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1.  PAM50 assay and the three-gene model for identifying the major and clinically relevant molecular subtypes of breast cancer 
It has recently been proposed that a three-gene model (SCMGENE) that measures ESR1, ERBB2, and AURKA identifies the major breast cancer intrinsic subtypes and provides robust discrimination for clinical use in a manner very similar to a 50-gene subtype predictor (PAM50). However, the clinical relevance of both predictors was not fully explored, which is needed given that a ~30 % discordance rate between these two predictors was observed. Using the same datasets and subtype calls provided by Haibe-Kains and colleagues, we compared the SCMGENE assignments and the research-based PAM50 assignments in terms of their ability to (1) predict patient outcome, (2) predict pathological complete response (pCR) after anthracycline/taxane-based chemotherapy, and (3) capture the main biological diversity displayed by all genes from a microarray. In terms of survival predictions, both assays provided independent prognostic information from each other and beyond the data provided by standard clinical–pathological variables; however, the amount of prognostic information was found to be significantly greater with the PAM50 assay than the SCMGENE assay. In terms of chemotherapy response, the PAM50 assay was the only assay to provide independent predictive information of pCR in multivariate models. Finally, compared to the SCMGENE predictor, the PAM50 assay explained a significantly greater amount of gene expression diversity as captured by the two main principal components of the breast cancer microarray data. Our results show that classification of the major and clinically relevant molecular subtypes of breast cancer are best captured using larger gene panels.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-012-2143-0) contains supplementary material, which is available to authorized users.
doi:10.1007/s10549-012-2143-0
PMCID: PMC3413822  PMID: 22752290
Breast cancer; Microarrays; PAM50; Prognosis; Gene expression
2.  Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen 
Annals of Oncology  2012;23(11):2866-2873.
Background
ER-positive (ER+ ) breast cancer includes all of the intrinsic molecular subtypes, although the luminal A and B subtypes predominate. In this study, we evaluated the ability of six clinically relevant genomic signatures to predict relapse in patients with ER+ tumors treated with adjuvant tamoxifen only.
Methods
Four microarray datasets were combined and research-based versions of PAM50 intrinsic subtyping and risk of relapse (PAM50-ROR) score, 21-gene recurrence score (OncotypeDX), Mammaprint, Rotterdam 76 gene, index of sensitivity to endocrine therapy (SET) and an estrogen-induced gene set were evaluated. Distant relapse-free survival (DRFS) was estimated by Kaplan–Meier and log-rank tests, and multivariable analyses were done using Cox regression analysis. Harrell's C-index was also used to estimate performance.
Results
All signatures were prognostic in patients with ER+ node-negative tumors, whereas most were prognostic in ER+ node-positive disease. Among the signatures evaluated, PAM50-ROR, OncotypeDX, Mammaprint and SET were consistently found to be independent predictors of relapse. A combination of all signatures significantly increased the performance prediction. Importantly, low-risk tumors (>90% DRFS at 8.5 years) were identified by the majority of signatures only within node-negative disease, and these tumors were mostly luminal A (78%–100%).
Conclusions
Most established genomic signatures were successful in outcome predictions in ER+ breast cancer and provided statistically independent information. From a clinical perspective, multiple signatures combined together most accurately predicted outcome, but a common finding was that each signature identified a subset of luminal A patients with node-negative disease who might be considered suitable candidates for adjuvant endocrine therapy alone.
doi:10.1093/annonc/mds080
PMCID: PMC3477878  PMID: 22532584
breast cancer; genomics; luminal; mammaprint; oncotype; PAM50
3.  A phase II study of sequential neoadjuvant gemcitabine plus doxorubicin followed by gemcitabine plus cisplatin in patients with operable breast cancer: prediction of response using molecular profiling 
British Journal of Cancer  2008;98(8):1327-1335.
This study examined the pathological complete response (pCR) rate and safety of sequential gemcitabine-based combinations in breast cancer. We also examined gene expression profiles from tumour biopsies to identify biomarkers predictive of response. Indian women with large or locally advanced breast cancer received 4 cycles of gemcitabine 1200 mg m−2 plus doxorubicin 60 mg m−2 (Gem+Dox), then 4 cycles of gemcitabine 1000 mg m−2 plus cisplatin 70 mg m−2 (Gem+Cis), and surgery. Three alternate dosing sequences were used during cycle 1 to examine dynamic changes in molecular profiles. Of 65 women treated, 13 (24.5% of 53 patients with surgery) had a pCR and 22 (33.8%) had a complete clinical response. Patients administered Gem d1, 8 and Dox d2 in cycle 1 (20 of 65) reported more toxicities, with G3/4 neutropenic infection/febrile neutropenia (7 of 20) as the most common cycle-1 event. Four drug-related deaths occurred. In 46 of 65 patients, 10-fold cross validated supervised analyses identified gene expression patterns that predicted with ⩾73% accuracy (1) clinical complete response after eight cycles, (2) overall clinical complete response, and (3) pCR. This regimen shows strong activity. Patients receiving Gem d1, 8 and Dox d2 experienced unacceptable toxicity, whereas patients on other sequences had manageable safety profiles. Gene expression patterns may predict benefit from gemcitabine-containing neoadjuvant therapy.
doi:10.1038/sj.bjc.6604322
PMCID: PMC2361717  PMID: 18382427
breast cancer; chemotherapy; gemcitabine; gene expression; microarrays; neoadjuvant therapy
4.  Human epidermal growth factor receptor-2 and estrogen receptor expression, a demonstration project using the residual tissue respository of the Surveillance, Epidemiology, and End Results (SEER) program 
Background
In 2001, the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program established Residual Tissue Repositories (RTR) in the Hawaii, Iowa, and Los Angeles Tumor Registries to collect discarded tissue blocks from pathologic laboratories within their catchment areas. To validate the utility of the RTR for supplementing SEER’s central database, we assessed human epidermal growth factor receptor-2 (HER2) and estrogen receptor expression (ER) in a demonstration project.
Materials
Using a prepared set of tissue microarrays (TMAs) residing in the Hawaii Tumor Registry (HTR), we performed standard immunohistochemistry. Breast cancers in the TMA were diagnosed in 1995, followed through 2006, and linked to SEER’s main database.
Results
The TMA included 354 cases, representing 51% of 687 breast cancers in the HTR (1995). The HTR and TMA cases were similar with respect to patient demographics and tumor characteristics. Seventy-six percent (76%, 268 of 354) of TMA cases were HER2+ and/or ER+, i.e., 28 HER2+ER−, 12 HER2+ER+, and 228 HER2−ER+. There were 67 HER2−ER− cases and 19 were unclassified. Age distributions at diagnosis were bimodal with dominant early-onset modes for HER2+ER−tumors and dominant late-onset modes for HER2−ER+ breast cancers. Epidemiologic patterns for concordant HER2+ER+ (double-positive) and HER2−ER−(double-negative) were intermediate to discordant HER2+ER− and HER2−ER+.
Conclusion
Results showed contrasting incidence patterns for HER2+ (HER2+ER−) and ER+ (HER2−ER+) breast cancers, diagnosed in 1995. Though sample sizes were small, this demonstration project validates the potential utility of the RTR for supplementing the SEER program.
doi:10.1007/s10549-008-9918-3
PMCID: PMC2676874  PMID: 18256926
Immunohistochemical stains; Tissue microarrays; Human epidermal growth factor receptor-2 (HER2); Estrogen receptor (ER); Breast cancer incidence and survival; SEER

Results 1-4 (4)