Screening the Cancer Genome Atlas Database for Genes of Prognostic Value in Acute Myeloid Leukemia

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Abstract

Object: To identify genes of prognostic value which associated with tumor microenvironment (TME) in acute myeloid leukemia (AML).

Methods and Materials: Level 3 AML patients gene transcriptome profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Clinical characteristics and survival data were extracted from the Genomic Data Commons (GDC) tool. Then, limma package was utilized for normalization processing. ESTIMATE algorithm was used for calculating immune, stromal and ESTIMATE scores. We examined the distribution of these scores in Cancer and Acute Leukemia Group B (CALGB) cytogenetics risk category. Kaplan-Meier (K-M) curves were used to evaluate the relationship between immune scores, stromal scores, ESTIMATE scores and overall survival. We performed clustering analysis and screened differential expressed genes (DEGs) by using heatmaps, volcano plots and Venn plots. After pathway enrichment analysis and gene set enrichment analysis (GESA), protein-protein interaction (PPI) network was constructed and hub genes were screened. We explore the prognostic value of hub genes by calculating risk scores (RS) and processing survival analysis. Finally, we verified the expression level, association of overall survival and gene interactions of hub genes in the Vizome database.

Results: We enrolled 173 AML samples from TCGA database in our study. Higher immune score was associated with higher risk rating in CALGB cytogenetics risk category ( P = 0.0396) and worse overall survival outcomes ( P = 0.0224). In Venn plots, 827 intersect genes were screened with differential analysis. Functional enrichment clustering analysis revealed a significant association between intersect genes and the immune response. After PPI network, 18 TME-related hub genes were identified. RS was calculated and the survival analysis results revealed that high RS was related with poor overall survival ( P < 0.0001). Besides, the survival receiver operating characteristic curve (ROC) showed superior predictive accuracy (area under the curve = 0.725). Finally, the heatmap from Vizome database demonstrated that 18 hub genes showed high expression in patient samples.

Conclusion: We identified 18 TME-related genes which significantly associated with overall survival in AML patients from TCGA database.

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Most cited references 32

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Tumor refractoriness to anti-VEGF treatment is mediated by CD11b+Gr1+ myeloid cells.

Farbod Shojaei, Xiumin Wu, Ajay K. Malik … (2007)

Vascular endothelial growth factor (VEGF) is an essential regulator of normal and abnormal blood vessel growth. A monoclonal antibody (mAb) that targets VEGF suppresses tumor growth in murine cancer models and human patients. We investigated cellular and molecular events that mediate refractoriness of tumors to anti-angiogenic therapy. Inherent anti-VEGF refractoriness is associated with infiltration of the tumor tissue by CD11b+Gr1+ myeloid cells. Recruitment of these myeloid cells is also sufficient to confer refractoriness. Combining anti-VEGF treatment with a mAb that targets myeloid cells inhibits growth of refractory tumors more effectively than anti-VEGF alone. Gene expression analysis in CD11b+Gr1+ cells isolated from the bone marrow of mice bearing refractory tumors reveals higher expression of a distinct set of genes known to be implicated in active mobilization and recruitment of myeloid cells. These findings indicate that, in our models, refractoriness to anti-VEGF treatment is determined by the ability of tumors to prime and recruit CD11b+Gr1+ cells.

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Tumor necrosis factor-α blocks differentiation and enhances suppressive activity of immature myeloid cells during chronic inflammation.

Moshe Sade-Feldman, Julia Kanterman, Eliran Ish-Shalom … (2013)

Elevated concentrations of tumor necrosis factor-α (TNF-α) are detected in pathologies characterized by chronic inflammation. Whether TNF-α plays a role in manipulating the host's immune system toward generating an immunosuppressive milieu, typical of ongoing chronic inflammation, is unclear. Here we showed that TNF-α exhibited a dual function during chronic inflammation: arresting differentiation of immature myeloid-derived suppressor cells (MDSCs) primarily via the S100A8 and S100A9 inflammatory proteins and their corresponding receptor (RAGE) and augmenting MDSC suppressive activity. These functions led to in vivo T and NK cell dysfunction accompanied by T cell antigen receptor ζ chain downregulation. Furthermore, administration of etanercept (TNF-α antagonist) during early chronic inflammatory stages reduced MDSCs' suppressive activity and enhanced their maturation into dendritic cells and macrophages, resulting in the restoration of in vivo immune functions and recovery of ζ chain expression. Thus, TNF has a fundamental role in promoting an immunosuppressive environment generated during chronic inflammation. Copyright © 2013 Elsevier Inc. All rights reserved.

