Practical implications of gene-expression-based assays for breast oncologists

Acid ceramidase is associated with an improved prognosis in both DCIS and invasive breast cancer

Acid ceramidase (ASAH1) a key enzyme of sphingolipid metabolism converting pro-apoptotic ceramide to sphingosine has been shown to be overexpressed in various cancers. We previously demonstrated higher expression of ASAH1 in ER positive compared to ER negative breast cancer. In the current study we performed subtype specific analyses of ASAH1 gene expression in invasive and non invasive breast cancer. We show that expression of ASAH1 is mainly associated with luminal A - like cancers which are known to have the best prognosis of all breast cancer subtypes. Moreover tumors with high ASAH1 expression among the other subtypes are also characterized by an improved prognosis. The good prognosis of tumors with high ASAH1 is independent of the type of adjuvant treatment in breast cancer and is also detected in non small cell lung cancer patients. Moreover, even in pre-invasive DCIS of the breast ASAH1 is associated with a luminal phenotype and a reduced frequency of recurrences. Thus, high ASAH1 expression is generally associated with an improved prognosis in invasive breast cancer independent of adjuvant treatment and could also be valuable as prognostic factor for pre-invasive DCIS.

High Ki-67 Expression and Low Progesterone Receptor Expression Could Independently Lead to a Worse Prognosis for Postmenopausal Patients With Estrogen Receptor-Positive and HER2-Negative Breast Cancer

We examined the prognostic significance of progesterone receptor (PgR) expression in immunohistochemical-based luminal subtypes defined by Ki-67 expression, taking menopausal status into consideration. The study included 327 surgically removed estrogen receptor-positive and human epidermal growth factor receptor 2-negative breast cancers. High Ki-67 expression (> 15%) and low PgR expression (£ 20%) were significant independent factors resulting in worse distant relapse-free survival. This association was observed in postmenopausalwomen but not in premenopausal women.

BACKGROUND

Accurate classification of luminal A and luminal B characteristics of estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer is considered clinically important for determining effective adjuvant treatment. Although Ki-67 expression has been identified as an essential constituent for this classification, the role of progesterone receptor (PgR) expression has yet to be fully elucidated. Because PgR expression is influenced by the estrogen milieu, we examined the prognostic significance of PgR expression in immunohistochemical (IHC)-based luminal subtypes defined by Ki-67 expression, taking menopausal status into consideration.

MATERIALS AND METHODS

We examined 327 surgically removed ER(+) and HER2(-) breast cancer specimens. ER, PgR, and Ki67 expression was determined IHC for semiquantitative measurement. We used 1%, 20%, and 15% as the cutoff value for ER, PgR, and Ki-67, respectively.

RESULTS

Breast cancer with low PgR (≤ 20%) expression was significantly associated with postmenopausal status, a large tumor size, and low ER expression. The low PgR expression subset had significantly worse distant relapse-free survival (DRFS) than the high PgR expression subset (P = .0067). This association was observed consistently in postmenopausal women but not in the premenopausal women. Multivariate analysis demonstrated that high Ki-67 expression (hazard ratio [HR], 3.80; 95% confidence interval [CI], 1.57-10.58; P = .003) and low PgR expression (HR, 2.54; 95% CI, 1.08-6.40; P = .038) were significant independent factors affecting DRFS.

CONCLUSION

Low PgR expression was independently associated with a poorer prognosis for ER(+) and HER2(-) breast cancer. Determination of PgR expression combined with that of Ki-67 could thus improve the accuracy of IHC-based classification of luminal A and luminal B breast cancer, especially for postmenopausal women.

Why should cancer biologists care about tRNAs? tRNA synthesis, mRNA translation and the control of growth

Transfer RNAs (tRNAs) are essential for mRNA translation. They are transcribed in the nucleus by RNA polymerase III and undergo many modifications before contributing to cytoplasmic protein synthesis. In this review I highlight our understanding of how tRNA biology may be linked to the regulation of mRNA translation, growth and tumorigenesis. First, I review how oncogenes and tumour suppressor signalling pathways, such as the PI3 kinase/TORC1, Ras/ERK, Myc, p53 and Rb pathways, regulate Pol III and tRNA synthesis. In several cases, this regulation contributes to cell, tissue and body growth, and has implications for our understanding of tumorigenesis. Second, I highlight some recent work, particularly in model organisms such as yeast and Drosophila, that shows how alterations in tRNA synthesis may be not only necessary, but also sufficient to drive changes in mRNA translation and growth. These effects may arise due to both absolute increases in total tRNA levels, but also changes in the relative levels of tRNAs in the overall pool. Finally, I review some recent studies that have revealed how tRNA modifications (amino acid acylation, base modifications, subcellular shuttling, and cleavage) can be regulated by growth and stress cues to selectively influence mRNA translation. Together these studies emphasize the importance of the regulation of tRNA synthesis and modification as critical control points in protein synthesis and growth. This article is part of a Special Issue entitled: Translation and Cancer.

Molecular Markers as Prognostic Factors in DCIS and Small Invasive Breast Cancers

Ductal carcinoma in situ (DCIS) accounts for up to half of screen-detected breast cancers and thus constitutes a major public health problem. Despite effective current treatment many patients with DCIS are either over- or undertreated because of the paucity of precise models to predict recurrence or progression. The combination of clinical and molecular factors as already applied for invasive disease may help to build such models also for DCIS. We compared 53 DCIS (36.6 %) and 92 (63.4 %) invasive breast cancer cases and found no significant differences in age, receptor status of ER, PR, and HER2, and the use of radiotherapy. Interestingly, the proportion of disseminated tumor cells (DTC) did also not significantly differ between DCIS and invasive cases (p = 0.57). A negative PR status was associated with the detection of DTCs (p = 0.026). We then compared relationships of clinical parameters and biomarkers with patients' prognosis in 43 DCIS and 40 small invasive tumors ≤ 5 mm (T1a). ER negativity was associated with shorter relapse free survival in the complete cohort (p = 0.004) and showed a trend in both subgroups (p = 0.053 for DCIS and p = 0.046 for T1a, respectively). In conclusion, we found markedly similar properties of both DCIS and small invasive breast cancers with respect to the distribution of several parameters as well as to the prognostic value of biomarkers. DCIS with a luminal phenotype seem to be characterized by a favourable prognosis.

Axes of differentiation in breast cancer: untangling stemness, lineage identity, and the epithelial to mesenchymal transition

Differentiation-associated regulatory programs are central in determining tumor phenotype, and contribute to heterogeneity between tumors and between individual cells within them. The transcriptional programs that control luminal and basal lineage identity in the normal mammary epithelium, as well as progenitor and stem cell function, are active in breast cancers, and show distinct associations with different disease subtypes. Also active in some tumors is the epithelial to mesenchymal transition (EMT) program, which endows carcinoma cells with mesenchymal as well as stem cell traits. The differentiation state of breast cancer cells is thus dictated by the complex combination of regulatory programs, and these can dramatically affect tumor growth and metastatic capacity. Breast cancer differentiation is often viewed along an axis between a basal–mesenchymal–stem cell state and a luminal–epithelial–differentiated state. Here we consider the links, as well as the distinctions, between the three components of this axis: basal versus luminal, mesenchymal versus epithelial, and stem cell versus differentiated identity. Analysis on a multidimensional scale, in which each of these axes is assessed separately, may offer increased resolution of tumor differentiation state. Cancer cells possessing a high degree of stemness would display increased capacity to shift between positions on such a multidimensional scale, and to acquire intermediate phenotypes on its different axes. Further molecular analysis of breast cancer cells with a focus on single-cell profiling, and the development of improved tools for dissection of the circuits controlling gene activity, are essential for the elucidation of the programs dictating breast cancer differentiation state.

