcome the treatment of resistance.

Identify DNA-Binding Proteins Through the Extreme Gradient Boosting Algorithm

The exploration of DNA-binding proteins (DBPs) is an important aspect of studying biological life activities. Research on life activities requires the support of scientific research results on DBPs. The decline in many life activities is closely related to DBPs. Generally, the detection method for identifying DBPs is achieved through biochemical experiments. This method is inefficient and requires considerable manpower, material resources and time. At present, several computational approaches have been developed to detect DBPs, among which machine learning (ML) algorithm-based computational techniques have shown excellent performance. In our experiments, our method uses fewer features and simpler recognition methods than other methods and simultaneously obtains satisfactory results. First, we use six feature extraction methods to extract sequence features from the same group of DBPs. Then, this feature information is spliced together, and the data are standardized. Finally, the extreme gradient boosting (XGBoost) model is used to construct an effective predictive model. Compared with other excellent methods, our proposed method has achieved better results. The accuracy achieved by our method is 78.26% for PDB2272 and 85.48% for PDB186. The accuracy of the experimental results achieved by our strategy is similar to that of previous detection methods.

Characterized the diversity of ABCB1 subtypes in immunogenomic landscape for predicting the drug response in breast cancer

ABCB1 is an important gene that closely related to analgesic tolerance to opioids, and plays an important role in their postoperative treatment. Recent studies have demonstrated that ABCB1 genotype is significantly associated with the chemico-resistance and chemical sensitivity in breast cancer patients. So, it is become very important to investigate the important role of ABCB1 for predicting drug response in breast cancer patients. In this study, by conducting the Cox proportional hazards regression analysis in breast cancer patients, significant differences were found in prognosis between the ABCB1 high- and low-expression subtypes. Meanwhile, by using immune infiltration profiles as well as transcriptomics datasets, the ABCB1 high subtype was found to be significantly enriched in many immune-related KEGG pathways and biological processes, and was characterized by the high infiltration levels of immune cell types. Furthermore, bioinformatics inference revealed that the ABCB1 subtypes were associated with the therapeutic effect of immunotherapy, which would be important for patient prognosis. In conclusion, these findings may provide useful help for recognizing the diversity between ABCB1 subtypes in tumor immune microenvironment, and may unravel prognosis outcomes and immunotherapy utility for ABCB1 in breast cancer.

MRPL13 Promotes Tumor Cell Proliferation, Migration and EMT Process in Breast Cancer Through the PI3K-AKT-mTOR Pathway

Purpose

Breast cancer (BC), with varying histopathology, biology and response to systemic treatment, is the second leading cause of cancer-related mortality. Previous studies have inferred that the expression of mitochondrial ribosomal proteins (MRPs) is possibly related to the occurrence/progression of BC. MRPL13 might be one of the potential MRP candidates that are involved in BC tumorigenesis, but its role in BC has rarely been reported. The purpose of the current study was to evaluate the prognostic significance of MRPL13, as well as to explore its potential biological functions in BC.

Materials and Methods

A series of bioinformatic and statistical methods were adopted to assess the MRPL13 expression profile, its relationship with clinicopathological characteristics, copy number variation (CNV), impact on clinical outcomes and relevant functions. All the results are analysed by 1097 BC patients collected from The Cancer Genome Atlas (TCGA) dataset and 52 clinical samples for immunohistochemistry (IHC) assay.

Results

The results demonstrated that the expression of MRPL13 in BC tissues was remarkably elevated than that in normal breast tissues. In addition, the Kaplan-Meier curves and Cox model indicated that patients with high MRPL13 expression were connected to a worse prognosis, heralding the independent prognostic value of this protein in BC. Moreover, an enrichment analysis showed that MRPL13 was mainly involved in cell cycle/division-related, RNA processing (degradation/splicing), MYC targets and the MTORC1 pathways. In addition, RNA interference (RNAi)-mediated MRPL13 silencing remarkedly inhibited proliferation and migration as well as the expression of EMT-related genes of BC cells in vitro. Mechanistically, attenuation of MRPL13 significantly suppressed the phosphorylation of AKT and mTOR, which could be partially abolished by 740Y-P (a PI3K agonist).

