Journal of Pathology and Translational Medicine

Original Articles

Diagnosis of invasive encapsulated follicular variant papillary thyroid carcinoma by protein-based machine learning: Truong Phan-Xuan Nguyen, Minh-Khang Le, Sittiruk Roytrakul, Shanop Shuangshoti, Nakarin Kitkumthorn, Somboon Keelawat; J Pathol Transl Med. 2025;59(1):39-49. Published online October 24, 2024; DOI: https://doi.org/10.4132/jptm.2024.09.14

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Abstract PDF Supplementary Material: Background
Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples.
Methods
We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples.
Results
We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5.
Conclusions
We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Single umbilical artery and associated birth defects in perinatal autopsies: prenatal diagnosis and management: Manushree Saxena, Bhagyashri Hungund; J Pathol Transl Med. 2024;58(5):214-218. Published online July 9, 2024; DOI: https://doi.org/10.4132/jptm.2024.07.03

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Background
The umbilical cord forms the connection between the fetus and the placenta at the feto-maternal interface and normally comprises two umbilical arteries and one umbilical vein. In some cases, only a single umbilical artery (SUA) is present. This study was conducted to evaluate associations between SUA and other congenital malformations discovered in perinatal autopsies and to ascertain the existence of preferential associations between SUA and certain anomalies.
Methods
We evaluated records of all fetuses sent for autopsy to the Department of Pathology during the 10-year period from 2013 through 2022 (n = 1,277). The data were obtained from the hospital’s pathology laboratory records. The congenital anomalies were grouped by organ or system for analysis and included cardiovascular, urinary tract, nervous system, gastrointestinal tract, musculoskeletal, and lung anomalies.
Results
A SUA was present in 8.61% of the autopsies. The gestational age of the affected fetuses ranged between 13 to 40 weeks. An SUA presented as an isolated single anomaly in 44 cases (3.4%). Of the 110 SUA cases, 60% had other congenital anomalies. There was a significant association between birth defects and SUAs (p < .001). Strong associations between SUA and urinary tract, lung, and musculoskeletal anomalies were observed.
Conclusions
A SUA is usually seen in association with other congenital malformations rather than as an isolated defect. Therefore, examination for associated anomalies when an SUA is detected either antenatally or postnatally is imperative. The findings of this study should be helpful in counseling expectant mothers and their families in cases of SUA.

Citations

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Single Umbilical Artery with Symmetrical IUGR and Multiple Fetal Anomalies - An Interesting Case Report
Amulya Choudary Kotapati, Bhargavi Khandru, Vijayasree M.
Journal of Evolution of Medical and Dental Sciences.2025; : 10. CrossRef

Review

A stepwise approach to fine needle aspiration cytology of lymph nodes: Yosep Chong, Gyeongsin Park, Hee Jeong Cha, Hyun-Jung Kim, Chang Suk Kang, Jamshid Abdul-Ghafar, Seung-Sook Lee; J Pathol Transl Med. 2023;57(4):196-207. Published online July 11, 2023; DOI: https://doi.org/10.4132/jptm.2023.06.12

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Abstract PDF Supplementary Material

The cytological diagnosis of lymph node lesions is extremely challenging because of the diverse diseases that cause lymph node enlargement, including both benign and malignant or metastatic lymphoid lesions. Furthermore, the cytological findings of different lesions often resemble one another. A stepwise diagnostic approach is essential for a comprehensive diagnosis that combines: clinical findings, including age, sex, site, multiplicity, and ultrasonography findings; low-power reactive, metastatic, and lymphoma patterns; high-power population patterns, including two populations of continuous range, small monotonous pattern and large monotonous pattern; and disease-specific diagnostic clues including granulomas and lymphoglandular granules. It is also important to remember the histological features of each diagnostic category that are common in lymph node cytology and to compare them with cytological findings. It is also essential to identify a few categories of diagnostic pitfalls that often resemble lymphomas and easily lead to misdiagnosis, particularly in malignant small round cell tumors, poorly differentiated squamous cell carcinomas, and nasopharyngeal undifferentiated carcinoma. Herein, we review a stepwise approach for fine needle aspiration cytology of lymphoid diseases and suggest a diagnostic algorithm that uses this approach and the Sydney classification system.

