SIPA1 enhances SMAD2/3 expression to maintain stem cell features in breast cancer cells

A novel transcription factor SIPA1: identification and verification in triple-negative breast cancer

Transcription factors (TFs) regulate the expression of genes responsible for cell growth, differentiation, and responses to environmental factors. In this study, we demonstrated that signal-induced proliferation-associated 1 (SIPA1), known as a Rap-GTPase-activating protein, bound DNA and served as a TF. Importin β1 was found to interact with SIPA1 upon fibronectin treatment. A TGAGTCAB motif was recognized and bound by DNA-binding region (DBR) of SIPA1, which was confirmed by electrophoretic mobility shift assay. SIPA1 regulated the transcription of multiple genes responsible for signal transduction, DNA synthesis, cell adhesion, cell migration, and so on. Transcription of fibronectin 1, which is crucial for cell junction and migration of triple-negative breast cancer (TNBC) cells, was regulated by SIPA1 in a DBR-dependent manner both in vivo and in vitro. Furthermore, single-cell transcriptome sequencing analysis of specimens from a metastatic TNBC patient revealed that SIPA1 was highly expressed in metastatic TNBC. Hence, this study demonstrated that SIPA1 served as a TF, promoting TNBC migration, invasion, and metastasis.

The Orphan GPR50 Receptor Regulates the Aggressiveness of Breast Cancer Stem-like Cells via Targeting the NF-kB Signaling Pathway

The expression of GPR50 in CSLC and several breast cancer cell lines was assessed by RT-PCR and online platform (UALCAN, GEPIA, and R2 gene analysis). The role of GPR50 in driving CSLC, sphere formation, cell proliferation, and migration was performed using shGPR50 gene knockdown, and the role of GPR50-regulated signaling pathways was examined by Western blotting and Luciferase Assay. Herein, we confirmed that the expression of G protein-coupled receptor 50 (GPR50) in cancer stem-like cells (CSLC) is higher than that in other cancer cells. We examined that the knockdown of GPR50 in CSLC led to decreased cancer properties, such as sphere formation, cell proliferation, migration, and stemness. GPR50 silencing downregulates NF-kB signaling, which is involved in sphere formation and aggressiveness of CSLC. In addition, we demonstrated that GPR50 also regulates ADAM-17 activity by activating NOTCH signaling pathways through the AKT/SP1 axis in CSLC. Overall, we demonstrated a novel GPR50-mediated regulation of the NF-κB-Notch signaling pathway, which can provide insights into CSLC progression and prognosis, and NF-κB-NOTCH-based CSLC treatment strategies.

A computational approach based on weighted gene co-expression network analysis for biomarkers analysis of Parkinson's disease and construction of diagnostic model

Background

Parkinson's disease (PD) is a common age-related chronic neurodegenerative disease. There is currently no affordable, effective, and less invasive test for PD diagnosis. Metabolite profiling in blood and blood-based gene transcripts is thought to be an ideal method for diagnosing PD.

Aim

In this study, the objective is to identify the potential diagnostic biomarkers of PD by analyzing microarray gene expression data of samples from PD patients.

Methods

A computational approach, namely, Weighted Gene Co-expression Network Analysis (WGCNA) was used to construct co-expression gene networks and identify the key modules that were highly correlated with PD from the GSE99039 dataset. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to identify the hub genes in the key modules with strong association with PD. The selected hub genes were then used to construct a diagnostic model based on logistic regression analysis, and the Receiver Operating Characteristic (ROC) curves were used to evaluate the efficacy of the model using the GSE99039 dataset. Finally, Reverse Transcription-Polymerase Chain Reaction (RT-PCR) was used to validate the hub genes.

Results

WGCNA identified two key modules associated with inflammation and immune response. Seven hub genes, LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3 were identified from the two modules and used to construct diagnostic models. ROC analysis showed that the diagnostic model had a good diagnostic performance for PD in the training and testing datasets. Results of the RT-PCR experiments showed that there were significant differences in the mRNA expression of LILRB1, LSP1, and MBOAT7 among the seven hub genes.

Conclusion

The 7-gene panel (LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3) will serve as a potential diagnostic signature for PD.

