Cutaneous involvement in diffuse large B cell lymphoma at presentation: report of two rare cases and literature review

Background Diffuse large B cell lymphoma (DLBCL) can occur at nodal and/or extra-nodal sites. After the gastrointestinal tract, cutaneous involvement predominates in extra-nodal DLBCL. Skin involvement at presentation can be in the form of plaques, papules, nodules or ulcers. Differentiating primary cutaneous DLBCL from systemic DLBCL with cutaneous involvement is important for appropriate patient management. Case presentation We describe here, two interesting cases of skin involvement in DLBCL- one primary cutaneous DLBCL and the other, cutaneous involvement in systemic DLBCL with different clinico-pathological profiles. Though both cases had almost similar morphology of the skin lesions (ulcero-proliferative) at presentation, the disease was confined to the skin in the former, while the latter had involvement of lymph nodes and bone marrow. Conclusions Meticulous clinical evaluation, appropriate histopathological and immunohistochemical workup helped in their diagnosis and correct classification of the disease status, guiding the further treatment decisions.

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Despite extensive research, the molecular alterations leading to PCNSL have not been fully elucidated. In order to provide a comprehensive description of the genomic and transcriptional landscape of PCNSL, we here performed whole-genome and transcriptome sequencing and integrative analysis of 51 lymphomas presenting in the CNS, including 42 EBV-negative PCNSL, 6 secondary CNS lymphomas (SCNSL) and 3 EBV+ CNSL and matched controls. The results were compared to an independent validation cohort of 31 FFPE CNSL specimens (PCNSL, n = 19; SCNSL, n = 9; EBV+ CNSL, n = 3) as well as 39 FL and 36 systemic DLBCL cases outside the CNS. Somatic genomic alterations in PCNSL mainly affect the JAK-STAT, NFkB, and B-cell receptor signaling pathways, with hallmark recurrent mutations including MYD88 L265P (67%) and CD79B (63%), CDKN2A deletions (83%) and also non-coding RNA genes such as MALAT1 (70%), NEAT (60%), and MIR142 (80%). Kataegis events, which affected 15 of 50 identified driver genes and 21 of the top 50 mutated ncRNAs, played a decisive role in shaping the mutational repertoire of PCNSL. Compared to systemic DLBCL, PCNSLs exhibited significantly more focal deletions in 6p21 targeting the HLA-D locus that encodes for MHC class II molecules as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis (SBS1, ID1 and ID2) were significantly enriched in PCNSL (SBS1: p = 0.0027, ID1/ID2: p < 1x10-4). Furthermore, TERT gene expression was significantly higher in PCNSL compared to ABC-DLBCL (p = 0.027). Although PCNSL share many genetic alterations with systemic ABC-DLBCL in the same signaling pathways, transcriptome analysis clearly distinguished both into distinct molecular subtypes. EBV+ CNSL cases may be distinguished by lack of recurrent mutational hotspots apart from IG and HLA-DRB loci.

Testis-Specific Thioredoxins TXNDC2, TXNDC3, and TXNDC6 Are Expressed in Both Testicular and Systemic DLBCL and Correlate with Clinical Disease Presentation

DLBCL is the most common type of non-Hodgkin lymphoma with a substantial group of patients suffering a poor prognosis. Therefore more specific markers are required for better understanding of disease biology and treatment. This study demonstrates that testis-specific antioxidant enzymes TXNDC2, TXNDC3, and TXNDC6 alongside oxidative stress marker 8-OHdG are expressed in both testicular and systemic DLBCL, and their presence or absence has correlations with clinical risk factors such as the number of extranodal effusion, the appearance of B-symptoms, and treatment response. Biopsy samples were collected from 28 systemic and 21 testicular male DLBCL patients. The samples were histostained with TXNDC2, TXNDC3, TXNDC6, and 8-OHdG, then graded by a hematopathologist blinded to clinical data. Immunoelectron microscopy was used as a second method to confirm the reliability of the acquired immunohistochemistry data. The absence of nuclear TXNDC2 expression in testicular DLBCL cells correlated with worse primary treatment response, cytoplasmic TXNDC3 expression in testicular and systemic DLBCL associated with lower frequency of B-symptoms, and TXNDC6 expression in cytoplasm in systemic DLBCL had a clinical significance with higher LD levels suggesting a role in the biological nature of these lymphomas. Overall, TXNDC3 cytoplasmic expression is correlated with a more positive outcome in both testicular and systemic DLBCL, while TXNDC6 cytoplasmic expression is associated with a negative outcome in systemic DLBCL.

