Predict Breast Cancer Patient Research Articles

Highly robust model of transcription regulator activity predicts breast cancer overall survival

BackgroundWhile several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes.MethodsGene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-expressed targets in TCGA using a nonlinear approach. We then used this information to predict breast cancer patient survival outcome.ResultWe built a multiple regulator-based prediction model for breast cancer. This model was validated in more than 5000 breast cancer patients from the Gene Expression Omnibus (GEO) databases. We demonstrated our regulator model was significantly associated with clinical stage and that cell cycle and DNA replication related pathways were significantly enriched in high regulator risk patients.ConclusionOur findings demonstrate that transcriptional regulator activities can predict patient survival. This finding provides additional biological insights into the mechanisms of breast cancer progression.

The RNA-binding protein AKAP8 suppresses tumor metastasis by antagonizing EMT-associated alternative splicing

Alternative splicing has been shown to causally contribute to the epithelial–mesenchymal transition (EMT) and tumor metastasis. However, the scope of splicing factors that govern alternative splicing in these processes remains largely unexplored. Here we report the identification of A-Kinase Anchor Protein (AKAP8) as a splicing regulatory factor that impedes EMT and breast cancer metastasis. AKAP8 not only is capable of inhibiting splicing activity of the EMT-promoting splicing regulator hnRNPM through protein–protein interaction, it also directly binds to RNA and alters splicing outcomes. Genome-wide analysis shows that AKAP8 promotes an epithelial cell state splicing program. Experimental manipulation of an AKAP8 splicing target CLSTN1 revealed that splice isoform switching of CLSTN1 is crucial for EMT. Moreover, AKAP8 expression and the alternative splicing of CLSTN1 predict breast cancer patient survival. Together, our work demonstrates the essentiality of RNA metabolism that impinges on metastatic breast cancer.

A transcriptome-based signature of pathological angiogenesis predicts breast cancer patient survival.

The specific genes and molecules that drive physiological angiogenesis differ from those involved in pathological angiogenesis, suggesting distinct mechanisms for these seemingly related processes. Unveiling genes and pathways preferentially associated with pathologic angiogenesis is key to understanding its mechanisms, thereby facilitating development of novel approaches to managing angiogenesis-dependent diseases. To better understand these different processes, we elucidated the transcriptome of the mouse retina in the well-accepted oxygen-induced retinopathy (OIR) model of pathological angiogenesis. We identified 153 genes changed between normal and OIR retinas, which represent a molecular signature relevant to other angiogenesis-dependent processes such as cancer. These genes robustly predict the survival of breast cancer patients, which was validated in an independent 1,000-patient test cohort (40% difference in 15-year survival; p = 2.56 x 10−21). These results suggest that the OIR model reveals key genes involved in pathological angiogenesis, and these may find important applications in stratifying tumors for treatment intensification or for angiogenesis-targeted therapies.

LINC02273 drives breast cancer metastasis by epigenetically increasing AGR2 transcription

BackgroundThe majority of breast cancer patients die of metastasis rather than primary tumors, whereas the molecular mechanisms orchestrating cancer metastasis remains poorly understood. Long noncoding RNAs (lncRNA) have been shown to regulate cancer occurrence and progression. However, the lncRNAs that drive metastasis in cancer patients and their underlying mechanisms are still largely unknown.MethodslncRNAs highly expressed in metastatic lymph nodes were identified by microarray. Survival analysis were made by Kaplan-Meier method. Cell proliferation, migration, and invasion assay was performed to confirm the phenotype of LINC02273. Tail vein model and mammary fat pad model were used for in vivo study. RNA pull-down and RIP assay were used to confirm the interaction of hnRNPL and LINC02273. Chromatin isolation by RNA purification followed by sequencing (ChIRP-seq), RNA-seq, ChIP-seq, and luciferase reporter assay reveal hnRNPL-LINC02273 regulates AGR2. Antisense oligonucleotides were used for in vivo treatment.ResultsWe identified a novel long noncoding RNA LINC02273, whose expression was significantly elevated in metastatic lesions compared to the primary tumors, by genetic screen of matched tumor samples. Increased LINC02273 promoted breast cancer metastasis in vitro and in vivo. We further showed that LINC02273 was stabilized by hnRNPL, a protein increased in metastatic lesions, in breast cancer cells. Mechanistically, hnRNPL-LINC02273 formed a complex which activated AGR2 transcription and promoted cancer metastasis. The recruitment of hnRNPL-LINC02273 complex to AGR2 promoter region epigenetically upregulated AGR2 by augmenting local H3K4me3 and H3K27ac levels. Combination of AGR2 and LINC02273 was an independent prognostic factor for predicting breast cancer patient survival. Moreover, our data revealed that LINC02273-targeting antisense oligonucleotides (ASO) substantially inhibited breast cancer metastasis in vivo.ConclusionsOur findings uncover a key role of LINC02273-hnRNPL-AGR2 axis in breast cancer metastasis and provide potential novel therapeutic targets for metastatic breast cancer intervention.

