[ { "id": "authors:cg1kq-3pm68", "collection": "authors", "collection_id": "cg1kq-3pm68", "cite_using_url": "https://authors.library.caltech.edu/records/cg1kq-3pm68", "type": "article", "title": "Integrative genomic analysis of DLBCL identifies immune environments associated with bispecific antibody response", "author": [ { "family_name": "Tumuluru", "given_name": "Sravya", "orcid": "0009-0001-2091-821X" }, { "family_name": "Godfrey", "given_name": "James K.", "orcid": "0000-0002-4103-4288" }, { "family_name": "Cooper", "given_name": "Alan", "orcid": "0000-0001-9739-0866" }, { "family_name": "Yu", "given_name": "Jovian", "orcid": "0000-0001-9214-7576" }, { "family_name": "Chen", "given_name": "Xiufen", "orcid": "0009-0006-6895-2819" }, { "family_name": "MacNabb", "given_name": "Brendan W.", "orcid": "0000-0003-1827-0247", "clpid": "MacNabb-Brendan-W" }, { "family_name": "Venkataraman", "given_name": "Girish", "orcid": "0000-0002-8674-2608" }, { "family_name": "Zha", "given_name": "Yuanyuan", "orcid": "0000-0002-0574-7352" }, { "family_name": "Pelzer", "given_name": "Benedikt", "orcid": "0000-0002-1892-3650" }, { "family_name": "Song", "given_name": "Joo", "orcid": "0000-0003-3497-2513" }, { "family_name": "Duns", "given_name": "Gerben", "orcid": "0000-0001-8060-694X" }, { "family_name": "Sworder", "given_name": "Brian J.", "orcid": "0000-0002-5902-5507" }, { "family_name": "Raj", "given_name": "Sandeep", "orcid": "0000-0003-4629-0528" }, { "family_name": "Bolen", "given_name": "Christopher", "orcid": "0000-0003-2270-5565" }, { "family_name": "Penuel", "given_name": "Elicia", "orcid": "0000-0001-7285-1929" }, { "family_name": "Postovalova", "given_name": "Ekaterina", "orcid": "0000-0002-3413-3122" }, { "family_name": "Kotlov", "given_name": "Nikita", "orcid": "0000-0002-6393-7357" }, { "family_name": "Bagaev", "given_name": "Aleksander", "orcid": "0000-0002-8680-854X" }, { "family_name": "Fowler", "given_name": "Nathan", "orcid": "0000-0002-9494-1877" }, { "family_name": "Shouval", "given_name": "Roni", "orcid": "0000-0001-9827-8032" }, { "family_name": "Smith", "given_name": "Sonali M.", "orcid": "0000-0002-9893-4949" }, { "family_name": "Alizadeh", "given_name": "Ash A.", "orcid": "0000-0002-5153-5625" }, { "family_name": "Steidl", "given_name": "Christian", "orcid": "0000-0001-9842-9750" }, { "family_name": "Kline", "given_name": "Justin", "orcid": "0000-0002-2967-6448" } ], "abstract": "

Most patients with diffuse large B-cell lymphoma (DLBCL) treated with immunotherapies such as bispecific antibodies (BsAbs) or chimeric antigen receptor (CAR) T cells fail to achieve durable treatment responses, underscoring the need for a deeper understanding of mechanisms that regulate the immune environment and response to treatment. Here, an integrative multiomics approach was applied to multiple large independent data sets to characterize DLBCL immune environments and to define their association with tumor cell–intrinsic genomic alterations and outcomes to CD19-directed CAR T-cell and CD20 × CD3 BsAb therapies. This approach effectively segregated DLBCLs into 4 immune quadrants (IQs) defined by cell-of-origin and immune-related gene set expression scores. These quadrants consisted of activated B cell–like (ABC) hot, ABC cold, germinal center B cell–like (GCB) hot, and GCB cold DLBCLs. Recurrent genomic alterations were enriched in each IQ, suggesting that lymphoma cell-intrinsic alterations contribute significantly to orchestrating unique DLBCL immune environments. For instance, SOCS1 loss-of-function mutations were significantly enriched among GCB hot DLBCLs, identifying a putative subset of inflamed DLBCLs that may be inherently susceptible to immunotherapy. In patients with relapsed/refractory DLBCL, DLBCL-IQ assignment correlated significantly with clinical benefit with a CD20 × CD3 BsAb (N = 74), but not with CD19-directed CAR T cells (Stanford, N = 51; Memorial Sloan Kettering Cancer Center, N = 69). Thus, DLBCL-IQ provides a new framework to conceptualize the DLBCL immune landscape and suggests the endogenous immune environment has a more significant impact on outcomes to BsAb than CAR T-cell treatment.

", "doi": "10.1182/blood.2024025355", "issn": "0006-4971", "publisher": "American Society of Hematology", "publication": "Blood", "publication_date": "2025-05-22", "series_number": "21", "volume": "145", "issue": "21", "pages": "2460-2472" }, { "id": "authors:96hjm-gj025", "collection": "authors", "collection_id": "96hjm-gj025", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20230227-88449200.51", "type": "article", "title": "Speed and navigation control of thymocyte development by the fetal T-cell gene regulatory network", "author": [ { "family_name": "MacNabb", "given_name": "Brendan W.", "orcid": "0000-0003-1827-0247", "clpid": "MacNabb-Brendan-W" }, { "family_name": "Rothenberg", "given_name": "Ellen V.", "orcid": "0000-0002-3901-347X", "clpid": "Rothenberg-E-V" } ], "abstract": "T-cell differentiation is a tightly regulated developmental program governed by interactions between transcription factors (TFs) and chromatin landscapes and affected by signals received from the thymic stroma. This process is marked by a series of checkpoints: T-lineage commitment, T-cell receptor (TCR)\u03b2 selection, and positive and negative selection. Dynamically changing combinations of TFs drive differentiation along the T-lineage trajectory, through mechanisms that have been most extensively dissected in adult mouse T-lineage cells. However, fetal T-cell development differs from adult in ways that suggest that these TF mechanisms are not fully deterministic. The first wave of fetal T-cell differentiation occurs during a unique developmental window during thymic morphogenesis, shows more rapid kinetics of differentiation with fewer rounds of cell division, and gives rise to unique populations of innate lymphoid cells (ILCs) and invariant \u03b3\u03b4T cells that are not generated in the adult thymus. As the characteristic kinetics and progeny biases are cell-intrinsic properties of thymic progenitors, the differences could be based on distinct TF network circuitry within the progenitors themselves. Here, we review recent single-cell transcriptome data that illuminate the TF networks involved in T-cell differentiation in the fetal and adult mouse thymus.", "doi": "10.1111/imr.13190", "pmcid": "PMC10771342", "issn": "0105-2896", "publisher": "Wiley-Blackwell", "publication": "Immunological Reviews", "publication_date": "2023-05", "series_number": "1", "volume": "315", "issue": "1", "pages": "171-196" } ]