Ian O. Ellis

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ∼40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

Prognostic markers in triple-negative breast cancer.

Triple‐negative breast cancer (estrogen receptor‐negative, progesterone receptor‐negative, and HER2‐negative) is a high risk breast cancer that lacks the benefit of specific therapy that targets these proteins.

The Nottingham prognostic index in primary breast cancer

SummaryIn 1982 we constructed a prognostic index for patients with primary, operable breast cancer. This index was based on a retrospective analysis of 9 factors in 387 patients. Only 3 of the factors (tumour size, stage of disease, and tumour grade) remained significant on multivariate analysis. The index was subsequently validated in a prospective study of 320 patients. We now present the results of applying this prognostic index to all of the first 1,629 patients in our series of operable breast cancer up to the age of 70. We have used the index to define three subsets of patients with different chances of dying from breast cancer: 1) good prognosis, comprising 29% of patients with 80% 15-year survival; 2) moderate prognosis, 54% of patients with 42% 15-year survival; 3) poor prognosis, 17% of patients with 13% 15-year survival. The 15-year survival of an age-matched female population was 83%.

MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype

BackgroundMicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression.ResultsHere we report the analysis of miRNA expression in 93 primary human breast tumors, using a bead-based flow cytometric miRNA expression profiling method. Of 309 human miRNAs assayed, we identify 133 miRNAs expressed in human breast and breast tumors. We used mRNA expression profiling to classify the breast tumors as luminal A, luminal B, basal-like, HER2+ and normal-like. A number of miRNAs are differentially expressed between these molecular tumor subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumor subtypes in an independent data set. In some cases, changes in miRNA expression correlate with genomic loss or gain; in others, changes in miRNA expression are likely due to changes in primary transcription and or miRNA biogenesis. Finally, the expression of DICER1 and AGO2 is correlated with tumor subtype and may explain some of the changes in miRNA expression observed.ConclusionThis study represents the first integrated analysis of miRNA expression, mRNA expression and genomic changes in human breast cancer and may serve as a basis for functional studies of the role of miRNAs in the etiology of breast cancer. Furthermore, we demonstrate that bead-based flow cytometric miRNA expression profiling might be a suitable platform to classify breast cancer into prognostic molecular subtypes.

Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies

Paul Pharoah and colleagues evaluate the prognostic significance of immunohistochemical subtype classification in more than 10,000 breast cancer cases with early disease, and examine the influence of a patients survival time on the prediction of future survival.

Expression of luminal and basal cytokeratins in human breast carcinoma

We have examined basal and luminal cell cytokeratin expression in 1944 cases of invasive breast carcinoma, using tissue microarray (TMA) technology, to determine the frequency of expression of each cytokeratin subtype, their relationships and prognostic relevance, if any. Expression was determined by immunocytochemistry staining using antibodies to the luminal cytokeratins (CKs) 7/8, 18 and 19 and the basal markers CK 5/6 and CK 14. Additionally, assessment of α‐smooth muscle actin (SMA) and oestrogen receptor status (ER) was performed. The vast majority of the cases showed positivity for CK 7/8, 18 and 19 indicating a differentiated glandular phenotype, a finding associated with good prognosis, ER positivity and older patient age. In contrast, basal marker expression was significantly related to poor prognosis, ER negativity and younger patient age. Multivariate analysis showed that CK 5/6 was an independent indicator for relapse free interval. We were able to subgroup the cases into four distinct phenotype categories (pure luminal, mixed luminal/basal, pure basal and null), which had significant differences in relation to the biological features and the clinical course of the disease. Tumours classified as expressing a basal phenotype (the combined luminal plus basal and the pure basal) were in a poor prognostic subgroup, typically ER negative in most cases. These findings provide further evidence that breast cancer has distinct differentiation subclasses that have both biological and clinical relevance. Copyright

High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses

Recent studies on gene molecular profiling using cDNA microarray in a relatively small series of breast cancer have identified biologically distinct groups with apparent clinical and prognostic relevance. The validation of such new taxonomies should be confirmed on larger series of cases prior to acceptance in clinical practice. The development of tissue microarray (TMA) technology provides methodology for high‐throughput concomitant analyses of multiple proteins on large numbers of archival tumour samples. In our study, we have used immunohistochemistry techniques applied to TMA preparations of 1,076 cases of invasive breast cancer to study the combined protein expression profiles of a large panel of well‐characterized commercially available biomarkers related to epithelial cell lineage, differentiation, hormone and growth factor receptors and gene products known to be altered in some forms of breast cancer. Using hierarchical clustering methodology, 5 groups with distinct patterns of protein expression were identified. A sixth group of only 4 cases was also identified but deemed too small for further detailed assessment. Further analysis of these clusters was performed using multiple layer perceptron (MLP)‐artificial neural network (ANN) with a back propagation algorithm to identify key biomarkers driving the membership of each group. We have identified 2 large groups by their expression of luminal epithelial cell phenotypic characteristics, hormone receptors positivity, absence of basal epithelial phenotype characteristics and lack of c‐erbB‐2 protein overexpression. Two additional groups were characterized by high c‐erbB‐2 positivity and negative or weak hormone receptors expression but showed differences in MUC1 and E‐cadherin expression. The final group was characterized by strong basal epithelial characteristics, p53 positivity, absent hormone receptors and weak to low luminal epithelial cytokeratin expression. In addition, we have identified significant differences between clusters identified in this series with respect to established prognostic factors including tumour grade, size and histologic tumour type as well as differences in patient outcomes. The different protein expression profiles identified in our study confirm the biologic heterogeneity of breast cancer and demonstrate the clinical relevance of classification in this manner. These observations could form the basis of revision of existing traditional classification systems for breast cancer.