A prognostic 10-lncRNA expression signature for predicting the risk of tumour recurrence in breast cancer patients.

Breast cancer is one of the most frequently diagnosed malignancies and a leading cause of cancer death among females. Multiple molecular alterations are observed in breast cancer. LncRNA transcripts were proved to play important roles in the biology of tumorigenesis. In this study, we aimed to identify lncRNA expression signature that can predict breast cancer patient survival. We developed a 10‐lncRNA signature‐based risk score which was used to separate patients into high‐risk and low‐risk groups. Patients in the low‐risk group had significantly better survival than those in the high‐risk group. Receiver operating characteristic analysis indicated that this signature exhibited excellent diagnostic efficiency for 1‐, 3‐ and 5‐year disease‐relapse events. Moreover, multivariate Cox regression analysis demonstrated that this 10‐lncRNA signature was an independent risk factor when adjusting for several clinical signatures such as age, tumour size and lymph node status. The prognostic value of risk scores was validated in the validation set. In addition, a nomogram was established and the calibration plots analysis indicated the good performance and clinical utility of the nomogram. In conclusion, our results demonstrated that this 10‐lncRNA signature effectively grouped patients at low and high risk of disease recurrence.

Development and validation of novel microenvironment-based immune molecular subtypes of breast cancer: Implications for immunotherapy.

1094 Background: Breast cancer treatment with immunotherapy can improve clinical benefits, but the majority of patients did not respond to the treatment. To understand tumor–immune interactions in breast cancer, we identified novel microenvironment-based immune molecular subtypes. Methods: A training cohort of 1,394 breast cancer patients from the Molecular Taxonomy of Breast Cancer International Consortium profiled by RNA and DNA sequencing data were analyzed to calculate immune-related gene biomarkers and to assign prognostic categories using LASSO Cox regression model. Additionally, 969 patients from The Cancer Genome Atlas data set was used as an independent validation cohort. We further compared tumor mutation burden (TMB) and cytolytic activity (CYT) levels between different immune molecular subtypes. Results: Using the LASSO model, we established an immune molecular classifier based on following 5 features: IFN-γ signature, ICOSLG, TNFRSF14, Mast.cells.resting, and T.cells. CD4.memory.resting. Then we found that it contained two distinct microenvironment-based subtypes (immune class and non-immune class), characterized by significant differences in overall survival in the training cohort (hazard ratio [HR] 0.71; 95% confidence interval [CI] 0.61 to 0.81; P < 0.001) and in the validation cohort (HR 0.34; 95% CI 0.22 to 0.54; P < 0.001). We found an inverse association between immune gene expression and TMB levels (ρ = 0.096, P < 0.001). Immune class subtype patients with good prognosis had significantly lower TMB and higher CYT than did non-immune class subtype patients with poor prognosis (all, P < 0.05). The clinical use of the immune molecular subtypes showed a closer association with survival than did IFN-γ signature or PD-L1 expression (all, P < 0.05). The robustness of the immune molecular subtypes was confirmed in the validation cohort. Conclusions: We revealed novel immune molecular subtypes, which represented better utility in predicting breast cancer patients’ survival compared with IFN-γ signature or PD-L1, and could be an important guide for precision immunotherapy.

