Discovery and technical validation of high-performance methylated DNA markers for the detection of cervical lesions at risk of malignant progression in low- and middle-income countries.

BACKGROUND: Cervical cancer remains a leading cause of death, particularly in developing countries. WHO screening guidelines recommend human papilloma virus (HPV) detection as a means to identify women at risk of developing cervical cancer. While HPV testing identifies those at risk, it does not specifically distinguish individuals with neoplasia. We investigated whether a quantitative molecular test that measures methylated DNA markers could identify high-risk lesions in the cervix with accuracy. RESULTS: Marker discovery was performed in TCGA-CESC Infinium Methylation 450 K Array database and verified in three other public datasets. The panel was technically validated using Quantitative Multiplex-Methylation-Specific PCR in tissue sections (N = 252) and cervical smears (N = 244) from the USA, South Africa, and Vietnam. The gene panel consisted of FMN2, EDNRB, ZNF671, TBXT, and MOS. Cervical tissue samples from all three countries showed highly significant differential methylation in squamous cell carcinoma (SCC) with a sensitivity of 100% [95% CI 74.12-100.00], and specificity of 91% [95% CI 62.26-99.53] to 96% [95% CI 79.01-99.78], and receiver operating characteristic area under the curve (ROC AUC) = 1.000 [95% CI 1.00-1.00] compared to benign cervical tissue, and cervical intraepithelial neoplasia 2/3 with sensitivity of 55% [95% CI 37.77-70.84] to 89% [95% CI 67.20-98.03], specificity of 93% [95% CI 84.07-97.38] to 96% [95% CI 79.01-99.78], and a ROC AUC ranging from 0.793 [95% CI 0.68-0.89] to 0.99 [95% CI 0.97-1.00] compared to CIN1. In cervical smears, the marker panel detected SCC with a sensitivity of 87% [95% CI 77.45-92.69], specificity 95% [95% CI 88.64-98.18], and ROC AUC = 0.925 [95% CI 0.878-0.974] compared to normal, and high-grade squamous intraepithelial lesion (HSIL) at a sensitivity of 70% (95% CI 58.11-80.44), specificity of 94% (95% CI 88.30-97.40), and ROC AUC = 0.884 (95% CI 0.822-0.945) compared to low-grade intraepithelial lesion (LSIL)/normal in an analysis of pooled data from the three countries. Similar to HPV-positive, HPV-negative cervical carcinomas were frequently hypermethylated for these markers. CONCLUSIONS: This 5-marker panel detected SCC and HSIL in cervical smears with a high level of sensitivity and specificity. Molecular tests with the ability to rapidly detect high-risk HSIL will lead to timely treatment for those in need and prevent unnecessary procedures in women with low-risk lesions throughout the world. Validation of these markers in prospectively collected cervical smear cells followed by the development of a hypermethylated marker-based cervical cancer detection test is warranted.

Evaluation of a Liquid Biopsy-Breast Cancer Methylation (LBx-BCM) Cartridge Assay for Predicting Early Disease Progression and Survival: TBCRC 005 Prospective Trial.

PURPOSE: We previously demonstrated that high levels of circulating methylated DNA are associated with subsequent disease progression in women with metastatic breast cancer (MBC). In this study, we evaluated the clinical utility of a novel liquid biopsy-breast cancer methylation (LBx-BCM) prototype assay using the GeneXpert cartridge system for early assessment of disease progression in MBC. EXPERIMENTAL DESIGN: The 9-marker LBx-BCM prototype assay was evaluated in TBCRC 005, a prospective biomarker study, using plasma collected at baseline, week 4, and week 8 from 144 patients with MBC. RESULTS: At week 4, patients with MBC with high cumulative methylation (CM) had a significantly shorter median PFS (2.88 months vs. 6.60 months, P = 0.001) and OS (14.52 months vs. 22.44 months, P = 0.005) compared with those with low CM. In a multivariable model, high versus low CM was also associated with shorter PFS (HR, 1.90; 95% CI, 1.20-3.01; P = 0.006). Change in CM from baseline to week 4 (OR, 4.60; 95% CI, 1.77-11.93; P = 0.002) and high levels of CM at week 4 (OR, 2.78; 95% CI, 1.29-5.99; P = 0.009) were associated with progressive disease at the time of first restaging. A robust risk model based on week 4 circulating CM levels was developed to predict disease progression as early as 3 months after initiating a new treatment. CONCLUSIONS: The automated LBx-BCM prototype assay is a promising clinical tool for detecting disease progression a month after initiating treatment in women with MBC undergoing routine care. The next step is to validate its clinical utility for specific treatments.

