Introduction: Human breast tumors are heterogeneous and consist of phenotypically diverse cells. Breast cancer cells with a CD44⁺/CD24^- phenotype have been suggested to have tumor-initiating properties with stem cell-like and invasive features, although it is unclear whether their presence within a tumor has clinical implications. There is also a large heterogeneity between tumors, illustrated by reproducible stratification into various subtypes based on gene expression profiles or histopathological features. We have explored the prevalence of cells with different CD44/CD24 phenotypes within breast cancer subtypes. Methods: Double-staining immunohistochemistry was used to quantify CD44 and CD24 expression in 240 human breast tumors for which information on other tumor markers and clinical characteristics was available. Gene expression data were also accessible for a cohort of the material. Results: A considerable heterogeneity in CD44 and CD24 expression was seen both between and within tumors. A complete lack of both proteins was evident in 35% of the tumors, while 13% contained cells of more than one of the CD44⁺/CD24^-, CD44^-/CD24⁺ and CD44⁺/CD24⁺ phenotypes. CD44⁺/CD24^- cells were detected in 31% of the tumors, ranging in proportion from only a few to close to 100% of tumor cells. The CD44⁺/CD24^- phenotype was most common in the basal-like subgroup – characterized as negative for the estrogen and progesterone receptors as well as for HER2, and as positive for cytokeratin 5/14 and/or epidermal growth factor receptor, and particularly common in BRCA1 hereditary tumors, of which 94% contained CD44⁺/CD24^- cells. The CD44⁺/CD24^- phenotype was surprisingly scarce in HER2+ tumors, which had a predominantly CD24⁺ status. A CD44⁺/CD24^- gene expression signature was generated, which included CD44 and α₆-integrin (CD49f) among the top-ranked overexpressed genes. Conclusion: We demonstrate an association between basal-like and particularly BRCA1 hereditary breast cancer and the presence of CD44⁺/CD24^- cells. Not all basal-like tumors and very few HER2+ tumors, however, contain CD44⁺/CD24^- cells, emphasizing that a putative tumorigenic ability may not be confined to cells of this phenotype and that other breast cancer stem cell markers remain to be identified.

The CD44 cell adhesion molecule is aberrantly expressed in many breast tumors and has been implicated in the metastatic process as well as in the putative cancer stem cell (CSC) compartment. We aimed to investigate potential associations between alternatively spliced isoforms of CD44 and CSCs as well as to various breast cancer biomarkers and molecular subtypes.

Introduction: Basal-phenotype or basal-like breast cancers are characterized by basal epithelium cytokeratin (CK5/14/17) expression, negative estrogen receptor (ER) status and distinct gene expression signature. We studied the clinical and biological features of the basal-phenotype tumors determined by immunohistochemistry (IHC) and cDNA microarrays especially within the ER-negative subgroup. Methods: IHC was used to evaluate the CK5/14 status of 445 stage II breast cancers. The gene expression signature of the CK5/14 immunopositive tumors was investigated within a subset (100) of the breast tumors (including 50 ER-negative tumors) with a cDNA microarray. Survival for basal-phenotype tumors as determined by CK5/14 IHC and gene expression signature was assessed. Results: From the 375 analyzable tumor specimens, 48 (13%) were immunohistochemically positive for CK5/14. We found adverse distant disease-free survival for the CK5/14-positive tumors during the first years (3 years hazard ratio (HR) 2.23, 95% confidence interval (CI) 1.17 to 4.24, p = 0.01; 5 years HR 1.80, 95% CI 1.02 to 3.15, p = 0.04) but the significance was lost at the end of the follow-up period (10 years HR 1.43, 95% CI 0.84 to 2.43, p = 0.19). Gene expression profiles of immunohistochemically determined CK5/14-positive tumors within the ER-negative tumor group implicated 1,713 differently expressed genes (p < 0.05). Hierarchical clustering analysis with the top 500 of these genes formed one basal-like and a non-basal-like cluster also within the ER-negative tumor entity. A highly concordant classification could be constructed with a published gene set (Sorlie's intrinsic gene set, concordance 90%). Both gene sets identified a basal-like cluster that included most of the CK5/14-positive tumors, but also immunohistochemically CK5/14-negative tumors. Within the ER-negative tumor entity there was no survival difference between the non-basal and basal-like tumors as identified by immunohistochemical or gene-expression-based classification. Conclusion: Basal cytokeratin-positive tumors have a biologically distinct gene expression signature from other ER-negative tumors. Even if basal cytokeratin expression predicts early relapse among non-selected tumors, the clinical outcome of basal tumors is similar to non-basal ER-negative tumors. Immunohistochemically basal cytokeratin-positive tumors almost always belong to the basal-like gene expression profile, but this cluster also includes few basal cytokeratin-negative tumors.

Background: Assessing RNA quality is essential for gene expression analysis, as the inclusion of degraded samples may influence the interpretation of expression levels in relation to biological and/or clinical parameters. RNA quality can be analyzed by agarose gel electrophoresis, UV spectrophotometer, or microcapillary electrophoresis traces, and can furthermore be evaluated using different methods. No generally accepted recommendations exist for which technique or evaluation method is the best choice. The aim of the present study was to use microcapillary electrophoresis traces from the Bioanalyzer to compare three methods for evaluating RNA quality in 24 fresh frozen invasive breast cancer tissues: 1) Manual method = subjective evaluation of the electropherogram, 2) Ratio Method = the ratio between the 28S and 18S peaks, and 3) RNA integrity number (RIN) method = objective evaluation of the electropherogram. The results were also related to gene expression profiling analyses using 27K oligonucleotide microarrays, unsupervised hierarchical clustering analysis and ontological mapping. Results: Comparing the methods pair-wise, Manual vs. Ratio showed concordance (good vs. degraded RNA) in 20/24, Manual vs. RIN in 23/24, and Ratio vs. RIN in 21/24 samples. All three methods were concordant in 20/24 samples. The comparison between RNA quality and gene expression analysis showed that pieces from the same tumor and with good RNA quality clustered together in most cases, whereas those with poor quality often clustered apart. The number of samples clustering in an unexpected manner was lower for the Manual (n = 1) and RIN methods (n = 2) as compared to the Ratio method (n = 5). Assigning the data into two groups, RIN ≥ 6 or RIN < 6, all but one of the top ten differentially expressed genes showed decreased expression in the latter group; i.e. when the RNA became degraded. Ontological mapping using GoMiner (p ≤ 0.05; ≥ 3 genes changed) revealed deoxyribonuclease activity, collagen, regulation of cell adhesion, cytosolic ribosome, and NADH dehydrogenase activity, to be the five categories most affected by RNA quality. Conclusion: The results indicate that the Manual and RIN methods are superior to the Ratio method for evaluating RNA quality in fresh frozen breast cancer tissues. The objective measurement when using the RIN method is an advantage. Furthermore, the inclusion of samples with degraded RNA may profoundly affect gene expression levels.

Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction. We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day’s signatures. We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.