Abstract P1-05-01: Breast cancer cell-derived IL-1B drives metastasis and colonisation of the bone microenvironment

Abstract Background: Breast cancer bone metastases are incurable and new therapeutic targets needed. After homing and colonising bone, cancer cells remain dormant, until signals from the microenvironment stimulate their proliferation to form overt metastases. We have recently identified interleukin-1B (IL-1B) as a potential marker for predicting breast cancer patients at increased risk of skeletal relapse and established a role for IL-1 signalling in tumour dormancy in bone. Here we present novel data to support that tumour cell-derived IL-1B plays major roles in breast cancer metastasis and growth in bone. Methods: Tumour/stromal IL-B and IL-1R1 expression was assessed in samples from the AZURE study following immunohistochemical staining. A humanised mouse model of MDA-MB-231 bone metastasis was used to assess effects of the IL-1R antagonist, Anakinra, on tumour growth and spontaneous metastasis. Effects of tumour cell-derived IL-1B on parameters associated with epithelial to mesenchymal transition and metastasis were measured by ELISA, QPCR, Western blot, transwell and scratch assays in MDA-MB-231, MCF7 and T47D cells transfected with IL-1B/control. Homing of breast cancer cells to bone was monitored in BALB/c nude mice intra venously injected with IL-1B overexpressing/control cells. To assess anti-tumour effects of IL-1 inhibition combined with standard of care, BALB/c or C57BL/6 mice were injected with 4T1 or E0771 cells (intra cardiac or intra ductal) 7-days prior to administration of Anakinra, doxorubicin, zoledronic acid (ZA) or placebo, alone or in combination for 14 days. Results: In tissue samples from >1300 patients with stage II/III breast cancer, active IL-1B in tumour cells correlated with relapse in bone (hazard ratio 1.85; 95% CI 1.05-3.26; P=0.02) and other sites (hazard ratio 2.09; 95% CI 1.26-3.48; P=0.0016). In a model of spontaneous human breast cancer metastasis to human bone, Anakinra significantly reduced metastasis to bone (from 80% in control animals to, 20% in Anakinra treated mice) and reduced the number of tumour cells shed into the circulation. Genetic manipulation of breast cancer cells to overexpress IL-1B demonstrated that exogenous production of IL-1B promoted EMT (decreased E-Cadherin, N-Cadherin and G-Catenin), invasion, migration and organ-specific homing in ER-ve (MDA-MB-231) and ER+ve (T47D and MCF7) cells in vitro and in vivo. Contact between tumour cells and osteoblasts or bone marrow cells increased IL-1B secretion from all three cell types. Exposure of tumour cells to IL-1B in the absence of bone cells did not stimulate tumour cell proliferation. Instead, elevated concentrations of IL-1B caused expansion of the bone metastatic niche (increased osteoblasts and blood vessels) that in turn stimulated tumour proliferation. Adding Anakinra to chemotherapy and ZA to mice injected with E0771 cells completely prevented bone metastasis formation and reduced extra-skeletal metastasis by 33%. In mice injected with 4T1 cells, the triple combination therapy reduced bone metastasis by 50% and extra-skeletal metastases by 65%. Conclusion: Our novel data demonstrate that IL-1B/IL-1R1 signalling plays an important role in breast cancer metastasis to bone. Pharmacological inhibition of IL-1B has potential as a novel treatment. Citation Format: Ottewell PD, Lefley DV, Freeman K, Gregory WM, Hanby AM, Spicer-Hadlington AR, Liu X, Bradbury SM, Hambley L, Allocca G, Cookson V, Kruithof de-Julio M, Coleman RE, Brown JE, Holen I, Tulotta C. Breast cancer cell-derived IL-1B drives metastasis and colonisation of the bone microenvironment [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-05-01.

