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Background The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories. Methods 514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies. Results The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online. Conclusions The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.

Resistance to oestrogen-deprivation therapy is common in oestrogen-receptor-positive (ER+) breast cancer. To better understand the contributions of tumour heterogeneity and evolution to resistance, here we perform comprehensive genomic characterization of 22 primary tumours sampled before and after 4 months of neoadjuvant aromatase inhibitor (NAI) treatment. Comparing whole-genome sequencing of tumour/normal pairs from the two time points, with coincident tumour RNA sequencing, reveals widespread spatial and temporal heterogeneity, with marked remodelling of the clonal landscape in response to NAI. Two cases have genomic evidence of two independent tumours, most obviously an ER− ‘collision tumour’, which was only detected after NAI treatment of baseline ER+ disease. Many mutations are newly detected or enriched post treatment, including two ligand-binding domain mutations in ESR1 . The observed clonal complexity of the ER+ breast cancer genome suggests that precision medicine approaches based on genomic analysis of a single specimen are likely insufficient to capture all clinically significant information. Aromatase inhibitors are used to treat oestrogen-receptor-positive breast cancer. Here, the authors use genomic approaches to analyse tumours before and after neo-adjuvant treatment and find that treatment alters the clonal landscape of the tumours.

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities. Patient-derived xenografts recapitulate major genomic signatures and transcriptome profiles of their original tumours. Here, the authors, performing proteomic and phosphoproteomic analyses of 24 breast cancer PDX models, demonstrate that druggable candidates can be identified based on a comprehensive proteogenomic profiling.

Mutations in the alpha catalytic subunit of phosphoinositol-3-kinase (PIK3CA) occur in ~30% of ER positive breast cancers. We therefore sought to determine the impact of PIK3CA mutation on response to neoadjuvant endocrine therapy. Exons 9 (helical domain) and 20 (kinase domain—KD) mutations in PIK3CA were determined samples from four neoadjuvant endocrine therapy trials. Interactions with clinical, pathological, and biomarker response parameters were examined. A weak negative interaction between PIK3CA mutation status and clinical response to neoadjuvant endocrine treatment was detected (N = 235 P ≤ 0.05), but not with treatment-induced changes in Ki67-based proliferation index (N = 418). Despite these findings, PIK3CA KD mutation was a favorable prognostic factor for relapse-free survival (RFS log-rank P = 0.02) in the P024 trial (N = 153). The favorable prognostic effect was maintained in a multivariable analysis (N = 125) that included the preoperative endocrine prognostic index, an approach to predicting RFS based on postneoadjuvant endocrine therapy pathological stage, ER, and Ki67 levels (HR for no PIK3CA KD mutation, 14, CI 1.9-105 P = 0.01). PIK3CA mutation status did not strongly interact with neoadjuvant endocrine therapy responsiveness in estrogen receptor-positive breast cancer. Nonetheless, as with other recent studies, a favorable interaction between PIK3CA KD mutation and prognosis was detected. The mechanism for the favorable prognostic impact of PIK3CA mutation status therefore remains unexplained.

Understanding the signaling pathways that drive aggressive breast cancers is critical to the development of effective therapeutics. The oncogene MET is associated with decreased survival in breast cancer, yet the role that MET plays in the various breast cancer subtypes is unclear. We describe a knockin mouse with mutationally activated Met (Metmut) that develops a high incidence of diverse mammary tumors with basal characteristics, including metaplasia, absence of progesterone receptor and ERBB2 expression, and expression of cytokeratin 5. With gene expression and tissue microarray analysis, we show that high MET expression in human breast cancers significantly correlated with estrogen receptor negative/ERBB2 negative tumors and with basal breast cancers. Few treatment options exist for breast cancers of the basal or trastuzumab-resistant ERBB2 subtypes. We conclude from these studies that MET may play a critical role in the development of the most aggressive breast cancers and may be a rational therapeutic target.

