Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours

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.

Joint analysis of expression profiles from multiple cancers improves the identification of microRNA-gene interactions

MOTIVATION

MicroRNAs (miRNAs) play a crucial role in tumorigenesis and development through their effects on target genes. The characterization of miRNA-gene interactions will lead to a better understanding of cancer mechanisms. Many computational methods have been developed to infer miRNA targets with/without expression data. Because expression datasets are in general limited in size, most existing methods concatenate datasets from multiple studies to form one aggregated dataset to increase sample size and power. However, such simple aggregation analysis results in identifying miRNA-gene interactions that are mostly common across datasets, whereas specific interactions may be missed by these methods. Recent releases of The Cancer Genome Atlas data provide paired expression profiling of miRNAs and genes in multiple tumors with sufficiently large sample size. To study both common and cancer-specific interactions, it is desirable to develop a method that can jointly analyze multiple cancers to study miRNA-gene interactions without combining all the data into one single dataset.

RESULTS

We developed a novel statistical method to jointly analyze expression profiles from multiple cancers to identify miRNA-gene interactions that are both common across cancers and specific to certain cancers. The benefit of this joint analysis approach is demonstrated by both simulation studies and real data analysis of The Cancer Genome Atlas datasets. Compared with simple aggregate analysis or single sample analysis, our method can effectively use the shared information among different but related cancers to improve the identification of miRNA-gene interactions. Another useful property of our method is that it can estimate similarity among cancers through their shared miRNA-gene interactions.

AVAILABILITY AND IMPLEMENTATION

The program, MCMG, implemented in R is available at http://bioinformatics.med.yale.edu/group/.

The gene desert mammary carcinoma susceptibility locus Mcs1a regulates Nr2f1 modifying mammary epithelial cell differentiation and proliferation

Genome-wide association studies have revealed that many low-penetrance breast cancer susceptibility loci are located in non-protein coding genomic regions; however, few have been characterized. In a comparative genetics approach to model such loci in a rat breast cancer model, we previously identified the mammary carcinoma susceptibility locus Mcs1a. We now localize Mcs1a to a critical interval (277 Kb) within a gene desert. Mcs1a reduces mammary carcinoma multiplicity by 50% and acts in a mammary cell-autonomous manner. We developed a megadeletion mouse model, which lacks 535 Kb of sequence containing the Mcs1a ortholog. Global gene expression analysis by RNA-seq revealed that in the mouse mammary gland, the orphan nuclear receptor gene Nr2f1/Coup-tf1 is regulated by Mcs1a. In resistant Mcs1a congenic rats, as compared with susceptible congenic control rats, we found Nr2f1 transcript levels to be elevated in mammary gland, epithelial cells, and carcinoma samples. Chromatin looping over ∼820 Kb of sequence from the Nr2f1 promoter to a strongly conserved element within the Mcs1a critical interval was identified. This element contains a 14 bp indel polymorphism that affects a human-rat-mouse conserved COUP-TF binding motif and is a functional Mcs1a candidate. In both the rat and mouse models, higher Nr2f1 transcript levels are associated with higher abundance of luminal mammary epithelial cells. In both the mouse mammary gland and a human breast cancer global gene expression data set, we found Nr2f1 transcript levels to be strongly anti-correlated to a gene cluster enriched in cell cycle-related genes. We queried 12 large publicly available human breast cancer gene expression studies and found that the median NR2F1 transcript level is consistently lower in 'triple-negative' (ER-PR-HER2-) breast cancers as compared with 'receptor-positive' breast cancers. Our data suggest that the non-protein coding locus Mcs1a regulates Nr2f1, which is a candidate modifier of differentiation, proliferation, and mammary cancer risk.

ROCK: a resource for integrative breast cancer data analysis

Given the steady increase in breast cancer rates in both the developed and developing world, there has been a concerted research effort undertaken worldwide to understand the molecular mechanisms underpinning the disease. The data generated from numerous clinical trials and experimental studies shed light on different aspects of the disease. We present a new version of the ROCK database (rock.icr.ac.uk), which integrates such diverse data types allowing unique analyses of published breast cancer experimental data. We have added several new data types and analysis modules to ROCK, which allow the user to interactively query and research the huge amounts of available experimental data and perform complex correlations across studies and data types such as gene expression, genomic copy number aberrations, micro RNA expression, RNA interference, survival analysis, clinical annotation and signalling protein networks. We present the recent and major functional updates and enhancements to the ROCK resource, including new analysis modules and microRNA and NGS data integration, and illustrate how ROCK can be used to confirm known experimental results as well as generate novel leads and new experimental hypotheses using the Wnt signalling cell surface receptor FZD7 and the Myc oncogene. ROCK provides a unique breast cancer analysis platform of integrated experimental datasets at the genomic, transcriptomic and proteomic level. This paper presents how ROCK has transitioned from being simply a database to an interactive resource useful to the broader breast cancer research community in our effort to facilitate research into the underlying molecular mechanisms of breast cancer.

Interplay between estrogen receptor and AKT in estradiol-induced alternative splicing

Background

Alternative splicing is critical for generating complex proteomes in response to extracellular signals. Nuclear receptors including estrogen receptor alpha (ERα) and their ligands promote alternative splicing. The endogenous targets of ERα:estradiol (E2)-mediated alternative splicing and the influence of extracellular kinases that phosphorylate ERα on E2-induced splicing are unknown.

Methods

MCF-7 and its anti-estrogen derivatives were used for the majority of the assays. CD44 mini gene was used to measure the effect of E2 and AKT on alternative splicing. ExonHit array analysis was performed to identify E2 and AKT-regulated endogenous alternatively spliced apoptosis-related genes. Quantitative reverse transcription polymerase chain reaction was performed to verify alternative splicing. ERα binding to alternatively spliced genes was verified by chromatin immunoprecipitation assay. Bromodeoxyuridine incorporation-ELISA and Annexin V labeling assays were done to measure cell proliferation and apoptosis, respectively.

Results

We identified the targets of E2-induced alternative splicing and deconstructed some of the mechanisms surrounding E2-induced splicing by combining splice array with ERα cistrome and gene expression array. E2-induced alternatively spliced genes fall into at least two subgroups: coupled to E2-regulated transcription and ERα binding to the gene without an effect on rate of transcription. Further, AKT, which phosphorylates both ERα and splicing factors, influenced ERα:E2 dependent splicing in a gene-specific manner. Genes that are alternatively spliced include FAS/CD95, FGFR2, and AXIN-1. E2 increased the expression of FGFR2 C1 isoform but reduced C3 isoform at mRNA level. E2-induced alternative splicing of FAS and FGFR2 in MCF-7 cells correlated with resistance to FAS activation-induced apoptosis and response to keratinocyte growth factor (KGF), respectively. Resistance of MCF-7 breast cancer cells to the anti-estrogen tamoxifen was associated with ERα-dependent overexpression of FGFR2, whereas resistance to fulvestrant was associated with ERα-dependent isoform switching, which correlated with altered response to KGF.