Inside the stemness engine: Mechanistic links between deregulated transcription factors and stemness in cancer

Cell identity is largely determined by its transcriptional profile. In tumour, deregulation of transcription factor expression and/or activity enables cancer cell to acquire a stem-like state characterised by capacity to self-renew, differentiate and form tumours in vivo. These stem-like cancer cells are highly metastatic and therapy resistant, thus warranting a more complete understanding of the molecular mechanisms downstream of the transcription factors that mediate the establishment of stemness state. Here, we review recent research findings that provide a mechanistic link between the commonly deregulated transcription factors and stemness in cancer. In particular, we describe the role of master transcription factors (SOX, OCT4, NANOG, KLF, BRACHYURY, SALL, HOX, FOX and RUNX), signalling-regulated transcription factors (SMAD, β-catenin, YAP, TAZ, AP-1, NOTCH, STAT, GLI, ETS and NF-κB) and unclassified transcription factors (c-MYC, HIF, EMT transcription factors and P53) across diverse tumour types, thereby yielding a comprehensive overview identifying shared downstream targets, highlighting unique mechanisms and discussing complexities.

SIPA1 Regulates LINC01615 to Promote Metastasis in Triple-Negative Breast Cancer

Simple Summary

Breast cancer is a malignant tumor that often endangers women. After undergoing surgery and supplementary chemotherapy, however, tumor recurrence has not been well researched. The primary cause is high metastatic rates. Hence, bioinformatic and functional analyses were performed to indicate the effect of LINC01615 on breast cancer. We revealed that LINC01615 is regulated by the transcription factor SIPA1 in promoting breast cancer cell malignancy.

Abstract

Long non-coding RNAs (lncRNAs) are reported to play an important regulatory effect in carcinogenesis and malignancy. We found by high-throughput sequencing that LINC01615 is upregulated in breast cancer patients and reduces patients’ overall survival. In vivo and in vitro experiments, we clarified that overexpression of LINC01615 can promote breast cancer cell metastasis ability. The expression of LINC01615 is regulated by the transcriptional activator SIPA1, thereby promoting carcinogenesis in breast cancer cells. Our research clarified that LINC01615 can act as an oncogenic factor in promoting the development of breast cancer.

Extracellular Vesicles Derived from SIPA1high Breast Cancer Cells Enhance Macrophage Infiltration and Cancer Metastasis through Myosin-9

Simple Summary

The high expression of signal-induced proliferation-associated 1 (SIPA1) in breast cancer could aggravate cancer cell metastasis, but how the tumour microenvironment is involved in this incident is unknown. In this study, we investigated whether breast cancer cells with high SIPA1 expression recruited macrophages into the tumour microenvironment. We also found that extracellular vesicles (EVs) derived from MDA-MB-231 cells significantly enhanced macrophage migration, compared with that from SIPA1-knockdown MDA-MB-231 cells both in vitro and in vivo. In terms of the mechanism, SIPA1 in cancer cells modulated the key protein myosin-9 in EVs and promoted macrophage infiltration via EVs. We confirmed that either down-regulating SIPA1 expression or blocking myosin-9 by its inhibitor, blebbistatin, led to the suppression of macrophage infiltration. These findings contribute to a deep understanding of how SIPA1 regulates the tumour microenvironment in breast cancer to facilitate tumour metastasis and provide a basis for the development of therapeutics against breast cancer metastasis.

Abstract

Tumour cell metastasis can be genetically regulated by proteins contained in cancer cell-derived extracellular vesicles (EVs) released to the tumour microenvironment. Here, we found that the number of infiltrated macrophages was positively correlated with the expression of signal-induced proliferation-associated 1 (SIPA1) in invasive breast ductal carcinoma tissues and MDA-MB-231 xenograft tumours. EVs derived from MDA-MB-231 cells (231-EVs) significantly enhanced macrophage migration, compared with that from SIPA1-knockdown MDA-MB-231 cells (231/si-EVs) both in vitro and in vivo. We revealed that SIPA1 promoted the transcription of MYH9, which encodes myosin-9, and up-regulated the expression level of myosin-9 in breast cancer cells and their EVs. We also found that blocking myosin-9 by either down-regulating SIPA1 expression or blebbistatin treatment led to the suppression of macrophage infiltration. Survival analysis showed that breast cancer patients with high expression of SIPA1 and MYH9 molecules had worse relapse-free survival (p = 0.028). In summary, SIPA1^high breast cancer can enhance macrophage infiltration through EVs enriched with myosin-9, which might aggravate the malignancy of breast cancer.

