Molecular Classification Of Breast Cancer Research Articles

Breast cancer special types: why bother?

Breast cancer is a heterogeneous disease, encompassing multiple entities associated with distinct biological features and clinical behaviours. Microarray-based expression profiling analysis has been used to unravel the molecular underpinning of several characteristics of breast cancer, including its proclivity to disseminate to distant sites and the molecular basis of histological grade. Furthermore, a breast cancer molecular classification based on transcriptional analysis has been proposed. However, microarray studies have primarily analysed invasive ductal carcinomas of no special type. Histological special types of breast cancer, which account for up to 25% of all invasive breast cancers, have not been systematically studied. Despite the limited interest, in recent years it has become apparent that the histopathological characteristics of these cancers may be underpinned by distinct arrays of genetic changes, providing direct evidence for genotypic-phenotypic correlations between morphological patterns and molecular changes in breast cancer (eg t(12;15) in secretory carcinoma of the breast). Here we review the molecular characteristics of special types of breast cancer, with special emphasis on their microarray-based expression profiles and their impact on our understanding of breast cancer.

A study on the relationship between breast cancer molecular classification and prognosis

To investigate the relationship between breast cancer molecular classification and prognosis. From January 2002 to December 2003, 708 female primary breast cancer patients with a mean age of 53 years old were retrospectively analyzed. The classification of breast cancer was according to the immunohistochemical results of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2) status. Molecular classification definitions included highly endocrine responsive, incompletely endocrine responsive, triple negative, and HER2 positive. The prognosis among different molecular classifications of breast cancer was investigated. The survival rates of different classifications were compared by Log-rank test. The proportion of highly endocrine responsive, incompletely endocrine responsive, HER2 positive and triple-negative breast cancer was 33.2% (235/708), 23.6% (167/708), 21.3% (151/708) and 21.9% (155/708). The follow-up period were from 3 to 68 months with a median of 40.2 months. A total of 100 cases were identified to had disease recurrence or death. Factors affecting the prognosis were tumor size, axillary lymph node status, molecular classification, adjuvant radiotherapy and adjuvant endocrine therapy by univariate analysis. Multivariate analysis revealed that the molecular classification and lymph node status were the independent prognostic factors with the hazard ratio 1.205 (P = 0.047) and 4.512 (P = 0.000), respectively. Survival analysis showed that highly endocrine responsive breast cancer was with superior prognosis versus others. Molecular classification of breast cancer is an independent predictor of prognosis. Breast cancer patients classified as highly endocrine responsive subtype have the best outcome.

Refinement of breast cancer classification by molecular characterization of histological special types

Most invasive breast cancers are classified as invasive ductal carcinoma not otherwise specified (IDC NOS), whereas about 25% are defined as histological 'special types'. These special-type breast cancers are categorized into at least 17 discrete pathological entities; however, whether these also constitute discrete molecular entities remains to be determined. Current therapy decision-making is increasingly governed by the molecular classification of breast cancer (luminal, basal-like, HER2+). The molecular classification is derived from mainly IDC NOS and it is unknown whether this classification applies to all histological subtypes. We aimed to refine the breast cancer classification systems by analysing a series of 11 histological special types [invasive lobular carcinoma (ILC), tubular, mucinous A, mucinous B, neuroendocrine, apocrine, IDC with osteoclastic giant cells, micropapillary, adenoid cystic, metaplastic, and medullary carcinoma] using immunohistochemistry and genome-wide gene expression profiling. Hierarchical clustering analysis confirmed that some histological special types constitute discrete entities, such as micropapillary carcinoma, but also revealed that others, including tubular and lobular carcinoma, are very similar at the transcriptome level. When classified by expression profiling, IDC NOS and ILC contain all molecular breast cancer types (ie luminal, basal-like, HER2+), whereas histological special-type cancers, apart from apocrine carcinoma, are homogeneous and only belong to one molecular subtype. Our analysis also revealed that some special types associated with a good prognosis, such as medullary and adenoid cystic carcinomas, display a poor prognosis basal-like transcriptome, providing strong circumstantial evidence that basal-like cancers constitute a heterogeneous group. Taken together, our results imply that the correct classification of breast cancers of special histological type will allow a more accurate prognostication of breast cancer patients and facilitate the identification of optimal therapeutic strategies.

Analyse du transcriptome des cancers du sein ER+ : discriminer les tumeurs agressives ou définir le traitement le plus adapté ?

