The molecular landscape of high-risk early breast cancer: comprehensive biomarker analysis of a phase III adjuvant population.

Breast cancer is a heterogeneous disease and patients are managed clinically based on ER, PR, HER2 expression, and key risk factors. We sought to characterize the molecular landscape of high-risk breast cancer patients enrolled onto an adjuvant chemotherapy study to understand how disease subsets and tumor immune status impact survival. DNA and RNA were extracted from 861 breast cancer samples from patients enrolled onto the United States Oncology trial 01062. Samples were characterized using multiplex gene expression, copy number, and qPCR mutation assays. HR+ patients with a PIK3CA mutant tumor had a favorable disease-free survival (DFS; HR 0.66, P=0.05), however, the prognostic effect was specific to luminal A patients (Luminal A: HR 0.67, P=0.1; Luminal B: HR 1.01, P=0.98). Molecular subtyping of triple-negative breast cancers (TNBCs) suggested that the mesenchymal subtype had the worst DFS, whereas the immunomodulatory subtype had the best DFS. Profiling of immunologic genes revealed that TNBC tumors (n=280) displaying an activated T-cell signature had a longer DFS following adjuvant chemotherapy (HR 0.59, P=0.04), while a distinct set of immune genes was associated with DFS in HR+ cancers. Utilizing a discovery approach, we identified genes associated with a high risk of recurrence in HR+ patients, which were validated in an independent data set. Molecular classification based on PAM50 and TNBC subtyping stratified clinical high-risk patients into distinct prognostic subsets. Patients with high expression of immune-related genes showed superior DFS in both HR+ and TNBC. These results may inform patient management and drug development in early breast cancer.

Development of a robust RNA-based classifier to accurately determine ER, PR, and HER2 status in breast cancer clinical samples.

Breast cancers are categorized into three subtypes based on protein expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2/ERBB2). Patients enroll onto experimental clinical trials based on ER, PR, and HER2 status and, as receptor status is prognostic and defines treatment regimens, central receptor confirmation is critical for interpreting results from these trials. Patients enrolling onto experimental clinical trials in the metastatic setting often have limited available archival tissue that might better be used for comprehensive molecular profiling rather than slide-intensive reconfirmation of receptor status. We developed a Random Forests-based algorithm using a training set of 158 samples with centrally confirmed IHC status, and subsequently validated this algorithm on multiple test sets with known, locally determined IHC status. We observed a strong correlation between target mRNA expression and IHC assays for HER2 and ER, achieving an overall accuracy of 97 and 96%, respectively. For determining PR status, which had the highest discordance between central and local IHC, incorporation of expression of co-regulated genes in a multivariate approach added predictive value, outperforming the single, target gene approach by a 10% margin in overall accuracy. Our results suggest that multiplexed qRT-PCR profiling of ESR1, PGR, and ERBB2 mRNA, along with several other subtype associated genes, can effectively confirm breast cancer subtype, thereby conserving tumor sections and enabling additional biomarker data to be obtained from patients enrolled onto experimental clinical trials.

Considerations for the successful co-development of targeted cancer therapies and companion diagnostics.

As diagnostic tests become increasingly important for optimizing the use of drugs to treat cancers, the co-development of a targeted therapy and its companion diagnostic test is becoming more prevalent and necessary. In July 2011, the US Food and Drug Administration released a draft guidance that gave the agency's formal definition of companion diagnostics and introduced a drug-diagnostic co-development process for gaining regulatory approval. Here, we identify areas of drug-diagnostic co-development that were either not covered by the guidance or that would benefit from increased granularity, including how to determine when clinical studies should be limited to biomarker-positive patients, defining the diagnostically selected patient population in which to use a companion diagnostic, and defining and clinically validating a biomarker signature for assays that use more than one biomarker. We propose potential approaches that sponsors could use to deal with these challenges and provide strategies to help guide the future co-development of drugs and diagnostics.

An industry statistician's perspective on PHC drug development.