Conclusion

Our results provide evidence for the first time that increased MRPL13 expression correlates with adverse clinicopathological variables and unfavorable clinical outcomes of BC patients. Knockdown of MRPL13 restrains the proliferation and migration potential and EMT process of BC through inhibiting PI3K/AKT/mTOR signaling pathway.

Preeclampsia: Cardiotonic Steroids, Fibrosis, Fli1 and Hint to Carcinogenesis

Despite prophylaxis and attempts to select a therapy, the frequency of preeclampsia does not decrease and it still takes the leading position in the structure of maternal mortality and morbidity worldwide. In this review, we present a new theory of the etiology and pathogenesis of preeclampsia that is based on the interaction of Na/K-ATPase and its endogenous ligands including marinobufagenin. The signaling pathway of marinobufagenin involves an inhibition of transcriptional factor Fli1, a negative regulator of collagen synthesis, followed by the deposition of collagen in the vascular tissues and altered vascular functions. Moreover, in vitro and in vivo neutralization of marinobufagenin is associated with the restoration of Fli1. The inverse relationship between marinobufagenin and Fli1 opens new possibilities in the treatment of cancer; as Fli1 is a proto-oncogene, a hypothesis on the suppression of Fli1 by cardiotonic steroids as a potential anti-tumor therapeutic strategy is discussed as well. We propose a novel therapy of preeclampsia that is based on immunoneutralization of the marinobufagenin by monoclonal antibodies, which is capable of impairing marinobufagenin-Na/K-ATPase interactions.

eHSCPr discriminating the cell identity involved in endothelial to hematopoietic transition

MOTIVATION

Hematopoietic stem cells (HSCs) give rise to all blood cells and play a vital role throughout the whole lifespan through their pluripotency and self-renewal properties. Accurately identifying the stages of early HSCs is extremely important, as it may open up new prospects for extracorporeal blood research. Existing experimental techniques for identifying the early stages of HSCs development are time-consuming and expensive. Machine learning has shown its excellence in massive single-cell data processing and it is desirable to develop related computational models as good complements to experimental techniques.

RESULTS

In this study, we presented a novel predictor called eHSCPr specifically for predicting the early stages of HSCs development. To reveal the distinct genes at each developmental stage of HSCs, we compared F-score with three state-of-art differential gene selection methods (limma, DESeq2, edgeR) and evaluated their performance. F-score captured the more critical surface markers of endothelial cells and hematopoietic cells, and the area under receiver operating characteristic curve (ROC) value was 0.987. Based on SVM, the 10-fold cross-validation accuracy of eHSCpr in the independent dataset and the training dataset reached 94.84% and 94.19%, respectively. Importantly, we performed transcription analysis on the F-score gene set, which indeed further enriched the signal markers of HSCs development stages. eHSCPr can be a powerful tool for predicting early stages of HSCs development, facilitating hypothesis-driven experimental design and providing crucial clues for the in vitro blood regeneration studies.

AVAILABILITY

http://bioinfor.imu.edu.cn/ehscpr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterization of the relationship between FLI1 and immune infiltrate level in tumour immune microenvironment for breast cancer

Breast cancer is the most common cancer and the leading cause of cancer death among women in the world. Tumour‐infiltrating lymphocytes were defined as the white blood cells left in the vasculature and localized in tumours. Recently, tumour‐infiltrating lymphocytes were found to be associated with good prognosis and response to immunotherapy in tumours. In this study, to examine the influence of FLI1 in immune system in breast cancer, we interrogated the relationship between the FLI1 expression levels with infiltration levels of 28 immune cell types. By splitting the breast cancer samples into high and low expression FLI1 subtypes, we found that the high expression FLI1 subtype was enriched in many immune cell types, and the up‐regulated differentially expressed genes between them were enriched in immune system processes, immune‐related KEGG pathways and biological processes. In addition, many important immune‐related features were found to be positively correlated with the FLI1 expression level. Furthermore, we found that the FLI1 was correlated with the immune‐related genes. Our findings may provide useful help for recognizing the relationship between tumour immune microenvironment and FLI1, and may unravel clinical outcomes and immunotherapy utility for FLI1 in breast cancer.