Journal of Pathology and Translational Medicine

Yong Mee Cho

4 Articles

Histopathologic classification and immunohistochemical features of papillary renal neoplasm with potential therapeutic targets: Jeong Hwan Park, Su-Jin Shin, Hyun-Jung Kim, Sohee Oh, Yong Mee Cho; J Pathol Transl Med. 2024;58(6):321-330. Published online September 12, 2024; DOI: https://doi.org/10.4132/jptm.2024.07.31

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Background
Papillary renal cell carcinoma (pRCC) is the second most common histological subtype of renal cell carcinoma and is considered a morphologically and molecularly heterogeneous tumor. Accurate classification and assessment of the immunohistochemical features of possible therapeutic targets are needed for precise patient care. We aimed to evaluate immunohistochemical features and possible therapeutic targets of papillary renal neoplasms
Methods
We collected 140 papillary renal neoplasms from three different hospitals and conducted immunohistochemical studies on tissue microarray slides. We performed succinate dehydrogenase B, fumarate hydratase, and transcription factor E3 immunohistochemical studies for differential diagnosis and re-classified five cases (3.6%) of papillary renal neoplasms. In addition, we conducted c-MET, p16, c-Myc, Ki-67, p53, and stimulator of interferon genes (STING) immunohistochemical studies to evaluate their pathogenesis and value for therapeutic targets.
Results
We found that c-MET expression was more common in pRCC (classic) (p = .021) among papillary renal neoplasms and Ki-67 proliferation index was higher in pRCC (not otherwise specified, NOS) compared to that of pRCC (classic) and papillary neoplasm with reverse polarity (marginal significance, p = .080). Small subsets of cases with p16 block positivity (4.5%) (pRCC [NOS] only) and c-Myc expression (7.1%) (pRCC [classic] only) were found. Also, there were some cases showing STING expression and those cases were associated with increased Ki-67 proliferation index (marginal significance, p = .063).
Conclusions
Our findings suggested that there are subsets of pRCC with c-MET, p16, c-MYC, and STING expression and those cases could be potential candidates for targeted therapy.

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Tissue-Based Biomarkers Important for Prognostication and Management of Genitourinary Tumors, Including Surrogate Markers of Genomic Alterations
Leonie Beauchamp, Shreeya Indulkar, Eric Erak, Mohammad Salimian, Andres Matoso
Surgical Pathology Clinics.2025; 18(1): 175. CrossRef

Artificial intelligence algorithm for neoplastic cell percentage estimation and its application to copy number variation in urinary tract cancer: Jinahn Jeong, Deokhoon Kim, Yeon-Mi Ryu, Ja-Min Park, Sun Young Yoon, Bokyung Ahn, Gi Hwan Kim, Se Un Jeong, Hyun-Jung Sung, Yong Il Lee, Sang-Yeob Kim, Yong Mee Cho; J Pathol Transl Med. 2024;58(5):229-240. Published online August 9, 2024; DOI: https://doi.org/10.4132/jptm.2024.07.13

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Abstract PDF Supplementary Material: Background
Bladder cancer is characterized by frequent mutations, which provide potential therapeutic targets for most patients. The effectiveness of emerging personalized therapies depends on an accurate molecular diagnosis, for which the accurate estimation of the neoplastic cell percentage (NCP) is a crucial initial step. However, the established method for determining the NCP, manual counting by a pathologist, is time-consuming and not easily executable.
Methods
To address this, artificial intelligence (AI) models were developed to estimate the NCP using nine convolutional neural networks and the scanned images of 39 cases of urinary tract cancer. The performance of the AI models was compared to that of six pathologists for 119 cases in the validation cohort. The ground truth value was obtained through multiplexed immunofluorescence. The AI model was then applied to 41 cases in the application cohort that underwent next-generation sequencing testing, and its impact on the copy number variation (CNV) was analyzed.
Results
Each AI model demonstrated high reliability, with intraclass correlation coefficients (ICCs) ranging from 0.82 to 0.88. These values were comparable or better to those of pathologists, whose ICCs ranged from 0.78 to 0.91 in urothelial carcinoma cases, both with and without divergent differentiation/ subtypes. After applying AI-driven NCP, 190 CNV (24.2%) were reclassified with 66 (8.4%) and 78 (9.9%) moved to amplification and loss, respectively, from neutral/minor CNV. The neutral/minor CNV proportion decreased by 6%.
Conclusions
These results suggest that AI models could assist human pathologists in repetitive and cumbersome NCP calculations.

