Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers.

Breast cancer prognostic classification in the molecular era: the role of histological grade

Molecular Subtypes and Local-Regional Control of Breast Cancer.

Breast cancer is a highly prevalent disease among women worldwide. While the expression of certain proteins within these tumours is used for prognosis and selection of therapies, there is a continuing need for additional markers to be identified. A considerable amount of current literature, based predominantly on cell culture systems, suggests that a major mechanism responsible for the progression of breast cancer is due to tumour cells losing their epithelial features and gaining mesenchymal properties. These events are proposed to be very similar to the epithelial-mesenchymal transition (EMT) process that has been well characterised in embryonic development. For the developmental and putative cancer EMT, the cell intermediate filament status changes from a keratin-rich network which connects to adherens junctions and hemidesmosomes, to a vimentin-rich network connecting to focal adhesions. This review summarises observations of vimentin expression in breast cancer model systems, and discusses the potential role of EMT in human breast cancer progression, and the prognostic usefulness of vimentin expression.

Vimentin and epithelial-mesenchymal transition in human breast cancer : observations in vitro and in vivo

Here we report for the first time the relation between breast cancer subtypes and 10-year recurrence rates and mortality in the Netherlands. All operated women diagnosed with invasive non-metastatic breast cancer in 2005 in the Netherlands were included. Patients were classified into breast cancer subtypes according to ER, PR, HER2 status and grade: luminal A, luminal B, HER2 positive and triple negative. Percentages and hazards of recurrence were compared among subtypes. Adjusted 10-year overall (OS) and recurrence-free survival (RFS) were calculated using multivariable Cox regression. Of 8,062 patients, 4,482 (56%) were luminal A, 2,090 (26%) luminal B, 504 (6%) HER2 positive and 986 (12%) triple negative. Local recurrences (7.5%) and distant metastases (25.6%) occurred most often in HER2 positive disease and the least often in luminal A (3.7% and 9.5%, respectively). Regional recurrences were most often diagnosed in triple negative disease (5.2%), and the least often in luminal A (1.7%). HER2 positive and triple negative subtypes had the highest recurrence rates in the second year, while luminal A and B showed a more continuous pattern over time, with lobular tumours recurring more often. After adjustment for differences in baseline characteristics, triple negative disease showed worse 10-year OS and triple negative and HER2 positive disease had the lowest 10-year RFS. In the Netherlands, breast cancer subtypes are important predictors for 10-year recurrence rates. Knowledge on recurrence and survival rates according to these different subtypes, in combination with other prognostic factors, can support patient-tailored treatment and individualised follow-up.

Ten-year recurrence rates for breast cancer subtypes in the Netherlands: A large population-based study.

BACKGROUND: A better definition of biomarkers and biological processes related to local recurrence and disease progression is highly warranted for ductal breast carcinoma in situ (DCIS). Stromal-epithelial interactions are likely of major importance for the biological, clinical, and pathological distinctions between high- and low-risk DCIS cases.METHODS: Stromal platelet derived growth factor receptor (PDGFR) was immunohistochemically assessed in two DCIS patient cohorts (n = 458 and n = 80). Cox proportional hazards models were used to calculate the hazard ratios of recurrence. The molecular mechanisms regulating stromal PDGFR expression were investigated in experimental in vitro co-culture systems of DCIS cells and fibroblasts and analyzed using immunoblot and quantitative real-time PCR. Knock-out of JAG1 in DCIS cells and NOTCH2 in fibroblasts was obtained through CRISPR/Cas9. Experimental data were validated by mammary fat pad injection of DCIS and DCIS-JAG1 knock-out cells (10 mice per group). All statistical tests were two-sided.RESULTS: PDGFRα(low)/PDGFRβ(high) fibroblasts were associated with increased risk for recurrence in DCIS (univariate hazard ratio = 1.59, 95% confidence interval [CI] = 1.02 to 2.46; P = .04 Wald test; multivariable hazard ratio = 1.78, 95% CI = 1.07 to 2.97; P = .03). Tissue culture and mouse model studies indicated that this fibroblast phenotype is induced by DCIS cells in a cell contact-dependent manner. Epithelial Jagged1 and fibroblast Notch2 were identified through loss-of-function studies as key juxtacrine signaling components driving the formation of the poor prognosis-associated fibroblast phenotype.CONCLUSIONS: A PDGFRα(low)/PDGFRβ(high) fibroblast subset was identified as a marker for high-risk DCIS. The Jagged-1/Notch2/PDGFR stroma-epithelial pathway was described as a novel signaling mechanism regulating this poor prognosis-associated fibroblast subset. In general terms, the study highlights epithelial-stromal crosstalk in DCIS and contributes to ongoing efforts to define clinically relevant fibroblast subsets and their etiology. (Less)

Impact of Epithelial-Stromal Interactions on Peritumoral Fibroblasts in Ductal Carcinoma in Situ.

Background: The St Gallen surrogate definition of the intrinsic subtypes of breast cancer consist of five subgroups based on estrogen receptor (ER), progesterone receptor (PgR), human epidermal gro ...

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Histological grade provides significant prognostic information in addition to breast cancer subtypes defined according to St Gallen 2013.

