Tumor Endothelial Inflammation Predicts Clinical Outcome in Diverse Human Cancers

Abstract

BackgroundVascular endothelial cells contribute to the pathogenesis of numerous human diseases by actively regulating the stromal inflammatory response; however, little is known regarding the role of endothelial inflammation in the growth of human tumors and its influence on the prognosis of human cancers.MethodsUsing an experimental model of tumor necrosis factor-alpha (TNF-α)-mediated inflammation, we characterized inflammatory gene expression in immunopurified tumor-associated endothelial cells. These genes formed the basis of a multivariate molecular predictor of overall survival that was trained and validated in four types of human cancer.ResultsWe report that expression of experimentally derived tumor endothelial genes distinguished pathologic tissue specimens from normal controls in several human diseases associated with chronic inflammation. We trained these genes in human cancer datasets and defined a six-gene inflammatory signature that predicted significantly reduced overall survival in breast cancer, colon cancer, lung cancer, and glioma. This endothelial-derived signature predicted outcome independently of, but cooperatively with, standard clinical and pathological prognostic factors. Consistent with these findings, conditioned culture media from human endothelial cells stimulated by pro-inflammatory cytokines accelerated the growth of human colon and breast tumors in immunodeficient mice as compared with conditioned media from untreated endothelial cells.ConclusionsThis study provides the first prognostic cancer gene signature derived from an experimental model of tumor-associated endothelial inflammation. These findings support the notion that activation of inflammatory pathways in non-malignant tumor-infiltrating endothelial cells contributes to tumor growth and progression in multiple human cancers. Importantly, these results identify endothelial-derived factors that could serve as potential targets for therapy in diverse human cancers.

Computational prognostic indicators for breast cancer

“…As prognostic biomarkers, these models calculate a score per sample and use a simple threshold value of 1 to dichotomize patients into prognostic groups. Pitroda et al piloted a tumor endothelium-derived inflammatory signature consisting of six genes that were associated with poor outcome in multiple cancers 52. Similarly, in multiple adult tumors, we found that histologically poorly differentiated tumors display an ESC-associated expression imbalance, ie, preferential overexpression of targets of ESC-associated transcription factors ( NANOG , OCT , SOX2 , and MYC ) combined with underexpression of Polycomb-regulated genes 53.…”

“…A popular solution is to compare the median scores of a calculated indicator in a measured cohort,52 whereas adding new patients changes the estimation of median score and thus the final decision.…”

Effect of High-Fat Diet on Hepatic Proteomics of Hamsters

“…48 By using an experimental model of tumor necrosis factor-α (TNF-α)-mediated inflammation, Pitroda et al reported increased expression of ANXA3 in four types of human cancer and several human diseases associated with chronic inflammation. 49 ANXA5 is associated with the development and progression of breast cancer, prostate cancer, cervical cancer, colorectal adenocarcinoma, gastric cancer, pancreatic adenocarcinoma, sarcoma, bladder cancer, and glioma. ANXA5 is considered as a predictive marker for tumor development and a therapeutic target for early diagnosis and treatment of tumors.…”

Identifying Novel Biomarkers in Sarcoidosis Using Genome-Based Approaches

“…These high-throughput approaches have been applied to diseases of unknown cause to help understand disease pathogenesis [31-33] including identification of disease-associated candidate genes with diagnostic and prognostic applications [34-37]. …”