EBV-Negative Monomorphic B-Cell Posttransplant Lymphoproliferative Disorder with Marked Morphologic Pleomorphism and Pathogenic Mutations in ASXL1, BCOR, CDKN2A, NF1, and TP53

Primary central nervous system CD20-negative diffuse large B-cell lymphoma: a case report

BACKGROUND

CD20-negative diffuse large B-cell lymphoma is a very rare and heterogeneous invasive cancer characterized by chemical resistance and poor prognosis. Primary CD20-negative diffuse large B-cell lymphoma of the central nervous system is even rarer, presenting great challenges in pathological diagnosis and clinical treatment.

CASE PRESENTATION

We report a case of primary CD20-negative diffuse large B-cell lymphoma of the CNS in a 54-year-old woman admitted to the hospital with a headache lasting more than 10 days. CT and MRI scans showed right temporal lobe lymphoma. Microscopically, large infiltrating lymphoid cells that induced brain tissue damage were observed. Immunohistochemistry showed that the tumor cells were CD79a⁺, PAX-5⁺, MUM1⁺, and CD20^-. The patient was diagnosed with lymphoma and transferred to an oncology hospital for chemotherapy. However, because the disease progressed rapidly, the patient died only after two rounds of chemotherapy.

CONCLUSIONS

To the best of our knowledge, this is one of the first reported cases of unclassifiable CD20-negative diffuse large B-cell lymphoma located in the CNS. This case report aims to deepen the understanding of clinicopathological features of this type of lymphoma and expand the scope of this disease.

High ETV6 Levels Support Aggressive B Lymphoma Cell Survival and Predict Poor Outcome in Diffuse Large B-Cell Lymphoma Patients

The identification of prognostic factors for aggressive B-cell lymphomas still represents an unmet clinical need. We used forward phase protein arrays (FFPA) to identify proteins associated with overall survival (OS) from diagnostic formalin-fixed paraffin-embedded material of diffuse large B-cell lymphoma (DLBCL) patients (n = 47). Univariate Cox regression analysis identified numerous proteins, including immune check-point molecules (PDCD1, PDCD2 and PD1L2) and BCL2 to be significantly associated with OS. However, only ETV6 and PIM2 proteins persisted following multivariate Cox analysis. Independent validation studies by immunohistochemistry and analysis of public gene expression profiles of DLBCL confirmed a prognostic role for high ETV6 and ETV6/PIM2 ratios in DLBCL. ETV6 is a recurrently mutated/deleted gene in DLBCL for which its function in this disease entity is currently unknown. We find that ETV6 is upregulated during oncogenic transformation of germinal center B-cells and that it regulates DLBCL survival, as its acute loss results in marked apoptosis. Fluctuations in survivin (BIRC5) expression levels were associated with this phenomenon. Furthermore, an inverse correlation between ETV6 and BIRC5 expression levels was found and correlated with a response to the BIRC5 inhibitor, YM155. In conclusion, we present evidence for an oncogenic function of ETV6 in DLBCL.

The Role of RUNX1 in NF1-Related Tumors and Blood Disorders

Neurofibromatosis type 1 (NF1) is an autosomal dominant disorder. NF1 patients are predisposed to formation of several type solid tumors as well as to juvenile myelomonocytic leukemia. Loss of NF1 results in dysregulation of MAPK, PI3K and other signaling cascades, to promote cell proliferation and to inhibit cell apoptosis. The RUNX1 gene is associated with stem cell function in many tissues, and plays a key role in the fate of stem cells. Aberrant RUNX1 expression leads to context-dependent tumor development, in which RUNX1 may serve as a tumor suppressor or an oncogene in specific tissue contexts. The co-occurrence of mutation of NF1 and RUNX1 is detected rarely in several cancers and signaling downstream of RAS-MAPK can alter RUNX1 function. Whether aberrant RUNX1 expression contributes to NF1-related tumorigenesis is not fully understood. This review focuses on the role of RUNX1 in NF1-related tumors and blood disorders, and in sporadic cancers.

Survival associated alternative splicing events in diffuse large B-cell lymphoma

Growing evidence has revealed that the initiation of various malignancies is closely associated with alternative splicing (AS) events in certain key oncogenes. However, in diffuse large B-cell lymphoma (DLBCL), there is still a great deal to learn about AS variants. In this study, 33,724 AS variant profiles were obtained from 16,278 genes in 48 DLBCL cases. A total of 10 AS variants were identified as overall survival (OS)- related events via multivariate Cox regression analysis. Notably, alternative donor (AD) sites in AS events in the low-risk group showed a significantly better outcome in DLBCL patients than in the high-risk group (P=0.0002). The area under the curve (AUC) of the receiver-operator characteristic curve (ROC) for ADs in DLBCL was 0.746. Furthermore, 66 related splicing factors were obtained to investigate their potential correlations with AS events. Factors SF1, HNRNPC, HNRNPD, and HNRNPH3 were significantly involved in different OS-related AS variants. Collectively, we constructed valuable prognostic predictors for DLBCL patients and mapped novel splicing networks for further investigation of the underlying mechanisms related to AS variants in DLBCLs.

Identification of Hub Genes and Key Pathways Associated with Two Subtypes of Diffuse Large B-Cell Lymphoma Based on Gene Expression Profiling via Integrated Bioinformatics

There is a significant difference in prognosis between the germinal center B-cell (GCB) and activated B-cell (ABC) subtypes of diffuse large B-cell lymphoma (DLBCL). However, the signaling pathways and driver genes involved in these disparate subtypes are ambiguous. This study integrated three cohort profile datasets, including 250 GCB samples and 250 ABC samples, to elucidate potential candidate hub genes and key pathways involved in these two subtypes. Differentially expressed genes (DEGs) were identified. After Gene Ontology functional enrichment analysis of the DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted using the STRING database and Cytoscape software. Subsequently, the Oncomine database and the cBioportal online tool were employed to verify the alterations and differential expression of the 8 hub genes (MME, CD44, IRF4, STAT3, IL2RA, ETV6, CCND2, and CFLAR). Gene set enrichment analysis was also employed to identify the intersection of the key pathways (JAK-STAT, FOXO, and NF-κB pathways) validated in the above analyses. These hub genes and key pathways could improve our understanding of the process of tumorigenesis and the underlying molecular events and may be therapeutic targets for the precise treatment of these two subtypes with different prognoses.