Molecular features of a large cohort of primary central nervous system lymphoma using tissue microarray

Key Points PCNSL has a unique molecular profile distinct from that of systemic DLBCL. BCL6 rearrangements are associated with a poor prognosis in PCNSL.

Clinical Relevance of MYD88 L265P Mutation and Interleukin-10 Level in Cerebrospinal Fluid of Patients with Both Newly Diagnosed and Relapsed Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System

Introduction: Early diagnosis remains a major concern in pts with primary diffuse large B-cell lymphoma (DLBCL) of the CNS (PCNSL). Diagnostic delay leads to severe neurological impairment due to prolonged exposure of CNS tissues to tumor infiltration, and protracted steroid therapy, which causes immunodepression and infective complications, the main reasons for treatment interruptions. A few molecular markers have been proposed as diagnostic tools, but reliable parameters that can be easily incorporated in routine practice are still needed. Near 70% of PCNSLs display MYD88 L265P mutation and release high levels of interleukin-10 (IL10). These two parameters are widely used for routine diagnosis of different disorders, but are hardly detectable in peripheral blood of PCNSL pts; accordingly, cerebrospinal fluid (CSF) may be an attractive alternative for their evaluation. Thus, we investigated the sensitivity and specificity of MYD88 L265P mut and IL10 levels in CSF samples to distinguish PCNSL from other neurological disorders, and to identify earlier relapsing lymphomas. Methods: MYD88 mutational status and IL6 and IL10 levels were assessed by TaqMan RT-PCR assay and ELISA, respectively, on CSF samples from 198 HIV-neg adults with 1) histologically-confirmed PCNSL at presentation (pPCNSL; n= 27) or relapse (rPCNSL; n= 26); 2) neurological disorders currently entering in differential diagnosis with PCNSL (n= 105; degenerative and inflammatory disorders, toxic or infective encephalitis, gliomas, and others); 3) systemic DLBCL at high-risk of CNS dissemination (n= 40). MYD88 status was assessed in 85 neurological controls and interleukins in 78; both parameters were assessed in 58. Differences in MYD88 status (categorical variable) and IL10 levels (continuous variables) among pts subgroups were assessed by Fisher exact and Mann-Whitney U tests, respectively. Predictive accuracy of IL6 & IL10 was evaluated in terms of sensitivity and specificity by means of ROC curves. Associations between PCNSL features (site and number of lesions; CSF protein level and cytological status) and analyzed molecules were addressed by Spearman's correlation. Results: Demographic characteristics of analyzed subgroups were similar, with a median (range) age of 62 (39-81) ys for PCNSLs and 63 (28-89) ys for controls (p= 0.42); with 27 (51%) and 69 (48%) males (p= 0.70), respectively. MYD88 L265P mut was detected in 19 (70%) of 27 pPCNSL, in 11 (42%) of 26 rPCNSL, in 1 (1%) of 85 neurological controls and in 1 (3%) of 40 systemic DLBCL (p< 0.00001), with a sensitivity and specificity for pPCNSL detection of 70% and 98%, respectively. Median IL6 concentration was 4.62 pg/mL (0-157.7) for the 53 PCNSLs and 2 pg/mL (0-200) for the 118 assessed controls (p= 1.0). High IL6 levels (>12 pg/mL) were recorded in 5 (18%) of 27 pPCNSL, in 7 (27%) of 26 rPCNSL, in 7 (9%) of 78 neurological controls, and in 0 (0%) of 40 systemic DLBCL. The ROC curve showed a low sensitivity and specificity of IL6 to distinguish PCNSL from other disorders and DLBCL, with an area under the curve of 0.66 (poor accuracy). Median IL10 concentration was 53.3 pg/mL (0-400) for PCNSLs and 0 pg/mL (0-10) for controls (p< 0.00001). Increased IL10 levels were recorded in 20 (91%) of 22 assessed pPCNSL, in 20 (91%) of 23 assessed rPCNSL, in 1 (1%) of 78 neurological controls, and in 1 (2%) of 40 systemic DLBCL, with a sensitivity and specificity for PCNSL detection of 91% and 98%, respectively, and an area under the ROC curve of 0.95 (high accuracy). At least one of analyzed parameters (MYD88 L265P mut & high IL10 level) was recorded in 26 (96%) of 27 pPCNSL, in 23 (88%) of 26 rPCNSL, in 1 (1%) of 58 neurological controls and in 2 (5%) of 40 systemic DLBCL, with a sensitivity and specificity to detect PCNSL of 96% and 97%, respectively. Both MYD88 L265P mut and IL10 levels were independent of lymphoma features. Conclusions: The occurrence of MYD88 L265P mut and high IL10 level in CSF samples are associated with very high sensitivity and specificity in PCNSL pts. These simple and fast procedures, currently used in routine practice, are reliable tools to generate early and strong suspicion of PCNSL at both diagnosis and relapse. These results support the use of MYD88 L265P mut and high IL10 level as diagnostic tools in pts with suspected PCNSL localized in areas unsuitable for biopsy (i.e., brain stem). The role of these parameters in monitoring lymphoma behavior should be addressed in prospective trials. Disclosures No relevant conflicts of interest to declare.