Development of an automated liquid biopsy assay for methylated markers in advanced breast cancer.

Current molecular liquid biopsy assays to detect recurrence or monitor response to treatment require sophisticated technology, highly trained personnel, and a turnaround time of weeks. We describe the development and technical validation of an automated Liquid Biopsy for Breast Cancer Methylation (LBx-BCM) prototype, a DNA methylation detection cartridge assay that is simple to perform and quantitatively detects nine methylated markers within 4.5 h. LBx-BCM demonstrated high interassay reproducibility when analyzing exogenous methylated DNA (75-300 DNA copies) spiked into plasma (Coefficient of Variation, CV = 7.1 - 10.9%) and serum (CV = 19.1 - 36.1%). It also demonstrated high interuser reproducibility (Spearman r = 0.887, P < 0.0001) when samples of metastatic breast cancer (MBC, N = 11) and normal control (N = 4) were evaluated independently by two users. Analyses of interplatform reproducibility indicated very high concordance between LBx-BCM and the reference assay, cMethDNA, among 66 paired plasma samples (MBC N = 40, controls N = 26; Spearman r = 0.891; 95% CI = 0.825 - 0.933, P< 0.0001). LBx-BCM achieved a ROC AUC = 0.909 (95% CI = 0.836 - 0.982), 83% sensitivity and 92% specificity; cMethDNA achieved a ROC AUC = 0.896 (95% CI = 0.817 - 0.974), 83% sensitivity and 92% specificity in test set samples. The automated LBx-BCM cartridge prototype is fast, with performance levels equivalent to the highly sensitive, manual cMethDNA method. Future prospective clinical studies will evaluate LBx-BCM detection sensitivity and its ability to monitor therapeutic response during treatment for advanced breast cancer.

High performance methylated DNA markers for detection of colon adenocarcinoma.

BACKGROUND: Colon cancer (CC) is treatable if detected in its early stages. Improved CC detection assays that are highly sensitive, specific, and available at point of care are needed. In this study, we systematically selected and tested methylated markers that demonstrate high sensitivity and specificity for detection of CC in tissue and circulating cell-free DNA. METHODS: Hierarchical analysis of 22 candidate CpG loci was conducted using The Cancer Genome Atlas (TCGA) COAD 450K HumanMethylation database. Methylation of 13 loci was analyzed using quantitative multiplex methylation-specific PCR (QM-MSP) in a training set of fresh frozen colon tissues (N = 53). Hypermethylated markers were identified that were highest in cancer and lowest in normal colon tissue using the 75th percentile in Mann-Whitney analyses and the receiver operating characteristic (ROC) statistic. The cumulative methylation status of the marker panel was assayed in an independent test set of fresh frozen colon tissues (N = 52) using conditions defined and locked in the training set. A minimal marker panel of 6 genes was defined based on ROC area under the curve (AUC). Plasma samples (N = 20 colorectal cancers, stage IV and N = 20 normal) were tested by cMethDNA assay to evaluate marker performance in liquid biopsy. RESULTS: In the test set of samples, compared to normal tissue, a 6-gene panel showed 100% sensitivity and 90% specificity for detection of CC, and an AUC of 1.00 (95% CI 1.00, 1.00). In stage IV colorectal cancer plasma versus normal, an 8-gene panel showed 95% sensitivity, 100% specificity, and an AUC of 0.996 (95% CI 0.986, 1.00) while a 5-gene subset showed 100% sensitivity, 100% specificity, and an AUC of 1.00 (95% CI 1.00, 1.00), highly concordant with our observations in tissue. CONCLUSIONS: We identified high performance methylated DNA marker panels for detection of CC. This knowledge has set the stage for development and implementation of novel, automated, self-contained CC detection assays in tissue and blood which can expeditiously and accurately detect colon cancer in both developed and underdeveloped regions of the world, enabling optimal use of limited resources in low- and middle-income countries.

Automated and rapid detection of cancer in suspicious axillary lymph nodes in patients with breast cancer.

