Nanostring-based multigene assay to predict recurrence for gastric cancer patients after surgery.

Published

Journal Article

Despite the benefits from adjuvant chemotherapy or chemoradiotherapy, approximately one-third of stage II gastric cancer (GC) patients developed recurrences. The aim of this study was to develop and validate a prognostic algorithm for gastric cancer (GCPS) that can robustly identify high-risk group for recurrence among stage II patients. A multi-step gene expression profiling study was conducted. First, a microarray gene expression profiling of archived paraffin-embedded tumor blocks was used to identify candidate prognostic genes (N=432). Second, a focused gene expression assay including prognostic genes was used to develop a robust clinical assay (GCPS) in stage II patients from the same cohort (N=186). Third, a predefined cut off for the GCPS was validated using an independent stage II cohort (N=216). The GCPS was validated in another set with stage II GC who underwent surgery without adjuvant treatment (N=300). GCPS was developed by summing the product of Cox regression coefficients and normalized expression levels of 8 genes (LAMP5, CDC25B, CDK1, CLIP4, LTB4R2, MATN3, NOX4, TFDP1). A prospectively defined cut-point for GCPS classified 22.7% of validation cohort treated with chemoradiotherapy (N=216) as high-risk group with 5-year recurrence rate of 58.6% compared to 85.4% in the low risk group (hazard ratio for recurrence=3.16, p=0.00004). GCPS also identified high-risk group among stage II patients treated with surgery only (hazard ratio=1.77, p=0.0053).

Full Text

Duke Authors

Cited Authors

  • Lee, J; Sohn, I; Do, I-G; Kim, K-M; Park, SH; Park, JO; Park, YS; Lim, HY; Sohn, TS; Bae, JM; Choi, MG; Lim, DH; Min, BH; Lee, JH; Rhee, PL; Kim, JJ; Choi, DI; Tan, IB; Das, K; Tan, P; Jung, SH; Kang, WK; Kim, S

Published Date

  • January 2014

Published In

Volume / Issue

  • 9 / 3

Start / End Page

  • e90133 -

PubMed ID

  • 24598828

Pubmed Central ID

  • 24598828

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

International Standard Serial Number (ISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0090133

Language

  • eng