Retrospective analysis of elderly patients with DLBCL: Single center experience with FIL.

e19024 Background: Diffuse Large B-Cell Lymphoma (DLBCL) is the most common subtype of Non-Hodgkin’s Lymphoma (NHL). According to the SEER database, median age of diagnosis is 67 with 30% of cases diagnosed in patients greater than 75. 1/3 of patients older than 80 do not receive therapy for this potentially curable disease. The Lymphoma Italian Foundation (FIL) tool has been shown to help objectively identify elderly DLBCL patients most likely to benefit from therapy with curative intent. The tool identifies patients as “Fit,” “Unfit,” or “Frail” based on age, comorbidities, and ability to perform activities of daily living. We retrospectively applied the FIL tool to patients treated at our center to evaluate its efficacy in identifying elderly patients most likely to benefit from curative chemoimmunotherapy. Methods: Research protocol was approved by University of California, Irvine IRB. We identified patients with a diagnosis of systemic DLBCL and age ≥70 between January 1, 2010 and November 8, 2018. Medical charts were used to retrospectively apply the FILtool. Results: A total of 86 patients were identified. Mean age was 77. Ratio of germinal center (GC) DLBCL to non-GC was approximately 1:1. 23 patients were categorized as Fit, 8 as Unfit, and 55 as Frail. 96% of Fit, 100% of Unfit, and 91% of Frail patients were evaluated. Rates of complete responses (CR) to initial therapy with curative intent were 77% (17/22) in Fit, 88% (7/8) in Unfit, and 44% (22/50) in Frail patients. CR rate was not different between Fit and Unfit (p>0.05), but the CR rate in Frail patients was significantly reduced compared to the other groups combined (p<0.01). Among Fit and Unfit patients, only one death was treatment-related, but in the Frail group, 6 deaths were related to treatment. Conclusions: Our data suggest that the FILTool is useful in identifying Frail patients that perhaps should be treated with reduced dose-intensity. Additionally, our findings support that Fit and Unfit patients benefit from treatment with curative intent. Future studies will apply the FIL tool prospectively to further validate these findings. [Table: see text]

