Journal of Pathology and Translational Medicine

Original Articles

Categorizing high-grade serous ovarian carcinoma into clinically relevant subgroups using deep learning–based histomic clusters: Byungsoo Ahn, Eunhyang Park; J Pathol Transl Med. 2025;59(2):91-104. Published online February 18, 2025; DOI: https://doi.org/10.4132/jptm.2024.10.23

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Abstract PDF Supplementary Material: Background
High-grade serous ovarian carcinoma (HGSC) exhibits significant heterogeneity, posing challenges for effective clinical categorization. Understanding the histomorphological diversity within HGSC could lead to improved prognostic stratification and personalized treatment approaches. Methods: We applied the Histomic Atlases of Variation Of Cancers model to whole slide images from The Cancer Genome Atlas dataset for ovarian cancer. Histologically distinct tumor clones were grouped into common histomic clusters. Principal component analysis and K-means clustering classified HGSC samples into three groups: highly differentiated (HD), intermediately differentiated (ID), and lowly differentiated (LD). Results: HD tumors showed diverse patterns, lower densities, and stronger eosin staining. ID tumors had intermediate densities and balanced staining, while LD tumors were dense, patternless, and strongly hematoxylin-stained. RNA sequencing revealed distinct patterns in mitochondrial oxidative phosphorylation and energy metabolism, with upregulation in the HD, downregulation in the LD, and the ID positioned in between. Survival analysis showed significantly lower overall survival for the LD compared to the HD and ID, underscoring the critical role of mitochondrial dynamics and energy metabolism in HGSC progression. Conclusions: Deep learning-based histologic analysis effectively stratifies HGSC into clinically relevant prognostic groups, highlighting the role of mitochondrial dynamics and energy metabolism in disease progression. This method offers a novel approach to HGSC categorization.

Senescent tumor cells in colorectal cancer are characterized by elevated enzymatic activity of complexes 1 and 2 in oxidative phosphorylation: Jun Sang Shin, Tae-Gyu Kim, Young Hwa Kim, So Yeong Eom, So Hyun Park, Dong Hyun Lee, Tae Jun Park, Soon Sang Park, Jang-Hee Kim; J Pathol Transl Med. 2023;57(6):305-314. Published online November 7, 2023; DOI: https://doi.org/10.4132/jptm.2023.10.09

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Background
Cellular senescence is defined as an irreversible cell cycle arrest caused by various internal and external insults. While the metabolic dysfunction of senescent cells in normal tissue is relatively well-established, there is a lack of information regarding the metabolic features of senescent tumor cells.
Methods
Publicly available single-cell RNA-sequencing data from the GSE166555 and GSE178341 datasets were utilized to investigate the metabolic features of senescent tumor cells. To validate the single-cell RNA-sequencing data, we performed senescence-associated β-galactosidase (SA-β-Gal) staining to identify senescent tumor cells in fresh frozen colorectal cancer tissue. We also evaluated nicotinamide adenine dinucleotide dehydrogenase–tetrazolium reductase (NADH-TR) and succinate dehydrogenase (SDH) activity using enzyme histochemical methods and compared the staining with SA-β-Gal staining. MTT assay was performed to reveal the complex 1 activity of the respiratory chain in in-vitro senescence model.
Results
Single-cell RNA-sequencing data revealed an upregulation in the activity of complexes 1 and 2 in oxidative phosphorylation, despite overall mitochondrial dysfunction in senescent tumor cells. Both SA-β-Gal and enzyme histochemical staining using fresh frozen colorectal cancer tissues indicated a high correlation between SA-β-Gal positivity and NADH-TR/SDH staining positivity. MTT assay showed that senescent colorectal cancer cells exhibit higher absorbance in 600 nm wavelength.
Conclusions
Senescent tumor cells exhibit distinct metabolic features, characterized by upregulation of complexes 1 and 2 in the oxidative phosphorylation pathway. NADH-TR and SDH staining represent efficient methods for detecting senescent tumor cells in colorectal cancer.

Citations

Citations to this article as recorded by

Cellular Aging and Senescence in Cancer: A Holistic Review of Cellular Fate Determinants
Muhammad Tufail, Yu-Qi Huang, Jia-Ju Hu, Jie Liang, Cai-Yun He, Wen-Dong Wan, Can-Hua Jiang, Hong Wu, Ning Li
Aging and disease.2024;[Epub] CrossRef
Real-time assessment of relative mitochondrial ATP synthesis response against inhibiting and stimulating substrates (MitoRAISE)
Eun Sol Chang, Kyoung Song, Ji-Young Song, Minjung Sung, Mi-Sook Lee, Jung Han Oh, Ji-Yeon Kim, Yeon Hee Park, Kyungsoo Jung, Yoon-La Choi
Cancer & Metabolism.2024;[Epub] CrossRef

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