Abstract 2151: Development of small-molecule mTORC1 radiotracers for evaluation of targeted therapy resistance using PET

Abstract Overcoming resistance is an area of unmet clinical need for patients undergoing trastuzumab-based HER2-directed therapy. PTEN loss or PI3K mutation has been shown to induce mTOR activation and mediate trastuzumab resistance. During the BOLERO-3 phase III clinical trial, the addition of everolimus to trastuzumab plus vinorelbine significantly prolonged progression-free survival in patients with trastuzumab-resistant and taxane-pretreated, HER2-positive advanced breast cancer. It is critically important to identify HER2-positive breast cancer patients who are sensitive to mTOR inhibition. Our aim is to develop noninvasive mTORC1 binding small-molecule imaging probes to predict breast cancer patient resistance to treatment utilizing positron emission tomography (PET). Utilizing the benzofuran-based compound ChemBridge 5219657, we have developed a panel of potent inhibitors specific for mTOR complex 1. Alkyne derivatives suitable for conjugation with 2-[18F]fluoroethylazide were developed via Cu(I)-catalyzed click chemistry. Radiolabeling was performed on the automated iPhase FlexLab module providing reliable amounts of radiotracer. Synthesis of click precursor was achieved over 5 linear steps with a 24% isolated yield. Quality control was characterized using NMR, MS, UV- and radio-HPLC analysis. 18F-labeling conjugation with precursor resulted in a 40 ± 5% isolated radiochemical yield with >99% radiochemical purity and a molar activity of 12.5 ± 6.0 GBq/µmol. Initial in vitro sensitivity to everolimus was performed via SRB proliferation analysis following cold-compound treatment on HER2-positive human breast cancer cell lines (BT-474 and HCC1419) and HER2 low expressing control cell lines (MDA-MB-468 and MDA-MB-231). In vitro 18F-labeled binding experiments demonstrated an increased uptake in BT-474 and HCC-1419 cells, 1.5 and 2.5-fold compared to the negative controls, respectively. NSG mice bearing BT-474, MDA-MB-231 and MDA-MB-468 xenografts were explored for in vivo dynamic PET imaging experiments confirming this selective uptake of radiotracer in everolimus-sensitive cells. Our synthesis strategies identified a reliable radiolabeling approach capable of producing sufficient amounts of radiochemically pure radiotracer for in vivo investigation. The increased tracer uptake in mTOR treatment-sensitive cell lines in vitro as well as in vivo provides an encouraging outcome warranting further preclinical studies for the investigation of HER2-positive therapy resistance in mTOR-sensitive models. Citation Format: Adam C. Parslow, Christian W. Wichmann, Angela Rigopoulos, Uwe Ackermann, Jonathan M. White, Andrew M. Scott. Development of small-molecule mTORC1 radiotracers for evaluation of targeted therapy resistance using PET [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2151.

The role of IL-1B in breast cancer bone metastasis.

Approximately 75% of patients with late-stage breast cancer will develop bone metastasis. This condition is currently considered incurable and patients’ life expectancy is limited to 2–3 years following diagnosis of bone involvement. Interleukin (IL)-1B is a pro-inflammatory cytokine whose expression in primary tumours has been identified as a potential biomarker for predicting breast cancer patients at increased risk for developing bone metastasis. In this review, we discuss how IL-1B from both the tumour cells and the tumour microenvironment influence growth of primary breast tumours, dissemination into the bone metastatic niche and proliferation into overt metastases. Recent evidence indicates that targeting IL-1B signalling may provide promising new treatments that can hold tumour cells in a dormant state within bone thus preventing formation of overt bone metastases.

Salivary biomarkers in the diagnosis of breast cancer: A review.

