Neural Tumor Classification via Gene Expression ML
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Solution Overview
Problem
Current cancer treatments, such as immune checkpoint blockade therapy, are not effective for all tumors due to variations in tumor types and patient responses, highlighting the need for better characterization of individual tumors to determine suitable treatment options.
Innovation Solution
A computer-implemented method using a machine-learning model trained on gene-expression data to identify whether a tumor is neurally related or non-neurally related, enabling the specification of a gene panel for checkpoint-blockade-therapy amenability and recommending personalized therapy approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If immune checkpoint blockade therapy is applied to all tumors, then T-cell activation is promoted, but treatment effectiveness varies significantly across different tumor types
Solution Approach 1:
The patent segments tumors into distinct molecular subtypes (e.g., neural subtype, mesenchymal subtype, luminal subtype) based on gene expression profiles. This segmentation allows for tailored treatment recommendations within each subtype, improving treatment effectiveness by matching therapy to specific tumor characteristics rather than applying a uniform approach to all tumors.
Solution Approach 2:
The patent changes the parameter of tumor characterization from broad histological classification to detailed molecular subtyping based on gene expression patterns. By analyzing expression levels of multiple genes and identifying specific molecular signatures, the system transforms how tumors are categorized, enabling more precise treatment selection and improving reliability of treatment outcomes.
2Reliability
If personalized treatment approaches are implemented based on tumor characterization, then treatment efficacy is improved, but complexity of treatment decision-making increases
Solution Approach 1:
The patent introduces a computational classification system as an intermediary between tumor analysis and treatment selection. This intermediary processes complex gene expression data and translates it into clear molecular subtype classifications, which then guide treatment decisions. This intermediary simplifies the decision-making process by providing structured, data-driven recommendations rather than requiring clinicians to directly interpret complex molecular data.
Solution Approach 2:
The patent performs preliminary classification of tumors into molecular subtypes before treatment selection is made. By pre-characterizing tumors based on gene expression profiles and assigning them to specific molecular categories, the system prepares treatment recommendations in advance, reducing the complexity of real-time treatment decision-making and improving efficiency.
3Measurement precision
If comprehensive gene expression analysis is performed on all tumors, then accurate tumor classification is achieved, but cost and time requirements increase
Solution Approach 1:
The patent extracts and focuses on specific genes and gene pathways that are most informative for distinguishing between molecular subtypes. Rather than analyzing all possible genes, the system identifies and measures a targeted set of genes that provide the highest classification accuracy. This extraction of key features maintains measurement precision while reducing the overall analytical burden and time requirements.
Data Source
AI summary
Embodiments disclosed herein generally relate to classifying a tumor, based on gene expression data, as being neurally related or non-neurally related. The tumor may be classified using a machine-learning model, which may have been trained to differentiate gene-expression data associated with neuronal or neuroendocrine tumors from gene-expression data associated with non-neuronal and non-neuroendocrine tumors. Differential treatment and/or treatment recommendations may be provided based on the classification. First-line checkpoint blockade therapy may be used or recommended when a tumor is identified as being non-neurally related, and a combination therapy (e.g., initial chemotherapy and subsequent checkpoint blockade therapy) may be used or recommended when a tumor is identified as being neurally related.