Journal of Pathology and Translational Medicine

Woo-Hee Jung

4 Articles

Pathologic Evaluation of Breast Cancer after Neoadjuvant Therapy: Cheol Keun Park, Woo-Hee Jung, Ja Seung Koo; J Pathol Transl Med. 2016;50(3):173-180. Published online April 11, 2016; DOI: https://doi.org/10.4132/jptm.2016.02.02

15,100 View
521 Download
33 Web of Science
32 Crossref

Breast cancer, one of the most common cancers in women, has various treatment modalities. Neoadjuvant therapy (NAT) has been used in many clinical trials because it is easy to evaluate the treatment response to therapeutic agents in a short time period; consequently, NAT is currently a standard treatment modality for large-sized and locally advanced breast cancers, and its use in early-stage breast cancer is becoming more common. Thus, chances to encounter breast tissue from patients treated with NAT is increasing. However, systems for handling and evaluating such specimens have not been established. Several evaluation systems emphasize a multidisciplinary approach to increase the accuracy of breast cancer assessment. Thus, detailed and systematic evaluation of clinical, radiologic, and pathologic findings is important. In this review, we compare the major problems of each evaluation system and discuss important points for handling and evaluating NAT-treated breast specimens.

Citations

Citations to this article as recorded by

Evaluating the Tumor Burden, Histological Changes, and Immune Landscape of Breast Cancer Post-neoadjuvant Chemotherapy: Insights From 50 Cases
Arasi Rajesh, Dharma Saranya Gurusamy, Rajalakshmi Manikkam
Cureus.2025;[Epub] CrossRef
Prognostic value of residual cancer burden after neoadjuvant chemotherapy in breast cancer: a comprehensive subtype-specific analysis
Soo-Young Lee, Tae-Kyung Yoo, Sae Byul Lee, Jisun Kim, Il Yong Chung, Beom Seok Ko, Hee Jeong Kim, Jong Won Lee, Byung Ho Son
Scientific Reports.2025;[Epub] CrossRef
Good practice: The experiences with the utilization of residual cancer burden—A single institution study
Anita Sejben, Fanni Hegedűs, Szintia Almási, Márton Berta, Orsolya Oláh‐Németh, Tamás Zombori
Thoracic Cancer.2023; 14(11): 963. CrossRef
Assessing the Correlation of Rate of Pathological Complete Response and Outcome in Post Neoadjuvant Chemotherapy Setting and Molecular Subtypes of Breast Cancer
Ahmad Omair, Abdulmohsen Alkushi, Ghaida Alamri, Talal Almojel, Sara Alsadun, Emad Masuadi, Haitham Arabi, Amin E Mohamed, Omalkhair A Abulkhair
Cureus.2023;[Epub] CrossRef
Compression OCT-elastography combined with speckle-contrast analysis as an approach to the morphological assessment of breast cancer tissue
Anton A. Plekhanov, Ekaterina V. Gubarkova, Marina A. Sirotkina, Alexander A. Sovetsky, Dmitry A. Vorontsov, Lev A. Matveev, Sergey S. Kuznetsov, Alexandra Y. Bogomolova, Alexey Y. Vorontsov, Alexander L. Matveyev, Sergey V. Gamayunov, Elena V. Zagaynova,
Biomedical Optics Express.2023; 14(6): 3037. CrossRef
Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning
Xiangyu Li, Xinjie Liang, Gongning Luo, Wei Wang, Kuanquan Wang, Shuo Li
Medical Image Analysis.2023; 90: 102944. CrossRef
Concurrent Chemo-radiation As a Means of Achieving Pathologic Complete Response in Triple Negative Breast Cancer
Maryam Nemati Shafaee, Shalini Makawita, Bora Lim, Matthew J Ellis, Michelle S Ludwig
Clinical Breast Cancer.2022; 22(4): e536. CrossRef
Pathology after neoadjuvant treatment – How to assess residual disease
Giuseppe Viale, Nicola Fusco
The Breast.2022; 62: S25. CrossRef
Efficacy Evaluation of Neoadjuvant Chemotherapy in Breast Cancer by MRI
Yongguang Liu, Mingxiang Wu, Wenyong Tan, Jingshan Gong, Jie Ma, Mohammad Farukh Hashmi
Contrast Media & Molecular Imaging.2022;[Epub] CrossRef
Predictive Role of Soluble IL-6R, TNF-R1/2, and Cell Adhesion Molecules Serum Levels in the Preoperative and Adjuvant Therapy in Women with Nonmetastatic Breast Cancer: A Preliminary Study
Weronika Bulska-Będkowska, Paulina Czajka-Francuz, Sylwia Cisoń-Jurek, Aleksander J. Owczarek, Tomasz Francuz, Jerzy Chudek
Journal of Interferon & Cytokine Research.2022; 42(11): 557. CrossRef
The prognostic role of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy: A dose-response meta-analysis
Jinzhao Liu, Yifei Li, Weifang Zhang, Chenhui Yang, Chao Yang, Liang Chen, Mingjian Ding, Liang Zhang, Xiaojun Liu, Guozhong Cui, Yunjiang Liu
Frontiers in Surgery.2022;[Epub] CrossRef
The Role of miR-375-3p, miR-210-3p and Let-7e-5p in the Pathological Response of Breast Cancer Patients to Neoadjuvant Therapy
Lorena Alexandra Lisencu, Andrei Roman, Simona Visan, Eduard-Alexandru Bonci, Andrei Pașca, Emilia Grigorescu, Elena Mustea, Andrei Cismaru, Alexandru Irimie, Cosmin Lisencu, Loredana Balacescu, Ovidiu Balacescu, Oana Tudoran
Medicina.2022; 58(10): 1494. CrossRef
Post-Neoadjuvant Treatment Strategies for Patients with Early Breast Cancer
Elisa Agostinetto, Flavia Jacobs, Véronique Debien, Alex De Caluwé, Catalin-Florin Pop, Xavier Catteau, Philippe Aftimos, Evandro de Azambuja, Laurence Buisseret
