The Humoral Immune System Has a Key Prognostic Impact in Node-Negative Breast Cancer

Abstract

Estrogen receptor (ER) expression and proliferative activity are established prognostic factors in breast cancer. In a search for additional prognostic motifs, we analyzed the gene expression patterns of 200 tumors of patients who were not treated by systemic therapy after surgery using a discovery approach. After performing hierarchical cluster analysis, we identified coregulated genes related to the biological process of proliferation, steroid hormone receptor expression, as well as B-cell and T-cell infiltration. We calculated metagenes as a surrogate for all genes contained within a particular cluster and visualized the relative expression in relation to time to metastasis with principal component analysis. Distinct patterns led to the hypothesis of a prognostic role of the immune system in tumors with high expression of proliferationassociated genes. In multivariate Cox regression analysis, the proliferation metagene showed a significant association with metastasis-free survival of the whole discovery cohort [hazard ratio (HR), 2.20; 95% confidence interval (95% CI), 1.40-3.46]. The B-cell metagene showed additional independent prognostic information in carcinomas with high proliferative activity (HR, 0.66; 95% CI, 0.46-0.97). A prognostic influence of the B-cell metagene was independently confirmed by multivariate analysis in a first validation cohort enriched for high-grade tumors (n = 286; HR, 0.78; 95% CI,) and a second validation cohort enriched for younger patients (n = 302; HR, 0.83; 95% CI, 0.7-0.97). Thus, we could show in three cohorts of untreated, node-negative breast cancer patients that the humoral immune system plays a pivotal role in metastasis-free survival of carcinomas of the breast. [Cancer Res 2008;68(13):5405-13]

Data driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer

“…We included 238 of our own samples (datasets Frankfurt, Frankfurt-2, and Frankfurt-3) which have been described previously (Ahr et al 2002 [9], [10], Rody et al 2008 [11], Ruckhäberle et al 2008 [12], and Rody et al 2007 [13], respectively) as well as 2792 samples from 22 different publicly available datasets (Table 1): Rotterdam [14][15][16], Mainz [17], Trans-BIG [18], Oxford-Untreated [19], London [20], London-2 [21], Oxford-Tamoxifen, Veridex-Tam [22], Stockholm [23], Uppsala [24,25], San Francisco [26], New York [27], MDA133 [28], EORTC [29], Edinburgh [30], ExpO [31], Signapore [32], Genentech [33], Boston [34], Berlin [35], Paris [36], and Tampa [37]. For comparability, only the ProbeSets from the Affymetrix HG-U133A microarray were used from seven datasets where HG-U133?…”

Control of EVI-1 oncogene expression in metastatic breast cancer cells through microRNA miR-22

“…All or only true prognostic data sets (no systemic therapy) were included in the analysis. These data sets are described in Gene Expression Omnibus accession numbers GSE11121 (Schmidt et al, 2008), GSE7390 (Desmedt et al, 2007) and select data from GSE3494, GSE2990 and GSE2034 (Miller et al, 2005;Wang et al, 2005;Sotiriou et al, 2006). C17orf91 expression was analyzed using the affymetrix probe set 214696_at (excellent probe set), whereas EVI-1 (MECOM) was measured using the probe set 221884_at (intermediate probe set).…”

Design and Multiseries Validation of a Web-Based Gene Expression Assay for Predicting Breast Cancer Recurrence and Patient Survival

“…Sample processing and hybridization (GeneChip) was performed according to manufacturer recommendations, as reported by the respective original publications. [11][12][13][14]17 Raw GeneChip output files (CEL files) were processed with the MAS5 method and median centered using the housekeeping/ reference gene set (Affymetrix) value, defined by determining the median.…”