Citations

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Development and Validation of Explainable Artificial Intelligence System for Automatic Diagnosis of Cervical Lymphadenopathy From Ultrasound Images
Ming Xu, Yubiao Yue, Zhenzhang Li, Yinhong Li, Guoying Li, Haihua Liang, Di Liu, Xiaohong Xu, Mohamadreza (Mohammad) Khosravi
International Journal of Intelligent Systems.2025;[Epub] CrossRef
Immunocytochemical markers, molecular testing and digital cytopathology for aspiration cytology of metastatic breast carcinoma
Joshua J. X. Li, Gary M. Tse
Cytopathology.2024; 35(2): 218. CrossRef
Response to comment on “A stepwise approach to fine needle aspiration cytology of lymph nodes”
Yosep Chong, Gyeongsin Park, Hee Jeong Cha, Hyun-Jung Kim, Chang Suk Kang, Jamshid Abdul-Ghafar, Seung-Sook Lee
Journal of Pathology and Translational Medicine.2024; 58(1): 43. CrossRef
Comment on “A stepwise approach to fine needle aspiration cytology of lymph nodes”
Elisabetta Maffei, Valeria Ciliberti, Pio Zeppa, Alessandro Caputo
Journal of Pathology and Translational Medicine.2024; 58(1): 40. CrossRef
The Incidence of Thyroid Cancer in Bethesda III Thyroid Nodules: A Retrospective Analysis at a Single Endocrine Surgery Center
Iyad Hassan, Lina Hassan, Nahed Balalaa, Mohamad Askar, Hussa Alshehhi, Mohamad Almarzooqi
Diagnostics.2024; 14(10): 1026. CrossRef
Efficiency of Fine-Needle Aspiration (FNA) in Relation to Tru-Cut Biopsy of Lateral Neck Swellings
Mohammed S Al Olaimat, Fahad S Al Qooz, Zaid R Alzoubi, Elham M Alsharaiah, Ali S Al Murdif, Mohammad O Alanazi
Cureus.2024;[Epub] CrossRef
Pitfalls in the Cytological Diagnosis of Nodal Hodgkin Lymphoma
Uma Handa, Rasheeda Mohamedali, Rajpal Singh Punia, Simrandeep Singh, Ranjeev Bhagat, Phiza Aggarwal, Manveen Kaur
Diagnostic Cytopathology.2024; 52(12): 715. CrossRef
Rapid 3D imaging at cellular resolution for digital cytopathology with a multi-camera array scanner (MCAS)
Kanghyun Kim, Amey Chaware, Clare B. Cook, Shiqi Xu, Monica Abdelmalak, Colin Cooke, Kevin C. Zhou, Mark Harfouche, Paul Reamey, Veton Saliu, Jed Doman, Clay Dugo, Gregor Horstmeyer, Richard Davis, Ian Taylor-Cho, Wen-Chi Foo, Lucas Kreiss, Xiaoyin Sara J
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Original Article

Extremely well-differentiated adenocarcinoma of the stomach: diagnostic pitfalls in endoscopic biopsy: Jongwon Lee, In-Seob Lee, Ji Yong Ahn, Young Soo Park, Jihun Kim; J Pathol Transl Med. 2022;56(2):63-72. Published online November 16, 2021; DOI: https://doi.org/10.4132/jptm.2021.10.12

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Abstract PDF Supplementary Material

Background
Extremely well-differentiated adenocarcinoma (EWDA) is a deceptively bland-looking adenocarcinoma of the stomach. It often causes diagnostic problems, especially in endoscopic biopsy samples. To better recognize this deceptively bland lesion, we carefully reviewed a series of EWDAs treated at our institution.
Methods
A total of 55 specimens from 19 patients were obtained. Endoscopic, gross and microscopic features defining EWDA were described and documented. For comparison, hyperplastic polyp specimens were randomly selected and analyzed.
Results
Most cases (18 of 19, 94.7%) were advanced gastric cancer (AGC) and primarily located in the body of the stomach (15 of 19, 79.0%). The majority of AGCs were non-ulcerated (11 of 18, 61.1%) with an undermining growth pattern and a relatively small mucosal involvement. Specific histologic features included an irregular glandular shape, an undulating apical cytoplasmic border, disproportionately large glands, a variably distended mucinous cytoplasm. Classical features, such as small infiltrating glands or desmoplastic reactions, were barely observed. Identification of irregularly spaced nuclei and disruption of the foveolar epithelial structure, along with atypical features described above were helpful in making a diagnosis especially in gastric forceps biopsies.
Conclusions
Awareness of the histomorphologic characteristics described in this report would lead to timely diagnosis and prevent repeated endoscopic procedures.