In the past decade, the cost of drug development has increased significantly. The estimates vary widely but frequently quoted numbers are staggering-it takes 10-15 years and billions of dollars to bring a drug to patients. To a large extent this is due to many long, expensive and ultimately unsuccessful drug trials. While one approach to combat the low yield on investment could be to continue searching for new blockbusters, an alternative method would lead us to focus on testing new targeted treatments that have a strong underlying scientific rationale and are more likely to provide enhanced clinical benefit in population subsets defined by molecular diagnostics. Development of these new treatments, however, cannot follow the usual established path; new strategies and approaches are required for the co-development of novel therapeutics and the diagnostic. In this paper we will review, from the point of view of industry, the approaches to, and challenges of drug development strategies incorporating predictive biomarkers into clinical programs. We will outline the basic concepts behind co-development with predictive biomarkers and summarize the current regulatory paradigm. We will present guiding principles of personalized health care (PHC) development and review the statistical, strategic, regulatory and operational challenges that statisticians regularly encounter on development programs with a PHC component. Some practical recommendations for team statisticians involved in PHC drug development are included. The majority of the examples and recommendations are drawn from oncology but broader concepts apply across all therapeutic areas.

Phosphoinositide 3-kinase (PI3K) pathway alterations are associated with histologic subtypes and are predictive of sensitivity to PI3K inhibitors in lung cancer preclinical models.

PURPOSE: Class 1 phosphatidylinositol 3-kinase (PI3K) plays a major role in cell proliferation and survival in a wide variety of human cancers. Here, we investigated biomarker strategies for PI3K pathway inhibitors in non-small-cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: Molecular profiling for candidate PI3K predictive biomarkers was conducted on a collection of NSCLC tumor samples. Assays included comparative genomic hybridization, reverse-transcription polymerase chain reaction gene expression, mutation detection for PIK3CA and other oncogenes, PTEN immunohistochemistry, and FISH for PIK3CA copy number. In addition, a panel of NSCLC cell lines characterized for alterations in the PI3K pathway was screened with PI3K and dual PI3K/mTOR inhibitors to assess the preclinical predictive value of candidate biomarkers. RESULTS: PIK3CA amplification was detected in 37% of squamous tumors and 5% of adenocarcinomas, whereas PIK3CA mutations were found in 9% of squamous and 0% of adenocarcinomas. Total loss of PTEN immunostaining was found in 21% of squamous tumors and 4% of adenocarcinomas. Cell lines harboring pathway alterations (receptor tyrosine kinase activation, PI3K mutation or amplification, and PTEN loss) were exquisitely sensitive to the PI3K inhibitor GDC-0941. A dual PI3K/mTOR inhibitor had broader activity across the cell line panel and in tumor xenografts. The combination of GDC-0941 with paclitaxel, erlotinib, or a mitogen-activated protein-extracellular signal-regulated kinase inhibitor had greater effects on cell viability than PI3K inhibition alone. CONCLUSIONS: Candidate biomarkers for PI3K inhibitors have predictive value in preclinical models and show histology-specific alterations in primary tumors, suggesting that distinct biomarker strategies may be required in squamous compared with nonsquamous NSCLC patient populations.

Widespread potential for growth-factor-driven resistance to anticancer kinase inhibitors.

Mutationally activated kinases define a clinically validated class of targets for cancer drug therapy. However, the efficacy of kinase inhibitors in patients whose tumours harbour such alleles is invariably limited by innate or acquired drug resistance. The identification of resistance mechanisms has revealed a recurrent theme­the engagement of survival signals redundant to those transduced by the targeted kinase. Cancer cells typically express multiple receptor tyrosine kinases (RTKs) that mediate signals that converge on common critical downstream cell-survival effectors­most notably, phosphatidylinositol-3-OH kinase (PI(3)K) and mitogen-activated protein kinase (MAPK). Consequently, an increase in RTK-ligand levels, through autocrine tumour-cell production, paracrine contribution from tumour stroma or systemic production, could confer resistance to inhibitors of an oncogenic kinase with a similar signalling output. Here, using a panel of kinase-'addicted' human cancer cell lines, we found that most cells can be rescued from drug sensitivity by simply exposing them to one or more RTK ligands. Among the findings with clinical implications was the observation that hepatocyte growth factor (HGF) confers resistance to the BRAF inhibitor PLX4032 (vemurafenib) in BRAF-mutant melanoma cells. These observations highlight the extensive redundancy of RTK-transduced signalling in cancer cells and the potentially broad role of widely expressed RTK ligands in innate and acquired resistance to drugs targeting oncogenic kinases.

Analysis of tumor burden versus progression-free survival for Phase II decision making.

