Lymphoid gene expression as a predictor of risk of secondary brain tumors.
Gene expression profiles are tissue-specific but may also reflect germ-line-driven expression patterns across tissue types. Previously, using a targeted pharmacologic approach, we identified germ-line polymorphisms in a single gene (thiopurine methyltransferase) associated with the risk of irradiation- and chemotherapy-induced secondary brain tumors in children with acute lymphoblastic leukemia (ALL). To identify additional candidate genetic risk factors, in identically treated patients, we compared the gene expression profiles of diagnostic ALL blasts of those who did develop irradiation-associated brain tumors (n = 9) with the profiles from those who did not (n = 33). Weighted rank regression was used to identify 33 probe sets associated with the time-dependent development of brain tumors; k-means clustering (k = 2) identified 2 groups that differed significantly in cumulative incidence of brain tumors (P = 0.012). Permutation analysis was used to estimate the probability (P = 0.18) of obtaining 2 such clusters by chance. Linear discriminant analysis (time-independent categorization of outcome) was used to identify 70 probe sets whose expression differentiated between the 2 groups of patients. Permutation analyses (n = 1,000) was used to estimate the probability of selecting these probe sets by chance (P = 0.055). Five probe sets were in common between the time-independent and time-dependent methods. The distinguishing genes are involved in neural growth (FGFR1) and in nuclear trafficking (HNRPL, KPNB1). These data suggest that gene expression profiling from accessible tissues may identify targets involved in therapy-related malignancies in unrelated tissues.
Edick
Mathew J
MJ
Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, University of Tennessee, Memphis, Tennessee, USA.
Cheng
Cheng
C
Yang
Wenjian
W
Cheok
Meyling
M
Wilkinson
Mark R
MR
Pei
Deqing
D
Evans
William E
WE
Kun
Larry E
LE
Pui
Ching-Hon
CH
Relling
Mary V
MV
D000293:Adolescent; D001932:Brain Neoplasms / Q000209:etiology / Q000235:genetics* / Q000532:radiotherapy; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D019295:Computational Biology / Q000706:statistics & numerical data; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods* / Q000706:statistics & numerical data; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D006801:Humans; D007223:Infant; D008297:Male; D009381:Neoplasms, Radiation-Induced / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000706:statistics & numerical data; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000235:genetics / Q000532:radiotherapy; D011237:Predictive Value of Tests