Multi-omics analysis reveals epigenetically regulated processes and patient classification in lung adenocarcinoma

Aberrant DNA methylation is a hallmark of many cancer types. Despite our knowledge of epigenetic and transcriptomic alterations in lung adenocarcinoma (LUAD), we lack robust multi-modal molecular classifications for patient stratification. This is partly because the impact of epigenetic alterations on lung cancer development and progression is still not fully understood. To that end, we identified disease-associated processes under epigenetic regulation in LUAD. We performed a genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis by integrating DNA methylation and gene expression data from 453 patients in the TCGA cohort. Using a community detection algorithm, we identified distinct communities of CpG-gene associations with diverse biological processes. Interestingly, we identified a community linked to hormone response and lipid metabolism; the identified CpGs in this community were enriched in enhancer regions and binding regions of transcription factors such as FOXA1/2, GRHL2, HNF1B, AR, and ESR1. Furthermore, the CpGs were connected to their associated genes through chromatin interaction loops. These findings suggest that the expression of genes involved in hormone response and lipid metabolism in LUAD is epigenetically regulated through DNA methylation and enhancer-promoter interactions. By applying consensus clustering on the integrated expression-methylation pattern of the emQTL-genes and CpGs linked to hormone response and lipid metabolism, we further identified subclasses of patients with distinct prognoses. This novel patient stratification was validated in an independent patient cohort of 135 patients and showed increased prognostic significance compared to previously defined molecular subtypes.

An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer

Treatment with the anti-angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response-related epigenetic events. Fresh-frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non-metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression-methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation-epithelial-to-mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell-specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients.

MRI Assessment of Changes in Tumor Vascularization during Neoadjuvant Anti-Angiogenic Treatment in Locally Advanced Breast Cancer Patients

Anti-VEGF (vascular endothelial growth factor) treatment improves response rates, but not progression-free or overall survival in advanced breast cancer. It has been suggested that subgroups of patients may benefit from this treatment; however, the effects of adding anti-VEGF treatment to a standard chemotherapy regimen in breast cancer patients are not well studied. Understanding the effects of the anti-vascular treatment on tumor vasculature may provide a selection of patients that can benefit. The aim of this study was to study the vascular effect of bevacizumab using clinical dynamic contrast-enhanced MRI (DCE-MRI). A total of 70 women were randomized to receive either chemotherapy alone or chemotherapy with bevacizumab for 25 weeks. DCE-MRI was performed at baseline and at 12 and 25 weeks, and in addition 25 of 70 patients agreed to participate in an early MRI after one week. Voxel-wise pharmacokinetic analysis was performed using semi-quantitative methods and the extended Tofts model. Vascular architecture was assessed by calculating the fractal dimension of the contrast-enhanced images. Changes during treatment were compared with baseline and between the treatment groups. There was no significant difference in tumor volume at any point; however, DCE-MRI parameters revealed differences in vascular function and vessel architecture. Adding bevacizumab to chemotherapy led to a pronounced reduction in vascular DCE-MRI parameters, indicating decreased vascularity. At 12 and 25 weeks, the difference between the treatment groups is severely reduced.

ABCB1 Amplicon Contains Cyclic AMP Response Element-Driven TRIP6 Gene in Taxane-Resistant MCF-7 Breast Cancer Sublines

A limited number of studies are devoted to regulating TRIP6 expression in cancer. Hence, we aimed to unveil the regulation of TRIP6 expression in MCF-7 breast cancer cells (with high TRIP6 expression) and taxane-resistant MCF-7 sublines (manifesting even higher TRIP6 expression). We found that TRIP6 transcription is regulated primarily by the cyclic AMP response element (CRE) in hypomethylated proximal promoters in both taxane-sensitive and taxane-resistant MCF-7 cells. Furthermore, in taxane-resistant MCF-7 sublines, TRIP6 co-amplification with the neighboring ABCB1 gene, as witnessed by fluorescence in situ hybridization (FISH), led to TRIP6 overexpression. Ultimately, we found high TRIP6 mRNA levels in progesterone receptor-positive breast cancer and samples resected from premenopausal women.

Transcriptomic pan-cancer analysis using rank-based Bayesian inference

The analysis of whole genomes of pan-cancer data sets provides a challenge for researchers, and we contribute to the literature concerning the identification of robust subgroups with clear biological interpretation. Specifically, we tackle this unsupervised problem via a novel rank-based Bayesian clustering method. The advantages of our method are the integration and quantification of all uncertainties related to both the input data and the model, the probabilistic interpretation of final results to allow straightforward assessment of the stability of clusters leading to reliable conclusions, and the transparent biological interpretation of the identified clusters since each cluster is characterized by its top-ranked genomic features. We applied our method to RNA-seq data from cancer samples from 12 tumor types from the Cancer Genome Atlas. We identified a robust clustering that mostly reflects tissue of origin but also includes pan-cancer clusters. Importantly, we identified three pan-squamous clusters composed of a mix of lung squamous cell carcinoma, head and neck squamous carcinoma, and bladder cancer, with different biological functions over-represented in the top genes that characterize the three clusters. We also found two novel subtypes of kidney cancer that show different prognosis, and we reproduced known subtypes of breast cancer. Taken together, our method allows the identification of robust and biologically meaningful clusters of pan-cancer samples.

Complex molecular profile of DNA repair genes in epithelial ovarian carcinoma patients with different sensitivity to platinum-based therapy

Epithelial ovarian carcinoma (EOC) is known for high mortality due to diagnosis at advanced stages and frequent therapy resistance. Previous findings suggested that the DNA repair system is involved in the therapeutic response of cancer patients and DNA repair genes are promising targets for novel therapies. This study aimed to address complex inter-relations among gene expression levels, methylation profiles, and somatic mutations in DNA repair genes and EOC prognosis and therapy resistance status. We found significant associations of DUT expression with the presence of peritoneal metastases in EOC patients. The high-grade serous EOC subtype was enriched with TP53 mutations compared to other subtypes. Furthermore, somatic mutations in XPC and PRKDC were significantly associated with worse overall survival of EOC patients, and higher FAAP20 expression in platinum-resistant than platinum-sensitive patients was observed. We found higher methylation of RAD50 in platinum-resistant than in platinum-sensitive patients. Somatic mutations in BRCA1 and RAD9A were significantly associated with higher RBBP8 methylation in platinum-sensitive compared to platinum-resistant EOC patients. In conclusion, we discovered associations of several candidate genes from the DNA repair pathway with the prognosis and platinum resistance status of EOC patients, which deserve further validation as potential predictive biomarkers.

Rank-based Bayesian variable selection for genome-wide transcriptomic analyses

Variable selection is crucial in high-dimensional omics-based analyses, since it is biologically reasonable to assume only a subset of non-noisy features contributes to the data structures. However, the task is particularly hard in an unsupervised setting, and a priori ad hoc variable selection is still a very frequent approach, despite the evident drawbacks and lack of reproducibility. We propose a Bayesian variable selection approach for rank-based unsupervised transcriptomic analysis. Making use of data rankings instead of the actual continuous measurements increases the robustness of conclusions when compared to classical statistical methods, and embedding variable selection into the inferential tasks allows complete reproducibility. Specifically, we develop a novel extension of the Bayesian Mallows model for variable selection that allows for a full probabilistic analysis, leading to coherent quantification of uncertainties. Simulation studies demonstrate the versatility and robustness of the proposed method in a variety of scenarios, as well as its superiority with respect to several competitors when varying the data dimension or data generating process. We use the novel approach to analyze genome-wide RNAseq gene expression data from ovarian cancer patients: several genes that affect cancer development are correctly detected in a completely unsupervised fashion, showing the usefulness of the method in the context of signature discovery for cancer genomics. Moreover, the possibility to also perform uncertainty quantification plays a key role in the subsequent biological investigation.

PHLPP1 regulates CFTR activity and lumen expansion through AMPK

Complex organ development depends on single lumen formation and its expansion during tubulogenesis. This can be achieved by correct mitotic spindle orientation during cell division, combined with luminal fluid filling that generates hydrostatic pressure. Using a human 3D cell culture model, we have identified two regulators of these processes. We find that pleckstrin homology leucine-rich repeat protein phosphatase (PHLPP) 2 regulates mitotic spindle orientation, and thereby midbody positioning and maintenance of a single lumen. Silencing the sole PHLPP family phosphatase in Drosophila melanogaster, phlpp, resulted in defective spindle orientation in Drosophila neuroblasts. Importantly, cystic fibrosis transmembrane conductance regulator (CFTR) is the main channel regulating fluid transport in this system, stimulated by phosphorylation by protein kinase A and inhibited by the AMP-activated protein kinase AMPK. During lumen expansion, CFTR remains open through the action of PHLPP1, which stops activated AMPK from inhibiting ion transport through CFTR. In the absence of PHLPP1, the restraint on AMPK activity is lost and this tips the balance in the favour of channel closing, resulting in the lack of lumen expansion and accumulation of mucus.

