Molecular Drivers of Oncotype DX, Prosigna, EndoPredict, and the Breast Cancer Index: A TransATAC Study.

PURPOSE: The Oncotype DX Recurrence Score (RS), Prosigna Prediction Analysis of Microarray 50 (PAM50) Risk of Recurrence (ROR), EndoPredict (EP), and Breast Cancer Index (BCI) are used clinically for estimating risk of distant recurrence for patients receiving endocrine therapy. Discordances in estimates occur between them. We aimed to identify the molecular features that drive the tests and lead to these differences. PATIENTS AND METHODS: Analyses for RS, ROR, EP, and BCI were conducted by the manufacturers in the TransATAC sample collection that consisted of the tamoxifen or anastrozole arms of the ATAC trial. Estrogen receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative cases without chemotherapy treatment were included in which all four tests were available (n = 785). Clinicopathologic features included in some tests were excluded from the comparisons. Estrogen, proliferation, invasion, and HER2 module scores from RS were used to characterize the respective molecular features. Spearman correlation and analysis of variance tests were applied. RESULTS: There were moderate to strong correlations among the four molecular scores (ρ = 0.63-0.74) except for RS versus ROR (ρ = 0.32) and RS versus BCI (ρ = 0.35). RS had strong negative correlation with its estrogen module (ρ = -0.79) and moderate positive correlation with its proliferation module (ρ = 0.36). RS's proliferation module explained 72.5% of ROR's variance, while the estrogen module explained only 0.6%. Most of EP's and BCI's variation was accounted for by the proliferation module (50.0% and 54.3%, respectively) and much less by the estrogen module (20.2% and 2.7%, respectively). CONCLUSION: In contrast to common understanding, RSs are determined more strongly by estrogen-related features and only weakly by proliferation markers. However, the EP, BCI, and particularly ROR scores are determined largely by proliferative features. These relationships help to explain the differences in the prognostic performance of the tests

Comparison of EndoPredict and EPclin With Oncotype DX Recurrence Score for Prediction of Risk of Distant Recurrence After Endocrine Therapy

This work was supported by the Royal Marsden National Institutes of Health Biomedical Research Centre and the Breast Cancer Now grant awarded to MD (CTR-Q4-Y1) and the Cancer Research UK grant awarded to JC (C569/A16891)

Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients

BACKGROUND: Molecular markers and the rich biological information they contain have great potential for cancer diagnosis, prognostication and therapy prediction. So far, however, they have not superseded routine histopathology and staging criteria, partly because the few studies performed on molecular subtyping have had little validation and limited clinical characterization. METHODS: We obtained gene expression and clinical data for 412 breast cancers obtained from population-based cohorts of patients from Stockholm and Uppsala, Sweden. Using the intrinsic set of approximately 500 genes derived in the Norway/Stanford breast cancer data, we validated the existence of five molecular subtypes – basal-like, ERBB2, luminal A/B and normal-like – and characterized these subtypes extensively with the use of conventional clinical variables. RESULTS: We found an overall 77.5% concordance between the centroid prediction of the Swedish cohort by using the Norway/Stanford signature and the k-means clustering performed internally within the Swedish cohort. The highest rate of discordant assignments occurred between the luminal A and luminal B subtypes and between the luminal B and ERBB2 subtypes. The subtypes varied significantly in terms of grade (p < 0.001), p53 mutation (p < 0.001) and genomic instability (p = 0.01), but surprisingly there was little difference in lymph-node metastasis (p = 0.31). Furthermore, current users of hormone-replacement therapy were strikingly over-represented in the normal-like subgroup (p < 0.001). Separate analyses of the patients who received endocrine therapy and those who did not receive any adjuvant therapy supported the previous hypothesis that the basal-like subtype responded to adjuvant treatment, whereas the ERBB2 and luminal B subtypes were poor responders. CONCLUSION: We found that the intrinsic molecular subtypes of breast cancer are broadly present in a diverse collection of patients from a population-based cohort in Sweden. The intrinsic gene set, originally selected to reveal stable tumor characteristics, was shown to have a strong correlation with progression-related properties such as grade, p53 mutation and genomic instability

Predicting Expected Absolute Chemotherapy Treatment Benefit in Women With Early-Stage Breast Cancer Using EndoPredict, an Integrated 12-Gene Clinicomolecular Assay.

