PDE3A Modulator Patient Stratification via Molecular Markers
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Solution Overview
Problem
Current methods for identifying cancer patients responsive to phosphodiesterase 3A (PDE3A) modulators are inadequate, as existing approaches do not effectively stratify patients based on molecular characteristics, leading to a lack of effective therapeutic options for many cancer patients.
Innovation Solution
The method involves detecting the co-expression of PDE3A and Schlafen 12 (SLFN12) polynucleotides or polypeptides, or a lack of decrease in CREB3L1 polynucleotides or polypeptides in cancer cells to identify patients responsive to PDE3A modulators, using compounds such as those with structures similar to Compounds 1-6, which are administered to reduce cancer cell survival or proliferation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current methods for identifying cancer patients are used, then patient identification is performed, but effective therapeutic options are not provided for many patients due to inadequate stratification
Solution Approach 1:
The patent segments the cancer patient population into distinct molecular subgroups based on expression levels of specific genes (PDE3A, SLFN12, CREB3L1). This segmentation allows for precise identification of patients who will respond to PDE3A modulator treatment versus those who will not, thereby improving therapeutic effectiveness without requiring overly complex stratification methods.
Solution Approach 2:
The patent uses changes in gene expression parameters (expression levels of PDE3A, SLFN12, and CREB3L1) to stratify patients. By measuring and comparing these molecular parameters against established thresholds, the method reliably identifies responsive patient populations, enhancing therapeutic effectiveness through parameter-based classification.
2Measurement precision
If molecular characterization methods are implemented to stratify patients, then treatment responsiveness can be predicted, but the complexity of detection and measurement increases
Solution Approach 1:
The patent employs universal molecular markers (PDE3A, SLFN12, CREB3L1 expression levels) that can be measured using standard, widely-available techniques such as RT-qPCR, RNA sequencing, or immunohistochemistry. This multi-functional approach allows the same molecular characterization to serve both diagnostic and prognostic purposes, improving measurement precision while leveraging existing detection infrastructure to minimize complexity.
3Productivity
If PDE3A modulators are administered to cancer patients, then cancer cell proliferation is reduced in responsive subjects, but treatment resistance cannot be identified without molecular stratification
Solution Approach 1:
The patent performs preliminary molecular stratification before administering PDE3A modulators by assessing expression levels of PDE3A, SLFN12, and CREB3L1. This preliminary action identifies patients who are likely to respond to treatment and predicts those who may develop resistance, allowing for informed treatment decisions that maximize cancer cell proliferation reduction while preventing loss of information about treatment resistance through pre-treatment molecular profiling.
Data Source
AI summary
The present invention features improved compounds, especiallymethods of identifying patients having cancer using biomarkers (e.g., PDE3A, SLFN12 and/or CREB3L1) that correlate with drug sensitivity and consequently treating a stratified patient population with an agent of the invention (e.g., Compounds 1-6 disclosed herein).