DNA methylation changes in response to neoadjuvant chemotherapy are associated with breast cancer survival

BACKGROUND

Locally advanced breast cancer is a heterogeneous disease with respect to response to neoadjuvant chemotherapy (NACT) and survival. It is currently not possible to accurately predict who will benefit from the specific types of NACT. DNA methylation is an epigenetic mechanism known to play an important role in regulating gene expression and may serve as a biomarker for treatment response and survival. We investigated the potential role of DNA methylation as a prognostic marker for long-term survival (> 5 years) after NACT in breast cancer.

METHODS

DNA methylation profiles of pre-treatment (n = 55) and post-treatment (n = 75) biopsies from 83 women with locally advanced breast cancer were investigated using the Illumina HumanMethylation450 BeadChip. The patients received neoadjuvant treatment with epirubicin and/or paclitaxel. Linear mixed models were used to associate DNA methylation to treatment response and survival based on clinical response to NACT (partial response or stable disease) and 5-year survival, respectively. LASSO regression was performed to identify a risk score based on the statistically significant methylation sites and Kaplan-Meier curve analysis was used to estimate survival probabilities using ten years of survival follow-up data. The risk score developed in our discovery cohort was validated in an independent validation cohort consisting of paired pre-treatment and post-treatment biopsies from 85 women with locally advanced breast cancer. Patients included in the validation cohort were treated with either doxorubicin or 5-FU and mitomycin NACT.

RESULTS

DNA methylation patterns changed from before to after NACT in 5-year survivors, while no significant changes were observed in non-survivors or related to treatment response. DNA methylation changes included an overall loss of methylation at CpG islands and gain of methylation in non-CpG islands, and these changes affected genes linked to transcription factor activity, cell adhesion and immune functions. A risk score was developed based on four methylation sites which successfully predicted long-term survival in our cohort (p = 0.0034) and in an independent validation cohort (p = 0.049).

CONCLUSION

Our results demonstrate that DNA methylation patterns in breast tumors change in response to NACT. These changes in DNA methylation show potential as prognostic biomarkers for breast cancer survival.

Pioneer transcription factors are associated with the modulation of DNA methylation patterns across cancers

Methylation of cytosines on DNA is a prominent modification associated with gene expression regulation. Aberrant DNA methylation patterns have recurrently been linked to dysregulation of the regulatory program in cancer cells. To shed light on the underlying molecular mechanism driving this process, we hypothesised that aberrant methylation patterns could be controlled by the binding of specific transcription factors (TFs) across cancer types. By combining DNA methylation arrays and gene expression data with TF binding sites (TFBSs), we explored the interplay between TF binding and DNA methylation in 19 cancer types. We performed emQTL (expression–methylation quantitative trait loci) analyses independently in each cancer type and identified 13 TFs whose expression levels are correlated with local DNA methylation patterns around their binding sites in at least 2 cancer types. The 13 TFs are mainly associated with local demethylation and are enriched for pioneer function, suggesting a specific role for these TFs in modulating chromatin structure and transcription in cancer patients. Furthermore, we confirmed that de novo methylation is precluded across cancers at CpGs lying in genomic regions enriched for TF binding signatures associated with SP1, CTCF, NRF1, GABPA, KLF9, and/or YY1. The modulation of DNA methylation associated with TF binding was observed at cis-regulatory regions controlling immune- and cancer-associated pathways, corroborating that the emQTL signals were derived from both cancer and tumor-infiltrating cells. As a case example, we experimentally confirmed that FOXA1 knock-down is associated with higher methylation in regions bound by FOXA1 in breast cancer MCF-7 cells. Finally, we reported physical interactions between FOXA1 with TET1 and TET2 both in an in vitro setup and in vivo at physiological levels in MCF-7 cells, adding further support for FOXA1 attracting TET1 and TET2 to induce local demethylation in cancer cells.

Epigenetic alterations at distal enhancers are linked to proliferation in human breast cancer

Aberrant DNA methylation is an early event in breast carcinogenesis and plays a critical role in regulating gene expression. Here, we perform genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis through the integration of DNA methylation and gene expression to identify disease-driving pathways under epigenetic control. By grouping the emQTLs using biclustering we identify associations representing important biological processes associated with breast cancer pathogenesis including regulation of proliferation and tumor-infiltrating fibroblasts. We report genome-wide loss of enhancer methylation at binding sites of proliferation-driving transcription factors including CEBP-β, FOSL1, and FOSL2 with concomitant high expression of proliferation-related genes in aggressive breast tumors as we confirm with scRNA-seq. The identified emQTL-CpGs and genes were found connected through chromatin loops, indicating that proliferation in breast tumors is under epigenetic regulation by DNA methylation. Interestingly, the associations between enhancer methylation and proliferation-related gene expression were also observed within known subtypes of breast cancer, suggesting a common role of epigenetic regulation of proliferation. Taken together, we show that proliferation in breast cancer is linked to loss of methylation at specific enhancers and transcription factor binding and gene activation through chromatin looping.

Multi-Omics Marker Analysis Enables Early Prediction of Breast Tumor Progression

Ductal carcinoma in situ (DCIS) is a preinvasive form of breast cancer with a highly variable potential of becoming invasive and affecting mortality of the patients. Due to the lack of accurate markers of disease progression, many women with detected DCIS are currently overtreated. To distinguish those DCIS cases who are likely to require therapy from those who should be left untreated, there is a need for robust and predictive biomarkers extracted from molecular or genetic profiles. We developed a supervised machine learning approach that implements multi-omics feature selection and model regularization for the identification of biomarker combinations that could be used to distinguish low-risk DCIS lesions from those with a higher likelihood of progression. To investigate the genetic heterogeneity of disease progression, we applied this approach to 40 pure DCIS and 259 invasive breast cancer (IBC) samples profiled with genome-wide transcriptomics, DNA methylation, and DNA copy number variation. Feature selection using the multi-omics Lasso-regularized algorithm identified both known genes involved in breast cancer development, as well as novel markers for early detection. Even though the gene expression-based model features led to the highest classification accuracy alone, methylation data provided a complementary source of features and improved especially the sensitivity of correctly classifying DCIS cases. We also identified a number of repeatedly misclassified DCIS cases when using either the expression or methylation markers. A small panel of 10 gene markers was able to distinguish DCIS and IBC cases with high accuracy in nested cross-validation (AU-ROC = 0.99). The marker panel was not specific to any of the established breast cancer subtypes, suggesting that the 10-gene signature may provide a subtype-agnostic and cost-effective approach for breast cancer detection and patient stratification. We further confirmed high accuracy of the 10-gene signature in an external validation cohort (AU-ROC = 0.95), profiled using distinct transcriptomic assay, hence demonstrating robustness of the risk signature.

Crosstalk between microRNA expression and DNA methylation drives the hormone-dependent phenotype of breast cancer

BACKGROUND

Abnormal DNA methylation is observed as an early event in breast carcinogenesis. However, how such alterations arise is still poorly understood. microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and play key roles in various biological processes. Here, we integrate miRNA expression and DNA methylation at CpGs to study how miRNAs may affect the breast cancer methylome and how DNA methylation may regulate miRNA expression.

METHODS

miRNA expression and DNA methylation data from two breast cancer cohorts, Oslo2 (n = 297) and The Cancer Genome Atlas (n = 439), were integrated through a correlation approach that we term miRNA-methylation Quantitative Trait Loci (mimQTL) analysis. Hierarchical clustering was used to identify clusters of miRNAs and CpGs that were further characterized through analysis of mRNA/protein expression, clinicopathological features, in silico deconvolution, chromatin state and accessibility, transcription factor binding, and long-range interaction data.

RESULTS

Clustering of the significant mimQTLs identified distinct groups of miRNAs and CpGs that reflect important biological processes associated with breast cancer pathogenesis. Notably, two major miRNA clusters were related to immune or fibroblast infiltration, hence identifying miRNAs associated with cells of the tumor microenvironment, while another large cluster was related to estrogen receptor (ER) signaling. Studying the chromatin landscape surrounding CpGs associated with the estrogen signaling cluster, we found that miRNAs from this cluster are likely to be regulated through DNA methylation of enhancers bound by FOXA1, GATA2, and ER-alpha. Further, at the hub of the estrogen cluster, we identified hsa-miR-29c-5p as negatively correlated with the mRNA and protein expression of DNA methyltransferase DNMT3A, a key enzyme regulating DNA methylation. We found deregulation of hsa-miR-29c-5p already present in pre-invasive breast lesions and postulate that hsa-miR-29c-5p may trigger early event abnormal DNA methylation in ER-positive breast cancer.

CONCLUSIONS

We describe how miRNA expression and DNA methylation interact and associate with distinct breast cancer phenotypes.

