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EP-4737591-A1 - METHOD AND KIT FOR DIAGNOSIS, PROGNOSIS, AND/OR STRATIFICATION OF DIFFUSE LARGE B-CELL LYMPHOMA (DLBCL)

EP4737591A1EP 4737591 A1EP4737591 A1EP 4737591A1EP-4737591-A1

Abstract

The present invention relates to a method and a kit for the diagnosis, prognosis, and/or stratification of diffuse large B-cell lymphoma (DLBCL).

Inventors

  • The designation of the inventor has not yet been filed

Assignees

  • Johann-Wolfgang-Goethe-Universität Frankfurt am Main
  • Deutsches Krebsforschungszentrum Stiftung des öffentlichen Rechts

Dates

Publication Date
20260506
Application Date
20241105

Claims (15)

  1. A method for the diagnosis, prognosis, and/or stratification of a diffuse large B-cell lymphoma (DLBCL) of a patient, comprising the steps of a) providing a sample of said patient, b) determining whether said sample comprises at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v): i) a genotype comprising an activated B-cell genotype with a MYD88 L265P mutation and a CD79B mutation, or a double-hit signature positive germinal center B-cell genotype; wherein, preferably, said genotype further comprises a BTG1 mutation and/or a TBL1XR1 mutation; ii) a dark-zone phenotype; iii) an enhanced signaling of TCF3, TCF4, MYC, BCR, MYD88, and/or PI3K compared to a control; wherein, preferably, the control is a reference sample, a collection of reference samples, a reference value, or a collection of reference values; wherein, more preferably, the control is a reference sample, a collection of reference samples, a reference value, or a collection of reference values of a healthy individual, a healthy cohort, or a cohort of DLBCL patients; iv) an enhanced expression of one or more, preferably a plurality of proteins selected from ribosomal proteins and ribosome-associated proteins, preferably ribosomal proteins, compared to the control; v) a tumor microenvironment characterized by depleted T cells compared to the control, preferably by depleted CD8+ effector memory T-cells compared to the control; wherein the presence of at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v) in said sample of said patient is indicative for the presence of a high-risk diffuse large B-cell lymphoma (DLBCL) in said patient.
  2. The method according to claim 1, wherein said determining in step b) comprises determining whether said sample comprises an enhanced signaling of TCF3, TCF4, MYC, BCR, MYD88, and/or PI3K compared to the control; wherein, preferably, said determining comprises determining whether said sample comprises an enhanced signaling of at least two, preferably at least three, more preferably at least four, even more preferably all of TCF3, TCF4, MYC, BCR, MYD88, and PI3K compared to the control.
  3. The method according to claim 1 or 2, wherein step b) comprises determining whether said sample comprises at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v): i) a genotype comprising an activated B-cell genotype with a MYD88 L265P mutation and a CD79B mutation; wherein, preferably, said genotype further comprises a BTG1 mutation and/or a TBL1XR1 mutation; ii) a dark-zone phenotype; iii) an enhanced signaling of TCF4, MYC, BCR, MYD88, and/or PI3K compared to the control, preferably of TCF4, MYC, BCR, MYD88, and PI3K compared to the control; iv) an enhanced expression of one or more, preferably a plurality of proteins selected from ribosomal proteins and ribosome-associated proteins, preferably ribosomal proteins, compared to the control; v) a tumor microenvironment characterized by depleted T cells compared to the control, preferably by depleted CD8+ effector memory T-cells compared to the control; wherein the presence of at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v) in said sample of said patient is indicative for the presence of a high-risk DLBCL in said patient.
