Tuesday 30 September 2003
breast carcinomas, mammary carcinoma, breast cancers, mammary carcinomas
Breast cancer, rather than constituting a monolithic entity, comprises heterogeneous tumors with different clinical characteristics, disease courses, and responses to specific treatments.
Tumor-intrinsic features, including classical histological and immunopathological classifications as well as more recently described molecular subtypes, separate breast tumors into multiple groups.
Tumor-extrinsic features, including microenvironmental configuration, also have prognostic significance and further expand the list of tumor-defining variables.
A better understanding of the features underlying heterogeneity, as well as of the mechanisms and consequences of their interactions, is essential to improve targeting of existing therapies and to develop novel agents addressing specific combinations of features.
To understand how such variation arises, it is instructive to examine the normal architecture of the breast environment.
Each lobe arises from multiple lobules, which connect to a common terminal interlobular duct.
These ducts then continue to their outlet at the nipple. Histologically, lobules and ducts are lined by a single layer of luminal epithelial cells, surrounded by transversely oriented myoepithelial cells.
These structures are separated from the surrounding tissue, or stroma, by a basement membrane, the breach of which distinguishes invasive carcinoma from carcinoma in situ.
The surrounding stroma comprises ECM, discrete cells (e.g., fibroblasts, immune cells, and adipocytes), and organized structures (e.g., blood vessels), each of which contributes to the overall configuration of the local microenvironment.
Classical pathology has segregated breast tumors into multiple categories, based on their overall morphology and structural organization.
The most common type observed and reported is invasive ductal carcinoma, not otherwise specified (IDC NOS; about 75% of cases), while invasive lobular carcinoma (ILC) represents the next most frequent histologic type of breast tumor (about 10% of cases).
Together, these two categories and combinations thereof make up the vast majority (about 90%) of breast cancers, while the remainder are categorized as medullary, neuroendocrine, tubular, apocrine, metaplastic, mucinous (A and B), inflammatory, comedo, adenoid cystic, and micropapillary types.
Interestingly, histologic type is linked to prognosis. While IDC NOS, ILC, apocrine, and medullary carcinomas have similar 10-year survival rates, adenoid cystic, medullary, mucinous, and tubular carcinomas exhibit relatively better overall outcomes.
However, the rarity of specific non-ILC/non-IDC tumors (known as “special types”) has resulted in a relative paucity of in-depth characterization of larger cohorts of such cases, and thus the details of how membership in these groups interacts with other factors contributing to tumor heterogeneity are not well understood.
The presence of specific markers in breast cancer has long been recognized to both define subtypes with differential overall prognosis and to identify tumors susceptible to targeted treatments.
Expression of the first two is assayed almost exclusively by immunohistochemistry (IHC)-based methods, which report levels of the corresponding proteins, while HER2 assays combine IHC and FISH approaches.
Ambiguous IHC-derived HER2 results are subjected to FISH testing for genomic amplification of HER2; cases in which the overall ratio of copies of the HER2 gene to those of its chromosome is greater than 2.2 are reported as HER2+.
ER status is utilized to identify tumors that may respond to anti-estrogen (endocrine) therapy, including ER antagonists or aromatase inhibitors, which target ER-dependent signaling.
PR status, generally correlated with ER status, has less clinical significance. PR status does not appear to predict relative benefit from specific types of endocrine therapy, and overall, ER+/PR+ cases may not receive additional benefit from endocrine therapy compared with ER+/PR– cases.
HER2+ cases are treated with targeted therapies such as the monoclonal antibody trastuzumab, which binds to HER2, mediates antibody-dependent cytotoxicity, and disrupts HER2-dependent signaling.
There is currently no standard targeted therapy for cases assessed as ER– and HER– by IHC, although this represents an intensive area of research.
Combinations of these markers allow for the assignment of individual cases to specific categories, namely:
triple negative (TN; ER–/PR–/HER2–)
triple positive (ER+/PR+/HER2+).
From a prognostic viewpoint, ER+ tumors exhibit the best overall outcome.
Following the advent of HER2-targeted therapies, HER2+ tumors, previously associated with poor outcome, now exhibit an improved overall outcome when treated with such therapies.
TN tumors, on the other hand, are linked to the worst prognosis among the subtypes, while triple-positive cases appeared to have a prognosis intermediate between those of ER+ and HER2+ cases prior to the introduction of HER2-targeted treatments.
mammary adenoid cystic carcinoma
mammary adenosquamous carcinoma, low grade
mammary apocrine carcinoma
mammary cribriform carcinoma
mammary infiltrating ductal carcinoma
mammary glycogen rich clear cell carcinoma
mammary histiocytoid carcinoma
mammary infiltrating lobular carcinoma
mammary inflammatory carcinoma
mammary lipid rich carcinoma
mammary low grade adenosquamous carcinoma
mammary medullary carcinoma
mammary metaplastic carcinoma
mammary invasive micropapillary carcinoma
mammary mucinous carcinoma
mammary neuroendocrine carcinoma, low grade
mammary neuroendocrine carcinoma, NOS
mammary neuroendocrine carcinoma, high grade
mammary oncocytic carcinoma
mammary carcinoma with osteoclast-like giant cells
mammary Paget disease
mammary secretory sarcinoma (secretory breast carcinoma)
mammary signet ring carcinoma (variant of lobular)
mammary small cell carcinoma
mammary tubular carcinoma
mammary tubulolobular carcinoma
Breast cancer susceptibility
See : breast cancer susceptibility
10q23.32-q25.3 locus (17171685)
Gene expression profiling
Gene expression profiling with breast carcinomas has allowed further classification of these tumors into 5 distinct subtypes with unique clinical outcomes:
Subsequent studies have shown that breast carcinomas can also be divided into 5 similar subgroups using immunohistochemical (IHC) analysis with a limited panel of molecular markers (including estrogen receptor, progesterone receptor, HER2, CK5/6, and epidermal growth factor receptor).