The cDNA microarray technology allows the simultaneous analysis of all genes expressed in a tumor. This approach has already permitted to propose a molecular classification of breast cancers. Gene expression profiling is now expected to define prognosis signatures claiming the disease outcome as well as signatures predicting response to therapy. The over-expression of a cluster of genes that are implicated in cell cycle and mitosis control has been shown to discriminate a subgroup of ER+ breast cancers exhibiting a poor prognosis. This "proliferation cluster" is shown to be also present in signatures predicting relapse of ER+ breast cancers treated by the anti-estrogen tamoxifen, including the 36-gene classifier that we have recently identified. Consequently, it seems legitimate to wonder if this part of such predictive signature is really specific to the insensitivity to tamoxifen or rather indicates a poor disease outcome whatever the therapy applied. On the other hand, low expression of ER+ related genes and high expression of genes associated to ER- status or low ERalpha levels have been shown to sign a poor prognosis. Whether the estrogen-related genes that are present in our 36-gene classifier specify the clinical disease outcome or are really specific to the response to tamoxifen, remains to be determined. In any case, the specificity of our 36-gene classifier as those predicting the recurrence of ER+ breast cancer under one treatment or another should be demonstrated. In the same way, future studies should define molecular signatures that will be really predictive of the response to the treatment in order to define which one is the most suitable to decrease the risk of relapse of ER+ breast cancers. These studies should be based on neoadjuvant clinical trials that permit to evaluate the response to treatment in an objective manner.

The molecular classification of breast cancer according to the stem-cell model provides important informations for systemic adjuvant treatment decision

The molecular classification of breast cancer according to the stem-cell model provides important informations for systemic adjuvant treatment decision

Approaching molecular classification of breast cancer by using a panel of molecular tumor markers

Approaching molecular classification of breast cancer by using a panel of molecular tumor markers

Clinical, Histopathologic, and Immunohistochemical Features of Microglandular Adenosis and Transition Into In Situ and Invasive Carcinoma

Microglandular adenosis (MGA) of the breast is widely known as a benign lesion that can mimic invasive carcinoma. In situ and invasive carcinomas have been described as arising in MGA, but which cases of MGA will progress to carcinoma is unclear. Criteria for distinguishing uncomplicated MGA, MGA with atypia (AMGA), and carcinoma arising in MGA (MGACA) are not standardized. The primary objective of this study was to illustrate the clinical, histopathologic, and immunophenotypical characteristics of MGA, AMGA, and MGACA in an effort to provide criteria for distinguishing the 3 types. We retrospectively identified 108 cases seen at M.D. Anderson Cancer Center between 1983 and 2007 that had a diagnosis of MGA. Of the 108 cases, 65 cases had available material for review. Inclusion criteria were glands of MGA expressing S-100 protein and lacking myoepithelial layer (smooth muscle actin negative). Eleven out of 65 cases qualified to have an MGA component; myoepithelial layer was detected in the remaining 54 cases and were classified as adenosis. Out of the 11 MGA patients, there were 3 patients with uncomplicated MGA, 2 had AMGA, and 6 had MGACA. Staining indices for the cell cycle markers p53 and Ki-67 were used to compare the 3 tumor categories. Additional staining for other tumor markers [estrogen and progesterone receptors, HER2, epidermal growth factor receptor (EGFR), c-kit, CK5/6, and CK18] were performed. Patient demographics, tumor radiologic features, and clinical follow-up data were collected for all cases. Multiple invasive histologic components were identified in each of the MGACA cases. All invasive MGACAs had a duct-forming component. In addition, basal-like component was present in 2 cases, aciniclike in 2, matrix producing in 4, sarcomatoid in 1, and adenoid cystic in 1. All tumors had strong and diffuse CK8/18 and EGFR expression but no estrogen receptor, progesterone receptor, HER2 (ie, triple negative), or CK5/6 expression. C-kit was focally expressed in 2 of the MGACAs. Ki-67 and p53 labeling indices was < 3% in all MGAs, 5% to 10% in the AMGAs, and > 30% in MGACAs. In a follow-up ranging from 14 days to 8 years, none of the MGA cases recurred. One of the AMGA cases recurred as invasive carcinoma in a background of AMGA after 8 years following incomplete excision of the lesion. Three out of 6 MGACA cases (50%) required multiple consecutive resections ending up with mastectomy due to involved margins by invasive or in situ carcinoma. Two out of 6 MGACA cases (34%) developed metastasis and died of disease. Our data showed that Ki-67 and p53 expression, in conjunction with the morphologic features, could be a reliable marker to distinguish MGA from AMGA and MGACA. Although 11 tumors were only included in our study, 64% of the tumors were carcinomas arising in MGA. This high incidence of MGACA may not represent the actual frequency of MGAs progressing into carcinoma and is likely due to referral bias in our institution. Nonetheless, the high association of carcinoma with MGA necessitates complete excision of MGA to rule out invasion. Although all the MGACA cases were triple negative and express EGFR (basal-like features), all the cases in our study showed a luminal type of differentiation by CK8/18 expression, indicating that MGACA may not fit well into the current proposed molecular classification of breast cancer.