Prognostic Value of a Combined Estrogen Receptor, Progesterone Receptor, Ki-67, and Human Epidermal Growth Factor Receptor 2 Immunohistochemical Score and Comparison With the Genomic Health Recurrence Score in Early Breast Cancer

PURPOSE We recently reported that the mRNA-based, 21-gene Genomic Health recurrence score (GHI-RS) provided additional prognostic information regarding distant recurrence beyond that obtained from classical clinicopathologic factors (age, nodal status, tumor size, grade, endocrine treatment) in women with early breast cancer, confirming earlier reports. The aim of this article is to determine how much of this information is contained in standard immunohistochemical (IHC) markers. PATIENTS AND METHODS The primary cohort comprised 1,125 estrogen receptor-positive (ER-positive) patients from the Arimidex, Tamoxifen, Alone or in Combination (ATAC) trial who did not receive adjuvant chemotherapy, had the GHI-RS computed, and had adequate tissue for the four IHC measurements: ER, progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki-67. Distant recurrence was the primary end point, and proportional hazards models were used with sample splitting to control for overfitting. A prognostic model that used classical variables and the four IHC markers (IHC4 score) was created and assessed in a separate cohort of 786 patients. RESULTS All four IHC markers provided independent prognostic information in the presence of classical variables. In sample-splitting analyses, the information in the IHC4 score was found to be similar to that in the GHI-RS, and little additional prognostic value was seen in the combined use of both scores. The prognostic value of the IHC4 score was further validated in the second separate cohort. CONCLUSION This study suggests that the amount of prognostic information contained in four widely performed IHC assays is similar to that in the GHI-RS. Additional studies are needed to determine the general applicability of the IHC4 score.

An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer

BackgroundEstrogen receptor (ER)-negative breast cancer specimens are predominantly of high grade, have frequent p53 mutations, and are broadly divided into HER2-positive and basal subtypes. Although ER-negative disease has overall worse prognosis than does ER-positive breast cancer, not all ER-negative breast cancer patients have poor clinical outcome. Reliable identification of ER-negative tumors that have a good prognosis is not yet possible.ResultsWe apply a recently proposed feature selection method in an integrative analysis of three major microarray expression datasets to identify molecular subclasses and prognostic markers in ER-negative breast cancer. We find a subclass of basal tumors, characterized by over-expression of immune response genes, which has a better prognosis than the rest of ER-negative breast cancers. Moreover, we show that, in contrast to ER-positive tumours, the majority of prognostic markers in ER-negative breast cancer are over-expressed in the good prognosis group and are associated with activation of complement and immune response pathways. Specifically, we identify an immune response related seven-gene module and show that downregulation of this module confers greater risk for distant metastasis (hazard ratio 2.02, 95% confidence interval 1.2-3.4; P = 0.009), independent of lymph node status and lymphocytic infiltration. Furthermore, we validate the immune response module using two additional independent datasets.ConclusionWe show that ER-negative basal breast cancer is a heterogeneous disease with at least four main subtypes. Furthermore, we show that the heterogeneity in clinical outcome of ER-negative breast cancer is related to the variability in expression levels of complement and immune response pathway genes, independent of lymphocytic infiltration.

Triple-Negative Breast Cancer: Distinguishing between Basal and Nonbasal Subtypes

Purpose: Triple-negative (TN; estrogen receptor, progesterone receptor, and HER-2 negative) cancer and basal-like breast cancer (BLBC) are associated with poor outcome and lack the benefit of targeted therapy. It is widely perceived that BLBC and TN tumors are synonymous and BLBC can be defined using a TN definition without the need for the expression of basal markers. Experimental Design: We have used two well-defined cohorts of breast cancers with a large panel of biomarkers, BRCA1 mutation status, and follow-up data to compare the clinicopathologic and immunohistochemical features of TN tumors expressing one or more of the specific basal markers (CK5/6, CK17, CK14, and epidermal growth factor receptor; BLBC) with those TN tumors that express none of these markers (TN3BKE−). Results: Here, we show that although the morphologic features of BLBC are not significantly different from that of TN3BKE- tumors, BLBC showed distinct clinical and immunophenotypic differences. BLBC showed a statistically significant association with the expression of the hypoxia-associated factor (CA9), neuroendocrine markers, and other markers of poor prognosis such as p53. A difference in the expression of cell cycle-associated proteins and biomarkers involved in the immunologic portrait of tumors was seen. Compared with TN3BKE- tumors, BLBC was positively associated with BRCA1 mutation status and showed a unique pattern of distant metastasis, better response to chemotherapy, and shorter survival. Conclusion: TN breast cancers encompass a remarkably heterogeneous group of tumors. Expression of basal markers identifies a biologically and clinically distinct subgroup of TN tumors, justifying the use of basal markers (in TN tumors) to define BLBC.