Submitted:
13 February 2025
Posted:
14 February 2025
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Abstract
Since epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors were introduced in 2004, various driver gene mutations have been identified in non-small cell lung cancer, particularly adenocarcinoma, where mutations are typically mutually exclusive. EGFR and Kirsten rat sarcoma viral oncogene (KRAS) mutations are most prevalent in Japan, with routine testing now standard. However, hematoxylin and eosin (HE) staining often fails to detect mutations, except in cases such as ALK fusion lung cancer. We report a 76-year-old non-smoking Japanese woman diagnosed as having adenocarcinoma confirmed as KRAS G12D/S-positive. Histological features, including thanatosomes (hyaline globules; HGs), nuclear pleomorphism, and cytoplasmic clearing, may aid in identifying mutations. Numerous thanatosomes were identified, some containing nuclear dust. Thanatosomes revealed periodic acid-Schiff reactivity with diastase resistance, fuchsinophilia with Masson’s trichrome stain, and dark blue-black color with Mallory’s PTAH stain. This is the first report linking thanatosomes in KRAS-mutant pulmonary adenocarcinoma to apoptosis via cleaved caspase-3 staining. Research on medical applications of generative artificial intelligence (AI) has advanced significantly in recent years, and standard implementations of AI in pathology are likely not far off. Multiple studies have shown that convolutional neural networks make it possible to predict the presence of various driver gene mutations solely from HE-stained images.
Keywords:
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| EGFR | epidermal growth factor receptor |
| KRAS | Kirsten rat sarcoma viral oncogene |
| HG | hyaline globule |
| TTF | thyroid transcription factor |
| AI | artificial intelligence |
| NCC | National Cancer Center |
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