Molecular classification of breast carcinoma

Breast cancer is a complex disease encompassing multiple tumour entities each with a characteristic morphology and behaviour. Current clinical practice relies on the recognition of various pathology prognostic factors to guide patient management, including histological type and grade, stage and biomarker receptor status. However, there is increasing concern that these parameters are of limited value for the accurate prediction of individual patient outcome. The introduction of genome-wide microarray-based expression profiling studies has allowed better understanding of the molecular underpinning of several characteristics of breast cancer, including histological grade and metastatic potential. Expression profiling has also facilitated the identification of prognostic and predictive gene expression signatures and novel therapeutic targets. Here we review the evolution of molecular classification of breast cancer, including special types, the implications for clinical management, limitations of findings thus far and predictions for the future.     

Molecular evolution of breast cancer

Molecular analysis of invasive breast cancer and its precursors has furthered our understanding of breast cancer progression. In the past few years, new multi-step pathways of breast cancer progression have been delineated through genotypic-phenotypic correlations. Nuclear grade, more than any other pathological feature, is strongly associated with the number and pattern of molecular genetic abnormalities in breast cancer cells. Thus, there are two distinct major pathways to the evolution of low- and high-grade invasive carcinomas: whilst the former consistently show oestrogen receptor (ER) and progesterone receptor (PgR) positivity and 16q loss, the latter are usually ER/PgR-negative and show Her-2 overexpression/amplification and complex karyotypes. The boundaries between the evolutionary pathways of well-differentiated/low-grade ductal and lobular carcinomas have been blurred, with changes in E-cadherin expression being one of the few distinguishing features between the two. In addition, lesions long thought to be precursors of breast carcinomas, such as hyperplasia of usual type, are currently considered mere risk indicators, whilst columnar cell lesions are now implicated as non-obligate precursors of atypical ductal hyperplasia (ADH) and well-differentiated ductal carcinoma in situ (DCIS). However, only through the combination of comprehensive morphological analysis and cutting-edge molecular tools can this knowledge be translated into clinical practice and patient management.     

Molecular diagnosis in breast cancer

Breast cancer is a complex and heterogeneous disease, encompassing a plethora of entities with distinct biological features and clinical behaviour. The advent of high throughput molecular methods has allowed a systematic characterization of the genomic landscape of breast cancer, revealing a profound heterogeneity in this disease. These methods are having a profound effect on the understanding of breast cancer. Some have already been incorporated in clinical practice, such as the prognostic ‘gene signatures’ that allow the tailoring of therapy in the subgroup of patients with oestrogen receptor (ER)-positive and HER2-negative breast cancer. In this review, we discuss the contribution of the main molecular methods in breast cancer research and how this information is changing our approaches to the diagnosis and management of this disease. We also address novel developments in the diagnosis and management of HER2-positive breast carcinomas and familial breast cancer.     

Molecular classification of estrogen receptor-positive/luminal breast cancers

Estrogen receptor (ER)-positive breast cancer is the most prevalent subtype of invasive breast cancers. Patients with ER-positive breast cancers have variable clinical outcomes and responses to endocrine therapy and chemotherapy. With the advent of microarray-based gene expression profiling, unsupervised analysis methods have resulted in a classification of ER-positive disease into subtypes with different outcomes (ie, luminal A and luminal B); subsequent studies have demonstrated that these subtypes have different patterns of genetic aberrations and outcome. Studies based on supervised methods of microarray analysis have led to the development of prognostic gene signatures that identify a subgroup of ER-positive breast cancer patients with excellent outcome, who could forego chemotherapy. Despite the excitement with these approaches, several lines of evidence have demonstrated that the subclassification of ER-positive cancers and the prognostic value of gene signatures is largely driven by the expression levels of proliferation-related genes and that proliferation markers, such as Ki67, may provide equivalent prognostic information to that provided by gene signatures. In this review, we discuss the contribution of gene expression profiling to the classification of ER-positive breast cancer, the role of prognostic and predictive signatures, and the potential stratification of ER-positive disease according to their dependency on the phosphatidylinositol 3-kinase pathway.     

Molecular classification of breast carcinomas using tissue microarrays.

