Identification of predictive pathways for non-Hodgkin lymphoma prognosis

Xuesong Han, Yang Li, Jian Huang, Yawei Zhang, Theodore Holford, Qing Lan, Nathaniel Rothman, Tongzhang Zheng, Michael R. Kosorok, Shuangge Ma

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

Despite decades of intensive research, NHL (non-Hodgkin lymphoma) still remains poorly understood and is largely incurable. Recent molecular studies suggest that genomic variants measured with SNPs (single nucleotide polymorphisms) in genes may have additional predictive power for NHL prognosis beyond clinical risk factors. We analyzed a genetic association study. The prognostic cohort consisted of 346 patients, among whom 138 had DLBCL (diffuse large B-cell lymphoma) and 101 had FL (follicular lymphoma). For DLBCL, we analyzed 1229 SNPs which represented 122 KEGG pathways. For FL, we analyzed 1228 SNPs which represented 122 KEGG pathways. Unlike in existing studies, we targeted at identifying pathways with significant additional predictive power beyond clinical factors. In addition, we accounted for the joint effects of multiple SNPs within pathways, whereas some existing studies drew pathway-level conclusions based on separate analysis of individual SNPs. For DLBCL, we identified four pathways, which, combined with the clinical factors, had medians of the prediction logrank statistics as 2.535, 2.220, 2.094, 2.453, and 2.512, respectively. As a comparison, the clinical factors had a median of the prediction logrank statistics around 0.552. For FL, we identified two pathways, which, combined with the clinical factors, had medians of the prediction logrank statistics as 4.320 and 3.532, respectively. As a comparison, the clinical factors had a median of the prediction logrank statistics around 1.212. For NHL overall, we identified three pathways, which, combined with the clinical factors, had medians of the prediction logrank statistics as 5.722, 5.314, and 5.441, respective. As a comparison, the clinical factors had a median of the prediction logrank statistics around 4.411. The identified pathways have sound biological bases. In addition, they are different from those identified using existing approaches. They may provide further insights into the biological mechanisms underlying the prognosis of NHL.
Original languageEnglish
Pages (from-to)281-292
Number of pages12
JournalCancer Informatics
Volume9
DOIs
Publication statusPublished - 30 Dec 2010
Externally publishedYes

Keywords

  • NHL prognosis
  • Pathway analysis
  • Prediction
  • SNP data

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this