Peripheral Blood Immunoprofiling for Immunotherapy Response Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for immunoprofiling, such as RNA sequencing and cytometry, are inadequate in determining leukocyte profiles for cancer patients, particularly in predicting cancer prognosis and response to immunotherapy without considering the patient's health status.
Innovation Solution
A method involving flow cytometry and RNA expression analysis is used to determine leukocyte immunoprofiles by processing cytometry or RNA expression data to identify cell composition percentages for at least 20 cell types, generating a leukocyte signature, and identifying a specific immunoprofile type using machine learning models and clustering algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If flow cytometry and RNA expression analysis are used to determine leukocyte immunoprofiles, then measurement precision and predictive accuracy are improved, but device complexity and analysis complexity increase
Solution Approach 1:
The patent segments the complex immunoprofiling process into distinct analytical components: flow cytometry data acquisition for cell surface markers, RNA expression analysis for intracellular gene profiles, and separate computational pipelines for integrating these multi-omic datasets. This segmentation allows each component to be optimized independently while maintaining overall system precision.
Solution Approach 2:
The patent employs parameter changes by analyzing multiple dimensions of leukocyte characterization simultaneously - combining physical parameters (flow cytometry fluorescence intensities, cell size, granularity) with molecular parameters (RNA expression levels of immune-related genes). This multi-parameter approach enhances measurement precision by capturing both phenotypic and functional states of immune cells.
2Loss of information
If comprehensive cytometry data processing is performed to determine cell composition percentages for multiple cell types, then information completeness is improved, but loss of time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-defining panels of cell surface markers and RNA genes that are most relevant for cancer immunoprofiling before sample analysis. These pre-selected marker panels enable rapid identification of key leukocyte subsets without requiring comprehensive analysis of all possible cell types, thus reducing processing time while maintaining diagnostic completeness.
Solution Approach 2:
The patent extracts and focuses on specific critical information from the comprehensive cytometry and RNA data - namely, the percentages of key immune cell types (CD4+ T cells, CD8+ T cells, B cells, NK cells, monocytes) and their activation states. By extracting only the most diagnostically relevant parameters from the full dataset, the system maintains information completeness for clinical decision-making while reducing computational burden.
3Adaptability or versatility
If leukocyte immunoprofile analysis is performed independent of patient health status, then adaptability and generalizability are improved, but measurement precision for specific cancer types may decrease
Solution Approach 1:
The patent implements universality by developing a health-status-independent leukocyte immunoprofiling methodology that can be applied to both healthy individuals and cancer patients. The same flow cytometry panels and RNA expression assays are used across all subject groups, allowing the system to identify conserved immune cell population patterns that are relevant regardless of disease state, thereby enhancing adaptability and generalizability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables accurate prediction of cancer prognosis and likelihood of response to immunotherapy by characterizing leukocyte populations, allowing for personalized treatment decisions based on leukocyte immunoprofiles.
Implementation Method 1
Flow cytometry measures the intensity produced by fluorescent markers that are used to label cells in the biological sample
Data Source
AI summary
Aspects of the disclosure relate to methods, systems, and computer-readable storage media, that are useful for characterizing subjects having cancer. The disclosure is based, in part, on methods for immunoprofiling a cancer subject and the subject's prognosis and/or likelihood of responding to an immunotherapy based upon analysis of leukocyte populations in the peripheral blood of the subject.