Esophageal Cancer NGS Panel for Predicting CCRT Response
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Solution Overview
Problem
Esophageal cancer, particularly esophageal squamous cell carcinoma, has a high recurrence rate and poor prognosis despite concurrent chemoradiotherapy (CCRT), with limited effective markers for predicting treatment response and prognosis.
Innovation Solution
A method involving next-generation sequencing (NGS) to detect genetic variants in tumor tissues before and after CCRT, focusing on specific gene loci such as MUC17 and MUC4, to evaluate treatment response, recurrence, and survival in esophageal cancer patients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional treatment and TNM staging are used for esophageal cancer, then treatment protocols are standardized, but prediction accuracy for treatment response and prognosis remains insufficient
Solution Approach 1:
The patent segments the genomic information into specific gene panels (MUC17, MUC4, CLDN18.2, etc.) rather than analyzing the entire genome. This segmentation allows focused detection of clinically relevant genetic variants while maintaining manageable complexity in the detection system.
Solution Approach 2:
The patent changes the parameter of detection from macroscopic TNM staging to molecular-level genetic variants. By detecting specific gene mutations and expressions, the system achieves higher prediction accuracy for treatment response and prognosis while keeping the detection protocol standardized.
2Reliability
If comprehensive genetic detection is performed to improve prognosis prediction, then prediction accuracy improves, but detection cost and complexity increase
Solution Approach 1:
The patent designs a multi-functional gene detection panel that simultaneously evaluates multiple prognostic indicators (treatment response, recurrence risk, survival probability) using a single comprehensive assay. This universal approach improves reliability without proportionally increasing complexity, as the same panel detects multiple clinical outcomes.
Solution Approach 2:
The patent performs genetic detection before treatment (neoadjuvant phase) to establish baseline prognostic information. This preliminary action allows clinicians to predict treatment response and adjust therapy plans in advance, improving overall prognosis prediction reliability while using a standardized panel.
3Productivity
If genetic variants are detected only before treatment, then detection process is simple, but post-treatment response evaluation cannot be performed
Solution Approach 1:
The patent implements a feedback mechanism by detecting genetic variants both before and after CCRT treatment. The comparison of pre- and post-treatment genetic profiles provides feedback on treatment response, allowing evaluation of whether the therapy effectively targeted the tumor's genetic drivers. This dual-timepoint approach prevents loss of treatment response information.
Solution Approach 2:
The patent maintains continuous genetic monitoring throughout the treatment journey, from pre-treatment baseline to post-treatment evaluation. This continuity ensures that useful information about treatment response is captured without interruption, enabling comprehensive prognosis assessment while maintaining efficient standardized protocols.
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
The method significantly correlates genetic variant changes with treatment response, recurrence, and survival, providing valuable predictive markers for improving the prognosis of esophageal cancer patients.
Implementation Method 1
performing next generation sequencing (NGS) to obtain at least one genomic DNA datum
Data Source
AI summary
The present disclosure provides a method and a gene detection panel for evaluating treatment response, recurrence and survival by detecting genetic variants and their changes before and after concurrent chemoradiotherapy in tumor tissues of patients with esophageal cancer. The present disclosure develops a set of esophageal cancer NGS analysis panel. Aiming at 402 mutation sites including 35 genes that frequently occur in esophageal squamous cell carcinoma tissue cells, 62 pairs of esophageal squamous cell carcinoma tissues before and after CCRT are analyzed for specific site variation, hoping to find new predictive markers. The present disclosure combines these potential markers into an esophageal cancer detection panel, which has extremely high value for improving the prognosis of esophageal cancer.