Cancers.2022; 14(21): 5467. CrossRef
Tumor Microenvironment in Breast Cancer—Updates on Therapeutic Implications and Pathologic Assessment
Joshua J. Li, Julia Y. Tsang, Gary M. Tse
Cancers.2021; 13(16): 4233. CrossRef
SPIE-AAPM-NCI BreastPathQ challenge: an image analysis challenge for quantitative tumor cellularity assessment in breast cancer histology images following neoadjuvant treatment
Nicholas Petrick, Shazia Akbar, Kenny H. Cha, Sharon Nofech-Mozes, Berkman Sahiner, Marios A. Gavrielides, Jayashree Kalpathy-Cramer, Karen Drukker, Anne L. Martel, for the BreastPathQ Challenge Group
Journal of Medical Imaging.2021;[Epub] CrossRef
Diagnostic performance of digital breast tomosynthesis for predicting response to neoadjuvant systemic therapy in breast cancer patients: A comparison with magnetic resonance imaging, ultrasound, and full-field digital mammography
Ryusuke Murakami, Hitomi Tani, Shinichiro Kumita, Nachiko Uchiyama
Acta Radiologica Open.2021;[Epub] CrossRef
Los márgenes
Laia Bernet, María Angeles Montero Fernández
Revista de Senología y Patología Mamaria.2021; 34: S25. CrossRef
Neoadjuvant chemotherapy in non‐metastatic breast cancer: a study on practice trends in a regional cancer treatment service
Edmond Ang, Navin Wewala, Rebecca Carroll, Garry Forgeson, Malcolm Anderson, Jennifer Fernando, Jody Jordan, Richard Isaacs
Internal Medicine Journal.2020; 50(3): 315. CrossRef
Examination of Tumor Regression Grading Systems in Breast Cancer Patients Who Received Neoadjuvant Therapy
Anita Sejben, Renáta Kószó, Zsuzsanna Kahán, Gábor Cserni, Tamás Zombori
Pathology & Oncology Research.2020; 26(4): 2747. CrossRef
Integrating evolutionary dynamics into cancer therapy
Robert A. Gatenby, Joel S. Brown
Nature Reviews Clinical Oncology.2020; 17(11): 675. CrossRef
Assessing the accuracy of conventional gadolinium‐enhanced breast MRI in measuring the nodal response to neoadjuvant chemotherapy (NAC) in breast cancer
Lisa Christine Murphy, Edel Marie Quinn, Zeeshan Razzaq, Claire Brady, Vicki Livingstone, Lorna Duddy, Josephine Barry, Henry Paul Redmond, Mark Anthony Corrigan
The Breast Journal.2020; 26(11): 2151. CrossRef
Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning
Joon Ho Choi, Hyun-Ah Kim, Wook Kim, Ilhan Lim, Inki Lee, Byung Hyun Byun, Woo Chul Noh, Min-Ki Seong, Seung-Sook Lee, Byung Il Kim, Chang Woon Choi, Sang Moo Lim, Sang-Keun Woo
Scientific Reports.2020;[Epub] CrossRef
Patterns of Regression in Breast Cancer after Primary Systemic Treatment
Tamás Zombori, Gábor Cserni
Pathology & Oncology Research.2019; 25(3): 1153. CrossRef
The Role of Neutrophil-lymphocyte Ratio and Platelet-lymphocyte Ratio in Predicting Neoadjuvant Chemotherapy Response in Breast Cancer
Hee Yeon Kim, Tae Hyun Kim, Hye Kyoung Yoon, Anbok Lee
Journal of Breast Cancer.2019; 22(3): 425. CrossRef
Higher underestimation of tumour size post-neoadjuvant chemotherapy with breast magnetic resonance imaging (MRI)—A concordance comparison cohort analysis
Wen-Pei Wu, Hwa-Koon Wu, Chih-Jung Chen, Chih-Wie Lee, Shou-Tung Chen, Dar-Ren Chen, Chen-Te Chou, Chi Wei Mok, Hung-Wen Lai, Pascal A. T. Baltzer
PLOS ONE.2019; 14(10): e0222917. CrossRef
Multimodal image-guided surgery of HER2-positive breast cancer using [111In]In-DTPA-trastuzumab-IRDye800CW in an orthotopic breast tumor model
Marion M. Deken, Desirée L. Bos, Willemieke S. F. J. Tummers, Taryn L. March, Cornelis J. H. van de Velde, Mark Rijpkema, Alexander L. Vahrmeijer
EJNMMI Research.2019;[Epub] CrossRef
Mammographic density is a potential predictive marker of pathological response after neoadjuvant chemotherapy in breast cancer
Ida Skarping, Daniel Förnvik, Hanna Sartor, Uffe Heide-Jørgensen, Sophia Zackrisson, Signe Borgquist
BMC Cancer.2019;[Epub] CrossRef
ALDH1 and tumor infiltrating lymphocytes as predictors for neoadjuvant chemotherapy response in breast cancer
Anbok Lee, Kyu Yeoun Won, Sung-Jig Lim, Sun Young Cho, Sang-Ah Han, SaeGwang Park, Jeong-Yoon Song
Pathology - Research and Practice.2018; 214(5): 619. CrossRef
Early Prediction of Response to Neoadjuvant Chemotherapy Using Dynamic Contrast-Enhanced MRI and Ultrasound in Breast Cancer
Yunju Kim, Sung Hun Kim, Byung Joo Song, Bong Joo Kang, Kwang-il Yim, Ahwon Lee, Yoonho Nam
Korean Journal of Radiology.2018; 19(4): 682. CrossRef
Outcomes of neoadjuvant and adjuvant chemotherapy in stage 2 and 3 non-small cell lung cancer: an analysis of the National Cancer Database
Matthew MacLean, Xin Luo, Shidan Wang, Kemp Kernstine, David E. Gerber, Yang Xie
Oncotarget.2018; 9(36): 24470. CrossRef
Automatic cellularity assessment from post‐treated breast surgical specimens
Mohammad Peikari, Sherine Salama, Sharon Nofech‐Mozes, Anne L. Martel
Cytometry Part A.2017; 91(11): 1078. CrossRef
The importance of tissue confirmation of metastatic disease in patients with breast cancer: lesson from a brain metastasis case
Jingxian Ding, Pinghua Hu, Jun Chen, Xiaobo Wu, Yali Cao
Oncoscience.2016; 3(9-10): 268. CrossRef