Conclusion

E2 may partly alter cellular proteome through alternative splicing uncoupled to its effects on transcription initiation and aberration in E2-induced alternative splicing events may influence response to anti-estrogens.

Molecular pathways: PI3K pathway targets in triple-negative breast cancers

The triple-negative breast cancer (TNBC) subtype, defined clinically by the lack of estrogen, progesterone, and Her2 receptor expression, accounts for 10% to 15% of annual breast cancer diagnoses. Currently, limited therapeutic options have shown clinical benefit beyond cytotoxic chemotherapy. Defining this clinical cohort and identifying subtype-specific molecular targets remain critical for new therapeutic development. The current era of high-throughput molecular analysis has revealed new insights into these targets and confirmed the phosphoinositide 3-kinase (PI3K) as a key player in pathogenesis. The improved knowledge of the molecular basis of TNBC in parallel with efforts to develop new PI3K pathway-specific inhibitors may finally produce the therapeutic breakthrough that is desperately needed.

Identification of thresholds for dichotomizing DNA methylation data

: DNA methylation plays an important role in many biological processes by regulating gene expression. It is commonly accepted that turning on the DNA methylation leads to silencing of the expression of the corresponding genes. While methylation is often described as a binary on-off signal, it is typically measured using beta values derived from either microarray or sequencing technologies, which takes continuous values between 0 and 1. If we would like to interpret methylation in a binary fashion, appropriate thresholds are needed to dichotomize the continuous measurements. In this paper, we use data from The Cancer Genome Atlas project. For a total of 992 samples across five cancer types, both methylation and gene expression data are available. A bivariate extension of the StepMiner algorithm is used to identify thresholds for dichotomizing both methylation and expression data. Hypergeometric test is applied to identify CpG sites whose methylation status is significantly associated to silencing of the expression of their corresponding genes. The test is performed on either all five cancer types together or individual cancer types separately. We notice that the appropriate thresholds vary across different CpG sites. In addition, the negative association between methylation and expression is highly tissue specific.

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.

SF3B1 mutations in chronic lymphocytic leukemia

SF3B1 is a critical component of the splicing machinery, which catalyzes the removal of introns from precursor messenger RNA (mRNA). Next-generation sequencing studies have identified mutations in SF3B1 in chronic lymphocytic leukemia (CLL) at high frequency. In CLL, SF3B1 mutation is associated with more aggressive disease and shorter survival, and recent studies suggest that it can be incorporated into prognostic schema to improve the prediction of disease progression. Mutations in SF3B1 are predominantly subclonal genetic events in CLL, and hence are likely later events in the progression of CLL. Evidence of altered pre-mRNA splicing has been detected in CLL cases with SF3B1 mutations. Although the causative link between SF3B1 mutation and CLL pathogenesis remains unclear, several lines of evidence suggest SF3B1 mutation might be linked to genomic stability and epigenetic modification.

Targeted therapies of solid cancers: new options, new challenges

PURPOSE OF REVIEW

The landscape of medical oncology is filled with approvals of new anticancer agents, the majority of which are targeted agents. This shift in therapies raises multiple challenges including the appearance of new toxicities, the need for biomarkers, the emergence of genomics and the evolution of cancer molecular imaging.

RECENT FINDINGS

Biopsy of metastatic lesions is slowly becoming a standard of care before the initiation of any therapy. These invasive procedures have been found to be generally well tolerated and are being put to use with the emergence of genomics. Gene sequencing and new imaging techniques are serving the understanding of tumor biology and the search for 'biomarkers' predicting response and resistance to treatment. New clinical trial designs incorporating the 'presumed' biomarkers are guiding patients to specific treatments and have shown outcome improvements.

SUMMARY

Many questions remain however unanswered and new challenges appear. Intratumor heterogeneity emerges as a brake to personalized cancer care. Relevant targets remain undruggable and costs may hinder progress. Furthermore, technical issues continue to arise. The ultimate goal remains to achieve cure by blocking the multiple pathways of cancer development and proliferation, while sparing the patients the burden of therapy.

Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis

Weighted gene coexpression network analysis (WGCNA) is a powerful 'guilt-by-association'-based method to extract coexpressed groups of genes from large heterogeneous messenger RNA expression data sets. We have utilized WGCNA to identify 11 coregulated gene clusters across 2342 breast cancer samples from 13 microarray-based gene expression studies. A number of these transcriptional modules were found to be correlated to clinicopathological variables (e.g. tumor grade), survival endpoints for breast cancer as a whole (disease-free survival, distant disease-free survival and overall survival) and also its molecular subtypes (luminal A, luminal B, HER2+ and basal-like). Examples of findings arising from this work include the identification of a cluster of proliferation-related genes that when upregulated correlated to increased tumor grade and were associated with poor survival in general. The prognostic potential of novel genes, for example, ubiquitin-conjugating enzyme E2S (UBE2S) within this group was confirmed in an independent data set. In addition, gene clusters were also associated with survival for breast cancer molecular subtypes including a cluster of genes that was found to correlate with prognosis exclusively for basal-like breast cancer. The upregulation of several single genes within this coexpression cluster, for example, the potassium channel, subfamily K, member 5 (KCNK5) was associated with poor outcome for the basal-like molecular subtype. We have developed an online database to allow user-friendly access to the coexpression patterns and the survival analysis outputs uncovered in this study (available at http://glados.ucd.ie/Coexpression/).

Somatic mutation profiling and associations with prognosis and trastuzumab benefit in early breast cancer

Background

Certain somatic alterations in breast cancer can define prognosis and response to therapy. This study investigated the frequencies, prognostic effects, and predictive effects of known cancer somatic mutations using a randomized, adjuvant, phase III clinical trial dataset.

Methods

The FinHER trial was a phase III, randomized adjuvant breast cancer trial involving 1010 women. Patients with human epidermal growth factor receptor 2 (HER2)–positive breast cancer were further randomized to 9 weeks of trastuzumab or no trastuzumab. Seven hundred five of 1010 tumors had sufficient DNA for genotyping of 70 somatic hotspot mutations in 20 genes using mass spectrometry. Distant disease-free survival (DDFS), overall survival (OS), and interactions with trastuzumab were explored with Kaplan-Meier and Cox regression analyses. All statistical tests were two-sided.