Molecular features and survival outcomes of the intrinsic subtypes within HER2-positive breast cancer

Background

The clinical impact of the biological heterogeneity within HER2-positive (HER2+) breast cancer is not fully understood. Here, we evaluated the molecular features and survival outcomes of the intrinsic subtypes within HER2+ breast cancer.

Methods

We interrogated The Cancer Genome Atlas (n = 495) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets (n = 1730) of primary breast cancers for molecular data derived from DNA, RNA and protein, and determined intrinsic subtype. Clinical HER2 status was defined according to American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines or DNA copy-number aberration by single nucleotide polymorphism arrays. Cox models tested the prognostic significance of each variable in patients not treated with trastuzumab (n = 1711).

Results

Compared with clinically HER2 (cHER2)-negative breast cancer, cHER2+ breast cancer had a higher frequency of the HER2-enriched (HER2E) subtype (47.0% vs 7.1%) and a lower frequency of Luminal A (10.7% vs 39.0%) and Basal-like (14.1% vs 23.4%) subtypes. The likelihood of cHER2-positivity in HER2E, Luminal B, Basal-like and Luminal A subtypes was 64.6%, 20.0%, 14.4% and 7.3%, respectively. Within each subtype, only 0.3% to 3.9% of genes were found differentially expressed between cHER2+ and cHER2-negative tumors. Within cHER2+ tumors, HER2 gene and protein expression was statistically significantly higher in the HER2E and Basal-like subtypes than either luminal subtype. Neither cHER2 status nor the new 10-subtype copy number-based classification system (IntClust) added independent prognostic value to intrinsic subtype.

Conclusions

When the intrinsic subtypes are taken into account, cHER2-positivity does not translate into large changes in the expression of downstream signaling pathways, nor does it affect patient survival in the absence of HER2 targeting.

Bioinformatic analysis reveals a pattern of STAT3-associated gene expression specific to basal-like breast cancers in human tumors

Signal transducer and activator of transcription 3 (STAT3), a latent transcription factor associated with inflammatory signaling and innate and adaptive immune responses, is known to be aberrantly activated in a wide variety of cancers. In vitro analysis of STAT3 in human cancer cell lines has elucidated a number of specific targets associated with poor prognosis in breast cancer. However, to date, no comparison of cancer subtype and gene expression associated with STAT3 signaling in human patients has been reported. In silico analysis of human breast cancer microarray and reverse-phase protein array data was performed to identify expression patterns associated with STAT3 in basal-like and luminal breast cancers. Results indicate clearly identifiable STAT3-regulated signatures common to basal-like breast cancers but not to luminal A or luminal B cancers. Furthermore, these differentially expressed genes are associated with immune signaling and inflammation, a known phenotype of basal-like cancers. These findings demonstrate a distinct role for STAT3 signaling in basal breast cancers, and underscore the importance of considering subtype-specific molecular pathways that contribute to tissue-specific cancers.

Biological subtypes of breast cancer: Prognostic and therapeutic implications

Breast cancer is a heterogeneous complex of diseases, a spectrum of many subtypes with distinct biological features that lead to differences in response patterns to various treatment modalities and clinical outcomes. Traditional classification systems regarding biological characteristics may have limitations for patient-tailored treatment strategies. Tumors with similar clinical and pathological presentations may have different behaviors. Analyses of breast cancer with new molecular techniques now hold promise for the development of more accurate tests for the prediction of recurrence. Gene signatures have been developed as predictors of response to therapy and protein gene products that have direct roles in driving the biology and clinical behavior of cancer cells are potential targets for the development of novel therapeutics. The present review summarizes current knowledge in breast cancer molecular biology, focusing on novel prognostic and predictive factors.

How many etiological subtypes of breast cancer: two, three, four, or more?

Breast cancer is a heterogeneous disease, divisible into a variable number of clinical subtypes. A fundamental question is how many etiological classes underlie the clinical spectrum of breast cancer? An etiological subtype reflects a grouping with a common set of causes, whereas a clinical subtype represents a grouping with similar prognosis and/or prediction. Herein, we review the evidence for breast cancer etiological heterogeneity. We then evaluate the etiological evidence with mRNA profiling data. A bimodal age distribution at diagnosis with peak frequencies near ages 50 and 70 years is a fundamental characteristic of breast cancer for important tumor features, clinical characteristics, risk factor profiles, and molecular subtypes. The bimodal peak frequencies at diagnosis divide breast cancer overall into a "mixture" of two main components in varying proportions in different cancer populations. The first breast cancer tends to arise early in life with modal age-at-diagnosis near 50 years and generally behaves aggressively. The second breast cancer occurs later in life with modal age near 70 years and usually portends a more indolent clinical course. These epidemiological and molecular data are consistent with a two-component mixture model and compatible with a hierarchal view of breast cancers arising from two main cell types of origin. Notwithstanding the potential added value of more detailed categorizations for personalized breast cancer treatment, we suggest that the development of better criteria to identify the two proposed etiologic classes would advance breast cancer research and prevention.

Invasive lobular breast cancer and its variants: how special are they for systemic therapy decisions?

The WHO classification of breast tumors distinguishes, besides invasive breast cancer 'of no special type' (former invasive ductal carcinoma, representing 60-70% of all breast cancers), 30 special types, of which invasive lobular carcinoma (ILC) is the most common (5-15%). We review the literature on (i) the specificity and heterogeneity of ILC biology as documented by various analytical techniques, including the results of molecular testing for risk of recurrence; (ii) the impact of lobular histology on prediction of prognosis and effect of systemic therapies in patients. Though it is generally admitted that ILC has a better prognosis than IDC, is endocrine responsive, and responds poorly to chemotherapy, currently available data do not unanimously support these assumptions. This review demonstrates some lack of specific data and a need for improving clinical research design to allow oncologists to make informed systemic therapy decisions in patients with ILC. Importantly, future studies should compare various endpoints in ILC breast cancer patients among the group of hormonosensitive breast cancer.

Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations

Introduction

Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts.

Methods

An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147).

Results

The original training cohort reached a statistically significant difference (p < 0.05) in disease-free survivals between the three CMTC groups after an additional two years of follow-up (median = 55 months). The prognostic value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups.

