Systems and methods of oral cancer assessment using cellular phenotype data
Inventors
McDevitt, John T. • McRae, Michael P.
Assignees
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Publication Number
US-12493038-B2
Publication Date
2025-12-09
Expiration Date
Abstract
The present disclosure is related to systems and methods to be used as aids in the diagnosis of risk for oral cancer by identifying cellular phenotype characteristics of a noninvasive brush biopsy sample.
Core Innovation
The invention provides a method of treating oral cancer in a subject by identifying a cellular phenotype of one or more cells in a sample of the subject and determining four or more cellular phenotype characteristics based upon the identified cellular phenotype. The four or more cellular phenotype characteristics comprise percent of normal squamous cells, percent of small round cells, percent of white blood cells, and percent of lone nuclei.
The method uses the four or more cellular phenotype characteristics to assess the presence or severity of oral cancer in the subject. The assessed presence or severity is used to determine treatment selection, aligning cellular phenotype characteristics with oral cancer presence or severity for clinical decisioning.
The invention further provides that the subject is treated with an oral cancer treatment regimen selected from the group consisting of chemotherapy, radiation, hormone therapy, surgery, and targeted therapy. In dependent refinements, additional determinations include morphological characteristics and/or biomarker levels combined with the cellular phenotype characteristics to assess the severity of oral cancer.
Claims Coverage
Independent coverage is provided by a single independent claim method for treating oral cancer. The claim requires determining four or more cellular phenotype characteristics from an identified cellular phenotype and using those characteristics to assess presence or severity, followed by selecting an oral cancer treatment regimen from a defined group.
Identifying cellular phenotype and determining specified cellular phenotype characteristics
Identifying a cellular phenotype of one or more cells in a sample and determining four or more cellular phenotype characteristics based upon the identified cellular phenotype, wherein the four or more cellular phenotype characteristics comprise percent of normal squamous cells, percent of small round cells, percent of white blood cells, and percent of lone nuclei.
Assessing oral cancer presence or severity using the cellular phenotype characteristics
Using the four or more cellular phenotype characteristics to assess the presence or severity of oral cancer in the subject.
Selecting an oral cancer treatment regimen based on the assessed presence or severity
Treating the subject with an oral cancer treatment regimen selected from the group consisting of chemotherapy, radiation, hormone therapy, surgery, and targeted therapy.
Adding biomarker levels with cellular phenotype characteristics for severity assessment
Determining biomarker levels in cells from a sample, transmitting those levels to a computer, and using the cellular phenotype characteristics together with the biomarker levels to assess the severity of oral cancer in a subject.
Adding morphological characteristics with cellular phenotype characteristics for severity assessment
Determining morphological characteristics from individual cells, transmitting those morphological characteristics to a computer, and using the cellular phenotype characteristics together with the morphological characteristics to assess the severity of oral cancer in a subject.
Distinguishing normal, benign lesions, dysplasia grades, carcinoma in situ, and malignant lesions
Distinguishing between normal tissue, benign lesions, different dysplasia grades, carcinoma in situ, and malignant lesions.
Calculating a risk score from cellular phenotype characteristics
Calculating a risk score based on the cellular phenotype characteristics.
Risk-score calculation using specified machine-learning classifiers
Calculating the risk score using artificial neural nets, logistic regression, linear discriminant analysis, or random forests.
Across the independent claim and dependent refinements, the core coverage centers on using specified cellular phenotype percentages to assess oral cancer presence or severity and then selecting an oral cancer treatment regimen from chemotherapy, radiation, hormone therapy, surgery, and targeted therapy. Dependent claims expand the severity assessment with morphological characteristics and/or biomarker levels, provide category outputs including dysplasia grades and carcinoma in situ/malignant, and optionally compute a risk score using specified modeling approaches.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Not explicitly described in patent.
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