PURPOSE: There have been recent recommendations to use percentage change in tumor burden (dTB) as a primary endpoint in randomized Phase II trials. We assessed whether dTB is better for the decision to start a Phase III trial than is progression-free survival (PFS). METHODS: We repeatedly sampled patients from six large randomized trials to obtain simulated Phase II trials. We derived PFS and dTB endpoints on the trial patients and determined the fraction of simulated trials with positive results for each endpoint. We supplemented these analyses with regression analyses to assess the ability of PFS and dTB to predict overall survival (OS). RESULTS: The best PFS endpoint included tumor assessments through 6 months after the last patient enrolled. With 70 patients in each simulated Phase II trial, the estimated rate of a correct 'Phase III go' decision ranged from 0.74 to 0.91 across the six parent studies. The best dTB endpoint was the last dTB through 6 months after the last patient enrolled, with corresponding rates of 0.54 to 0.81. The PFS rate was better than the dTB rate in five studies. PFS and dTB are individually statistically significant predictors of OS (p < 0.05). In all six studies PFS added significantly to the regression models with dTB included, while in only two studies did dTB add significantly to the regression model with PFS included. CONCLUSION: Analysis of PFS in randomized Phase II trials generally leads to better 'Phase III go' decisions than does analysis of dTB. Tumor burden analyses should be used in supportive analyses to a primary PFS analysis.

Statistical techniques to construct assays for identifying likely responders to a treatment under evaluation from cell line genomic data.

BACKGROUND: Developing the right drugs for the right patients has become a mantra of drug development. In practice, it is very difficult to identify subsets of patients who will respond to a drug under evaluation. Most of the time, no single diagnostic will be available, and more complex decision rules will be required to define a sensitive population, using, for instance, mRNA expression, protein expression or DNA copy number. Moreover, diagnostic development will often begin with in-vitro cell-line data and a high-dimensional exploratory platform, only later to be transferred to a diagnostic assay for use with patient samples. In this manuscript, we present a novel approach to developing robust genomic predictors that are not only capable of generalizing from in-vitro to patient, but are also amenable to clinically validated assays such as qRT-PCR. METHODS: Using our approach, we constructed a predictor of sensitivity to dacetuzumab, an investigational drug for CD40-expressing malignancies such as lymphoma using genomic measurements of cell lines treated with dacetuzumab. Additionally, we evaluated several state-of-the-art prediction methods by independently pairing the feature selection and classification components of the predictor. In this way, we constructed several predictors that we validated on an independent DLBCL patient dataset. Similar analyses were performed on genomic measurements of breast cancer cell lines and patients to construct a predictor of estrogen receptor (ER) status. RESULTS: The best dacetuzumab sensitivity predictors involved ten or fewer genes and accurately classified lymphoma patients by their survival and known prognostic subtypes. The best ER status classifiers involved one or two genes and led to accurate ER status predictions more than 85% of the time. The novel method we proposed performed as well or better than other methods evaluated. CONCLUSIONS: We demonstrated the feasibility of combining feature selection techniques with classification methods to develop assays using cell line genomic measurements that performed well in patient data. In both case studies, we constructed parsimonious models that generalized well from cell lines to patients.

Reversing HOXA9 oncogene activation by PI3K inhibition: epigenetic mechanism and prognostic significance in human glioblastoma.

HOXA genes encode critical transcriptional regulators of embryonic development that have been implicated in cancer. In this study, we documented functional relevance and mechanism of activation of HOXA9 in glioblastoma (GBM), the most common malignant brain tumor. Expression of HOXA genes was investigated using reverse transcription-PCR in primary gliomas and glioblastoma cell lines and was validated in two sets of expression array data. In a subset of GBM, HOXA genes are aberrently activated within confined chromosomal domains. Transcriptional activation of the HOXA cluster was reversible by a phosphoinostide 3-kinase (PI3K) inhibitor through an epigenetic mechanism involving histone H3K27 trimethylation. Functional studies of HOXA9 showed its capacity to decrease apoptosis and increase cellular proliferation along with tumor necrosis factor-related apoptosis-including ligand resistance. Notably, aberrant expression of HOXA9 was independently predictive of shorter overall and progression-free survival in two GBM patient sets and improved survival prediction by MGMT promoter methylation. Thus, HOXA9 activation is a novel, independent, and negative prognostic marker in GBM that is reversible through a PI3K-associated epigenetic mechanism. Our findings suggest a transcriptional pathway through which PI3K activates oncogenic HOXA expression with implications for mTOR or PI3K targeted therapies.

Characterization of a naturally occurring breast cancer subset enriched in epithelial-to-mesenchymal transition and stem cell characteristics.