Conclusions

Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

Intrinsic basal and luminal subtypes of muscle-invasive bladder cancer

Whole-genome analyses have revealed that muscle-invasive bladder cancers (MIBCs) are heterogeneous and can be grouped into basal and luminal subtypes that are highly reminiscent of those found in breast cancer. Basal MIBCs are enriched with squamous and sarcomatoid features and are associated with advanced stage and metastatic disease at presentation. Like basal breast cancers, basal bladder tumours contain a claudin-low subtype that is enriched with biomarkers characteristic of epithelial-to-mesenchymal transition. The stem cell transcription factor ΔNp63α controls basal MIBC gene expression, just as it does in basal breast cancers. Luminal MIBCs are enriched with activating FGFR3 and ERBB3 mutations and ERBB2 amplifications, and their gene expression profiles are controlled by peroxisome proliferator activator receptor γ (PPARγ) and possibly also by oestrogen receptor activation. Luminal bladder cancers can be further subdivided into two subtypes, p53-like and luminal, which can be distinguished from one another by different levels of biomarkers that are characteristic of stromal infiltration, cell cycle progression, and proliferation. Importantly, basal bladder cancers are intrinsically aggressive, but are highly sensitive to cisplatin-based combination chemotherapy. Although the luminal subtypes are not as intrinsically aggressive as basal cancers, p53-like tumours are resistant to chemotherapy and might, therefore, represent a problem for treated patients.

Tumour cell invasion: an emerging role for basal epithelial cell extrusion

Metastasis is the leading cause of cancer-related deaths, but it is unclear how cancer cells escape their primary sites in epithelia and disseminate to other sites in the body. One emerging possibility is that transformed epithelial cells could invade the underlying tissue by a process called cell extrusion, which epithelia use to remove cells without disrupting their barrier function. Typically, during normal cell turnover, live cells extrude apically from the epithelium into the lumen and later die by anoikis; however, several oncogenic mutations shift cell extrusion basally, towards the tissue that the epithelium encases. Tumour cells with high levels of survival and motility signals could use basal extrusion to escape from the tissue and migrate to other sites within the body.

High-throughput gene expression and mutation profiling: current methods and future perspectives

Following the completion of the human genome sequence at the beginning of the new millennium, a series of high-throughput methods have changed cancer research. Using these techniques, global analysis such as expression profiling could be carried out on a genomic scale. In breast cancer they led to the classification of the intrinsic subtypes, and the development of several prognostic and predictive 'genomic tests' for patient stratification. During the last 2 years we have faced a similar dramatic revolution with the introduction of next generation sequencing (NGS). These techniques allow sequencing of the complete human exome or whole genome with a cost reduction in the order of 10,000-100,000 fold. Consequently, the number of known cancer genome sequences exploded with more than 6,000 samples, published between 2011 and 2013. These studies have led to important and surprising discoveries both for basic cancer research and clinical applications. They relate to understanding the development of cancer as well as the heterogeneity of the disease, and how to use this information to guide the development and application of therapies. Although it is foreseeable that the sequencing surveys of neoplasms will soon conclude, their introduction into clinical practice is just beginning.

A Tumor initiating cell-enriched prognostic signature for HER2+:ERα- breast cancer; rationale, new features, controversies and future directions

The high intra- and inter-tumor heterogeneity of many types of cancers, including breast cancer (BC), poses great challenge to development of subtype-specific prognosis. In BC, the classification of tumors as either ERα⁺ (Luminal A and Luminal B), HER2⁺ (ERα⁺ or ERα⁻) or triple-negative (TNBC)(Basal-like, claudin-low) guides both prognostication and therapy. Indeed, prognostic signatures for ERα⁺ BC are being incorporated into clinical use. However, these signatures distinguish between luminal A (low risk) and Luminal B (high risk) BC; signatures that identify low/high risk patients with luminal B BC are yet to be developed. Likewise, no signature is in clinical use for HER2⁺ or TNBC. The major obstacles to development of robust signatures stem from diversity of BC, clonal evolution and heterogeneity within each subtype. We have recently generated a prognostic signature for HER2⁺:ERα⁻ BC based on the identification of genes that were differentially expressed in a tumor-initiating cell (TIC)-enriched fraction versus non-TIC fraction from a mouse model of HER2⁺ BC (MMTV-Hers/Neu). Here we describe the rationale behind development of this prognosticator, and present new features of the signature, including elevated PI3K pathway activity and low TNFalpha and IFNgamma signaling in high-risk tumors. In addition, we address controversies in the field such as whether random gene expression signatures significantly associate with cancer outcome. Finally, we suggest a guideline for development of prognostic signatures and discuss future directions.

Where cancer genomics should go next: a clinician's perspective

Large-scale, genomic studies of specific tumors such as The Cancer Genome Atlas have provided a better understanding of the alterations of pathways involved in the development of solid tumors including glioblastoma, breast cancer, ovarian and endometrial cancers, colon cancer and lung squamous cell carcinoma. This tremendous effort of the scientific community has confirmed the view that cancer actually represents a wide variety of diseases originating from different organs. These studies showed that TP53 and PI3KCA are the two most mutated genes in all types of cancers and that 30-70% of all solid tumors harbor potentially 'actionable' mutations that can be exploited for patient stratification or treatment optimization. Translation of this huge oncogenomic data set to clinical application in personalized medicine programs is now the main challenge for the future. The gap between our basic knowledge and clinical application is still wide. Closing the gap will require translational personalized trials, which may initiate a radical change in our routine clinical practice in oncology.

Cancer biomarker discovery: current status and future perspectives

PURPOSE

Cancer is a multigene disease which arises as a result of mutational and epigenetic changes coupled with activation of complex signaling networks. The use of biomarkers for early cancer detection, staging and individualization of therapy might improve patient care. A few fundamental issues such as tumor heterogeneity, a highly dynamic nature of the intrinsic and extrinsic determinants of radio- and chemoresistance, along with the plasticity and diversity of cancer stem cells (CSC) make biomarker development a challenging task. In this review we outline the preclinical strategies of cancer biomarker discovery including genomic, proteomic, metabolomic and microRNomic profiling, comparative genome hybridization (CGH), single nucleotide polymorphism (SNP) analysis, high throughput screening (HTS) and next generation sequencing (NGS). Other promising approaches such as assessment of circulating tumor cells (CTC), analysis of CSC-specific markers and cell-free circulating tumor DNA (ctDNA) are also discussed.

CONCLUSIONS

The emergence of powerful proteomic and genomic technologies in conjunction with advanced bioinformatic tools allows the simultaneous analysis of thousands of biological molecules. These techniques yield the discovery of new tumor signatures, which are sensitive and specific enough for early cancer detection, for monitoring disease progression and for proper treatment selection, paving the way to individualized cancer treatment.

