40-Gene cSCC Profiling for Recurrence and Metastasis Risk
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Solution Overview
Problem
Current clinical and pathologic features for predicting the risk of recurrence and metastasis in cutaneous squamous cell carcinoma (cSCC) are inadequate, failing to identify 30-40% of recurrences and misclassifying tumors, leading to overtreatment or undertreatment.
Innovation Solution
A 40-gene expression profile (40-GEP) test that predicts the risk of metastasis and recurrence by analyzing the expression levels of 34 genes in cSCC tumors, providing a probability score for low, moderate, or high risk classifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If clinical and pathologic features are used to predict recurrence risk, then treatment decisions can be made based on available data, but 30-40% of recurrences are missed and tumors are misclassified leading to overtreatment or undertreatment
Solution Approach 1:
The patent transitions from using traditional clinical and pathologic parameters to molecular parameters (gene expression profiles) to predict recurrence risk. This parameter change enables more precise classification of tumors into risk categories, accurately identifying recurrence risk while reducing misclassification and improving treatment decision reliability
Solution Approach 2:
The patent introduces gene expression analysis as an intermediary between traditional clinical assessment and treatment decision-making. This molecular intermediary provides additional information that bridges the gap in prediction accuracy, enabling more reliable identification of patients who will recur without causing overtreatment of low-risk patients
2Reliability
If aggressive treatment is administered to all high-risk patients, then metastasis risk is reduced, but many patients with high-risk features do not have recurrences leading to unnecessary procedures
Solution Approach 1:
The patent applies local quality by differentiating treatment intensity based on individual patient risk profiles generated by gene expression analysis. Instead of uniform aggressive treatment for all patients with high-risk clinical features, the molecular profile enables tailored treatment intensity - aggressive treatment only for those with truly high molecular risk, while low-molecular-risk patients receive conservative management, eliminating overtreatment harm while maintaining metastasis prevention for those who need it
3Ease of manufacture
If traditional risk assessment methods are used, then treatment planning can proceed with standard protocols, but the positive predictive value is insufficient to accurately identify patients at much higher risk of metastasis
Solution Approach 1:
The patent performs preliminary action by conducting gene expression analysis on tumor samples before final treatment decisions are made. This preliminary molecular risk assessment is integrated into the treatment planning process, providing accurate positive predictive value for identifying high-risk patients who need aggressive treatment, while maintaining streamlined protocols for low-risk patients, thus improving measurement precision without significantly complicating the overall treatment planning workflow
Data Source
AI summary
The present disclosure relates to methods for predicting the risk of recurrence and/or metastasis, or both in primary cutaneous squamous cell carcinoma (cSCC).