Gene expression profiling and histopathological characterization of triple-negative/basal-like breast carcinomas.
TL;DR: Triple-negative tumors are synonymous with basal-like tumors, and can be identified by immunohistochemistry, based on gene-expression profiling, which revealed five distinct subgroups of triple-negative breast cancers.
Abstract: Introduction
Breast cancer is a heterogeneous group of tumors, and can be subdivided on the basis of histopathological features, genetic alterations and gene-expression profiles One well-defined subtype of breast cancer is characterized by a lack of HER2 gene amplification and estrogen and progesterone receptor expression ('triple-negative tumors') We examined the histopathological and gene-expression profile of triple-negative tumors to define subgroups with specific characteristics, including risk of developing distant metastases
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TL;DR: Gen expression profiles from 21 breast cancer data sets and identified 587 TNBC cases may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
Abstract: Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem–like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted “driver” signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
4,215 citations
Cites result from "Gene expression profiling and histo..."
...A previous TNBC study identified 5 distinct hierarchical clusters in which 91% (88 of 97) of TNBCs identified by IHC correlated to the basal-like subtype (42)....
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TL;DR: Triple-negative breast cancer, so called because it lacks expression of the estrogen receptor, progesterone receptor, and HER2, is often, but not always, a basal-like breast cancer.
Abstract: Triple-negative breast cancer, so called because it lacks expression of the estrogen receptor, progesterone receptor, and HER2, is often, but not always, a basal-like breast cancer. This review focuses on its origin, molecular and clinical characteristics, and treatment.
3,125 citations
TL;DR: Two broad categories of tumor escape based on cellular and molecular characteristics of the tumor microenvironment are suggested, which appear to resist immune attack through immune system exclusion or ignorance and may require distinct immunotherapeutic interventions for maximal therapeutic effect.
Abstract: Most tumor cells express antigens that can mediate recognition by host CD8(+) T cells. Cancers that are detected clinically must have evaded antitumor immune responses to grow progressively. Recent work has suggested two broad categories of tumor escape based on cellular and molecular characteristics of the tumor microenvironment. One major subset shows a T cell-inflamed phenotype consisting of infiltrating T cells, a broad chemokine profile and a type I interferon signature indicative of innate immune activation. These tumors appear to resist immune attack through the dominant inhibitory effects of immune system-suppressive pathways. The other major phenotype lacks this T cell-inflamed phenotype and appears to resist immune attack through immune system exclusion or ignorance. These two major phenotypes of tumor microenvironment may require distinct immunotherapeutic interventions for maximal therapeutic effect.
2,939 citations
TL;DR: The results of gene-expression studies that hold the most promise to accelerate the transition between empirical and molecular medicine are summarized.
Abstract: Gene-expression profiling with the use of DNA microarrays allows measurement of thousands of messenger RNA (mRNA) transcripts in a single experiment. Results of such studies have confirmed that breast cancer is not a single disease with variable morphologic features and biomarkers but, rather, a group of molecularly distinct neoplastic disorders. Profiling results also support the hypothesis that estrogen-receptor (ER)–negative and ER-positive breast cancers originate from distinct cell types and point to biologic processes that govern metastatic progression. Moreover, such profiling has uncovered molecular signatures that could influence clinical care. In this review, we summarize the results of gene-expression studies that hold the most promise to accelerate the transition between empirical and molecular medicine.
1,269 citations
TL;DR: A neoadjuvant trial of cisplatin in TNBC explored specific biomarkers to identify predictors of response and found decreased BRCA1 expression may identify subsets of TNBCs that are cis platin sensitive.
Abstract: PURPOSE Cisplatin is a chemotherapeutic agent not used routinely for breast cancer treatment. As a DNA cross-linking agent, cisplatin may be effective treatment for hereditary BRCA1-mutated breast cancers. Because sporadic triple-negative breast cancer (TNBC) and BRCA1-associated breast cancer share features suggesting common pathogenesis, we conducted a neoadjuvant trial of cisplatin in TNBC and explored specific biomarkers to identify predictors of response. PATIENTS AND METHODS Twenty-eight women with stage II or III breast cancers lacking estrogen and progesterone receptors and HER2/Neu (TNBC) were enrolled and treated with four cycles of cisplatin at 75 mg/m(2) every 21 days. After definitive surgery, patients received standard adjuvant chemotherapy and radiation therapy per their treating physicians. Clinical and pathologic treatment response were assessed, and pretreatment tumor samples were evaluated for selected biomarkers. Results Six (22%) of 28 patients achieved pathologic complete responses, including both patients with BRCA1 germline mutations;18 (64%) patients had a clinical complete or partial response. Fourteen (50%) patients showed good pathologic responses (Miller-Payne score of 3, 4, or 5), 10 had minor responses (Miller-Payne score of 1 or 2), and four (14%) progressed. All TNBCs clustered with reference basal-like tumors by hierarchical clustering. Factors associated with good cisplatin response include young age (P = .001), low BRCA1 mRNA expression (P = .03), BRCA1 promoter methylation (P = .04), p53 nonsense or frameshift mutations (P = .01), and a gene expression signature of E2F3 activation (P = .03). CONCLUSION Single-agent cisplatin induced response in a subset of patients with TNBC. Decreased BRCA1 expression may identify subsets of TNBCs that are cisplatin sensitive. Other biomarkers show promise in predicting cisplatin response.
