Repeated observation of breast tumor subtypes in independent gene expression data sets

Abstract

Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 ''intrinsic'' genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.

Ferroportin and Iron Regulation in Breast Cancer Progression and Prognosis

“…To perform this analysis, we leveraged four large patient cohorts with accompanying gene expression profiling data from studies of breast cancer patients with extensive clinical follow-up. These represent four of the largest data sets in the public domain in which microarray profiles and long-term patient outcomes are available: (i) 103 patients from the Norway/Stanford study of response to chemotherapy of locally advanced cancer (33); (ii) 295 consecutive breast cancer patients from the Netherlands Cancer Institute (NKI) (34); (iii) 251 consecutive breast cancer patients from Uppsala, Sweden (35); and (iv) 159 surgically resected breast cancer patients from the Karolinska Institute in Stockholm, Sweden (31). Patient outcomes measured in these studies were either disease-specific survival (DSS) (death due to breast cancer) or distant metastasis–free survival (DMFS) (recurrence of cancer at a distant organ site).…”

“…Correlations between ferroportin expression in primary breast tumors and metastatic recurrence in patients were assessed with gene expression profiles from publicly accessible microarray data sets: (i) the Norway/Stanford study (33) (http://genome-www.stanford.edu/breast_cancer/mopo_clinical/data.shtml), (ii) the NKI study (34) (http://www.rii. com/publications/2002/nejm.html), (iii) the Uppsala study (35) [Gene Expression Omnibus (GEO) accession number GSE3494], and (iv) the Stockholm study (31) (GEO accession number GSE1456).…”

“…Breast cancer patients were ranked according to ferroportin expression levels, and DSS or DMFS of patients with below-mean expression was compared to that of patients with above-mean expression. ( A to D ) Kaplan-Meier plots are shown for (A) the Norway/Stanford cohort (33) (included were 103 tumors with reported expression values for ferroportin; data for 19 tumors were reported as “missing” in the original data set and these were excluded from the analysis), (B) the NKI cohort (34), (C) the Uppsala cohort (35), and (D) the Stockholm cohort (31). Log-rank tests were used to compare the survival curves between groups and to generate the P values for these comparisons.…”

Basal phenotype of ductal carcinoma in situ: recognition and immunohistologic profile

“…[1][2][3][4] As the recognition of the different epithelial phenotypes become more widespread, tailored therapeutic strategies may become more important.…”

Prognostic value of the ubiquitin ligase carboxyl terminus of the Hsc70‐interacting protein in postmenopausal breast cancer

“…initially proposed a molecular classification for breast cancer. Using a cDNA microarray of 38 breast cancer cases, this group defined a list of intrinsic genes 27, 28. Moreover, a larger cohort of breast cancer patients revealed that the luminal subgroup may be divided into luminal A and B 29.…”