| Title |
An Aged/Autoimmune B-cell Program Defines the Early Transformation of Extranodal Lymphomas
|
|---|---|
| Published in |
Cancer Discovery, October 2022
|
| DOI | 10.1158/2159-8290.cd-22-0561 |
| Pubmed ID | |
| Authors |
Leandro Venturutti, Martin A. Rivas, Benedikt W. Pelzer, Ruth Flümann, Julia Hansen, Ioannis Karagiannidis, Min Xia, Dylan R. McNally, Yusuke Isshiki, Andrew Lytle, Matt Teater, Christopher R. Chin, Cem Meydan, Gero Knittel, Edd Ricker, Christopher E. Mason, Xiaofei Ye, Qiang Pan-Hammarström, Christian Steidl, David W. Scott, Hans Christian Reinhardt, Alessandra B. Pernis, Wendy Béguelin, Ari M. Melnick |
| Abstract |
A third of diffuse large B-cell lymphoma (DLBCL) patients present with extranodal dissemination, associated with inferior clinical outcome. MYD88L265P is a hallmark extranodal DLBCL mutation that supports lymphoma proliferation. Yet, extranodal lymphomagenesis and the role of MYD88L265P in transformation remain mostly unknown. Here, we show that B-cells expressing Myd88L252P (MYD88L265P murine equivalent) activate, proliferate, and differentiate, with minimal T-cell co-stimulation. Additionally, Myd88L252P skewed B-cells towards the memory fate. Unexpectedly, the transcriptional and phenotypic profiles of B-cells expressing Myd88L252P, or other extranodal lymphoma founder mutations, resembled those of CD11c+T-BET+ aged/autoimmune memory B-cells (AiBC). AiBC-like cells progressively accumulated in animals prone to develop lymphomas, and ablation of T-BET, the AiBC master regulator, stripped mouse and human mutant B-cells of their competitive fitness. By identifying a phenotypically-defined prospective lymphoma precursor population and its dependencies, our findings pave the way for the early detection of premalignant states and targeted prophylactic interventions in high-risk patients. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 45% |
| Spain | 2 | 10% |
| Germany | 2 | 10% |
| Unknown | 7 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 40% |
| Scientists | 6 | 30% |
| Science communicators (journalists, bloggers, editors) | 3 | 15% |
| Practitioners (doctors, other healthcare professionals) | 3 | 15% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 15% |
| Student > Ph. D. Student | 4 | 12% |
| Student > Bachelor | 3 | 9% |
| Other | 1 | 3% |
| Student > Doctoral Student | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 18 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 21% |
| Agricultural and Biological Sciences | 3 | 9% |
| Immunology and Microbiology | 3 | 9% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 18 | 53% |