BluePrint breast cancer molecular subtyping recognizes single and dual subtype tumors with implications for therapeutic guidance.

PURPOSE: BluePrint (BP) is an 80-gene molecular subtyping test that classifies early-stage breast cancer (EBC) into Basal, Luminal, and HER2 subtypes. In most cases, breast tumors have one dominant subtype, representative of a single activated pathway. However, some tumors show a statistically equal representation of more than one subtype, referred to as dual subtype. This study aims to identify and examine dual subtype tumors by BP to understand their biology and possible implications for treatment guidance. METHODS: The BP scores of over 15,000 tumor samples from EBC patients were analyzed, and the differences between the highest and the lowest scoring subtypes were calculated. Based upon the distribution of the differences between BP scores, a threshold was determined for each subtype to identify dual versus single subtypes. RESULTS: Approximately 97% of samples had one single activated BluePrint molecular subtype, whereas ~ 3% of samples were classified as BP dual subtype. The most frequently occurring dual subtypes were the Luminal-Basal-type and Luminal-HER2-type. Luminal-Basal-type displays a distinct biology from the Luminal single type and Basal single type. Burstein's classification of the single and dual Basal samples showed that the Luminal-Basal-type is mostly classified as 'luminal androgen receptor' and 'mesenchymal' subtypes, supporting molecular evidence of AR activation in the Luminal-Basal-type tumors. Tumors classified as Luminal-HER2-type resemble features of both Luminal-single-type and HER2-single-type. However, patients with dual Luminal-HER2-type have a lower pathological complete response after receiving HER2-targeted therapies in addition to chemotherapy in comparison with patients with a HER2-single-type. CONCLUSION: This study demonstrates that BP identifies tumors with two active functional pathways (dual subtype) with specific transcriptional characteristics and highlights the added value of distinguishing BP dual from single subtypes as evidenced by distinct treatment response rates.

Controlling technical variation amongst 6693 patient microarrays of the randomized MINDACT trial.

Gene expression data obtained in large studies hold great promises for discovering disease signatures or subtypes through data analysis. It is also prone to technical variation, whose removal is essential to avoid spurious discoveries. Because this variation is not always known and can be confounded with biological signals, its removal is a challenging task. Here we provide a step-wise procedure and comprehensive analysis of the MINDACT microarray dataset. The MINDACT trial enrolled 6693 breast cancer patients and prospectively validated the gene expression signature MammaPrint for outcome prediction. The study also yielded a full-transcriptome microarray for each tumor. We show for the first time in such a large dataset how technical variation can be removed while retaining expected biological signals. Because of its unprecedented size, we hope the resulting adjusted dataset will be an invaluable tool to discover or test gene expression signatures and to advance our understanding of breast cancer.

MammaPrint and BluePrint Molecular Diagnostics Using Targeted RNA Next-Generation Sequencing Technology.

Next-generation DNA sequencing is rapidly becoming an indispensable tool for genome-directed cancer diagnostics, but next-generation RNA sequencing (RNA-seq) is currently not standardly used in clinical diagnostics for expression assessment. However, multigene RNA diagnostic assays are used increasingly in the routine diagnosis of early-stage breast cancer. Two of the most widely used tests are currently available only as a central laboratory service, which limits their clinical use. We evaluated the use of RNA-seq as a decentralized method to perform such tests. The MammaPrint and BluePrint RNA-seq tests were found to be equivalent to the clinically validated microarray tests. The RNA-seq tests were highly reproducible when performed in different locations and were stable over time. The MammaPrint RNA-seq test was clinically validated. Our data demonstrate that RNA-seq can be used as a decentralized platform, yielding results substantially equivalent to results derived from the predicate diagnostic device.

Assessment of PD-L1 expression across breast cancer molecular subtypes, in relation to mutation rate, BRCA1-like status, tumor-infiltrating immune cells and survival.