Cellular heterogeneity profiling by hyaluronan probes reveals an invasive but slow-growing breast tumor subset

Tumor heterogeneity confounds cancer diagnosis and the outcome of therapy, necessitating analysis of tumor cell subsets within the tumor mass. Elevated expression of hyaluronan (HA) and HA receptors, receptor for HA-mediated motility (RHAMM)/HA-mediated motility receptor and cluster designation 44 (CD44), in breast tumors correlates with poor outcome. We hypothesized that a probe for detecting HA-HA receptor interactions may reveal breast cancer (BCa) cell heterogeneity relevant to tumor progression. A fluorescent HA (F-HA) probe containing a mixture of polymer sizes typical of tumor microenvironments (10-480 kDa), multiplexed profiling, and flow cytometry were used to monitor HA binding to BCa cell lines of different molecular subtypes. Formulae were developed to quantify binding heterogeneity and to measure invasion in vivo. Two subsets exhibiting differential binding (HA(-/low) vs. HA(high)) were isolated and characterized for morphology, growth, and invasion in culture and as xenografts in vivo. F-HA-binding amounts and degree of heterogeneity varied with BCa subtype, were highest in the malignant basal-like cell lines, and decreased upon reversion to a nonmalignant phenotype. Binding amounts correlated with CD44 and RHAMM displayed but binding heterogeneity appeared to arise from a differential ability of HA receptor-positive subpopulations to interact with F-HA. HA(high) subpopulations exhibited significantly higher local invasion and lung micrometastases but, unexpectedly, lower proliferation than either unsorted parental cells or the HA(-/low) subpopulation. Querying F-HA binding to aggressive tumor cells reveals a previously undetected form of heterogeneity that predicts invasive/metastatic behavior and that may aid both early identification of cancer patients susceptible to metastasis, and detection/therapy of invasive BCa subpopulations.

Regulation of mammary epithelial cell homeostasis by lncRNAs

The epithelial cells of the mammary gland develop primarily after birth and undergo surges of hormonally regulated proliferation, differentiation, and apoptosis during both puberty and pregnancy. Thus, the mammary gland is a useful model to study fundamental processes of development and adult tissue homeostasis, such as stem and progenitor cell regulation, cell fate commitment, and differentiation. Long noncoding RNAs (lncRNAs) are emerging as prominent regulators of these essential processes, as their extraordinary versatility allows them to modulate gene expression via diverse mechanisms at both transcriptional and post-transcriptional levels. Not surprisingly, lncRNAs are also aberrantly expressed in cancer and promote tumorigenesis by disrupting vital cellular functions, such as cell cycle, survival, and migration. In this review, we first broadly summarize the functions of lncRNAs in mammalian development and cancer. Then we focus on what is currently known about the role of lncRNAs in mammary gland development and breast cancer. This article is part of a Directed Issue entitled: The Non-coding RNA Revolution.

O6-methylguanine-DNA methyltransferase as a prognostic and predictive marker for basal-like breast cancer treated with cyclophosphamide-based chemotherapy

The O⁶-methylguanine-DNA methyltransferase (MGMT) protein protects cells from alkylating agents by removing alkyl groups from the O⁶-position of guanine. However, its effect on DNA damage induced by cyclophosphamide (CPM) is unclear. The present study investigated whether MGMT expression was correlated with prognosis in patients with breast cancer that was managed according to a common therapeutic protocol or treated with CPM-based chemotherapy. The intrinsic subtypes and MGMT protein expression levels were assessed in 635 consecutive patients with breast cancer using immunohistochemistry. In total, 425 (67%) luminal A, 95 (15%) luminal B, 47 (7%) human epidermal growth factor receptor-2⁺/estrogen receptor^- (HER2⁺/ER^-) and 48 (8%) basal-like subtypes were identified. Of these, MGMT positivity was identified in 398 (63%) of 635 breast cancers; 68% of luminal A, 67% of luminal B, 30% of HER2⁺/ER^- and 46% of basal-like subtypes were positive. The overall survival (OS) and disease-free survival (DFS) rates did not significantly differ according to the MGMT status among patients with luminal A, luminal B or HER2⁺/ER^- subtypes, and patients with MGMT-negative basal-like cancers tended to have a longer DFS, but not a significantly longer OS time. CPM-containing chemotherapy was administered to 26%, 40%, 47% and 31% of patients with luminal A, luminal B, HER2⁺/ER^- and basal-like tumors, respectively. Although the MGMT status and clinical outcomes of patients with the luminal A, luminal B or HER2⁺/ER^- subtypes treated with CPM were not significantly correlated, the patients with MGMT-negative basal-like tumors who received CPM exhibited significantly improved DFS and OS compared with the CPM-treated patients with MGMT-positive tumors. MGMT may be a useful prognostic and predictive marker for CPM-containing chemotherapy in basal-like breast cancer.

Intrinsic subtypes from PAM50 gene expression assay in a population-based breast cancer cohort: differences by age, race, and tumor characteristics

BACKGROUND

Data are lacking to describe gene expression-based breast cancer intrinsic subtype patterns for population-based patient groups.

METHODS

We studied a diverse cohort of women with breast cancer from the Life After Cancer Epidemiology and Pathways studies. RNA was extracted from 1 mm punches from fixed tumor tissue. Quantitative reverse-transcriptase PCR was conducted for the 50 genes that comprise the PAM50 intrinsic subtype classifier.

RESULTS

In a subcohort of 1,319 women, the overall subtype distribution based on PAM50 was 53.1% luminal A, 20.5% luminal B, 13.0% HER2-enriched, 9.8% basal-like, and 3.6% normal-like. Among low-risk endocrine-positive tumors (i.e., estrogen and progesterone receptor positive by immunohistochemistry, HER2 negative, and low histologic grade), only 76.5% were categorized as luminal A by PAM50. Continuous-scale luminal A, luminal B, HER2-enriched, and normal-like scores from PAM50 were mutually positively correlated. Basal-like score was inversely correlated with other subtypes. The proportion with non-luminal A subtype decreased with older age at diagnosis, P Trend < 0.0001. Compared with non-Hispanic Whites, African American women were more likely to have basal-like tumors, age-adjusted OR = 4.4 [95% confidence intervals (CI), 2.3-8.4], whereas Asian and Pacific Islander women had reduced odds of basal-like subtype, OR = 0.5 (95% CI, 0.3-0.9).

CONCLUSIONS

Our data indicate that over 50% of breast cancers treated in the community have luminal A subtype. Gene expression-based classification shifted some tumors categorized as low risk by surrogate clinicopathologic criteria to higher-risk subtypes.

IMPACT

Subtyping in a population-based cohort revealed distinct profiles by age and race.

Tumor microenvironment-associated modifications of alternative splicing

Pre-mRNA alternative splicing is modified in cancer, but the origin and specificity of these changes remain unclear. Here, we probed ovarian tumors to identify cancer-associated splicing isoforms and define the mechanism by which splicing is modified in cancer cells. Using high-throughput quantitative PCR, we monitored the expression of splice variants in laser-dissected tissues from ovarian tumors. Surprisingly, changes in alternative splicing were not limited to the tumor tissues but were also found in the tumor microenvironment. Changes in the tumor-associated splicing events were found to be regulated by splicing factors that are differentially expressed in cancer tissues. Overall, ∼20% of the alternative splicing events affected by the down-regulation of the splicing factors QKI and RBFOX2 were altered in the microenvironment of ovarian tumors. Together, our results indicate that the tumor microenvironment undergoes specific changes in alternative splicing orchestrated by a limited number of splicing factors.