Enhanced Expression of FGF Signaling in Primary Central Nervous System Lymphoma

Introduction: Primary central nervous system lymphoma (PCNSL) is a rare intracranial lymphoma that accounts for less than 1% of all non-Hodgkins lymphomas and 3% of all brain tumors. Histopathologically, approximately 90% of PCNSL cases are categorized as a diffuse large B-Cell lymphoma (DLBCL). DLBCL malignancies are subdivided by Cell of Origin (COO), with the vast majority of PCNSL categorized as non-germinal center B cell (non-GCB) by immunohistochemistry. Gene expression profiling (GEP), however, has shown that immunohistochemically defined non-GCB resolves into two distinct subtypes, namely activated B-cell (ABC) and unclassified (UNC) subtypes. Using the Lymph2Cx molecular COO subtyping assay, we have found that 91% of PCNSL are ABC (unpublished data). Unlike systemic-DLBCL, PCNSL is largely confined to and rarely metastasizes outside of the immune privileged central nervous system. Despite this, PCNSL is one of the most aggressive forms of DLBCL. Given the immune privileged milieu in which PCNSL arises, we hypothesized that this milieu elicits a transcriptional profile that contributes to the enhanced aggressive nature of PCNSL compared to systemic-DLBCL. To investigate this hypothesis, this study assessed the gene expression differences between ABC-PCNSL and ABC-systemic-DLBCL, in order to identify novel players in the pathogenesis of ABC-PCNSL. Methods: A total of 35 HIV negative samples, with proven ABC-subtype COO as per the GEP Lymph2Cx assay, were employed; including 10 ABC systemic-DLBCL and 25 primary ABC PCNSL cases with no concurrent or prior history of systemic DLBCL. Samples were reviewed by a hematopathologist to confirm diagnoses and determine tumor content. Samples with <60% tumor content were macro-dissected before nucleic acid extraction, which was performed using the Qiagen AllPrep DNA/RNA FFPE Kit. Extracted DNA and RNA were quantified using the Qubit HS-kit and NanoDrop respectively. Digital gene expression technology was used to perform the PanCancer Pathways panel (NanoString, Seattle, WA). Differential gene expression analysis was performed using the NanoString specific statistical method NanoStringDiff. Identified gene sets were analyzed using the online Gene Set Enrichment Analysis (GSEA) Molecular Signatures Database (MSigDB). Results: Of the 739 cancer related genes targeted by the PanCancer panel, 256 were found to be significantly differentially expressed in the ABC-PCNSL cohort compared to the ABC-DLBCL cohort (p<0.05). Fifty six genes were upregulated and 200 were downregulated. With a 4.9 fold change, the most significantly overexpressed gene was FGF1 (p=4.7E-11). FGF1 encodes a primary ligand for the fibroblast growth factor receptors (FGFR) -1, -2, -3 and -4; of which, FGFR2 (p=1.0E-7) and FGFR3 (p=0.003) were also significantly overexpressed. Moreover, MSigDB identified the FGF signaling pathway as enriched in the upregulated gene set (5 genes, p=7.4E-9, FDR=6.6E-7). FGFRs are a family of receptors that activate known mitogenic signaling pathways including MAPK signaling, which MSigDB identified as the most enriched pathway in the upregulated gene set (14 genes, p=1.65E-19, FDR=2.2E-16). MSigDB analysis of the 200 down regulated genes revealed that 5 of the top 20 enriched signaling pathways were immune related and included Signaling by interleukins (26 genes, p=2.9E-38, FDR=3.2E-36), Immune cytokine signaling (31 genes, p=1.1 E-34, FDR=1.1E-32), chemokine signaling (28 genes, p=1.5E-34, FDR=1.4E-32), T-cell receptor signaling (24 genes, p=2.4E-34, FDR=1.9E-32) and Toll-like receptor signaling (23 genes, p=4.1E-33, FDR=3.0E-31). Conclusions: We show, for the first time, that ABC-PCNSL and ABC-systemic-DLBCL possess significantly different transcriptional profiles despite identical, molecularly determined, COO status. A principle difference between these DLBCL malignancies is their anatomical location related immune privilege status which is reflected as reduced immune related signaling in the CNS-DLBCL cohort and may have important mitogenic signaling implications. Indeed, the results suggest that the enhanced aggressive nature of PCNSL compared to systemic-DLBCL is mediated, at least in part, by enhanced FGF signaling; a pathway with known roles in cell survival and proliferation. Disclosures Rimsza: NanoString: Other: Inventor on the patent for the Lymph2Cx assay.