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Costimulatory and coinhibitory receptors in anti-tumor immunity.

Gregory Driessens, Thomas Gajewski, Justin Kline (2009)

Despite the expression of antigens by tumor cells, spontaneous immune-mediated rejection of cancer seems to be a rare event. T-cell receptor engagement by peptide/major histocompatibility complexes constitutes the main signal for the activation of naive T cells but is not sufficient to initiate a productive generation and maintenance of effector cells. Full activation of T cells requires additional signals driven by costimulatory molecules present on activated antigen-presenting cells but rarely on tumors. Following the discovery of B7-1 (CD80), several other costimulatory molecules have been shown to contribute to T-cell activation and have relevance for improving anti-tumor immunity. Moreover, increasing the understanding of coinhibitory receptors has highlighted key additional pathways that can dominantly inhibit anti-tumor T-cell function. Improving positive costimulation, and interfering with negative regulation, continues to represent an attractive immunotherapeutic approach for the treatment of cancer. This review focuses upon those pathways with the highest potential for clinical application in human cancer patients.

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Author and article information

Contributors

Jie Ni: URI : http://loop.frontiersin.org/people/879719/overview

Yang Wu: URI : http://loop.frontiersin.org/people/872032/overview

Feng Qi: URI : http://loop.frontiersin.org/people/879717/overview

Xiao Li: URI : http://loop.frontiersin.org/people/717969/overview

Shaorong Yu: URI : http://loop.frontiersin.org/people/879741/overview

Siwen Liu: URI : http://loop.frontiersin.org/people/807046/overview

Jifeng Feng: URI : http://loop.frontiersin.org/people/802066/overview

Yuxiao Zheng: URI : http://loop.frontiersin.org/people/718356/overview

Journal

Journal ID (nlm-ta): Front Oncol

Journal ID (iso-abbrev): Front Oncol

Journal ID (publisher-id): Front. Oncol.

Title: Frontiers in Oncology

Publisher: Frontiers Media S.A.

ISSN (Electronic): 2234-943X

Publication date (Electronic): 21 January 2020

Publication date Collection: 2019

Volume: 9

Electronic Location Identifier: 1509

Affiliations

[1] ¹Department of Medical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University , Nanjing, China

[2] ²Research Center for Clinical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University , Nanjing, China

[3] ³Department of Urology, The First Affiliated Hospital of Nanjing Medical University , Nanjing, China

[4] ⁴Department of Urology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University , Nanjing, China

Author notes

Edited by: Marcos De Lima, Case Western Reserve University, United States

Reviewed by: Pier Paolo Piccaluga, University of Bologna, Italy; Rehan Khan, Mayo Clinic Arizona, United States

*Correspondence: Jifeng Feng jifeng_feng@ 123456163.com

Yuxiao Zheng zheng_yuxiao@ 123456163.com

This article was submitted to Hematologic Malignancies, a section of the journal Frontiers in Oncology

†These authors have contributed equally to this work

Article

DOI: 10.3389/fonc.2019.01509

PMC ID: 6990132

PubMed ID: 32039005

SO-VID: fa3b4366-0f17-4346-8237-a6689373c2f0

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 23 September 2019

Date accepted : 16 December 2019

Page count

Figures: 8, Tables: 1, Equations: 0, References: 60, Pages: 13, Words: 6594

Funding

Funded by: National Natural Science Foundation of China 10.13039/501100001809

Award ID: 81570186

Award ID: 81871873

Funded by: Jiangsu Provincial Key Research and Development Program 10.13039/501100013058

Screening the Cancer Genome Atlas Database for Genes of Prognostic Value in Acute Myeloid Leukemia

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Journal of Circulating Biomarkers

Most cited references 32

Tumor refractoriness to anti-VEGF treatment is mediated by CD11b+Gr1+ myeloid cells.

Tumor necrosis factor-α blocks differentiation and enhances suppressive activity of immature myeloid cells during chronic inflammation.

Costimulatory and coinhibitory receptors in anti-tumor immunity.

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