Identification of prognostic genes in the acute myeloid leukemia microenvironment

Huang, Shaoxin; Zhang, Biyu; Fan, Wei; Zhao, Qihan; Yang, Lei; Wang, Xin; Fu, Denggang

doi:10.18632/aging.102477

Cited by 40 publications

(37 citation statements)

References 85 publications

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“…In addition, immune scores were significantly correlated with cytogenetic risk and overall survival, indicating that immune microenvironment plays an important role in the development and progression of AML. These results are consistent with recent reports that included all AML patients in TCGA [11][12][13], however our study excluded patients with other tumors.…”

Section: Discussionsupporting

confidence: 93%

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A Novel Immune-related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

Wang

Liu

et al. 2020

Preprint

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Background Acute myeloid leukemia is a genetically, biologically and clinically heterogeneous hematopoietic malignancy that is highly dependent on the bone marrow microenvironment. Infiltrated immune cells and stromal cells are an important part of the bone marrow microenvironment and significantly affect the progression of acute myeloid leukemia. Recently, the competing endogenous RNA hypothesis has gained great interests in the study of molecular and biological mechanisms of tumor occurrence and progression. However, research on how competing endogenous RNA relates to leukemia tumor microenvironment remains uninvestigated.Methods In this study, mRNA, miRNA and lncRNA data and clinical information of the acute myeloid leukemia cohort were obtained from The Cancer Genome Atlas database, and the immune and stromal scores were calculated using the ESTIMATE algorithm.Results We found that immune scores were significantly correlated with cytogenetic risk and overall survival, and also identified microenvironment-related mRNAs, miRNAs, and lncRNAs based on the immune and stromal scores. Differentially expressed mRNAs and lncRNAs were applied to weighted correlation network analysis to identify the modules most relevant to the immune microenvironment of acute myeloid leukemia. Using miRNA database to predict miRNA-targeted genes, we established the immune-related competing endogenous RNA network consisting of 33 lncRNAs, 21 miRNAs and 135 mRNAs. Prognostic analysis was performed on the genes in the immune-related competing endogenous RNA network to screen out 15 lncRNAs, 2 miRNAs and 31 mRNAs with prognostic values.Conclusions In summary, we identified a novel immune-related mRNA-miRNA-lncRNA competing endogenous RNA network associated with the prognosis of acute myeloid leukemia, which may contribute to better understanding of the development and progression of acute myeloid leukemia and to serve as novel therapeutic targets.

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Section: Discussionsupporting

confidence: 93%

“…The ESTIMATE program is a common method to explore the microenvironment of many tumors [10]. Recently, it has also been used to explore the prognostic genes in the microenvironment of AML patients [11][12][13]. Most studies have focused on differentially expressed genes.…”

Section: Introductionmentioning

confidence: 99%

A Novel Immune-related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

Wang

Liu

et al. 2020

Preprint

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“…Kaplan-Meier survival curves indicated that higher immune scores usually portended unfavorable clinical outcomes. These results are the same as previous studies [41,42].…”

Section: Discussionsupporting

confidence: 92%

Identification of a Prognostic Gene Signature Associated with Microenvironment in Acute Myeloid Leukemia

