Foxm1 controls a pro-stemness microRNA network in neural stem cells

Liu

et al. 2020

Journal of Oncology

Background. Whether DNA methyltransferase 1 (DNMT1)/miR-34a/FoxM1 signaling promotes the stemness of liver cancer stem cells (LCSCs) remains unclear. This study aimed to assess whether methylation-based silencing of miR-34a by DNMT1 contributes to stemness features via FoxM1 upregulation in LCSCs. Methods. The CD133+ subgroup of MHCC97H cells sorted by MACS was used as LCSCs. DNMT1, BMI1, SOX2, and OCT4 mRNA levels, and miR-34a amounts were determined by qRT-PCR. DNMT1, CD44, and FoxM1 proteins were analyzed by immunoblot. Sphere and colony formation abilities were detected by respective assays. CD133+ cell percentages were assessed by flow cytometry. In vivo oncogenicity was evaluated using a tumor xenograft model in mice. The effects of DNMT1/miR-34a signaling on the stemness of LCSCs were examined by knockdown or overexpression of DNMT1 and/or transfection of miR-34a mimic or inhibitor using lentivirus-delivery systems. FoxM1 association with miR-34a was detected by a reporter assay. Results. We here showed that LCSCs exhibited elevated DNMT1 activity and expression, lower miR-34a expression with higher promoter methylation, and stronger stemness, compared with the parental liver cancer cells. DNMT1 knockdown repressed DNMT1, increased miR-34a amounts by promoter demethylation, and reduced stemness in LCSCs, whereas DNMT1 overexpression had the opposite effects in liver cancer cells. Transfection with miR-34a mimic repressed the stemness of LCSCs, while miR-34a inhibitor significantly downregulated miR-34a and enhanced stemness, without affecting DNMT1 in liver cancer cells. MiR-34a mimic rescued the effects of DNMT1 overexpression on the stemness of LCSCs, without affecting DNMT1 expression. Finally, FOXM1 was identified as a direct target by miR-34a in LCSCs. Conclusions. We revealed that aberrant activation of DNMT1 causes miR-34a promoter methylation and suppression, leading to FoxM1 upregulation by disinhibition and promotion of LCSC stemness. These findings suggest that blockage of DNMT1/miR-34a-mediated FOXM1 upregulation might suppress liver cancer by targeting LCSCs.

Section: Discussionmentioning

confidence: 99%

The DNMT1/miR-34a/FOXM1 Axis Contributes to Stemness of Liver Cancer Cells

Liu

et al. 2020

Journal of Oncology

“…Foxm1 was recently reported to regulate a micro-RNA network which controls the self-renewal capacity in neural stem cells [51]. redPATH provides an interactive plot that can visualize different cell types, cell cycle stages, and gene expression together.…”

Section: Coupling Proliferation With Differentiationmentioning

confidence: 99%

redPATH: Reconstructing the Pseudo Development Time of Cell Lineages in Single-Cell RNA-Seq Data and Applications in Cancer

Xie

Liu

Chen

et al. 2020

Preprint

Recent advancement of single-cell RNA-seq technology facilitates the study of cell lineages in developmental processes as well as cancer. In this manuscript, we developed a computational method, called redPATH, to reconstruct the pseudo developmental time of cell lineages using a consensus asymmetric Hamiltonian path algorithm. Besides, we implemented a novel approach to visualize the trajectory development of cells and visualization methods to provide biological insights. We validated the performance of redPATH by segmenting different stages of cell development on multiple neural stem cell and cancerous datasets, as well as other single-cell transcriptome data. In particular, we identified a subpopulation of malignant glioma cells, which are stem cell-like. These cells express known proliferative markers such as GFAP (also identified ATP1A2, IGFBPL1, ALDOC) and remain silenced in quiescent markers such as ID3. Furthermore, MCL1 is identified as a significant gene that regulates cell apoptosis, and CSF1R confirms previous studies for re-programming macrophages to control tumor growth. In conclusion, redPATH is a comprehensive tool for analyzing single-cell RNA-Seq datasets along a pseudo developmental time. The software is available via http://github.com/tinglab/redPATH.

“…NSC mirnome data were obtained from our recently published manuscript [26]. Animal experiments were performed according to the European Community Council Directive 2010/63/EU and were approved by the local Ethics Committee for Animal Experiments (Prot.…”

Section: Methodsmentioning

confidence: 99%

“…Three biological replicates of SHH MB CSCs were subjected to miRNA-sequencing, quality control, mapping, quantification and differential expression analysis was performed between SHH MB CSCs and NSCs, as previously described [26]. In detail, an average of 10.48 ± 0.748 million reads per biological replicate were obtained by the sequencing and quality control was performed using the FastQC tool (, accessed on 01/Februay/2017 before mapping where an average of 92% of reads with a quality score >30 were obtained.…”

Section: Methodsmentioning

confidence: 99%

Sonic Hedgehog Medulloblastoma Cancer Stem Cells Mirnome and Transcriptome Highlight Novel Functional Networks

Pò

Abballe

Sabato

et al. 2018

IJMS

Self Cite

Molecular classification has improved the knowledge of medulloblastoma (MB), the most common malignant brain tumour in children, however current treatments cause severe side effects in patients. Cancer stem cells (CSCs) have been described in MB and represent a sub population characterised by self-renewal and the ability to generate tumour cells, thus representing the reservoir of the tumour. To investigate molecular pathways that characterise this sub population, we isolated CSCs from Sonic Hedgehog Medulloblastoma (SHH MB) arisen in Patched 1 (Ptch1) heterozygous mice, and performed miRNA- and mRNA-sequencing. Comparison of the miRNA-sequencing of SHH MB CSCs with that obtained from cerebellar Neural Stem Cells (NSCs), allowed us to obtain a SHH MB CSC miRNA differential signature. Pathway enrichment analysis in SHH MB CSCs mirnome and transcriptome was performed and revealed a series of enriched pathways. We focused on the putative targets of the SHH MB CSC miRNAs that were involved in the enriched pathways of interest, namely pathways in cancer, PI3k-Akt pathway and protein processing in endoplasmic reticulum pathway. In silico analysis was performed in SHH MB patients and identified several genes, whose expression was associated with worse overall survival of SHH MB patients. This study provides novel candidates whose functional role should be further investigated in SHH MB.