A study on the relationship between breast cancer molecular classification and prognosis

A study on the relationship between breast cancer molecular classification and prognosis

Gene arrays for diagnosis, prognosis and treatment of breast cancer metastasis

The advent of microarray tools has generated a massive amount of gene expression data. These data have greatly enhanced our understanding of the biology of breast cancer metastasis and provide a way to improve the prediction of the metastatic potential of breast tumours. Gene-expression profiling has highlighted the molecular heterogeneity of mammary tumours and contributed to the identification of a new molecular classification of breast cancers. In addition, several molecular signatures predicting the likelihood of distant metastases for breast cancer patients have been characterized. Further reports have described gene expression profiles associated with specific metastatic phenotypes, including the organ preference of breast cancer metastasis. Here we review the major studies that had important impacts on the understanding of breast cancer metastasis. We also discuss the future challenges in this research field and the special issues that still need to be examined.

Taking gene-expression profiling to the clinic: when will molecular signatures become relevant to patient care?

The advent of microarray technology has enabled scientists to simultaneously investigate the expression of thousands of genes. Gene-expression profiling studies have provided a molecular classification of breast cancer into clinically relevant subtypes, new tools to predict disease recurrence and response to different treatments, and new insights into various oncogenic pathways and the process of metastatic progression. Here we describe the state of the art of gene-expression studies in breast cancer, and consider both their current limitations and future promises. We also discuss the potential of molecular signatures to have an impact on individual breast cancer patient management, and ultimately to accelerate the transition between empirical and tailored medicine.

Les cancers du sein

Breast cancer is a major health problem as well as scientifically poorly understood. Our knowledge of breast cancer is however rapidly progressing in several directions. First, genomic studies are establishing a new molecular classification of breast cancers. Molecular subtypes have been identified and are being associated with the histoclinical forms of breast cancers. Second, genetic alterations are discovered and classified, generating new potential therapeutical targets. Third, mammary stem cells have been identified in the normal mammary epithelium. Their altered counterparts have been identified in tumors and are being characterized. These combined studies allow a new integrated cellular and molecular definition of breast cancers and a conceptual basis that will help the management of the disease.

Molecular classification of breast cancer: implications for selection of adjuvant chemotherapy

Adjuvant chemotherapy improves survival of patients with stage I-III breast cancer but it is being increasingly recognized that the benefit is not equal for all patients. Molecular characteristics of the cancer affect sensitivity to chemotherapy. In general, estrogen-receptor-negative disease is more sensitive to chemotherapy than estrogren-receptor-positive disease. Large-scale genomic analyses of breast cancer suggest that further molecular subsets may exist within the categories defined by hormone receptor status. It is hoped that the new molecular classification schemes might improve patient selection for therapy. Before any new molecular classification (or predictive test) is adopted for routine clinical use, however, several criteria need to be met. There must be an agreed and reproducible method by which to assign molecular class to a new case. Cancers that belong to different molecular classes must show differences in disease outcome and treatment efficacy that affect management and treatment selection. Also desirable are results from prospective clinical trials that demonstrate improved patient outcome when the new test is used in decision-making, compared with the current standard of care. This Review describes the current limitations and future promises of gene-expression-based molecular classification of breast cancer and how it might impact on selection of adjuvant therapy for individual patients.

Molecular Classification of Breast Cancer: Limitations and Potential

Reverse transcription polymerase chain reaction and DNA microarrays are increasingly used in the clinic and in clinical research as prognostic or predictive tests. Results from these tests led to novel risk stratification methods and to new molecular classification of breast cancer. Some of these tools already complement existing diagnostic tests and can aid medical decision making in some situations. Better understanding of the molecular classes of breast cancer, independent of their prognostic and predictive values, may also lead to new biological insights and eventually to better therapies that are directed toward particular molecular subsets. However, there is substantially less experience with these emerging technologies than with the more established methods, the accuracy of which is often overestimated. This review discusses some of the limitations and strengths of current gene expression-based molecular classification of breast cancer. To provide context for this discussion, we also briefly examine the performance of estrogen receptor immunohistochemistry, which represents an essential part of the routine diagnostic workup for all breast cancer patients.