Multi-modal meta-analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor

Molecular and functional profiling of cancer cell lines is subject to laboratory-specific experimental practices and data analysis protocols. The current challenge therefore is how to make an integrated use of the omics profiles of cancer cell lines for reliable biological discoveries. Here, we carried out a systematic analysis of nine types of data modalities using meta-analysis of 53 omics studies across 12 research laboratories for 2,018 cell lines. To account for a relatively low consistency observed for certain data modalities, we developed a robust data integration approach that identifies reproducible signals shared among multiple data modalities and studies. We demonstrated the power of the integrative analyses by identifying a novel driver gene, ECHDC1, with tumor suppressive role validated both in breast cancer cells and patient tumors. The multi-modal meta-analysis approach also identified synthetic lethal partners of cancer drivers, including a co-dependency of PTEN deficient endometrial cancer cells on RNA helicases.

Epigenome-wide gene-age interaction analysis reveals reversed effects of PRODH DNA methylation on survival between young and elderly early-stage NSCLC patients

DNA methylation changes during aging, but it remains unclear whether the effect of DNA methylation on lung cancer survival varies with age. Such an effect could decrease prediction accuracy and treatment efficacy. We performed a methylation–age interaction analysis using 1,230 early-stage lung adenocarcinoma patients from five cohorts. A Cox proportional hazards model was used to investigate lung adenocarcinoma and squamous cell carcinoma patients for methylation–age interactions, which were further confirmed in a validation phase. We identified one adenocarcinoma-specific CpG probe, cg14326354_PRODH, with effects significantly modified by age (HR_interaction = 0.989; 95% CI: 0.986–0.994; P = 9.18×10–7). The effect of low methylation was reversed for young and elderly patients categorized by the boundary of 95% CI standard (HR_young = 2.44; 95% CI: 1.26–4.72; P = 8.34×10-3; HR_elderly = 0.58; 95% CI: 0.42–0.82; P = 1.67×10-3). Moreover, there was an antagonistic interaction between low cg14326354_PRODH methylation and elderly age (HR_interaction = 0.21; 95% CI: 0.11–0.40; P = 2.20×10−6). In summary, low methylation of cg14326354PRODH might benefit survival of elderly lung adenocarcinoma patients, providing new insight to age-specific prediction and potential drug targeting.

Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects

Background

DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions.

Research Question

Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis?

Study Design and Methods

Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated.

Results

Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10^–17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10^–18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC_{3 year}, 0.88 [95% CI, 0.83-0.93]; and AUC_{5 year}, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively.

Interpretation

The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.

Trans-omics biomarker model improves prognostic prediction accuracy for early-stage lung adenocarcinoma

Limited studies have focused on developing prognostic models with trans-omics biomarkers for early-stage lung adenocarcinoma (LUAD). We performed integrative analysis of clinical information, DNA methylation, and gene expression data using 825 early-stage LUAD patients from 5 cohorts. Ranger algorithm was used to screen prognosis-associated biomarkers, which were confirmed with a validation phase. Clinical and biomarker information was fused using an iCluster plus algorithm, which significantly distinguished patients into high- and low-mortality risk groups (Pdiscovery = 0.01 and Pvalidation = 2.71×10-3). Further, potential functional DNA methylation-gene expression-overall survival pathways were evaluated by causal mediation analysis. The effect of DNA methylation level on LUAD survival was significantly mediated through gene expression level. By adding DNA methylation and gene expression biomarkers to a model of only clinical data, the AUCs of the trans-omics model improved by 18.3% (to 87.2%) and 16.4% (to 85.3%) in discovery and validation phases, respectively. Further, concordance index of the nomogram was 0.81 and 0.77 in discovery and validation phases, respectively. Based on systematic review of published literatures, our model was superior to all existing models for early-stage LUAD. In summary, our trans-omics model may help physicians accurately identify patients with high mortality risk.

Toward Personalized Computer Simulation of Breast Cancer Treatment: A Multiscale Pharmacokinetic and Pharmacodynamic Model Informed by Multitype Patient Data

The usefulness of mechanistic models to disentangle complex multiscale cancer processes, such as treatment response, has been widely acknowledged. However, a major barrier for multiscale models to predict treatment outcomes in individual patients lies in their initialization and parametrization, which needs to reflect individual cancer characteristics accurately. In this study, we use multitype measurements acquired routinely on a single breast tumor, including histopathology, MRI, and molecular profiling, to personalize parts of a complex multiscale model of breast cancer treated with chemotherapeutic and antiangiogenic agents. The model accounts for drug pharmacokinetics and pharmacodynamics. We developed an open-source computer program that simulates cross-sections of tumors under 12-week therapy regimens and used it to individually reproduce and elucidate treatment outcomes of 4 patients. Two of the tumors did not respond to therapy, and model simulations were used to suggest alternative regimens with improved outcomes dependent on the tumor's individual characteristics. It was determined that more frequent and lower doses of chemotherapy reduce tumor burden in a low proliferative tumor while lower doses of antiangiogenic agents improve drug penetration in a poorly perfused tumor. Furthermore, using this model, we were able to correctly predict the outcome in another patient after 12 weeks of treatment. In summary, our model bridges multitype clinical data to shed light on individual treatment outcomes. SIGNIFICANCE: Mathematical modeling is used to validate possible mechanisms of tumor growth, resistance, and treatment outcome.

SIPA1L3 methylation modifies the benefit of smoking cessation on lung adenocarcinoma survival: an epigenomic-smoking interaction analysis

Smoking cessation prolongs survival and decreases mortality of patients with non‐small‐cell lung cancer (NSCLC). In addition, epigenetic alterations of some genes are associated with survival. However, potential interactions between smoking cessation and epigenetics have not been assessed. Here, we conducted an epigenome‐wide interaction analysis between DNA methylation and smoking cessation on NSCLC survival. We used a two‐stage study design to identify DNA methylation–smoking cessation interactions that affect overall survival for early‐stage NSCLC. The discovery phase contained NSCLC patients from Harvard, Spain, Norway, and Sweden. A histology‐stratified Cox proportional hazards model adjusted for age, sex, clinical stage, and study center was used to test DNA methylation–smoking cessation interaction terms. Interactions with false discovery rate‐q ≤ 0.05 were further confirmed in a validation phase using The Cancer Genome Atlas database. Histology‐specific interactions were identified by stratification analysis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. We identified one CpG probe (cg02268510_SIPA1L3) that significantly and exclusively modified the effect of smoking cessation on survival in LUAD patients [hazard ratio (HR)_interaction = 1.12; 95% confidence interval (CI): 1.07–1.16; P = 4.30 × 10^–7]. Further, the effect of smoking cessation on early‐stage LUAD survival varied across patients with different methylation levels of cg02268510_SIPA1L3. Smoking cessation only benefited LUAD patients with low methylation (HR = 0.53; 95% CI: 0.34–0.82; P = 4.61 × 10^–3) rather than medium or high methylation (HR = 1.21; 95% CI: 0.86–1.70; P = 0.266) of cg02268510_SIPA1L3. Moreover, there was an antagonistic interaction between elevated methylation of cg02268510_SIPA1L3 and smoking cessation (HR_interaction = 2.1835; 95% CI: 1.27–3.74; P = 4.46 × 10⁻³). In summary, smoking cessation benefited survival of LUAD patients with low methylation at cg02268510_SIPA1L3. The results have implications for not only smoking cessation after diagnosis, but also possible methylation‐specific drug targeting.

Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation

Global loss of DNA methylation and CpG island (CGI) hypermethylation are key epigenomic aberrations in cancer. Global loss manifests itself in partially methylated domains (PMDs) which extend up to megabases. However, the distribution of PMDs within and between tumor types, and their effects on key functional genomic elements including CGIs are poorly defined. We comprehensively show that loss of methylation in PMDs occurs in a large fraction of the genome and represents the prime source of DNA methylation variation. PMDs are hypervariable in methylation level, size and distribution, and display elevated mutation rates. They impose intermediate DNA methylation levels incognizant of functional genomic elements including CGIs, underpinning a CGI methylator phenotype (CIMP). Repression effects on tumor suppressor genes are negligible as they are generally excluded from PMDs. The genomic distribution of PMDs reports tissue-of-origin and may represent tissue-specific silent regions which tolerate instability at the epigenetic, transcriptomic and genetic level.

