Central Nervous System Lymphoma: Novel Therapies

Imaging Features of Immunodeficiency-Associated Primary CNS Lymphoma: A Review

In the immunocompromised setting, there are distinct radiologic findings of primary central nervous system lymphoma (PCNSL), including necrotic ring-enhancing lesions, increased propensity for intralesional haemorrhage, and multiplicity. In this clinical context, advanced imaging with MR perfusion, spectroscopy, and diffusion-weighted imaging can be used to increase accuracy in the diagnosis of lymphoma over mimics such as high-grade glioma, metastases, or infection. This review summarizes the histology and pathophysiology of PCNSL in immunodeficient hosts, which provide a basis for its imaging appearances, prognosis, and treatment. This discussion is important for the general radiologist as the incidence of immunodeficiency-related PCNSL may be increasing.

Prognostic value of POD18 combined with improved IELSG in primary central nervous system lymphoma

PURPOSE

The International Extranodal Lymphoma Study Group (IELSG) score is widely used in clinical practice to stratify the risk of primary central nervous system lymphoma (PCNSL) patients. Our study aims to confirm and improve the IELSG score in PCNSL patients based on Chinese populations.

MATERIALS AND METHODS

A total of 79 PCNSL patients were retrospectively analyzed. All patients treated with high-dose methotrexate (HD-MTX)-based therapy collected clinical data. The receiver-operating characteristic (ROC) curve was used to determine the optimal cut-off values for the factors in IELSG score. Progression of disease (POD) at the most landmark time point was determine by Epanechnikov kernel and the area under the ROC curve (AUROC). Kaplan-Meier and multivariable regression methods were used to analyze survival data. Nomogram was generated for calculating the weight of each selected factor.

RESULTS

The traditional IELSG score had no significant difference on OS and PFS except ECOG ≥ 2 and could not stratify the risk groups in PCNSL. The improved IELSG scoring system was established, which incorporated age ≥ 54 years, ECOG ≥ 2, deep brain structure, elevated CSF protein, and LDH/ULN > 0.75. On the other hand, POD18 was identified as a new powerful prognostic factor for PCNSL. In multivariate analysis, POD18 and the improved IELSG scoring system were independent prognostic factors for OS. Nomogram including the two significant variables showed the best performance (C-index = 0.828).

CONCLUSIONS

In this study, the IELSG score was improved and a new prognostic indicator POD18 was incorporated to construct a nomogram prognostic model, thereby further improving the predictive ability of the model.

Analysis of genomic alterations in primary central nervous system lymphoma

Primary central nervous system lymphoma (PCNSL) is a rare and special type of non-Hodgkin lymphoma with a significantly worse median overall prognosis than that of non-Hodgkin lymphoma outside the brain. Clarifying the genomic characteristics and alterations in PCNSL could provide clues regarding its distinctive pathophysiology and new treatment options. However, current knowledge about the genomics of PCNSL is limited. In this study, next-generation sequencing (NGS) was performed to investigate the genomic profile of PCNSL. Samples from 12 patients diagnosed with PCNSL at our institution were analyzed for gene mutations using NGS. This study showed that missense mutations were the most common mutation type. C > A/G > T accounted for most of the single-base mutations, which reflected the preference of the tumor sample mutation type and may serve as an important prognostic factor. The most significantly mutated gene was myeloid differentiation factor 88 (MYD88) (0.55), followed by CD79B, LRP1B, and PRDM1 (0.36). None of the cases showed a high tumor mutational burden. In addition to the traditional driver genes, we also identified some new possible ones such as MET, PIM1, and RSBN1L. Enrichment analysis revealed that genes mutated in PCNSL were involved in many pathways and functional protein activities, such as the extracellular matrix and adhesion molecules. The most common genetic alterations in PCNSL were identified using NGS. Mutations in multiple genes highlights the complex molecular heterogeneity of PCNSL. Enrichment analysis revealed possible pathogenesis. Further exploration of new driver genes could provide novel insights into diagnosis and precision medicine for PCNSL.

Treatment Options for Epstein-Barr Virus-Related Disorders of the Central Nervous System

Epstein-Barr virus (EBV), a causative agent for several types of lymphomas and mucosal cancers, is a human lymphotropic herpesvirus with the capacity to establish lifelong latent infection. More than 90% of the human population worldwide is infected. The primary infection is usually asymptomatic in childhood, whereas infectious mononucleosis (IM) is common when the infection occurs in adolescence. Primary EBV infection, with or without IM, or reactivation of latent infection in immunocompromised individuals have been associated with a wide range of neurologic conditions, such as encephalitis, meningitis, acute disseminated encephalomyelitis, and cerebellitis. EBV is also involved in malignant lymphomas in the brain. An increasing number of reports on EBV-related disorders of the central nervous system (CNS) including the convincing association with multiple sclerosis (MS) have put in focus EBV-related conditions beyond its established link to malignancies. In this review, we present the clinical manifestations of EBV-related CNS-disorders, put them in the context of known EBV biology and focus on available treatment options and future therapeutic approaches.

Decision Tree Model for Predicting the Overall Survival of Patients with Diffused Large B-Cell Lymphoma in the Central Nervous System

OBJECTIVE

To identify the significant predictors of overall survival for patients living with diffused large B-cell lymphoma (DLBCL) in the central nervous system and establish a novel decision tree model to help predict survival status at several time points.

METHODS

Patients diagnosed with DLBCL were identified from the SEER database and randomly divided into training and test samples (6:4). Dichotomous decision trees were developed for survival status at 3, 12, 24, and 60 months. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy rate, and area under the receiver operating characteristic curve were calculated to evaluate the model performance.

RESULTS

A total of 2998 patients were included, with 1799 and 1199 patients divided into the training and testing groups. Decision trees for 3, 12, 24, and 60 months survival status were generated. Chemotherapy and patient's age were of the primary importance for prognosis in the novel models. Favorable consistency between the predicted and actual survival status was presented. The accuracy rates were 0.79, 0.71, 0.68, and 0.86 for training sample at 3, 12, 24, and 60 months, respectively, and 0.75, 0.69, 0.58, and 0.84 for test sample at 3, 12, 24, and 60 months, respectively. The area under the receiver operating characteristic curve values ranged between 0.645 and 0.721 for the training sample and between 0.607 and 0.712 for the test sample.

CONCLUSIONS

Novel decision tree models were established for predicting the 3, 12, 24, and 60 months survival status of patients with DLBCL. The newly developed models were verified using training and test samples, showing favorable accuracy and predictive value on overall survival.