Metaplastic breast cancers (MBC) are aggressive, chemoresistant tumors characterized by lineage plasticity. To advance understanding of their pathogenesis and relatedness to other breast cancer subtypes, 28 MBCs were compared with common breast cancers using comparative genomic hybridization, transcriptional profiling, and reverse-phase protein arrays and by sequencing for common breast cancer mutations. MBCs showed unique DNA copy number aberrations compared with common breast cancers. PIK3CA mutations were detected in 9 of 19 MBCs (47.4%) versus 80 of 232 hormone receptor-positive cancers (34.5%; P = 0.32), 17 of 75 HER-2-positive samples (22.7%; P = 0.04), 20 of 240 basal-like cancers (8.3%; P < 0.0001), and 0 of 14 claudin-low tumors (P = 0.004). Of 7 phosphatidylinositol 3-kinase/AKT pathway phosphorylation sites, 6 were more highly phosphorylated in MBCs than in other breast tumor subtypes. The majority of MBCs displayed mRNA profiles different from those of the most common, including basal-like cancers. By transcriptional profiling, MBCs and the recently identified claudin-low breast cancer subset constitute related receptor-negative subgroups characterized by low expression of GATA3-regulated genes and of genes responsible for cell-cell adhesion with enrichment for markers linked to stem cell function and epithelial-to-mesenchymal transition (EMT). In contrast to other breast cancers, claudin-low tumors and most MBCs showed a significant similarity to a "tumorigenic" signature defined using CD44(+)/CD24(-) breast tumor-initiating stem cell-like cells. MBCs and claudin-low tumors are thus enriched in EMT and stem cell-like features, and may arise from an earlier, more chemoresistant breast epithelial precursor than basal-like or luminal cancers. PIK3CA mutations, EMT, and stem cell-like characteristics likely contribute to the poor outcomes of MBC and suggest novel therapeutic targets.

Improving melanoma classification by integrating genetic and morphologic features.

BACKGROUND: In melanoma, morphology-based classification systems have not been able to provide relevant information for selecting treatments for patients whose tumors have metastasized. The recent identification of causative genetic alterations has revealed mutations in signaling pathways that offer targets for therapy. Identifying morphologic surrogates that can identify patients whose tumors express such alterations (or functionally equivalent alterations) would be clinically useful for therapy stratification and for retrospective analysis of clinical trial data. METHODOLOGY/PRINCIPAL FINDINGS: We defined and assessed a panel of histomorphologic measures and correlated them with the mutation status of the oncogenes BRAF and NRAS in a cohort of 302 archival tissues of primary cutaneous melanomas from an academic comprehensive cancer center. Melanomas with BRAF mutations showed distinct morphological features such as increased upward migration and nest formation of intraepidermal melanocytes, thickening of the involved epidermis, and sharper demarcation to the surrounding skin; and they had larger, rounder, and more pigmented tumor cells (all p-values below 0.0001). By contrast, melanomas with NRAS mutations could not be distinguished based on these morphological features. Using simple combinations of features, BRAF mutation status could be predicted with up to 90.8% accuracy in the entire cohort as well as within the categories of the current World Health Organization (WHO) classification. Among the variables routinely recorded in cancer registries, we identified age < 55 y as the single most predictive factor of BRAF mutation in our cohort. Using age < 55 y as a surrogate for BRAF mutation in an independent cohort of 4,785 patients of the Southern German Tumor Registry, we found a significant survival benefit (p < 0.0001) for patients who, based on their age, were predicted to have BRAF mutant melanomas in 69% of the cases. This group also showed a different pattern of metastasis, more frequently involving regional lymph nodes, compared to the patients predicted to have no BRAF mutation and who more frequently displayed satellite, in-transit metastasis, and visceral metastasis (p < 0.0001). CONCLUSIONS: Refined morphological classification of primary melanomas can be used to improve existing melanoma classifications by forming subgroups that are genetically more homogeneous and likely to differ in important clinical variables such as outcome and pattern of metastasis. We expect this information to improve classification and facilitate stratification for therapy as well as retrospective analysis of existing trial data.

High-resolution genomic and expression analyses of copy number alterations in breast tumors.