Taxonomy of breast cancer based on normal cell phenotype predicts outcome

Accurate classification is essential for understanding the pathophysiology of a disease and can inform therapeutic choices. For hematopoietic malignancies, a classification scheme based on the phenotypic similarity between tumor cells and normal cells has been successfully used to define tumor subtypes; however, use of normal cell types as a reference by which to classify solid tumors has not been widely emulated, in part due to more limited understanding of epithelial cell differentiation compared with hematopoiesis. To provide a better definition of the subtypes of epithelial cells comprising the breast epithelium, we performed a systematic analysis of a large set of breast epithelial markers in more than 15,000 normal breast cells, which identified 11 differentiation states for normal luminal cells. We then applied information from this analysis to classify human breast tumors based on normal cell types into 4 major subtypes, HR0-HR3, which were differentiated by vitamin D, androgen, and estrogen hormone receptor (HR) expression. Examination of 3,157 human breast tumors revealed that these HR subtypes were distinct from the current classification scheme, which is based on estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Patient outcomes were best when tumors expressed all 3 hormone receptors (subtype HR3) and worst when they expressed none of the receptors (subtype HR0). Together, these data provide an ontological classification scheme associated with patient survival differences and provides actionable insights for treating breast tumors.

Research-based PAM50 subtype predictor identifies higher responses and improved survival outcomes in HER2-positive breast cancer in the NOAH study

PURPOSE

We report a retrospective exploratory analysis of the association of the research-based prediction analysis of microarray 50 (PAM50) subtype predictor with pathologic complete response (pCR) and event-free survival (EFS) in women enrolled in the NeOAdjuvant Herceptin (NOAH) trial.

EXPERIMENTAL DESIGN

Gene expression profiling was performed using RNA from formalin-fixed paraffin-embedded core biopsies from 114 pretreated patients with HER2-positive (HER2(+)) tumors randomized to receive neoadjuvant doxorubicin/paclitaxel (AT) followed by cyclophosphamide/methotrexate/fluorouracil (CMF), or the same regimen in combination with trastuzumab for one year. A control cohort of 42 patients with HER2-negative tumors treated with AT-CMF was also included. The PAM50 subtypes, the PAM50 proliferation score, and the PAM50 risk of relapse score based on subtype (RORS) and subtype and proliferation (RORP) were evaluated.

RESULTS

HER2-enriched (HER2-E) tumors predominated within HER2(+) disease, although all PAM50 intrinsic subtypes were identified across the three cohorts. The OR for achieving pCR with trastuzumab-based chemotherapy for HER2(+)/HER2-E and HER2(+)/RORP-high were 5.117 (P = 0.009) and 8.469 (P = 0.025), respectively, compared with chemotherapy only. The pCR rates of HER2(+)/HER2-E and HER2(+)/RORP-high after trastuzumab-based chemotherapy were 52.9% and 75.0%, respectively. A statistically nonsignificant trend was observed for more pronounced survival benefit with trastuzumab in patients with HER2(+)/HER2-E and HER2(+)/RORP-high tumors compared with patients with HER2(+)/non-HER2-E and HER2(+)/non-RORP-high tumors, respectively.

CONCLUSIONS

As determined by EFS and pCR, patients with HER2(+)/HER2-E tumors, or HER2(+)/RORP-high tumors, benefit substantially from trastuzumab-based chemotherapy. The clinical value of this genomic test within HER2(+) disease warrants further investigation.

The prognostic value of Ki67 in systemically untreated patients with node-negative breast cancer

AIM

To evaluate the utility of Ki67 as a prognostic marker in a series of patients with node-negative breast cancer untreated with adjuvant systemic therapy.

METHODS

The cohort consisted of 203 cases treated with breast conserving surgery and radiation only; median follow-up was 183 months (range 156-277 months). An immunohistochemical panel of oestrogen receptor (ER), progesterone receptor (PR), cytokeratin (CK)5/6 and Ki67 and human epidermal growth factor 2 in situ hybridization (HER2-ISH) was performed on the tumour samples. Ki67 scores were evaluable in 193/203 patients (95.1%). The primary outcome was breast cancer specific survival (BCSS).

RESULTS

Of the cohort, 29 (14.2%) died of breast cancer. A cut off of 10% separated tumours into a 'Ki67-low' (n=70) or 'Ki67-high' group (n=123). The breast cancer specific survival was 97.1% and 77.6% for Ki67-low and Ki67-high groups, respectively. Univariate analysis showed that in this lymph node-negative cohort, the predictors for BCSS were tumour size, Ki67, LVI, age and histological grade 3. Multivariable analysis showed that Ki67 index and lymphovascular space invasion were independent predictors of breast cancer death. To examine the utility of Ki67 in assignment of immunohistochemically molecular subtypes, cases were assigned into Luminal A (ER-positive, HER2-negative, Ki67 ≤14%), Luminal B (ER-positive, HER2-negative, Ki67 >14%) and triple negative (ER/PR-negative and HER2-negative, any Ki67). The 15-year breast cancer specific survival was 91.7%, 79.4% and 75.8%, respectively.

CONCLUSIONS

A statistically significant difference in breast cancer specific survival is seen in groups defined using Ki67 and receptor status, whereas histological grading was not a significant predictor of survival. Ki67 immunostaining provides prognostic information beyond traditionally assessed clinicopathological variables.

[Breast cancer classification is evolving]

Diagnostic strategy of breast cancer has changed enormously during the last thirty years. To classical obligatory morphological data on the macroscopical and microscopical levels are now added imunocytochemistry, which is capable of detecting therapeutic targets such hormonal receptors and HER2 (Human Epidermal growth factor Receptor2), and molecular biology, which yields the molecular profile of tumors and their multigenic properties. By leaning on up-to-date classifications (TNM system and UICC grades), the pathologist is able to evaluate not only diagnostic but also pronostic criteria, leading to personalized and predictive treatments.

Cancer stem cells, a fuzzy evolving concept: a cell population or a cell property?

The cancer stem cells (CSC) hypothesis represents a pathological extrapolation of the physiological concept of embryonic and somatic stem cells. In its initial definition, it encompassed the hypothesis of a qualitatively distinct population of immortal cancer cells originating from somatic stem cells, which generate in xenotransplants by a deterministic irreversible process, the hierarchy of more differentiated finite lifespan derived cells, which constitute, themselves, the bulk of the cancer. These CSC would express specific biomarkers and gene expressions related to chemo- and radioresistance, stemness, epithelial–mesenchymal transition, etc.

No convincing congruence of several of these properties in one cell population has been demonstrated. The concept has greatly evolved with time and with different authors (“the plasticity of cancer stem cells”), leading to a minimal definition of cells generating a hierarchy of derived cells. In this article these concepts are analyzed. It is proposed that stemness is a property, more or less reversible, a hallmark of some cells at some time in a cancer cell population, as immortality, dormancy, chemo- or radioresistance, epithelial–mesenchymal transition etc. These phenotypic properties represent the result of independent, linked, or more or less congruent, genetic, epigenetic, or signaling programs.

