Evidence map›Paper›PMID 39506437›Full record

ArticleCurrent medicinal chemistry2026

An Innovative Telomere-associated Prognosis Model in AML: Predicting Immune Infiltration and Treatment Responsiveness.

Binyang Song, Jinzhan Lou, Lijun Mu, Xiao Lu, Jian Sun, Bo Tang

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Article in Current medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Binyang SongDepartment of Hematology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China.
Jinzhan LouDepartment of Hematology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China.
Lijun MuDepartment of Hematology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China.
Xiao LuDepartment of Hematology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China.
Jian SunDepartment of Hematology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China.
Bo TangDepartment of Hematology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People's Republic of China.ORCID 0000-0002-0909-3034

Funding

Doctoral Startup Scientific Research Foundation of Liaoning Province 20180540088National Natural Science Foundation of China 81800203
6 · The paper itself

Abstract

aimsTo build an innovative telomere-associated scoring model to predict prognosis and treatment responsiveness in acute myeloid leukemia (AML).

backgroundAML is a highly heterogeneous malignant hematologic disorder with a poor prognosis. While telomere maintenance is frequently observed in tumors, investigations into telomere-related genes (TRGs) in AML remain limited.

objectivesThis study aimed to identify prognostic TRGs using the least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression, evaluate their predictive value, explore the association between TRG scores and immune cell infiltration, and assess the sensitivity of high-scoring AML patients to chemotherapeutic agents.

methodsUnivariate Cox regression analysis was conducted on the TCGA cohort to identify prognostic TRGs and to develop the TRG scoring model using LASSO-Cox and multivariate Cox regression. Validation was performed on the GSE37642 cohort. Immune cell infiltration patterns were assessed through computational analysis, and the sensitivity to chemotherapeutic agents was evaluated.

resultsThirteen prognostic TRGs were identified, and a seven-TRG scoring model (including NOP10, OBFC1, PINX1, RPA2, SMG5, MAPKAPK5, and SMN1) was developed. Higher TRG scores were associated with a poorer prognosis, as confirmed in the GSE37642 cohort, and remained an independent prognostic factor even after adjusting for other clinical characteristics. The high-score group was characterized by elevated infiltration of B cells, T helper cells, natural killer cells, tumor-infiltrating lymphocytes, regulatory T (Treg) cells, M2 macrophages, neutrophils, and monocytes, along with reduced infiltration of gamma delta T cells, CD4- T cells, and resting mast cells. Moreover, high infiltration of M2 macrophages and Tregs was associated with poor overall survival compared to low infiltration. Notably, high-risk AML patients were resistant to Erlotinib, Parthenolide, and Nutlin-3a, but sensitive to AC220, Midostaurin, and Tipifarnib. Additionally, using RT-qPCR, we observed significantly higher expression of two model genes, OBFC1 and SMN1, in AML tissues compared to control tissues.

conclusionThis innovative TRG scoring model demonstrates considerable predictive value for AML patient prognosis, offering valuable insights for optimizing treatment strategies and personalized medicine approaches. The identified TRGs and associated scoring models could aid in risk stratification and guide tailored therapeutic interventions in AML patients.

Indexed as

Antineoplastic AgentsLeukemia, Myeloid, AcuteTelomereFemaleHumansMaleMiddle AgedPrognosisAntineoplastic AgentsAcute myeloid leukemiadrug sensitivityimmune infiltrationOBFC1prognostic modelSMN1.telomere-related genes

Identifiers

PMID39506437

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