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CD30 Expression in Diffuse Large B-Cell Lymphoma

2012· article· en· W2593953634 on OpenAlexaff
Graham W. Slack, Christian Steidl, Laurie H. Sehn, Randy D. Gascoyne

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsCD30Diffuse large B-cell lymphomaCHOPBCL6LymphomaImmunohistochemistryTissue microarrayBrentuximab vedotinPathologyMedicineCancer researchLarge-cell lymphomaVincristineOncologyChemotherapyInternal medicineGerminal centerB cellImmunologyAntibodyCyclophosphamide

Abstract

fetched live from OpenAlex

Abstract Abstract 1558 Background: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with a variable clinical course. The addition of rituximab (R) to CHOP combination chemotherapy has improved overall (OS) and progression free survival (PFS) but some patients progress despite treatment and alternative therapies are needed. Brentuximab vedotin is an antibody-drug conjugate that targets CD30. It is efficacious in the treatment of relapsed Hodgkin lymphoma and relapsed systemic anaplastic large cell lymphoma, two lymphomas associated with CD30 expression. The association between DLBCL and CD30 expression has not been well described. The aim of this study was to examine CD30 expression in DLBCL. Design: 395 cases of formalin-fixed paraffin-embedded DLBCL (excluding PMBCL) in a tissue microarray were independently evaluated by two pathologists for expression of CD30, CD10, BCL6, and MUM1 by immunohistochemistry (IHC) and EBV RNA (EBER) by in situ hybridization. CD30 expression was correlated with cell of origin (COO) phenotype, OS and PFS, EBV infection, International Prognostic Index (IPI) score and CD30 mRNA expression. The COO phenotype, germinal center B-cell like (GCB) or non-GCB, was determined by IHC using the Hans algorithm. CD30 mRNA expression and COO genotype by gene expression profiling (GEP) were determined using Affymetrix U133 2.0 Plus arrays (n=170). Outcome analysis only included patients treated with R-CHOP chemotherapy. CD30 was considered positive by IHC if any malignant cells exhibited membranous staining. The threshold for calling higher CD30 expression by GEP was determined using X-Tile software. Results: 25% (95/385) of DLBCL cases expressed CD30 by IHC with excellent concordance between two observers (r = 0.94). CD30 expression trended towards a non-GCB phenotype but was not significantly different (p=0.067). CD30 expression was not associated with PFS or OS in all R-CHOP treated cases (n=313); however, it was associated with a prolonged PFS in GCB-DLBCL (n=147) (p=0.019). In GCB-DLBCL CD30 expression remained an independent predictor of PFS in a multivariate analysis with IPI (p=0.038). CD30 expression by IHC was significantly associated with higher levels of CD30 mRNA (p=0.002). ABC-DLBCL exhibited significantly higher expression levels of CD30 mRNA (p=0.037). Higher CD30 mRNA expression was associated with a prolonged PFS in all R-CHOP treated DLBCL (p=0.012) as well as in DLBCL with a GCB-genotype (p=0.008), but not ABC or U-genotypes. Higher CD30 mRNA expression was also associated with a prolonged OS in the GCB-genotype (p=0.022). In the GCB-genotype higher CD30 mRNA expression remained an independent predictor of PFS, but not OS, in a multivariate analysis with IPI (p=0.037). EBV was identified in 3% of DLBCL (11/391), all of which exhibited a non-GCB phenotype (p=0.001) and were almost exclusively positive for CD30 expression (10/11)(p=<0.001). Conclusions: CD30 is expressed in approximately 25% of DLBCL and brentuximab vedotin could be considered for study in combination with traditional front-line therapies or as an alternative therapy in the relapsed or refractory disease. CD30 immunohistochemistry may be useful as a prognostic marker in R-CHOP treated GCB-DLBCL and the significant association of CD30 with EBV-positive non-GCB DLBCL suggests a distinct pathobiology for these cases. Disclosures: Slack: Seattle Genetics: Research Funding. Steidl:Seattle Genetics: Research Funding. Gascoyne:Seattle Genetics: Research Funding.

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)0.000
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.011
GPT teacher head0.246
Teacher spread0.234 · 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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Citations5
Published2012
Admission routes1
Has abstractyes

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