Estrogen receptor-positive breast cancer molecular signatures and therapeutic potentials (Review)

In this review, the advances in the study of breast cancer molecular classifications and the molecular signatures of the luminal subtypes A and B of breast cancer were summarized. Effective clinical outcomes depend mainly on successful preclinical diagnosis and therapeutic decisions. Over the last few years, the ever-expanding investigations focusing on breast cancer diagnosis and the clinical trials have provided accumulating information on the molecular characteristics of breast cancer. Specifically, among the estrogen receptor (ER)-positive types of breast cancer, the luminal subtype A breast cancer has been shown to exhibit good clinical outcomes with endocrine therapy, whereas the luminal subtype B breast cancer represents the more complicated type, diagnostically as well as therapeutically. Furthermore, even in luminal subtype A breast cancer, the resistance to treatment has become the major limitation for endocrine-based therapy. Accumulating molecular data and further clinical trials may enable more accurate diagnostic and therapeutic decisions. The molecular signatures have emerged as a powerful tool for future diagnosis and therapeutic decisions, although currently available data are limited.

Molecular differences between chronic and aggressive periodontitis

The 2 major forms of periodontitis, chronic (CP) and aggressive (AgP), do not display sufficiently distinct histopathological characteristics or microbiological/immunological features. We used molecular profiling to explore biological differences between CP and AgP and subsequently carried out supervised classification using machine-learning algorithms including an internal validation. We used whole-genome gene expression profiles from 310 'healthy' or 'diseased' gingival tissue biopsies from 120 systemically healthy non-smokers, 65 with CP and 55 with AgP, each contributing with ≥ 2 'diseased' gingival papillae (n = 241; with bleeding-on-probing, probing depth ≥ 4 mm, and clinical attachment loss ≥ 3 mm), and, when available, a 'healthy' papilla (n = 69; no bleeding-on-probing, probing depth ≤ 4 mm, and clinical attachment loss ≤ 4 mm). Our analyses revealed limited differences between the gingival tissue transcriptional profiles of AgP and CP, with genes related to immune responses, apoptosis, and signal transduction overexpressed in AgP, and genes related to epithelial integrity and metabolism overexpressed in CP. Different classifying algorithms discriminated CP from AgP with an area under the curve ranging from 0.63 to 0.99. The small differences in gene expression and the highly variable classifier performance suggest limited dissimilarities between established AgP and CP lesions. Future analyses may facilitate the development of a novel, 'intrinsic' classification of periodontitis based on molecular profiling.

Relationship between PTEN, DNA mismatch repair, and tumor histotype in endometrial carcinoma: retained positive expression of PTEN preferentially identifies sporadic non-endometrioid carcinomas

Loss of PTEN (phosphatase and tensin homolog) expression and microsatellite instability are two of the more common molecular alterations in endometrial carcinoma. From the published literature, it is controversial as to whether there is a relationship between these different molecular mechanisms. Therefore, a cohort of 187 pure endometrioid and non-endometrioid endometrial carcinomas, carefully characterized as to clinical and pathological features, was examined for PTEN sequence abnormalities and the immunohistochemical expression of PTEN and the DNA mismatch repair proteins MLH1, MSH2, MSH6, and PMS2. MLH1 methylation analysis was performed when tumors had loss of MLH1 protein. Mismatch repair protein loss was more frequent in endometrioid carcinomas compared with non-endometrioid carcinomas, a difference primarily attributable to the presence of MLH1 methylation in a greater proportion of endometrioid tumors. Among the non-endometrioid group, mixed endometrioid/non-endometrioid carcinomas were the histotype that most commonly had loss of a mismatch repair protein. In endometrioid tumors, the frequency of PTEN loss measured by immunohistochemistry and mutation did not differ significantly between the mismatch repair protein intact or mismatch repair protein loss groups, suggesting that PTEN loss is independent of mismatch protein repair status in this group. However, in non-endometrioid carcinomas, both intact positive PTEN immunohistochemical expression and PTEN wild type were highly associated with retained positive expression of mismatch repair proteins in the tumor. Relevant to screening endometrial cancers for Lynch Syndrome, an initial PTEN immunohistochemistry determination may be able to replace the use of four mismatch repair immunohistochemical markers in 63% of patients with non-endometrioid endometrial carcinoma. Therefore, PTEN immunohistochemistry, in combination with tumor histotype, is a useful adjunct in the clinical evaluation of endometrial carcinomas for Lynch Syndrome.

Signaling events mediated by α3β1 integrin are essential for mammary tumorigenesis

The constitutive activation of β-catenin signaling in the mammary basal epithelial cell layer in transgenic K5ΔNβcat mice leads to basal-type tumor development. Integrins of the β1 family and integrin-mediated signaling events have an important role in breast tumor growth and progression. We show here that the deletion of α3β1 integrin, a major laminin receptor, from the basal layer of the mammary epithelium of K5ΔNβcat mice completely prevented the tumorigenesis induced by β-catenin signaling. Moreover, the depletion of α3β1 integrin from a spontaneously transformed mouse mammary basal epithelial cell line (MEC) prevented the cells from forming colonies in soft agar and greatly reduced tumor development in orthotopic grafts. Inhibition of the integrin signaling intermediates Rac1 or PAK1 (P21-activated Kinase 1) in MEC affected tumor cell growth in soft agar, whereas the expression of activated forms of these effectors in α3-depleted cells rescued the capacity of these cells to grow in non-adherent conditions. Similarly, the tumorigenic potential of α3-depleted cells was restored by the expression of activated PAK1, as assessed by orthotopic transplantation assay. In three-dimensional Matrigel culture, MEC survival and proliferation were affected by the depletion of α3β1 integrin, which also significantly decreased the activation of focal adhesion kinase (FAK), mitogen-activated protein kinase (MAPK) and c-Jun NH2-terminal kinase (JNK). Our data suggest that the activation of signaling cascades downstream from α3β1 and involving the Rac1/PAK1 pathway, MAPK and JNK, promotes prosurvival and proproliferative signals required for the malignant growth of basal mammary epithelial cells, providing further insight into the molecular mechanisms underlying breast cancer initiation and progression.

Characterization of synergistic anti-cancer effects of docosahexaenoic acid and curcumin on DMBA-induced mammary tumorigenesis in mice

BACKGROUND

The major obstacles to the successful use of individual nutritional compounds as preventive or therapeutic agents are their efficacy and bioavailability. One approach to overcoming this problem is to use combinations of nutrients to induce synergistic effects. The objective of this research was to investigate the synergistic effects of two dietary components: docosahexaenoic acid (DHA), an omega-3 fatty acid present in cold-water fish, and curcumin (CCM), an herbal nutrient present in turmeric, in an in vivo model of DMBA-induced mammary tumorigenesis in mice.

METHODS

We used the carcinogen DMBA to induce breast tumors in SENCAR mice on control, CCM, DHA, or DHA + CCM diets. Appearance and tumor progression were monitored daily. The tumors were harvested 15 days following their first appearance for morphological and immunohistological analysis. Western analysis was performed to determine expression of maspin and survivin in the tumor tissues. Characterization of tumor growth was analyzed using appropriate statistical methods. Otherwise all other results are reported as mean ± SD and analyzed with one-way ANOVA and Tukey's post hoc procedure.

RESULTS

Analysis of gene microarray data indicates that combined treatment with DHA + CCM altered the profile of "PAM50" genes in the SK-BR-3 cell line from an ER⁻/Her-2⁺ to that resembling a "normal-like" phenotype. The in vivo studies demonstrated that DHA + CCM treatment reduced the incidence of breast tumors, delayed tumor initiation, and reduced progression of tumor growth. Dietary treatment had no effect on breast size development, but tumors from mice on a control diet (untreated) were less differentiated than tumors from mice fed CCM or DHA + CCM diets. The synergistic effects also led to increased expression of the pro-apoptotic protein, maspin, but reduced expression of the anti-apoptotic protein, survivin.