Citations

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Artificial intelligence-assisted diagnosis of early gastric cancer: present practice and future prospects
Changda Lei, Wenqiang Sun, Kun Wang, Ruixia Weng, Xiuji Kan, Rui Li
Annals of Medicine.2025;[Epub] CrossRef
Unusual or Uncommon Histology of Gastric Cancer
Jinho Shin, Young Soo Park
Journal of Gastric Cancer.2024; 24(1): 69. CrossRef
A case of gastric adenocarcinoma with pyloric gland-type infiltrating submucosa
Kaiho Hirata, Shusuke Yagi, Hideki Miyazaki, Kazuhiko Yamada, Naoki Akazawa, Naoki Enomoto, Kyoko Nohara, Chizu Yokoi, Toru Igari, Norihiro Kokudo
Surgical Case Reports.2024;[Epub] CrossRef
Gastric-type extremely well-differentiated adenocarcinoma of the stomach: A rare tumor with diagnostic difficulties and high inter-observer variation in endoscopic pinch biopsies
Soomin Ahn, Sujin Park, Hyun Hee Koh, Han Gyeol Kim, Hyunjin Kim, Jae Yeong Son, Boram Lee, Hyunwoo Lee, Soohyun Hwang, Junhun Cho, Yun Kyung Lee, Ryoji Kushima, Amitabh Srivastava, Kyoung-Mee Kim
Pathology - Research and Practice.2024; 263: 155599. CrossRef

Review

Standardization of the pathologic diagnosis of appendiceal mucinous neoplasms: Dong-Wook Kang, Baek-hui Kim, Joon Mee Kim, Jihun Kim, Hee Jin Chang, Mee Soo Chang, Jin-Hee Sohn, Mee-Yon Cho, So-Young Jin, Hee Kyung Chang, Hye Seung Han, Jung Yeon Kim, Hee Sung Kim, Do Youn Park, Ha Young Park, So Jeong Lee, Wonae Lee, Hye Seung Lee, Yoo Na Kang, Younghee Choi; J Pathol Transl Med. 2021;55(4):247-264. Published online July 8, 2021; DOI: https://doi.org/10.4132/jptm.2021.05.28

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Abstract PDF Supplementary Material

Although the understanding of appendiceal mucinous neoplasms (AMNs) and their relationship with disseminated peritoneal mucinous disease have advanced, the diagnosis, classification, and treatment of AMNs are still confusing for pathologists and clinicians. The Gastrointestinal Pathology Study Group of the Korean Society of Pathologists (GPSG-KSP) proposed a multicenter study and held a workshop for the “Standardization of the Pathologic Diagnosis of the Appendiceal Mucinous Neoplasm” to overcome the controversy and potential conflicts. The present article is focused on the diagnostic criteria, terminologies, tumor grading, pathologic staging, biologic behavior, treatment, and prognosis of AMNs and disseminated peritoneal mucinous disease. In addition, GPSG-KSP proposes a checklist of standard data elements of appendiceal epithelial neoplasms to standardize pathologic diagnosis. We hope the present article will provide pathologists with updated knowledge on how to handle and diagnose AMNs and disseminated peritoneal mucinous disease.

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Predicting Survival in Mucinous Adenocarcinoma of the Appendix: Demographics, Disease Presentation, and Treatment Methodology
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Annals of Surgical Oncology.2024; 31(9): 6237. CrossRef
Histoséminaire biopsies péritonéales tumorales. Néoplasies mucineuses appendiculaires
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Histoséminaire biopsies péritonéales tumorales. Cas no 2
Peggy Dartigues
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Muzinöse Tumoren des Peritoneums
Anne Kristin Fischer, Andrea Tannapfel, Alexander Quaas
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Landscape of Genetic Mutations in Appendiceal Cancers
Marian Constantin, Cristina Mătanie, Livia Petrescu, Alexandra Bolocan, Octavian Andronic, Coralia Bleotu, Mihaela Magdalena Mitache, Sorin Tudorache, Corneliu Ovidiu Vrancianu
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Madison Bowles, Jessica Y Ng, Hajir Nabi
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Original Article