Salivary biomarkers could be helpful to characterize breast cancer. Therefore, this review was performed to evaluate the capability of salivary biological markers in the diagnosis and monitoring of breast cancer. Studies were eligible for inclusion if they assessed the potential diagnostic value or other discriminatory properties of biological markers in saliva of patients with breast cancer. The search was performed in six electronic databases (Cochrane, LILACS, PubMed, Science Direct, Scopus, Web of Science). In addition the biomarkers were classified according to their potential clinical application. We identified 567 pertinent studies, of which 13 met the inclusion criteria. Combined biomarker approaches demonstrated better ability to predict breast cancer patients than individual biomarkers. As single biomarker, namely proline, reported great capacity in both early and late stage breast cancer diagnosis. Taurine showed interesting capability to identify early breast cancer individuals. Furthermore, valine also demonstrated excellent diagnostic test accuracy for advanced stages of breast cancer. Only seven studies reported sensitivity and specificity (Zhang et al., 2010; Streckfus et al., 2000a; Brooks et al., 2008; Cheng et al., 2015; Bigler et al., 2002; Zhong et al., 2016; Streckfus, 2009), which varied considerably from 50% to 100%, and from 51% to 97%, respectively. In general, salivary biomarkers identified advanced stages of breast cancer better than early stages. There is currently limited evidence to confirm the putative implementation of salivary biomarkers as diagnostic tools for breast cancer. However, current review provides new research directions.

IL-1 drives breast cancer growth and bone metastasisin vivo

BackgroundWe have recently identified interleukin 1B (IL-1B) as a potential biomarker for predicting breast cancer patients at increased risk for developing bone metastasis. In mouse models, IL-1B and its receptor (IL-1R1) are upregulated in breast cancer cells that metastasise to bone compared with cells that do not. We have now investigated the functional role of IL-1 by blocking IL-1R signalling with the clinically licensed antagonist, anakinra.Methodology6-week old female BALB/c mice received a subcutaneous or intra-venous injection of MDA-MB-231-IV or MCF7 cells. Anakinra (1mg/kg/day) or placebo was administered 3 days before (preventative) or 7 days later (treatment). Tumour volume, apoptosis (TUNEL, Caspase 3), proliferation (Ki67) and angiogenesis (CD34, VEGF and endothelin) were analysed. Effects on bone were measured by uCT, and TRAP, P1NP, IL-1B, TNF alpha and IL-6 ELISA.ResultsAnakinra significantly reduced growth of MDA-MB-231-IV tumours in bone from 6.50+/3.00mm2 (placebo) to 2.56+/−1.07mm2 (treatment) and 0.63+/−0.18mm2 (preventative). Anakinra also reduced the number of mice that developed bone metastasis from 90% (placebo) to 40% (treatment) and 10% (preventative). Anti-tumour effects were not confined to bone, subcutaneous tumour volumes reduced from 656.68mm3 (placebo) to 160.47mm3 (treatment) and 31.08mm3 (preventative). Anakinra did not increase tumour cell apoptosis but reduced proliferation and angiogenesis in addition to exerting significant effects on the tumour environment reducing bone turnover markers, IL-1B and TNF alpha.ConclusionsOur novel data demonstrate a functional role of IL-1 signalling in breast tumour progression and metastasis, supporting that anakinra could be repurposed for the treatment of breast cancer bone metastasis.

Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival.

Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan–Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT104, LINC01234, and STXBP5-AS1) was identified. The Kaplan–Meier analysis and ROC curves proved that the model could predict the prognostic survival with good sensitivity and specificity in both the validation set (AUC = 0.752, 95% confidence intervals (CI): 0.651–0.854) and the microarray dataset (AUC = 0.714, 95%CI: 0.615–0.814). Further study showed the three-lncRNA signature was not only pervasive in different breast cancer stages, subtypes and age groups, but also provides more accurate prognostic information than some widely known biomarkers. The results suggested that RNA-seq transcriptome profiling provides that the three-lncRNA signature is an independent prognostic biomarker, and have clinical significance. In addition, lncRNA, miRNA, and mRNA interaction network indicated lncRNAs may intervene in breast cancer pathogenesis by binding to miR-190b, acting as competing endogenous RNAs.

