Evaluation of mantle cell lymphoma and methods related thereto
Inventors
Staudt, Louis M. • Scott, David William • Wright, George W. • Rosenwald, Andreas • Abrisqueta, Pau • Braziel, Rita • Campo Guerri, Elias • Chan, Wing C. • Connors, Joseph M. • Delabie, Jan • Villa, Diego • Fu, Kai • Gascoyne, Randy D. • Greiner, Timothy • Jaffe, Elaine S. • Jares, Pedro • Mottok, Anja • Ott, German • Rimsza, Lisa M. • Slack, Graham • Weisenburger, Dennis • Smeland, Erlend B. • Cook, James Robert
Assignees
British Columbia Cancer Agency BCCA • Julius Maximilians Universitaet Wuerzburg • Universitat de Barcelona UB • Hospital Clinic de Barcelona • Oslo Universitetssykehus hf • Cleveland Clinic Foundation • Mayo Foundation for Medical Education and Research • Oregon Health and Science University • University of Nebraska System • US Department of Health and Human Services
Publication Number
US-11725248-B2
Publication Date
2023-08-15
Expiration Date
2037-04-20
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Abstract
The present invention provides methods of determining a survival predictor score of a subject having mantle cell lymphoma (MCL). The present invention also provides methods of predicting the survival outcome of a subject having MCL and provides methods of selecting a treatment for a subject having MCL.
Core Innovation
Mantle cell lymphoma (MCL) is an incurable B-cell malignancy characterized by the t(11;14)(q13;q32) translocation leading to cyclin D1 overexpression and cell cycle dysregulation. The disease exhibits heterogeneity, with some patients experiencing aggressive progression requiring immediate treatment and others showing indolent behavior. Existing prognostic tools, such as the MCL International Prognostic Index (MIPI) and the proliferation signature derived from gene expression profiling, have clinical utility but limitations. The proliferation signature requires fresh frozen tissue and microarray platforms, while the Ki-67 proliferation index measured by immunohistochemistry has issues with reproducibility and variability.
The invention addresses these issues by providing methods to determine a survival predictor score for patients with MCL using gene expression data derived from RNA isolated from formalin-fixed paraffin-embedded (FFPE) biopsy samples. The method quantifies expression levels of a specified gene set using digital gene expression platforms, such as NanoString nCounter assays, and calculates a weighted survival predictor score by multiplying expression signal values or their log transformations by gene-specific coefficient values and summing these products. This score enables prediction of patient survival outcomes and classification into prognosis groups: good, intermediate, and poor prognosis.
Further, the invention provides methods for selecting appropriate treatments for patients based on their classified prognosis group. Treatments include chemotherapy regimens such as R-CHOP, biologic agents including BTK inhibitors, and autologous stem cell transplantation, with treatment timing potentially informed by the prognostic classification. The method leverages a refined, reproducible gene expression signature that overcomes limitations of prior proliferation assays and aids in risk-stratification and treatment decisions in MCL.
Claims Coverage
The patent contains multiple independent claims directed to methods involving determining a survival predictor score for a human subject with mantle cell lymphoma (MCL) based on gene expression data, predicting survival outcomes, and selecting treatments accordingly. Below are the main inventive features extracted from each independent claim set.
Method of determining survival predictor score using FFPE biopsy and gene expression data
Providing a formalin-fixed paraffin-embedded biopsy sample from the subject; isolating RNA gene expression product; obtaining gene expression data comprising signal values for a defined gene set; determining a survival predictor score by calculating the product of the log transformation of signal values with predefined gene-specific coefficients and summing these products.
Method of determining survival predictor score using signal values without log transformation
Providing a FFPE biopsy; isolating RNA; obtaining gene expression data with signal values for the defined gene set; calculating the survival predictor score by multiplying the signal values directly with gene-specific coefficients and summing the products.
Method of predicting survival outcome
Determining the survival predictor score via methods above; classifying the subject into good, intermediate, or poor prognosis groups based on threshold values of the survival predictor score (e.g., less than −143 for good prognosis, between −143 and −28 for intermediate, and greater than −28 for poor prognosis for log-transformed score).
Method of selecting treatment based on prognosis
Classifying the subject into prognosis groups using the survival predictor score; selecting treatments based on classification, which may include chemotherapy regimens such as R-CHOP, immunotherapy, biologic agents (BTK inhibitors, IMiDs, mTor inhibitors), bendamustine, or combinations thereof; optionally administering treatment immediately or delaying based on prognosis.
The independent claims cover methods for calculating a survival predictor score of MCL patients from gene expression obtained from FFPE biopsies, classification of survival prognosis based on that score, and selection of treatments according to prognosis. The essential inventive features lie in the defined gene sets, coefficient-weighted calculation of the survival score, the use of digital gene expression platforms for RNA from FFPE samples, and subsequent prognosis-based clinical decision making.
Stated Advantages
Provides a consistent and reproducible method to predict prognosis of MCL patients using RNA from FFPE biopsy samples compatible with clinical workflows.
Improves upon existing proliferation signatures by enabling use with archival samples and reducing variability compared to immunohistochemical methods such as Ki-67.
Enables stratification of patients into distinct prognostic groups with different median survival times, aiding clinical decision-making.
Maintains prognostic power independent of clinical indices like MIPI and integrates well with existing clinical variables.
Demonstrates low intra- and inter-laboratory variability, facilitating wide clinical applicability.
Documented Applications
Determining a survival predictor score in human subjects diagnosed with mantle cell lymphoma.
Predicting survival outcomes by classifying patients into good, intermediate, and poor prognosis groups based on gene expression data from FFPE biopsy samples.
Selecting and administering appropriate treatment regimens for mantle cell lymphoma patients based on prognosis classification, including use of chemotherapy (e.g., R-CHOP), immunotherapy, targeted biologics (BTK inhibitors, IMiDs, mTor inhibitors), bendamustine, or stem cell transplantation.
Use of the method for selecting patients in clinical trials evaluating novel agents and treatment regimens for MCL.
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