EGLN2 DNA methylation and expression interact with HIF1A to affect survival of early-stage NSCLC

Hypoxia occurs frequently in human cancers and promotes stabilization and activation of hypoxia inducible factor (HIF). HIF-1α is specific for the hypoxia response, and its degradation mediated by three enzymes EGLN1, EGLN2 and EGLN3. Although EGLNs expression has been found to be related to prognosis of many cancers, few studies examined DNA methylation in EGLNs and its relationship to prognosis of early-stage non-small cell lung cancer (NSCLC). We analyzed EGLNs DNA methylation data from tumor tissue samples of 1,230 early-stage NSCLC patients, as well as gene expression data from The Cancer Genome Atlas. The sliding windows sequential forward feature selection method and weighted random forest were used to screen out the candidate CpG probes in lung adenocarcinomas (LUAD) and lung squamous cell carcinomas patients, respectively, in both discovery and validation phases. Then Cox regression was performed to evaluate the association between DNA methylation and overall survival. Among the 34 CpG probes in EGLNs, DNA methylation at cg25923056EGLN2 was identified to be significantly associated with LUAD survival (HR = 1.02, 95% CI: 1.01-1.03, P = 9.90 × 10-5), and correlated with EGLN2 expression (r = - 0.36, P = 1.52 × 10-11). Meanwhile, EGLN2 expression was negatively correlated with HIF1A expression in tumor tissues (r = - 0.30, P = 4.78 × 10-8) and significantly (P = 0.037) interacted with HIF1A expression on overall survival. Therefore, DNA methylation of EGLN2- HIF1A is a potential marker for LUAD prognosis and these genes are potential treatment targets for further development of HIF-1α inhibitors in lung cancer therapy.

Time series analysis of neoadjuvant chemotherapy and bevacizumab-treated breast carcinomas reveals a systemic shift in genomic aberrations

Background

Chemotherapeutic agents such as anthracyclines and taxanes are commonly used in the neoadjuvant setting. Bevacizumab is an antibody which binds to vascular endothelial growth factor A (VEGFA) and inhibits its receptor interaction, thus obstructing the formation of new blood vessels.

Methods

A phase II randomized clinical trial of 123 patients with Her2-negative breast cancer was conducted, with patients treated with neoadjuvant chemotherapy (fluorouracil (5FU)/epirubicin/cyclophosphamide (FEC) and taxane), with or without bevacizumab. Serial biopsies were obtained at time of diagnosis, after 12 weeks of treatment with FEC ± bevacizumab, and after 25 weeks of treatment with taxane ± bevacizumab. A time course study was designed to investigate the genomic landscape at the three time points when tumor DNA alterations, tumor percentage, genomic instability, and tumor clonality were assessed. Substantial differences were observed with some tumors changing mainly between diagnosis and at 12 weeks, others between 12 and 25 weeks, and still others changing in both time periods.

Results

In both treatment arms, good responders (GR) and non-responders (NR) displayed significant difference in genomic instability index (GII) at time of diagnosis. In the combination arm, copy number alterations at 25 loci at the time of diagnosis were significantly different between the GR and NR. An inverse aberration pattern was also observed between the two extreme response groups at 6p22-p12 for patients in the combination arm. Signs of subclonal reduction were observed, with some aberrations disappearing and others being retained during treatment. Increase in subclonal amplification was observed at 6p21.1, a locus which contains the VEGFA gene for the protein which are targeted by the study drug bevacizumab. Of the 13 pre-treatment samples that had a gain at VEGFA, 12 were responders. Significant decrease of frequency of subclones carrying gains at 17q21.32-q22 was observed at 12 weeks, with the peak occurring at TMEM100, an ALK1 receptor signaling-dependent gene essential for vasculogenesis. This implies that cells bearing amplifications of VEGFA and TMEM100 are particularly sensitive to this treatment regime.

Conclusions

Taken together, these results suggest that heterogeneity and subclonal architecture influence the response to targeted treatment in combination with chemotherapy, with possible implications for clinical decision-making and monitoring of treatment efficacy.

Trial registration

NCT00773695. Registered 15 October 2008

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0601-y) contains supplementary material, which is available to authorized users.

DNA Methylation of LRRC3B: A Biomarker for Survival of Early-Stage Non-Small Cell Lung Cancer Patients

BACKGROUND

Previous studies support a tumor-suppressor role for LRRC3B across various types of cancers. We aimed to investigate the association between DNA methylation of LRRC3B and overall survival (OS) for patients with early-stage non-small cell lung cancer (NSCLC).

METHODS

This study included 1,230 patients with early-stage NSCLC. DNA was extracted from lung tumor tissues and DNA methylation was measured using Illumina Infinium HumanMethylation450 BeadChips. The association between DNA methylation and OS was first tested using Cox regression on a discovery cohort and then validated in an independent cohort. Next, the association between DNA methylation and gene expression was investigated in two independent cohorts. Finally, the association between gene expression and OS was investigated in three independent groups of patients.

RESULTS

Three novel DNA methylation sites in LRRC3B were significantly associated with OS in two groups of patients. Patients with hypermethylation in the DNA methylation sites had significantly longer survival than the others in both the discovery cohort (HR, 0.62; P = 2.02 × 10^-05) and validation cohort (HR, 0.55; P = 4.44 × 10^-04). The three DNA methylation sites were significantly associated with LRRC3B expression, which was also associated with OS.

CONCLUSIONS

Using clinical data from a large population, we illustrated the association between DNA methylation of LRRC3B and OS of early-stage NSCLC.

IMPACT

We provide evidence of plausibility for building biomarkers on DNA methylation of LRRC3B for OS of early-stage NSCLC, thus filling a gap between previous in vitro studies and clinical applications.

Serum cytokine levels in breast cancer patients during neoadjuvant treatment with bevacizumab

A high concentration of circulating vascular endothelial growth factor (VEGF) in cancer patients is associated with an aggressive tumor phenotype. Here, serum levels of 27 cytokines and blood cell counts were assessed in breast cancer patients receiving neoadjuvant chemotherapy with or without bevacizumab (Bev) in a randomized cohort of 132 patients with non-metastatic HER2-negative tumors. Cytokine levels were determined prior to treatment and at various time-points. The cytotoxic chemotherapy regimen of fluorouracil, epirubicin, and cyclophosphamide (FEC) had a profound impact on both circulating white blood cells and circulating cytokine levels. At the end of FEC treatment, the global decrease in cytokine levels correlated with the drop in white blood cell counts and was significantly greater in the patients of the Bev arm for cytokines, such as VEGF-A, IL-12, IP-10 and IL-10. Among patients who received Bev, those with pathological complete response (pCR) exhibited significantly lower levels of VEGF-A, IFN-γ, TNF-α and IL-4 than patients without pCR. This effect was not observed in the chemotherapy-only arm. Certain circulating cytokine profiles were found to correlate with different immune cell types at the tumor site. For the Bev arm patients, the serum cytokine levels correlated with higher levels of cytotoxic T cells at the end of the therapy regimen, which was indicative of treatment response. The higher response rate for Bev-treated patients and stronger correlations between serum cytokine levels and infiltrating CD8T cells merits further investigation.

A multi-omic study reveals BTG2 as a reliable prognostic marker for early-stage non-small cell lung cancer

B-cell translocation gene 2 (BTG2) is a tumour suppressor protein known to be downregulated in several types of cancer. In this study, we investigated a potential role for BTG2 in early-stage non-small cell lung cancer (NSCLC) survival. We analysed BTG2 methylation data from 1230 early-stage NSCLC patients from five international cohorts, as well as gene expression data from 3038 lung cancer cases from multiple cohorts. Three CpG probes (cg01798157, cg06373167, cg23371584) that detected BTG2 hypermethylation in tumour tissues were associated with lower overall survival. The prognostic model based on methylation could distinguish patient survival in the four cohorts [hazard ratio (HR) range, 1.51-2.21] and the independent validation set (HR = 1.85). In the expression analysis, BTG2 expression was positively correlated with survival in each cohort (HR range, 0.28-0.68), which we confirmed with meta-analysis (HR = 0.61, 95% CI 0.54-0.68). The three CpG probes were all negatively correlated with BTG2 expression. Importantly, an integrative model of BTG2 methylation, expression and clinical information showed better predictive ability in the training set and validation set. In conclusion, the methylation and integrated prognostic signatures based on BTG2 are stable and reliable biomarkers for early-stage NSCLC. They may have new applications for appropriate clinical adjuvant trials and personalized treatments in the future.

Epigenetic modifications in KDM lysine demethylases associate with survival of early-stage NSCLC

Background

KDM lysine demethylase family members are related to lung cancer clinical outcomes and are potential biomarkers for chemotherapeutics. However, little is known about epigenetic alterations in KDM genes and their roles in lung cancer survival.

Methods

Tumor tissue samples of 1230 early-stage non-small cell lung cancer (NSCLC) patients were collected from the five independent cohorts. The 393 methylation sites in KDM genes were extracted from epigenome-wide datasets and analyzed by weighted random forest (Ranger) in discovery phase and validation dataset, respectively. The variable importance scores (VIS) for the sites in top 5% of both discovery and validation sets were carried forward for Cox regression to further evaluate the association with patient’s overall survival. TCGA transcriptomic data were used to evaluate the correlation with the corresponding DNA methylation.

Results

DNA methylation at sites cg11637544 in KDM2A and cg26662347 in KDM1A were in the top 5% of VIS in both discovery phase and validation for squamous cell carcinomas (SCC), which were also significantly associated with SCC survival (HR_cg11637544 = 1.32, 95%CI, 1.16–1.50, P = 1.1 × 10⁻⁴; HR_cg26662347 = 1.88, 95%CI, 1.37–2.60, P = 3.7 × 10⁻³), and correlated with corresponding gene expression (cg11637544 for KDM2A, P = 1.3 × 10⁻¹⁰; cg26662347 for KDM1A P = 1.5 × 10⁻⁵). In addition, by using flexible criteria for Ranger analysis followed by survival classification tree analysis, we identified four clusters for adenocarcinomas and five clusters for squamous cell carcinomas which showed a considerable difference of clinical outcomes with statistical significance.