The histopathologic classification of breast cancer stratifies tumors based on tumor grade, stage, and type. Despite an overall correlation with survival, this classification is poorly predictive and tumors with identical grade and stage can have markedly contrasting outcomes. Recently, breast carcinomas have been classified by their gene expression profiles on frozen material. The validation of such a classification on formalin-fixed paraffin-embedded tumor archives linked to clinical information in a high-throughput fashion would have a major impact on clinical practice. The authors tested the ability of tumor tissue microarrays (TMAs) to sub-classify breast cancers using a TMA containing 107 breast cancers. The pattern of expression of 13 different protein biomarkers was assessed by immunohistochemistry and the multidimensional data was analyzed using an unsupervised two-dimensional clustering algorithm. This revealed distinct tumor clusters which divided into two main groups correlating with tumor grade (P<0.001) and nodal status (P = 0.04). None of the protein biomarkers tested could individually identify these groups. The biological significance of this classification is supported by its similarity with one derived from gene expression microarray analysis. Thus, molecular profiling of breast cancer using a limited number of protein biomarkers in TMAs can sub-classify tumors into clinically and biologically relevant subgroups.     

乳腺癌治疗靶点及靶向治疗研究新进展

乳腺癌靶向治疗在临床实践中取得了显著的疗效,把乳腺癌的治疗推向了一个前所未有的水平。信号转导干预治疗是针对信号转导通路中发生异常的环节来干预这种不正常的信号转导,从而达到抑制肿瘤生长的目的,主要治疗药物有曲妥珠单抗、拉帕替尼、蛋白激酶C（PKC）-α抑制剂、环氧化酶2（COX-2）抑制剂。表皮生长因子受体（EGFR）靶向治疗的主要药物有吉非替尼和西妥昔单抗,其它的靶点和药物有血管内皮生长因子（VEGF）的靶向治疗（贝伐单抗）、血管生成抑制（阿瓦斯丁）、细胞凋亡（G3139和组蛋白脱乙酰基转移酶抑制剂）和热点靶蛋白（Mr70000）。本文主要讲述了乳腺癌治疗的靶点及靶向治疗研究新进展。乳腺癌分子靶向治疗的优势很多,但还不能替代传统的手术切除和化疗,靶向治疗只是术后辅助治疗的一种重要的手段。     

炎性乳腺癌分子病理学研究进展

炎性乳腺癌(inflammatory breast cancer,IBC)~([1])虽为一种较少见的乳腺恶性肿瘤,但由于它的高侵袭性、高转移复发率和低无病生存率而引起肿瘤学家的关注.而以往病理学者多认为IBC是一种以临床表现为特征的乳腺癌,对其缺乏重视.近年来国外学者们对于其概念和意义有了新的认识,在分子病理学方面的研究进展也很快.但国内研究尚少~([2-3]).笔者拟从几方面介绍其新进展,希望能引起同道们的研究兴趣.     

三阴性乳腺癌分子分型研究进展

肿瘤的治疗模式日趋个体化, 选用精准的治疗方案, 对于三阴性乳腺癌患者来说具有重要意义。三阴性乳腺癌异质性较高, 即使是同样的临床分期和治疗方案, 不同类型的三阴性乳腺癌患者治疗效果也不完全一样。近年来, 研究者们通过对基因组和转录组测序分析发现, 三阴性乳腺癌患者的分子表型不尽相同, 提示其分子表型的差异可能是导致化疗反应及预后不同的原因。本文介绍三阴性乳腺癌分子分型研究进展, 有助于选择有效的靶向药物, 以期在提高疗效和延长生存方面取得更大突破。     

Molecular classification predicts survival for breast cancer patients in Vietnam: a single institutional retrospective analysis

