DLBCL Molecular Classification for Targeted Combination Therapy
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Solution Overview
Problem
Current treatments for diffuse large B-cell lymphoma (DLBCL) are inadequate for patients with recurrent or progressive disease, and there is a need for improved compositions and methods to address the genetic heterogeneity of this lymphoma.
Innovation Solution
A method for classifying DLBCL into distinct classes based on specific sequence variants and copy number variations, followed by tailored therapeutic options such as NOTCH inhibitors, BCL6 inhibitors, BCR/TLR signaling inhibitors, BCL2 inhibitors, PI3K inhibitors, epigenetic modifier inhibitors, JAK/STAT inhibitors, and BRAF/MEK1 inhibitors, using techniques like whole exome sequencing and oligonucleotide probes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard combination therapy (R-CHOP) is used for DLBCL treatment, then curability is achieved in over 60% of patients, but treatment options remain limited for patients with recurrent or progressive disease
Solution Approach 1:
The patent segments DLBCL into five distinct molecular classes (C1-C5) based on specific genetic alterations and pathogenic mechanisms. Each class is characterized by unique combinations of mutations, copy number variations, and functional pathways, enabling differentiated treatment strategies rather than using a single standardized therapy for all patients.
Solution Approach 2:
The invention applies local quality by tailoring therapeutic interventions to specific molecular subtypes. Different classes receive targeted therapies based on their predominant pathogenic mechanisms—for example, NOTCH inhibitors for C1, BCL2 inhibitors for C2, PI3K inhibitors for C3, epigenetic modifiers for C4, and JAK/STAT inhibitors for C5—thereby optimizing treatment efficacy for each local molecular context.
2Device complexity
If DLBCL is treated as a homogeneous disease, then treatment protocols are simplified, but therapeutic efficacy is reduced due to genetic heterogeneity
Solution Approach 1:
The patent divides DLBCL into five molecularly distinct classes based on comprehensive genomic profiling, including specific mutations (e.g., MYD88, CD79B, BRAF), copy number variations (e.g., 18q, 3q), and functional pathway analyses. This segmentation enables precision medicine approaches that match treatments to specific molecular drivers, thereby improving therapeutic efficacy despite increased classification complexity.
3Reliability
If personalized treatment strategies are implemented for each molecular class, then therapeutic efficacy is enhanced, but diagnostic and treatment selection complexity increases
Solution Approach 1:
The patent performs preliminary molecular classification using a standardized panel of genetic markers and algorithms before treatment selection. By pre-characterizing patients into molecular classes based on defined criteria (e.g., presence of MYD88 L265P mutation, specific copy number variations, expression profiles), the system enables systematic treatment matching without requiring overly complex real-time decision-making during patient care.
Data Source
AI summary
The present disclosure relates to compositions and methods for the diagnosis and treatment or prevention of DLBCL. In particular, the instant disclosure provides a DLBCL classifier that has identified at least five distinct classes of DLBCL cancer, each of which possesses distinct pathogenic mechanisms and outcomes. The instant classifier identifies preferred therapeutic options (including combination therapies) for each such class of DLBCL cancer.