Results

Median follow-up was 62 months. Of 705 tumors, 687 were successfully genotyped. PIK3CA mutations (exons 1, 2, 4, 9, 13, 18, and 20) were present in 25.3% (174 of 687) and TP53 mutations in 10.2% (70 of 687). Few other mutations were found: three ERBB2 and single cases of KRAS, ALK, STK11/LKB1, and AKT2. PIK3CA mutations were associated with estrogen receptor positivity (P < .001) and the luminal-A phenotype (P = .04) but were not statistically significantly associated with prognosis (DDFS: hazard ratio [HR] = 0.88, 95% confidence [CI] = 0.58 to 1.34, P = .56; OS: HR = 0.603, 95% CI = .32 to 1.13, P = .11), although a statistically significant nonproportional prognostic effect was observed for DDFS (P = .002). PIK3CA mutations were not statistically significantly associated with trastuzumab benefit (P_interaction: DDFS P = .14; OS P = .24).

Conclusions

In this dataset, targeted genotyping revealed only two alterations at a frequency greater than 10%, with other mutations observed infrequently. PIK3CA mutations were associated with a better outcome, however this effect disappeared after 3 years. There were no statistically significant associations with trastuzumab benefit.

Prolactin-induced protein (PIP) regulates proliferation of luminal A type breast cancer cells in an estrogen-independent manner

Prolactin-induced Protein (PIP), an aspartyl protease unessential for normal mammalian cell function, is required for the proliferation and invasion of some breast cancer (BCa) cell types. Because PIP expression is particularly high in the Luminal A BCa subtype, we investigated the roles of PIP in the related T47D BCa cell line. Nucleic acid and antibody arrays were employed to screen effects of PIP silencing on global gene expression and activation of receptor tyrosine kinases (RTKs), respectively. Expression of PIP-stimulated genes, as defined in the T47D cell culture model, was well correlated with the expression of PIP itself across a cohort of 557 mRNA profiles of diverse BCa tumors, and bioinformatics analysis revealed cJUN and cMYC as major nodes in the PIP-dependent gene network. Among 71 RTKs tested, PIP silencing resulted in decreased phosphorylation of focal adhesion kinase (FAK), ephrin B3 (EphB3), FYN, and hemopoietic cell kinase (HCK). Ablation of PIP also abrogated serum-induced activation of the downstream serine/threonine kinases AKT, ERK1/2, and JNK1. Consistent with these results, PIP-depleted cells exhibited defects in adhesion to fibronectin, cytoskeletal stress fiber assembly and protein secretion. In addition, PIP silencing abrogated the mitogenic response of T47D BCa cells to estradiol (E2). The dependence of BCa cell proliferation was unrelated, however, to estrogen signaling because: 1) PIP silencing did not affect the transcriptional response of estrogen target genes to hormone treatment, and 2) PIP was required for the proliferation of tamoxifen-resistant BCa cells. Pharmacological inhibition of PIP may therefore serve the bases for both augmentation of existing therapies for hormone-dependent tumors and the development of novel therapeutic approaches for hormone-resistant BCa.

Tight junction proteins: from barrier to tumorigenesis

The tight junction is a multi-protein complex and is the apical most junctional complex in certain epithelial and endothelial cells. A great deal of attention has been devoted to the understanding of these proteins in contributing to the barrier function - that is, regulating the paracellular flux or permeability between adjacent cells. However, tight junction proteins are now recognized as having functions beyond the barrier. The focus of this review is to discuss the barrier function of the tight junction and to summarize the literature with a focus on the role of tight junction proteins in proliferation, transformation, and metastasis.

Progesterone signalling in breast cancer: a neglected hormone coming into the limelight

Understanding the biology of the breast and how ovarian hormones impinge on it is key to rational new approaches in breast cancer prevention and therapy. Because of the success of selective oestrogen receptor modulators (SERMs), such as tamoxifen, and aromatase inhibitors in breast cancer treatment, oestrogens have long received the most attention. Early progesterone receptor (PR) antagonists, however, were dismissed because of severe side effects, but awareness is now increasing that progesterone is an important hormone in breast cancer. Oestrogen receptor-α (ERα) signalling and PR signalling have distinct roles in normal mammary gland biology in mice; both ERα and PR delegate many of their biological functions to distinct paracrine mediators. If the findings in the mouse model translate to humans, new preventive and therapeutic perspectives might open up.

Evaluating the repair of DNA derived from formalin-fixed paraffin-embedded tissues prior to genomic profiling by SNP-CGH analysis

Pathology archives contain vast resources of clinical material in the form of formalin-fixed paraffin-embedded (FFPE) tissue samples. Owing to the methods of tissue fixation and storage, the integrity of DNA and RNA available from FFPE tissue is compromized, which means obtaining informative data regarding epigenetic, genomic, and expression alterations can be challenging. Here, we have investigated the utility of repairing damaged DNA derived from FFPE tumors prior to single-nucleotide polymorphism (SNP) arrays for whole-genome DNA copy number analysis. DNA was extracted from FFPE samples spanning five decades, involving tumor material obtained from surgical specimens and postmortems. Various aspects of the protocol were assessed, including the method of DNA extraction, the role of Quality Control quantitative PCR (qPCR) in predicting sample success, and the effect of DNA restoration on assay performance, data quality, and the prediction of copy number aberrations (CNAs). DNA that had undergone the repair process yielded higher SNP call rates, reduced log R ratio variance, and improved calling of CNAs compared with matched FFPE DNA not subjected to repair. Reproducible mapping of genomic break points and detection of focal CNAs representing high-level gains and homozygous deletions (HD) were possible, even on autopsy material obtained in 1974. For example, DNA amplifications at the ERBB2 and EGFR gene loci and a HD mapping to 13q14.2 were validated using immunohistochemistry, in situ hybridization, and qPCR. The power of SNP arrays lies in the detection of allele-specific aberrations; however, this aspect of the analysis remains challenging, particularly in the distinction between loss of heterozygosity (LOH) and copy neutral LOH. In summary, attempting to repair DNA that is damaged during fixation and storage may be a useful pretreatment step for genomic studies of large archival FFPE cohorts with long-term follow-up or for understanding rare cancer types, where fresh frozen material is scarce.