Background: The Bhagarva surrogate molecular subtype definitions classify invasive breast cancer into seven the different subgroups based on immunohistochemical (IHC) criteria according to expression levels of markers as ER, PR, HER2, EGFR and/or basal cytokeratin (CK5/6) which are different in prognosis and responsiveness to adjuvant therapy. Purpose: The present study aimed to classify primary breast cancers and directly compares the prognostic significance of the intrinsic subtypes. Methods: The current study was conducted on 522 breast cancer patients who had surgery, but had not received neoadjuvant chemotherapy, from 2011 to 2014. The clinicopathologic characteristics were recorded. IHC staining was performed for ER, PR, HER2, Ki67, CK5/6, EGFR and D2-40 markers. All breast cancer patients were stratified according to Bhagarva criteria. The followed-up patients’ survival was analyzed by using Kaplan-Meier and Log-Rank models. Results: The luminal A (LUMA) was observed at the highest rate (32.5%). Non-basal-like triple negative phenotype (TNB-) and Luminal A HER2-Hybrid (LAHH) were the least common (3.3% in both). LUMA and luminal B (LUMB) were significantly associated with better prognostic features compared to HER2, basal-like triple negative phenotype (TNB+) and TNB-. Statistically significant differences were demonstrated between overall survival (OS), disease-free survival (DFS) and molecular subtypes (P<0.05), of which LUMB and LUMA had the highest rate of OS and DFS being 97.2 and 93.7%; and 97.2 and 90.5%, respectively. Conversely, HER2 revealed the worst prognosis with the lowest prevalence of OS and DFS (72.5 and 69.9%, respectively). Conclusion: The molecular subtypes had a distinct OS and DFS. The intrinsic stratification displayed inversely to clinicopathological features in breast cancer.     

Molecular assays in breast cancer pathology

Recent advances in understanding the molecular pathology of breast cancer offer significant potential to identify patients who may benefit from adjuvant therapies. To date, few of these advances are utilised in a routine setting. We review molecular assays that are currently in use or are in the advanced stages of development, which may be used as predictive or prognostic biomarkers in breast cancer.The only widely used breast cancer molecular assay is in situ hybridisation (ISH) for human epidermal growth factor receptor 2 (HER2) gene amplification and we highlight key issues with the interpretation of this assay, with particular attention to the difficulties of the equivocal category. New molecular assays such as ISH for the topoisomerase II alpha (TOP2A) gene and for the aberrations in the copy number of the centromeric region of chromosome 17 are readily performed in a standard histopathology laboratory, but to date there are insufficient data to support their routine use. We also review the current data on two commercially available multigene expression assays, Oncotype DX and MammaPrint and discuss their potential use. Overall, while new molecular assays have significant potential to improve patient selection for therapy, well-performed histopathology with reliable interpretation of standard hormone and HER2 assays provides the most important predictive and prognostic information in early breast cancer.     

Molecular evolutionary patterns in breast cancer

Geno-phenotypic patterns of pre-invasive and invasive lobular breast cancers and infiltrating ductal carcinomas of low, intermediate, and high grade are reviewed. One of the main differences between lobular breast cancers and ductal carcinomas is the presence of inactivating E-cadherin gene mutations in lobular breast cancers. In many other respects, lobular breast cancers and low-grade ductal carcinomas exhibit similar geno-phenotypic profiles. The development of p53 dysfunction may be a hallmark of infiltrating ductal cancers of intermediate and high grade. Sequential Her-2/neu and ras abnormalities define a subset of aggressive high-grade tumors, and the development of Rb dysfunction may define a separate subset of aggressive ductal cancers. Based on these observations, a branching molecular evolutionary model for the development and progression of breast cancer is proposed.     

Molecular and functional imaging of breast cancer

Despite several major advances in breast cancer diagnosis and treatment, the American Cancer Society has estimated that in the US alone 43300 women and 400 men will die from breast cancer in 2007. Breast cancer typically is a multi-focal, multi-faceted disease, with the major cause of mortality being complications due to metastasis. Whereas a decade ago genetic alterations were the primary focus in cancer research, it is now apparent that the physiological tumor microenvironment, interactions between cancer cells and stromal cells such as endothelial cells, fibroblasts and macrophages, the extracellular matrix, and a multitude of secreted factors and cytokines influence progression, aggressiveness, and response of the disease to treatment. Prevention, early diagnosis, and treatment are the three broad challenges for MR molecular and functional imaging in reducing mortality from this disease. Multi-parametric molecular and functional MRI provides unprecedented opportunities for identifying novel targets for imaging and therapy at the bench, as well as for accurate diagnosis and monitoring response to therapy at the bedside. Here we provide an overview of the current status of molecular and functional MRI of breast cancer, outlining some key developments, as well as identifying some of the important challenges facing this field in the future.