To better understand the expression pattern of programmed death-ligand 1 (PD-L1) expression in different breast cancer types, we characterized PD-L1 expression in tumor and tumor-infiltrating immune cells, in relation to mutation rate, BRCA1-like status and survival. We analyzed 410 primary treatment-naive breast tumors comprising 162 estrogen receptor-positive (ER+) and HER2-, 101 HER2+ and 147 triple-negative (TN) cancers. Pathologists quantified tumor-infiltrating lymphocytes (TILs) and PD-L1 expression in tumor cells and TILs using whole slides and tissue microarray. Mutation rate was assessed by DNA sequencing, BRCA1-like status using multiplex ligation-dependent probe amplification, and immune landscape by multiplex image analyses of CD4, CD68, CD8, FOXP3, cytokeratin, and PD-L1. Half of PD-L1 scores evaluated by tissue microarray were false negatives compared to whole slide evaluations. We observed at least 1% of PD-L1-positive (PD-L1+) cells in 53.1% of ER+HER2-, 73.3% of HER2+, and 84.4% of TN tumors. PD-L1 expression was higher in ductal compared to lobular carcinomas, also within ER+HER2- tumors (p = 0.04). High PD-L1+ TILs score (> 50%) was independently associated with better outcome in TN tumors (HR = 0.27; 95%CI = 0.10-0.69). Within TN tumors, PD-L1 and TIL scores showed a modest but significant positive association with the number of silent mutations, but no association with BRCA1-like status. Multiplex image analyses indicated that PD-L1 is expressed on multiple immune cells (CD68+ macrophages, CD4+, FOXP3+, and CD8+ T cells) in the breast tumor microenvironment, independent of the PD-L1 status of the tumor cells. We found no evidence that levels of PD-L1+ TILs in TN breast cancer are driven by high mutation rate or BRCA1-like status.

A Computational Workflow Translates a 58-Gene Signature to a Formalin-Fixed, Paraffin-Embedded Sample-Based Companion Diagnostic for Personalized Treatment of the BRAF-Mutation-Like Subtype of Colorectal Cancers.

Colorectal cancer patients with the BRAF(p.V600E) mutation have poor prognosis in metastatic setting. Personalized treatment options and companion diagnostics are needed to better treat these patients. Previously, we developed a 58-gene signature to characterize the distinct gene expression pattern of BRAF-mutation-like subtype (accuracy 91.1%). Further experiments repurposed drug Vinorelbine as specifically lethal to this BRAF-mutation-like subtype. The aim of this study is to translate this 58-gene signature from a research setting to a robust companion diagnostic that can use formalin-fixed, paraffin-embedded (FFPE) samples to select patients with the BRAF-mutation-like subtype. BRAF mutation and gene expression data of 302 FFPE samples were measured (mutants = 57, wild-type = 245). The performance of the 58-gene signature in FFPE samples showed a high sensitivity of 89.5%. In the identified BRAF-mutation-like subtype group, 50% of tumours were known BRAF mutants, and 50% were BRAF wild-type. The stability of the 58-gene signature in FFPE samples was evaluated by two control samples over 40 independent experiments. The standard deviations (SD) were within the predefined criteria (control 1: SD = 0.091, SD/Range = 3.0%; control 2: SD = 0.169, SD/Range = 5.5%). The fresh frozen version and translated FFPE version of this 58-gene signature were compared using 170 paired fresh frozen and FFPE samples and the result showed high consistency (agreement = 99.3%). In conclusion, we translated this 58-gene signature to a robust companion diagnostic that can use FFPE samples.

Equivalence of MammaPrint array types in clinical trials and diagnostics.

MammaPrint is an FDA-cleared microarray-based test that uses expression levels of the 70 MammaPrint genes to assess distant recurrence risk in early-stage breast cancer. The prospective RASTER study proved that MammaPrint Low Risk patients can safely forgo chemotherapy, which is further subject of the prospective randomized MINDACT trial. While MammaPrint diagnostic results are obtained from mini-arrays, clinical trials may be performed on whole-genome arrays. Here we demonstrate the equivalence and reproducibility of the MammaPrint test. MammaPrint indices were collected for breast cancer samples: (i) on both customized certified array types (n = 1,897 sample pairs), (ii) with matched fresh and FFPE tissues (n = 552 sample pairs), iii) for control samples replicated over a period of 10 years (n = 11,333), and iv) repeated measurements (n = 280). The array type indicated a near perfect Pearson correlation of 0.99 (95 % CI: 0.989-0.991). Paired fresh and FFPE samples showed an excellent Pearson correlation of 0.93 (95 % CI 0.92-0.94), in spite of the variability introduced by intratumoral tissue heterogeneity. Control samples showed high consistency over 10 year's time (overall reproducibility of 97.4 %). Precision and repeatability are overall 98.2 and 98.3 %, respectively. Results confirm that the combination of the near perfect correlation between array types, excellent equivalence between tissue types, and a very high stability, precision, and repeatability demonstrate that results from clinical trials (such as MINDACT and I-SPY 2) are equivalent to current MammaPrint FFPE and fresh diagnostics, and can be used interchangeably.

Performance characteristics of the MammaPrint® breast cancer diagnostic gene signature.

BACKGROUND: The analytical performance of multigene signatures depends on many parameters, including precision, repeatability, reproducibility and intratumor heterogeneity. Indicators such as sensitivity, specificity, positive predictive value and negative predictive value are typically used to define the clinical performance of a diagnostic test. AIM: Here we study these performance characteristics of the MammaPrint® (Agendia NV, Amsterdam, The Netherlands) 70-gene signature using the US FDA-recommended guidelines, as well as predetermined acceptance criteria. RESULTS: The clinical and analytical performance characteristics show that MammaPrint is a robust, reproducible, precise test, with a maximum variation of 5% in multiple samplings of the same tissue. CONCLUSION: MammaPrint is a reliable indicator of distant metastasis in early-stage breast cancer patients of all ages and is well suited for personalized medical care.