Deep learning for computer-assisted diagnosis of hereditary diffuse gastric cancer: Sean A. Rasmussen, Thomas Arnason, Weei-Yuarn Huang; J Pathol Transl Med. 2021;55(2):118-124. Published online January 22, 2021; DOI: https://doi.org/10.4132/jptm.2020.12.22

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Abstract PDF

Background
Patients with hereditary diffuse gastric cancer often undergo prophylactic gastrectomy to minimize cancer risk. Because intramucosal poorly cohesive carcinomas in this setting are typically not grossly visible, many pathologists assess the entire gastrectomy specimen microscopically. With 150 or more slides per case, this is a major time burden for pathologists. This study utilizes deep learning methods to analyze digitized slides and detect regions of carcinoma.
Methods
Prophylactic gastrectomy specimens from seven patients with germline CDH1 mutations were analyzed (five for training/validation and two for testing, with a total of 133 tumor foci). All hematoxylin and eosin slides containing cancer foci were digitally scanned, and patches of size 256×256 pixels were randomly extracted from regions of cancer as well as from regions of normal background tissue, resulting in 15,851 images for training/validation and 970 images for testing. A model with DenseNet-169 architecture was trained for 150 epochs, then evaluated on images from the test set. External validation was conducted on 814 images scanned at an outside institution.
Results
On individual patches, the trained model achieved a receiver operating characteristic (ROC) area under the curve (AUC) of 0.9986. This enabled it to maintain a sensitivity of 90% with a false-positive rate of less than 0.1%. On the external validation dataset, the model achieved a similar ROC AUC of 0.9984. On whole slide images, the network detected 100% of tumor foci and correctly eliminated an average of 99.9% of the non-cancer slide area from consideration.
Conclusions
Overall, our model shows encouraging progress towards computer-assisted diagnosis of hereditary diffuse gastric cancer.

Citations

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Non-endoscopic Applications of Machine Learning in Gastric Cancer: A Systematic Review
Marianne Linley L. Sy-Janairo, Jose Isagani B. Janairo
Journal of Gastrointestinal Cancer.2024; 55(1): 47. CrossRef
Artificial intelligence applicated in gastric cancer: A bibliometric and visual analysis via CiteSpace
Guoyang Zhang, Jingjing Song, Zongfeng Feng, Wentao Zhao, Pan Huang, Li Liu, Yang Zhang, Xufeng Su, Yukang Wu, Yi Cao, Zhengrong Li, Zhigang Jie
Frontiers in Oncology.2023;[Epub] CrossRef
Deep learning of endoscopic features for the assessment of neoadjuvant therapy response in locally advanced rectal cancer
Anqi Wang, Jieli Zhou, Gang Wang, Beibei Zhang, Hongyi Xin, Haiyang Zhou
Asian Journal of Surgery.2023; 46(9): 3568. CrossRef
Preparing Data for Artificial Intelligence in Pathology with Clinical-Grade Performance
Yuanqing Yang, Kai Sun, Yanhua Gao, Kuansong Wang, Gang Yu
Diagnostics.2023; 13(19): 3115. CrossRef
Using Deep Learning to Predict Final HER2 Status in Invasive Breast Cancers That are Equivocal (2+) by Immunohistochemistry
Sean A. Rasmussen, Valerie J. Taylor, Alexi P. Surette, Penny J. Barnes, Gillian C. Bethune
Applied Immunohistochemistry & Molecular Morphology.2022; 30(10): 668. CrossRef

Reviews

Standardized pathology report for breast cancer: Soo Youn Cho, So Yeon Park, Young Kyung Bae, Jee Yeon Kim, Eun Kyung Kim, Woo Gyeong Kim, Youngmee Kwon, Ahwon Lee, Hee Jin Lee, Ji Shin Lee, Jee Young Park, Gyungyub Gong, Hye Kyoung Yoon; J Pathol Transl Med. 2021;55(1):1-15. Published online January 11, 2021; DOI: https://doi.org/10.4132/jptm.2020.11.20

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Abstract PDF Supplementary Material