Conclusions

These findings highlight the association between somatic DNA methylation in KDM genes and early-stage NSCLC patient survival, which may reveal potential epigenetic therapeutic targets.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0474-3) contains supplementary material, which is available to authorized users.

Abstract LB-097: DNA methylation at enhancers distinguishes distinct breast cancer lineages

Breast cancers exhibit genome-wide aberrant DNA methylation patterns. To investigate how these affect the transcriptome and which changes are linked to transformation or progression we applied genome-wide expression-methylation quantitative trait loci (emQTL) analysis between 5meCpG and gene expression. We find that on a whole genome scale, DNA methylation and gene expression have remarkably and reproducibly conserved patterns of association, both in cis and in trans, which lead to identify distinct transcriptional networks and specific disease cell lineages deviating from the normal tissue. In three breast cancer cohorts (n=104, n=253 and n=330), we invariably identify enhancers whose DNA methylation tethers the binding of three key transcription factors in breast cancer in a lineage specific manner. Our emQTL analysis also identifies tumor infiltrating immune cell signatures. Using ChromHMM segmentation and ChIP-seq associated TF binding regions, we identify enhancers and TF binding sites around emQTLs-CpGs. We functionally validate the genes associated with these CpGs using knock-down by siRNA and applying GRO-seq analysis after transcriptional stimulation with estrogen. DNA methylation at TF binding regions is considered an early event during normal breast cell transformation into estrogen dependent breast cancer. Two distinct key gene regulatory networks reported here are prominently altered by DNA methylation.

Citation Format: Thomas Fleischer, Xavier Tekpli, Anthony Mathelier, Shixiong Wang, Daniel Nebdal, Hari P. Dhakal, Kristine Kleivi Sandberg, Ellen Schliting, Oslo Breast Cancer Research Consortium (OSBREAC), Anne-Lise Børresen-Dale, Elin Borgen, Bjørn Naume, Ragnhild Eskeland, Arnoldo Frigessi, Jörg Tost, Antoni Hurtado, Vessela N. Kristensen. DNA methylation at enhancers distinguishes distinct breast cancer lineages [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-097. doi:10.1158/1538-7445.AM2017-LB-097

The Longitudinal Transcriptional Response to Neoadjuvant Chemotherapy with and without Bevacizumab in Breast Cancer

Purpose: Chemotherapy-induced alterations to gene expression are due to transcriptional reprogramming of tumor cells or subclonal adaptations to treatment. The effect on whole-transcriptome mRNA expression was investigated in a randomized phase II clinical trial to assess the effect of neoadjuvant chemotherapy with the addition of bevacizumab.Experimental Design: Tumor biopsies and whole-transcriptome mRNA profiles were obtained at three fixed time points with 66 patients in each arm. Altogether, 358 specimens from 132 patients were available, representing the transcriptional state before treatment start, at 12 weeks and after treatment (25 weeks). Pathologic complete response (pCR) in breast and axillary nodes was the primary endpoint.Results: pCR was observed in 15 patients (23%) receiving bevacizumab and chemotherapy and 8 patients (12%) receiving only chemotherapy. In the estrogen receptor-positive patients, 11 of 54 (20%) treated with bevacizumab and chemotherapy achieved pCR, while only 3 of 57 (5%) treated with chemotherapy reached pCR. In patients with estrogen receptor-positive tumors treated with combination therapy, an elevated immune activity was associated with good response. Proliferation was reduced after treatment in both treatment arms and most pronounced in the combination therapy arm, where the reduction in proliferation accelerated during treatment. Transcriptional alterations during therapy were subtype specific, and the effect of adding bevacizumab was most evident for luminal-B tumors.Conclusions: Clinical response and gene expression response differed between patients receiving combination therapy and chemotherapy alone. The results may guide identification of patients likely to benefit from antiangiogenic therapy. Clin Cancer Res; 23(16); 4662-70. ©2017 AACR.

DNA methylation signature (SAM40) identifies subgroups of the Luminal A breast cancer samples with distinct survival

Breast cancer patients with Luminal A disease generally have a good prognosis, but among this patient group are patients with good prognosis that are currently overtreated with adjuvant chemotherapy, and also patients that have a bad prognosis and should be given more aggressive treatment. There is no available method for subclassification of this patient group. Here we present a DNA methylation signature (SAM40) that segregates Luminal A patients based on prognosis, and identify one good prognosis group and one bad prognosis group. The prognostic impact of SAM40 was validated in four independent patient cohorts. Being able to subdivide the Luminal A patients may give the two-sided benefit of identifying one subgroup that may benefit from a more aggressive treatment than what is given today, and importantly, identifying a subgroup that may benefit from less treatment.

Abstract LB-337: Systemic shift in genomic aberrations in breast carcinomas during neoadjuvant chemotherapy in combination with bevacizumab

A time course study was designed to investigate the dynamics of copy number aberrations in tumor DNA during treatment of breast cancer patients. A phase II randomized clinical trial of Her2 negative breast cancer patients was conducted, with patients being treated with neoadjuvant chemotherapy (FEC and taxane), with or without bevacizumab. Serial biopsies were obtained at time of diagnosis, at 12 weeks after treatment with FEC +/- bevacizumab, and at 25 weeks after treatment with taxane +/- bevacizumab. Tumor DNA alterations and tumor percentage were studied over time, and substantial differences were observed with some tumors changing mainly between diagnosis and 12 weeks (after the FEC cycle), others between 12 and 25 weeks (taxanes), and still others changing in both time periods. In both treatment arms, good responders (GR) and non-responders (NR) displayed significant difference in genomic instability index (GII) at time of diagnosis. In the Combination arm at time of diagnosis, 25 loci harbored copy number alterations, which were significantly different between the GR and NR. An inverse aberration pattern was observed between the two extreme response groups at 6p22-p12 for patients in the Combination arm. In most cases, tumors that retained aberrations at all time points did not decrease in size. Signs of subclonal reduction were observed, with some aberrations disappearing and others being retained during treatment. In both treatment arms an increase in subclonal amplification was observed at 6p21.1, the locus which contains the VEGFA gene targeted by bevacizumab and was associated with good response. Significant decrease of frequency of subclones carrying gains at 17q21.32-q22 was observed at 12 week, with the peak occurring at TMEM100, an ALK1 receptor signaling-dependent gene essential for vasculogenesis. This implies that cells bearing amplifications of TMEM100 are particularly sensitive to the treatment regime. Taken together, these results suggest that heterogeneity and subclonal architecture influence the response to targeted treatment in combination with chemotherapy, with possible implications for clinical decision making and monitoring of treatment efficacy.

Citation Format: Elen K. Møller, Silje Nord, David Wedge, Ole Christian Lngjærde, Laxmi Silwal-Pandit, Hedda vdL Gythfeld, Hans Kristian M. Vollan, Thomas Fleischer, Marit Krohn, Ellen Schlichting, Elin Borgen, Øystein Garred, Marit M. Holmen, Erik Wist, Bjørn Naume, Peter V. Loo, Anne-Lise Børresen-Dale, Olav Engebråten, Vessela Kristensen. Systemic shift in genomic aberrations in breast carcinomas during neoadjuvant chemotherapy in combination with bevacizumab. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-337.

Genome-wide DNA methylation analyses in lung adenocarcinomas: Association with EGFR, KRAS and TP53 mutation status, gene expression and prognosis

BACKGROUND

DNA methylation alterations are early events in tumorigenesis and important in the regulation of gene expression in cancer cells. Lung cancer patients have in general a poor prognosis, and a deeper insight into the epigenetic landscape in lung adenocarcinoma tumors and its prognostic implications is needed.

RESULTS

We determined whole-genome DNA methylation profiles of 164 fresh frozen lung adenocarcinoma samples and 19 samples of matched normal lung tissue using the Illumina Infinium 450K array. A large number of differentially methylated CpGs in lung adenocarcinoma tissue were identified, and specific methylation profiles were observed in tumors with mutations in the EGFR-, KRAS- or TP53 genes and according to the patients' smoking status. The methylation levels were correlated with gene expression and both positive and negative correlations were seen. Methylation profiles of the tumor samples identified subtypes of tumors with distinct prognosis, including one subtype enriched for TP53 mutant tumors. A prognostic index based on the methylation levels of 33 CpGs was established, and was significantly associated with prognosis in the univariate analysis using an independent cohort of lung adenocarcinoma patients from The Cancer Genome Atlas project. CpGs in the HOX B and HOX C gene clusters were represented in the prognostic signature.

