Tumor Minimal Residual Disease Stratification by Drug-Tolerant Cell Signatures
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Solution Overview
Problem
The emergence of drug-tolerant and drug-resistant subpopulations within tumors, particularly in melanoma, poses a significant challenge to effective targeted therapy, as current methods fail to account for the heterogeneous nature of cancer cells, leading to rapid acquisition of resistance.
Innovation Solution
The method involves analyzing gene expression signatures in tumor samples to identify specific subpopulations, such as neural drug-tolerant cells (NDTCs), hypometabolic cells (HMTCs), pigmented cells, and invasive cells, using gene signatures A1 to D1, and selecting or optimizing therapy based on these profiles to target these subpopulations with compounds like CD36 antagonists, AXL inhibitors, or melanocyte-directed enzyme prodrugs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If targeted therapy is applied to treat tumor cells, then initial treatment response is improved, but rapid acquisition of resistance occurs due to heterogeneous tumor cell populations
Solution Approach 1:
The patent segments the heterogeneous tumor cell population into distinct subpopulations based on gene expression profiles (e.g., MITF-high, AXL-high, neural stem cell-like, invasive cells). This segmentation allows identification and targeting of specific resistant subpopulations that conventional bulk therapy misses, thereby extending treatment efficacy by addressing resistance mechanisms at the subpopulation level
Solution Approach 2:
The patent performs preliminary characterization of tumor cell subpopulations through single-cell or bulk RNA sequencing before treatment initiation. By pre-identifying resistant subpopulations and their marker genes, the therapy can be optimized to target these subpopulations proactively, preventing resistance acquisition rather than reacting to it after it develops
2Ease of operation
If conventional bulk therapy is used, then treatment simplicity is maintained, but tumor cell heterogeneity is ignored leading to treatment failure
Solution Approach 1:
The patent applies local quality by tailoring therapy strategies to specific tumor subpopulations based on their unique gene expression profiles. Instead of uniform bulk therapy, the approach identifies locally distinct subpopulations (e.g., neural stem cell-like cells with specific markers) and selects targeted therapies appropriate for each subpopulation, thereby maintaining treatment simplicity at the patient level while achieving heterogeneity-aware precision at the cellular level
3Measurement precision
If single-cell analysis is performed to identify subpopulations, then treatment precision is improved, but analysis complexity and cost increase
Solution Approach 1:
The patent extracts and focuses on specific marker genes and gene expression signatures that are characteristic of resistant subpopulations (e.g., MITF, AXL, GFRA2, CD36). By concentrating analysis on these key markers rather than performing comprehensive single-cell sequencing of all genes, the approach maintains high measurement precision for subpopulation detection while reducing analytical complexity and computational resource requirements
Data Source
Figure 1A~1C
Figure 1D
Figure 2A~2E
AI summary
The invention relates to the field of tumor disease stratification, in particular melanoma disease stratification. In particular it relates to the methods for tumor analysis, such as for determining tumor cell heterogeneity during treatment. These methods are helpful in selecting or optimizing tumor therapy, or in predicting responses to tumor therapy. The invention further relates to methods for screening for cytotoxic or cytostatic compounds targeting one or more of the heterogeneous tumor cell populations occurring such as during therapy, such as during the minimal residual disease phase.