Personalized Risk最新文献

{"title":"Abstract A30: PELP1 and AIB1 cooperate to promote breast cancer progression in ER+ breast cancer models","authors":"Thu H. Truong, Hsiangyu Hu, J. Ostrander, C. Lange","doi":"10.1158/1557-3125.ADVBC17-A30","DOIUrl":"https://doi.org/10.1158/1557-3125.ADVBC17-A30","url":null,"abstract":"Luminal breast cancers account for ~75% of newly diagnosed cases and express estrogen receptor (ER) and a range of progesterone receptor (PR)-positive cells. Although adjuvant hormone therapies that target ER actions (e.g., tamoxifen or aromatase inhibitors) have improved overall patient survival, up to ~40% of luminal breast tumors eventually progress to ER+, but endocrine-resistant disease. Therefore, there is a critical need to delineate the processes driving ER+ breast cancer progression and identify new biomarkers that can be targeted in combination with ER-targeted therapies. An emerging biomarker of increased breast cancer risk and aggressive tumor behavior is oncogenic PELP1 (i.e., partially localized to the cytoplasm; cyto PELP1). PELP1 is typically located in the nucleus in normal breast tissue; however, partial to complete localization of PELP1 to the cytoplasm has been observed in up to 50% of PELP1+ breast tumors. Although a number of studies have implicated oncogenic PELP1 in luminal breast cancer biology, the mechanisms underlying oncogenic PELP1 actions in cancer remain poorly defined. To elucidate the impact of oncogenic PELP1 on steroid hormone receptor (SR) signaling pathways and transcription programs, we generated SR+ breast cancer cell models expressing vector control, wild-type (nuclear) PELP1, and oncogenic (cyto) PELP1. Herein, we identified AIB1 (amplified in breast cancer 1; ER coactivator) as a preferential binding partner of oncogenic PELP1. In particular, our data demonstrate that oncogenic PELP1 overexpression increases activation (i.e., phosphorylation) of AIB1, enhances tumorsphere formation in SR+ breast cancer models, and upregulates specific target genes identified through RNA-Seq analysis that are related to cell survival, breast cancer progression, and stem/progenitor formation independent of hormone stimulation. Knockdown of AIB1 inhibits oncogenic PELP1-induced tumorsphere formation and downregulates oncogenic PELP1 target genes. Moreover, knockdown of PELP1 in AIB1-mouse derived tumor cells results in decreased tumor growth in vivo. To our knowledge, our findings are the first to directly link oncogenic PELP1-induced phenotypes to AIB1 in breast cancer. Our studies suggest that directly targeting PELP1 may halt tumor progression, particularly in the context of AIB1-mediated tumorigenesis. Taken together, our data highlight the oncogenic PELP1/AIB1 interaction as an important hormone-independent mechanism of increased breast tumor cell survival and altered cell fate, and as an important mediator of disease progression. In sum, we conclude that oncogenic PELP1 and AIB1 could be used as biomarkers in conjunction with each other to identify breast cancer patients likely to respond to therapeutic strategies designed to selectively target PELP1, AIB1, or the oncogenic PELP1/AIB1 signaling and transcriptional complex. Citation Format: Thu H. Truong, Hsiangyu Hu, Julie H. Ostrander, Carol A. Lange. PELP1 and AIB1 ","PeriodicalId":427521,"journal":{"name":"Personalized Risk","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116961054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract A31: Risk stratification of ductal carcinoma in situ: Analytical validation of a prognostic test analyzing live-primary cells via phenotypic biomarkers and machine learning at single-cell resolution","authors":"A. Chander, Michael S. Manak, J. Varsanik, B. Hogan, G. Sant, K. Knopf","doi":"10.1158/1557-3125.ADVBC17-A31","DOIUrl":"https://doi.org/10.1158/1557-3125.ADVBC17-A31","url":null,"abstract":"Largely due to tumor heterogeneity, risk stratification of patients diagnosed with ductal carcinoma in situ (DCIS) of the breast remains a significant challenge. Management of DCIS is also problematic as we wish to personalize treatment of a patient’s tumor in order to avoid overtreatment of lower-risk lesions or undertreatment of DCIS that may recur or progress into invasive cancer. Matching treatment to the underlying severity of the illness is key to practicing cost-effective cancer care in an era where this is a very large concern to society. The aim of this study was to analytically validate a precision risk-stratification tool based on phenotype, which is capable of predicting which patients will develop invasive cancer with greater than 80% sensitivity and specificity. Leveraging the novel capability to rapidly culture primary breast biopsy cells, we present a “biopsy-on-a-chip” microfluidic platform that quantifies dynamic and static phenotypic biomarkers via machine vision to generate predictive clinical scores via machine learning algorithms to determine if a DCIS patient will experience invasive cancer. 