Interobserver Variability of Ki-67 Measurement in Breast Cancer: Yul Ri Chung, Min Hye Jang, So Yeon Park, Gyungyub Gong, Woo-Hee Jung, The Korean Breast Pathology Ki- Study Group; J Pathol Transl Med. 2016;50(2):129-137. Published online February 15, 2016; DOI: https://doi.org/10.4132/jptm.2015.12.24

10,945 View
123 Download
25 Web of Science
27 Crossref

Abstract PDF

Background
As measurement of Ki-67 proliferation index is an important part of breast cancer diagnostics, we conducted a multicenter study to examine the degree of concordance in Ki-67 counting and to find factors that lead to its variability. Methods: Thirty observers from thirty different institutions reviewed Ki-67–stained slides of 20 different breast cancers on whole sections and tissue microarray (TMA) by online system. Ten of the 20 breast cancers had hot spots of Ki-67 expression. Each observer scored Ki-67 in two different ways: direct counting (average vs. hot spot method) and categorical estimation. Intraclass correlation coefficient (ICC) of Ki-67 index was calculated for comparative analysis. Results: For direct counting, ICC of TMA was slightly higher than that of whole sections using average method (0.895 vs 0.858). The ICC of tumors with hot spots was lower than that of tumors without (0.736 vs 0.874). In tumors with hot spots, observers took an additional counting from the hot spot; the ICC of whole sections using hot spot method was still lower than that of TMA (0.737 vs 0.895). In categorical estimation, Ki-67 index showed a wide distribution in some cases. Nevertheless, in tumors with hot spots, the range of distribution in Ki-67 categories was decreased with hot spot method and in TMA platform. Conclusions: Interobserver variability of Ki-67 index for direct counting and categorical estimation was relatively high. Tumors with hot spots showed greater interobserver variability as opposed to those without, and restricting the measurement area yielded lower interobserver variability.