Growth of triple-negative breast cancer cells relies upon coordinate autocrine expression of the proinflammatory cytokines IL-6 and IL-8

Triple-negative breast cancers (TNBC) are aggressive with no effective targeted therapies. A combined database analysis identified 32 inflammation-related genes differentially expressed in TNBCs and 10 proved critical for anchorage-independent growth. In TNBC cells, an LPA-LPAR2-EZH2 NF-κB signaling cascade was essential for expression of interleukin (IL)-6, IL-8, and CXCL1. Concurrent inhibition of IL-6 and IL-8 expression dramatically inhibited colony formation and cell survival in vitro and stanched tumor engraftment and growth in vivo. A Cox multivariable analysis of patient specimens revealed that IL-6 and IL-8 expression predicted patient survival times. Together these findings offer a rationale for dual inhibition of IL-6/IL-8 signaling as a therapeutic strategy to improve outcomes for patients with TNBCs.

The T-box transcription factors TBX2 and TBX3 in mammary gland development and breast cancer

TBX2 and TBX3, closely related members of the T-box family of transcription factor genes, are expressed in mammary tissue in both humans and mice. Ulnar mammary syndrome (UMS), an autosomal dominant disorder caused by mutations in TBX3, underscores the importance of TBX3 in human breast development, while abnormal mammary gland development in Tbx2 or Tbx3 mutant mice provides models for experimental investigation. In addition to their roles in mammary development, aberrant expression of TBX2 and TBX3 is associated with breast cancer. TBX2 is preferentially amplified in BRCA1/2-associated breast cancers and TBX3 overexpression has been associated with advanced stage disease and estrogen-receptor-positive breast tumors. The regulation of Tbx2 and Tbx3 and the downstream targets of these genes in development and disease are not as yet fully elucidated. However, it is clear that the two genes play unique, context-dependent roles both in mammary gland development and in mammary tumorigenesis.

Photoacoustic and photothermal detection of circulating tumor cells, bacteria and nanoparticles in cerebrospinal fluid in vivo and ex vivo

Circulating cells, bacteria, proteins, microparticles, and DNA in cerebrospinal fluid (CSF) are excellent biomarkers of many diseases, including cancer and infections. However, the sensitivity of existing methods is limited in their ability to detect rare CSF biomarkers at the treatable, early-stage of diseases. Here, we introduce novel CSF tests based on in vivo photoacoustic flow cytometry (PAFC) and ex vivo photothermal scanning cytometry. In the CSF of tumor-bearing mice, we molecularly detected in vivo circulating tumor cells (CTCs) before the development of breast cancer brain metastasis with 20-times higher sensitivity than with current assays. For the first time, we demonstrated assessing three pathways (i.e., blood, lymphatic, and CSF) of CTC dissemination, tracking nanoparticles in CSF in vivo and their imaging ex vivo. In label-free CSF samples, we counted leukocytes, erythrocytes, melanoma cells, and bacteria and imaged intracellular cytochromes, hemoglobin, melanin, and carotenoids, respectively. Taking into account the safety of PAFC, its translation for use in humans is expected to improve disease diagnosis beyond conventional detection limits.

RETRACTED: Collagen prolyl hydroxylases are essential for breast cancer metastasis

The presence of hypoxia and fibrosis within the primary tumor are two major risk factors for metastasis of human breast cancer. In this study, we demonstrate that hypoxia-inducible factor 1 activates the transcription of genes encoding collagen prolyl hydroxylases that are critical for collagen deposition by breast cancer cells. We show that expression of collagen prolyl hydroxylases promotes cancer cell alignment along collagen fibers, resulting in enhanced invasion and metastasis to lymph nodes and lungs. Finally, we establish the prognostic significance of collagen prolyl hydroxylase mRNA expression in human breast cancer biopsies and show that ethyl 3,4-dihydroxybenzoate, a prolyl hydroxylase inhibitor, decreases tumor fibrosis and metastasis in a mouse model of breast cancer.

Optimizing clinical management of surgical margins in breast-conserving therapy for breast cancer

There has been, and continues to be, significant controversy over the definition of an "optimal" surgical margin in breast-conserving therapy (BCT). The historic basis of this controversy stems from the original trials documenting the safety of BCT and many conflicting retrospective studies that have sought to define the association between surgical margin width and outcomes over the last 20 years. It is important to understand that margin assessment is an inexact science, and current laboratory approaches to surgical-margin assessment represent only a sampling of the surgical margin. Currently available evidence suggests that decisions regarding surgical margins in BCT should be made in the context of what is known about the biology of breast cancer, as well the interactions of tumor biology, adjuvant treatment for breast cancer, and outcomes. Achieving consensus on management of surgical margins in BCT should be a clinical priority as it offers the opportunity to reduce the burden of breast cancer treatment on patients without compromising cancer-related outcomes.

Circulating tumour cells and cell-free DNA as tools for managing breast cancer

Circulating blood biomarkers promise to become non-invasive real-time surrogates for tumour tissue-based biomarkers. Circulating biomarkers have been investigated as tools for breast cancer diagnosis, the dissection of breast cancer biology and its genetic and clinical heterogeneity, prognostication, prediction and monitoring of therapeutic response and resistance. Circulating tumour cells and cell-free plasma DNA have been analysed in retrospective studies, and the assessment of these biomarkers is being incorporated into clinical trials. As the scope of breast cancer intratumour genetic heterogeneity unravels, the development of robust and standardized methods for the assessment of circulating biomarkers will be essential for the realization of the potentials of personalized medicine. In this Review, we discuss the current status of blood-born biomarkers as surrogates for tissue-based biomarkers, and their burgeoning impact on the management of patients with breast cancer.

Lessons from the cancer genome

Systematic studies of the cancer genome have exploded in recent years. These studies have revealed scores of new cancer genes, including many in processes not previously known to be causal targets in cancer. The genes affect cell signaling, chromatin, and epigenomic regulation; RNA splicing; protein homeostasis; metabolism; and lineage maturation. Still, cancer genomics is in its infancy. Much work remains to complete the mutational catalog in primary tumors and across the natural history of cancer, to connect recurrent genomic alterations to altered pathways and acquired cellular vulnerabilities, and to use this information to guide the development and application of therapies.

Interplay between the cancer genome and epigenome

Cancer arises as a consequence of cumulative disruptions to cellular growth control with Darwinian selection for those heritable changes that provide the greatest clonal advantage. These traits can be acquired and stably maintained by either genetic or epigenetic means. Here, we explore the ways in which alterations in the genome and epigenome influence each other and cooperate to promote oncogenic transformation. Disruption of epigenomic control is pervasive in malignancy and can be classified as an enabling characteristic of cancer cells, akin to genome instability and mutation.

