Integrative analysis with machine learning identifies diagnostic and prognostic signatures in neuroblastoma based on differentially DNA methylated enhancers between INSS stage 4 and 4S neuroblastoma

作者全名："Li, Shan; Mi, Tao; Jin, Liming; Liu, Yimeng; Zhang, Zhaoxia; Wang, Jinkui; Wu, Xin; Ren, Chunnian; Wang, Zhaoying; Kong, Xiangpan; Liu, Jiayan; Luo, Junyi; He, Dawei"

作者地址："[Li, Shan; Mi, Tao; Jin, Liming; Liu, Yimeng; Zhang, Zhaoxia; Wang, Jinkui; Wu, Xin; Ren, Chunnian; Wang, Zhaoying; Kong, Xiangpan; Liu, Jiayan; Luo, Junyi; He, Dawei] Chongqing Med Univ, Childrens Hosp, Dept Urol, 136,Zhongshan 2nd Rd, Chongqing 400014, Peoples R China; [Li, Shan; Mi, Tao; Jin, Liming; Liu, Yimeng; Zhang, Zhaoxia; Wang, Jinkui; Wu, Xin; Ren, Chunnian; Wang, Zhaoying; Kong, Xiangpan; Liu, Jiayan; Luo, Junyi; He, Dawei] Chongqing Key Lab Children Urogenital Dev & Tissue, Chongqing 400014, Peoples R China; [Li, Shan; Mi, Tao; Jin, Liming; Liu, Yimeng; Zhang, Zhaoxia; Wang, Jinkui; Wu, Xin; Ren, Chunnian; Wang, Zhaoying; Kong, Xiangpan; Liu, Jiayan; Luo, Junyi; He, Dawei] Chongqing Med Univ, Childrens Hosp,Chongqing Key Lab Pediat, Natl Clin Res Ctr Child Hlth & Disorders,Minist Ed, China Int Sci & Technol Cooperat Base Child Dev &, Chongqing 400014, Peoples R China"

通信作者："He, DW (通讯作者)，Chongqing Med Univ, Childrens Hosp, Dept Urol, 136,Zhongshan 2nd Rd, Chongqing 400014, Peoples R China.; He, DW (通讯作者)，Chongqing Key Lab Children Urogenital Dev & Tissue, Chongqing 400014, Peoples R China.; He, DW (通讯作者)，Chongqing Med Univ, Childrens Hosp,Chongqing Key Lab Pediat, Natl Clin Res Ctr Child Hlth & Disorders,Minist Ed, China Int Sci & Technol Cooperat Base Child Dev &, Chongqing 400014, Peoples R China."

来源：JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001190600700002

JCR分区：Q3

影响因子：2.7

年份：2024

卷号：150

期号：3

开始页：　

结束页：　

文献类型：Article

关键词：Neuroblastoma; Machine learning; Prognostic prediction; DNA methylation; Single-cell analysis

摘要："Introduction Accumulating evidence demonstrates that aberrant methylation of enhancers is crucial in gene expression profiles across several cancers. However, the latent effect of differently expressed enhancers between INSS stage 4S and 4 neuroblastoma (NB) remains elusive.Methods We utilized the transcriptome and methylation data of stage 4S and 4 NB patients to perform Enhancer Linking by Methylation/Expression Relationships (ELMER) analysis, discovering a differently expressed motif within 67 enhancers between stage 4S and 4 NB. Harnessing the 67 motif genes, we established the INSS stage related signature (ISRS) by amalgamating 12 and 10 distinct machine learning (ML) algorithms across 113 and 101 ML combinations to precisely diagnose stage 4 NB among all NB patients and to predict the prognosis of NB patients. Based on risk scores calculated by prognostic ISRS, patients were categorized into high and low-risk groups according to median risk score. We conducted comprehensive comparisons between two risk groups, in terms of clinical applications, immune microenvironment, somatic mutations, immunotherapy, chemotherapy and single-cell analysis. Ultimately, we empirically validated the differential expressions of two ISRS model genes, CAMTA2 and FOXD1, through immunochemistry staining.Results Through leave-one-out cross-validation, in both feature selection and model construction, we selected the random forest algorithm to diagnose stage 4 NB, and Enet algorithm to develop prognostic ISRS, due to their highest average C-index across five NB cohorts. After validations, the ISRS demonstrated a stable predictive capability, outperforming the previously published NB signatures and several clinic variables. We stratified NB patients into high and low-risk group based on median risk score, which showed the low-risk group with a superior survival outcome, an abundant immune infiltration, a decreased mutation landscape, and an enhanced sensitivity to immunotherapy. Single-cell analysis between two risk groups reveals biologically cellular variations underlying ISRS. Finally, we verified the significantly higher protein levels of CAMTA2 and FOXD1 in stage 4S NB, as well as their protective prognosis value in NB.Conclusion Based on multi-omics data and ML algorithms, we successfully developed the ISRS to enable accurate diagnosis and prognostic stratification in NB, which shed light on molecular mechanisms of spontaneous regression and clinical utilization of ISRS."

基金机构：Chongqing Municipal Science and Technology Bureau

基金资助正文："We sincerely thank Dr. Jianming Zeng (University of Macau), and all the members of his bioinformatics team, biotrainee, for generously sharing their experience and codes."