Analysis of recurrent DNA amplification can lead to the identification of cancer driver genes, but this process is often hampered by the low resolution of existing copy number analysis platforms. Fifty-one breast tumors were profiled for copy number alterations (CNAs) with the high-resolution Affymetrix 500K SNP array. These tumors were also expression-profiled and surveyed for mutations in selected genes commonly mutated in breast cancer (TP53, CDKN2A, ERBB2, KRAS, PIK3CA, PTEN). Combined analysis of common CNAs and mutations revealed putative associations between features. Analysis of both the prevalence and amplitude of CNAs defined regions of recurrent alteration. Compared with previous array comparative genomic hybridization studies, our analysis provided boundaries for frequently altered regions that were approximately one-fourth the size, greatly reducing the number of potential alteration-driving genes. Expression data from matched tumor samples were used to further interrogate the functional relevance of genes located in recurrent amplicons. Although our data support the importance of some known driver genes such as ERBB2, refined amplicon boundaries at other locations, such as 8p11-12 and 11q13.5-q14.2, greatly reduce the number of potential driver genes and indicate alternatives to commonly suggested driver genes in some cases. For example, the previously reported recurrent amplification at 17q23.2 is reduced to a 249 kb minimal region containing the putative driver RPS6KB1 as well as the putative oncogenic microRNA mir-21. High-resolution copy number analysis provides refined insight into many breast cancer amplicons and their relationships to gene expression, point mutations and breast cancer subtype classifications. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Integration of genomic analysis and in vivo transfection to identify sprouty 2 as a candidate tumor suppressor in liver cancer.

UNLABELLED: Hepatocellular carcinoma (HCC) is 1 of the leading causes of cancer-related deaths worldwide, yet the molecular genetics underlying this malignancy are still poorly understood. In our study, we applied statistical methods to correlate human HCC gene expression data obtained from complementary DNA (cDNA) microarrays and corresponding DNA copy number variation data obtained from array-based comparative genomic hybridization. We have thus identified 76 genes that are up-regulated and show frequent DNA copy number gain, and 37 genes that are down-regulated and show frequent DNA copy loss in human HCC samples. Among these down-regulated genes is Sprouty2 (Spry2), a known inhibitor of receptor tyrosine kinases. We investigated the potential role of Spry2 in HCC by expressing dominant negative Spry2 (Spry2Y55F) and activated beta-catenin (DeltaN90-beta-catenin) in the mouse liver through hydrodynamic injection and sleeping beauty-mediated somatic integration. When stably expressed in mouse hepatocytes, Spry2Y55F cooperates with DeltaN90-beta-catenin to confer a neoplastic phenotype in mice. Tumor cells show high levels of expression of phospho-extracellular signal-regulated kinase (ERK), as well as deregulation of genes involved in cell proliferation, apoptosis, and angiogenesis. CONCLUSION: We identified a set of candidate oncogenes and tumor suppressor genes for human HCC. Our study provides evidence that inhibition of Spry activity cooperates with other oncogenes to promote liver cancer in mouse models, and Spry2 may function as a candidate tumor suppressor for HCC development in vivo. In addition, we demonstrate that the integration of genomic analysis and in vivo transfection is a powerful tool to identify genes that are important during hepatic carcinogenesis.

Acquired genomic aberrations associated with methotrexate resistance vary with background genomic instability.

Tumors vary widely in chromosomal level genome instability. To gain a better understanding of the underlying defects which foster specific types of aberrations, we investigated the response of cells of related genetic backgrounds to challenge with methotrexate. We studied mismatch repair deficient HCT116 cells, two derivatives also deficient in XRCC5 (HCT116 Ku86+/-) or BLM (HCT116 BLM-/-), and mismatch repair competent HCT116+chr3 cells. We show that colony formation occurred at a significantly higher frequency in HCT116 cells and HCT116 Ku86+/- cells compared to HCT116 BLM-/- and HCT116+chr3 cells. Visible colonies arose most rapidly in HCT116 Ku86+/- cells, whereas they formed most slowly in HCT116+chr3 cells. Copy number changes acquired by the methotrexate resistant HCT116 and HCT116 BLM-/- cells most often included whole chromosome gains or losses or no acquired copy number changes, whereas resistance in HCT116+chr3 and HCT116 Ku86+/- cells was associated with amplification of DHFR and copy number transitions leading to increased copy number of DHFR, respectively. The additional copies of DHFR were present on unstable chromosomes and organized as inverted repeats in HCT116+chr3 cells, while they were most often present as direct repeats in HCT116 Ku86+/- cells. These observations suggest that different mutational mechanisms promote drug resistance in these genetic backgrounds; mismatch repair deficiency in HCT116, high rates of chromosomal instability in HCT116 Ku86+/-, and low rates of chromosomal instability in HCT116+chr3. On the other hand, it appears that loss of BLM function suppresses the mismatch repair mutator mechanism in mismatch repair and BLM deficient HCT116 BLM-/- cells.