Revealing selection in cancer using the predicted functional impact of cancer mutations. Application to nomination of cancer drivers

Every malignant tumor has a unique spectrum of genomic alterations including numerous protein mutations. There are also hundreds of personal germline variants to be taken into account. The combinatorial diversity of potential cancer-driving events limits the applicability of statistical methods to determine tumor-specific "driver" alterations among an overwhelming majority of "passengers". An alternative approach to determining driver mutations is to assess the functional impact of mutations in a given tumor and predict drivers based on a numerical value of the mutation impact in a particular context of genomic alterations.Recently, we introduced a functional impact score, which assesses the mutation impact by the value of entropic disordering of the evolutionary conservation patterns in proteins. The functional impact score separates disease-associated variants from benign polymorphisms with an accuracy of ~80%. Can the score be used to identify functionally important non-recurrent cancer-driver mutations? Assuming that cancer-drivers are positively selected in tumor evolution, we investigated how the functional impact score correlates with key features of natural selection in cancer, such as the non-uniformity of distribution of mutations, the frequency of affected tumor suppressors and oncogenes, the frequency of concurrent alterations in regions of heterozygous deletions and copy gain; as a control, we used presumably non-selected silent mutations. Using mutations of six cancers studied in TCGA projects, we found that predicted high-scoring functional mutations as well as truncating mutations tend to be evolutionarily selected as compared to low-scoring and silent mutations. This result justifies prediction of mutations-drivers using a shorter list of predicted high-scoring functional mutations, rather than the "long tail" of all mutations.

A neu view of invasive lobular breast cancer

Genome sequencing of relapsed, invasive lobular breast cancer identified actionable mutations in 86% of the cases. HER2 alterations occur in 27% of the cases, including 4 cases with activating HER2 mutations and 1 with a novel HER2-GRB7 gene fusion. This fusion links the HER2 tyrosine kinase domain to the GRB7 src homology 2 (SH2) domain.

Simultaneous identification of multiple driver pathways in cancer

Distinguishing the somatic mutations responsible for cancer (driver mutations) from random, passenger mutations is a key challenge in cancer genomics. Driver mutations generally target cellular signaling and regulatory pathways consisting of multiple genes. This heterogeneity complicates the identification of driver mutations by their recurrence across samples, as different combinations of mutations in driver pathways are observed in different samples. We introduce the Multi-Dendrix algorithm for the simultaneous identification of multiple driver pathways de novo in somatic mutation data from a cohort of cancer samples. The algorithm relies on two combinatorial properties of mutations in a driver pathway: high coverage and mutual exclusivity. We derive an integer linear program that finds set of mutations exhibiting these properties. We apply Multi-Dendrix to somatic mutations from glioblastoma, breast cancer, and lung cancer samples. Multi-Dendrix identifies sets of mutations in genes that overlap with known pathways – including Rb, p53, PI(3)K, and cell cycle pathways – and also novel sets of mutually exclusive mutations, including mutations in several transcription factors or other genes involved in transcriptional regulation. These sets are discovered directly from mutation data with no prior knowledge of pathways or gene interactions. We show that Multi-Dendrix outperforms other algorithms for identifying combinations of mutations and is also orders of magnitude faster on genome-scale data. Software available at: http://compbio.cs.brown.edu/software.

Cancer is a disease driven largely by the accumulation of somatic mutations during the lifetime of an individual. The declining costs of genome sequencing now permit the measurement of somatic mutations in hundreds of cancer genomes. A key challenge is to distinguish driver mutations responsible for cancer from random passenger mutations. This challenge is compounded by the observation that different combinations of driver mutations are observed in different patients with the same cancer type. One reason for this heterogeneity is that driver mutations target signaling and regulatory pathways which have multiple points of failure. We introduce an algorithm, Multi-Dendrix, to find these pathways solely from patterns of mutual exclusivity between mutations across a cohort of patients. Unlike earlier approaches, we simultaneously find multiple pathways, an essential feature for analyzing cancer genomes where multiple pathways are typically perturbed. We apply our algorithm to mutation data from hundreds of glioblastoma, breast cancer, and lung adenocarcinoma patients. We identify sets of interacting genes that overlap known pathways, and gene sets containing subtype-specific mutations. These results show that multiple cancer pathways can be identified directly from patterns in mutation data, and provide an approach to analyze the ever-growing cancer mutation datasets.

Comprehensive functional annotation of seventy-one breast cancer risk Loci

Breast Cancer (BCa) genome-wide association studies revealed allelic frequency differences between cases and controls at index single nucleotide polymorphisms (SNPs). To date, 71 loci have thus been identified and replicated. More than 320,000 SNPs at these loci define BCa risk due to linkage disequilibrium (LD). We propose that BCa risk resides in a subgroup of SNPs that functionally affects breast biology. Such a shortlist will aid in framing hypotheses to prioritize a manageable number of likely disease-causing SNPs. We extracted all the SNPs, residing in 1 Mb windows around breast cancer risk index SNP from the 1000 genomes project to find correlated SNPs. We used FunciSNP, an R/Bioconductor package developed in-house, to identify potentially functional SNPs at 71 risk loci by coinciding them with chromatin biofeatures. We identified 1,005 SNPs in LD with the index SNPs (r(2)≥0.5) in three categories; 21 in exons of 18 genes, 76 in transcription start site (TSS) regions of 25 genes, and 921 in enhancers. Thirteen SNPs were found in more than one category. We found two correlated and predicted non-benign coding variants (rs8100241 in exon 2 and rs8108174 in exon 3) of the gene, ANKLE1. Most putative functional LD SNPs, however, were found in either epigenetically defined enhancers or in gene TSS regions. Fifty-five percent of these non-coding SNPs are likely functional, since they affect response element (RE) sequences of transcription factors. Functionality of these SNPs was assessed by expression quantitative trait loci (eQTL) analysis and allele-specific enhancer assays. Unbiased analyses of SNPs at BCa risk loci revealed new and overlooked mechanisms that may affect risk of the disease, thereby providing a valuable resource for follow-up studies.

