By Dr. Chinta SidharthanReviewed by Lily Ramsey, LLMJun 28 2024 In a recent study published in Nature Communications, a team of researchers used artificial intelligence to classify histopathological images and differentiate between endometrial cancer subtypes. The tool identified a subtype of endometrial cancer known as NSMP or No Specific Molecular Profile, which is characterized by aggressive disease and low survival rates.
The Cancer Genome Atlas project showed that exome and whole genome sequencing and microsatellite instability assays can be used to stratify endometrial cancers into four prognostic subtypes based on the predominant genetic mutations. The first was the POLE mutant subtype, in which the gene involved in deoxyribonucleic acid proofreading and repair—DNA polymerase epsilon or POLE—contained pathogenic mutations.
Here, the researchers used AI-based image classification to analyze the histopathological features and distinguish between the subtypes NSMP and p53abn. The researchers also conducted shallow whole-genome sequencing of representative samples from both subtypes and p53abn-like NSMP samples from the validation cohort. This data was used for analysis of copy number profiles, and gene expression profiles.
The deep learning model also identified tumors having tumor protein TP53 mutations even though the immunostaining for p53 was normal, which would have otherwise been a false negative based on immunohistochemistry classification.
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