Protein biomarker identification in the CSF of patients with CNS lymphoma.

PURPOSE: Elucidation of the CSF proteome may yield insights into the pathogenesis of CNS disease. We tested the hypothesis that individual CSF proteins distinguish CNS lymphoma from benign focal brain lesions. METHODS: We used a liquid chromatography/mass spectrometry-based method to differentially quantify and identify several hundred CSF proteins in CNS lymphoma and control patients. We used enzyme-linked immunosorbent assay (ELISA) to confirm one of these markers in an additional validation set of 101 cases. RESULTS: Approximately 80 CSF proteins were identified and found to be present at significantly different concentrations, both higher and lower, in training and test studies, which were highly concordant. To further validate these observations, we defined in detail the expression of one of these candidate biomarkers, antithrombin III (ATIII). ATIII RNA transcripts were identified within CNS lymphomas, and ATIII protein was localized selectively to tumor neovasculature. Determination of ATIII concentration by ELISA was significantly more accurate (> 75% sensitivity; > 98% specificity) than cytology in the identification of cancer. Measurement of CSF ATIII levels was found to potentially enhance the ability to diagnose and predict outcome. CONCLUSION: Our findings demonstrate for the first time that proteomic analysis of CSF yields individual biomarkers with greater sensitivity in the identification of cancer than does CSF cytology. We propose that the discovery of CSF protein biomarkers will facilitate early and noninvasive diagnosis in patients with lesions not amenable to brain biopsy, as well as provide improved surrogates of prognosis and treatment response in CNS lymphoma and brain metastasis.

FBXW7 and DNA copy number instability.

SKP1-cullin-F-box protein (SCF) type ubiquitin ligases degrade proteins controlling the G1/S transition. Deficiency for FBXW7 (also known as hCDC4), which encodes the F-box protein of the SCF type ubiquitin ligase is associated with genomic instability. Here, we investigated the association of FBXW7 deficiency with chromosomal instability in breast cancer. We screened 49 tumors previously profiled by array CGH for mutations in conserved regions of FBXW7, but found no mutations. Copy number loss of FBXW7, however was associated with enhanced genomic instability in the Complex breast tumor subtype, but instability may not be due to FBXW7 haploinsufficiency, since transcript levels were not reduced in tumors with loss of the locus, whereas reduced expression was observed for other neighboring genes involved in maintenance of genome stability. We also investigated whether cells deficient for FBXW7 showed enhanced instability by challenging cells with methotrexate and assessing numbers of genomic alterations arising in resistant cells. Although methotrexate resistant colonies formed at high frequencies in HCT116 FBXW7+/- and HCT116 FBXW7-/- cells compared to parental HCT116, few copy number alterations were detected in the resistant cells. Taken together these studies suggest that FBXW7 deficiency is unlikely to contribute to the extensive copy number aberrations associated with breast and possibly other tumor types.

Evaluation of whole genome amplification protocols for array and oligonucleotide CGH.

Genome-based technologies such as genomic arrays and next generation sequencing are poised to make significant contributions to clinical oncology. However, translation of these technologies to the clinic will require that they produce high-quality reproducible data from small archived tumor specimens and biopsies. Herein, we report on a systematic and comprehensive microarray analysis comparing multiple whole genome amplification methods using a variety of difficult clinical specimens, including formalin-fixed and paraffin-embedded tissues. Quantitative analysis and clustering suggest that Sigma's whole genome amplification protocol performed best on all specimens and, moreover, worked well with a formalin-fixed, paraffin-embedded biopsy.

Amplification of PVT1 contributes to the pathophysiology of ovarian and breast cancer.