Implementation of a novel microarray-based diagnostic test for cancer of unknown primary.

Patients with carcinoma of unknown primary (CUP) present with metastatic disease for which the primary site cannot be found, despite extensive standard investigation. Here, we describe the development and implementation of the first clinically available microarray-based test for this cancer type (CUPPrint), based on 633 individual tumors representing 30 carcinoma and 17 noncarcinoma classes. Tissue of origin prediction for either fresh frozen or paraffin-embedded tumor samples is achieved with the use of a custom 8-pack 1.9k microarray and robust classification algorithm. An expression profile of 495 genes was used to predict tumor origin by applying a k-nearest neighbor algorithm. Internal cross-validation and analysis of an independent, previously published, 229-sample dataset revealed that clinically informative predictions were made for up to 94% of samples analyzed. Analysis of 13 previously published CUP specimens yielded predicted tumor origins that supported the clinical suspicion in 12 cases (92%). Microarray profiling presents a promising tool to assist in the identification of the primary tumor and might direct a more tailored treatment for CUP patients.

The transcriptomic signature of fasting murine liver.

BACKGROUND: The contribution of individual organs to the whole-body adaptive response to fasting has not been established. Hence, gene-expression profiling, pathway, network and gene-set enrichment analysis and immunohistochemistry were carried out on mouse liver after 0, 12, 24 and 72 hours of fasting. RESULTS: Liver wet weight had declined approximately 44, approximately 5, approximately 11 and approximately 10% per day after 12, 24, 48 and 72 hours of fasting, respectively. Liver structure and metabolic zonation were preserved. Supervised hierarchical clustering showed separation between the fed, 12-24 h-fasted and 72 h-fasted conditions. Expression profiling and pathway analysis revealed that genes involved in amino-acid, lipid, carbohydrate and energy metabolism responded most significantly to fasting, that the response peaked at 24 hours, and had largely abated by 72 hours. The strong induction of the urea cycle, in combination with increased expression of enzymes of the tricarboxylic-acid cycle and oxidative phosphorylation, indicated a strong stimulation of amino-acid oxidation peaking at 24 hours. At this time point, fatty-acid oxidation and ketone-body formation were also induced. The induction of genes involved in the unfolded-protein response underscored the cell stress due to enhanced energy metabolism. The continuous high expression of enzymes of the urea cycle, malate-aspartate shuttle, and the gluconeogenic enzyme Pepck and the re-appearance of glycogen in the pericentral hepatocytes indicate that amino-acid oxidation yields to glucose and glycogen synthesis during prolonged fasting. CONCLUSION: The changes in liver gene expression during fasting indicate that, in the mouse, energy production predominates during early fasting and that glucose production and glycogen synthesis become predominant during prolonged fasting.

Fasting induces a biphasic adaptive metabolic response in murine small intestine.

BACKGROUND: The gut is a major energy consumer, but a comprehensive overview of the adaptive response to fasting is lacking. Gene-expression profiling, pathway analysis, and immunohistochemistry were therefore carried out on mouse small intestine after 0, 12, 24, and 72 hours of fasting. RESULTS: Intestinal weight declined to 50% of control, but this loss of tissue mass was distributed proportionally among the gut's structural components, so that the microarrays' tissue base remained unaffected. Unsupervised hierarchical clustering of the microarrays revealed that the successive time points separated into distinct branches. Pathway analysis depicted a pronounced, but transient early response that peaked at 12 hours, and a late response that became progressively more pronounced with continued fasting. Early changes in gene expression were compatible with a cellular deficiency in glutamine, and metabolic adaptations directed at glutamine conservation, inhibition of pyruvate oxidation, stimulation of glutamate catabolism via aspartate and phosphoenolpyruvate to lactate, and enhanced fatty-acid oxidation and ketone-body synthesis. In addition, the expression of key genes involved in cell cycling and apoptosis was suppressed. At 24 hours of fasting, many of the early adaptive changes abated. Major changes upon continued fasting implied the production of glucose rather than lactate from carbohydrate backbones, a downregulation of fatty-acid oxidation and a very strong downregulation of the electron-transport chain. Cell cycling and apoptosis remained suppressed. CONCLUSION: The changes in gene expression indicate that the small intestine rapidly looses mass during fasting to generate lactate or glucose and ketone bodies. Meanwhile, intestinal architecture is maintained by downregulation of cell turnover.