Phosphorylated RelB Detection for Solid Cancer Prognosis
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Solution Overview
Problem
Current cancer prognostic methods lack effective markers for predicting the prognosis of solid cancers, particularly in identifying subjects with a high risk of metastasis and poor overall survival, which hinders personalized treatment strategies and resource allocation in healthcare.
Innovation Solution
Detection of phosphorylated RelB protein at serine residue 472 in cancer cell samples using antibodies or aptamers, which correlates with cytoplasmic and nuclear labelling patterns, allowing for classification of cancer prognosis and guiding therapeutic decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current cancer prognostic methods are used, then general cancer care can be provided, but accurate prediction of individual patient prognosis and identification of high-risk metastasis patients is insufficient
Solution Approach 1:
The invention changes the parameter being measured from general cancer markers to specific phosphorylated RelB protein levels at serine residue 472. This parameter change enables precise stratification of patients into good and poor prognosis groups, directly addressing the insufficiency of current prognostic markers for predicting individual patient outcomes and metastasis risk
Solution Approach 2:
The phosphorylated RelB protein serves as an intermediary biomarker that links cancer cell behavior to clinical prognosis. By detecting this specific molecular intermediary, the method bridges the gap between general cancer diagnosis and accurate individual prognosis prediction, resolving the information loss about patient-specific outcomes
2Adaptability or versatility
If personalized treatment strategies are implemented, then patient care can be optimized, but lack of reliable prognostic markers hinders effective patient stratification
Solution Approach 1:
The invention introduces a new measurable parameter (phosphorylated RelB protein levels) that enables personalized treatment stratification. By quantifying this specific parameter, clinicians can reliably adapt treatment strategies to individual patient prognosis, transforming the capability for personalized care from theoretical to practically implementable
Solution Approach 2:
The invention replaces unreliable clinical judgment and generic prognostic methods with a reliable molecular detection system. This substitution provides objective, quantifiable data that enables consistent and reliable patient stratification, forming the foundation for effective personalized treatment decisions
3Measurement precision
If effective prognostic markers are identified, then patient stratification and treatment planning can be improved, but current methods lack such markers for solid cancers
Solution Approach 1:
The invention identifies and measures a previously undetected parameter (phosphorylated RelB at serine 472) that serves as a reliable prognostic indicator. This parameter change transforms the situation from having no detectable markers to having a specific, measurable indicator that accurately classifies patients into prognostic groups
Solution Approach 2:
The phosphorylated RelB protein acts as a detectable intermediary that translates complex cancer cell behavior into a measurable signal. This intermediary makes prognosis prediction feasible by providing a concrete molecular target that can be detected and quantified using standard immunohistochemical methods
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 provides a reliable prognostic indicator for overall survival, distant metastasis-free survival, and metastasis occurrence, enabling more accurate patient stratification and treatment planning, including chemotherapy and surgical interventions.
Implementation Method 1
Detection of phosphorylated RelB protein at serine residue 472 in cancer cell samples using antibodies or aptamers
Data Source
AI summary
An in vitro method belonging to the field of medicine, more specifically the field of cancer prognostic and therapeutic management, is disclosed. The method is for classifying a subject afflicted with a solid cancer as having a good prognosis or a poor prognosis. The method comprises detecting in a cancer cell sample from the subject phosphorylated RelB protein at the serine residue 472 and/or detecting a RelB homolog phosphorylated at a corresponding serine. A kit for implementing the method also is disclosed.


