Follicular lymphoma treatment decisions: put GELF on the shelf?

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The Lymphoma Epidemiology of Outcomes cohort study: Design, baseline characteristics, and early outcomes.

To address the current and long-term unmet health needs of the growing population of non-Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18-99). Participants came from 49 US states and included 538 Black/African-Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population-based SEER data (2015-2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population-based SEER rates for indolent B-cell (follicular and marginal zone) and T-cell lymphomas, but were 10%-15% higher than SEER rates for aggressive B-cell subtypes (diffuse large B-cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.

Follicular lymphoma B cells exhibit heterogeneous transcriptional states with associated somatic alterations and tumor microenvironments.

Follicular lymphoma (FL) is an indolent non-Hodgkin lymphoma of germinal center origin, which presents with significant biologic and clinical heterogeneity. Using RNA-seq on B cells sorted from 87 FL biopsies, combined with machine-learning approaches, we identify 3 transcriptional states that divide the biological ontology of FL B cells into inflamed, proliferative, and chromatin-modifying states, with relationship to prior GC B cell phenotypes. When integrated with whole-exome sequencing and immune profiling, we find that each state was associated with a combination of mutations in chromatin modifiers, copy-number alterations to TNFAIP3, and T follicular helper cells (Tfh) cell interactions, or primarily by a microenvironment rich in activated T cells. Altogether, these data define FL B cell transcriptional states across a large cohort of patients, contribute to our understanding of FL heterogeneity at the tumor cell level, and provide a foundation for guiding therapeutic intervention.

Marginal zone lymphoma international prognostic index: a unifying prognostic index for marginal zone lymphomas requiring systemic treatment.

Background: Marginal zone lymphomas (MZL), comprised of three unique but related subtypes, lack a unifying prognostic score applicable to all the patients in need for systemic chemotherapy and/or immunotherapy. Methods: Patients from the prospective NF10 study (NCT02904577) with newly diagnosed MZL and receiving frontline systemic therapy at diagnosis or after observation were used to train a prognostic model. The primary endpoint was progression-free survival (PFS) from start of treatment. The model was externally validated in a pooled analysis of two independent cohorts from the University of Iowa and Mayo Clinic Molecular Epidemiology Resource and the University of Miami. Findings: We identified 501 eligible patients. After multivariable modeling, lactate dehydrogenase (LDH) above upper normal limit, hemoglobin <12 g/dL, absolute lymphocyte count <1 × 109/L, platelets <100 × 109/L, and MZL subtype (nodal or disseminated) were independently associated with inferior PFS. The proposed MZL International Prognostic index (MZL-IPI) combined these 5 factors, and we defined low (LRG, 0 factors, 27%), intermediate (IRG, 1-2 factors, 57%) and high (HRG, 3+ factors, 16%) risk groups with 5-y PFS of 85%, 66%, and 37%, respectively (c-Harrell = 0.64). Compared to the LRG, the IRG (Hazard Ratio [HR] = 2.30, 95% CI 1.39-3.80) and HRG (HR = 5.41, 95% CI 3.12-9.38) had inferior PFS. Applying the MZL-IPI to the pooled US cohort (N = 353), 94 (27%), 192 (54%), and 67 (19%) patients were classified as LRG, IRG, and HRG, respectively, and the model was validated for PFS (log-rank test p = 0.0018; c-Harrell = 0.578, 95% CI 0.54-0.62). The MZL-IPI was also prognostic for OS in both the training and the external validation sets. Interpretation: MZL-IPI is a new prognostic score for use in all patients with MZL considered for systemic treatment. Funding: The MER was supported by P50 CA97274 and U01 CA195568.

Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL.

Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis was used to identify a signature associated with high risk of early clinical failure independent of IPI and COO. Further analysis revealed the signature was associated with metabolic reprogramming and identified cases with a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. This novel and integrative approach is the first to identify a signature at diagnosis, in a real-world cohort of DLBCL, that identifies patients at high risk for early clinical failure and may have significant implications for design of therapeutic options.

Transcriptomic classification of diffuse large B-cell lymphoma identifies a high-risk activated B-cell-like subpopulation with targetable MYC dysregulation.

Immunochemotherapy has been the mainstay of treatment for newly diagnosed diffuse large B-cell lymphoma (ndDLBCL) yet is inadequate for many patients. In this work, we perform unsupervised clustering on transcriptomic features from a large cohort of ndDLBCL patients and identify seven clusters, one called A7 with poor prognosis, and develop a classifier to identify these clusters in independent ndDLBCL cohorts. This high-risk cluster is enriched for activated B-cell cell-of-origin, low immune infiltration, high MYC expression, and copy number aberrations. We compare and contrast our methodology with recent DLBCL classifiers to contextualize our clusters and show improved prognostic utility. Finally, using pre-clinical models, we demonstrate a mechanistic rationale for IKZF1/3 degraders such as lenalidomide to overcome the low immune infiltration phenotype of A7 by inducing T-cell trafficking into tumors and upregulating MHC I and II on tumor cells, and demonstrate that TCF4 is an important regulator of MYC-related biology in A7.

Integrative analysis of clinicopathological features defines novel prognostic models for mantle cell lymphoma in the immunochemotherapy era: a report from The North American Mantle Cell Lymphoma Consortium.

BACKGROUND: Patients with mantle cell lymphoma (MCL) exhibit a wide variation in clinical presentation and outcome. However, the commonly used prognostic models are outdated and inadequate to address the needs of the current multidisciplinary management of this disease. This study aims to investigate the clinical and pathological features of MCL in the immunochemotherapy era and improve the prognostic models for a more accurate prediction of patient outcomes. METHODS: The North American Mantle Cell Lymphoma Project is a multi-institutional collaboration of 23 institutions across North America to evaluate and refine prognosticators for front-line therapy. A total of 586 MCL cases diagnosed between 2000 and 2012 are included in this study. A comprehensive retrospective analysis was performed on the clinicopathological features, treatment approaches, and outcomes of these cases. The establishment of novel prognostic models was based on in-depth examination of baseline parameters, and subsequent validation in an independent cohort of MCL cases. RESULTS: In front-line strategies, the use of hematopoietic stem cell transplantation was the most significant parameter affecting outcomes, for both overall survival (OS, p < 0.0001) and progression-free survival (PFS, p < 0.0001). P53 positive expression was the most significant pathological parameter correlating with inferior outcomes (p < 0.0001 for OS and p = 0.0021 for PFS). Based on the baseline risk factor profile, we developed a set of prognostic models incorporating clinical, laboratory, and pathological parameters that are specifically tailored for various applications. These models, when tested in the validation cohort, exhibited strong predictive power for survival and showed a stratification resembling the training cohort. CONCLUSIONS: The outcome of patients with MCL has markedly improved over the past two decades, and further enhancement is anticipated with the evolution of clinical management. The innovative prognostic models developed in this study would serve as a valuable tool to guide the selection of more suitable treatment strategies for patients with MCL.