904 citations
Cites methods from "Gene expression profiling and histo..."
...Predictors of Response The TNBCs tend to be classified as basal-like in gene expression array hierarchical cluster analysis using the intrinsic genes.(12,22) We determined the intrinsic subtype of all cases with adequate material (n 24) by co-clustering these cases with a reference set of tumors for which intrinsic subtype had been determined independently (Supplemental Fig 1, Supplemental Methods)....
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References
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TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Abstract: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is de- scribed that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be inter- preted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly charac- terized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
16,371 citations
TL;DR: Variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals were characterized using complementary DNA microarrays representing 8,102 human genes, providing a distinctive molecular portrait of each tumour.
Abstract: Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cell's identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.
14,768 citations
"Gene expression profiling and histo..." refers background or methods in this paper
...[4] as describing a subgroup of tumors that was defined by their great similarity in overall gene-expression pattern of the 'intrinsic gene subset' when unsupervised hierarchical clustering was applied....
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...[3-6] to define basallike, luminal A-like, luminal B-like, ERBB2-like and normal breast-like tumor classes on the basis of hierarchical clustering and correlation to the class centroids; using the intrinsic gene list as recently updated by Hu et al....
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...were the first to show that breast carcinomas can also be subdivided based on gene-expression analysis [3-6]....
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...This category of breast carcinomas has been shown to stand out from the other breast cancer subtypes by a unique geneexpression profile (basal-like subtype) revealed by geneexpression profiling studies [3-6,24-26]....
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...The largest difference in overall gene-expression profile is observed between tumors that are estrogen receptor (ER) positive and those that are ER negative [4]....
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TL;DR: A method that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements is described, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.
Abstract: Microarrays can measure the expression of thousands of genes to identify changes in expression between different biological states. Methods are needed to determine the significance of these changes while accounting for the enormous number of genes. We describe a method, Significance Analysis of Microarrays (SAM), that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of genes identified by chance, the false discovery rate (FDR). When the transcriptional response of human cells to ionizing radiation was measured by microarrays, SAM identified 34 genes that changed at least 1.5-fold with an estimated FDR of 12%, compared with FDRs of 60 and 84% by using conventional methods of analysis. Of the 34 genes, 19 were involved in cell cycle regulation and 3 in apoptosis. Surprisingly, four nucleotide excision repair genes were induced, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.
12,102 citations
"Gene expression profiling and histo..." refers methods in this paper
...Supervised classification was performed on the 71 samples with follow-up data using SAM-software [22] developed by Tusher et al. We used the settings in the software for cen- Page 3 of 14 (page number not for citation purposes) sored survival data....
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...Supervised classification was performed on the 71 samples with follow-up data using SAM-software [22] developed by Tusher et al....
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TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
Abstract: The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
10,791 citations
"Gene expression profiling and histo..." refers background or methods in this paper
...[3-6] to define basallike, luminal A-like, luminal B-like, ERBB2-like and normal breast-like tumor classes on the basis of hierarchical clustering and correlation to the class centroids; using the intrinsic gene list as recently updated by Hu et al....
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...were the first to show that breast carcinomas can also be subdivided based on gene-expression analysis [3-6]....
[...]
...This category of breast carcinomas has been shown to stand out from the other breast cancer subtypes by a unique geneexpression profile (basal-like subtype) revealed by geneexpression profiling studies [3-6,24-26]....
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...studied larger series of tumors (n = 416 cases) and refined the composition of the intrinsic gene set [3,5,6]....
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...It is believed that basal-like tumors constitute a homogenous sub-group of breast carcinomas [3-8]....
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TL;DR: DNA microarray analysis on primary breast tumours of 117 young patients is used and supervised classification is applied to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis, providing a strategy to select patients who would benefit from adjuvant therapy.
Abstract: Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.
9,664 citations
"Gene expression profiling and histo..." refers background in this paper
...Specific subgroups of triple-negative tumors may be formed by medullary and atypical medullary cancers [12,37-39]....
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...We have previously identified a 70-gene prognosis profile [12,13]....
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