  4. The method according to claim 1 or 2, wherein step b) comprises determining whether said sample comprises at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v): i) a genotype comprising a double-hit signature positive germinal center B-cell genotype; wherein, preferably, said genotype further comprises a BTG1 mutation and/or a TBL1XR1 mutation; ii) a dark-zone phenotype; iii) an enhanced signaling of TCF3, MYC, BCR, and/or PI3K compared to the control, preferably of TCF3, MYC, BCR, and PI3K compared to the control; iv) an enhanced expression of one or more, preferably a plurality of proteins selected from ribosomal proteins and ribosome-associated proteins, preferably ribosomal proteins, compared to the control; v) a tumor microenvironment characterized by depleted T cells compared to the control, preferably by depleted CD8+ effector memory T-cells compared to the control; wherein the presence of at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v) in said sample of said patient is indicative for the presence of a high-risk DLBCL in said patient.
  5. The method according to any one of the foregoing claims, wherein said determining in step b) comprises determining whether said sample comprises an enhanced expression of one or more, preferably a plurality of proteins selected from ribosomal proteins and ribosome-associated proteins, preferably ribosomal proteins, compared to the control.
  6. The method according to any one of the foregoing claims, wherein said determining in step b) comprises determining whether said sample comprises a tumor microenvironment characterized by depleted T cells compared to the control, preferably by depleted CD8+ effector memory T-cells compared to the control.
  7. The method according to any one of the foregoing claims, wherein said determining in step b) comprises determining whether said sample comprises a dark-zone phenotype; wherein, optionally, said determining in step b) comprises determining whether said sample comprises ii) a dark-zone phenotype; iii) an enhanced signaling of TCF3, TCF4, and/or MYC compared to the control, preferably TCF3, TCF4, and MYC compared to the control; iv) an enhanced expression of one or more, preferably a plurality of proteins selected from ribosomal proteins and ribosome-associated proteins, preferably ribosomal proteins, compared to the control; and v) a tumor microenvironment characterized by depleted T cells compared to the control, preferably by depleted CD8+ effector memory T-cells compared to the control.
  8. The method according to any one of the foregoing claims, wherein said enhanced signaling of TCF3, TCF4, MYC, BCR, MYD88, and/or PI3K compared to the control comprises an enhanced signaling of TCF4, MYC, BCR, and MYD88; TCF3, MYC, BCR, and PI3K; TCF3; TCF4; MYC; BCR; MYD88; PI3K; TCF3 and TCF4; TCF3 and MYC; TCF3 and BCR; TCF3 and MYD88; TCF3 and PI3K; TCF4 and MYC; TCF4 and BCR; TCF4 and MYD88; TCF4 and PI3K; MYC and BCR; MYC and MYD88; MYC and PI3K; BCR and MYD88; BCR and PI3K; MYD88 and PI3K; TCF3, TCF4, and MYC; TCF3, TCF4, and BCR; TCF3, TCF4, and MYD88; TCF3, TCF4, and PI3K; TCF3, MYC, and BCR; TCF3, MYC, and MYD88; TCF3, MYC, and PI3K; TCF3, BCR, and MYD88; TCF3, BCR, and PI3K; TCF3, MYD88, and PI3K; TCF4, MYC, and BCR; TCF4, MYC, and MYD88; TCF4, MYC, and PI3K; TCF4, BCR, and MYD88; TCF4, BCR, and PI3K; TCF4, MYD88, and PI3K; MYC, BCR, and MYD88; MYC, BCR, and PI3K; MYC, MYD88, and PI3K; BCR, MYD88, and PI3K; TCF3, TCF4, MYC, and BCR; TCF3, TCF4, MYC, and MYD88; TCF3, TCF4, MYC, and PI3K; TCF3, TCF4, BCR, and MYD88; TCF3, TCF4, BCR, and PI3K; TCF3, TCF4, MYD88, and PI3K; TCF3, MYC, BCR, and MYD88; TCF3, MYC, MYD88, and PI3K; TCF3, BCR, MYD88, and PI3K; TCF4, MYC, BCR, and PI3K; TCF4, MYC, MYD88, and PI3K; TCF4, BCR, MYD88, and PI3K; MYC, BCR, MYD88, and PI3K; TCF3, TCF4, MYC, BCR, and MYD88; TCF3, TCF4, MYC, BCR, and PI3K; TCF3, TCF4, MYC, MYD88, and PI3K; TCF3, TCF4, BCR, MYD88, and PI3K; TCF3, MYC, BCR, MYD88, and PI3K; TCF4, MYC, BCR, MYD88, and PI3K; or TCF3, TCF4, MYC, BCR, MYD88, and PI3K; preferably comprises an enhanced signaling of TCF4, MYC, BCR, and MYD88 or an enhanced signaling of TCF3, MYC, BCR, and PI3K; wherein said enhanced signaling is indicative for the presence of a high-risk DLBCL in said patient.