Whole-Genome Sequencing of Primary Central Nervous System Lymphoma and Diffuse Large B-Cell Lymphoma

Introduction Primary central nervous system lymphoma (PCNSL) is a rare subtype of non-Hodgkin's lymphoma. Although most cases (~95%) show histology of diffuse large B-cell lymphomas (DLBCLs), PCNSL shows very different biological and clinical characteristics from systemic DLBCL. Nevertheless, our knowledge about the molecular pathogenesis of PCNSL and genetic differences between both lymphomas are still incomplete. Method To obtain a comprehensive view of the genetic alterations, including mutations in non-coding regions as well as structural variants (SVs), we performed whole-genome sequencing (WGS) of 22 PCNSL cases. Subsequently, to unravel the genetic differences between PCNSL and systemic DLBCL, we re-analyzed WGS data from systemic DLBCL cases (N = 47) generated by the Cancer Genome Atlas Network (TCGA) and Cancer Genome Characterization Initiative (CGCI) using our in-house pipeline. The mean depth of WGS for tumor samples were 49X and 37X for PCNSL and DLBCL cases, respectively. Whole-exome sequencing (WES) was also performed for an additional 37 PCNSL cases to reliably capture driver alterations and also to analyze mutational signatures in PCNSL, which were compared to those obtained from the WES data for DLBCL from TCGA (N = 49). Results WGS identified 10.5 and 5.6 mutations per mega-base on average in PCNSL and DLBCL, respectively. We first explored the density of somatic mutations and identified 64 and 33 genomic loci showing significantly high mutation densities in PCNSL and DLBCL, respectively. In PCNSL, most of these loci corresponded to known targets of somatic hypermutations (SHMs) induced by activation-induced cytidine deaminase (AID), including those for IG genes (IGK, IGH and IGL), BCL6, and PIM1, as well as those for known driver genes, such as MYD88 and CD79B. Although most of the hypermutated regions were overlapped between PCNSL and DLBCL, some regions were differentially affected by hypermutations between both lymphoma types. For example, BCL2 and SGK1 loci were frequently affected by SHMs in germinal center B-cell (GCB) DLBCL, while not in PCNSL. In terms of non-coding driver mutations, we identified frequent mutations in a PAX5 enhancer region in 8/22 (36%) of PCNSL and 18/47 (38%) of DLBCL cases. SVs were common in both lymphoma types, where 104 (PCNSL) and 57 (DLBCL) SVs were detected per sample. SV clusters were identified in 34 (PCNSL) and 13 (DLBCL) regions, of which several clusters were commonly seen in both PCNSL and DLBCL, and included IG loci, BCL6, FHIT, TOX and CDKN2A. In PCNSL, SVs were clustered within the loci for known targets of SHMs, such as BCL6, BTG2 and PIM1. As was the case with somatic mutations, the SV cluster corresponding to BCL2 was only seen in DLBCL. We then analyzed these clustered breakpoints for their proximity to known sequence motifs targeted by AID (CpG and WGCW). Breakpoints of SVs found in the targets of SHMs, including PIM1, BCL6, BTG2 and BCL2, showed an enrichment at or near the CpG, supporting the involvement of AID in the generation of these SVs. By analyzing these SV clusters, we identified several novel driver genes in PCNSL. For example, WGS and WES identified an enrichment of breakpoints of deletions (7/22) and loss-of-function mutations (6/37) in GRB2, strongly indicating its tumor suppressor role in PCNSL. We also analyzed pentanucleotide signatures of mutations in coding sequences detected by WES of PCNSL and DLBCL, taking into consideration the two adjacent bases 3' and 5' of the substitutions as well as transcription strand biases. Two predominant mutational signatures were identified in PCNSL: the AID signature characterized by C>T mutations within the WRCY motif targeted by SHMs and the age-related signature involving C>T transition at CpG dinucleotides. For DLBCL, an additional signature (signature 17 according to Alexandrov et al.) was detected as well, which had been reported in DLBCL with an unknown mechanistic basis. Conclusions Comprehensive genomic analyses of a large cohort of PCNSL and DLBCL cases have revealed the major targets of somatic mutations and SVs, including novel driver genes. In both PCNSL and systemic DLBCL, an enhanced AID activity is thought to be associated with generation of both SHMs and SVs, although the activity and targets of AID seem to substantially differ between both lymphoma types, suggesting distinct pathogenesis therein. Disclosures Kataoka: Boehringer Ingelheim: Honoraria; Yakult: Honoraria; Kyowa Hakko Kirin: Honoraria. Ogawa:Takeda Pharmaceuticals: Consultancy, Research Funding; Kan research institute: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding.