Correlation Between <i>GATA-3</i>, <i>Ki67</i> and p53 Expressions to Histopathology Grading of Breast Cancer in Makassar, Indonesia

<i>Background:</i> During the last two decades, research about GATA-3, Ki-67, p53 expressions have been done, but it is still a debate on their use in predicting breast cancer patients’ prognosis and survival rate. Expressions of GATA-3 decreased with increasing of histopathology grading of breast cancer and increase with decrease of histopathology grading of breast cancer. The level expression of Ki-67 has a positive relation with breast cancer histopathology grading. p53 has no correlation with high grade differentiation of breast cancer. p53 is a transcription factor which is activated as a part of cellular stress response that can regulate genes’ cellular process, including apoptosis and senescence. <i>Aim:</i> To determine correlation between expressions of GATA 3, Ki-67 and p53 with histopathology grading of breast cancer in Makassar, Indonesia. <i>Methods:</i> Antibody monoclonal GATA 3, Ki-67 and p53 on the nucleus cell were detected with immunohistochemistry method. The positive and negative expressions of GATA 3, Ki-67 and p53 were assessed using scoring system according to the proportion of positive cell and coloring intensities. <i>Results:</i> There is no correlation between the higher positive expression ofp53 and higher expression of histopathology grading of breast cancer (<i>P</i> = 0.089). While Ki-67 had positive association with higher grade malignancy (<i>P</i> = 0.03). However, there was no association between GATA-3 expression and histopathology grading. <i>Conclusion:</i> In our research we found there is no correlation between higher expression of p53 and low expression of GATA-3 with higher histopathology grading of breast cancer. High expression of Ki-67 have significantly statistic analysis with high expression of histopathology grading of mammary cancer.

Abstract 3825: Whole genome bisulfite sequencing from plasma of patients with metastatic breast cancer identifies putative biomarkers

Abstract Although several improvements in the management of breast cancer(BC) have been made, an estimated 90% of BC related deaths are due to the development of distant metastasis to organs such as lung, bone, liver, and brain. Numerous studies suggest that cell-free (cf)DNA methylation could serve as a useful biomarker for improving clinical management. The objective of our study was to identify novel blood-based biomarkers that can be used to predict BC patients at high risk of distant metastasis. For the first time we performed paired-end whole genome bisulfite sequencing (WGBS) using 15 ng of cf plasma DNA from three pools of samples which included metastatic BC to various organs (M, n = 40), breast cancer free survivors (BCF n = 40) and healthy individuals (H, n = 40). Sequences were aligned using the bismark tool and data analysis was conducted using the R package methylKit to identify base-pair resolution DNA methylation differences between groups. A minimum of 5 reads in each group, delta beta values ≥0.2 and p values&amp;lt;0.001 were considered differentially methylated loci (DML). Overall, the data revealed that H and BCF had very similar plasma methylomes with approximately 1792 DML, compared with 0.8 million and 1.1 million DML between HvsM and BFSvsM, respectively. The M pool had greater overall hypomethylation across the genome, particularly in gene bodies compared with H and BFS. However, M had greater CpG island and promoter hypermethylation compared with H and BFS. The average coverage of CpG loci across the genome was 18, 11 and 9 for M, BFS, and H, respectively indicating that plasma of M samples has greater genomic representation. Among the genes differentially methylated in plasma of M was RUNX3, which was hypomethylated overall in M compared to H and BFS except for one CpG island hotspot, where methylation and number of reads significantly exceeded that of H and BFS. Other genes with similar hotspots were also identified. We validated these data using bisulfite amplicon sequencing (Ion Torrent) in each pool and individual plasma samples. Using the HumanMethylation27K bead array, we analyzed 32 breast brain metastasis (BBM) tumor tissues compared to a series of 50 unmatched early stage BC samples and identified RUNX3 hypermethylation in the same hotspot region as WGBS. Lastly, comparing 25 early stage BC samples with known outcomes of BBM had RUNX3 hotspot hypermethylation compared with samples from patients who were BM-free for greater than 5 years. This suggested that prediction of metastasis may occur at the time of early stage of disease. Together these data identified DNA-methylation hotspots in circulation and tissue that are unique to distant MBC and which could be translated into predictive biomarkers of metastasis. Biomarkers indicating a high-risk population can shift current paradigms by allowing increased surveillance and/or prophylactic therapies aimed at preventing metastasis and improving outcomes. Citation Format: Christophe Legendre, Gerald C. Gooden, Kyle N. Johnson, Rae Anne Martinez, Bodour Salhia. Whole genome bisulfite sequencing from plasma of patients with metastatic breast cancer identifies putative biomarkers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3825. doi:10.1158/1538-7445.AM2015-3825

Interaction between smoking history and gene expression levels impacts survival of breast cancer patients.

