Development and validation of a 10-gene prognostic signature for acute myeloid leukaemia.

Journal of Cellular and Molecular Medicine
Zuyi YangXiaohui Chen

Abstract

Acute myeloid leukaemia (AML) is the most common type of adult acute leukaemia and has a poor prognosis. Thus, optimal risk stratification is of greatest importance for reasonable choice of treatment and prognostic evaluation. For our study, a total of 1707 samples of AML patients from three public databases were divided into meta-training, meta-testing and validation sets. The meta-training set was used to build risk prediction model, and the other four data sets were employed for validation. By log-rank test and univariate COX regression analysis as well as LASSO-COX, AML patients were divided into high-risk and low-risk groups based on AML risk score (AMLRS) which was constituted by 10 survival-related genes. In meta-training, meta-testing and validation sets, the patient in the low-risk group all had a significantly longer OS (overall survival) than those in the high-risk group (P < .001), and the area under ROC curve (AUC) by time-dependent ROC was 0.5854-0.7905 for 1 year, 0.6652-0.8066 for 3 years and 0.6622-0.8034 for 5 years. Multivariate COX regression analysis indicated that AMLRS was an independent prognostic factor in four data sets. Nomogram combining the AMLRS and two clinical parameters performed well in predict...Continue Reading

References

Apr 30, 2004·The New England Journal of Medicine·Izidore S LossosRonald Levy
Nov 10, 2004·Clinical Cancer Research : an Official Journal of the American Association for Cancer Research·Robert L CampDavid L Rimm
Feb 16, 2006·Proceedings of the National Academy of Sciences of the United States of America·Jerald P RadichPeter S Linsley
Mar 31, 2006·Current Topics in Microbiology and Immunology·T Chen, E Li
Sep 5, 2008·Leukemia·H QuentmeierH G Drexler
Aug 30, 2011·Nature Medicine·Kolja EppertJohn E Dick
Feb 6, 2013·Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology·Zejuan LiJianjun Chen
Feb 13, 2013·Lancet·Felicetto Ferrara, Charles A Schiffer
Jun 22, 2013·British Journal of Haematology·Anjali ShahPaul C Lambert
Jun 23, 2015·Cancer·Dolores A GrossoMark A Weiss
Jan 6, 2016·Blood·Isabell SchulzeCarsten Müller-Tidow
Jan 24, 2016·Annals of Oncology : Official Journal of the European Society for Medical Oncology·T M KadiaH Kantarjian
Mar 1, 2011·Journal of Statistical Software·Noah SimonRob Tibshirani
May 22, 2016·Bioinformatics·Zuguang GuMatthias Schlesner
Jul 2, 2016·Blood Cancer Journal·I De Kouchkovsky, M Abdul-Hay
Nov 23, 2017·Cell Reports·Marta MorenoNúria de la Iglesia
Jun 30, 2018·International Journal of Molecular Medicine·Xiaoyan ZhaoHaibing Wu
Jul 11, 2018·Nature·Sagi AbelsonLiran I Shlush
Aug 7, 2018·Lancet·Nicholas J ShortJorge E Cortes
Aug 24, 2018·Frontiers in Oncology·Kuan-Yeh Huang, Hsi-Hsien Lin

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Methods Mentioned

BETA
PCA
TARGET

Software Mentioned

R package glmnet
AMLRS
LASSO COX
SPSS
COX
LASSO
R package sva
survminer
ComplexHeatmap
gmodels

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