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Loss of CIITA and MHC Class II Expression in Diffuse Large B-Cell Lymphoma Is Not Explained by Methylation of CIITA Promoters III and IV.

2008· article· en· W2554544625 on OpenAlexaff
Sarah T. Wilkinson, Diane R. Fernandez, Shawn P. Murphy, Wing C. Chan, Randy D. Gascoyne, Elı́as Campo, Elaine S. Jaffe, Louis M. Staudt, Jan Delabie, Andreas Rosenwald, Lisa M. Rimsza

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsCIITABiologyDiffuse large B-cell lymphomaCancer researchMajor histocompatibility complexMHC class IIMHC class IImmunologyLymphomaImmune system

Abstract

fetched live from OpenAlex

Abstract Diffuse large B-cell lymphoma (DLBCL) is the most commonly diagnosed lymphoma in the United States, accounting for approximately 40% of non-Hodgkin lymphoma cases. It is a heterogeneous disease that is marked by highly variable patient outcome. Characterizing the mechanism(s) responsible for poor patient outcome is critical for improving treatment. Major histocompatibility complex class II (MHC II) molecules are cell-surface glycoproteins that present peptides for antigen recognition, and are important for the adaptive immune response. Loss of MHC II expression correlates with poor patient prognosis in DLBCL. The expression of classical MHC II, non-classical MHC II, and invariant chain molecules are coordinately regulated by the class II transactivator (CIITA), the master regulator of MHC II transcription. We have previously shown that expression of individual MHC II molecules, invariant chain, and CIITA all change in concert with one another in DLBCL patient samples. These coordinate changes are not explained by large genetic deletions within the MHC II region, and suggest that altered transcription via CIITA is the mechanism for MHC II down-regulation in DLBCL patients. We have also previously shown that somatic mutations of CIITA do not explain the coordinate down-regulation. In this study, we asked whether epigenetic silencing of CIITA by CpG methylation could explain the loss of MHC II expression in DLBCL patients with poor prognosis. CIITA pIII and pIV promoters are active in B cells, and loss of MHC II due to epigenetic silencing of pIII and pIV has been shown in other tumor types. A total of 74 DLBCL and other lymphoma patient samples and cell lines with varying levels of MHC II expression were analyzed. The extent of DNA methylation of the CIITA promoter regions pIII and pIV was determined by bisulfite modification, amplification of the regions of interest, and cloning and sequencing of 10 successful bisulfite-modified amplicons per sample. The pIII and pIV promoter regions contain 9 and 12 potential CpG methylation sites, respectively. Negative control cell lines demonstrated an average of 0.1 % methylated cytosines in the pIII promoter and 0.0 % in the pIV promoter. A positive control cell line demonstrated an average of 67 % methylated cytosines in the pIII promoter and 58 % in the pIV promoter. In contrast to controls, DLBCL cell lines and patient samples did not display consistent patterns of methylation at CIITA pIII or pIV promoters, but demonstrated variation within and between samples. Some variability could be due to heterogeneity of cell types within tissue samples. The overall incidence of methylation of CIITA pIII and pIV promoters in DLBCL cell lines and patient samples was low, usually 10 % or less. Importantly, DNA methylation at the CIITA promoters did not correlate with downregulation of MHC II expression. Therefore, epigenetic silencing of CIITA by DNA methylation is not a likely mechanism for loss of MHC II expression in DLBCL. The role of histone modifications of CIITA as a mechanism for loss of MHC II expression in DLBCL is currently being pursued.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.230
Teacher spread0.218 · 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 designBench or experimental
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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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