The study aimed to investigate expression of epithelial-to-mesenchymal transition (EMT)-related proteins and phenotypes during breast cancer progression and to relate this to patient outcome. Protein expression patterns of E-cadherin, N-cadherin, twist, and vimentin were examined by immunohistochemistry on formalin-fixed paraffin-embedded samples from primary tumors (PTs) (n = 419), synchronous lymph node metastases (LNMs) (n = 131) and recurrences (n = 34) from patients included in an observational prospective primary breast cancer study. Markers were evaluated individually and combined as defined EMT phenotypes (epithelial, mesenchymal, partial EMT, and negative). EMT profiles were compared between matched tumor progression stages, and related to clinicopathological data and distant recurrence-free interval (DRFi). N-cadherin-positivity, vimentin-positivity, mesenchymal and partial EMT phenotypes were associated with more aggressive tumor characteristics such as triple-negative subtype. Single EMT markers and phenotype discordance rates between paired tumor samples were observed in the range of 2–35%. Non-epithelial phenotypes were more frequently identified in recurrences compared to PTs, however, no skewness of expression or phenotype was detected between PTs and matched LNMs or between PTs and matched recurrences (Exact McNemar test). Interestingly, patients with a twist positive PT had shorter DRFi, compared to patients with a twist negative PT (hazard ratio (HR) 2.4, 95% confidence interval (CI) 1.2–5.1, P = 0.02). Essentially, the same effect was seen in multivariable analysis (HR 2.5, 95% CI 0.97–6.6, P = 0.06). The epithelial phenotype was indicated to be lost between PTs and recurrences as a reflection of tumor progression. Twist status of the PT was related to long-term prognosis warranting further investigation in larger cohorts.

/pdf/expression-of-epithelial-mesenchymal-transition-related-20d7jfs7x8.pdf

Expression of epithelial-mesenchymal transition-related markers and phenotypes during breast cancer progression.

Prognostic factors in breast cancer are often measured on a continuous scale, but categorized for clinical decision-making. The primary aim of this study was to evaluate if accounting for continuous non-linear effects of the three factors age at diagnosis, tumor size, and number of positive lymph nodes improves prognostication. These factors will most likely be included in the management of breast cancer patients also in the future, after an expected implementation of gene expression profiling for adjuvant treatment decision-making. Four thousand four hundred forty seven and 1132 women with primary breast cancer constituted the derivation and validation set, respectively. Potential non-linear effects on the log hazard of distant recurrences of the three factors were evaluated during 10 years of follow-up. Cox-models of successively increasing complexity: dichotomized predictors, predictors categorized into three or four groups, and predictors transformed using fractional polynomials (FPs) or restricted cubic splines (RCS), were used. Predictive performance was evaluated by Harrell’s C-index. Using FP-transformations, non-linear effects were detected for tumor size and number of positive lymph nodes in univariable analyses. For age, non-linear transformations did, however, not improve the model fit significantly compared to the linear identity transformation. As expected, the C-index increased with increasing model complexity for multivariable models including the three factors. By allowing more than one cut-point per factor, the C-index increased from 0.628 to 0.674. The additional gain, as measured by the C-index, when using FP- or RCS-transformations was modest (0.695 and 0.696, respectively). The corresponding C-indices for these four models in the validation set, based on the same transformations and parameter estimates from the derivation set, were 0.675, 0.700, 0.706, and 0.701. Categorization of each factor into three to four groups was found to improve prognostication compared to dichotomization. The additional gain by allowing continuous non-linear effects modeled by FPs or RCS was modest. However, the continuous nature of these transformations has the advantage of making it possible to form risk groups of any size.

/pdf/non-linear-transformations-of-age-at-diagnosis-tumor-size-1lvncj0g1e.pdf

Non-linear transformations of age at diagnosis, tumor size, and number of positive lymph nodes in prediction of clinical outcome in breast cancer

The platelet-derived growth factor (PDGF) signalling pathway is often dysregulated in cancer and PDGF-receptor expression has been linked to unfavourable prognostic factors in breast cancer (eg ER negativity, high Ki67 and high grade) This study aimed to evaluate the expression of PDGFRα, PDGFRβ and ligand PDGF-CC in breast cancer in relation to molecular subtypes and prognosis Protein expression of tumour and/or stromal cell PDGFRα, PDGFRβ and PDGF-CC was evaluated in primary tumours (N = 489), synchronous lymph node metastases (N = 135) and asynchronous recurrences (N = 39) using immunohistochemistry in a prospectively maintained cohort of primary breast cancer patients included during 1999–2003 Distant recurrence-free interval (DRFi) was the primary end-point High expression of all investigated PDGF family members correlated to increasing Nottingham histopathological grade and high Ki67 Tumour cells displayed high expression of PDGFRα in 20%, and PDGF-CC in 21% of primary tumours, which correlated with the triple-negative subtype (TNBC) Patients with high PDGF-CC had inferior prognosis (P = 004) in terms of 5-year DRFi, whereas PDGFRα was up-regulated in lymph node metastasis and recurrences compared to primary tumours High primary tumour PDGFRα was associated with increased risk of central nervous system (CNS) recurrence High PDGFRα and PDGF-CC expression were linked to breast cancer with an aggressive biological phenotype, eg the TNBC subtype, and high PDGF-CC increased the risk of 5-year distant recurrence Tumour cell PDGFRα was significantly up-regulated in lymph node metastases and asynchronous recurrences Our findings support an active role of the PDGF signalling pathway in tumour progression

/pdf/the-pdgf-pathway-in-breast-cancer-is-linked-to-tumour-348fsqjbbr.pdf

The PDGF pathway in breast cancer is linked to tumour aggressiveness, triple-negative subtype and early recurrence

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Histological grade provides significant prognostic information in addition to breast cancer subtypes defined according to St Gallen 2013.

Expression of epithelial-mesenchymal transition-related markers and phenotypes during breast cancer progression.

Non-linear transformations of age at diagnosis, tumor size, and number of positive lymph nodes in prediction of clinical outcome in breast cancer

The PDGF pathway in breast cancer is linked to tumour aggressiveness, triple-negative subtype and early recurrence