Given the recent advances in management and understanding of breast cancer, a standardized pathology report reflecting these changes is critical. To meet this need, the Breast Pathology Study Group of the Korean Society of Pathologists has developed a standardized pathology reporting format for breast cancer, consisting of ‘standard data elements,’ ‘conditional data elements,’ and a biomarker report form. The ‘standard data elements’ consist of the basic pathologic features used for prognostication, while other factors related to prognosis or diagnosis are described in the ‘conditional data elements.’ In addition to standard data elements, all recommended issues are also presented. We expect that this standardized pathology report for breast cancer will improve diagnostic concordance and communication between pathologists and clinicians, as well as between pathologists inter-institutionally.

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Residual pure intralymphatic carcinoma component only (lymphovascular tumor emboli without invasive carcinoma) after neoadjuvant chemotherapy is associated with poor outcome: Not pathologic complete response
Hyunwoo Lee, Yunjeong Jang, Yoon Ah Cho, Eun Yoon Cho
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Sentinel lymph node biopsy in patients with ductal carcinomain situ: systematic review and meta-analysis
Matthew G. Davey, Colm O’Flaherty, Eoin F. Cleere, Aoife Nohilly, James Phelan, Evan Ronane, Aoife J. Lowery, Michael J. Kerin
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Molecular characteristics of meningiomas: Young Suk Lee, Youn Soo Lee; J Pathol Transl Med. 2020;54(1):45-63. Published online January 15, 2020; DOI: https://doi.org/10.4132/jptm.2019.11.05

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Abstract PDF

Meningioma is the most common primary intracranial tumor in adults. The grading of meningioma is based on World Health Organization criteria, which rely on histopathological features alone. This grading system is unable to conclusively predict the clinical behavior of these tumors (i.e., recurrence or prognosis in benign or atypical grades). Advances in molecular techniques over the last decade that include genomic and epigenomic data associated with meningiomas have been used to identify genetic biomarkers that can predict tumor behavior. This review summarizes the molecular characteristics of meningioma using genetic and epigenetic biomarkers. Molecular alterations that can predict meningioma behavior may be integrated into the upcoming World Health Organization grading system.

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Original Articles

Cytological Features That Differentiate Follicular Neoplasm from Mimicking Lesions: Kanghee Han, Hwa-Jeong Ha, Joon Seog Kong, Jung-Soon Kim, Jae Kyung Myung, Jae Soo Koh, Sunhoo Park, Myung-Soon Shin, Woo-Tack Song, Hye Sil Seol, Seung-Sook Lee; J Pathol Transl Med. 2018;52(2):110-120. Published online January 29, 2018; DOI: https://doi.org/10.4132/jptm.2018.01.17

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204 Download
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Abstract PDF

Background
It is difficult to correctly diagnose follicular neoplasms (FNs) on fine-needle aspiration cytology (FNAC) because it shares many cytological features with other mimicking lesions. The aim of this study was to identify the cytological features that differentiate FNs from mimicking lesions.
Methods
We included the cytological slides from 116 cases of thyroid FN diagnosed on FNAC, and included their subsequent histological diagnoses. We evaluated the cytological architectural pattern and nuclear features of the lesions according to their histological groups.
Results
The final histological diagnoses of the 116 cases varied, and included 51 FNs (44%), 47 papillary thyroid carcinomas (40%) including follicular variant, and seventeen cellular nodular hyperplasias (15%). Regardless of the final histological diagnosis, microfollicular pattern was observed in most cases. On the other hand, trabecular pattern was identified in 34% of FNs, but not in any other lesions. Additionally, elongated nuclei and ground glass chromatin were found in only some papillary thyroid carcinomas.
Conclusions
This study shows that the trabecular pattern is a representative cytological feature of FNs that can be used to distinguish FNs from mimicking lesions. In addition, nuclear shape and chromatin pattern can be used to further confirm the diagnosis of FNs from mimicking lesions through FNAC.

