Insights into the mechanisms underlying aberrant SOX11 oncogene expression in mantle cell lymphoma

Biological and clinical determinants shaping heterogeneity in mantle cell lymphoma

ABSTRACT

Mantle cell lymphoma (MCL) is an uncommon mature B-cell lymphoma that presents a clinical spectrum ranging from indolent to aggressive disease, with challenges in disease management and prognostication. MCL is characterized by significant genomic instability, affecting various cellular processes, including cell cycle regulation, cell survival, DNA damage response and telomere maintenance, NOTCH and NF-κB/ B-cell receptor pathways, and chromatin modification. Recent molecular and next-generation sequencing studies unveiled a broad genetic diversity among the 2 molecular subsets, conventional MCL (cMCL) and leukemic nonnodal MCL (nnMCL), which may partially explain their clinical heterogeneity. Some asymptomatic and genetically stable nnMCL not requiring treatment at diagnosis may eventually progress clinically. Overall, the high proliferation of tumor cells, blastoid morphology, TP53 and/or CDKN2A/B inactivation, and high genetic complexity influence treatment outcome in cases treated with standard regimens. Emerging targeted and immunotherapeutic strategies are promising for refractory or relapsed cases and a few genetic and nongenetic determinants of refractoriness have been reported. This review summarizes the recent advances in MCL biology, focusing on molecular insights, prognostic markers, and novel therapeutic approaches.

Epigenomic Characterization of Lymphoid Neoplasms

Lymphoid neoplasms represent a heterogeneous group of disease entities and subtypes with markedly different molecular and clinical features. Beyond genetic alterations, lymphoid tumors also show widespread epigenomic changes. These severely affect the levels and distribution of DNA methylation, histone modifications, chromatin accessibility, and three-dimensional genome interactions. DNA methylation stands out as a tracer of cell identity and memory, as B cell neoplasms show epigenetic imprints of their cellular origin and proliferative history, which can be quantified by an epigenetic mitotic clock. Chromatin-associated marks are informative to uncover altered regulatory regions and transcription factor networks contributing to the development of distinct lymphoid tumors. Tumor-intrinsic epigenetic and genetic aberrations cooperate and interact with microenvironmental cells to shape the transcriptome at different phases of lymphoma evolution, and intraclonal heterogeneity can now be characterized by single-cell profiling. Finally, epigenetics offers multiple clinical applications, including powerful diagnostic and prognostic biomarkers as well as therapeutic targets.

Chronic lymphocytic leukaemia/small lymphocytic lymphoma and mantle cell lymphoma: from early lesions to transformation

The International Clinical Advisory Committee reviewed advances in our understanding of the clinicopathologic and biologic features of chronic lymphocytic leukaemia/small lymphocytic lymphoma, B-cell prolymphocytic leukaemia, and mantle cell lymphoma since the revised 4th edition of the WHO Classification of Tumours of the Haematopoietic and Lymphoid Tissues. Discussions amongst pathologists, clinicians, and molecular geneticists around these diseases focussed on incorporating new knowledge into the next classification system. In this manuscript, we review these disease entities and incorporate results of these deliberations, including advances in our understanding of early lesions and transformation.

Artificial Intelligence Predicted Overall Survival and Classified Mature B-Cell Neoplasms Based on Immuno-Oncology and Immune Checkpoint Panels

Artificial intelligence (AI) can identify actionable oncology biomarkers. This research integrates our previous analyses of non-Hodgkin lymphoma. We used gene expression and immunohistochemical data, focusing on the immune checkpoint, and added a new analysis of macrophages, including 3D rendering. The AI comprised machine learning (C5, Bayesian network, C&R, CHAID, discriminant analysis, KNN, logistic regression, LSVM, Quest, random forest, random trees, SVM, tree-AS, and XGBoost linear and tree) and artificial neural networks (multilayer perceptron and radial basis function). The series included chronic lymphocytic leukemia, mantle cell lymphoma, follicular lymphoma, Burkitt, diffuse large B-cell lymphoma, marginal zone lymphoma, and multiple myeloma, as well as acute myeloid leukemia and pan-cancer series. AI classified lymphoma subtypes and predicted overall survival accurately. Oncogenes and tumor suppressor genes were highlighted (MYC, BCL2, and TP53), along with immune microenvironment markers of tumor-associated macrophages (M2-like TAMs), T-cells and regulatory T lymphocytes (Tregs) (CD68, CD163, MARCO, CSF1R, CSF1, PD-L1/CD274, SIRPA, CD85A/LILRB3, CD47, IL10, TNFRSF14/HVEM, TNFAIP8, IKAROS, STAT3, NFKB, MAPK, PD-1/PDCD1, BTLA, and FOXP3), apoptosis (BCL2, CASP3, CASP8, PARP, and pathway-related MDM2, E2F1, CDK6, MYB, and LMO2), and metabolism (ENO3, GGA3). In conclusion, AI with immuno-oncology markers is a powerful predictive tool. Additionally, a review of recent literature was made.

Mantle cell lymphoma in 2022-A comprehensive update on molecular pathogenesis, risk stratification, clinical approach, and current and novel treatments

The field of mantle cell lymphoma (MCL) has witnessed remarkable progress due to relentless advances in molecular pathogenesis, prognostication, and newer treatments. MCL consists of a spectrum of clinical subtypes. Rarely, atypical cyclin D1-negative MCL and in situ MCL neoplasia are identified. Prognostication of MCL is further refined by identifying somatic mutations (such as TP53, NSD2, KMT2D), methylation status, chromatin organization pattern, SOX-11 expression, minimal residual disease (MRD), and genomic clusters. Lymphoid tissue microenvironment studies demonstrated the role of B-cell receptor signaling, nuclear factor kappa B (NF-kB), colony-stimulating factor (CSF)-1, the CD70-SOX-11 axis. Molecular mechanism of resistance, mutation dynamics, and pathogenic pathways (B-cell receptor (BCR), oxidative phosphorylation, and MYC) were identified in mediating resistance to various treatments (bruton tyrosine kinase (BTK) inhibitors [ibrutinib, acalabrutinib]. Treatment options range from conventional chemoimmunotherapy and stem cell transplantation (SCT) to targeted therapies against BTK (covalent and noncovalent), Bcl2, ROR1, cellular therapy such as anti-CD19 chimeric antigen receptor therapy (CAR-T), and most recently bispecific antibodies against CD19 and CD20. MCL patients frequently relapse. Complex pathogenesis and the management of patients with progression after treatment with BTK/Bcl2 inhibitors and CAR-T (triple-resistant MCL) remain a challenge. Next-generation clinical trials incorporating newer agents and concurrent translational and molecular investigations are ongoing.