PAM50 intrinsic breast cancer subtypes are prognostic independent of standard clinicopathologic factors. CALGB 9741 demonstrated improved recurrence-free (RFS) and overall survival (OS) with 2-weekly dose-dense (DD) versus 3-weekly therapy. A significant interaction between intrinsic subtypes and DD-therapy benefit was hypothesized. Suitable tumor samples were available from 1,471 (73%) of 2,005 subjects. Multiplexed gene-expression profiling generated the PAM50 subtype call, proliferation score, and risk of recurrence score (ROR-PT) for the evaluable subset of 1,311 treated patients. The interaction between DD-therapy benefit and intrinsic subtype was tested in a Cox proportional hazards model using two-sided alpha=0.05. Additional multivariable Cox models evaluated the proliferation and ROR-PT scores as continuous measures with selected clinical covariates. Improved outcomes for DD therapy in the evaluable subset mirrored results from the complete data set (RFS; hazard ratio=1.20; 95% confidence interval=0.99–1.44) with 12.3-year median follow-up. Intrinsic subtypes were prognostic of RFS ( P <0.0001) irrespective of treatment assignment. No subtype-specific treatment effect on RFS was identified (interaction P =0.44). Proliferation and ROR-PT scores were prognostic for RFS (both P <0.0001), but no association with treatment benefit was seen ( P =0.14 and 0.59, respectively). Results were similar for OS. The prognostic value of PAM50 intrinsic subtype was greater than estrogen receptor/HER2 immunohistochemistry classification. PAM50 gene signatures were highly prognostic but did not predict for improved outcomes with DD anthracycline- and taxane-based therapy. Clinical validation studies will assess the ability of PAM50 and other gene signatures to stratify patients and individualize treatment based on expected risks of distant recurrence. Genomic testing: Predictive power of multigene activity Testing the activity of a set of 50 genes predicts breast cancer outcomes, but requires further validation as a tool to guide treatment. Minetta Liu of the Mayo Clinic in Minnesota, United States, together with US and Canadian colleagues, assessed the predictive power of the PAM50 genomic test for breast cancer. They analyzed tumor samples taken from 1,471 patients more than 12 years ago, comparing their results with knowledge of subsequent clinical outcomes and relapse. The team found that while specific PAM50 gene activity signatures were highly predictive of disease outcome and the incidence of relapse, PAM50 test results did not indicate the likelihood of improved outcomes with 2-weekly dose dense anthracycline and taxane-based chemotherapy. Predicting the benefit of different therapeutic strategies therefore remains a challenge. Future studies should investigate the potential of PAM50 testing for guiding chemotherapy choices.

Tubular carcinoma (TC) is a rare, luminal A subtype of breast carcinoma with excellent prognosis, for which adjuvant chemotherapy is usually contraindicated. To examine the levels of estrogen receptor (ER) and progesterone receptor expression in cases of TC and well-differentiated invasive ductal carcinoma as compared to normal breast glands and to determine if any significant differences could be detected via molecular testing. We examined ER and progesterone receptor via immunohistochemistry in tubular (N = 27), mixed ductal/tubular (N = 16), and well-differentiated ductal (N = 27) carcinomas with comparison to surrounding normal breast tissue. We additionally performed molecular subtyping of 10 TCs and 10 ductal carcinomas via the PAM50 assay. Although ER expression was high for all groups, TC had statistically significantly lower ER staining percentage (ER%) (P = .003) and difference in ER expression between tumor and accompanying normal tissue (P = .02) than well-differentiated ductal carcinomas, with mixed ductal/tubular carcinomas falling between these 2 groups. Mean ER% was 79%, 87%, and 94%, and mean tumor-normal ER% differences were 13.6%, 25.9%, and 32.6% in tubular, mixed, and ductal carcinomas, respectively. Most tumors that had molecular subtyping were luminal A (9 of 10 tubular and 8 of 10 ductal), and no significant differences in specific gene expression between the 2 groups were identified. Tubular carcinoma exhibited decreased intensity in ER expression, closer to that of normal breast parenchyma, likely as a consequence of a high degree of differentiation. Lower ER% expression by TC may represent a potential pitfall when performing commercially available breast carcinoma prognostic assays that rely heavily on ER-related gene expression.

Whenever I can, I attend Humanities lectures— such as the one given by Leah Price at the University of Iowa, or sessions at conferences that come very close to the world of library and information science. From what I am seeing, academics from English, comparative literature, linguistics, and sociology are knocking at ourdoor. [...]

Cybèle Werts passed away on October 2, 2010 at the age of 47. Cybèle was a dynamic, energetic, and vivacious person. When I met her several years ago at an SLA conference, she was talking a mile a minute; ready for any challenge. [...]