Person: Brachtel, Elena
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Brachtel
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Elena
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Brachtel, Elena
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Publication Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast(Public Library of Science, 2014) Dong, Fei; Irshad, Humayun; Oh, Eun-Yeong; Lerwill, Melinda F.; Brachtel, Elena; Jones, Nicholas C.; Knoblauch, Nicholas W.; Montaser-Kouhsari, Laleh; Johnson, Nicole B.; Rao, Luigi K. F.; Faulkner-Jones, Beverly; Wilbur, David; Schnitt, Stuart; Beck, AndrewThe categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions.Publication Mitotic Figure Recognition: Agreement among Pathologists and Computerized Detector(IOS Press, 2012) Malon, Christopher; Brachtel, Elena; Cosatto, Eric; Graf, Hans Peter; Kurata, Atsushi; Kuroda, Masahiko; Meyer, John S.; Saito, Akira; Wu, Shulin; Yagi, YukakoDespite the prognostic importance of mitotic count as one of the components of the Bloom – Richardson grade [3], several studies ([2, 9, 10]) have found that pathologists’ agreement on the mitotic grade is fairly modest. Collecting a set of more than 4,200 candidate mitotic figures, we evaluate pathologists' agreement on individual figures, and train a computerized system for mitosis detection, comparing its performance to the classifications of three pathologists. The system’s and the pathologists’ classifications are based on evaluation of digital micrographs of hematoxylin and eosin stained breast tissue. On figures where the majority of pathologists agree on a classification, we compare the performance of the trained system to that of the individual pathologists. We find that the level of agreement of the pathologists ranges from slight to moderate, with strong biases, and that the system performs competitively in rating the ground truth set. This study is a step towards automatic mitosis count to accelerate a pathologist's work and improve reproducibility.Publication Blocking the formation of radiation–induced breast cancer stem cells(Impact Journals LLC, 2014) Wang, YangYang; Li, Wende; Patel, Shalin; Cong, Juan; Zhang, Nan; Sabbatino, Francesco; Liu, Xiaoyan; Qi, Yuan; Huang, Peigen; Lee, Hang; Taghian, Alphonse; Li, Jian-Jian; DeLeo, Albert B.; Ferrone, Soldano; Epperly, Michael W.; Ferrone, Cristina; Ly, Amy; Brachtel, Elena; Wang, XinhuiThe goal of adjuvant (post-surgery) radiation therapy (RT) for breast cancer (BC) is to eliminate residual cancer cells, leading to better local tumor control and thus improving patient survival. However, radioresistance increases the risk of tumor recurrence and negatively affects survival. Recent evidence shows that breast cancer stem cells (BCSCs) are radiation-resistant and that relatively differentiated BC cells can be reprogrammed into induced BCSCs (iBCSCs) via radiation-induced re-expression of the stemness genes. Here we show that in irradiation (IR)-treated mice bearing syngeneic mammary tumors, IR-induced stemness correlated with increased spontaneous lung metastasis (51.7%). However, IR-induced stemness was blocked by targeting the NF-κB- stemness gene pathway with disulfiram (DSF)and Copper (Cu2+). DSF is an inhibitor of aldehyde dehydrogenase (ALDH) and an FDA-approved drug for treating alcoholism. DSF binds to Cu2+ to form DSF-Cu complexes (DSF/Cu), which act as a potent apoptosis inducer and an effective proteasome inhibitor, which, in turn, inhibits NF-κB activation. Treatment of mice with RT and DSF significantly inhibited mammary primary tumor growth (79.4%) and spontaneous lung metastasis (89.6%) compared to vehicle treated mice. This anti-tumor efficacy was associated with decreased stem cell properties (or stemness) in tumors. We expect that these results will spark clinical investigation of RT and DSF as a novel combinatorial treatment for breast cancer.Publication Origins of lymphatic and distant metastases in human colorectal cancer(American Association for the Advancement of Science (AAAS), 2017) Nahrendorf, Kamila; Reiter, Johannes; Brachtel, Elena; Lennerz, Jochen; van de Wetering, Marc; Rowan, Andrew; Cai, Tianxi; Clevers, Hans; Swanton, Charles; Nowak, Martin; Elledge, Stephen; Jain, RakeshThe spread of cancer cells from primary tumors to regional lymph nodes is often associated with reduced survival. One prevailing model to explain this association posits that fatal, distant metastases are seeded by lymph node metastases. This view provides a mechanistic basis for the TNM staging system and is the rationale for surgical resection of tumor-draining lymph nodes. Here we examine the evolutionary relationship between primary tumor, lymph node, and distant metastases in human colorectal cancer. Studying 213 archival biopsy samples from 17 patients, we used somatic variants in hypermutable DNA regions to reconstruct high-confidence phylogenetic trees. We found that in 65% of cases, lymphatic and distant metastases arose from independent subclones in the primary tumor, whereas in 35% of cases they shared common subclonal origin. Therefore, two different lineage relationships between lymphatic and distant metastases exist in colorectal cancer.Publication Prediction of primary breast cancer size and T-stage using micro-computed tomography in lumpectomy specimens(Medknow, 2015) Sarraj, WafaM; Tang, Rong; Najjar, Anas L; Griffin, Molly; Bui, Anthony H; Zambeli-Ljepovic, Alan; Senter-Zapata, Mike; Lewin-Berlin, Maya; Fernandez, Leopoldo; Buckley, Juliette; Ly, Amy; Brachtel, Elena; Aftreth, Owen; Gilbertson, John R; Yagi, Yukako; Gadd, Michele; Hughes, Kevin; Smith, BarbaraL; Michaelson, JamesSBackground: Histopathology is the only accepted method to measure and stage the breast tumor size. However, there is a need to find another method to measure and stage the tumor size when the pathological assessment is not available. Micro-computed tomography. (micro-CT) has the ability to measure tumor in three dimensions in an intact lumpectomy specimen. In this study, we aimed to determine the accuracy of micro-CT to measure and stage the primary tumor size in breast lumpectomy specimens, as compared to the histopathology. Materials and Methods: Seventy-two women who underwent lumpectomy surgery at the Massachusetts General Hospital Department of Surgery from June 2011 to September 2011, and from August 2013 to December 2013 participated in this study. The lumpectomy specimens were scanned using micro-CT followed by routine pathological processing. The maximum dimension of the invasive breast tumor was obtained from the micro-CT image and was compared to the corresponding pathology report for each subject. Results: The invasive tumor size measurement by micro-CT was underestimated in 24 cases. (33%), overestimated in 37 cases. (51%), and matched it exactly in 11 cases. (15%) compared to the histopathology measurement for all the cases. However, micro-CT T-stage classification differed from histopathology in only 11. (15.2%) with 6 cases. (8.3%) classified as a higher stage by micro-CT, and 5 cases. (6.9%) classified as lower compared to histopathology. In addition, micro-CT demonstrated a statically significant strong agreement (κ =0.6, P < 0.05) with pathological tumor size and staging for invasive ductal carcinoma. (IDC) group. In contrast, there was no agreement. (κ = −2, P = 0.67) between micro-CT and pathology in estimating and staging tumor size for invasive lobular carcinoma. (ILC) group. This could be explained by a small sample size. (7) for ILC group. Conclusions: Micro-CT is a promising modality for measuring and staging the IDC.