CONCLUSIONS

Methylation differences mirror biologically important features in the etiology of lung adenocarcinomas and influence prognosis.

Aberrant DNA methylation impacts gene expression and prognosis in breast cancer subtypes

DNA methylation has a substantial impact on gene expression, affecting the prognosis of breast cancer (BC) patients dependent on molecular subtypes. In this study, we investigated the prognostic relevance of the expression of genes reported as aberrantly methylated, and the link between gene expression and DNA methylation in BC subtypes. The prognostic value of the expression of 144 aberrantly methylated genes was evaluated in ER+/HER2-, HER2+, and ER-/HER2- molecular BC subtypes, in a meta-analysis of two large transcriptomic cohorts of BC patients (n = 1,938 and n = 1,640). The correlation between gene expression and DNA methylation in distinct gene regions was also investigated in an independent dataset of 104 BCs. Survival and Pearson correlation analyses were computed for each gene separately. The expression of 48 genes was significantly associated with BC prognosis (p < 0.05), and 32 of these prognostic genes exhibited a direct expression-methylation correlation. The expression of several immune-related genes, including CD3D and HLA-A, was associated with both relapse-free survival (HR = 0.42, p = 3.5E-06; HR = 0.35, p = 1.7E-08) and overall survival (HR = 0.50, p = 5.5E-04; HR = 0.68, p = 4.5E-02) in ER-/HER2- BCs. On the overall, the distribution of both positive and negative expression-methylation correlation in distinct gene regions have different effects on gene expression and prognosis in BC subtypes. This large-scale meta-analysis allowed the identification of several genes consistently associated with prognosis, whose DNA methylation could represent a promising biomarker for prognostication and clinical stratification of patients with distinct BC subtypes.

DNA methylation in ductal carcinoma in situ related with future development of invasive breast cancer

Background

Ductal carcinoma in situ (DCIS) is a heterogeneous, pre-invasive lesion associated with an increased risk for future invasive ductal carcinoma. However, accurate risk stratification for development of invasive disease and appropriate treatment decisions remain clinical challenges. DNA methylation alterations are early events in the progression of cancer and represent emerging molecular markers that may predict invasive recurrence more accurately than traditional measures of DCIS prognosis.

Results

We measured DNA methylation using the Illumina HumanMethylation450K array of estrogen-receptor positive DCIS (n = 40) and adjacent-normal (n = 15) tissues from subjects in the New Hampshire Mammography Network longitudinal breast imaging registry. We identified locus-specific methylation differences between DCIS and matched adjacent-normal tissue (95,609 CpGs, Q < 0.05). Among 40 DCIS cases, 13 later developed invasive disease and we identified 641 CpG sites that exhibited differential DNA methylation (P < 0.01 and median |∆β| > 0.1) in these cases compared with age-matched subjects without invasive disease. The set of differentially methylated CpG loci associated with disease progression was enriched in homeobox-containing genes (P = 1.3E-09) and genes involved with limb morphogenesis (P = 1.0E-05). In an independent cohort, a subset of genes with progression-related differential methylation between DCIS and invasive breast cancer were confirmed. Further, the functional relevance of these genes’ regulation by methylation was demonstrated in early stage breast cancers from The Cancer Genome Atlas database.

Conclusions

This work contributes to the understanding of epigenetic alterations that occur in DCIS and illustrates the potential of DNA methylation as markers of DCIS progression.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-015-0094-0) contains supplementary material, which is available to authorized users.

Abstract P4-11-14: Molecular response in breast cancer treated with neoadjuvant chemotherapy with and without bevacizumab: Results from NeoAva - a randomized phase II study

The NeoAva study is a phase II clinical trial of patients with HER2 negative primary tumors of ≥25 mm treated with neoadjuvant chemotherapy (4 x FEC100 + 12 weeks of taxane-based therapy) and randomized (1:1) to receive bevacizumab or no bevacizumab. Mammography, ultrasound and MR imaging were used for response evaluation, in addition to final pathology assessment.

Tumor response were evaluable in 131 patients; of which 66 received bevacizumab in addition to chemotherapy. Tumor material was obtained at screening, 12 weeks into treatment and at surgical removal of tumors at 25 weeks. mRNA expression profiling was performed on Agilent 8x60K platform and the tumors were classified into LuminalA, LuminalB, Her2-enriched, Basal and Normal-like subtypes using the PAM50 classifier. Ratio of the tumor size at final pathology assessment, and at inclusion (by radiology assessment) was calculated to obtain a continuous scale of response reflecting the percentage of tumor shrinkage in response to therapy. Genomic Grade Index (GGI scores) based on expression profiles of 97 genes (including cell-cycle and proliferation genes) were calculated.

There were no significant differences in the tumor size, lymph node, hormone receptor status or PAM50 subtypes between the treatment arms. pCR in breast and axilla were obtained in 14 (21.1%) patients in the chemo+bev arm, and in 7 (10.6%) patients in the chemo-only arm. Tumors that obtained pCR were in higher number ER negative and TP53 mutated and exhibited Basal-like phenotype. The overall pCR rates were higher in the ER negative tumors compared to ER positive tumors {39.1% (9 of 23) vs 11.1% (12 of 108)}. However, addition of bevacizumab seemed to improve pCR in the ER positive patient group (9 vs 3) and not in ER negative patient group (5 vs 4).

On evaluating the continuous response variable, ER status, TP53 mutation status and PAM50 subtypes were significantly associated to response (p &lt; 0.001). GGI scores were highly correlated to response (p&lt; 0.001), i. e tumors with higher GGI scores showed better response. Importantly, when the chemo+bev and the chemo-only arms were evaluated separately, although similar trend of associations was observed in both arms, the associations were found to be enhanced in the chemo+bev arm.

Next, we evaluated a shift in PAM50 subtypes across the timepoints. A shift towards a better prognosis group, i.e Luminal A or Normal-like profile was observed in response to therapy. Distribution of Luminal A and Normal-like tumors at week 25, (and not at screening or week 12) was significantly different in the chemo+bev vs chemo-only group (p = 0.026, Fisher’s exact test).

GGI scores regressed across timepoints reflecting the loss of aggressive and proliferating component of the tumors in response to therapy. GGI scores in the chemo+bev group became significantly lower (p &lt; 0.01) already at week 12. This suggests that the removal of the proliferating component of the tumors by chemotherapy is accelerated and improved by addition of bevacizumab.

These results, with potentially important clinical relevance will be further investigated with respect to subtypes and the molecular changes induced by antiangiogenic therapy.

Citation Format: Olav Engebraaten, Laxmi Silwal-Pandit, Marit Krohn, Elen K Møller, Silje Nord, Thomas Fleischer, Hedda von der Lippe Gythfelt, Elin Borgen, Øystein Garred, Anne Fangberget, Marit Muri Holmen, Ellen Schlichting, Helle Skjerven, Steinar Lundgren, Vessela N Kristensen, Ole Christian Lingjaerde, Erik Wist, Bjørn Naume, Anne-Lise Børresen-Dale. Molecular response in breast cancer treated with neoadjuvant chemotherapy with and without bevacizumab: Results from NeoAva - a randomized phase II study [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-14.

DNA methylation status of key cell-cycle regulators such as CDKNA2/p16 and CCNA1 correlates with treatment response to doxorubicin and 5-fluorouracil in locally advanced breast tumors

PURPOSE

To explore alterations in gene promoter methylation as a potential cause of acquired drug resistance to doxorubicin or combined treatment with 5-fluorouracil and mitomycin C in human breast cancers.

EXPERIMENTAL DESIGN

Paired tumor samples from locally advanced breast cancer patients treated with doxorubicin and 5-fluorouracil-mitomycin C were used in the genome-wide DNA methylation analysis as discovery cohort. An enlarged cohort from the same two prospective studies as those in the discovery cohort was used as a validation set in pyrosequencing analysis.

RESULTS

A total of 469 genes were differentially methylated after treatment with doxorubicin and revealed a significant association with canonical pathways enriched for immune cell response and cell-cycle regulating genes including CDKN2A, CCND2, CCNA1, which were also associated to treatment response. Treatment with FUMI resulted in 343 differentially methylated genes representing canonical pathways such as retinoate biosynthesis, gαi signaling, and LXR/RXR activation. Despite the clearly different genes and pathways involved in the metabolism and therapeutic effect of both drugs, 46 genes were differentially methylated before and after treatment with both doxorubicin and FUMI. DNA methylation profiles in genes such as BRCA1, FOXC1, and IGFBP3, and most notably repetitive elements like ALU and LINE1, were associated with TP53 mutations status.

CONCLUSION

We identified and validated key cell-cycle regulators differentially methylated before and after neoadjuvant chemotherapy such as CDKN2A and CCNA1 and reported that methylation patterns of these genes may be potential predictive markers to anthracycline/mitomycine sensitivity.

