In November 2023, a study led by Professor XiaoFan Zhu from Chinese Academy of Medical Sciences Blood Disease Hospital (Institute of Hematology, Chinese Academy of Medical Sciences) was published in the international academic journal ——Open Medicine(Wars). The title of the study is "Establishing a novel Fanconi anemia signaling pathway-associated prognostic model and tumor clustering for pediatric acute myeloid leukemia patients". This study heralds the establishment of a novel prognostic model and tumor clustering approach tailored specifically for pediatric AML, anchored in the FA signaling pathway.Acute myeloid leukemia (AML) constitutes a heterogeneous hematological malignancy characterized by a myriad of genetic mutations, cytogenetic abnormalities, and diverse gene expression profiles. Accurate prognostic stratification is paramount for tailoring personalized treatment strategies and optimizing therapeutic outcomes for AML patients. Despite the existence of several prognostic models, the pediatric AML population lacks tailored prognostic tools based on gene expression patterns. Addressing this gap, this study endeavors to establish a novel prognostic model and tumor clustering approach specifically for pediatric AML, utilizing insights from the Fanconi anemia (FA) signaling pathway.
The investigation commenced with a comprehensive analysis of the expression profiles of 23 key FA genes alongside clinical characteristics, leveraging combined datasets from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA)-AML cohorts. Subsequently, tumor clustering analysis was performed using the ConsensusClusterPlus R package to delineate distinct subgroups within the pediatric AML cohort. Employing Lasso regression modeling analysis, samples were stratified into high- and low-risk groups based on calculated risk scores. The prognostic significance of these risk groups was evaluated through Cox regression analysis of overall survival (OS). Furthermore, gene enrichment and diffusion analyses were conducted to elucidate the functional implications of differentially expressed genes.
Analysis of FA gene expression profiles unveiled two distinct clusters within the pediatric AML population. Building upon this insight, a robust prognostic model was devised, incorporating five pivotal FA hub genes: BRIP1, FANCC, FANCL, MAD2L2, and RFWD3. Remarkably, the high-risk group exhibited a significantly poorer prognosis in terms of OS compared to their low-risk counterparts. The validity and reliability of the prognostic model were further confirmed through external validation using an independent dataset, reaffirming its clinical utility. Additionally, gene enrichment analysis unveiled associations between FA-related high/low-risk groups or clusters and critical biological processes such as DNA repair mechanisms, cell cycle regulation, and peroxide-related metabolic events, providing valuable mechanistic insights into pediatric AML pathogenesis.
（Open Med (Wars) . 2023 Nov 9;18(1):20230847.）
This pioneering study heralds the establishment of a novel prognostic model and tumor clustering approach tailored specifically for pediatric AML, anchored in the FA signaling pathway. By integrating gene expression profiles with clinical data, the developed prognostic model not only demonstrates robust predictive accuracy for OS but also holds promise for refining prognostic stratification and enhancing therapeutic decision-making in pediatric AML management. The elucidation of distinct molecular subgroups and their associated biological processes underscores the intricate interplay between FA pathway dysregulation and pediatric AML pathogenesis. Moving forward, the integration of such tailored prognostic models and clustering techniques into clinical practice has the potential to revolutionize risk stratification and treatment optimization, ultimately improving outcomes for pediatric AML patients.