Preoperative staging of suspicious axillary lymph nodes (ALNs) allows patients to be triaged to ALN dissection or to sentinel lymph node biopsy (SLNB). Ultrasound-guided fine needle aspiration (FNA) and cytology of ALN is moderately sensitive but its clinical utility relies heavily on the cytologist's experience. We proposed that the 5-h automated GeneXpert system-based prototype breast cancer detection assay (BCDA) that quantitatively measures DNA methylation in ten tumor-specific gene markers could provide a facile, accurate test for detecting cancer in FNA of enlarged lymph nodes. We validated the assay in ALN-FNA samples from a prospective study of patients (N = 230) undergoing SLNB. In a blinded analysis of 218 evaluable LN-FNAs from 108 malignant and 110 benign LNs by histology, BCDA displayed a sensitivity of 90.7% and specificity of 99.1%, achieving an area under the ROC curve, AUC of 0.958 (95% CI: 0.928-0.989; P < 0.0001). Next, we conducted a study of archival FNAs of ipsilateral palpable LNs (malignant, N = 72, benign, N = 53 by cytology) collected in the outpatient setting prior to neoadjuvant chemotherapy (NAC). Using the ROC-threshold determined in the prospective study, compared to cytology, BCDA achieved a sensitivity of 94.4% and a specificity of 92.5% with a ROC-AUC = 0.977 (95% CI: 0.953-1.000; P < 0.0001). Our study shows that the automated assay detects cancer in suspicious lymph nodes with a high level of accuracy within 5 h. This cancer detection assay, scalable for analysis to scores of LN FNAs, could assist in determining eligibility of patients to different treatment regimens.

DNA methylation markers predict recurrence-free interval in triple-negative breast cancer.

We lack tools to risk-stratify triple-negative breast cancer (TNBC). Our goal was to develop molecular tools to predict disease recurrence. Methylation array analysis was performed on 110 samples treated by locoregional therapy obtained from institutional cohorts. Discovered marker sets were then tested by Kaplan-Meier analyses in a prospectively collected TNBC cohort of 49 samples from the no-chemotherapy arms of IBCSG trials VIII and IX, and by logistic regression in a chemotherapy-treated cohort of 121 TNBCs from combined IBCSG trials and institutional repositories. High methylation was associated with shorter recurrence-free interval in the no-chemotherapy arm of the IBCSG studies, as well as in the chemotherapy-treated patients within the combined institutional and IBCSG chemotherapy cohorts (100 marker panel, p = 0.002; 30 marker panel, p = 0.05). Chromosome 19 sites were enriched among these loci. In conclusion, our hypermethylation signatures identify increased recurrence risk independent of whether patients receive chemotherapy.

DNA Methylation Markers for Breast Cancer Detection in the Developing World.

PURPOSE: An unmet need in low-resource countries is an automated breast cancer detection assay to prioritize women who should undergo core breast biopsy and pathologic review. Therefore, we sought to identify and validate a panel of methylated DNA markers to discriminate between cancer and benign breast lesions using cells obtained by fine-needle aspiration (FNA).Experimental Design: Two case-control studies were conducted comparing cancer and benign breast tissue identified from clinical repositories in the United States, China, and South Africa for marker selection/training (N = 226) and testing (N = 246). Twenty-five methylated markers were assayed by Quantitative Multiplex-Methylation-Specific PCR (QM-MSP) to select and test a cancer-specific panel. Next, a pilot study was conducted on archival FNAs (49 benign, 24 invasive) from women with mammographically suspicious lesions using a newly developed, 5-hour, quantitative, automated cartridge system. We calculated sensitivity, specificity, and area under the receiver-operating characteristic curve (AUC) compared with histopathology for the marker panel. RESULTS: In the discovery cohort, 10 of 25 markers were selected that were highly methylated in breast cancer compared with benign tissues by QM-MSP. In the independent test cohort, this panel yielded an AUC of 0.937 (95% CI = 0.900-0.970). In the FNA pilot, we achieved an AUC of 0.960 (95% CI = 0.883-1.0) using the automated cartridge system. CONCLUSIONS: We developed and piloted a fast and accurate methylation marker-based automated cartridge system to detect breast cancer in FNA samples. This quick ancillary test has the potential to prioritize cancer over benign tissues for expedited pathologic evaluation in poorly resourced countries.

Correction to: Quantitative phosphoproteomic analysis reveals reciprocal activation of receptor tyrosine kinases between cancer epithelial cells and stromal fibroblasts.

[This corrects the article DOI: 10.1186/s12014-018-9197-x.].

Breast Hormone Concentrations in Random Fine-Needle Aspirates of Healthy Women Associate with Cytological Atypia and Gene Methylation.

