Inflammatory and microRNA gene expression as prognostic classifier of Barrett's-associated esophageal adenocarcinoma

Esophageal cancer is one of the most aggressive and deadly forms of cancer; highlighting the need to identify biomarkers for early detection and prognostic classification. Our recent studies have identified inflammatory gene and microRNA signatures derived from tumor and nontumor tissues as prognostic biomarkers of hepatocellular, lung, and colorectal adenocarcinoma. Here, we examine the relationship between expression of these inflammatory genes and micro RNA (miRNA) expression in esophageal adenocarcinoma and patient survival.

We measured the expression of 23 inflammation-associated genes in tumors and adjacent normal tissues from 93 patients (58 Barrett's and 35 Sporadic adenocarcinomas) by quantitative reverse transcription-polymerase chain reaction. These data were used to build an inflammatory risk model, based on multivariate Cox regression, to predict survival in a training cohort (n = 47). We then determined whether this model could predict survival in a cohort of 46 patients. Expression data for miRNA-375 were available for these patients and was combined with inflammatory gene expression.

IFN-γ, IL-1α, IL-8, IL-21, IL-23, and proteoglycan expression in tumor and nontumor samples were each associated with poor prognosis based on Cox regression [(Z-score)>1.5] and therefore were used to generate an inflammatory risk score (IRS). Patients with a high IRS had poor prognosis compared with those with a low IRS in the training (P = 0.002) and test (P = 0.012) cohorts. This association was stronger in the group with Barrett's history. When combining with miRNA-375, the combined IRS/miR signature was an improved prognostic classifier than either one alone.

Transcriptional profiling of inflammation-associated genes and miRNA expression in resected esophageal Barrett's-associated adenocarcinoma tissues may have clinical utility as predictors of prognosis.