Citations

Citations to this article as recorded by

Comparative analysis of Ki-67 labeling index morphometry using deep learning, conventional image analysis, and manual counting
Mohammad Rizwan Alam, Kyung Jin Seo, Kwangil Yim, Phoebe Liang, Joe Yeh, Chifu Chang, Yosep Chong
Translational Oncology.2025; 51: 102159. CrossRef
Machine Learning-Based Approaches for Breast Density Estimation from Mammograms: A Comprehensive Review
Khaldoon Alhusari, Salam Dhou
Journal of Imaging.2025; 11(2): 38. CrossRef
Letter re: A critical appraisal of the DATA trial analysis on the prognostic and predictive value of the luminal-like subtype
M. Rizk, K. Mokbel
ESMO Open.2025; 10(5): 105067. CrossRef
Ki-67 Testing in Breast Cancer: Assessing Variability With Scoring Methods and Specimen Types and the Potential Subsequent Impact on Therapy Eligibility
Therese Bocklage, Virgilius Cornea, Caylin Hickey, Justin Miller, Jessica Moss, Mara Chambers, S. Emily Bachert
Applied Immunohistochemistry & Molecular Morphology.2024; 32(3): 119. CrossRef
Interobserver agreement and diagnostic challenges of Congo red staining for amyloid detection on fat pad aspiration biopsies
Levent Trabzonlu, T. Leif Helland, Melanie C. Kwan, Nathalie Kumiega, M. Lisa Zhang, Ivan Chebib, Vanda F. Torous
Journal of the American Society of Cytopathology.2024; 13(5): 359. CrossRef
Assessment of the Predictive Role of Ki-67 in Breast Cancer Patients’ Responses to Neoadjuvant Chemotherapy
Ghizlane Rais, Rania Mokfi, Farah Boutaggount, Meryem Maskrout, Soundouss Bennour, Chaymae Senoussi, Fadoua Rais
European Journal of Breast Health.2024; : 199. CrossRef
Improving the accuracy of reporting Ki-67 IHC by using an AI tool
Sahil Ajit Saraf, Aahan Singh, Wai Po Kevin Teng, Sencer Karakaya, M. Logaswari, Kaveh Taghipour, Rajasa Jialdasani, Li Yan Khor, Kiat Hon Lim, Sathiyamoorthy Selvarajan, Vani Ravikumar, Md Ali Osama, Priti Chatterjee, Santosh KV
Heliyon.2024; 10(22): e40193. CrossRef
Predictive Value of Ki-67 Index in Evaluating Sporadic Vestibular Schwannoma Recurrence: Systematic Review and Meta-analysis
Kunal Vakharia, Hirotaka Hasegawa, Christopher Graffeo, Mohammad H. A. Noureldine, Salomon Cohen-Cohen, Avital Perry, Matthew L. Carlson, Colin L. W. Driscoll, Maria Peris-Celda, Jamie J. Van Gompel, Michael J. Link
Journal of Neurological Surgery Part B: Skull Base.2023; 84(02): 119. CrossRef
Venous invasion and lymphatic invasion are correlated with the postoperative prognosis of pancreatic neuroendocrine neoplasm
Sho Kiritani, Junichi Arita, Yuichiro Mihara, Rihito Nagata, Akihiko Ichida, Yoshikuni Kawaguchi, Takeaki Ishizawa, Nobuhisa Akamatsu, Junichi Kaneko, Kiyoshi Hasegawa
Surgery.2023; 173(2): 365. CrossRef
Automated Molecular Subtyping of Breast Carcinoma Using Deep Learning Techniques
S. Niyas, Ramya Bygari, Rachita Naik, Bhavishya Viswanath, Dhananjay Ugwekar, Tojo Mathew, J Kavya, Jyoti R Kini, Jeny Rajan
IEEE Journal of Translational Engineering in Health and Medicine.2023; 11: 161. CrossRef
Grade Progression and Intrapatient Tumor Heterogeneity as Potential Contributors to Resistance in Gastroenteropancreatic Neuroendocrine Tumors
Diana Grace Varghese, Jaydira Del Rivero, Emily Bergsland
Cancers.2023; 15(14): 3712. CrossRef
Diagnostic Role and Prognostic Impact of PSAP Immunohistochemistry: A Tissue Microarray Study on 31,358 Cancer Tissues
Laura Sophie Tribian, Maximilian Lennartz, Doris Höflmayer, Noémi de Wispelaere, Sebastian Dwertmann Rico, Clara von Bargen, Simon Kind, Viktor Reiswich, Florian Viehweger, Florian Lutz, Veit Bertram, Christoph Fraune, Natalia Gorbokon, Sören Weidemann, C
Diagnostics.2023; 13(20): 3242. CrossRef
AI-Powered Segmentation of Invasive Carcinoma Regions in Breast Cancer Immunohistochemical Whole-Slide Images
Yiqing Liu, Tiantian Zhen, Yuqiu Fu, Yizhi Wang, Yonghong He, Anjia Han, Huijuan Shi
Cancers.2023; 16(1): 167. CrossRef
