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Basal-Like Breast Carcinoma

About: Basal-Like Breast Carcinoma is a research topic. Over the lifetime, 53 publications have been published within this topic receiving 42118 citations.


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Journal ArticleDOI
17 Aug 2000-Nature
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

Journal ArticleDOI
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

Journal ArticleDOI
TL;DR: The results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.
Abstract: Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.

5,281 citations

Journal ArticleDOI
07 Jun 2006-JAMA
TL;DR: Basal-like breast tumors occurred at a higher prevalence among premenopausal African American patients compared with postmenopausal American and non-African American patients in this population-based study, and their associations with tumor size, axillary nodal status, mitotic index, nuclear pleomorphism, combined grade, p53 mutation status, and breast cancer-specific survival were examined.
Abstract: ContextGene expression analysis has identified several breast cancer subtypes, including basal-like, human epidermal growth factor receptor-2 positive/estrogen receptor negative (HER2+/ER–), luminal A, and luminal B.ObjectivesTo determine population-based distributions and clinical associations for breast cancer subtypes.Design, Setting, and ParticipantsImmunohistochemical surrogates for each subtype were applied to 496 incident cases of invasive breast cancer from the Carolina Breast Cancer Study (ascertained between May 1993 and December 1996), a population-based, case-control study that oversampled premenopausal and African American women. Subtype definitions were as follows: luminal A (ER+ and/or progesterone receptor positive [PR+], HER2−), luminal B (ER+ and/or PR+, HER2+), basal-like (ER−, PR−, HER2−, cytokeratin 5/6 positive, and/or HER1+), HER2+/ER− (ER−, PR−, and HER2+), and unclassified (negative for all 5 markers).Main Outcome MeasuresWe examined the prevalence of breast cancer subtypes within racial and menopausal subsets and determined their associations with tumor size, axillary nodal status, mitotic index, nuclear pleomorphism, combined grade, p53 mutation status, and breast cancer–specific survival.ResultsThe basal-like breast cancer subtype was more prevalent among premenopausal African American women (39%) compared with postmenopausal African American women (14%) and non–African American women (16%) of any age (P<.001), whereas the luminal A subtype was less prevalent (36% vs 59% and 54%, respectively). The HER2+/ER− subtype did not vary with race or menopausal status (6%-9%). Compared with luminal A, basal-like tumors had more TP53 mutations (44% vs 15%, P<.001), higher mitotic index (odds ratio [OR], 11.0; 95% confidence interval [CI], 5.6-21.7), more marked nuclear pleomorphism (OR, 9.7; 95% CI, 5.3-18.0), and higher combined grade (OR, 8.3; 95% CI, 4.4-15.6). Breast cancer–specific survival differed by subtype (P<.001), with shortest survival among HER2+/ER− and basal-like subtypes.ConclusionsBasal-like breast tumors occurred at a higher prevalence among premenopausal African American patients compared with postmenopausal African American and non–African American patients in this population-based study. A higher prevalence of basal-like breast tumors and a lower prevalence of luminal A tumors could contribute to the poor prognosis of young African American women with breast cancer.

3,634 citations

Journal ArticleDOI
TL;DR: A panel of four antibodies (ER, HER1, HER2, and cytokeratin 5/6) can accurately identify basal-like tumors using standard available clinical tools and shows high specificity.
Abstract: Purpose: Expression profiling studies classified breast carcinomas into estrogen receptor (ER)+/luminal, normal breast-like, HER2 overexpressing, and basal-like groups, with the latter two associated with poor outcomes. Currently, there exist clinical assays that identify ER+/luminal and HER2-overexpressing tumors, and we sought to develop a clinical assay for breast basal-like tumors. Experimental Design: To identify an immunohistochemical profile for breast basal-like tumors, we collected a series of known basal-like tumors and tested them for protein patterns that are characteristic of this subtype. Next, we examined the significance of these protein patterns using tissue microarrays and evaluated the prognostic significance of these findings. Results: Using a panel of 21 basal-like tumors, which was determined using gene expression profiles, we saw that this subtype was typically immunohistochemically negative for estrogen receptor and HER2 but positive for basal cytokeratins, HER1, and/or c-KIT. Using breast carcinoma tissue microarrays representing 930 patients with 17.4-year mean follow-up, basal cytokeratin expression was associated with low disease-specific survival. HER1 expression was observed in 54% of cases positive for basal cytokeratins ( versus 11% of negative cases) and was associated with poor survival independent of nodal status and size. c-KIT expression was more common in basal-like tumors than in other breast cancers but did not influence prognosis. Conclusions: A panel of four antibodies (ER, HER1, HER2, and cytokeratin 5/6) can accurately identify basal-like tumors using standard available clinical tools and shows high specificity. These studies show that many basal-like tumors express HER1, which suggests candidate drugs for evaluation in these patients.

2,562 citations

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20211
20191
20181
20176
20164
20153