Genetic Basis of Primary Central Nervous System Lymphoma

Introduction Primary central nervous system lymphoma (PCNSL) is a rare subtype of non-Hodgkin lymphoma, of which approximately 95% are diffuse large B-cell lymphomas (DLBCLs). Despite the substantial development of intensive chemotherapy during the past two decades, overall clinical outcome of PCNSL has been poorly improved especially in elderly and so has been our knowledge about the molecular pathogenesis of PCNSL, in terms of driver alterations that are relevant to the development of PCNSL. Method To delineate the genetic basis of PCNSL pathogenesis, we performed a comprehensive genetic study. We first analyzed paired tumor/normal DNA from 35 PCNSL cases by whole-exome sequencing (WES). Significantly mutated genes identified by WES and previously known mutational targets in PCNSL and systemic DLBCL were further screened for mutations using SureSelect-based targeted deep sequencing (Agilent) in an extended cohort of PCNSL cases (N = 90). Copy number alterations (CNAs) have been also investigated using SNP array-karyotyping (N =54). We also analyzed WES and SNP array data of systemic DLBCL cases (N = 49) generated by the Cancer Genome Atlas Network (TCGA) to unravel the genetic difference between PCNSL and systemic DLBCL. Results The mean number of nonsynonymous mutations identified by WES was 183 per sample, which was comparable to the figure in systemic DLBCL and characterized by frequent somatic hypermutations (SHMs) involving non-Ig genes. A higher representation of C>T transition involving CpG dinucleotides and hotspot mutations within the WRCY motif targeted by SHM further suggested the involvement of activation-induced cytidine deaminase (AID) in the pathogenesis of PCNSL. We found 12 genes significantly mutated in PCNSL (q < 0.1), including MYD88, PIM1, HLA-A, TMEM30A, B2M, PRDM1, UBE2A, HIST1H1C, as well as several previously unreported mutational targets in systemic DLBCL or PCNSL, such as SETD1B, GRB2, ITPKB, EIF4A2. Copy number analysis identified recurrent genomic segments affected by focal deletions (N = 27) and amplifications (N = 10), most of which included driver genes targeted by recurrent somatic mutations or known targets of focal CNAs such as CDKN2A and FHIT. Subsequent targeted sequencing finally identified a total of 107 significantly mutated genes, of which 43 were thought to be targeted by SHM according to their mutational signature and genomic distribution. Most cases with PCNSL (98%) had mutations and CNAs involving genes that are relevant to constitutive NF-KB/Toll-like receptor (TLR)/BCR activity, including those in MYD88 (80%), CD79B/A (60%), CARD11 (18%), TNFAIP3 (26%), GRB2 (24%) and ITPKB (23%). Genetic alterations implicated in escape from immunosurveillance were also frequently identified in as many as 76% of cases. Mutations of HLA-B (64%), HLA-A (36%), HLA-C (28%), B2M (14%) and CD58 (12%) were commonly detected in addition to CNAs in 6p21.32 (HLA class II), 1p13.1 (CD58) and 15q15.2 (B2M), suggesting the importance of immune escape in the pathogenesis of PCNSL. SHMs were also seen in most cases (98%), which affected not only known targets of AID including PIM1, IGLL5 and BTG2 but also previously unreported genes involved in cell proliferation, apoptosis, or B cell development. The pattern of frequently mutated genes in PNCSL was more uniform compared with that in systemic DLBCL, and similar to that found in the activated B cell subtype of DLBCL (ABC-DLBCL), which was in accordance with the previous report of immunophenotypic analysis of PCNSL. On the other hand, mutations of HLA class I genes (HLA-B, HLA-A) were more frequently mutated in PCNSL compared with ABC-type DLBCL. Conclusion WES, SNP array karyotyping and follow-up targeted sequencing of a large cohort of PCNSL cases revealed the genetic landscape of PCNSL, which were more homogeneous than that of systemic DLBCL, and thought to be involved in activation of constitutive NF-KB/TLR/BCR signaling, escape from immunosurveillance, as well as highly frequent SHMs. Disclosures No relevant conflicts of interest to declare.

