Intrinsic Subtypes from the PAM50 Gene Expression Assay in a Population-Based Breast Cancer Survivor Cohort: Prognostication of Short- and Long-term Outcomes

Cancer Epidemiology Biomarkers & Prevention (Impact Factor: 4.13). 02/2014; 23(5). DOI: 10.1158/1055-9965.EPI-13-1017
Source: PubMed


Background: The PAM50, a gene expression assay to categorize breast tumors into intrinsic subtypes, has not been previously used to examine short- and long-term prognostication in a population-based cohort where treatment patterns and time of initial follow-up vary. Methods: In a stratified case-cohort design of 1,691 women from the LACE and Pathways breast cancer survivor cohorts, we used PAM50 to categorize tumors into Luminal A, Luminal B, HER2-enriched (E), Basal-like and Normal-like, and to examine risk of early and late recurrence and mortality by Cox proportional hazards regression. Results: Compared with Luminal A, cumulative risk of recurrence and breast cancer (BC) death was higher for Luminal B, Her2-E and Basal-like tumors at 2, 5 and 10 years. However, hazard ratios (HR) of BC death varied over time (<5 years (early) vs. >5 years (late)) for both Basal-like (HR 6.23 early vs.0.63 late) and HER2-E tumors (HR 2.97 early vs. HR 0.73 late) but not for Luminal B tumors where risk was elevated consistently (HR 2.67 early vs. HR 1.47 late). The contrast between Luminal B, HER2-E and Basal-like compared with Luminal A on early recurrence was stronger when subtype was defined by PAM50 than by immunohistochemistry markers (IHC). Conclusions: The PAM50 categorized intrinsic subtypes in a manner that more accurately predicts recurrence and survival, especially for luminal tumors, compared with commonly used methods that rely on traditional IHC clinical markers. Impact: The PAM50 is robust for use in epidemiological studies and should be considered when archived tumor tissues are available.

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    • "The most frequently diagnosed sub-type is Luminal A (51%), followed by Luminal B (29%), Basal (17%), HER2 (12.5%), and Claudin-low (2%). The importance of these molecular subtypes cannot be underestimated as they allow for prediction of therapeutic targets and they display distinct clinical courses (Caan et al., 2014). Women whose tumors fit the Luminal A profile have the best prognosis whereas those whose tumors have Luminal B or Basal profiles have poor prognosis. "
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    ABSTRACT: Nuclear receptors exert profound effects on mammary gland physiology and have complex roles in the etiology of breast cancer. In addition to receptors for classic steroid hormones such as estrogen and progesterone, the nuclear vitamin D receptor (VDR) interacts with its ligand 1α,25(OH)2D3 to modulate the normal mammary epithelial cell genome and subsequent phenotype. Observational studies suggest that vitamin D deficiency is common in breast cancer patients and that low vitamin D status enhances the risk for disease development or progression. Genomic profiling has characterized many 1α,25(OH)2D3 responsive targets in normal mammary cells and in breast cancers, providing insight into the molecular actions of 1α,25(OH)2D3 and the VDR in regulation of cell cycle, apoptosis, and differentiation. New areas of emphasis include regulation of tumor metabolism and innate immune responses. However, the role of VDR in individual cell types (i.e., epithelial, adipose, fibroblast, endothelial, immune) of normal and tumor tissues remains to be clarified. Furthermore, the mechanisms by which VDR integrates signaling between diverse cell types and controls soluble signals and paracrine pathways in the tissue/tumor microenvironment remain to be defined. Model systems of carcinogenesis have provided evidence that both VDR expression and 1α,25(OH)2D3 actions change with transformation but clinical data regarding vitamin D responsiveness of established tumors is limited and inconclusive. Because breast cancer is heterogeneous, analysis of VDR actions in specific molecular subtypes of the disease may help to clarify the conflicting data. The expanded use of genomic, proteomic and metabolomic approaches on a diverse array of in vitro and in vivo model systems is clearly warranted to comprehensively understand the network of vitamin D regulated pathways in the context of breast cancer.
    Frontiers in Physiology 06/2014; 5:213. DOI:10.3389/fphys.2014.00213 · 3.53 Impact Factor
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    ABSTRACT: To evaluate whether differences in PAM50 breast cancer (BC) intrinsic (Luminal A, Luminal B, Basal-like, and HER2-enriched) subtypes help explain the Black-White BC survival disparity. Utilizing a stratified case-cohort design, this study included 1,635 women from the Pathways and Life After Cancer Epidemiology cohorts, selecting women with tumors based upon IHC classification, recurrences, and deaths.One millimeter punches were obtained from tumor tissue, and expression of the PAM50 genes for molecular subtype was determined by RT-qPCR of extracted RNA. Cox proportional hazards models were used to analyze associations between race and BC outcomes, adjusted for PAM50 BC subtype. All tests of statistical significance were two-sided. Black women had a higher prevalence of the Basal-like BC subtype. Adjusted for potential confounding variables and disease characteristics at diagnosis, Black women had higher risks of recurrence (HR 1.65, 95 % CI 1.06-2.57) and breast cancer-specific mortality (HR 1.71, 95 % CI 1.02-2.86) than White women, but adjusting further for subtype did not attenuate survival disparities. By contrast, Hispanic women had a lower risk of recurrence (HR 0.54, 95 % CI 0.30-0.96) than Whites. Among those with the Basal-like subtype, Black women had a similar recurrence risk as women in other race groups but a higher recurrence risk for all other subtypes. Hispanic women had a lower recurrence risk within each subtype, though associations were not significant, given limited power. Although Black women had a higher risk of the Basal-like subtype, which has poor prognosis, this did not explain the Black-White BC survival disparity.
    Breast Cancer Research and Treatment 03/2014; 144(3). DOI:10.1007/s10549-014-2899-5 · 3.94 Impact Factor
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    Breast cancer research: BCR 09/2014; 16(5):441. DOI:10.1186/s13058-014-0441-7 · 5.49 Impact Factor
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