Microarray data analysis reveals gene expression changes in response to ionizing radiation in MCF7 human breast cancer cells

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer

Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.

ESCO2 promotes hypopharyngeal carcinoma progression in a STAT1-dependent manner

BACKGROUND

The establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2) is involved in the development of multiple malignancies. However, its role in hypopharyngeal carcinoma (HPC) progression remains uncharacterized.

METHODS

This study employed bioinformatics to determine the ESCO2 expression in head and neck squamous cell carcinoma (HNSC) and normal tissues. In vitro cell proliferation, migration, apoptosis, and/or cell cycle distribution assays were used to determine the function of ESCO2 and its relationship with STAT1. Xenograft models were established in nude mice to determine ESCO2 in HPC growth in vivo. Co-immunoprecipitation/mass spectrometry (Co-IP/MS) was conducted to identify the potential ESCO2 binding partners.

RESULTS

We found that ESCO2 expression was elevated in HNSC tissues, and ESCO2 depletion suppressed tumor cell migration in vitro and inhibited tumor growth in vitro and in vivo. Co-IP/MS and immunoblotting assays revealed the interaction between ESCO2 and STAT1 in HPC cells. STAT1-overexpression compromised ESCO2-mediated suppressive effects on HPC cell proliferation, viability, and migration.

CONCLUSIONS

These findings suggest that ESCO2 is crucial in promoting HPC malignant progression through the STAT1 pathway and provides novel therapeutic targets for HPC treatment.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

Silencing effects of FOXD1 inhibit metastatic potentials of the PCa via N-cadherin - Wnt/β-catenin crosstalk

The elucidation of the mechanisms controlling the metastatic processes is important for the development of new treatment methods to prevent the progression of localized disease to metastasis. Forkhead box D1 (FOXD1) is a member of the FOX transcription factor family and has been reported to play an important role in the development and progression of various cancers. However, its role in prostate cancer (PCa) remains only partially understood. Therefore, we aimed to explore the effects on the associated regulatory signal pathway of FOXD1 in prostate cancer. To clarify the roles of FOXD1 in prostate cancer, we used siRNA to suppress its expression in 22Rv1 cells with relatively higher expression of FOXD1. The effects of FOXD1 silencing on cell proliferation, migration and invasion were determined. WST-1 assays were used to determine cell proliferation. Cell migration and invasion were evaluated through wound healing and transwell assays. The possible underlying mechanism of FOXD1 silencing on 22Rv1 was evaluated by determining the expression of proteins related to EMT and Wnt/β-catenin signaling pathway. Our results showed that FOXD1 was highly expressed in prostate cancer cell lines -PC-3, DU145, LNCaP and 22Rv1- compared to normal prostate epithelial cell line RWPE-1. Additionally, silencing of FOXD1 significantly reduced proliferation, migration and invasion of 22Rv1 cells. Furthermore, silencing of FOXD1 decreased the expression of β-catenin and cyclin D1, which are involved in the Wnt/β-catenin signaling pathway. However, it did not appear to affect the expression of EMT-related proteins other than N-cadherin. Our results suggest that silencing of FOXD1 suppresses metastatic potentials of the PCa via N-cadherin - Wnt/β-catenin crosstalk. Therefore, the expression status of FOXD1 may be a new prognostic factor as well as a potential therapeutic target in prostate cancer treatment.

FOXD1 promotes EMT and cell stemness of oral squamous cell carcinoma by transcriptional activation of SNAI2

Background

Epithelial-mesenchymal transition (EMT) and cell stemness are implicated in the initiation and progression of oral squamous cell carcinoma (OSCC). Revealing the intrinsic regulatory mechanism may provide effective therapeutic targets for OSCC.

Results

In this study, we found that Forkhead box D1 (FOXD1) was upregulated in OSCC compared with normal samples. Patients with a higher FOXD1 expression had a poorer overall survival and disease-free survival. Immunohistochemical staining results showed that FOXD1 expression was related to the clinical stage and relapse status of OSCC patients. When FOXD1 expression was knocked down in CAL27 and SCC25 cells, the migration, invasion, colony formation, sphere formation, and proliferation abilities decreased. Moreover, EMT and stemness-related markers changed remarkably, which indicated that the EMT process and cell stemness were inhibited. Conversely, overexpression of FOXD1 promoted EMT and cell stemness. Further study demonstrated that FOXD1 could bind to the promoter region and activate the transcription of SNAI2. In turn, the elevated SNAI2 affected EMT and cell stemness. An in vivo study showed that FOXD1-overexpressing CAL27 cells possessed a stronger tumorigenic ability.

Conclusions

Our findings revealed a novel mechanism in regulating EMT and cell stemness and proposed FOXD1 as a potential marker for the diagnosis and treatment of OSCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-021-00671-9.

Investigation of Candidate Genes and Pathways in Basal/TNBC Patients by Integrated Analysis

PURPOSE

This study aims to identify the key pathway and related genes and to further explore the potential molecular mechanisms of triple negative breast cancer (TNBC).

METHODS

The transcriptome data and clinical information of breast cancer patients were downloaded from the TCGA database, including 94 cases of paracancerous tissue, 225 cases of Basal like type, 151 cases of Her2 type, 318 cases of Luminal type A, 281 cases of Luminal type B, and 89 cases of Normal Like type. The differentially expressed genes (DEGs) were identified based on the criteria of |logFC|≥1.5 and adjust P < 0.001.Their functions were annotated by gene ontology (GO) analysis and Kyoto Encyclopedia of differentially expressed genes & Genomes (KEGG) pathway analysis. Cox regression univariate analysis and Kaplan-Meier survival curves (Log-rank method) were used for survival analysis. FOXD1, DLL3 and LY6D were silenced in breast cancer cell lines, and cell viability was assessed by CCK-8 assay. Further, the expression of FOXD1, DLL3 and LY6D were explored by immunohistochemistry on triple negative breast tumor tissue and normal breast tissue.

RESULTS

A total of 533 DEGs were identified. Functional annotation showed that DEGs were significantly enriched in intermediate filament cytoskeleton, DNA-binding transcription activator activity, epidermis development, and Neuroactive ligand-receptor interaction. Survival analysis found that FOXD1, DLL3, and LY6D showed significant correlation with the prognosis of patients with the Basal-like type (P < 0.05). CCK-8 assay showed that compared with Doxorubicin alone group, the cytotoxicity of Doxorubicin combined with siRNA-knockdown of FOXD1, DLL3, or LY6D was much significant.

CONCLUSION

The DEGs and their enriched functions and pathways identified in this study contribute to the understanding of the molecular mechanisms of TNBC. In addition, FOXD1, DLL3, and LY6D may be defined as the prognostic markers and potential therapeutic targets for TNBC patients.