Expression of estrogen and progesterone receptors, HER2 protein and Ki-67 proliferation index in breast carcinoma in both tumor tissue and tissue microarray
UP Hacısalihoğlu, MA Dogan
Biotechnic & Histochemistry.2022; 97(4): 298. CrossRef
Diffusive Ki67 and vimentin are associated with worse recurrence-free survival of upper tract urothelial carcinoma: A retrospective cohort study from bench to bedside
Che Hsueh Yang, Wei Chun Weng, Yen Chuan Ou, Yi Sheng Lin, Li Hua Huang, Chin Heng Lu, Tang Yi Tsao, Chao Yu Hsu, Min Che Tung
Urologic Oncology: Seminars and Original Investigations.2022; 40(3): 109.e21. CrossRef
Should Ki-67 be adopted to select breast cancer patients for treatment with adjuvant abemaciclib?
P. Tarantino, H.J. Burstein, N.U. Lin, I.E. Krop, E.P. Winer, S.J. Schnitt, E.P. Hamilton, S.A. Hurvitz, H.S. Rugo, G. Curigliano, S.M. Tolaney
Annals of Oncology.2022; 33(3): 234. CrossRef
A novel deep classifier framework for automated molecular subtyping of breast carcinoma using immunohistochemistry image analysis
Tojo Mathew, S. Niyas, C.I. Johnpaul, Jyoti R. Kini, Jeny Rajan
Biomedical Signal Processing and Control.2022; 76: 103657. CrossRef
Deep learning for the standardized classification of Ki-67 in vulva carcinoma: A feasibility study
Matthias Choschzick, Mariam Alyahiaoui, Alexander Ciritsis, Cristina Rossi, André Gut, Patryk Hejduk, Andreas Boss
Heliyon.2021; 7(7): e07577. CrossRef
Oncotype DX Predictive Nomogram for Recurrence Score Output: The Novel System ADAPTED01 Based on Quantitative Immunochemistry Analysis
Fabio Marazzi, Roberto Barone, Valeria Masiello, Valentina Magri, Antonino Mulè, Angela Santoro, Federica Cacciatori, Luca Boldrini, Gianluca Franceschini, Francesca Moschella, Giuseppe Naso, Silverio Tomao, Maria Antonietta Gambacorta, Giovanna Mantini,
Clinical Breast Cancer.2020; 20(5): e600. CrossRef
Study of Ki-67 index in the molecular subtypes of breast cancer: Inter-observer variability and automated scoring
Divya Meermira, Meenakshi Swain, Swarnalata Gowrishankar
Indian Journal of Cancer.2020; 57(3): 289. CrossRef
Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning
Darshana Govind, Kuang-Yu Jen, Karen Matsukuma, Guofeng Gao, Kristin A. Olson, Dorina Gui, Gregory. E. Wilding, Samuel P. Border, Pinaki Sarder
Scientific Reports.2020;[Epub] CrossRef
Practical approaches to automated digital image analysis of Ki-67 labeling index in 997 breast carcinomas and causes of discordance with visual assessment
Ah-Young Kwon, Ha Young Park, Jiyeon Hyeon, Seok Jin Nam, Seok Won Kim, Jeong Eon Lee, Jong-Han Yu, Se Kyung Lee, Soo Youn Cho, Eun Yoon Cho, Irina V. Lebedeva
PLOS ONE.2019; 14(2): e0212309. CrossRef
Evaluation of Ki-67 Index in Core Needle Biopsies and Matched Breast Cancer Surgical Specimens
Soomin Ahn, Junghye Lee, Min-Sun Cho, Sanghui Park, Sun Hee Sung
Archives of Pathology & Laboratory Medicine.2018; 142(3): 364. CrossRef
Assessment of Ki-67 for Predicting Effective Prognosis in Breast Cancer Subtypes
Sangjung Park, Sunyoung Park, Jungho Kim, Sungwoo Ahn, Kwang Hwa Park, Hyeyoung Lee
Biomedical Science Letters.2018; 24(1): 9. CrossRef
Quantitative tumor heterogeneity assessment on a nuclear population basis
Anne‐Sofie Wessel Lindberg, Knut Conradsen, Rasmus Larsen, Michael Friis Lippert, Rasmus Røge, Mogens Vyberg
Cytometry Part A.2017; 91(6): 574. CrossRef
A comparison of Ki-67 counting methods in luminal Breast Cancer: The Average Method vs. the Hot Spot Method
Min Hye Jang, Hyun Jung Kim, Yul Ri Chung, Yangkyu Lee, So Yeon Park, William B. Coleman
PLOS ONE.2017; 12(2): e0172031. CrossRef
A Novel Breast Cancer Index for Prediction of Distant Recurrence in HR+ Early-Stage Breast Cancer with One to Three Positive Nodes
Yi Zhang, Brock E. Schroeder, Piiha-Lotta Jerevall, Amy Ly, Hannah Nolan, Catherine A. Schnabel, Dennis C. Sgroi
Clinical Cancer Research.2017; 23(23): 7217. CrossRef