Sex steroid hormones contribute to breast cancer development, but data on concentrations of these within breast tissue are limited. We performed simultaneous multiparameter measurement of breast sex steroids, breast epithelial cytology, and DNA methylation in 119 healthy women (54 pre- and 65 postmenopausal) without a history of breast cancer. Random fine-needle aspiration (rFNA) of the breast was performed simultaneously with blood collection. Breast samples were analyzed by LC/MS-MS for estrone, estradiol, progesterone, androstenedione, and testosterone. Blood samples were assayed for estradiol and progesterone by immunoassay. Cytomorphology was classified using the Masood Score, and DNA methylation of eight genes was analyzed using quantitative multiplexed methylation-specific PCR, and expressed as the cumulative methylation index (CMI). Serum and breast concentrations of estradiol and progesterone showed significant correlation (Spearman r = 0.34, Padj = 0.001 and r = 0.69, Padj < 0.0006, respectively). Progesterone concentration was significantly higher in the premenopausal breast (Padj < 0.0008), and showed a luteal surge. Breast estrone and estradiol concentrations did not differ significantly by menopause, but androstenedione concentration was higher in the breasts of postmenopausal women (P = 0.026 and Padj = 0.208). Breast androgens were significantly correlated with breast density (Spearman r = 0.27, Padj = 0.02 for testosterone) and CMI (Spearman r = 0.3, Padj = 0.038 for androstenedione). Our data indicate that future larger studies of breast steroid hormones along with other parameters are feasible. Significant associations of breast androgen concentrations with breast density and gene methylation warrant future study. Cancer Prev Res; 11(9); 557-68. ©2018 AACR.

Quantitative phosphoproteomic analysis reveals reciprocal activation of receptor tyrosine kinases between cancer epithelial cells and stromal fibroblasts.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are one of the most important components of tumor stroma and play a key role in modulating tumor growth. However, a mechanistic understanding of how CAFs communicate with tumor cells to promote their proliferation and invasion is far from complete. A major reason for this is that most current techniques and model systems do not capture the complexity of signal transduction that occurs between CAFs and tumor cells. METHODS: In this study, we employed a stable isotope labeling with amino acids in cell culture (SILAC) strategy to label invasive breast cancer cells, MDA-MB-231, and breast cancer patient-derived CAF this has already been defined above cells. We used an antibody-based phosphotyrosine peptide enrichment method coupled to LC-MS/MS to catalog and quantify tyrosine phosphorylation-mediated signal transduction events induced by the bidirectional communication between patient-derived CAFs and tumor cells. RESULTS: We discovered that distinct signaling events were activated in CAFs and in tumor epithelial cells during the crosstalk between these two cell types. We identified reciprocal activation of a number of receptor tyrosine kinases including EGFR, FGFR1 and EPHA2 induced by this bidirectional communication. CONCLUSIONS: Our study not only provides insights into the mechanisms of the interaction between CAFs and tumor cells, but the model system described here could be used as a prototype for analysis of intercellular communication in many different tumor microenvironments.

Quantitation of DNA Methylation by Quantitative Multiplex Methylation-Specific PCR (QM-MSP) Assay.

The defining feature of the Quantitative Multiplex Methylation-Specific PCR (QM-MSP) method to sensitively quantify DNA methylation is the two-step PCR approach for a multiplexed analysis of a panel of up to 12 genes in clinical samples with minimal quantities of DNA. In the first step, for up to 12 genes tested, one pair of gene-specific primers (forward and reverse) amplifies the methylated and unmethylated copies of the same gene simultaneously and in multiplex, in one PCR reaction. This methylation-independent amplification step produces amplicons of up to 109 copies per µL after 36 cycles of PCR. In the second step, the amplicons of the first reaction (STEP 1) are quantified with a standard curve using real-time PCR and two independent fluorophores to detect methylated/unmethylated DNA of each gene in the same well (e.g., 6FAM and VIC). One methylated copy is detectable in 100,000 reference gene copies. Methylation is reported on a continuous scale. For the gene panel, the highest level of normal DNA methylation above which a sample would be called positive is derived by using Receiver Operating Characteristic (ROC), maximizing assay specificity and sensitivity to distinguish between normal/benign versus tumor DNA. QM-MSP can be applied to clinical samples of fresh or fixed ductal cells, ductal fluid, nipple fluid, fine needle aspirates, core biopsies, and tumor tissue sections.

Tumor and serum DNA methylation in women receiving preoperative chemotherapy with or without vorinostat in TBCRC008.