PURPOSE: Previous studies have shown EndoPredict (EPclin), a test that integrates 12-gene expression data with nodal status and tumor size, to be predictive for risk of distant recurrence in women with estrogen receptor-positive, human epidermal growth factor receptor 2-negative early-stage breast cancer. Here, we modeled expected absolute chemotherapy benefit on the basis of EPclin test results. METHODS: The effect of chemotherapy was modeled using previously validated 10-year risk of distant recurrence as a function of EPclin score for patients treated without chemotherapy. Average relative chemotherapy benefit to reduce breast cancer distant recurrence was evaluated using a published meta-analysis from the Early Breast Cancer Trialists' Collaborative Group. Absolute chemotherapy benefit differences were estimated across a range of interaction strengths between relative chemotherapy benefit and EPclin score. The average absolute benefit was calculated for patients with high and low EPclin scores using the distribution of scores in 2,185 samples tested by Myriad Genetics. RESULTS: The average expected absolute benefit of chemotherapy treatment for patients with a low EPclin score was 1.8% in the absence of interaction and 1.5% for maximal interaction. Conversely, the expected average absolute chemotherapy benefit for patients with a high EPclin score was 5.3% and 7.3% for no interaction and maximal interaction, respectively. CONCLUSION: For women with estrogen receptor-positive, human epidermal growth factor receptor 2-negative early-stage breast cancer, a high EPclin score identified which patients would benefit most from adjuvant chemotherapy in terms of absolute reduction of distant recurrence, regardless of the amount of interaction between EPclin and relative chemotherapy benefit. A high degree of prognostic discrimination for distant recurrence is more important for identifying patients likely to benefit most from chemotherapy than an interaction between EPclin and treatment-relative benefit

Characterisation of breast fine-needle aspiration biopsies by centrosome aberrations and genomic instability

Recent studies have suggested that aneuploidy in malignant tumours could be a consequence of centrosome aberrations. Using immunofluorescence analysis with an antibody against γ-tubulin and DNA image cytometry, we measured centrosome aberrations and DNA ploidy patterns in fine-needle aspiration biopsies (FNABs) of 58 breast lesions. Benign lesions did not show any centrosome aberrations. DNA diploid carcinomas showed a mean percentage of cells with centrosomal defects of 2.1%. The aneuploid invasive carcinomas could be divided into two subgroups by their significantly (P=0.0003) different percentage of cells with centrosome aberrations (2.0 and 10.3%, respectively) and their significantly (P=0.0003) different percentage of cells with nonmodal DNA content values determined by the Stemline Scatter Index (SSI), a measure of genomic instability. The percentage of cells with centrosome aberrations demonstrated a positive, linear correlation with the corresponding SSI (r=0.82, P<0.0001) and loss of tissue differentiation (r=0.78, P<0.0001). Our results indicate the percentage of cells with centrosome aberrations as being sufficient to divide the investigated tumours into three significantly different groups: benign lesions with no centrosomal aberrations, and two malignant tumour types with mean values of 2.1 and 9.6% of centrosomal defects, respectively. Together, these results demonstrate that centrosome aberrations correlate with genomic instability and loss of tissue differentiation. Furthermore, this study shows the feasibility of centrosomal analysis in FNAB of the breast and suggests centrosomal aberrations as possessing diagnostic and prognostic value

Tyrosine kinase chromosomal translocations mediate distinct and overlapping gene regulation events

<p>Abstract</p> <p>Background</p> <p>Leukemia is a heterogeneous disease commonly associated with recurrent chromosomal translocations that involve tyrosine kinases including BCR-ABL, TEL-PDGFRB and TEL-JAK2. Most studies on the activated tyrosine kinases have focused on proximal signaling events, but little is known about gene transcription regulated by these fusions.</p> <p>Methods</p> <p>Oligonucleotide microarray was performed to compare mRNA changes attributable to BCR-ABL, TEL-PDGFRB and TEL-JAK2 after 1 week of activation of each fusion in Ba/F3 cell lines. Imatinib was used to control the activation of BCR-ABL and TEL-PDGFRB, and TEL-JAK2-mediated gene expression was examined 1 week after Ba/F3-TEL-JAK2 cells were switched to factor-independent conditions.</p> <p>Results</p> <p>Microarray analysis revealed between 800 to 2000 genes induced or suppressed by two-fold or greater by each tyrosine kinase, with a subset of these genes commonly induced or suppressed among the three fusions. Validation by Quantitative PCR confirmed that eight genes (Dok2, Mrvi1, Isg20, Id1, gp49b, Cxcl10, Scinderin, and collagen Vα1(Col5a1)) displayed an overlapping regulation among the three tested fusion proteins. Stat1 and Gbp1 were induced uniquely by TEL-PDGFRB.</p> <p>Conclusions</p> <p>Our results suggest that BCR-ABL, TEL-PDGFRB and TEL-JAK2 regulate distinct and overlapping gene transcription profiles. Many of the genes identified are known to be involved in processes associated with leukemogenesis, including cell migration, proliferation and differentiation. This study offers the basis for further work that could lead to an understanding of the specificity of diseases caused by these three chromosomal translocations.</p

Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

<p>Abstract</p> <p>Methods</p> <p>We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.</p> <p>Results</p> <p>Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR.</p> <p>Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.</p> <p>Conclusion</p> <p>The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.</p