Genome-wide DNA methylation profiles in progression to in situ and invasive carcinoma of the breast with impact on gene transcription and prognosis

BACKGROUND

Ductal carcinoma in situ (DCIS) of the breast is a precursor of invasive breast carcinoma. DNA methylation alterations are thought to be an early event in progression of cancer, and may prove valuable as a tool in clinical decision making and for understanding neoplastic development.

RESULTS

We generate genome-wide DNA methylation profiles of 285 breast tissue samples representing progression of cancer, and validate methylation changes between normal and DCIS in an independent dataset of 15 normal and 40 DCIS samples. We also validate a prognostic signature on 583 breast cancer samples from The Cancer Genome Atlas. Our analysis reveals that DNA methylation profiles of DCIS are radically altered compared to normal breast tissue, involving more than 5,000 genes. Changes between DCIS and invasive breast carcinoma involve around 1,000 genes. In tumors, DNA methylation is associated with gene expression of almost 3,000 genes, including both negative and positive correlations. A prognostic signature based on methylation level of 18 CpGs is associated with survival of breast cancer patients with invasive tumors, as well as with survival of patients with DCIS and mixed lesions of DCIS and invasive breast carcinoma.

CONCLUSIONS

This work demonstrates that changes in the epigenome occur early in the neoplastic progression, provides evidence for the possible utilization of DNA methylation-based markers of progression in the clinic, and highlights the importance of epigenetic changes in carcinogenesis.

Genome-wide DNA methylation profiles in progression to in situ and invasive carcinoma of the breast with impact on gene transcription and prognosis

BACKGROUND

Ductal carcinoma in situ (DCIS) of the breast is a precursor of invasive breast carcinoma. DNA methylation alterations are thought to be an early event in progression of cancer, and may prove valuable as a tool in clinical decision making and for understanding neoplastic development.

RESULTS

We generate genome-wide DNA methylation profiles of 285 breast tissue samples representing progression of cancer, and validate methylation changes between normal and DCIS in an independent dataset of 15 normal and 40 DCIS samples. We also validate a prognostic signature on 583 breast cancer samples from The Cancer Genome Atlas. Our analysis reveals that DNA methylation profiles of DCIS are radically altered compared to normal breast tissue, involving more than 5,000 genes. Changes between DCIS and invasive breast carcinoma involve around 1,000 genes. In tumors, DNA methylation is associated with gene expression of almost 3,000 genes, including both negative and positive correlations. A prognostic signature based on methylation level of 18 CpGs is associated with survival of breast cancer patients with invasive tumors, as well as with survival of patients with DCIS and mixed lesions of DCIS and invasive breast carcinoma.

CONCLUSIONS

This work demonstrates that changes in the epigenome occur early in the neoplastic progression, provides evidence for the possible utilization of DNA methylation-based markers of progression in the clinic, and highlights the importance of epigenetic changes in carcinogenesis.

Neues über Fluoride A[CoF4] mit A = Li-Cs sowie über CsFeF4/ News on Fluorides A[CoF4] with A = Li-Cs and on CsFeF4

By fluorination of CsFeBr4 · 2 H2O we obtained a new modification of CsFeF4 (a = 12,491(1), c = 13,272(1) A, Z - 20), which according to powder data crystallizes tetragonally in the structure type of β-RbAlF4, space group I4̄c2. The same structure type is adapted by CsCoF4 (a 12,478(1), c = 12,971(1) Å, Z = 20); in contrast RbCoF4 has similar lattice constants (a = 12,222(1), c = 12,356(2) Å, Z = 20), but another unknown structure; KCoF4 (a = 7,520(1), b = 7,584(1), c = 5,792(1) Å, Z = 4) crystallizes orthorhombic by isotypic to RbFeF4, and NaCoF4 (a - 4,965(1), b = 5,51(5(1), c = 10,800(2) A, Z = 4) is isotypic to NaTiF4. The first compound LiMIIIF4 (MIII = 3dmetals) is LiCoF4, which probably crystallizes monoclinicly (a = 5,540(3), 6 = 4,665(1), c = 5,447(3) Å, = 114,25(5)°, Z = 2). The colour of these cobaltates(III) is violet.

Zur Rutilverwandtschaft: Über neue Fluoride des Typs LiMIIMIIIF6 mit MIII = Co, Ni und MII = Mg, Ca, Sr, Ba, Ni, Cu, Zn, Cd [1]/On New Fluorides of the Type LiMIIMIIIF6 with MIII = Co, Ni and MII = Mg, Ca, Sr, Ba, Ni, Cu, Zn, Cd [1]

By pressure fluorination in monel autoklaves samples of LiCuCoF6 (rutile type structure), LiMgCoF6, LiNiCoF6 and LiZnCoF6 (trirutile type structure), LiCdCoF6, LiCaCoF6, LiCaNiF6 and LiSrNiF6 (LiCaAlF6-type [2] structure), LiSrCoF6 (LiSrFeF6-type structure [3]) and LiBaCoF6 (LiBaCrF6-type structure [4]) were synthesised for the first time. The Madelung Part of Lattice Energie, MAPLE, is studied and discussed. By magnetic measurements we obtained new information on the structure of fluorotrirutile.

Differential DNA methylation analysis of breast cancer reveals the impact of immune signaling in radiation therapy

Radiotherapy (RT) is a central treatment modality for breast cancer patients. The purpose of our study was to investigate the DNA methylation changes in tumors following RT, and to identify epigenetic markers predicting treatment outcome. Paired biopsies from patients with inoperable breast cancer were collected both before irradiation (n = 20) and after receiving 10-24 Gray (Gy) (n = 19). DNA methylation analysis was performed by using Illumina Infinium 27K arrays. Fourteen genes were selected for technical validation by pyrosequencing. Eighty-two differentially methylated genes were identified in irradiated (n = 11) versus nonirradiated (n = 19) samples (false discovery rate, FDR = 1.1%). Methylation levels in pathways belonging to the immune system were most altered after RT. Based on methylation levels before irradiation, a panel of five genes (H2AFY, CTSA, LTC4S, IL5RA and RB1) were significantly associated with clinical response (p = 0.041). Furthermore, the degree of methylation changes for 2,516 probes correlated with the given radiation dose. Within the 2,516 probes, an enrichment for pathways involved in cellular immune response, proliferation and apoptosis was identified (FDR < 5%). Here, we observed clear differences in methylation levels induced by radiation, some associated with response to treatment. Our study adds knowledge on the molecular mechanisms behind radiation response.

Integrated analysis of high-resolution DNA methylation profiles, gene expression, germline genotypes and clinical end points in breast cancer patients

Breast cancer is a heterogeneous disease for which alterations in DNA methylation patterns have been shown to be of biological and clinical importance. Here we report on the integrated analysis of molecular alterations including the methylation status of 27 gene promoters analyzed by highly quantitative pyrosequencing, and the association to gene expression, germline genotype and clinical parameters including survival. Breast cancer specific deregulation of DNA methylation (both hyper- and hypomethylation) was found in twenty genes including ACVR1, OGG1, IL8 and TFF1. The methylation level in the promoter regions was significantly negatively correlated to gene expression for twelve genes (such as MST1R, ST6GAL1 and TFF1) indicating that a gain of aberrant methylation (hypermethylation) inhibits gene expression. Multiple associations between molecular and clinical parameters were identified, and multivariate statistical analysis demonstrated that methylation was more strongly associated to clinical parameters than gene expression for the investigated genes. The methylation level of BCAP31 and OGG1 showed significant association to survival, and these associations were validated in a larger patient cohort (The Cancer Genome Atlas). Our study provides evidence for the promise of DNA methylation alterations for clinical applications.

Abstract P4-14-01: A time course study of genomic instability in breast cancer patients receiving neoadjuvant therapy with or without bevacizumab

Tumor heterogeneity is an area of intense research, revealing tumors with high complexity consisting of different subclones and infiltrating cells. Identification of subclones that are resistant to therapy may be critical to improve treatment outcome.

The NeoAva study is a randomized phase II, clinical trial of Her2 negative breast cancer patients treated in a neoadjuvant setting with chemotherapy (FEC and taxane) +/- bevacizumab. Core needle biopsies were obtained at screening and after 12 weeks, and the tumor was surgically removed after 25 weeks. DNA copy number changes in the tumors were analyzed using Affymetrix SNP Array 6.0. Allele specific copy number changes were assessed using the Allele-Specific Copy number Analysis of Tumors (ASCAT) algorithm (Van Loo, Norgard et al., PNAS 2010) and allele-specific Piecewise Constant Fitting (asPCF) algorithms (Nilsen, Liestol et al., BMC Genomics 2012). Measures of genomic instability were obtained through the complex arm-wise aberration index (CAAI) that captures local rearrangements (‘firestorms’) (Russnes, Vollan et al., Sci Transl Med 2010).

