Dataset Information

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Unravels the Molecular Feature of Tumor-Associated Macrophage of Acute Myeloid Leukemia.

ABSTRACT:

Background

The association between acute myeloid leukemia (AML) and macrophage remains to be deeply explored.

Methods

Gene expression profiles and clinical variable characteristics of AML patients were collected from TCGA, GEO, and TARGET databases. Consensus clustering was employed to construct the macrophage-related clusters. The macrophage-related index (MRI) was constructed using the LASSO and multivariate Cox analysis. The GSE71014 and TARGET datasets were utilized as external validation sets. Single-cell sequencing data for AML (GSE116256) was adopted to analyze modeled gene expression levels in cells.

Results

Two macrophage-related clusters with different prognostic and immune infiltration characteristics were constructed in AML. Cluster B had a poorer prognosis, more cancer-promoting pathway enrichment, and an immunosuppressive microenvironment. Relied on the MRI, patients of different groups showed different levels of immune infiltration, different mutations, and prognoses. LGALS1 and BCL2A1 may play roles in promoting cancer in AML, while ELANE may have a significant effect on suppressing cancer.

Conclusion

Macrophage-related genes (MRGs) had significant impacts on the occurrence and progression of AML. MRI may better evaluate the prognosis and immune features of AML patients.

SUBMITTER: Gao X

PROVIDER: S-EPMC10776189 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Publications

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Unravels the Molecular Feature of Tumor-Associated Macrophage of Acute Myeloid Leukemia.

Gao Xin X

Genetics research 20240102

<h4>Background</h4>The association between acute myeloid leukemia (AML) and macrophage remains to be deeply explored.<h4>Methods</h4>Gene expression profiles and clinical variable characteristics of AML patients were collected from TCGA, GEO, and TARGET databases. Consensus clustering was employed to construct the macrophage-related clusters. The macrophage-related index (MRI) was constructed using the LASSO and multivariate Cox analysis. The GSE71014 and TARGET datasets were utilized as externa ...[more]

PMID: 38205232

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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious and pathogenic coronavirus that emerged in late 2019 and caused a pandemic of respiratory illness termed as coronavirus disease 2019 (COVID-19). Cancer patients are more susceptible to SARS-CoV-2 infection. The treatment of cancer patients infected with SARS-CoV-2 is more complicated, and the patients are at risk of poor prognosis compared to other populations. Patients infected with SARS-CoV-2 are prone to rapid development of acute respiratory distress syndrome (ARDS) of which pulmonary fibrosis (PF) is considered a sequelae. Both ARDS and PF are factors that contribute to poor prognosis in COVID-19 patients. However, the molecular mechanisms among COVID-19, ARDS and PF in COVID-19 patients with cancer are not well-understood. In this study, the common differentially expressed genes (DEGs) between COVID-19 patients with and without cancer were identified. Based on the common DEGs, a series of analyses were performed, including Gene Ontology (GO) and pathway analysis, protein-protein interaction (PPI) network construction and hub gene extraction, transcription factor (TF)-DEG regulatory network construction, TF-DEG-miRNA coregulatory network construction and drug molecule identification. The candidate drug molecules (e.g., Tamibarotene CTD 00002527) obtained by this study might be helpful for effective therapeutic targets in COVID-19 patients with cancer. In addition, the common DEGs among ARDS, PF and COVID-19 patients with and without cancer are TNFSF10 and IFITM2. These two genes may serve as potential therapeutic targets in the treatment of COVID-19 patients with cancer. Changes in the expression levels of TNFSF10 and IFITM2 in CD14+/CD16+ monocytes may affect the immune response of COVID-19 patients. Specifically, changes in the expression level of TNFSF10 in monocytes can be considered as an immune signature in COVID-19 patients with hematologic cancer. Targeting N6-methyladenosine (m6A) pathways (e.g., METTL3/SERPINA1 axis) to restrict SARS-CoV-2 reproduction has therapeutic potential for COVID-19 patients.

Dataset Information

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Unravels the Molecular Feature of Tumor-Associated Macrophage of Acute Myeloid Leukemia.

Background

Methods

Results

Conclusion

Publications

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Unravels the Molecular Feature of Tumor-Associated Macrophage of Acute Myeloid Leukemia.

Similar Datasets

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