Primary Mucinous Cystadenocarcinoma of the Breast: Cytologic Finding and Expression of MUC5 Are Different from Mucinous Carcinoma: Sung Eun Kim, Ji Hye Park, SoonWon Hong, Ja Seung Koo, Joon Jeong, Woo-Hee Jung; Korean J Pathol. 2012;46(6):611-616. Published online December 26, 2012; DOI: https://doi.org/10.4132/KoreanJPathol.2012.46.6.611

8,466 View
64 Download
14 Crossref

Abstract PDF

Mucinous cystadenocarcinoma (MCA) in the breast is a rare neoplasm. There have been 13 cases of primary breast MCA reported. The MCA presents as a large, partially cystic mass in postmenopausal woman with a good prognosis. The microscopic findings resemble those of ovarian, pancreatic, or appendiceal MCA. The aspiration findings showed mucin-containing cell clusters in the background of mucin and necrotic material. The cell clusters had intracytoplasmic mucin displacing atypical nuclei to the periphery. Histologically, the tumor revealed an abundant mucin pool with small floating clusters of mucin-containing tumor cells. There were also small cysts lined by a single layer of tall columnar mucinous cells, resembling those of the uterine endocervix. The cancer cells were positive for mucin (MUC) 5 and negative for MUC2 and MUC6. This mucin profile is different from ordinary mucinous carcinoma and may be a unique characteristic of breast MCA.