  9. The method according to any one of the foregoing claims, wherein said one or more, preferably a plurality of proteins are selected from PCNA, MCM6, NCL, PAICS, MYBBP1A, SSRP1, MCM4, CSDE1, MCM5, MCM3, PABPC4, SUPT16H, NASP, DDX21, BZW2, NAT10, PABPC1, RRP12, IGF2BP3, SMC4, LRPPRC, NOP2, POLD1, MTHFD1L, MKI67, FEN1, TOP2A, DDX18, PDCD11, PA2G4, SHMT2, CDC2, CCDC58, MSH2, NME1-NME2, HSPD1, GART, HSPA9, UBAP2, TOP1, MCM7, RRM1, RPL4, LYAR, GEMIN5, RRM2, GARS, IPO5, RUVBL1, GRPEL1, EEF2, NCAPH, RANBP1, IARS, RSL1D1, EEF1B2, SLIRP, NME1, ABCF2, PNPT1, MCM2, FKBP4, PBK, IMPDH2, ATXN10, DUT, TRAP1, RPL3, NOC2L, LDHA, MRTO4, YBX1, FARSB, SLC25A5, HNRNPA1, NUDC, HSP90AB1, KPNA2, ASNS, BAG2, NPM1, UTP18, TDP2, HSPE1, UTP14A, RPL35A, MARS, LDHB, RPS9, NOLC1, BTK, IMP4, NOL7, WDR3, PSMG1, SLC25A19, ALDH18A1, NIP7, CAD, C1QBP, NOL6, WDHD1, EEF1E1, NOB1, BTF3, MAD2L1, CYCS, PNO1, RPL26, TBRG4, WDR75, CACYBP, and combinations thereof.
  10. The method according to any one of the foregoing claims, wherein said tumor microenvironment is characterized by depleted CD4+ T cells and/or depleted CD8+ T cells compared to the control; preferably by depleted follicular helper T cells and/or memory T cells compared to the control; more preferably by depleted CD8+ effector memory T-cells compared to the control.
  11. The method according to any one of the foregoing claims, wherein said tumor microenvironment is further characterized by exhausted T cells compared to the control, preferably exhausted cytotoxic T cells, more preferably exhausted cytotoxic T cells of the EM2 and/or EM3 compartment.
  12. The method according to any one of the foregoing claims, wherein said method comprises predicting a reduced time of progression-free survival and/or a reduced time of overall survival of said patient if said sample comprises at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v).
  13. The method according to any one of the foregoing claims, wherein said method comprises stratifying said patient for an R-CHOP treatment, wherein said method comprises deciding in favor of or against said treatment based on the presence or absence of features i)-v), wherein, if features i)-v) are absent in said sample, the decision is in favor of the R-CHOP treatment, and wherein, if features i)-v) are present in said sample, the decision is against said R-CHOP treatment and optionally in favor of a treatment other than an R-CHOP treatment, such as a CAR T-cell therapy, a treatment with a bispecific antibody, and/or a treatment with venetoclax, ibrutinib, prednisone, obinutuzumab, and lenalidomide (ViPOR).
  14. The method according to any one of the foregoing claims, wherein said determining in step b) comprises analyzing i) said genotype using sequencing such as RNA sequencing, optionally single cell sequencing; ii) said dark-zone phenotype using RNA sequencing; iii) said enhanced signaling using RNA sequencing, mass spectrometry, single cell sequencing, or an immunoassay such as ELISA; preferably using RNA sequencing, mass spectrometry, or single cell sequencing; iv) said one or more, preferably said plurality of proteins selected from ribosomal proteins and ribosome-associated proteins, preferably ribosomal proteins, using RNA sequencing, mass spectrometry, or an immunoassay such as ELISA; preferably using mass spectrometry; and v) said tumor microenvironment using flow cytometry, mass cytometry, and/or sequencing such as single cell sequencing; thereby obtaining biological data, wherein, optionally, said determining further comprises analyzing said biological data using a computer-implemented method which comprises a machine learning algorithm.
  15. A kit for performing a method according to any one of the foregoing claims, the kit comprising means for determining at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v), and comprising instructions for performing the method according to any one of the foregoing claims; wherein, preferably, the kit comprises means for performing proteomics, transcriptomics, single cell sequencing, and/or an immunoassay; wherein, more preferably, the kit comprises means for performing RNA extraction, cDNA library preparation, and/or sequencing, and optionally further comprises instructions for data analysis.