Age-specific gene expression signatures for breast tumors and cross-species conserved potential cancer progression markers in young women

Breast cancer in young women is more aggressive with a poorer prognosis and overall survival compared to older women diagnosed with the disease. Despite recent research, the underlying biology and molecular alterations that drive the aggressive nature of breast tumors associated with breast cancer in young women have yet to be elucidated. In this study, we performed transcriptomic profile and network analyses of breast tumors arising in Middle Eastern women to identify age-specific gene signatures. Moreover, we studied molecular alterations associated with cancer progression in young women using cross-species comparative genomics approach coupled with copy number alterations (CNA) associated with breast cancers from independent studies. We identified 63 genes specific to tumors in young women that showed alterations distinct from two age cohorts of older women. The network analyses revealed potential critical regulatory roles for Myc, PI3K/Akt, NF-κB, and IL-1 in disease characteristics of breast tumors arising in young women. Cross-species comparative genomics analysis of progression from pre-invasive ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) revealed 16 genes with concomitant genomic alterations, CCNB2, UBE2C, TOP2A, CEP55, TPX2, BIRC5, KIAA0101, SHCBP1, UBE2T, PTTG1, NUSAP1, DEPDC1, HELLS, CCNB1, KIF4A, and RRM2, that may be involved in tumorigenesis and in the processes of invasion and progression of disease. Array findings were validated using qRT-PCR, immunohistochemistry, and extensive in silico analyses of independently performed microarray datasets. To our knowledge, this study provides the first comprehensive genomic analysis of breast cancer in Middle Eastern women in age-specific cohorts and potential markers for cancer progression in young women. Our data demonstrate that cancer appearing in young women contain distinct biological characteristics and deregulated signaling pathways. Moreover, our integrative genomic and cross-species analysis may provide robust biomarkers for the detection of disease progression in young women, and lead to more effective treatment strategies.

C-Terminal Binding Protein: A Molecular Link between Metabolic Imbalance and Epigenetic Regulation in Breast Cancer

The prevalence of obesity has given rise to significant global concerns as numerous population-based studies demonstrate an incontrovertible association between obesity and breast cancer. Mechanisms proposed to account for this linkage include exaggerated levels of carbohydrate substrates, elevated levels of circulating mitogenic hormones, and inflammatory cytokines that impinge on epithelial programming in many tissues. Moreover, recently many scientists have rediscovered the observation, first described by Otto Warburg nearly a century ago, that most cancer cells undergo a dramatic metabolic shift in energy utilization and expenditure that fuels and supports the cellular expansion associated with malignant proliferation. This shift in substrate oxidation comes at the cost of sharp changes in the levels of the high energy intermediate, nicotinamide adenine dinucleotide (NADH). In this review, we discuss a novel example of how shifts in the concentration and flux of substrates metabolized and generated during carbohydrate metabolism represent components of a signaling network that can influence epigenetic regulatory events in the nucleus. We refer to this regulatory process as "metabolic transduction" and describe how the C-terminal binding protein (CtBP) family of NADH-dependent nuclear regulators represents a primary example of how cellular metabolic status can influence epigenetic control of cellular function and fate.

Combined targeting of mTOR and AKT is an effective strategy for basal-like breast cancer in patient-derived xenograft models

Basal-like breast cancer is an aggressive disease for which targeted therapies are lacking. Recent studies showed that basal-like breast cancer is frequently associated with an increased activity of the phosphatidylinositol 3-kinase (PI3K) pathway, which is critical for cell growth, survival, and angiogenesis. To investigate the therapeutic potential of PI3K pathway inhibition in the treatment of basal-like breast cancer, we evaluated the antitumor effect of the mTOR inhibitor MK-8669 and AKT inhibitor MK-2206 in WU-BC4 and WU-BC5, two patient-derived xenograft models of basal-like breast cancer. Both models showed high levels of AKT phosphorylation and loss of PTEN expression. We observed a synergistic effect of MK-8669 and MK-2206 on tumor growth and cell proliferation in vivo. In addition, MK-8669 and MK-2206 inhibited angiogenesis as determined by CD31 immunohistochemistry. Biomarker studies indicated that treatment with MK-2206 inhibited AKT activation induced by MK-8669. To evaluate the effect of loss of PTEN on tumor cell sensitivity to PI3K pathway inhibition, we knocked down PTEN in WU-BC3, a basal-like breast cancer cell line with intact PTEN. Compared with control (GFP) knockdown, PTEN knockdown led to a more dramatic reduction in cell proliferation and tumor growth inhibition in response to MK-8669 and MK-2206 both in vitro and in vivo. Furthermore, a synergistic effect of these two agents on tumor volume was observed in WU-BC3 with PTEN knockdown. Our results provide a preclinical rationale for future clinical investigation of this combination in basal-like breast cancer with loss of PTEN.

Targeted inhibition of Hsp90 by ganetespib is effective across a broad spectrum of breast cancer subtypes

Heat shock protein 90 (Hsp90) is a molecular chaperone essential for the stability and function of multiple cellular client proteins, a number of which have been implicated in the pathogenesis of breast cancer. Here we undertook a comprehensive evaluation of the activity of ganetespib, a selective Hsp90 inhibitor, in this malignancy. With low nanomolar potency, ganetespib reduced cell viability in a panel of hormone receptor-positive, HER2-overexpressing, triple-negative and inflammatory breast cancer cell lines in vitro. Ganetespib treatment induced a rapid and sustained destabilization of multiple client proteins and oncogenic signaling pathways and even brief exposure was sufficient to induce and maintain suppression of HER2 levels in cells driven by this receptor. Indeed, HER2-overexpressing BT-474 cells were comparatively more sensitive to ganetespib than the dual HER2/EGFR tyrosine kinase inhibitor lapatinib in three-dimensional culture. Ganetespib exposure caused pleiotropic effects in the inflammatory breast cancer line SUM149, including receptor tyrosine kinases, MAPK, AKT and mTOR signaling, transcription factors and proteins involved in cell cycle, stress and apoptotic regulation, as well as providing combinatorial benefit with lapatinib in these cells. This multimodal activity translated to potent antitumor efficacy in vivo, suppressing tumor growth in MCF-7 and MDA-MB-231 xenografts and inducing tumor regression in the BT-474 model. Thus, ganetespib potently inhibits Hsp90 leading to the degradation of multiple clinically-validated oncogenic client proteins in breast cancer cells, encompassing the broad spectrum of molecularly-defined subtypes. This preclinical activity profile suggests that ganetespib may offer considerable promise as a new therapeutic candidate for patients with advanced breast cancers.

Use of pharmacogenetics for predicting cancer prognosis and treatment exposure, response and toxicity

Cancer treatment is complicated because of a multitude of treatment options and little patient-specific information to help clinicians choose appropriate therapy. There are two genomes relevant in cancer treatment: the tumor (somatic) and the patient (germline). Together, these two genomes dictate treatment outcome through four processes: the somatic genome primarily determines tumor prognosis and response while the germline genome modulates treatment exposure and toxicity. In this review, we describe the influence of these genomes on treatment outcomes by highlighting examples of genetic variation that are predictors of each of these four factors, prognosis, response, toxicity and exposure, and discuss the translation and clinical implementation of each. Use of pre-treatment pharmacogenetic testing will someday enable clinicians to make individualized therapy decisions about aggressiveness, drug selection and dose, improving treatment outcomes for cancer patients.