Citations

Citations to this article as recorded by

Mucinous cystadenocarcinoma of the breast harbours TRPS1 expressions and PIK3CA alterations
Wei‐Yu Chen, Yu‐Hsuan Hu, Yu‐Hsin Tsai, Jen‐Fan Hang, Puay Hoon Tan, Chih‐Jung Chen
Histopathology.2024; 84(3): 550. CrossRef
Pure mucinous adenocarcinoma of the breast with the rare lymphoplasmacytic infiltration: A case report with review of literature
Yash Hasmukhbhai Prajapati, Vishal Bhabhor, Kahan Samirkumar Mehta, Mithoon Barot, Husen Boriwala, Mohamed Omar
Clinical Case Reports.2024;[Epub] CrossRef
HER2‐positive mucinous cystadenocarcinoma of the breast coexisting with invasive lobular carcinoma: A case report and review of the literature
Ismail Guzelis, Betul Bolat Kucukzeybek, Mehmet Ali Uyaroglu, Melek Bekler Gokova, Gulten Sezgin, Yuksel Kucukzeybek
Diagnostic Cytopathology.2024;[Epub] CrossRef
Primary mucinous cystadenocarcinoma of the breast: A case report and literature review
Xi Cao, Yongchao Luo, Songjie Shen, Xinyu Ren
Oncology Letters.2024;[Epub] CrossRef
Mammary mucinous cystadenocarcinoma with long-term follow-up: molecular information and literature review
Ting Lei, Yong Qiang Shi, Tong Bing Chen
Diagnostic Pathology.2023;[Epub] CrossRef
Primary Mucinous Cystadenocarcinoma of the Breast Intermixed with Pleomorphic Invasive Lobular Carcinoma: The First Report of This Rare Association
Federica Vegni, Nicoletta D’Alessandris, Angela Santoro, Giuseppe Angelico, Giulia Scaglione, Angela Carlino, Damiano Arciuolo, Michele Valente, Stefania Sfregola, Maria Natale, Alejandro Martin Sanchez, Valeria Masciullo, Gian Franco Zannoni, Antonino Mu
Journal of Personalized Medicine.2023; 13(6): 948. CrossRef
Special Histologic Type and Rare Breast Tumors – Diagnostic Review and Clinico-Pathological Implications
Benjamin Yongcheng Tan, Elaine Hsuen Lim, Puay Hoon Tan
Surgical Pathology Clinics.2022; 15(1): 29. CrossRef
Mucinous cystadenocarcinoma of the breast: a new entity with broad differentials—a case report
Kanwalpreet Kaur, Ashini Shah, Jahnvi Gandhi, Priti Trivedi
Journal of the Egyptian National Cancer Institute.2022;[Epub] CrossRef
Mucinous carcinoma of the breast: distinctive histopathologic and genetic characteristics
Minjung Jung
Kosin Medical Journal.2022; 37(3): 176. CrossRef
Primary Mucinous Cystadenocarcinoma of the Breast: A Rare Case Report With Review of Literature
Ekta Jain, Abhishek Kumar, Raajul Jain, Shivani Sharma
International Journal of Surgical Pathology.2021; 29(7): 740. CrossRef
Mucinous Cystadenocarcinoma of the Breast: Report of 2 Cases Including One With Long-Term Local Recurrence
Anupma Nayak, Ira J. Bleiweiss, Kimberly Dumoff, Tawfiqul A. Bhuiya
International Journal of Surgical Pathology.2018; 26(8): 749. CrossRef
Mucinous breast carcinoma with tall columnar cells
N Tsoukalas, M Kiakou, M Tolia, ID Kostakis, M Galanopoulos, G Nakos, D Tryfonopoulos, G Kyrgias, G Koumakis
The Annals of The Royal College of Surgeons of England.2018; 100(5): e132. CrossRef
Radiologic Findings of Primary Mucinous Cystadenocarcinoma of the Breast: A Report of Two Cases and a Literature Review
Minjung Seong, Eun Young Ko, Boo-Kyung Han, Soo Youn Cho, Eun Yoon Cho, Se Kyung Lee, Jeong Eon Lee
Journal of Breast Cancer.2016; 19(3): 330. CrossRef
Primary Mucinous Cystadenocarcinoma of the Breast with Endocervical-Like Mucinous Epithelium
Dong-Liang Lin, Ji-Lin Hu, Shi-Hong Shao, Dong-Mei Sun, Ji-Gang Wang
Breast Care.2013; 8(6): 445. CrossRef

The Clinicopathologic Features of Molecular Apocrine Breast Cancer: Yoon Jin Cha, Woo-Hee Jung, Ja Seung Koo; Korean J Pathol. 2012;46(2):169-176. Published online April 25, 2012; DOI: https://doi.org/10.4132/KoreanJPathol.2012.46.2.169

7,205 View
52 Download
12 Crossref

Abstract PDF

Background

To elucidate the clinicopathologic features and their implications on the immunohistochemistry in cases of molecular apocrine breast cancer (MABC).

Methods

Immunohistochemical (IHC) staining for estrogen receptor (ER), human epidermal growth factor receptor 2 (HER-2), cytokeratin (CK) 5/6, epidermal growth factor receptor (EGFR), androgen receptor (AR), gamma-glutamyltrasferase 1 (GGT1) and Ki-67 was performed on tissue microarray breast cancer samples from 204 patients. Phenotypes of breast cancer were divided based on the IHC status of ER, AR and GGT1 into the following: luminal type, ER positive and AR and/or GGT1 positive; basal type, ER, AR, and GGT1 negative; non-basal type, ER positive and AR and GGT1 negative; and MABC type, ER negative and AR and/or GGT1 positive.