Description

FIELD OF THE INVENTION The present invention relates to a method and a kit for the diagnosis, prognosis, and/or stratification of diffuse large B-cell lymphoma (DLBCL). BACKGROUND OF THE INVENTION Diffuse large B-cell lymphoma (DLBCL) is a genetically and clinically heterogenous disease. While about 60-70% of DLCBL patients can be cured with R-CHOP chemoimmunotherapy, 30-40% have either primary refractory disease or relapse after treatment. Gene expression profiling was the first step towards resolving this clinical heterogeneity. Two dominant gene expression subtypes were identified: the germinal center B cell-like (GCB) and activated B cell-like (ABC) lymphomas, expressing a gene expression program akin to either GC B cells or B cells activated through their B-cell antigen receptor, respectively. The fact that 10-15% of DLBCL remain unclassifiable by gene expression profiling and that several clinical studies revealed discrepant clinical outcome of the individual cell-of-origin subtypes point towards further molecular heterogeneity. Therefore, subsequent studies have elucidated the genomic landscape of DLBCL and established a genetic classification with seven major genetic subtypes, each being characterized by a specific pattern of genomic alterations. Distinct genetic profiles were found to be associated with the ABC or GCB gene expression profiles. For instance, tumors with mutations in the B-cell receptor (BCR) subunit CD79B and the immune signaling adapter protein MYD88 (the MCD/C5 genetic subtype) were identified as the most prevalent form of ABC-DLBCL. In contrast, mutations in the EZH2 gene and translocations of BCL2 were mainly found in GCB tumors. Importantly, some genetic alterations are linked to specific survival pathways that can be therapeutically exploited. The ABC-MCD-DLBCL subtype relies on chronic active BCR/NF-κB signaling and is sensitive to inhibitors targeting this pathway, while it is less sensitive to R-CHOP treatment. In contrast, GCB-EZB-DLBCL is more sensitive to chemoimmunotherapy and dependent on tonic BCR signaling mainly engaging the PI3-kinase pathway. Other genetic subtypes such as BN2, characterized by genetic alterations in BCL6 and NOTCH2, are associated with the ABC, GCB, and unclassifiable gene expression profiles, highlighting further molecular complexity of the disease. Even though the genomic characterization of DLBCL has revolutionized our molecular understanding of DLBCL, challenges remain. About half of the DLBCL cases that fail to respond to first-line chemoimmunotherapy cannot be diagnosed and explained by mere genomics. Thus, more efficient diagnostic and therapeutic strategies for such high-risk DLBCLs are urgently needed. There is growing evidence that tumor cell-intrinsic mechanisms beyond genomics, such as deregulated post-transcriptional and translational programs, as well as tumor microenvironment (TME)-related features strongly contribute to the pathophysiology of DLBCL and thereby critically influence the therapeutic responsiveness of the individual tumors [3]. Accordingly, there is the need to provide suitable biomarkers, particularly predictive biomarkers, for diagnosing high-risk DLBCL in a patient. Furthermore, there is the need for a method that allows for the diagnosis, prognosis, and/or stratification of a diffuse large B-cell lymphoma (DLBCL) of a patient. There is also the need to provide effective means to identify high-risk DLBCL, particularly means allowing to provide a prognosis for a patient. Furthermore, there is the need to predict an R-CHOP treatment outcome. There is also the need for means that allow for personalized treatments of DLBCL patients. SUMMARY OF THE INVENTION In the following, the elements of the invention will be described. These elements are listed with specific embodiments, however, it should be understood that they may be combined in any manner and in any number to create additional embodiments. The variously described examples and preferred embodiments should not be construed to limit the present invention to only the explicitly described embodiments. This description should be understood to support and encompass embodiments which combine two or more of the explicitly described embodiments or which combine the one or more of the explicitly described embodiments with any number of the disclosed and/or preferred elements. Furthermore, any permutations and combinations of all described elements in this application should be considered disclosed by the description of the present application unless the context indicates otherwise. In a first aspect, the present invention relates to a method for the diagnosis, prognosis, and/or stratification of a diffuse large B-cell lymphoma (DLBCL) of a patient, comprising the steps of a) providing a sample of said patient,b) determining whether said sample comprises at least two, preferably at least three, more preferably at least four, even more preferably all of features i)-v): i) a