The shaping and functional consequences of the microRNA landscape in breast cancer

MicroRNAs (miRNAs) show differential expression across breast cancer subtypes, and have both oncogenic and tumour-suppressive roles. Here we report the miRNA expression profiles of 1,302 breast tumours with matching detailed clinical annotation, long-term follow-up and genomic and messenger RNA expression data. This provides a comprehensive overview of the quantity, distribution and variation of the miRNA population and provides information on the extent to which genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture, suggesting an important role for post-transcriptional regulation. The key clinical parameters and cellular pathways related to the miRNA landscape are characterized, revealing context-dependent interactions, for example with regards to cell adhesion and Wnt signalling. Notably, only prognostic miRNA signatures derived from breast tumours devoid of somatic copy-number aberrations (CNA-devoid) are consistently prognostic across several other subtypes and can be validated in external cohorts. We then use a data-driven approach to seek the effects of miRNAs associated with differential co-expression of mRNAs, and find that miRNAs act as modulators of mRNA-mRNA interactions rather than as on-off molecular switches. We demonstrate such an important modulatory role for miRNAs in the biology of CNA-devoid breast cancers, a common subtype in which the immune response is prominent. These findings represent a new framework for studying the biology of miRNAs in human breast cancer.

The genomic landscape of small intestine neuroendocrine tumors

Small intestine neuroendocrine tumors (SI-NETs) are the most common malignancy of the small bowel. Several clinical trials target PI3K/Akt/mTOR signaling; however, it is unknown whether these or other genes are genetically altered in these tumors. To address the underlying genetics, we analyzed 48 SI-NETs by massively parallel exome sequencing. We detected an average of 0.1 somatic single nucleotide variants (SNVs) per 106 nucleotides (range, 0-0.59), mostly transitions (C>T and A>G), which suggests that SI-NETs are stable cancers. 197 protein-altering somatic SNVs affected a preponderance of cancer genes, including FGFR2, MEN1, HOOK3, EZH2, MLF1, CARD11, VHL, NONO, and SMAD1. Integrative analysis of SNVs and somatic copy number variations identified recurrently altered mechanisms of carcinogenesis: chromatin remodeling, DNA damage, apoptosis, RAS signaling, and axon guidance. Candidate therapeutically relevant alterations were found in 35 patients, including SRC, SMAD family genes, AURKA, EGFR, HSP90, and PDGFR. Mutually exclusive amplification of AKT1 or AKT2 was the most common event in the 16 patients with alterations of PI3K/Akt/mTOR signaling. We conclude that sequencing-based analysis may provide provisional grouping of SI-NETs by therapeutic targets or deregulated pathways.

Downregulation of BMP6 enhances cell proliferation and chemoresistance via activation of the ERK signaling pathway in breast cancer

Previous studies indicate that bone morphogenetic protein (BMP) 6 is involved in breast cancer development and progression. However, the mechanism underlying the role of BMP6 in breast cancer cell proliferation, differentiation and chemoresistance remains unknown. In this study, we confirmed that BMP6 expression was downregulated in breast cancer tissues compared with the adjacent normal breast tissues. We further demonstrated that the downregulation of BMP6 was correlated with the estrogen receptor (ER) and progesterone receptor (PR) status, tumor grade and enhanced proliferation (Ki67 proliferation index). In vitro functional experiments showed that the suppression of BMP6 expression by a specific small hairpin (sh)RNA vector led to increased proliferation in the MCF7 breast cancer cell line. Furthermore, knockdown of BMP6 in MCF7 cells enhanced the chemoresistance to doxorubicin by upregulation of mdr-1/P-gp expression and activation of the ERK signaling pathway. Taken together, our data suggest that BMP6 plays a critical role in breast cancer cell aberrant proliferation and chemoresistance and may serve as a novel diagnostic biomarker or therapeutic target for breast cancer.

Oncogenic ERBB3 mutations in human cancers

The human epidermal growth factor receptor (HER) family of tyrosine kinases is deregulated in multiple cancers either through amplification, overexpression, or mutation. ERBB3/HER3, the only member with an impaired kinase domain, although amplified or overexpressed in some cancers, has not been reported to carry oncogenic mutations. Here, we report the identification of ERBB3 somatic mutations in ~11% of colon and gastric cancers. We found that the ERBB3 mutants transformed colonic and breast epithelial cells in a ligand-independent manner. However, the mutant ERBB3 oncogenic activity was dependent on kinase-active ERBB2. Furthermore, we found that anti-ERBB antibodies and small molecule inhibitors effectively blocked mutant ERBB3-mediated oncogenic signaling and disease progression in vivo.

TPD52 represents a survival factor in ERBB2-amplified breast cancer cells

TPD52 and ERBB2 co-expression has been persistently reported in human breast cancer and animal models of this disease, but the significance of this is unknown. We identified significant positive associations between relative TPD52 and ERBB2 transcript levels in human diagnostic breast cancer samples, and maximal TPD52 expression in the hormone receptor (HR)- and ERBB2-positive sub-group. High-level TPD52 expression was associated with significantly reduced metastasis-free survival, within the overall cohort (log rank test, P = 8.6 × 10(-4), n = 375) where this was an independent predictor of metastasis-free survival (hazard ratio, 2.69, 95% confidence interval 1.59-4.54, P = 2.2 × 10(-4), n = 359), and the HR- and ERBB2-positive sub-group (log rank test, P = 0.035, n = 47). Transient TPD52 knock-down in the ERBB2-amplified breast cancer cell lines SK-BR-3 and BT-474 produced significant apoptosis, both singly and in combination with transient ERBB2 knock-down. Unlike ERBB2 knock-down, transient TPD52 knock-down produced no reduction in pAKT levels in SK-BR-3 or BT-474 cells. We then derived multiple SK-BR-3 cell lines in which TPD52 levels were stably reduced, and measured significant inverse correlations between pERBB2 and TPD52 levels in viable TPD52-depleted and control cell lines, all of which showed similar proliferative capacities. Our results therefore identify TPD52 as a survival factor in ERBB2-amplified breast cancer cells, and suggest complementary cellular functions for TPD52 and ERBB2.

