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Record W2909672303 · doi:10.1182/blood-2018-99-114218

Molecular Features of Primary Central Nervous System Lymphoma in a Large Tissue Microarray

2018· article· en· W2909672303 on OpenAlexaffabout
Diego Villa, Graham W. Slack, Muntadhar Al-Moosawi, Susana Ben‐Neriah, Tamara Shenkier, Joseph M. Connors, Laurie H. Sehn, Kerry J. Savage, David W. Scott, Christian Steidl, Randy D. Gascoyne, King Tan

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicCNS Lymphoma Diagnosis and Treatment
Canadian institutionsSpinal Cord Injury BCUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsBCL6Primary central nervous system lymphomaMedicineTissue microarrayImmunohistochemistryLymphomaIn situ hybridizationRituximabDiffuse large B-cell lymphomaPathologyOncologyBiopsyFluorescence in situ hybridizationCancerInternal medicineBiologyB cellAntibodyImmunologyGene expression

Abstract

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Abstract Background The pathogenesis of primary central nervous system lymphoma (PCNSL) remains poorly understood. The objective of this study was to evaluate the distribution and prognostic impact of a broad range of molecular attributes in a large tissue microarray (TMA) from immunocompetent patients with PCNSL. Methods Patients with PCNSL diagnosed during 1998 - 2010 were identified using the BC Cancer Lymphoid Cancer clinical and pathology databases. Archival formalin-fixed, paraffin-embedded diagnostic biopsy tissue was retrieved, and TMAs were constructed. Immunohistochemistry (IHC) for CD10, BCL6, MUM-1, GCET1, FOXP1, and LMO2 protein expression was used to assign cell of origin (COO) by three different algorithms. IHC for MYC, BCL2, PDL-1, and HLA class II protein expression was also performed. In situ hybridization for Epstein-Barr virus-encoded RNA (EBER) was performed. Fluorescent in-situ hybridization (FISH) was performed for MYC, BCL2, BCL6, PDL1/2 (9p24.1), and CIITA (16p13) rearrangements. Results A total of 115 patients with PCNSL with DLBCL histology were included in the final analysis: 59% male, 70% age >60 years, 77% performance status >1. Primary treatment modalities included high-dose methotrexate (HDMTX) based regimens in 52 (45%) patients, whole brain radiotherapy (WBRT) alone in 40 (35%) patients, and best supportive care in 23 (20%) patients. Among the 52 HDMTX-treated patients, 18 also received WBRT (pre-planned combined modality therapy or inability to tolerate HDMTX), and 11 also received rituximab. Failure of IHC/FISH occurred in 0-21% of individual assays, largely due to insufficient tissue material. The majority of patients had a non-GCB COO phenotype as determined by the Hans (76%), Choi (86%), and Tally (99%) algorithms. MYC protein expression was positive (≥40%) in 37/93 (40%) patients, BCL2 (≥50%) in 68/91 (75%) [124 antibody] and 87/111 (78%) [E17 antibody] patients, and dual MYC/BCL2 in 30/88 (35%) [124 antibody] and 32/92 (35%) [E17 antibody] patients. PDL-1 protein expression was positive (≥1%) in 31/107 (29%) patients. HLA class II antigen expression was positive (≥10%) in 75/112 (67%) patients, with staining restricted to cytoplasm (70%) or cell membrane (30%). EBER was positive (any staining) in 8/108 (7%) patients. Chromosomal rearrangements by FISH were very uncommon for MYC 1/93 (1%), BCL2 1/110 (1%), PDL1/2 1/101 (1%), and CIITA 3/105 (3%). There were no dual rearrangements involving MYC and BCL2, although the only patient with a MYC rearrangement also had a concurrent BCL6 rearrangement. In contrast, BCL6 rearrangements were present in 33/108 (31%) patients, while BCL6 protein expression was positive in 86/111 (77%) patients. With a median follow-up of 8 years (range 8 months - 16 years) in living patients, the 5-year PFS and OS estimates were 11% and 24%, respectively. In univariate analysis, elevated LDH, treatment with WBRT alone or supportive care, and the presence of BCL6 rearrangements (HR 1.73 [95% CI 1.12, 2.66], p=0.011) were significantly associated with worse PFS. Age >60, poor performance status, and treatment with WBRT alone or supportive care were significantly associated with worse OS, and a trend observed with the presence of BCL6 rearrangements (HR 1.46 [95% CI 0.95, 2.27], p=0.085). All other clinical and pathologic variables were not associated with PFS or OS. In the 52 patients treated with HDMTX-based regimens, the presence of a BCL6 rearrangement was the only variable associated with a worse PFS (HR 2.50 [95% CI 1.25 - 5.01], p=0.007), and no variables were associated with OS. Discussion and Conclusions This large TMA study shows that prominent molecular features of PCNSL are different from those of systemic DLBCL. There was a high TMA failure rate reflecting the limitations of brain biopsies, which are often stereotactic needle biopsies, small surgical samples, or obtained after a course of corticosteroids. Consistent with other reports, the majority of cases had a non-GCB phenotype by IHC algorithms, but cell of origin did not impact PFS or OS. MYC, BCL2, and PDL-1 protein expression were common but their corresponding gene rearrangements were extremely uncommon suggesting alternate mechanisms driving expression. BCL6 rearrangements were frequent and were the only factor associated with a poor prognosis in the overall cohort and in the subgroup of patients treated with HDTMX-based regimens. Disclosures Connors: Janssen: Research Funding; Genentech: Research Funding; NanoString Technologies: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Merck: Research Funding; Bristol Myers-Squibb: Research Funding; Bayer Healthcare: Research Funding; F Hoffmann-La Roche: Research Funding; Roche Canada: Research Funding; Lilly: Research Funding; Seattle Genetics: Honoraria, Research Funding; Takeda: Research Funding; Amgen: Research Funding; Cephalon: Research Funding. Sehn:TG Therapeutics: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria; Merck: Consultancy, Honoraria. Scott:Celgene: Consultancy, Honoraria; Janssen: Research Funding; Roche: Research Funding; NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding. Steidl:Juno Therapeutics: Consultancy; Bristol-Myers Squibb: Research Funding; Tioma: Research Funding; Seattle Genetics: Consultancy; Nanostring: Patents & Royalties: patent holding; Roche: Consultancy. Gascoyne:NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.226
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2018
Admission routes2
Has abstractyes

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