Chronic lymphocytic leukemia (CLL) is an incurable adult disease of unknown etiology. Understanding the biology of CLL cells, particularly cell maturation and growth in vivo, has been impeded by lack of a reproducible adoptive transfer model. We report a simple, reproducible system in which primary CLL cells proliferate in nonobese diabetes/severe combined immunodeficiency/γcnull mice under the influence of activated CLL-derived T lymphocytes. By cotransferring autologous T lymphocytes, activated in vivo by alloantigens, the survival and growth of primary CFSE-labeled CLL cells in vivo is achieved and quantified. Using this approach, we have identified key roles for CD4+ T cells in CLL expansion, a direct link between CD38 expression by leukemic B cells and their activation, and support for CLL cells preferentially proliferating in secondary lymphoid tissues. The model should simplify analyzing kinetics of CLL cells in vivo, deciphering involvement of nonleukemic elements and nongenetic factors promoting CLL cell growth, identifying and characterizing potential leukemic stem cells, and permitting preclinical studies of novel therapeutics. Because autologous activated T lymphocytes are 2-edged swords, generating unwanted graph-versus-host and possibly autologous antitumor reactions, the model may also facilitate analyses of T-cell populations involved in immune surveillance relevant to hematopoietic transplantation and tumor cytoxicity.

From paired blood and spleen samples from three adult donors, we performed high-throughput V_H sequencing of human B cell subsets defined by IgD and CD27 expression: IgD⁺CD27⁺ (“marginal zone [MZ]”), IgD⁻CD27⁺ (“memory,” including IgM [“IgM-only”], IgG and IgA) and IgD⁻CD27⁻ cells (“double-negative,” including IgM, IgG, and IgA). A total of 91,294 unique sequences clustered in 42,670 clones, revealing major clonal expansions in each of these subsets. Among these clones, we further analyzed those shared sequences from different subsets or tissues for V_H gene mutation, H-CDR3-length, and V_H/J_H usage, comparing these different characteristics with all sequences from their subset of origin for which these parameters constitute a distinct signature. The IgM-only repertoire profile differed notably from that of MZ B cells by a higher mutation frequency and lower V_H4 and higher J_H6 gene usage. Strikingly, IgM sequences from clones shared between the MZ and the memory IgG/IgA compartments showed a mutation and repertoire profile of IgM-only and not of MZ B cells. Similarly, all IgM clonal relationships (among MZ, IgM-only, and double-negative compartments) involved sequences with the characteristics of IgM-only B cells. Finally, clonal relationships between tissues suggested distinct recirculation characteristics between MZ and switched B cells. The “IgM-only” subset (including cells with its repertoire signature but higher IgD or lower CD27 expression levels) thus appear as the only subset showing precursor–product relationships with CD27⁺ switched memory B cells, indicating that they represent germinal center–derived IgM memory B cells and that IgM memory and MZ B cells constitute two distinct entities.

Refractory or relapsed diffuse large B-cell lymphoma (DLBCL) often associates with the activated B-cell-like (ABC) subtype and genetic alterations that drive constitutive NF-κB activation and impair B-cell terminal differentiation. Here, we show that DNA damage response by p53 is a central mechanism suppressing the pathogenic cooperation of IKK2ca-enforced canonical NF-κB and impaired differentiation resulting from Blimp1 loss in ABC-DLBCL lymphomagenesis. We provide evidences that the interplay between these genetic alterations and the tumor microenvironment select for additional molecular addictions that promote lymphoma progression, including aberrant coexpression of FOXP1 and the B-cell mutagenic enzyme activation-induced deaminase, and immune evasion through major histocompatibility complex class II downregulation, PD-L1 upregulation, and T-cell exhaustion. Consistently, PD-1 blockade cooperated with anti-CD20-mediated B-cell cytotoxicity, promoting extended T-cell reactivation and antitumor specificity that improved long-term overall survival in mice. Our data support a pathogenic cooperation among NF-κB-driven prosurvival, genetic instability, and immune evasion mechanisms in DLBCL and provide preclinical proof of concept for including PD-1/PD-L1 blockade in combinatorial immunotherapy for ABC-DLBCL.

Immunoglobulins or antibodies are the main effector molecules of the B-cell lineage and are encoded by hundreds of variable (V), diversity (D), and joining (J) germline genes, which recombine to generate enormous IG diversity. Recently, high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) of recombined V-(D)-J genes has offered unprecedented insights into the dynamics of IG repertoires in health and disease. Faithful biological interpretation of AIRR-seq studies depends upon the annotation of raw AIRR-seq data, using reference germline gene databases to identify the germline genes within each rearrangement. Existing reference databases are incomplete, as shown by recent AIRR-seq studies that have inferred the existence of many previously unreported polymorphisms. Completing the documentation of genetic variation in germline gene databases is therefore of crucial importance. Lymphocyte receptor genes and alleles are currently assigned by the Immunoglobulins, T cell Receptors and Major Histocompatibility Nomenclature Subcommittee of the International Union of Immunological Societies (IUIS) and managed in IMGT^®, the international ImMunoGeneTics information system^® (IMGT). In 2017, the IMGT Group reached agreement with a group of AIRR-seq researchers on the principles of a streamlined process for identifying and naming inferred allelic sequences, for their incorporation into IMGT^®. These researchers represented the AIRR Community, a network of over 300 researchers whose objective is to promote all aspects of immunoglobulin and T-cell receptor repertoire studies, including the standardization of experimental and computational aspects of AIRR-seq data generation and analysis. The Inferred Allele Review Committee (IARC) was established by the AIRR Community to devise policies, criteria, and procedures to perform this function. Formalized evaluations of novel inferred sequences have now begun and submissions are invited via a new dedicated portal (https://ogrdb.airr-community.org). Here, we summarize recommendations developed by the IARC—focusing, to begin with, on human IGHV genes—with the goal of facilitating the acceptance of inferred allelic variants of germline IGHV genes. We believe that this initiative will improve the quality of AIRR-seq studies by facilitating the description of human IG germline gene variation, and that in time, it will expand to the documentation of TR and IG genes in many vertebrate species.

Efficient and accurate high-throughput DNA sequencing of the adaptive immune receptor repertoire (AIRR) is necessary to study immune diversity in healthy subjects and disease-related conditions. The high complexity and diversity of the AIRR coupled with the limited amount of starting material which can compromise identification of the full biological diversity makes such sequencing particularly challenging. AIRR sequencing protocols often fail to fully capture the sampled AIRR diversity, especially for samples containing restricted numbers of B lymphocytes. Here, we describe a library preparation method for immunoglobulin sequencing that results in an exhaustive full-length repertoire where virtually every sampled B-cell is sequenced. This maximizes the likelihood of identifying and quantifying the entire IGHV-D-J repertoire of a sample, including the detection of rearrangements present in only one cell in the starting population. The methodology establishes the importance of circumventing genetic material dilution in the pre-amplification phases and incorporates the use of certain described concepts: 1) balancing the starting material amount and depth of sequencing, 2) avoiding IGHV gene specific amplification, and 3) using Unique Molecular Identifier. Together, this methodology is highly efficient, in particular for detecting rare rearrangements in the sampled population and when only a limited amount of starting material is available.