Abstract

In embodiments of the invention, the invention provides a method for distinguishing between lymphoma types based on gene expression measurements. In embodiments, the invention distinguishes between PMBCL and DLBCL based on gene expression signatures, and can further distinguish between DLBCL subtypes. In embodiments of the invention, the distinctions are used in methods of treatment.

Core Innovation

The invention provides a method for distinguishing between lymphoma types based on gene expression measurements. Specifically, the invention allows distinction between primary mediastinal large B cell lymphoma (PMBCL) and diffuse large B cell lymphoma (DLBCL) using gene expression signatures. Further, the invention enables differentiation between DLBCL subtypes such as activated B-cell (ABC) DLBCL and germinal center B-cell (GCB) DLBCL. The gene expression distinctions are employed in methods of treatment.

The method includes obtaining a formalin-fixed and paraffin-embedded (FFPE) lymphoma sample from a subject, isolating RNA, measuring gene expression data for a specific set of genes, and calculating a tumor predictor score based on model coefficient values for these genes. Classification thresholds applied to the predictor score enable categorization of the lymphoma as PMBCL, DLBCL, or uncertain between PMBCL and DLBCL, and similarly among DLBCL subtypes.

The background identifies a problem in clinical pathology: reliably distinguishing PMBCL from DLBCL is challenging because current diagnosis depends on clinico-pathologic consensus and morphological or immunophenotypic features, which are often difficult to interpret. Gene expression profiling methods to distinguish these lymphoma types exist but were developed for fresh-frozen tissue and thus are not routinely available in clinical practice. There is an unmet need for a reliable gene expression-based molecular classifier that is applicable to FFPE samples for accurately distinguishing PMBCL from DLBCL and further classifying DLBCL subtypes.

Claims Coverage

The patent includes 14 claims with one independent claim directed to a method of treating lymphoma based on classification obtained from gene expression data, encompassing several features relating to sample processing, gene expression measurement, score calculation, classification, and treatment.

Method of treating lymphoma based on gene expression profiling

A method comprising obtaining an FFPE lymphoma sample, isolating RNA, obtaining gene expression data representing expression levels for specified genes, calculating a tumor predictor score using specific gene coefficients, classifying the lymphoma type based on score thresholds distinguishing PMBCL, DLBCL and DLBCL subtypes (ABC or GCB), and applying treatment accordingly.

Determining probability scores for lymphoma subtype classification

Calculating probabilities that the sample is PMBCL or ABC DLBCL using tumor predictor scores via standard normal density functions with means and standard deviations specific to lymphoma subtypes, thereby refining classification certainty.

Classification criteria based on probability scores

Defining classification rules where a high probability (≥0.9) of PMBCL indicates PMBCL regardless of ABC probability; low PMBCL (≤0.1) combined with low or high ABC probabilities classifies lymphomas as GCB DLBCL, ABC DLBCL, or unclassified DLBCL accordingly.

Use of color-coded probe assays for gene expression data acquisition

Obtaining RNA gene expression data using assays comprising color-coded probes, specifically mentioning NanoString Technologies® nCounter® assays as an example.

The claimed invention covers a comprehensive method for lymphoma classification using gene expression profiling from FFPE samples, including calculation of tumor predictor scores and probability-based classification to direct specific treatments for PMBCL and DLBCL subtypes.

Stated Advantages

Provides a robust molecular classifier applicable to formalin-fixed, paraffin-embedded samples, overcoming limitations of previous methods requiring fresh-frozen tissue.

Enables accurate distinction between PMBCL and DLBCL and subclassification within DLBCL, improving diagnostic precision.

Utilizes a nanoprobe-based assay compatible with routine clinical pathology workflows, enhancing clinical applicability.

Demonstrates high concordance with expert hematopathologist panel diagnoses and reproducibility across laboratories.

Documented Applications

Classification of lymphoma subtypes, specifically differentiating PMBCL from DLBCL and further identifying DLBCL subtypes ABC and GCB.

Assisting in selecting appropriate treatment regimens: administering dose-adjusted EPOCH-R for PMBCL classified tumors and R-CHOP for DLBCL classified tumors and subtypes.

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