CONCLUSIONS

The SK-BR-3 cells and DMBA-induced tumors, both with an ER⁻ and Her-2⁺ phenotype, were affected by the synergistic interaction of DHA and CCM. This suggests that the specific breast cancer phenotype is an important factor for predicting efficacy of these nutraceuticals. The combination of DHA and CCM is potentially a dietary supplemental treatment for some breast cancers, likely dependent upon the molecular phenotype of the cancer.

Molecular and cellular heterogeneity in breast cancer: challenges for personalized medicine

Breast cancer is noted for disparate clinical behaviors and patient outcomes, despite common histopathological features at diagnosis. Molecular pathogenesis studies suggest that breast cancer is a collection of diseases with variable molecular underpinnings that modulate therapeutic responses, disease-free intervals, and long-term survival. Traditional therapeutic strategies for individual patients are guided by the expression status of the estrogen and progesterone receptors (ER and PR) and human epidermal growth factor receptor 2 (HER2). Although such methods for clinical classification have utility in selection of targeted therapies, short-term patient responses and long-term survival remain difficult to predict. Molecular signatures of breast cancer based on complex gene expression patterns have utility in prediction of long-term patient outcomes, but are not yet used for guiding therapy. Examination of the correspondence between these methods for breast cancer classification reveals a lack of agreement affecting a significant percentage of cases. To realize true personalized breast cancer therapy, a more complete analysis and evaluation of the molecular characteristics of the disease in the individual patient is required, together with an understanding of the contributions of specific genetic and epigenetic alterations (and their combinations) to management of the patient. Here, we discuss the molecular and cellular heterogeneity of breast cancer, the impact of this heterogeneity on practical breast cancer classification, and the challenges for personalized breast cancer treatment.

Correlation between imaging and molecular classification of breast cancers

The histological type of tumour according to the WHO: ductal, lobular, rare forms, is correlated with specific aspects of the imaging based on each type. This morphological classification was improved by knowledge of the molecular anomalies of breast cancers, resulting in the definition of cancer sub-groups with distinct prognoses and different responses to treatment: luminal A, luminal B, HER2 positive, basal-like, triple-negative. Studies are beginning to deal with the appearance of each sub-type in the imaging. It is now important for the radiologist to be familiar with them.

Metalloproteinase-disintegrin ADAM12 is associated with a breast tumor-initiating cell phenotype

Members of the ADAM family of proteases have been associated with mammary tumorigenesis. Gene profiling of human breast tumors identified several intrinsic subtypes of breast cancer, which differ in terms of their basic biology, response to chemotherapy/radiation, preferential sites of metastasis, and overall patient survival. Whether or not the expression of individual ADAM proteases is linked to a particular subtype of breast cancer and whether the functions of these ADAMs are relevant to the cancer subtype have not been investigated. We analyzed several transcriptomic datasets and found that ADAM12L is specifically up-regulated in claudin-low tumors. These tumors are poorly differentiated, exhibit aggressive characteristics, have molecular signatures of epithelial-to-mesenchymal transition (EMT), and are rich in markers of breast tumor-initiating cells (BTICs). Consistently, we find that ADAM12L, but not the alternative splice variant ADAM12S, is a part of stromal, mammosphere, and EMT gene signatures, which are all associated with BTICs. In patients with estrogen receptor-negative tumors, high expression of ADAM12L, but not ADAM12S, is predictive of resistance to neoadjuvant chemotherapy. Using MCF10DCIS.com breast cancer cells, which express the endogenous ADAM12L and efficiently form mammospheres when plated at the density of single cell per well, we show that ADAM12L plays an important role in supporting mammosphere growth. We postulate that ADAM12L may serve as a novel marker and/or a novel therapeutic target in BTICs.

Collagen triple helix repeat containing-1 (CTHRC1) expression in invasive ductal carcinoma of the breast: the impact on prognosis and correlation to clinicopathologic features

CTHRC1 has been known as a regulator of collagen expression and cell migration. The aim of this research was to clarify the clinicopathologic significance of CTHRC1 expression in human breast cancer. 22 cases of breast cancer tissues, randomly selected from clinically diagnosed patients, showed a significant increase of CTHRC1 mRNA expression compared to the normal tissue from the same patients using RT-PCR and real-time PCR. Additionally we investigated breast cancers from 189 patients by immunohistochemistry (IHC). A high level of CTHRC1 expression was observed in 111 (58.7 %) out of 189 breast cancer patients and the expression was significantly correlated with histologic grade (P = 0.026), nodal status (P < 0.001), and TNM pathologic stage (P = 0.002). High CTHRC1 expression was associated with a shorter recurrence free survival (P = 0.008). Taken together, the results showed that CTHRC1 over-expression was significantly associated with clinicopathological factors of poor prognosis in invasive ductal carcinoma. CTHRC1 could be used as a supplementary prognostic biomarker and a potential therapeutic target in breast cancer.

PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer

To identify a group of patients who might benefit from the addition of weekly paclitaxel to conventional anthracycline-containing chemotherapy as adjuvant therapy of node-positive operable breast cancer. The predictive value of PAM50 subtypes and the 11-gene proliferation score contained within the PAM50 assay were evaluated in 820 patients from the GEICAM/9906 randomized phase III trial comparing adjuvant FEC to FEC followed by weekly paclitaxel (FEC-P). Multivariable Cox regression analyses of the secondary endpoint of overall survival (OS) were performed to determine the significance of the interaction between treatment and the (1) PAM50 subtypes, (2) PAM50 proliferation score, and (3) clinical and pathological variables. Similar OS analyses were performed in 222 patients treated with weekly paclitaxel versus paclitaxel every 3 weeks in the CALGB/9342 and 9840 metastatic clinical trials. In GEICAM/9906, with a median follow up of 8.7 years, OS of the FEC-P arm was significantly superior compared to the FEC arm (unadjusted HR = 0.693, p = 0.013). A benefit from paclitaxel was only observed in the group of patients with a low PAM50 proliferation score (unadjusted HR = 0.23, p < 0.001; and interaction test, p = 0.006). No significant interactions between treatment and the PAM50 subtypes or the various clinical–pathological variables, including Ki-67 and histologic grade, were identified. Finally, similar OS results were obtained in the CALGB data set, although the interaction test did not reach statistical significance (p = 0.109). The PAM50 proliferation score identifies a subset of patients with a low proliferation status that may derive a larger benefit from weekly paclitaxel.