In contrast to studies focused on cigarette smoking and risk of breast cancer occurrence, this study explored the influence of smoking on breast cancer recurrence and progression. The goal was to evaluate the interaction between smoking history and gene expression levels on recurrence and overall survival of breast cancer patients. Multivariable Cox proportional hazards models were fitted for 48 cigarette smokers, 50 non-smokers, and the total population separately to determine which gene expressions and gene expression/cigarette usage interaction terms were significant in predicting overall and disease-free survival in breast cancer patients. Using methods similar to Andres et al. (BMC Cancer 13:326, 2013a; Horm Cancer 4:208-221, 2013b), multivariable analyses revealed CENPN, CETN1, CYP1A1, IRF2, LECT2, and NCOA1 to be important predictors for both breast carcinoma recurrence and mortality among smokers. Additionally, COMT was important for recurrence, and NAT1 and RIPK1 were important for mortality. In contrast, only IRF2, CETN1, and CYP1A1 were significant for disease recurrence and mortality among non-smokers, with NAT2 additionally significant for survival. Analysis of interaction between smoking status and gene expression values using the combined samples revealed significant interactions between smoking status and CYP1A1, LECT2, and CETN1. Signatures consisting of 7-8 genes were highly predictive for breast cancer recurrence and overall survival among smokers, with median C-index values of 0.8 and 0.73 for overall survival and recurrence, respectively. In contrast, median C-index values for non-smokers was only 0.59. Hence, significant interactions between gene expression and smoking status can play a key role in predicting breast cancer patient outcomes.

A four-long non-coding RNA signature in predicting breast cancer survival.

BackgroundMany long non-coding RNAs(lncRNAs) have been found to be a good marker for several tumors. Using lncRNA-mining approach, we aimed to identify lncRNA expression signature that can predict breast cancer patient survival.MethodsWe performed LncRNA expression profiling in 887 breast cancer patients from Gene Expression Omnibus (GEO) datasets. The association between lncRNA signature and clinical survival was analyzed using the training set(n = 327, from GSE 20685). The validation for the association was performed in another three independent testing sets(252 from GSE21653, 204 from GSE12276, and 104 from GSE42568).ResultsA set of four lncRNA genes (U79277, AK024118, BC040204, AK000974) have been identified by the random survival forest algorithm. Using a risk score based on the expression signature of these lncRNAs, we separated the patients into low-risk and high-risk groups with significantly different survival times in the training set. This signature was validated in the other three cohorts. Further study revealed that the four-lncRNA expression signature was independent of age and subtype. Gene Set Enrichment Analysis (GSEA) suggested that gene sets were involved in several cancer metastasis related pathways.ConclusionsThese findings indicate that lncRNAs may be implicated in breast cancer pathogenesis. The four-lncRNA signature may have clinical implications in the selection of high-risk patients for adjuvant therapy.Electronic supplementary materialThe online version of this article (doi:10.1186/s13046-014-0084-7) contains supplementary material, which is available to authorized users.

Predicting Breast Cancer Patients' Treatment Responses to Tamoxifen

Predicting Breast Cancer Patients' Treatment Responses to Tamoxifen

The Role of the Family Environment and Computer-Mediated Social Support on Breast Cancer Patients’ Coping Strategies

Despite the importance of family environment and computer-mediated social support (CMSS) for women with breast cancer, little is known about the interplay of these sources of care and assistance on patients’ coping strategies. To understand this relation, the authors examined the effect of family environment as a predictor of the use of CMSS groups as well as a moderator of the relation between group participation and forms of coping. Data were collected from 111 patients in CMSS groups in the Comprehensive Health Enhancement Support System “Living with Breast Cancer” intervention. Results indicate that family environment plays a crucial role in (a) predicting breast cancer patient's participation in CMSS groups and (b) moderating the effects of use of CMSS groups on breast cancer patients’ coping strategies such as problem-focused coping and emotion-focused coping.