BACKGROUND: Methylated gene markers have shown promise in predicting breast cancer outcomes and treatment response. We evaluated whether baseline and changes in tissue and serum methylation levels would predict pathological complete response (pCR) in patients with HER2-negative early breast cancer undergoing preoperative chemotherapy. METHODS: The TBCRC008 trial investigated pCR following 12 weeks of preoperative carboplatin and albumin-bound paclitaxel + vorinostat/placebo (n = 62). We measured methylation of a 10-gene panel by quantitative multiplex methylation-specific polymerase chain reaction and expressed results as cumulative methylation index (CMI). We evaluated association between CMI level [baseline, day 15 (D15), and change] and pCR using univariate and multivariable logistic regression models controlling for treatment and hormone receptor (HR) status, and performed exploratory subgroup analyses. RESULTS: In univariate analysis, one log unit increase in tissue CMI levels at D15 was associated with 40% lower chance of obtaining pCR (odds ratio, OR 0.60, 95% CI 0.37-0.97; p = 0.037). Subgroup analyses suggested a significant association between tissue D15 CMI levels and pCR in vorinostat-treated [OR 0.44 (0.20, 0.93), p = 0.03], but not placebo-treated patients. CONCLUSION: In this study investigating the predictive roles of tissue and serum CMI levels in patients with early breast cancer for the first time, we demonstrate that high D15 tissue CMI levels may predict poor response. Larger studies and improved analytical procedures to detect methylated gene markers in early stage breast cancer are needed. TBCRC008 is registered on ClinicalTrials.gov (NCT00616967).

Gene Methylation and Cytological Atypia in Random Fine-Needle Aspirates for Assessment of Breast Cancer Risk.

Methods to determine individualized breast cancer risk lack sufficient sensitivity to select women most likely to benefit from preventive strategies. Alterations in DNA methylation occur early in breast cancer. We hypothesized that cancer-specific methylation markers could enhance breast cancer risk assessment. We evaluated 380 women without a history of breast cancer. We determined their menopausal status or menstrual cycle phase, risk of developing breast cancer (Gail model), and breast density and obtained random fine-needle aspiration (rFNA) samples for assessment of cytopathology and cumulative methylation index (CMI). Eight methylated gene markers were identified through whole-genome methylation analysis and included novel and previously established breast cancer detection genes. We performed correlative and multivariate linear regression analyses to evaluate DNA methylation of a gene panel as a function of clinical factors associated with breast cancer risk. CMI and individual gene methylation were independent of age, menopausal status or menstrual phase, lifetime Gail risk score, and breast density. CMI and individual gene methylation for the eight genes increased significantly (P < 0.001) with increasing cytological atypia. The findings were verified with multivariate analyses correcting for age, log (Gail), log (percent density), rFNA cell number, and body mass index. Our results demonstrate a significant association between cytological atypia and high CMI, which does not vary with menstrual phase or menopause and is independent of Gail risk and mammographic density. Thus, CMI is an excellent candidate breast cancer risk biomarker, warranting larger prospective studies to establish its utility for cancer risk assessment. Cancer Prev Res; 9(8); 673-82. ©2016 AACR.

Global phosphotyrosine survey in triple-negative breast cancer reveals activation of multiple tyrosine kinase signaling pathways.

Breast cancer is the most prevalent cancer in women worldwide. About 15-20% of all breast cancers are triple negative breast cancer (TNBC) and are often highly aggressive when compared to other subtypes of breast cancers. To better characterize the biology that underlies the TNBC phenotype, we profiled the phosphotyrosine proteome of a panel of twenty-six TNBC cell lines using quantitative high resolution Fourier transform mass spectrometry. A heterogeneous pattern of tyrosine kinase activation was observed based on 1,789 tyrosine-phosphorylated peptides identified from 969 proteins. One of the tyrosine kinases, AXL, was found to be activated in a majority of aggressive TNBC cell lines and was accompanied by a higher level of AXL expression. High levels of AXL expression are correlated with a significant decrease in patient survival. Treatment of cells bearing activated AXL with a humanized AXL antibody inhibited cell proliferation and migration in vitro, and tumor growth in mice. Overall, our global phosphoproteomic analysis provided new insights into the heterogeneity in the activation status of tyrosine kinase pathways in TNBCs. Our approach presents an effective means of identifying important novel biomarkers and targets for therapy such as AXL in TNBC.

Erratum to: Modeling precision treatment of breast cancer.

During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum.

Do breast cancer cell lines provide a relevant model of the patient tumor methylome?