Immunohistochemical Profile and Prognostic Significance in Chinese Primary Central Nervous System Lymphoma: Analysis of 132 Cases

Primary central nervous system lymphoma (PCNSL) is aggressive and confined to the central nervous system, including the brain parenchyma, leptomeninges, spinal cord, eyes or cranial nervous. Morphologically, approximately 95% of these tumors are DLBCL according to the new World Health Organization (WHO) classification. However, PCNSL has treatment outcome distinct from those of systemic DLBCL, as well as dismal prognosis than systemic DLBCL. Our goal was to determine the immunohistochemical profile and prognostic significance for 132 Chinese PCNSL cases. The expression of CD20, CD10, BCL-6, MUM1, CD138, BCL-2, and Ki67 antigens were observed by immunohistochemical method. All cases expressed CD20. CD10, BCL-6, and MUM1 were positive in 15.2% (20/132), 86.4% (114/132), 90.2% (119/132). CD138 was negative in 100% (39/39). BCL-2 was positive in 89.3% (108/121). The Ki67 antigen, a proliferative index, ranging from 1% to 100% (median 85.3%) and 76.5% (101/132) PCNSLs showed Ki67 ≥ 90%. Among 132 cases, 25 (18.9%) were classified as germinal center B-cell-like (GCB); 107 (81.1%) were classified as activated B-cell-like (ABC). The Ki67 index in 25 GCB was similar to that in 107 ABC (p=0.663>0.05). No significant correlation was found between Ki67 index and BCL-2 (p=0.225>0.05). Significant positive correlation was found between Ki67 index and BCL-6 expression (p=.000<0.05). Among 132 cases, 43 had complete data of treatment that received chemotherapy regimens based on HD-MTX. GCB and ABC had similar OS (p=0.969) and PFS (p=0.070). These findings support that PCNSL predominantly express an ABC immunophenotype and express high Ki67 index, and suggest that the proliferative activity of GCB was similar to ABC and the expression of BCL-6 but not BCL-2 was positively correlated with the malignant degree of tumors. Table 1. Clinical characteristics. Characteristics Patients, n (%) Age (years); n=132 ≥60 y, n=53; <60 y, n=79 Median (range) 57 (21-85) Gender; n=132 Male 69 (52.3) Female 63 (47.7) ECOG; n=43 0-1 8 (18.6) 2-4 35 (81.4) LDH; n=43 Normal 25 (58.1) Elevated 18 (41.9) Numbers of lesions; n=132 1 48 (36.4) >2 84 (63.6) Involvement of deep structures; n=132 Absence 43 (32.6) Presence 89 (67.4) Table 2. Hans classification. CD10 BCL-6 MUM1 Immunoprofile PCNSL, n (%) + + + GCB 16 (12.1) + + - GCB 3 (2.3) + - + GCB 0 (0) + - - GCB 1 (0.7) - + - GCB 5 (3.8) - + + Non-GCB 90 (68.2) - - + Non-GCB 12 (9.1) - - - Non-GCB 5 (3.8) Table 3. Chang classification. CD10 BCL-6 MUM1 Immunoprofile PCNSL, n (%) + + - GCB (Pattern A) 3 (2.4) + - - GCB (Pattern A) 1 (0.8) - + - GCB (Pattern A) 5 (3.9) + + + activated GCB (Pattern B) 16 (12.6) + - + activated GCB (Pattern B) 0 (0) - + + activated GCB (Pattern B) 90 (70.9) - - + activated non-GCB (Pattern C) 12 (9.4) Figure 1. Immunohistochemical labeling. Figure 1. Immunohistochemical labeling. Figure 2. Kaplan-Meier curve shows clinical prognostic variables and their relationship to OS and/or PFS. Figure 2. Kaplan-Meier curve shows clinical prognostic variables and their relationship to OS and/or PFS. Figure 3. T1 axial, post-gadolinium magnetic resonance imaging of PCNSL. Figure 3. T1 axial, post-gadolinium magnetic resonance imaging of PCNSL. Disclosures No relevant conflicts of interest to declare.