Changes in copy number aberrations between the three different time points were observed in almost all tumors. Some tumors showed a decrease in tumor percentage and aberrations after just 12 weeks of treatment, where others showed loss of aberrations only at the time of surgery (25 weeks). Most of the tumors that did retain aberrations at all time points during treatment, did not demonstrate any decrease in tumor size. Other profiles indicated subclonal reduction, where some aberrations are kept throughout treatment and others disappear. Many of the tumors shrinking in size showed fewer whole arm aberrations than before treatment, but retained their focal amplicons. Some of the tumor aberrations seem to disappear after 12 weeks, but to reappear after 25 weeks, but with the addition of novel aberration.

Complex rearrangements were identified in 67% of tumors before treatment. The most frequent ‘firestorms’ were found on 20p, 11q and 8p. Some events were persistent through therapy, but the majority changed. An association between complex tumor genomes and patients having progressive disease/non-responders were observed.

These results show the complex structure of a tumor and suggest that heterogeneity will influence the response to treatment. The subclonal patterns of tumors may be of great importance for clinical decision-making, as well as for monitoring treatment efficacy.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-14-01.

Abstract P4-14-02: Molecular response in breast cancer tumors treated with neoadjuvant chemotherapy with and without bevacizumab: Results from NeoAva - A randomized phase II study

Patients treated with bevacizumab in addition to regular neoadjuvant chemotherapy achieve an increased rate of pathological complete response (pCR). The molecular characteristics of responding and non-responding tumors, including how treatment combinations influence the gene expression profiles and the signaling pathways, may be useful predictors of antiangiogenic response.

The NeoAva study included patients with HER2 negative primary tumors of ≥25 mm that were randomized (1:1) to receive neoadjuvant chemotherapy (4 x FEC100 + 12 weeks of taxane-based therapy) with or without bevacizumab. Mammography, ultrasound and MR imaging were used for response evaluation, in addition to final pathology assessment.

In the first part of the study 74 patients were evaluable for tumor response. The tumor size at time of inclusion was T2, T3 and T4 in 24.3%, 67.6% and 8.1% of the patients, respectively. Lymph node metastases were detected in 56.7% of the patients at inclusion and 82.4% were hormone receptor positive. There were no significant differences in the tumor size, lymph node or hormone receptor status between the treatment arms.

The patients were randomized with bevacizumab + chemotherapy (n = 37) and treatment with chemotherapy alone (n = 37). Of the nine patients who achieved pCR in breast and axilla (12.2%), seven patients received bevacizumab (7/37), while two were treated with chemotherapy alone (2/37). Four of the patients with pCR were hormone receptor negative, of which three received bevacizumab. Of the remaining five hormone receptor positive tumors that achieved complete response, four received bevacizumab.

In the second part of the study we evaluated gene expression signatures by RNA microarray and the time-response of pathways to treatment, using pathway analysis that integrates copy number and gene expression (Paradigm). Biopsies for molecular analyses were collected before therapy, after 12 weeks, and at surgery. Treatment associated gene expression changes to chemotherapy were subtracted, and bevacizumab associated differential expression was observed for 1069 genes. Furthermore, molecular profiling of the tumor tissue was performed at DNA level by copy number analysis (Affymetrix, SNP6.0) and mRNA level by gene expression arrays(Agilent 60K). At the screening time point, we found high proliferation through the activity of cyclin E and B and the transcription factors E2F1 and FOXM1. At 12 weeks, there was a strong increase in predicted p53 signaling, due to increased activity of downstream target genes. The 12 week timepoint was also characterized by an increase of Calmodulin 1, MAPK3, as well as Peroxisome proliferator-activated receptor alpha (PPAR-alpha), and both trends continued to the 25 week time point. At 25 weeks, there were broad increases in ERK1/2, JUN, and FOS signaling. The 25 week timepoint also showed a T-cell response signature that from increased activity of GATA3, IL6/IL6R, IL4, and NFATC1 and NFATC2. These results suggest that there are measurable and strongly significant aberrations in molecular activity during treatment, which may be useful to monitor treatment response.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-14-02.

The 5p12 breast cancer susceptibility locus affects MRPS30 expression in estrogen-receptor positive tumors

Genome-wide association studies have identified numerous loci linked to breast cancer susceptibility, but the mechanism by which variations at these loci influence susceptibility is usually unknown. Some variants are only associated with particular clinical subtypes of breast cancer. Understanding how and why these variants influence subtype-specific cancer risk contributes to our understanding of cancer etiology. We conducted a genome-wide expression Quantitative Trait Locus (eQTL) study in a discovery set of 287 breast tumors and 97 normal mammary tissue samples and a replication set of 235 breast tumors. We found that the risk-associated allele of rs7716600 in the 5p12 estrogen receptor-positive (ER-positive) susceptibility locus was associated with elevated expression of the nearby gene MRPS30 exclusively in ER-positive tumors. We replicated this finding in 235 independent tumors. Further, we showed the rs7716600 risk genotype was associated with decreased MRPS30 promoter methylation exclusively in ER-positive breast tumors. In vitro studies in MCF-7 cells carrying the protective genotype showed that estrogen stimulation decreased MRPS30 promoter chromatin availability and mRNA levels. In contrast, in 600MPE cells carrying the risk genotype, estrogen increased MRPS30 expression and did not affect promoter availability. Our data suggest the 5p12 risk allele affects MRPS30 expression in estrogen-responsive tumor cells after tumor initiation by a mechanism affecting chromatin availability. These studies emphasize that the genetic architecture of breast cancer is context-specific, and integrated analysis of gene expression and chromatin remodeling in normal and tumor tissues will be required to explain the mechanisms of risk alleles.

Individual and combined effects of DNA methylation and copy number alterations on miRNA expression in breast tumors

Background

The global effect of copy number and epigenetic alterations on miRNA expression in cancer is poorly understood. In the present study, we integrate genome-wide DNA methylation, copy number and miRNA expression and identify genetic mechanisms underlying miRNA dysregulation in breast cancer.

Results

We identify 70 miRNAs whose expression was associated with alterations in copy number or methylation, or both. Among these, five miRNA families are represented. Interestingly, the members of these families are encoded on different chromosomes and are complementarily altered by gain or hypomethylation across the patients. In an independent breast cancer cohort of 123 patients, 41 of the 70 miRNAs were confirmed with respect to aberration pattern and association to expression. In vitro functional experiments were performed in breast cancer cell lines with miRNA mimics to evaluate the phenotype of the replicated miRNAs. let-7e-3p, which in tumors is found associated with hypermethylation, is shown to induce apoptosis and reduce cell viability, and low let-7e-3p expression is associated with poorer prognosis. The overexpression of three other miRNAs associated with copy number gain, miR-21-3p, miR-148b-3p and miR-151a-5p, increases proliferation of breast cancer cell lines. In addition, miR-151a-5p enhances the levels of phosphorylated AKT protein.

Conclusions

Our data provide novel evidence of the mechanisms behind miRNA dysregulation in breast cancer. The study contributes to the understanding of how methylation and copy number alterations influence miRNA expression, emphasizing miRNA functionality through redundant encoding, and suggests novel miRNAs important in breast cancer.

Quantitative DNA methylation analyses reveal stage dependent DNA methylation and association to clinico-pathological factors in breast tumors

Background

Aberrant DNA methylation of regulatory genes has frequently been found in human breast cancers and correlated to clinical outcome. In the present study we investigate stage specific changes in the DNA methylation patterns in order to identify valuable markers to understand how these changes affect breast cancer progression.

Methods

Quantitative DNA methylation analyses of 12 candidate genes ABCB1, BRCCA1, CDKN2A, ESR1, GSTP1, IGF2, MGMT, HMLH1, PPP2R2B, PTEN, RASSF1A and FOXC1 was performed by pyrosequencing a series of 238 breast cancer tissue samples from DCIS to invasive tumors stage I to IV.

Results

Significant differences in methylation levels between the DCIS and invasive stage II tumors were observed for six genes RASSF1A, CDKN2A, MGMT, ABCB1, GSTP1 and FOXC1. RASSF1A, ABCB1 and GSTP1 showed significantly higher methylation levels in late stage compared to the early stage breast carcinoma. Z-score analysis revealed significantly lower methylation levels in DCIS and stage I tumors compared with stage II, III and IV tumors. Methylation levels of PTEN, PPP2R2B, FOXC1, ABCB1 and BRCA1 were lower in tumors harboring TP53 mutations then in tumors with wild type TP53. Z-score analysis showed that TP53 mutated tumors had significantly lower overall methylation levels compared to tumors with wild type TP53. Methylation levels of RASSF1A, PPP2R2B, GSTP1 and FOXC1 were higher in ER positive vs. ER negative tumors and methylation levels of PTEN and CDKN2A were higher in HER2 positive vs. HER2 negative tumors. Z-score analysis also showed that HER2 positive tumors had significantly higher z-scores of methylation compared to the HER2 negative tumors. Univariate survival analysis identifies methylation status of PPP2R2B as significant predictor of overall survival and breast cancer specific survival.

Conclusions

In the present study we report that the level of aberrant DNA methylation is higher in late stage compared with early stage of invasive breast cancers and DCIS for genes mentioned above.