Transglutaminase 2 Overexpression in Tumor Stroma Identifies Invasive Ductal Carcinomas of Breast at High Risk of Recurrence

IntroductionMolecular markers for predicting breast cancer patients at high risk of recurrence are urgently needed for more effective disease management. The impact of alterations in extracellular matrix components on tumor aggressiveness is under intense investigation. Overexpression of Transglutaminase 2 (TG2), a multifunctional enzyme, in cancer cells impacts epithelial mesenchymal transition, growth, invasion and interactions with tumor microenvironment. The objective of our study is to determine the clinical relevance of stromal TG2 overexpression and explore its potential to identify breast cancers at high risk of recurrence.MethodsThis retrospective study is based on immunohistochemical analysis of TG2 expression in normal breast tissues (n = 40) and breast cancers (n = 253) with clinical, pathological and follow-up data available for up to 12 years. TG2 expression was correlated with clinical and pathological parameters as well as disease free survival (DFS) of breast cancer patients.ResultsStromal TG2 overexpression was observed in 114/253 (45.0%) breast cancer tissues as compared to breast normal tissues. Among invasive ductal carcinomas (IDC) of the breast, 97/168 (57.7%) showed strong TG2 expression in tumor stroma. Importantly, IDC patients showing stromal TG2 accumulation had significantly reduced DFS (mean DFS = 110 months) in comparison with patients showing low expression (mean DFS = 130 months) in Kaplan-Meier survival analysis (p<0.001). In Cox multivariate regression analysis, stromal TG2 accumulation was an independent risk factor for recurrence (p = 0.006, Hazard’s ratio, H.R. = 3.79). Notably, these breast cancer patients also showed immunostaining of N-epsilon gamma-glutamyl lysine amino residues in tumor stroma demonstrating the transamidating activity of TG2.ConclusionsAccumulation of TG2 in tumor stroma is an independent risk factor for identifying breast cancer patients at high risk of recurrence. TG2 overexpression in tumor stroma may serve as a predictor of poor prognosis for IDC of the breast.

Transglutaminase II expression in invasive ductal carcinomas.

34 Background: Molecular markers for predicting breast cancer patients at high risk of recurrence are urgently needed for more effective disease management. The impact of alterations in extracellular matrix components on tumor aggressiveness is under intense investigation. Overexpression of Transglutaminase 2 (TG2), a multifunctional enzyme, in cancer cells impacts epithelial mesenchymal transition and cancer stem cell phenotype, growth, invasion and interactions with tumor microenvironment. The objective of our study is to determine the clinical relevance of stromal TG2 overexpression and explore its potential to identify which IDCs are at high risk of recurrence. Methods: This retrospective study is based on immunohistochemical analysis of TG2 expression in 168 invasive ductal carcinomas with clinical, pathological and follow-up data available for up to 12 years. TG2 expression was correlated with clinical and pathological parameters as well as disease free survival (DFS) of breast cancer patients. Results: Stromal TG2 overexpression was observed in 97/168 (57.7%) invasive ductal carcinomas (IDC). Notably, IDC patients showing stromal TG2 accumulation had significantly reduced disease free survival (mean DFS = 110 months) in comparison with patients showing low expression (mean DFS = 130 months), as revealed by Kaplan-Meier survival analysis (p &lt;0.001). In Cox multivariate regression analysis, TG2 accumulation in tumor stroma emerged as an independent risk factor for recurrence in IDC (p = 0.006, Hazard’s ratio, H.R. = 3.79). Conclusions: Accumulation of TG2 in tumor stroma is an independent risk factor for identifying breast cancer patients at high risk of recurrence. TG2 overexpression in tumor stroma may serve as a predictor of poor prognosis for IDC of the breast.