Citations

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Diagnostic implication of thyroid spherules for cytological diagnosis of thyroid nodules
Heeseung Sohn, Kennichi Kakudo, Chan Kwon Jung
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Fine needle aspiration cytology diagnoses of follicular thyroid carcinoma: results from a multicenter study in Asia
Hee Young Na, Miyoko Higuchi, Shinya Satoh, Kaori Kameyama, Chan Kwon Jung, Su-Jin Shin, Shipra Agarwal, Jen-Fan Hang, Yun Zhu, Zhiyan Liu, Andrey Bychkov, Kennichi Kakudo, So Yeon Park
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Using Deep Convolutional Neural Networks for Enhanced Ultrasonographic Image Diagnosis of Differentiated Thyroid Cancer
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The Role of Fine Needle Aspiration Biopsy with Bethesda System in the Evaluation of Thyroid Nodules
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Preoperative diagnostic categories of fine needle aspiration cytology for histologically proven thyroid follicular adenoma and carcinoma, and Hurthle cell adenoma and carcinoma: Analysis of cause of under- or misdiagnoses
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Reclassification of Mixed Oligoastrocytic Tumors Using a Genetically Integrated Diagnostic Approach: Seong-Ik Kim, Yujin Lee, Jae-Kyung Won, Chul-Kee Park, Seung Hong Choi, Sung-Hye Park; J Pathol Transl Med. 2018;52(1):28-36. Published online September 29, 2017; DOI: https://doi.org/10.4132/jptm.2017.09.25

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Abstract PDF

Background
Mixed gliomas, such as oligoastrocytomas (OA), anaplastic oligoastrocytomas, and glioblastomas (GBMs) with an oligodendroglial component (GBMO) are defined as tumors composed of a mixture of two distinct neoplastic cell types, astrocytic and oligodendroglial. Recently, mutations ATRX and TP53, and codeletion of 1p/19q are shown to be genetic hallmarks of astrocytic and oligodendroglial tumors, respectively. Subsequent molecular analyses of mixed gliomas preferred the reclassification to either oligodendroglioma or astrocytoma. This study was designed to apply genetically integrated diagnostic criteria to mixed gliomas and determine usefulness and prognostic value of new classification in Korean patients.
Methods
Fifty-eight cases of mixed OAs and GBMOs were retrieved from the pathology archives of Seoul National University Hospital from 2004 to 2015. Reclassification was performed according to genetic and immunohistochemical properties. Clinicopathological characteristics of each subgroup were evaluated. Overall survival was assessed and compared between subgroups.
Results
We could reclassify all mixed OAs and GBMOs into either astrocytic or oligodendroglial tumors. Notably, 29 GBMOs could be reclassified into 11 cases of GBM, IDH-mutant, 16 cases of GBM, IDH-wildtype, and two cases of anaplastic oligodendroglioma, IDH mutant. Overall survival was significantly different among these new groups (p<.001). Overall survival and progression-free survival were statistically better in gliomas with IDH mutation, ATRX mutation, no microscopic necrosis, and young patient age (cut off, 45 years old).
Conclusions
Our results strongly suggest that a genetically integrated diagnosis of glioma better reflects prognosis than former morphology-based methods.

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Reviews

Molecular Testing of Brain Tumor: Sung-Hye Park, Jaekyung Won, Seong-Ik Kim, Yujin Lee, Chul-Kee Park, Seung-Ki Kim, Seung-Hong Choi; J Pathol Transl Med. 2017;51(3):205-223. Published online May 12, 2017; DOI: https://doi.org/10.4132/jptm.2017.03.08

31,333 View
1,161 Download
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Abstract PDF

The World Health Organization (WHO) classification of central nervous system (CNS) tumors was revised in 2016 with a basis on the integrated diagnosis of molecular genetics. We herein provide the guidelines for using molecular genetic tests in routine pathological practice for an accurate diagnosis and appropriate management. While astrocytomas and IDH-mutant (secondary) glioblastomas are characterized by the mutational status of IDH, TP53, and ATRX, oligodendrogliomas have a 1p/19q codeletion and mutations in IDH, CIC, FUBP1, and the promoter region of telomerase reverse transcriptase (TERTp). IDH-wildtype (primary) glioblastomas typically lack mutations in IDH, but are characterized by copy number variations of EGFR, PTEN, CDKN2A/B, PDGFRA, and NF1 as well as mutations of TERTp. High-grade pediatric gliomas differ from those of adult gliomas, consisting of mutations in H3F3A, ATRX, and DAXX, but not in IDH genes. In contrast, well-circumscribed low-grade neuroepithelial tumors in children, such as pilocytic astrocytoma, pleomorphic xanthoastrocytoma, and ganglioglioma, often have mutations or activating rearrangements in the BRAF, FGFR1, and MYB genes. Other CNS tumors, such as ependymomas, neuronal and glioneuronal tumors, embryonal tumors, meningothelial, and other mesenchymal tumors have important genetic alterations, many of which are diagnostic, prognostic, and predictive markers and therapeutic targets. Therefore, the neuropathological evaluation of brain tumors is increasingly dependent on molecular genetic tests for proper classification, prediction of biological behavior and patient management. Identifying these gene abnormalities requires cost-effective and high-throughput testing, such as next-generation sequencing. Overall, this paper reviews the global guidelines and diagnostic algorithms for molecular genetic testing of brain tumors.

