An Endothelial Gene Signature Score Predicts Poor Outcome in Patients with Endocrine-Treated, Low Genomic Grade Breast Tumors

Abstract

Purpose: The ability of vascular genes to provide treatment predictive information in breast cancer patients remains unclear. As such, we assessed the expression of genes representative of normal endothelial microvasculature (MV) in relation to treatment-specific patient subgroups.Experimental Design: We used expression data from 993 breast tumors to assess 57 MV genes (summarized to yield an MV score) as well as the genomic grade index (GGI) and PAM50 signatures. MV score was compared with CD31 staining by correlation and gene ontology (GO) analysis, along with clinicopathologic characteristics and PAM50 subtypes. Uni-, multivariate, and/or t-test analyses were performed in all and treatment-specific subgroups, along with a clinical trial cohort of patients with metastatic breast cancer, seven of whom received antiangiogenic therapy.Results: MV score did not correlate with microvessel density (correlation ¼ 0.096), but displayed enrichment for angiogenic GO terms, and was lower in Luminal B tumors. In endocrinetreated patients, a high MV score was associated with decreased risk of metastasis [HR 0.58; 95% confidence interval (CI), 0.38-0.89], even after adjusting for histologic grade, but not GGI or PAM50. Subgroup analysis showed the prognostic strength of the MV score resided in low genomic grade tumors and MV score was significantly increased in metastatic breast tumors after treatment with sunitinib þ docetaxel (P ¼ 0.031).Conclusions: MV score identifies two groups of better and worse survival in low-risk endocrine-treated breast cancer patients. We also show normalization of tumor vasculature on a transcriptional level in response to an angiogenic inhibitor in human breast cancer samples.

IDH mutation status is associated with distinct vascular gene expression signatures in lower-grade gliomas

“…We generated an MV score by summarizing the standardized mRNA expression levels for the vascular enriched genes as described. 24 By dichotomizing patients into 2 groups of equal size according to their MV scores, we found that a high MV score was significantly associated with shorter survival ( P = 0.0265, log-rank test) ( Fig. 2A , Supplementary Tables S7 and S8 ).…”

“…For each sample, the standardized values of all 456 vascular enriched genes were added to yield a microvasculature (MV) signature score (an MV score), as described. 24 …”

Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing

“…The study is designed such that 190 breast cancer patients that developed distant metastatic disease (cases) were selected from a consecutive series of individuals, and each closely matched by adjuvant therapy, age, and calendar period at diagnosis with three patients free from metastasis (controls) 28 . The gene signature for vCAFs correlated strongly to an endothelial metagene 27 and a microvasculature signature 29 within the dataset from the case–control study, whereas mCAFs instead were highly associated with a stroma-derived invasion signature 30 and a stroma-related treatment-predictive signature 31 (Fig. 5i ).…”

“…Six gene expression signatures were explored for their correlation with the CAF populations. These included endothelial/microvasculature signatures 27 , 29 , stroma-related signatures 27 , 30 , 31 , and a proliferation signature 32 . Gene signature scores were derived as the weighted averages of the expression values of the constituent signature genes, where the weight for each gene is +1 or −1 depending on the direction with the phenotype in the original publication.…”

A VEGF-dependent gene signature enriched in mesenchymal ovarian cancer predicts patient prognosis

“…In this study, we extended previous work of exploiting gene expression profiling approach for accurate detection of VEGF downstream biological activity, and designed a more stringent analytical protocol to identify and validate a reliable VEGF-dependent gene signature in preclinical tumor models and in human patients. Although the VDGs overlapped with previously developed VEGF-related signatures in general 22 26 , the refined gene list presented here was physiologically relevant on the basis of suitable in vivo models and integration of gene profiling results from two independent microarray platforms. Furthermore, we presented a detailed analysis of the VDGs in ovarian cancer by systematically interrogating TCGA HGS-OvCa expression data and four additional genome-wide transcriptome cohorts in the public domain.…”