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. 2024 Jul 8:17:2967-2979.
doi: 10.2147/IJGM.S466364. eCollection 2024.

Screening of a Prognostic Gene Signature for Relapsed/Refractory Acute Myeloid Leukemia Based on Altered Circulating CircRNA Profiles

Honggang Guo #  1 , Yabin Cui #  2 , Yanliang Bai  1 , Fan Yan  1 , Wenhui Zhang  1 , Yuqing Chen #  1 , Mingyue Shi #  1
Affiliations

Screening of a Prognostic Gene Signature for Relapsed/Refractory Acute Myeloid Leukemia Based on Altered Circulating CircRNA Profiles

Honggang Guo et al. Int J Gen Med. .

Abstract

Background: Relapsed/refractory acute myeloid leukemia (R/R-AML) has dismal prognosis due to chemotherapy resistance. Circular RNAs (circRNAs) have shown emerging roles in chemotherapy resistance in various cancers including hematologic malignancies. However, the potential roles of circRNAs in AML progression and drug resistance remain largely undetermined.

Methods: In this study, circulating circRNAs expression profiles were analyzed among R/R-AML, de novo AML and healthy controls (HC) using a human circRNA Array. Bioinformatic analysis was carried out to explore the differentially expressed circRNAs (DE-circRNAs). GO, KEGG pathway analysis, along with circRNA-miRNA-mRNA network analysis, were conducted to identify the potential biological pathways involved in R/R-AML. Finally, the UALCAN database was used to assess the prognosis of different target DE-circRNAs-related mRNAs.

Results: Forty-eight DE-circRNAs were upregulated, whereas twenty-seven DE-circRNAs were downregulated in R/R-AML samples. Up-regulated DE-circRNAs in R/R-AML samples were mainly enrichment in the biological processes and pathways of cell migration, microRNAs in cancers, Rap1 and Ras signaling pathways. Six DE-circRNAs were randomly selected to further explore their relationships with R/R-AML. GO and KEGG pathway analyses of the six candidate DE-circRNAs-related target mRNAs were mainly involved in the regulation of signal transduction and Ras signaling pathway. By overlapping our RNA-sequencing results of differentially expressed genes (DEGs) in R/R-AML samples with the candidate DE-circRNAs-predicted target mRNAs, we identified sixty-eight overlapping targeted mRNAs. Using UALCAN database analysis, we identified that AML patients with six upregulated DE-circRNA-related genes (ECE1, PI4K2A, SLC9A6, CCND3, PPP1R16B, and TRIM32) and one downregulated gene DE-circRNA-related genes (ARHGAP10) might have a poor prognosis.

Conclusion: This study revealed the overall alterations of circRNAs in R/R-AML. DE-circRNAs and their related genes might be used as potential early, sensitive and stable biomarkers for AML diagnosis, R/R-AML monitoring, and even as novel treatment targets for R/R-AML.

Keywords: Relapsed/refractory; acute myeloid leukemia; biomarkers; circular RNAs; prognosis.

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Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Expression profiles of circRNAs in de novo AML patients, R/R-AML and HC. (A) Scatter plots, (B) Volcano plots, and (C) Heat map showing differentially expressed circRNAs in de novo AML and HC. (D) Scatter plots, (E) Volcano plots, and (F). Heat map showing differentially expressed circRNAs in R/R-AML and de novo AML.
Figure 2
Figure 2
Distribution and category of differentially expressed circRNAs (DE-circRNAs) in AML. (A) Distribution of DE-circRNAs in human chromosomes in de novo AML patients. (B) The percentage of DE-circRNAs derived from different genomic loci (exonic, intronic, antisense, intergenic, and sense overlapping) in de novo AML patients. (C) Distribution of DE-circRNAs in human chromosomes in R/R-AML patients. (D) The percentage of DE-circRNAs derived from different genomic loci (exonic, intronic, antisense, intergenic, and sense overlapping) in R/R-AML patients.
Figure 3
Figure 3
The GO and KEGG enrichment analysis of DE-circRNAs and DEGs between R/R-AML and de novo AML. (A and B). Enriched GO and KEGG terms of DE-circRNAs in R/R-AML patients. (C) Enriched GO and KEGG terms of DEGs in R/R-AML patients.
Figure 4
Figure 4
Candidate DE-circRNAs associated with R/R-AML. (A) Venn diagram of candidate DE-circRNAs. (B) Heatmap of the 30 overlapping DE-circRNAs.
Figure 5
Figure 5
CircRNAs/miRNAs/mRNAs network analysis of candidate DE-circRNAs. Predictions of circRNA‐miRNA‐mRNA interaction network, showing 6 DE-circRNAs: (A) has-circRNA-101819 and has-circRNA-406642, (B) has-circRNA-051239, (C) has-circRNA-101330, (D) has-circRNA-101539 and (E). has-circRNA-10249. (circRNAs were shown as yellow nodes, miRNAs were shown as blue nodes, and their target genes were shown as red nodes).
Figure 6
Figure 6
Overlapping of the predicted target mRNAs and our ceRNA. (A) Venn diagram of predicted target mRNAs and our RNA-sequencing profiles of R/R AML samples. (B) Heatmap of the 68 overlapping mRNAs.
Figure 7
Figure 7
Identify the prognostic gene signature of R/R-AML by the UALCAN data portal based on DE-circRNA profiles. AML with overexpression of 6 genes indicated a poor prognosis: (A) ECE1, (B) PI4K2A, (C) SLC9A6, (D) CCND3, (E) PPP1R16B, (F) TRIM32 and (G). ARHGAP10. (p < 0.05).
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