Seased samples are denoted by black hatches. Expression is depicted as

Seased samples are denoted by black hatches. Expression is depicted as

Seased samples are denoted by black hatches. Expression is depicted as mean-normalized, 15900046 log2-transformed values. (D) Forty-nine genes were mutually dysregulated in the datasets tested and concordant in expression with the experimental model. (E) Pathway analysis of the 49-gene set demonstrating significant over-representation of several inflammation-related pathways. P-values were calculated using Fisher’s exact test. Red line indicates p = 0.05. doi:10.1371/journal.pone.0046104.gates the growth of human tumors in immunodeficient mice. Finally, we derive a molecular signature reflective of tumor endothelial inflammatory gene expression that is highly predictive of poor clinical outcome in four types of human cancer. Concordant with our experimental model, patients with tumors that expressed these inflammatory genes had significantly larger primary tumors of higher histological grade. Molecular signatures discovered through gene expression profiling have been shown to add prognostic value to clinical and pathological findings in several human cancers. Identifying prognostic variables that work cooperatively with known factors may improve the identification of patients at higher risk for 79831-76-8 site relapse and death. Recently, several studies have identified host stromal signatures, either in 3397-23-7 purified stromal cells or from whole tumor samples, as significant prognostic factors in multiple types of human cancer including breast cancer, lung cancer, gastric cancer, prostate cancer, and lymphomas [19?6]. Finak et al [19] used laser capture microdissection (LCM) of primary breast tumors to construct a stroma-derived prognostic signature that predicted poor outcome in whole tumor-derived expression datasets. Theauthors found that poor outcome was strongly linked to the expression of numerous endothelial-derived genes and that patient samples within the poor outcome group had a significantly greater endothelial content than those in the good outcome group. Furthermore, Lenz et al [25] profiled gene expression in biopsy specimens from patients with diffuse large B-cell lymphoma and identified a highly prognostic stromal signature in patients with adverse outcome that was largely comprised of well-known endothelial markers. As well, Saadi et al [21] demonstrated that the progression from pre-malignant disease to esophageal adenocarcinoma was associated with a marked expression of inflammatory mediators in LCM stromal cells compromised, in part, by endothelial cells. These studies highlight the role of non-malignant tumor-infiltrating stromal cells in the prognosis of human cancers. In this regard, most tumor biopsies contain a significant fraction of stromal cells (up to 50 [10]). Therefore, signatures derived from whole tumor specimens reflect both tumor and stromal expression patterns. Nevertheless, few studies to date have identified prognostic molecular signatures relevant to multiple humanTumor Endothelial Inflammation in Cancer PrognosisFigure 3. Expression of a tumor endothelium-derived gene signature predicts poor clinical outcome in multiple human cancers. IREG expression is associated with poor prognosis in (A) breast cancer (n = 98), (B) colon cancer (n = 78), (C) glioma (n = 50), and (D) lung cancer (n = 184). Kaplan-Meier survival curves for patient groups identified by IREG score. P-values indicate significant differences in overall survival as measured by log-rank tests. Red = IREG+, blue = IREG2. (E ) Expression of the six-gene IREG score w.Seased samples are denoted by black hatches. Expression is depicted as mean-normalized, 15900046 log2-transformed values. (D) Forty-nine genes were mutually dysregulated in the datasets tested and concordant in expression with the experimental model. (E) Pathway analysis of the 49-gene set demonstrating significant over-representation of several inflammation-related pathways. P-values were calculated using Fisher’s exact test. Red line indicates p = 0.05. doi:10.1371/journal.pone.0046104.gates the growth of human tumors in immunodeficient mice. Finally, we derive a molecular signature reflective of tumor endothelial inflammatory gene expression that is highly predictive of poor clinical outcome in four types of human cancer. Concordant with our experimental model, patients with tumors that expressed these inflammatory genes had significantly larger primary tumors of higher histological grade. Molecular signatures discovered through gene expression profiling have been shown to add prognostic value to clinical and pathological findings in several human cancers. Identifying prognostic variables that work cooperatively with known factors may improve the identification of patients at higher risk for relapse and death. Recently, several studies have identified host stromal signatures, either in purified stromal cells or from whole tumor samples, as significant prognostic factors in multiple types of human cancer including breast cancer, lung cancer, gastric cancer, prostate cancer, and lymphomas [19?6]. Finak et al [19] used laser capture microdissection (LCM) of primary breast tumors to construct a stroma-derived prognostic signature that predicted poor outcome in whole tumor-derived expression datasets. Theauthors found that poor outcome was strongly linked to the expression of numerous endothelial-derived genes and that patient samples within the poor outcome group had a significantly greater endothelial content than those in the good outcome group. Furthermore, Lenz et al [25] profiled gene expression in biopsy specimens from patients with diffuse large B-cell lymphoma and identified a highly prognostic stromal signature in patients with adverse outcome that was largely comprised of well-known endothelial markers. As well, Saadi et al [21] demonstrated that the progression from pre-malignant disease to esophageal adenocarcinoma was associated with a marked expression of inflammatory mediators in LCM stromal cells compromised, in part, by endothelial cells. These studies highlight the role of non-malignant tumor-infiltrating stromal cells in the prognosis of human cancers. In this regard, most tumor biopsies contain a significant fraction of stromal cells (up to 50 [10]). Therefore, signatures derived from whole tumor specimens reflect both tumor and stromal expression patterns. Nevertheless, few studies to date have identified prognostic molecular signatures relevant to multiple humanTumor Endothelial Inflammation in Cancer PrognosisFigure 3. Expression of a tumor endothelium-derived gene signature predicts poor clinical outcome in multiple human cancers. IREG expression is associated with poor prognosis in (A) breast cancer (n = 98), (B) colon cancer (n = 78), (C) glioma (n = 50), and (D) lung cancer (n = 184). Kaplan-Meier survival curves for patient groups identified by IREG score. P-values indicate significant differences in overall survival as measured by log-rank tests. Red = IREG+, blue = IREG2. (E ) Expression of the six-gene IREG score w.

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