Clinical practice recommendations for the use of next-generation sequencing in patients with solid cancer: a joint report from KSMO and KSP: Miso Kim, Hyo Sup Shim, Sheehyun Kim, In Hee Lee, Jihun Kim, Shinkyo Yoon, Hyung-Don Kim, Inkeun Park, Jae Ho Jeong, Changhoon Yoo, Jaekyung Cheon, In-Ho Kim, Jieun Lee, Sook Hee Hong, Sehhoon Park, Hyun Ae Jung, Jin Won Kim, Han Jo Kim, Yongjun Cha, Sun Min Lim, Han Sang Kim, Choong-Kun Lee, Jee Hung Kim, Sang Hoon Chun, Jina Yun, So Yeon Park, Hye Seung Lee, Yong Mee Cho, Soo Jeong Nam, Kiyong Na, Sun Och Yoon, Ahwon Lee, Kee-Taek Jang, Hongseok Yun, Sungyoung Lee, Jee Hyun Kim, Wan-Seop Kim; J Pathol Transl Med. 2024;58(4):147-164. Published online January 10, 2024; DOI: https://doi.org/10.4132/jptm.2023.11.01

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Abstract PDF

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

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Apport de la génomique dans la prise en charge des cancers
Étienne Rouleau, Lucie Karayan-Tapon, Marie-Dominique Galibert, Alexandre Harlé, Isabelle Soubeyran
Revue Francophone des Laboratoires.2025; 2025(568): 67. CrossRef

Diverse Immunoprofile of Ductal Adenocarcinoma of the Prostate with an Emphasis on the Prognostic Factors: Se Un Jeong, Anuja Kashikar Kekatpure, Ja-Min Park, Minkyu Han, Hee Sang Hwang, Hui Jeong Jeong, Heounjeong Go, Yong Mee Cho; J Pathol Transl Med. 2017;51(5):471-481. Published online August 9, 2017; DOI: https://doi.org/10.4132/jptm.2017.06.02

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Abstract PDF

Background
Ductal adenocarcinoma (DAC) of the prostate is an uncommon histologic subtype whose prognostic factors and immunoprofile have not been fully defined. Methods: To define its prognostic factors and immunoprofile, the clinicopathological features, including biochemical recurrence (BCR), of 61 cases of DAC were analyzed. Immunohistochemistry was performed on tissue microarray constructs to assess the expression of prostate cancer-related and mammalian target of rapamycin (mTOR) signaling-related proteins. Results: During the median follow-up period of 19.3 months, BCR occurred in 26 cases (42.6%). DAC demonstrated a wide expression range of prostate cancer-related proteins, including nine cases (14.8%) that were totally negative for pan-cytokeratin (PanCK) immunostaining. The mTOR signaling-related proteins also showed diverse expression. On univariate analysis, BCR was associated with high preoperative serum levels of prostate-specific antigen (PSA), large tumor volume, predominant ductal component, high Gleason score (GS), comedo-necrosis, high tumor stage (pT), lymphovascular invasion, and positive surgical margin. High expressions of phospho-mTOR (p-mTOR) as well as low expressions of PSA, phospho-S6 ribosomal protein (pS6) and PanCK were associated with BCR. On multivariable analysis, GS, pT, and immunohistochemical expressions of PanCK and p-mTOR remained independent prognostic factors for BCR. Conclusions: These results suggest GS, pT, and immunohistochemical expressions of PanCK and p-mTOR as independent prognostic factors for BCR in DAC. Since DAC showed diverse expression of prostate cancer–related proteins, this should be recognized in interpreting the immunoprofile of DAC. The diverse expression of mTOR-related proteins implicates their potential utility as predictive markers for mTOR targeted therapy.

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