Dataset Information

An Immune Checkpoint-Related Gene Signature for Predicting Survival of Pediatric Acute Myeloid Leukemia.

ABSTRACT:

Objective

The aim of this research was to create a new genetic signature of immune checkpoint-associated genes as a prognostic method for pediatric acute myeloid leukemia (AML).

Methods

Transcriptome profiles and clinical follow-up details were obtained in Therapeutically Applicable Research to Generate Effective Treatments (TARGET), a database of pediatric tumors. Secondary data was collected from the Gene Expression Omnibus (GEO) to test the observations. In univariate Cox regression and multivariate Cox regression studies, the expression of immune checkpoint-related genes was studied. A three-mRNA signature was developed for predicting pediatric AML patient survival. Furthermore, the GEO cohort was used to confirm the reliability. A bioinformatics method was utilized to identify the diagnostic and prognostic value.

Results

A three-gene (STAT1, BATF, EML4) signature was developed to identify patients into two danger categories depending on their OS. A multivariate regression study showed that the immune checkpoint-related signature (STAT1, BATF, EML4) was an independent indicator of pediatric AML. By immune cell subtypes analyses, the signature was correlated with multiple subtypes of immune cells.

Conclusion

In summary, our three-gene signature can be a useful tool to predict the OS in AML patients.

SUBMITTER: Jiang F

PROVIDER: S-EPMC8079183 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

An Immune Checkpoint-Related Gene Signature for Predicting Survival of Pediatric Acute Myeloid Leukemia.

Jiang Feng F Wang Xin-Yu XY Wang Ming-Yan MY Mao Yan Y Miao Xiao-Lin XL Wu Chu-Yan CY Zhou Guo-Ping GP

Journal of oncology 20210419

<h4>Objective</h4>The aim of this research was to create a new genetic signature of immune checkpoint-associated genes as a prognostic method for pediatric acute myeloid leukemia (AML).<h4>Methods</h4>Transcriptome profiles and clinical follow-up details were obtained in Therapeutically Applicable Research to Generate Effective Treatments (TARGET), a database of pediatric tumors. Secondary data was collected from the Gene Expression Omnibus (GEO) to test the observations. In univariate Cox regre ...[more]

PMID: 33986802

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Project description:BackgroundThe immune response in the bone marrow microenvironment has implications for progression and prognosis in acute myeloid leukemia (AML). However, few immune-related biomarkers for AML prognosis and immunotherapy response have been identified. We aimed to establish a predictive gene signature and to explore the determinants of prognosis in AML.MethodsImmune-related genes with clinical significance were screened by a weighted gene co-expression network analysis. Seven immune-related genes were used to establish a gene signature by a multivariate Cox regression analysis. Based on the signature, low- and high-risk groups were compared with respect to the immune microenvironment, immune checkpoints, pathway activities, and mutation frequencies. The tumor immune dysfunction and exclusion (TIDE) method was used to predict the response to immune checkpoint blockade (ICB) therapy. The Connectivity Map database was used to explore small-molecule drugs expected to treat high-risk populations.ResultsA seven-gene prognostic signature was used to classify patients into high- and low-risk groups. Prognosis was poorer for patients in the former than in the latter. The high-risk group displayed higher levels of immune checkpoint molecules (LAG3, PD-1, CTLA4, PD-L2, and PD-L1), immune cell infiltration (dendritic cells, T helper 1, and gamma delta T), and somatic mutations (NPM1 and RUNX1). Moreover, hematopoietic stem cell/leukemia stem cell pathways were enriched in the high-risk phenotype. Compared with that in the low-risk group, the lower TIDE score for the high-risk group implied that this group is more likely to benefit from ICB therapy. Finally, some drugs (FLT3 inhibitors and BCL inhibitors) targeting the expression profiles associated with the high-risk group were generated using Connectivity Map.ConclusionThe newly developed immune-related gene signature is an effective biomarker for predicting prognosis in AML and provides a basis, from an immunological perspective, for the development of comprehensive therapeutic strategies.

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Dataset Information

An Immune Checkpoint-Related Gene Signature for Predicting Survival of Pediatric Acute Myeloid Leukemia.

Objective

Methods

Results

Conclusion

Publications

An Immune Checkpoint-Related Gene Signature for Predicting Survival of Pediatric Acute Myeloid Leukemia.

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