AC010973.2 promotes cell proliferation and is one of six stemness-related genes that predict overall survival of renal clear cell carcinoma

Extensive research indicates that tumor stemness promotes tumor progression. Nonetheless, the underlying roles of stemness-related genes in renal clear cell carcinoma (ccRCC) are unclear. Data used in bioinformatics analysis were downloaded from The Cancer Genome Atlas (TCGA) database. Moreover, the R software, SPSS, and GraphPad Prism 8 were used for mapping and statistical analysis. First, the stemness index of each patient was quantified using a machine learning algorithm. Subsequently, the differentially expressed genes between high and low stemness index were identified as stemness-related genes. Based on these genes, a stable and effective prognostic model was identified to predict the overall survival of patients using a random forest algorithm (Training cohort; 1-year AUC: 0.67; 3-year AUC: 0.79; 5-year AUC: 0.73; Validation cohort; 1-year AUC: 0.66; 3-year AUC: 0.71; 5-year AUC: 0.7). The model genes comprised AC010973.2, RNU6-125P, AP001209.2, Z98885.1, KDM5C-IT1, and AL021368.3. Due to its highest importance evaluated by randomforst analysis, the AC010973.2 gene was selected for further research. In vitro experiments demonstrated that AC010973.2 is highly expressed in ccRCC tissue and cell lines. Meanwhile, its knockdown could significantly inhibit the proliferation of ccRCC cells based on colony formation and CCK8 assays. In summary, our findings reveal that the stemness-related gene AC01097.3 is closely associated with the survival of patients. Besides, it remarkably promotes cell proliferation in ccRCC, hence a novel potential therapeutic target.

SIPA1 Enhances Aerobic Glycolysis Through HIF-2α Pathway to Promote Breast Cancer Metastasis

Increased dependence on aerobic glycolysis is characteristic of most cancer cells, whereas the mechanism underlying the promotion of aerobic glycolysis in metastatic breast cancer cells under ambient oxygen has not been well understood. Here, we demonstrated that aberrant expression of signal-induced proliferation-associated 1 (SIPA1) enhanced aerobic glycolysis and altered the main source of ATP production from oxidative phosphorylation to glycolysis in breast cancer cells. We revealed that SIPA1 promoted the transcription of EPAS1, which is known as the gene encoding hypoxia-inducible factor-2α (HIF-2α) and up-regulated the expression of multiple glycolysis-related genes to increase aerobic glycolysis. We also found that blocking aerobic glycolysis by either knocking down SIPA1 expression or oxamate treatment led to the suppression of tumor metastasis of breast cancer cells both in vitro and in vivo. Taken together, aberrant expression of SIPA1 resulted in the alteration of glucose metabolism from oxidative phosphorylation to aerobic glycolysis even at ambient oxygen levels, which might aggravate the malignancy of breast cancer cells. The present findings indicate a potential target for the development of therapeutics against breast cancers with dysregulated SIPA1 expression.

A novel nuclear localization region in SIPA1 determines protein nuclear distribution and epirubicin-sensitivity of breast cancer cells

Signal-induced proliferation-associated protein 1 (SIPA1) is highly expressed and mainly located in the nucleus in some breast cancer cell lines and clinical tumor tissues. Previous study revealed that nuclear localization of SIPA1 is functionally involved in breast cancer metastasis in the lymphatic gland. In the current study, we identified a non-typical region (140-179aa) of SIPA1 as a novel nuclear localization region (NLR) which is crucial for translocating the proteins into the nucleus in HEK293 cells and breast cancer cells. This region contained one basic amino acid, His160, and had no common features of typical nuclear localization signals. In addition, overexpressing SIPA1 without NLR could suppress breast cancer cell proliferation but could not promote cell migration in MCF7 cells. Furthermore, we found that a high expression of SIPA1 upregulated the expression of ABCB1, encoding multi-drug resistance protein MDR1, and promoted the resistance to epirubicin in breast cancer cells, while this effect was largely abolished in the cells with the expression of NLR-deleted SIPA1. This study overall, identified a nuclear localization-dependent region determining the nuclear distribution of SIPA1 and its regulation on epirubicin-sensitivity in breast cancer cells, which could be a potential drug target to facilitate the development of breast cancer chemotherapy.