RFC5, regulated by circ_0038985/miR-3614-5p, functions as an oncogene in the progression of colorectal cancer

Replication factor C 5 (RFC5) is involved in a variety of biological functions of cancer. However, the expression pattern of RFC5 and the underlying mechanisms in colorectal cancer (CRC) remain elusive. Here, we show that RFC5 is significantly upregulated in CRC tissues and cells. Patients with CRC and increased RFC5 levels have an unfavorable prognosis. RFC5 can promote the proliferation, migration, and invasion of CRC cells and inhibit the apoptosis of CRC cells. Additionally, upstream of RFC5, we constructed the competing endogenous RNA network and confirmed that RFC5 in this network was inhibited by miR-3614-5p by directly targeting its 3'-untranslated regions. We verified that circ_0038985, which is positively correlated with RFC5, directly targeted miR-3614-5p. Overexpression of circ_0038985 promoted CRC cell migration and invasion, and these effects were partially reversed by the reintroduction of miR-3614-5p. Moreover, we found that RFC5 may promote the vascular endothelial growth factor A (VEGFa)/vascular endothelial growth factor receptor 2 (VEGFR2)/extracellular signal-regulated protein kinase (ERK) pathway. The knockdown of RFC5 reduced CRC tumorigenesis in vivo. Collectively, these data demonstrate that the circ_0038985/miR-3614-5p/RFC5 axis plays a critical role in the progression of CRC, and RFC5 may promote CRC progression by affecting the VEGFa/VEGFR2/ERK pathway.

Prognostic biomarker replication factor C subunit 5 and its correlation with immune infiltrates in acute myeloid leukemia

OBJECTIVE

To determine the role of replication factor C subunit 5 (RFC5) in acute myeloid leukemia (AML) from four aspects: expression, prognosis, biological functions, and its effects on the immune system.

METHODS

The RFC5 gene expression and survival analyses, biological function analyses including functional enrichment analysis of genes co-expressed with RFC5, RFC5-interacted gene network construction, gene set enrichment analysis (GSEA), and immune infiltration analysis were performed using data based on GDC TCGA and GEO. The CIBERSORT algorithm was employed to quantify immune cell fractions. All the statistical analyses were performed in SPSS software, GraphPad Prism, and R software.

RESULTS

RFC5 expression was abnormally expressed in AML (P <0.05). Notably, differential RFC5 expression was observed among different FAB AML subtypes and hematopoietic lineages (all P <0.05). More importantly, high RFC5 expression served as an independent prognostic factor for the poor overall survival of AML patients (P <0.001). Enrichment analyses revealed that RFC5 was involved in cell cycle-related pathways in AML. CIBERSORT analysis showed high proportions of M2 macrophages in the high RFC5 expression group.

CONCLUSIONS

RFC5 might serve as an effective and robust biomarker for the diagnosis and prognosis of AML. RFC5 might be involved in the AML progression via cell cycle regulation. Moreover, the correlation between RFC5 and immune cells might provide potential assistance for AML treatment.

Identification of biomarkers for acute leukemia via machine learning-based stemness index

Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include constructing LSC-like cells and mouse models by transgenic or knock-in methods. However, there are some potential pitfalls in using this method, such as retroviral insertion mutagenesis, non-physiological level gene expression, non-physiological expansion, and difficulty to construct. The mRNAsi index for each sample of the Cancer Genome Atlas (TCGA) could avoid these potential pitfalls by machine learning. In this work, we aimed to construct a network of LSC genes utilizing the mRNAsi. First, mRNAsi value was analyzed with expressions distributions, survival analysis, age, and gender in acute myeloid leukemia (AML) samples. Then, we used the weighted gene co-expression network analysis (WGCNA) to construct modules of stemness genes. The correlation of the LSC genes transcription and interplay among LSC proteins was analyzed. We performed functional and pathway enrichment analysis to annotate stemness genes. Survival analysis further identified prognostic biomarkers by clinical data of TCGA and the Gene Expression Omnibus (GEO) database. We found that the result of mRNAsi overall survival is not significant, which may be due to the heterogeneity of AML in the stage of myeloid differentiation, French-American-British (FAB) classification systems. Enrichment analysis indicated that the stemness genes were biologically clustered as a group and mainly associated with cell cycle and mitosis. Moreover, 10 key genes (SNRNP40, RFC4, RFC5, CDC6, HSPE1, PA2G4, SNAP23P, DARS2, MIS18A, and HPRT1) were screened by survival analysis with the data from TCGA and GEO. Among them, RFC4 and RFC5 were the distinguished biomarkers for their double-validated prognostic value in both databases. Additionally, the expression of RFC4 and RFC5 had the same trend as mRNAsi score in FAB subtypes. In conclusion, our result demonstrated that mRNAsi based LSC-related genes were found to have strong interactions as a cluster. These genes, especially RFC4 and RFC5, could be the therapeutic targets for inhibiting the stemness characteristics of AML. This work is also a comprehensive pipeline for future cancer stem cell studies.

AEG-1 Knockdown Sensitizes Glioma Cells to Radiation Through Impairing Homologous Recombination Via Targeting RFC5

Radiotherapy is the most important adjuvant treatment for glioma; however, radioresistance is the major cause for inevitable recurrence and poor survival of glioma patients. Thus, this study aims to investigate the effect of astrocyte elevated gene-1 (AEG-1) on the radiosensitivity of glioma cells. Immunohistochemistry assay found that AEG-1 was generally overexpressed in glioma tissues and was correlated with poor clinicopathological features of glioma patients. AEG-1 knockdown inhibited proliferation of glioma cells. And γ-H2AX foci assay, colony formation assay, and flow cytometry analysis demonstrated that AEG-1 depletion enhanced radiosensitivity and promoted apoptosis as well as cell cycle arrest in G2 phase of glioma cells treated by ionizing radiation. Moreover, replication factor C5 (RFC5) was screened as the target of AEG-1 by using Affymetrix human gene expression array, and RFC5 expression was downregulated in AEG-1 knockdown glioma cells. Mechanistically, AEG-1 knockdown impaired homologous recombination repair activity induced by radiation through inhibiting RFC5 expression. Furthermore, the Kaplan-Meier analysis and multivariate Cox regression analysis indicated that high levels of AEG-1 and RFC5 were related to poor prognosis of glioma patients treated with radiotherapy. Taken together, our findings indicate that AEG-1 may serve as a reliable radiosensitizing target for glioma radiotherapy.