Literature DB >> 30364524

A METHOD FOR QUANTIFICATION OF CALPONIN EXPRESSION IN MYOEPITHELIAL CELLS IN IMMUNOHISTOCHEMICAL IMAGES OF DUCTAL CARCINOMA IN SITU.

Elliot Gray1, Elizabeth Mitchell2, Sonali Jindal2, Pepper Schedin2, Young Hwan Chang1.   

Abstract

Ductal carcinoma in situ (DCIS) is breast cancer confined within mammary ducts, surrounded by an intact myoepithelial cell layer that prevents local invasion. A DCIS diagnosis confers increased lifetime risk of developing invasive breast cancer (IBC) and results in surgical excision with radiation, and possibly endocrine- or chemo-therapy. DCIS is known to be over treated, with associated co-morbidities. Biomarkers are needed that delineate patients at low risk of DCIS progression from patients requiring more aggressive treatment. Investigating the role of myoepithelial cell differentiation in barrier function is anticipated to provide insight into DCIS progression and delineate between low and high risk lesions. Here, we develop a high throughput technique to assess loss of myoepithelial differentiation markers. This method facilitates automated analysis of a clinically relevant histopathologic feature, as demonstrated by a high correlation with pathologist annotation (r = 0.959), and further, contributes analytical foundations to a multiplexed immunohistochemistry (IHC) approach.

Entities:  

Keywords:  DCIS; calponin; feature engineering; invasive breast cancer; myoepithelial cell

Year:  2018        PMID: 30364524      PMCID: PMC6196724          DOI: 10.1109/ISBI.2018.8363692

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN: 1945-7928


  14 in total

1.  A nonlinear mapping approach to stain normalization in digital histopathology images using image-specific color deconvolution.

Authors:  Adnan Mujahid Khan; Nasir Rajpoot; Darren Treanor; Derek Magee
Journal:  IEEE Trans Biomed Eng       Date:  2014-06       Impact factor: 4.538

2.  Outcome of patients with ductal carcinoma in situ untreated after diagnostic biopsy: results from the Nurses' Health Study.

Authors:  Laura C Collins; Rulla M Tamimi; Heather J Baer; James L Connolly; Graham A Colditz; Stuart J Schnitt
Journal:  Cancer       Date:  2005-05-01       Impact factor: 6.860

Review 3.  Significance of immunohistochemistry in breast cancer.

Authors:  Dana Carmen Zaha
Journal:  World J Clin Oncol       Date:  2014-08-10

4.  Quantitative Multiplex Immunohistochemistry Reveals Myeloid-Inflamed Tumor-Immune Complexity Associated with Poor Prognosis.

Authors:  Takahiro Tsujikawa; Sushil Kumar; Rohan N Borkar; Vahid Azimi; Guillaume Thibault; Young Hwan Chang; Ariel Balter; Rie Kawashima; Gina Choe; David Sauer; Edward El Rassi; Daniel R Clayburgh; Molly F Kulesz-Martin; Eric R Lutz; Lei Zheng; Elizabeth M Jaffee; Patrick Leyshock; Adam A Margolin; Motomi Mori; Joe W Gray; Paul W Flint; Lisa M Coussens
Journal:  Cell Rep       Date:  2017-04-04       Impact factor: 9.423

5.  Computerized image analysis of Ki-67 in ductal breast carcinoma in situ.

Authors:  D G Menter; A Hoque; N Motiwala; A A Sahin; N Sneige; R Lieberman; S M Lippman
Journal:  Anal Quant Cytol Histol       Date:  2001-06       Impact factor: 0.302

Review 6.  Multiplexed immunohistochemistry, imaging, and quantitation: a review, with an assessment of Tyramide signal amplification, multispectral imaging and multiplex analysis.

Authors:  Edward C Stack; Chichung Wang; Kristin A Roman; Clifford C Hoyt
Journal:  Methods       Date:  2014-09-19       Impact factor: 3.608

7.  Myoepithelial cell differentiation markers in ductal carcinoma in situ progression.

Authors:  Tanya D Russell; Sonali Jindal; Samiat Agunbiade; Dexiang Gao; Megan Troxell; Virginia F Borges; Pepper Schedin
Journal:  Am J Pathol       Date:  2015-09-04       Impact factor: 4.307

Review 8.  Myoepithelial cells: their origin and function in breast morphogenesis and neoplasia.

Authors:  Thorarinn Gudjonsson; Melissa C Adriance; Mark D Sternlicht; Ole W Petersen; Mina J Bissell
Journal:  J Mammary Gland Biol Neoplasia       Date:  2005-07       Impact factor: 2.673

9.  Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.

Authors:  Yoichiro Yamamoto; Akira Saito; Ayako Tateishi; Hisashi Shimojo; Hiroyuki Kanno; Shinichi Tsuchiya; Ken-Ichi Ito; Eric Cosatto; Hans Peter Graf; Rodrigo R Moraleda; Roland Eils; Niels Grabe
Journal:  Sci Rep       Date:  2017-04-25       Impact factor: 4.379

10.  Automated Classification of Benign and Malignant Proliferative Breast Lesions.

Authors:  Evani Radiya-Dixit; David Zhu; Andrew H Beck
Journal:  Sci Rep       Date:  2017-08-29       Impact factor: 4.379

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