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Molecular Testing for Gastrointestinal Cancer: Hye Seung Lee, Woo Ho Kim, Yoonjin Kwak, Jiwon Koh, Jeong Mo Bae, Kyoung-Mee Kim, Mee Soo Chang, Hye Seung Han, Joon Mee Kim, Hwal Woong Kim, Hee Kyung Chang, Young Hee Choi, Ji Y. Park, Mi Jin Gu, Min Jin Lhee, Jung Yeon Kim, Hee Sung Kim, Mee-Yon Cho; J Pathol Transl Med. 2017;51(2):103-121. Published online February 19, 2017; DOI: https://doi.org/10.4132/jptm.2017.01.24

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Abstract PDF

With recent advances in molecular diagnostic methods and targeted cancer therapies, several molecular tests have been recommended for gastric cancer (GC) and colorectal cancer (CRC). Microsatellite instability analysis of gastrointestinal cancers is performed to screen for Lynch syndrome, predict favorable prognosis, and screen patients for immunotherapy. The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor has been approved in metastatic CRCs with wildtype RAS (KRAS and NRAS exon 2–4). A BRAF mutation is required for predicting poor prognosis. Additionally, amplification of human epidermal growth factor receptor 2 (HER2) and MET is also associated with resistance to EGFR inhibitor in metastatic CRC patients. The BRAF V600E mutation is found in sporadic microsatellite unstable CRCs, and thus is helpful for ruling out Lynch syndrome. In addition, the KRAS mutation is a prognostic biomarker and the PIK3CA mutation is a molecular biomarker predicting response to phosphoinositide 3-kinase/AKT/mammalian target of rapamycin inhibitors and response to aspirin therapy in CRC patients. Additionally, HER2 testing should be performed in all recurrent or metastatic GCs. If the results of HER2 immunohistochemistry are equivocal, HER2 silver or fluorescence in situ hybridization testing are essential for confirmative determination of HER2 status. Epstein-Barr virus–positive GCs have distinct characteristics, including heavy lymphoid stroma, hypermethylation phenotype, and high expression of immune modulators. Recent advances in next-generation sequencing technologies enable us to examine various genetic alterations using a single test. Pathologists play a crucial role in ensuring reliable molecular testing and they should also take an integral role between molecular laboratories and clinicians.

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Original Article

Differential Immunohistochemical Profiles for Distinguishing Prostate Carcinoma and Urothelial Carcinoma: Woo Jin Oh, Arthur Minwoo Chung, Jee Soon Kim, Ji Heun Han, Sung Hoo Hong, Ji Yeol Lee, Yeong Jin Choi; J Pathol Transl Med. 2016;50(5):345-354. Published online August 7, 2016; DOI: https://doi.org/10.4132/jptm.2016.06.14