Molecular characterization of basal-like and non-basal-like triple-negative breast cancer

Triple-negative (TN) and basal-like (BL) breast cancer definitions have been used interchangeably to identify breast cancers that lack expression of the hormone receptors and overexpression and/or amplification of HER2. However, both classifications show substantial discordance rates when compared to each other. Here, we molecularly characterize TN tumors and BL tumors, comparing and contrasting the results in terms of common patterns and distinct patterns for each. In total, when testing 412 TN and 473 BL tumors, 21.4% and 31.5% were identified as non-BL and non-TN, respectively. TN tumors identified as luminal or HER2-enriched (HER2E) showed undistinguishable overall gene expression profiles when compared versus luminal or HER2E tumors that were not TN. Similar findings were observed within BL tumors regardless of their TN status, which suggests that molecular subtype is preserved regardless of individual marker results. Interestingly, most TN tumors identified as HER2E showed low HER2 expression and lacked HER2 amplification, despite the similar overall gene expression profiles to HER2E tumors that were clinically HER2-positive. Lastly, additional genomic classifications were examined within TN and BL cancers, most of which were highly concordant with tumor intrinsic subtype. These results suggest that future clinical trials focused on TN disease should consider stratifying patients based upon BL versus non-BL gene expression profiles, which appears to be the main biological difference seen in patients with TN breast cancer.

A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer

Background

Robust transcriptional signatures in cancer can be identified by data similarity-driven meta-analysis of gene expression profiles. An unbiased data integration and interrogation strategy has not previously been available.

Methods and Findings

We implemented and performed a large meta-analysis of breast cancer gene expression profiles from 223 datasets containing 10,581 human breast cancer samples using a novel data similarity-based approach (iterative EXALT). Cancer gene expression signatures extracted from individual datasets were clustered by data similarity and consolidated into a meta-signature with a recurrent and concordant gene expression pattern. A retrospective survival analysis was performed to evaluate the predictive power of a novel meta-signature deduced from transcriptional profiling studies of human breast cancer. Validation cohorts consisting of 6,011 breast cancer patients from 21 different breast cancer datasets and 1,110 patients with other malignancies (lung and prostate cancer) were used to test the robustness of our findings. During the iterative EXALT analysis, 633 signatures were grouped by their data similarity and formed 121 signature clusters. From the 121 signature clusters, we identified a unique meta-signature (BRmet50) based on a cluster of 11 signatures sharing a phenotype related to highly aggressive breast cancer. In patients with breast cancer, there was a significant association between BRmet50 and disease outcome, and the prognostic power of BRmet50 was independent of common clinical and pathologic covariates. Furthermore, the prognostic value of BRmet50 was not specific to breast cancer, as it also predicted survival in prostate and lung cancers.

Conclusions

We have established and implemented a novel data similarity-driven meta-analysis strategy. Using this approach, we identified a transcriptional meta-signature (BRmet50) in breast cancer, and the prognostic performance of BRmet50 was robust and applicable across a wide range of cancer-patient populations.

Competing risks in low-risk breast cancer

In recent years a growing amount of data on prognostic features of breast cancer has allowed for identification of tumors with a very low risk of recurrence. Markers used to predict the risk of distant spread include classic clinicopathologic features as well as newer tumor gene signatures, which have been validated and are being used in cohorts of patients with breast cancer patients who have low-risk disease. However, the definition of "low-risk" breast cancer requires consideration of patient-related factors such as comorbidities and age in addition to tumor characteristics, as high competing risks for mortality might be more important than cancer recurrence from a patient's point of view. In addition, identification of low-risk breast cancer cohorts is only valuable if treatment decisions are based on this information. Therefore, the magnitude of any treatment benefit in low-risk disease needs to be quantified in a comprehensible way. However, treatment benefit in low-risk situations is hard to quantify, may vary over time, and needs to be compared to individual risks for side effects. Decision models considering tumor and patient characteristics as well as predictive markers for treatment efficacy and toxicity will be needed. Tools such as Adjuvant! Online ultimately need to include information from gene signatures in order to reliably recommend specific treatment options for patients with breast cancer patients who have low-risk disease.

Estrogen switches pure mucinous breast cancer to invasive lobular carcinoma with mucinous features

Mucinous breast cancer (MBC) is mainly a disease of postmenopausal women. Pure MBC is rare and augurs a good prognosis. In contrast, MBC mixed with other histological subtypes of invasive disease loses the more favorable prognosis. Because of the relative rarity of pure MBC, little is known about its cell and tumor biology and relationship to invasive disease of other subtypes. We have now developed a human breast cancer cell line called BCK4, in which we can control the behavior of MBC. BCK4 cells were derived from a patient whose poorly differentiated primary tumor was treated with chemotherapy, radiation and tamoxifen. Malignant cells from a recurrent pleural effusion were xenografted in mammary glands of a nude mouse. Cells from the solid tumor xenograft were propagated in culture to generate the BCK4 cell line. Multiple marker and chromosome analyses demonstrate that BCK4 cells are human, near diploid and luminal, expressing functional estrogen, androgen, and progesterone receptors. When xenografted back into immunocompromised cycling mice, BCK4 cells grow into small pure MBC. However, if mice are supplemented with continuous estradiol, tumors switch to invasive lobular carcinoma (ILC) with mucinous features (mixed MBC), and growth is markedly accelerated. Tamoxifen prevents the expansion of this more invasive component. The unexpected ability of estrogens to convert pure MBC into mixed MBC with ILC may explain the rarity of the pure disease in premenopausal women. These studies show that MBC can be derived from lobular precursors and that BCK4 cells are new, unique models to study the phenotypic plasticity, hormonal regulation, optimal therapeutic interventions, and metastatic patterns of MBC.

Mutation scanning using MUT-MAP, a high-throughput, microfluidic chip-based, multi-analyte panel

Targeted anticancer therapies rely on the identification of patient subgroups most likely to respond to treatment. Predictive biomarkers play a key role in patient selection, while diagnostic and prognostic biomarkers expand our understanding of tumor biology, suggest treatment combinations, and facilitate discovery of novel drug targets. We have developed a high-throughput microfluidics method for mutation detection (MUT-MAP, mutation multi-analyte panel) based on TaqMan or allele-specific PCR (AS-PCR) assays. We analyzed a set of 71 mutations across six genes of therapeutic interest. The six-gene mutation panel was designed to detect the most common mutations in the EGFR, KRAS, PIK3CA, NRAS, BRAF, and AKT1 oncogenes. The DNA was preamplified using custom-designed primer sets before the TaqMan/AS-PCR assays were carried out using the Biomark microfluidics system (Fluidigm; South San Francisco, CA). A cross-reactivity analysis enabled the generation of a robust automated mutation-calling algorithm which was then validated in a series of 51 cell lines and 33 FFPE clinical samples. All detected mutations were confirmed by other means. Sample input titrations confirmed the assay sensitivity with as little as 2 ng gDNA, and demonstrated excellent inter- and intra-chip reproducibility. Parallel analysis of 92 clinical trial samples was carried out using 2-100 ng genomic DNA (gDNA), allowing the simultaneous detection of multiple mutations. DNA prepared from both fresh frozen and formalin-fixed, paraffin-embedded (FFPE) samples were used, and the analysis was routinely completed in 2-3 days: traditional assays require 0.5-1 µg high-quality DNA, and take significantly longer to analyze. This assay can detect a wide range of mutations in therapeutically relevant genes from very small amounts of sample DNA. As such, the mutation assay developed is a valuable tool for high-throughput biomarker discovery and validation in personalized medicine and cancer drug development.