Immunotherapy Response Prediction Using TGFbeta Pathway Activity
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Solution Overview
Problem
Current methods lack the ability to reliably predict which cancer patients will respond to immunotherapy, leading to unnecessary treatment delays and high costs due to the lack of effective patient stratification for immunotherapy response.
Innovation Solution
Determine the TGFbeta cellular signaling pathway activity in a cancer patient's sample by measuring the expression levels of specific genes, such as ANGPTL4, CDC42EP3, CDKN1A, CDKN2B, CCN2, GADD45A, GADD45B, HMGA2, ID1, IL11, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SERPINE1, SGK1, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA, to predict the likelihood of a favorable response to immunotherapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If immunotherapy is administered to all cancer patients, then some patients may benefit from treatment, but many patients experience unnecessary treatment delays and high costs due to lack of response prediction
Solution Approach 1:
The patent performs TGFbeta pathway activity determination on tumor samples before initiating immunotherapy treatment. This preliminary assessment of pathway activity allows clinicians to predict treatment response in advance, identifying patients likely to benefit from immunotherapy versus those who would not respond, thereby avoiding unnecessary treatment delays for non-responders
Solution Approach 2:
The patent uses TGFbeta pathway activity level as an intermediary biomarker to mediate the decision between administering immunotherapy or alternative treatments. By measuring this intermediate parameter, the system translates complex tumor biology into a actionable prediction that guides treatment selection, separating patients into responder and non-responder groups
2Ease of operation
If immunotherapy is administered without patient stratification, then treatment access is simplified, but high costs are incurred due to treating patients who will not respond
Solution Approach 1:
The patent performs cost-effective stratification by measuring TGFbeta pathway activity in tumor samples before treatment initiation. This preliminary test uses accessible biomarkers that can be determined through standard laboratory techniques, enabling cost-effective patient selection without complex or expensive assays, thereby reducing overall treatment costs by avoiding ineffective therapies
Solution Approach 2:
The patent changes the parameter used for patient selection from broad clinical criteria to a specific molecular parameter (TGFbeta pathway activity level). This parameter change enables more precise identification of responders versus non-responders, allowing cost-effective allocation of expensive immunotherapy resources to patients most likely to benefit
Data Source
AI summary
The invention relates to a method for predicting whether a subject with cancer can successfully be treated with an immunotherapy. The method is based on measuring the TGFbeta and/or the MAPK pathway activity in a sample obtained from the subject, wherein a low TGFbeta and/or MAPK pathway activity indicates that immunotherapy is likely successful and a high TGFbeta and/or MAPK pathway activity indicates that immunotherapy is not likely to be successful. The invention further relates to an immunotherapy for use in the treatment of cancer, the use comprising determining the TGFbeta and/or MAPK pathway activity and administering the immunotherapy if the treatment is deemed likely to succeed. The invention further relates to kits of parts and their uses in the methods described herein.