These subgroups have distinguishing features closely associated with subtypes defined by gene expression profiling, including distinct clinical outcomes.
Comparative genomic hybridization (16457699)
CGH revealed approximately 20 regions of recurrent increased DNA sequence copy number in breast tumors. These regions are predicted to encode dominantly acting genes that may play a role in tumor progression or response to therapy.
1q32.1 amplification (66%) (16457699)
8q24.3 amplification (79%): MYC (MIM.190080) (16457699)
11q13 amplification: CCND1 (MIM.168461) and EMS1 (MIM.164765)
16p13.3 amplification (57%)
17q12 amplification: ERBB2 (MIM.164870)
20q13 amplification (18%)
In breast cancer, ERBB2, CCND1 and EMS1 amplification and overexpression are associated with decreased life expectancy, whereas MYC amplification has been associated with lymph node involvement, advanced stage, and an increased rate of relapse.
20q13 gains in greater than 25% of cancers of the ovary, colon, head and neck, brain, and pancreas.
13q > RB1 (26%) (16457699)
hypermethylation and hypomethylation of CpG islands (16575877)
< div style="width:425px" id="__ss_9262758"> < strong style="display:block;margin:12px 0 4px"> < a href="http://www.slideshare.net/kirubavijay/breast-carcinoma-pathology" title="Breast carcinoma pathology" target="_blank">Breast carcinoma pathology < /a> < /strong> < iframe src="http://www.slideshare.net/slideshow/embed_code/9262758" width="425" height="355" frameborder="0" marginwidth="0" marginheight="0" scrolling="no"> < /iframe> < div style="padding:5px 0 12px"> View more < a href="http://www.slideshare.net/" target="_blank">presentations < /a> from < a href="http://www.slideshare.net/kirubavijay" target="_blank">Kripa Vijay < /a> < /div> < /div>
The role of molecular analysis in breast cancer. Geyer FC, Marchio C, Reis-Filho JS. Pathology. 2009 Jan;41(1):77-88. PMID: 19089743
Stingl J, Caldas C. Molecular heterogeneity of breast carcinomas and the cancer stem cell hypothesis. Nat Rev Cancer. 2007 Oct;7(10):791-9. PMID: 17851544
Weigelt B, Peterse JL, van ’t Veer LJ. Breast cancer metastasis: markers and models. Nat Rev Cancer. 2005 Aug;5(8):591-602. PMID: 16056258
Hunter DJ, Riboli E, Haiman CA, Albanes D, et al.; National Cancer Institute Breast and Prostate Cancer Cohort Consortium. A candidate gene approach to searching for low-penetrance breast and prostate cancer genes. Nat Rev Cancer. 2005 Dec;5(12):977-85. PMID: 16341085
O’Connell P. Genetic and cytogenetic analyses of breast cancer yield different perspectives of a complex disease. Breast Cancer Res Treat. 2003 Apr;78(3):347-57. PMID: 12755493
Welcsh PL, King MC. BRCA1 and BRCA2 and the genetics of breast and ovarian cancer. Hum Mol Genet. 2001 Apr;10(7):705-13. PMID: 11257103
Stratton MR. Recent advances in understanding of genetic susceptibility to breast cancer. Hum Mol Genet. 1996;5 Spec No:1515-9. PMID: 8875258
Overexpression of cell division cycle 7 homolog is associated with gene amplification frequency in breast cancer. Choschzick M, Lebeau A, Marx AH, Tharun L, Terracciano L, Heilenkötter U, Jaenicke F, Bokemeyer C, Simon R, Sauter G, Schwarz J. Hum Pathol. 2009 Nov 5. PMID: 19896697 (CDC7L1)
Expression profiling technology: its contribution to our understanding of breast cancer. Rakha EA, El-Sayed ME, Reis-Filho JS, Ellis IO. Histopathology. 2008 Jan;52(1):67-81. PMID: 18171418
Bergamaschi A, Kim YH, Wang P, Sorlie T, Hernandez-Boussard T, Lonning PE, Tibshirani R, Borresen-Dale AL, Pollack JR. Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer. Genes Chromosomes Cancer. 2006 Nov;45(11):1033-40. PMID: 16897746
Naylor TL, Greshock J, Wang Y, Colligon T, Yu QC, Clemmer V, Zaks TZ, Weber BL. High resolution genomic analysis of sporadic breast cancer using array-based comparative genomic hybridization. Breast Cancer Res. 2005;7(6):R1186-98. PMID: 16457699
Piotrowski A, Benetkiewicz M, Menzel U, de Stahl TD, Mantripragada K, Grigelionis G, Buckley PG, Jankowski M, Hoffman J, Bala D, Srutek E, Laskowski R, Zegarski W, Dumanski JP. Microarray-based survey of CpG islands identifies concurrent hyper- and hypomethylation patterns in tissues derived from patients with breast cancer. Genes Chromosomes Cancer. 2006 Jul;45(7):656-67. PMID: 16575877