It is well documented that tumor cells undergo dramatic genetic and epigenetic changes during initial establishment as cell lines and in subsequent serial passaging, and that the resultant cell lines may have evolved significantly from the primary tumors from which they were derived. This has potential implications due to their widespread use in drug response experiments and studies of genomic function. One approach to optimizing the design of such cell line studies is to identify and use the cell lines that faithfully recapitulate critical features of primary tumors. To evaluate the epigenetic fidelity of breast cancer cell lines in the context of primary tumors, we performed methylation profiling of 55 well-characterized breast cancer cell lines on the Illumina HumanMethylation27 BeadChip platform, and compared them to publicly available methylation profiles of primary breast tumors. We found that the DNA methylation profiles of breast cancer cell lines largely retain the features that characterize primary tumors, although there are crucial differences as well. We describe these similarities and differences between primary tumors and breast cancer cell lines in detail, and develop a quantitative measure of similarity that is used to score each cell line with respect to how faithfully its methylation profile mirrors that of primary tumors.

Novel methylated biomarkers and a robust assay to detect circulating tumor DNA in metastatic breast cancer.

The ability to consistently detect cell-free tumor-specific DNA in peripheral blood of patients with metastatic breast cancer provides the opportunity to detect changes in tumor burden and to monitor response to treatment. We developed cMethDNA, a quantitative multiplexed methylation-specific PCR assay for a panel of ten genes, consisting of novel and known breast cancer hypermethylated markers identified by mining our previously reported study of DNA methylation patterns in breast tissue (103 cancer, 21 normal on the Illumina HumanMethylation27 Beadchip) and then validating the 10-gene panel in The Cancer Genome Atlas project breast cancer methylome database. For cMethDNA, a fixed physiologic level (50 copies) of artificially constructed, standard nonhuman reference DNA specific for each gene is introduced in a constant volume of serum (300 µL) before purification of the DNA, facilitating a sensitive, specific, robust, and quantitative assay of tumor DNA, with broad dynamic range. Cancer-specific methylated DNA was detected in training (28 normal, 24 cancer) and test (27 normal, 33 cancer) sets of recurrent stage IV patient sera with a sensitivity of 91% and a specificity of 96% in the test set. In a pilot study, cMethDNA assay faithfully reflected patient response to chemotherapy (N = 29). A core methylation signature present in the primary breast cancer was retained in serum and metastatic tissues collected at autopsy two to 11 years after diagnosis of the disease. Together, our data suggest that the cMethDNA assay can detect advanced breast cancer, and monitor tumor burden and treatment response in women with metastatic breast cancer.

Modeling precision treatment of breast cancer.

BACKGROUND: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. RESULTS: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. CONCLUSIONS: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

Molecular profiling of human mammary gland links breast cancer risk to a p27(+) cell population with progenitor characteristics.

Early full-term pregnancy is one of the most effective natural protections against breast cancer. To investigate this effect, we have characterized the global gene expression and epigenetic profiles of multiple cell types from normal breast tissue of nulliparous and parous women and carriers of BRCA1 or BRCA2 mutations. We found significant differences in CD44(+) progenitor cells, where the levels of many stem cell-related genes and pathways, including the cell-cycle regulator p27, are lower in parous women without BRCA1/BRCA2 mutations. We also noted a significant reduction in the frequency of CD44(+)p27(+) cells in parous women and showed, using explant cultures, that parity-related signaling pathways play a role in regulating the number of p27(+) cells and their proliferation. Our results suggest that pathways controlling p27(+) mammary epithelial cells and the numbers of these cells relate to breast cancer risk and can be explored for cancer risk assessment and prevention.

Genome-wide methylation analysis identifies genes specific to breast cancer hormone receptor status and risk of recurrence.

To better understand the biology of hormone receptor-positive and-negative breast cancer and to identify methylated gene markers of disease progression, we carried out a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples, using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen and/or progesterone receptor-positive tumors displayed more hypermethylated loci than estrogen receptor (ER)-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared with ER-positive tumors. An ER-classifier set of CpG loci was identified, which independently partitioned primary tumors into ER subtypes. A total of 40 (32 novel and 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors. Each of the 40 ER subtype-specific loci was validated in silico, using an independent, publicly available methylome dataset from the Cancer Genome Atlas. In addition, we identified 100 methylated CpG loci that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes. This pilot study shows the robustness of the breast cancer methylome and illustrates its potential to stratify and reveal biological differences between ER subtypes of breast cancer. Furthermore, it defines candidate ER-specific markers and identifies potential markers predictive of outcome within ER subgroups.