Signaling through cyclin D-dependent kinases

Research over the past quarter century has identified cyclin D-dependent kinases, CDK4 and CDK6, as the major oncogenic drivers among members of the CDK superfamily. CDK4/6 are rendered hyperactive in the majority of human cancers through a multitude of genomic alterations. Sustained activation of these protein kinases provides cancer cells with the power to enter the cell cycle continuously by triggering G1-S-phase transitions and dramatically shortening the duration of the G1 phase. It has also become clear, however, that CDK4/6 effectively counter cancer cell-intrinsic tumor suppression mechanisms, senescence and apoptosis, which must be overcome during cell transformation and kept at bay throughout all stages of tumorigenesis. As a central 'node' in cellular signaling networks, cyclin D-dependent kinases sense a plethora of mitogenic signals to orchestrate specific transcriptional programs. As the complexity of the cellular signaling network regulated by these oncogenic kinases unfolds, much remains to be learned about its architecture, its dynamics and the consequences of its perturbation.

Proteomic and bioinformatic analysis of mammalian SWI/SNF complexes identifies extensive roles in human malignancy

Subunits of mammalian SWI/SNF (mSWI/SNF or BAF) complexes have recently been implicated as tumor suppressors in human malignancies. To understand the full extent of their involvement, we conducted a proteomic analysis of endogenous mSWI/SNF complexes, which identified several new dedicated, stable subunits not found in yeast SWI/SNF complexes, including BCL7A, BCL7B and BCL7C, BCL11A and BCL11B, BRD9 and SS18. Incorporating these new members, we determined mSWI/SNF subunit mutation frequency in exome and whole-genome sequencing studies of primary human tumors. Notably, mSWI/SNF subunits are mutated in 19.6% of all human tumors reported in 44 studies. Our analysis suggests that specific subunits protect against cancer in specific tissues. In addition, mutations affecting more than one subunit, defined here as compound heterozygosity, are prevalent in certain cancers. Our studies demonstrate that mSWI/SNF is the most frequently mutated chromatin-regulatory complex (CRC) in human cancer, exhibiting a broad mutation pattern, similar to that of TP53. Thus, proper functioning of polymorphic BAF complexes may constitute a major mechanism of tumor suppression.

Targeting the PI3K/AKT/mTOR and Raf/MEK/ERK pathways in the treatment of breast cancer

Alterations of signal transduction pathways leading to uncontrolled cellular proliferation, survival, invasion, and metastases are hallmarks of the carcinogenic process. The phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) and the Raf/mitogen-activated and extracellular signal-regulated kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) signaling pathways are critical for normal human physiology, and also commonly dysregulated in several human cancers, including breast cancer (BC). In vitro and in vivo data suggest that the PI3K/AKT/mTOR and Raf/MEK/ERK cascades are interconnected with multiple points of convergence, cross-talk, and feedback loops. Raf/MEK/ERK and PI3K/AKT/mTOR pathway mutations may co-exist. Inhibition of one pathway can still result in the maintenance of signaling via the other (reciprocal) pathway. The existence of such "escape" mechanisms implies that dual targeting of these pathways may lead to superior efficacy and better clinical outcome in selected patients. Several clinical trials targeting one or both pathways are already underway in BC patients. The toxicity profile of this novel approach of dual pathway inhibition needs to be closely monitored, given the important physiological role of PI3K/AKT/mTOR and Raf/MEK/ERK signaling. In this article, we present a review of the current relevant pre-clinical and clinical data and discuss the rationale for dual inhibition of these pathways in the treatment of BC patients.

Controversies in the management of brain metastases

The multidisciplinary management of brain metastases has generated substantial controversy as treatment has diversified in recent years. Debate about the type, role, and timing of different diagnostic and therapeutic strategies has promoted rigorous scientific research into efficacy. However, much still remains unanswered in the treatment of this difficult disease process. This manuscript seeks to highlight some of the controversies identified in previous sections of this supplement, including prognosis, pathology, radiation and surgical treatment, neuroimaging, and the biochemical underpinnings of brain metastases. By recognizing what is yet unanswered, we hope to identify areas in which further research may yield promising results.

Noninvasive detection of HER2 amplification with plasma DNA digital PCR

PURPOSE

Digital PCR is a highly accurate method of determining DNA concentration. We adapted digital PCR to determine the presence of oncogenic amplification through noninvasive analysis of circulating free plasma DNA and exemplify this approach by developing a plasma DNA digital PCR assay for HER2 copy number.

EXPERIMENTAL DESIGN

The reference gene for copy number assessment was assessed experimentally and bioinformatically. Chromosome 17 pericentromeric probes were shown to be suboptimal, and EFTUD2 at chromosome position 17q21.31 was selected for analysis. Digital PCR assay parameters were determined on plasma samples from a development cohort of 65 patients and assessed in an independent validation cohort of plasma samples from 58 patients with metastatic breast cancer. The sequential probability ratio test was used to assign the plasma DNA digital PCR test as being HER2-positive or -negative in the validation cohort.

RESULTS

In the development cohort, the HER2:EFTUD2 plasma DNA copy number ratio had a receiver operator area under the curve (AUC) = 0.92 [95% confidence interval (CI), 0.86-0.99, P = 0.0003]. In the independent validation cohort, 64% (7 of 11) of patients with HER2-amplified cancers were classified as plasma digital PCR HER2-positive and 94% (44 of 47) of patients with HER2-nonamplified cancers were classified as digital PCR HER2-negative, with a positive and negative predictive value of 70% and 92%, respectively.

CONCLUSION

Analysis of plasma DNA with digital PCR has the potential to screen for the acquisition of HER2 amplification in metastatic breast cancer. This approach could potentially be adapted to the analysis of any locus amplified in cancer.

The current and future role of sequence-based analysis in prostate cancer treatment

Prostate cancer is the most commonly diagnosed, nondermatologic malignancy in US men. Localized disease can be managed through active surveillance or curative, locally directed therapies, but 30% of men treated with surgery or radiation will need additional (often systemic) treatment for relapsed disease. While spectacular advances in medical treatment of advanced prostate cancer have improved the quality and duration of patients' lives, metastatic prostate cancer remains an incurable, lethal disease that requires additional therapies and better treatment strategies. The advent of ultra-high-throughput sequencing technology provides an opportunity to comprehensively assess the constellation of genetic and molecular events underlying each patient's tumor, and promises to enhance our ability to deliver specifically tailored personalized treatment to men with prostate cancer. The known biological and clinical heterogeneity of prostate cancer presents both opportunities and challenges to the application and utilization of sequence-based analysis to guide prostate cancer treatment.