In search of a stem cell hierarchy in the human breast and its relevance to breast cancer evolution

By deliberate analogy with the well-established concept of hematopoiesis, the term "mammopoiesis" is occasionally used to describe the development of the different cellular lineages and functional units in the mammary gland. The use of this term signifies a strong bias towards the idea that tissue homeostasis during mammary development, pregnancy, lactation and involution is brought about by the action of somatic stem cells characterized by longevity and multipotency. The progenies hereof eventually differentiate into structurally and functionally well-defined ductal-lobular units. During the past two decades evidence of such a notion in the mouse has developed from being largely circumstantial based on non-clonal in vivo experiments to a quite elaborate characterization of individual candidate stem cells by a number of different properties. Within tumor biology this has led to a renaissance of the concept of tumors as caricatures of tissue renewal. Thus, recent molecular classification of breast cancer based on genome wide expression analysis operates with different subtypes with specific reference to the normal luminal epithelial and myoepithelial/basal lineages in the breast. Apparently some tumors are lineage restricted and others differentiate more broadly as if they have preserved some stem-like properties. This holds promise for the existence of a stem cell hierarchy, the understanding of which may prove to be instrumental in further dissecting the histogenesis of breast cancer evolution. Most attention has been devoted to the question of different cellular origins of cancer subtypes and different susceptibilities of possible stem cells to gain or loss of oncogenes and tumor suppressor genes, respectively. Invaluable progress has been made over the past two decades in culture technology not only in terms of population doubling and clonal growth, but also the availability of lineage specific markers, cell sorting, and three-dimensional functional assays for tissue specific morphogenesis. Transcriptional profiling of stem cell zones has unraveled a hitherto unknown preservation of signaling pathways for maintenance of stem cell properties across tissue boundaries and species. Somatic stem cells have therefore been narrowed down to specific anatomic locations not only in rapidly renewing tissues such as skin and skin derivatives, but also in tissues with slower turnover times, such as lung, kidney and prostate. It is therefore now possible to integrate this information in a search for similar cells within the breast. Even if cell turnover after birth is provided exclusively by dividing lineage-restricted cells, more information about the robustness of breast differentiation programs during tumor progression is still very much required. Complete knowledge of the primary cell of origin of breast cancer and the mechanisms that influence differentiation programs during tumor initiation, promotion and progression may be crucial for the development of novel non-toxic therapies that influence tumor cell behaviour. The scope of this review is to discuss reports that have begun to elucidate the topographic location, key cellular type and lineage fidelity in culture and xenograft models of candidate human breast stem cells and their differentiated progenies with particular emphasis on comparison with the differentiation programs of tumor subtypes.

Breast Cancer Molecular Subtypes Respond Differently to Preoperative Chemotherapy

Molecular classification of breast cancer has been proposed based on gene expression profiles of human tumors. Luminal, basal-like, normal-like, and erbB2+ subgroups were identified and were shown to have different prognoses. The goal of this research was to determine if these different molecular subtypes of breast cancer also respond differently to preoperative chemotherapy. Fine needle aspirations of 82 breast cancers were obtained before starting preoperative paclitaxel followed by 5-fluorouracil, doxorubicin, and cyclophosphamide chemotherapy. Gene expression profiling was done with Affymetrix U133A microarrays and the previously reported "breast intrinsic" gene set was used for hierarchical clustering and multidimensional scaling to assign molecular class. The basal-like and erbB2+ subgroups were associated with the highest rates of pathologic complete response (CR), 45% [95% confidence interval (95% CI), 24-68] and 45% (95% CI, 23-68), respectively, whereas the luminal tumors had a pathologic CR rate of 6% (95% CI, 1-21). No pathologic CR was observed among the normal-like cancers (95% CI, 0-31). Molecular class was not independent of conventional cliniocopathologic predictors of response such as estrogen receptor status and nuclear grade. None of the 61 genes associated with pathologic CR in the basal-like group were associated with pathologic CR in the erbB2+ group, suggesting that the molecular mechanisms of chemotherapy sensitivity may vary between these two estrogen receptor-negative subtypes. The basal-like and erbB2+ subtypes of breast cancer are more sensitive to paclitaxel- and doxorubicin-containing preoperative chemotherapy than the luminal and normal-like cancers.