PURPOSE: This study was designed to elucidate the role of amplification at 8q24 in the pathophysiology of ovarian and breast cancer because increased copy number at this locus is one of the most frequent genomic abnormalities in these cancers. EXPERIMENTAL DESIGN: To accomplish this, we assessed the association of amplification at 8q24 with outcome in ovarian cancers using fluorescence in situ hybridization to tissue microarrays and measured responses of ovarian and breast cancer cell lines to specific small interfering RNAs against the oncogene MYC and a putative noncoding RNA, PVT1, both of which map to 8q24. RESULTS: Amplification of 8q24 was associated with significantly reduced survival duration. In addition, small interfering RNA-mediated reduction in either PVT1 or MYC expression inhibited proliferation in breast and ovarian cancer cell lines in which they were both amplified and overexpressed but not in lines in which they were not amplified/overexpressed. Inhibition of PVT1 expression also induced a strong apoptotic response in cell lines in which it was overexpressed but not in lines in which it was not amplified/overexpressed. Inhibition of MYC, on the other hand, did not induce an apoptotic response in cell lines in which MYC was amplified and overexpressed. CONCLUSIONS: These results suggest that MYC and PVT1 contribute independently to ovarian and breast pathogenesis when overexpressed because of genomic abnormalities. They also suggest that PVT1-mediated inhibition of apoptosis may explain why amplification of 8q24 is associated with reduced survival duration in patients treated with agents that act through apoptotic mechanisms.

Aging impacts transcriptomes but not genomes of hormone-dependent breast cancers.

INTRODUCTION: Age is one of the most important risk factors for human malignancies, including breast cancer; in addition, age at diagnosis has been shown to be an independent indicator of breast cancer prognosis. Except for inherited forms of breast cancer, however, there is little genetic or epigenetic understanding of the biological basis linking aging with sporadic breast cancer incidence and its clinical behavior. METHODS: DNA and RNA samples from matched estrogen receptor (ER)-positive sporadic breast cancers diagnosed in either younger (age or= 70 years) Caucasian women were analyzed by array comparative genomic hybridization and by expression microarrays. Array comparative genomic hybridization data were analyzed using hierarchical clustering and supervised age cohort comparisons. Expression microarray data were analyzed using hierarchical clustering and gene set enrichment analysis; differential gene expression was also determined by conditional permutation, and an age signature was derived using prediction analysis of microarrays. RESULTS: Hierarchical clustering of genome-wide copy-number changes in 71 ER-positive DNA samples (27 younger women, 44 older women) demonstrated two age-independent genotypes; one with few genomic changes other than 1q gain/16q loss, and another with amplifications and low-level gains/losses. Age cohort comparisons showed no significant differences in total or site-specific genomic breaks and amplicon frequencies. Hierarchical clustering of 5.1 K genes variably expressed in 101 ER-positive RNA samples (53 younger women, 48 older women) identified six transcriptome subtypes with an apparent age bias (P < 0.05). Samples with higher expression of a poor outcome-associated proliferation signature were predominantly (65%) younger cases. Supervised analysis identified cancer-associated genes differentially expressed between the cohorts; with younger cases expressing more cell cycle genes and more than threefold higher levels of the growth factor amphiregulin (AREG), and with older cases expressing higher levels of four different homeobox (HOX) genes in addition to ER (ESR1). An age signature validated against two other independent breast cancer datasets proved to have >80% accuracy in discerning younger from older ER-positive breast cancer cases with characteristic differences in AREG and ESR1 expression. CONCLUSION: These findings suggest that epigenetic transcriptome changes, more than genotypic variation, account for age-associated differences in sporadic breast cancer incidence and prognosis.

Genome position and gene amplification.

BACKGROUND: Amplifications, regions of focal high-level copy number change, lead to overexpression of oncogenes or drug resistance genes in tumors. Their presence is often associated with poor prognosis; however, the use of amplification as a mechanism for overexpression of a particular gene in tumors varies. To investigate the influence of genome position on propensity to amplify, we integrated a mutant form of the gene encoding dihydrofolate reductase into different positions in the human genome, challenged cells with methotrexate and then studied the genomic alterations arising in drug resistant cells. RESULTS: We observed site-specific differences in methotrexate sensitivity, amplicon organization and amplification frequency. One site was uniquely associated with a significantly enhanced propensity to amplify and recurrent amplicon boundaries, possibly implicating a rare folate-sensitive fragile site in initiating amplification. Hierarchical clustering of gene expression patterns and subsequent gene enrichment analysis revealed two clusters differing significantly in expression of MYC target genes independent of integration site. CONCLUSION: These studies suggest that genome context together with the particular challenges to genome stability experienced during the progression to cancer contribute to the propensity to amplify a specific oncogene or drug resistance gene, whereas the overall functional response to drug (or other) challenge may be independent of the genomic location of an oncogene.