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Abstract PDF

Background
The pathologic distinction between high-grade prostate adenocarcinoma (PAC) involving the urinary bladder and high-grade urothelial carcinoma (UC) infiltrating the prostate can be difficult. However, making this distinction is clinically important because of the different treatment modalities for these two entities.
Methods
A total of 249 patient cases (PAC, 111 cases; UC, 138 cases) collected between June 1995 and July 2009 at Seoul St. Mary’s Hospital were studied. An immunohistochemical evaluation of prostatic markers (prostate-specific antigen [PSA], prostate-specific membrane antigen [PSMA], prostate acid phosphatase [PAP], P501s, NKX3.1, and α-methylacyl coenzyme A racemase [AMACR]) and urothelial markers (CK34βE12, p63, thrombomodulin, S100P, and GATA binding protein 3 [GATA3]) was performed using tissue microarrays from each tumor.
Results
The sensitivities of prostatic markers in PAC were 100% for PSA, 83.8% for PSMA, 91.9% for PAP, 93.7% for P501s, 88.3% for NKX 3.1, and 66.7% for AMACR. However, the urothelial markers CK34βE12, p63, thrombomodulin, S100P, and GATA3 were also positive in 1.8%, 0%, 0%, 3.6%, and 0% of PAC, respectively. The sensitivities of urothelial markers in UC were 75.4% for CK34βE12, 73.9% for p63, 45.7% for thrombomodulin, 22.5% for S100P, and 84.8% for GATA3. Conversely, the prostatic markers PSA, PSMA, PAP, P501s, NKX3.1, and AMACR were also positive in 9.4%, 0.7%, 18.8%, 0.7%, 0%, and 8.7% of UCs, respectively.
Conclusions
Prostatic and urothelial markers, including PSA, NKX3.1, p63, thrombomodulin, and GATA3 are very useful for differentiating PAC from UC. The optimal combination of prostatic and urothelial markers could improve the ability to differentiate PAC from UC pathologically.

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Review

Pathology Reporting of Thyroid Core Needle Biopsy: A Proposal of the Korean Endocrine Pathology Thyroid Core Needle Biopsy Study Group: Chan Kwon Jung, Hye Sook Min, Hyo Jin Park, Dong Eun Song, Jang Hee Kim, So Yeon Park, Hyunju Yoo, Mi Kyung Shin, Korean Endocrine Pathology Thyroid Core Needle Biopsy Study Group; J Pathol Transl Med. 2015;49(4):288-299. Published online June 17, 2015; DOI: https://doi.org/10.4132/jptm.2015.06.04

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Abstract PDF

In recent years throughout Korea, the use of ultrasound-guided core needle biopsy (CNB) has become common for the preoperative diagnosis of thyroid nodules. However, there is no consensus on the pathology reporting system for thyroid CNB. The Korean Endocrine Pathology Thyroid Core Needle Biopsy Study Group held a conference on thyroid CNB pathology and developed guidelines through contributions from the participants. This article discusses the outcome of the discussions that led to a consensus on the pathology reporting of thyroid CNB.

Citations

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Original Article

Diagnostic Accuracy of Endoscopic Ultrasound-Guided Fine Needle Aspiration Cytology of Pancreatic Lesions: Hae Woon Baek, Min Jee Park, Ye-Young Rhee, Kyoung Bun Lee, Min A Kim, In Ae Park; J Pathol Transl Med. 2015;49(1):52-60. Published online January 15, 2015; DOI: https://doi.org/10.4132/jptm.2014.10.26

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Abstract PDF

Background
Endoscopic ultrasound–guided fine needle aspiration cytology (EUS-FNAC) is currently the most commonly used procedure for obtaining cytologic specimens of the pancreas. It is accurate, minimally invasive, safe and cost-effective. However, there is discrepancy between cytological and surgical diagnoses. This study was aimed at evaluating the diagnostic accuracy of EUS-FNAC of the pancreas. Methods: We performed a retrospective review of 191 cases of pancreatic lesions initially diagnosed by EUS-FNAC with subsequent histological diagnosis between 2010 and 2012 in the Department of Pathology, Seoul National University Hospital. Cytologic and surgical diagnoses were categorized into five groups: negative, benign, atypical, malignant, and insufficient for diagnosis. Subsequently, 167 cases with satisfactory yield in both surgical and cytology specimens were statistically analyzed to determine correlations with diagnosis. Results: In comparison to surgical diagnoses, cytologic diagnoses were true-positive in 103 cases (61.7%), true-negative in 28 cases (16.8%), false-positive in 9 cases (5.4%), and false-negative in 27 cases (16.1%). The diagnostic accuracy was 78.4%, sensitivity was 79.2%, and specificity was 75.7%. The positive predictive value was 92.0%, and negative predictive value was 50.9%. Conclusions: EUS-FNAC has high accuracy, sensitivity, specificity and positive predictive value. Overcoming the limitations of EUS-FNAC will make it a useful and reliable diagnostic tool for accurate evaluation of pancreatic lesions.

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