47 consecutive lumpectomy or mastectomy samples were collected and objectively analyzed in a blinded study, measuring 1000 phenotypic biomarkers with single-cell resolution using machine vision software. Biomarker measurements were input into machine learning algorithms to develop predictive statistical algorithms. Statistical algorithms were able to independently predict surgical adverse pathology features such as extranodal extension, grade, lymphovascular invasion, lymph invasion, lobular carcinoma in situ (LCIS), and DCIS with sensitivities and specificities greater than 90%. Additional machine learning based algorithms were able to predict if DCIS patients were more likely to develop subsequent metastasis as measured by lymphovascular invasion and/or lymphatic invasion with area under the curve (AUC) > 0.85. This study is the first study to demonstrate the prediction of breast cancer adverse pathology features from live primary biopsy cells and provides the basis to develop a powerful precision risk-stratification tool to risk-stratify DCIS. Furthermore, the methodology described and its ability to rapidly analyze primary breast biopsy tissue with single-cell resolution in a high-throughput manner engenders a powerful research tool to further understand tumor heterogeneity in breast cancer towards the development of personalized therapeutics. Applications of cost effectiveness analysis to our methodology will achieve the triple goal of providing cost-effective, patient-centered, and appropriate breast cancer and DCIS care. Note: This abstract was not presented at the conference. Citation Format: Ashok Chander, Michael Manak, Jonathan Varsanik, Brad Hogan, Grannum Sant, Kevin Knopf. Risk stratification of ductal carcinoma in situ: Analytical validation of a prognostic test analyzing live-primary cells via phenotypic biomarkers and m","PeriodicalId":427521,"journal":{"name":"Personalized Risk","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127736919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract A29: Investigation of RECQL variants in European and African American breast cancer cohorts","authors":"Madison R. Chandler, Sydney Bergstresser, Anna L. W. Huskey, Elizabeth Stallworth, Amber Davis, Holly Dean, Brandon Johnson, Nancy D. Merner","doi":"10.1158/1557-3125.ADVBC17-A29","DOIUrl":"https://doi.org/10.1158/1557-3125.ADVBC17-A29","url":null,"abstract":"Although an average woman in the United States can have a 12.5% lifetime risk of developing breast cancer (BC), inherited genetic risk variants can greatly influence a woman’s overall lifetime risk. Genes that harbor BC risk variants are referred to as BC susceptibility genes. Unfortunately, mutations in known BC susceptibility genes only explain approximately 35% of hereditary BC cases, leaving a large portion, approximately 65%, genetically unexplained. With the introduction of next-generation sequencing, several attempts have been carried out to identify additional hereditary BC susceptibility genes using whole-exome sequencing. The majority of these studies were relatively unsuccessful; however, Cybulski et al. (2015) successfully associated two rare truncation variants in RECQL, p.K555delinsMYKLIHYSFR and p.R215*, in a Polish and French-Canadian cohort, respectively. Subsequently, two additional studies were carried out in northern and southern regions of China, which also confirmed that overtly deleterious coding mutations in RECQL are associated with familial BC. Herein, we investigated RECQL variants in BC-affected African Americans (AAs) and European Americans (EAs). To our knowledge, this study represents the first attempt to identify an association between RECQL variants and BC cases in the United States. We initially screened all RECQL coding exons using polymerase chain reaction and Sanger sequencing in 49 BC cases (19 AAs and 30 EAs) from Alabama. Primarily synonymous variants were detected in both ethnicities; thus, in order to further investigate the role of RECQL synonymous variants in BC risk, we analyzed RECQL in blood-derived exomes of 168 and 580 BC-affected AAs and EAs, respectively, from The Cancer Genome Atlas (TCGA) project using an in-house bioinformatics pipeline. A case-control analysis revealed that all rare synonymous variants detected in EA BC cases were associated with BC, and p.S64= was significantly associated in both ethnicities. Interestingly, only one truncation variant was detected (p.Y492*) in all 748 BC cases analyzed. Unlike previous findings, this preliminary analysis suggests that rare RECQL synonymous variants may also increase an individual’s lifetime risk of developing BC; further investigation is warranted. Citation Format: Madison R. Chandler, Sydney Bergstresser, Anna LW Huskey, Elizabeth Stallworth, Amber Davis, Holly Dean, Brandon Johnson, Nancy D. Merner. Investigation of RECQL variants in European and African American breast cancer cohorts [abstract]. In: Proceedings of the AACR Special Conference: Advances in Breast Cancer Research; 2017 Oct 7-10; Hollywood, CA. Philadelphia (PA): AACR; Mol Cancer Res 2018;16(8_Suppl):Abstract nr A29.","PeriodicalId":427521,"journal":{"name":"Personalized Risk","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129444722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}