Chen

Wang

et al. 2020

Preprint

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Background: Acute myeloid leukemia (AML) is a common hematologic malignancy with poor prognosis. Accumulating reports have indicated that the tumor microenvironment (TME) performs a critical role in the progress of the disease and the clinical outcomes of patients. To date, the role of TME in AML remains clouded due to the complex regulatory mechanisms in it. In this study, We identified key prognostic genes relate to TME in AML and developed a novel gene signature for individualized prognosis assessment. Methods: The expression profiles of AML samples with clinical information were obtained from the Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was applied to calculate the TME relevant immune and stromal scores. The differentially expressed genes (DEGs) were selected based on the immune and stromal scores. Then, the survival analysis was applied to select prognostic DEGs, and these genes were annotated by functional enrichment analysis. A TME relevant gene signature with predictive capability was constructed by a series of regression analyses and performed well in another cohort from the Gene Expression Omnibus (GEO) database. Moreover, we also developed a nomogram with the integration of the gene signature and clinical indicators to establish an individually quantified risk-scoring system. Results: In the AML microenvironment, a total of 181 DEGs with prognostic value were clarified. Then a seven-gene ( IL1R2, MX1, S100A4, GNGT2, ZSCAN23, PLXNB1 and DPY19L2 ) signature with robust prediction was identified, and was validated by an independent cohort of AML samples from the GSE71014. Gene set enrichment analysis (GSEA) of genes in the gene signature revealed these genes mainly enriched in the immune and inflammatory related processes. The correlation between the signature-calculated risk scores and the clinical features indicated that patients with high risk scores were accompanied by adverse survival. Finally, a nomogram with clinical utility was constructed. Conclusion: Our study explored and identified a novel TME relevant seven-gene signature, which could serve as a prognostic indicator for AML. Meanwhile, we also establish a nomogram with clinical significance. These findings might provide new insights into the diagnosis, treatment and prognosis of AML.

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“…The ESTIMATE program is a common method to explore the microenvironment of many tumors (10). Recently, it has also been used to explore the prognostic genes in the microenvironment of AML patients (11)(12)(13). Most studies have focused on differentially expressed genes (DEGs).…”

Section: Introductionmentioning

confidence: 99%

A Novel Immune-Related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

et al. 2020

View full text Add to dashboard Cite

Background: Acute myeloid leukemia (AML) is a genetically, biologically and clinically heterogeneous hematopoietic malignancy that is highly dependent on the bone marrow (BM) microenvironment. Infiltrated immune cells and stromal cells are an important part of the BM microenvironment and significantly affect the progression of AML. Recently, the competing endogenous RNA hypothesis has gained great interests in the study of molecular and biological mechanisms of tumor occurrence and progression. However, research on how competing endogenous RNA relates to leukemia tumor microenvironment remains uninvestigated. Methods: In this study, mRNA, miRNA and lncRNA data and clinical information of the AML cohort were obtained from The Cancer Genome Atlas (TCGA) database, and the immune and stromal scores were calculated using the ESTIMATE algorithm. Results: We found that immune scores were significantly correlated with cytogenetic risk and overall survival, and also identified microenvironment-related mRNAs, miRNAs, and lncRNAs based on the immune and stromal scores. Differentially expressed mRNAs and lncRNAs were applied to weighted correlation network analysis (WGCNA) to identify the modules most relevant to the immune microenvironment of AML. Using miRNA database to predict miRNA-targeted genes, we established the immune-related competing endogenous RNA network consisting of 33 lncRNAs, 21 miRNAs and 135 mRNAs. Prognostic analysis was performed on the genes in the immune-related competing endogenous RNA network to screen out 15 lncRNAs, 2 miRNAs and 31 mRNAs with prognostic values. Conclusion: In summary, we identified a novel immune-related mRNA-miRNA-lncRNA competing endogenous RNA network associated with the prognosis of AML, which may contribute to better understanding of the development and progression of AML and to serve as novel therapeutic targets.

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Identification of prognostic genes in the acute myeloid leukemia microenvironment

Cited by 40 publications

References 85 publications

A Novel Immune-related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

A Novel Immune-related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

Identification of a Prognostic Gene Signature Associated with Microenvironment in Acute Myeloid Leukemia

A Novel Immune-Related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

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Identification of prognostic genes in the acute myeloid leukemia microenvironment

Cited by 40 publications

References 85 publications

A Novel Immune-related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

A Novel Immune-related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

Identification of a Prognostic Gene Signature&nbsp;Associated with Microenvironment in&nbsp;Acute Myeloid Leukemia

A Novel Immune-Related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

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Identification of a Prognostic Gene Signature Associated with Microenvironment in Acute Myeloid Leukemia