Publications by authors named "Margaret Maltseva"
Article Synopsis
- Human papillomavirus (HPV) is linked to oropharyngeal squamous cell carcinoma (OPSCC) and tends to offer a better prognosis than tumors from other causes, such as tobacco or alcohol.
- A deep learning model was created to predict HPV association from standard hematoxylin and eosin (H&E) stained slides, showing better accuracy than traditional pathologists' assessments and effectively stratifying patient prognosis.
- The deep learning HPV prediction score (HPV-ps) can be used alone or with p16 status to identify patients with OPSCC who have a favorable prognosis, potentially improving patient management compared to existing biomarker methods.
Human papillomavirus type 16 (HPV16) is a major risk for development of oropharyngeal squamous-cell-carcinoma (OPSCC). Although HPV OPSCC metastasize faster than HPV tumors, they have a better prognosis. The molecular and cellular alterations underlying this pathobiology of HPV OPSCC remain elusive.
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