Clinically applicable 53-Gene prognostic assay predicts chemotherapy benefit in gastric cancer: A multicenter study

Abstract

Background We previously established a 53-gene prognostic signature for overall survival (OS) of gastric cancer patients. This retrospective multi-center study aimed to develop a clinically applicable gene expression detection assay and to investigate the prognostic value of this signature. Methods A TCGA gastric adenocarcinoma cohort (TCGA-STAD) was used for comparing 53-gene signature with other gene signatures. A high-throughput mRNA hybridization gene expression assay was developed to quantify the expression of 53-genes in formalin-fixed paraffin-embedded tissues of 540 patients enrolled from three hospitals. 180 patents were randomly selected from two hospitals to build a prognostic prediction model based on the 53-gene signature using leave-p-out (one-third out) cross-validation method together with Cox regression and Kaplan-Meier analysis, and the model was assessed on three validation cohorts. Findings In the evaluation phase, studies based on TCGA-STAD showed that the 53-gene signature was significantly superior to other three prognostic signatures and was independent of TCGA molecular subtypes and clinical factors. For clinical validation and utility, the prognostic scores were generated using the newly developed assay, which was reliable and sensitive, in 100 sampling training sets and were significantly associated with OS in 100 sampling validation sets. The scores were significantly associated with OS in three independent and combined validation cohorts, and in patients with stages II and III/IV. The multivariate Cox regression demonstrated that the prognostic power of the score was independent of clinical factors, consistent with those findings in the TCGA dataset. Finally, patients with good prognostic scores exhibited significantly a better 5-year OS rate from adjuvant FOLFOX chemotherapy after surgery than from other chemotherapies. Interpretation The 53-gene prognostic score system is clinically applicable for predicting the OS of patients independent of clinical factors in gastric cancers, which could also be a promising predictive biomarker for FOLFOX regimen. Funding Chinese National Science and Technology, National Natural Science Foundation and Natural Science Foundation of Jiangsu Province.

FHOD1 is upregulated in gastric cancer and promotes the proliferation and invasion of gastric cancer cells

“…The expression level of FHOD1 between normal gastric and GC tissues were compared. The gene expression data used to analyze the association between FHOD1 expression and the overall survival rate of patients with GC were obtained from our previous cohort study (Nanjing Drum Tower Hospital; Nanjing, China) on the multigene prognostic signature in GC (18).…”

“…Prognostic value of FHOD1 expression for patients with GC was assessed using Kaplan-Meier analysis. Original expression level data were from our previous panomics-based experiments (18). GC, gastric cancer; FHOD1, formin homology 2 domain containing 1; HR, hazard ratio.…”

“…In order to further evaluate the significance of FHOD1 in the development of GC, Kaplan-Meier analysis was performed on the transcriptome data of 203 patients with GC, which were obtained from our previous study using the Panomics technique designed to evaluate the prognostic value of a multigene panel for patients with GC in a hospital cohort (18).…”

Identification of a novel 15‐gene expression signature predicting overall survival of human colorectal cancer

“…However, there is still an urgent need to develop better and more robust gene signatures in this area. In this study, we developed a clinically applicable and robust prognostic signature for CRC patients using our multistep bioinformatics analysis strategy 5–8 …”

“…In this study, we developed a clinically applicable and robust prognostic signature for CRC patients using our multistep bioinformatics analysis strategy. [5][6][7][8] For our gene expression signature development, we first identified 738 genes (971 gene probe IDs) that were consistently deregulated in CRC versus normal colon tissue in six transcriptome datasets ( Figure 1A and B, Figure S1A, Table S1). Kaplan-Meier survival analysis together with Cox regression was used to evaluate whether their expression levels were associated with overall survival (OS) in GSE17536 dataset.…”