Results

In our series of patients (n=204), there were 26 cases of MABC. Besides, there were 18, 60, and 100 cases of luminal type, basal type and non-basal type, respectively. The MABC demonstrated apocrine histology and a higher prevalence of HER-2 positivity than other phenotypes. With the basal type, the MABC manifested a more frequent expression of CK5/6 and EGFR and a higher Ki-67 index than other phenotypes (p<0.001). There were no significant differences in patient prognosis between the phenotypes of breast cancer.

Conclusions

MABC are distinguishable from other phenotypes based on the apocrine histology and a higher expression rate of HER-2.

Citations

Citations to this article as recorded by

The role of histopathologic testing on apocrine carcinoma of the breast
Burak Ilhan, Selman Emiroğlu, Rustu Türkay, Rıdvan Ilhan
Current Problems in Cancer.2020; 44(2): 100501. CrossRef
Cancer du sein triple négatif exprimant le récepteur aux androgènes : de la biologie à la thérapeutique
Thomas Grellety
Bulletin du Cancer.2020; 107(4): 506. CrossRef
Triple‐negative apocrine carcinoma: A rare pathologic subtype with a better prognosis than other triple‐negative breast cancers
Cletus A. Arciero, Albert H. Diehl, Yuan Liu, Qin Sun, Theresa Gillespie, Xiaoxian Li, Preeti Subhedar
Journal of Surgical Oncology.2020; 122(6): 1232. CrossRef
Apocrine lesions of the breast: part 2 of a two-part review. Invasive apocrine carcinoma, the molecular apocrine signature and utility of immunohistochemistry in the diagnosis of apocrine lesions of the breast
Clare D'Arcy, Cecily M Quinn
Journal of Clinical Pathology.2019; 72(1): 7. CrossRef
Enhancing Abiraterone Acetate Efficacy in Androgen Receptor–positive Triple-negative Breast Cancer: Chk1 as a Potential Target
Thomas Grellety, Celine Callens, Elodie Richard, Adrien Briaux, Valérie Vélasco, Marina Pulido, Anthony Gonçalves, Pierre Gestraud, Gaetan MacGrogan, Hervé Bonnefoi, Bruno Cardinaud
Clinical Cancer Research.2019; 25(2): 856. CrossRef
A clinicopathologic study of invasive apocrine carcinoma of the breast: A single-center experience
Denira Imamovic, Nurija Bilalovic, Faruk Skenderi, Vanesa Beslagic, Timur Ceric, Berisa Hasanbegovic, Semir Beslija, Semir Vranic
The Breast Journal.2018; 24(6): 1105. CrossRef
Dose invasive apocrine adenocarcinoma has worse prognosis than invasive ductal carcinoma of breast: evidence from SEER database
Ning Zhang, Hanwen Zhang, Tong Chen, Qifeng Yang
Oncotarget.2017; 8(15): 24579. CrossRef
Pure Apocrine Carcinomas Represent a Clinicopathologically Distinct Androgen Receptor–Positive Subset of Triple-Negative Breast Cancers
Anne M. Mills, Chelsea E. Gottlieb, Scott M. Wendroth, Christiana M. Brenin, Kristen A. Atkins
American Journal of Surgical Pathology.2016; 40(8): 1109. CrossRef
Androgen Receptor: A Complex Therapeutic Target for Breast Cancer
Ramesh Narayanan, James Dalton
Cancers.2016; 8(12): 108. CrossRef
Early versus late distant metastasis and adjuvant chemotherapy alone versus both radiotherapy and chemotherapy in molecular apocrine breast cancer
Xiaozhen Liu, Yang Yang, Xiaolong Feng, Honghong Shen, Jian Liu, Xia Liu, Yun Niu
Oncotarget.2016; 7(31): 48905. CrossRef
Molecular and diagnostic features of apocrine breast lesions
Pavel Gromov, Jaime A Espinoza, Irina Gromova
Expert Review of Molecular Diagnostics.2015; 15(8): 1011. CrossRef
Prevalencia de receptores androgénicos en el cáncer de mama
Claudia Janeth Rodríguez-Silva, José Luis González-Vela, Ascary Alcides Velázquez-Pacheco
Gaceta Mexicana de Oncología.2015; 14(3): 135. CrossRef

Author index