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Immune prognostic risk score model in acute myeloid leukemia with normal karyotype.
Dong, Xiaomin; Zhang, Danyang; Zhang, Juan; Chen, Xiaolei; Zhang, Yue; Zhang, Yong; Zhou, Xiaohuan; Chen, Tingting; Zhou, Hebing.
Affiliation
  • Dong X; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Zhang D; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Zhang J; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Chen X; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Zhang Y; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Zhang Y; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Zhou X; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Chen T; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
  • Zhou H; Department of Hematology, The Affiliated Beijing Luhe Hospital of Capital Medical University, Beijing 101149, P.R. China.
Oncol Lett ; 20(6): 380, 2020 Dec.
Article in En | MEDLINE | ID: mdl-33154778
ABSTRACT
Acute myeloid leukemia with normal karyotype (NK-AML) is a group of diseases with high heterogeneity and immunological processes are significantly associated with its initiation and development. The implication of the immunogenomic landscape in the prognosis of patients with NK-AML has remained largely elusive. In the present study, the expression profiles of immune-related genes (IRGs) were examined and their association with overall survival (OS) was determined in 60 patients with NK-AML from The Cancer Genome Atlas dataset and 104 patients from the Gene Expression Omnibus (GEO) dataset no. GSE71014. Univariate Cox regression analysis was used to identify 42 and 203 IRGs in the two respective cohorts, which were significantly associated with OS in NK-AML. A risk model was constructed based on the regression coefficient and expression values of nine survival-associated IRGs shared between the two datasets [zinc finger CCCH-type containing, antiviral 1 like; transferrin receptor; suppressor of cytokine signaling 1; ELAV like RNA binding protein 1; roundabout guidance receptor 3; unc-93 homolog B1, Toll-like receptor signaling regulator; protein tyrosine phosphatase non-receptor type 6; interleukin 2 receptor subunit alpha (IL2RA) and IL3RA]. Using this risk model, patients with NK-AML may be divided into high- and low-risk groups in prognostic predictions. The area under the receiver operating characteristic curve for predicting OS was 0.793. The prognostic role of this risk model was successfully verified in another independent cohort (GEO dataset no. GSE71014). The prognostic risk score was positively associated with age and fms related receptor tyrosine kinase 3 mutation and correlated with infiltration by T regulatory cells. In conclusion, the results of the present study provided an IRG score model for prognostic stratification of adult patients with NK-AML, as well as further insight into the implication of IRGs in NK-AML that may lead to the development of novel immunotherapy approaches for this disease.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Oncol Lett Year: 2020 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Oncol Lett Year: 2020 Document type: Article