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Flow Cytometric Characterization of 129 Cases of Peripheral T Cell Lymphoma Not Otherwise Specified (PTCL NOS) and Angioimmunoblastic T Cell Lymphoma (AITL)

2015· article· en· W2463649602 on OpenAlexaff
Greg Hapgood, Anja Mottok, Graham W. Slack, Randy D. Gascoyne, Christian Steidl, Kerry J. Savage, Andrew P. Weng

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsAngioimmunoblastic T-cell lymphomaImmunophenotypingPathologyPeripheral T-cell lymphomaLymphomaCD5Flow cytometryT cellMedicineBiologyImmunologyImmune system

Abstract

fetched live from OpenAlex

Abstract Background: Peripheral T cell lymphoma not otherwise specified (PTCL NOS) and angioimmunoblastic T cell lymphoma (AITL) together comprise approximately half of all peripheral T cell lymphomas. Malignant T cells in AITL and in a subset of PTCL-NOS exhibit a phenotype mimicking that of normal T-follicular helper (TFH) cells. Immunohistochemical (IHC) studies performed on paraffin-embedded tissues are a mainstay of diagnostic histopathology, but can be difficult to interpret when the malignant T cells show limited cytological atypia and when there are abundant infiltrating reactive T cells. Flow cytometry represents an alternate means to define the cellular immunophenotype, but requires access to single cell suspensions of viable tumor cells. Flow cytometry has certain additional benefits over IHC including highly quantitative measurement of multiple antigens simultaneously and statistical power afforded by analyzing tens of thousands of individual cells. We report here immunophenotypic characterization of a large cohort of cases of PTCL NOS and AITL using a 12-color flow cytometry assay and correlation of immunophenotypic features with clinical outcomes. Methods: Cases of PTCL-NOS and AITL spanning a 24 year period (1990-2014) for which viably frozen cell suspensions from diagnostic lymph node biopsies were available were identified within the British Columbia Cancer Agency (BCCA) lymphoma database. Cryopreserved cell suspensions were thawed and stained with a 12-color panel including 11fluorochrome-conjugated antibodies against lineage (CD45, CD19, CD3, CD4, CD8), pan-T cell (CD2, CD5, CD7), and TFH cell (CD10, CD279, CXCR5) markers, plus DAPI for gating of live cells. Flow cytometric data was acquired on a Becton Dickinson FACSAria3 instrument as part of a sorting experiment to isolate tumor cell subpopulations. Data was analyzed by conventional gating and bivariate plot display using FlowJo software and correlated with clinical outcome data. Results: 74 cases of PTCL-NOS and 55 cases of AITL were analyzed. The median age at diagnosis was 57 years (y) for PTCL NOS (male:female 1.6) and 75 y for AITL (male:female 1.0). The median follow up for living patients was 5.15 y. The median specimen viability was 36.5% (range 0.8-89.3%) and median specimen tumour content was 64.3% of viable events (range 0.98-91.8%). Aberrant T cell immunophenotypes were identified in 50 of 74 cases (68%) of PTCL NOS and 36 of 55 cases (65%) of AITL. Five specimens had more than one identifiable immunophenotypically aberrant T cell population. For the 50 PTCL NOS cases with an aberrant immunophenotype, 31 (62%) demonstrated loss of CD3 and 42 (84%) demonstrated loss of CD7. About half of cases were CD4+CD8- (27, or 54%) including 11 (22%) that exhibited a TFH-like phenotype (positive for at least 2 of the 3 assayed TFH markers), while the remaining were CD4-CD8- (23, or 46%). TFH-like cells were also identified in 11 of 24 (46%) cases lacking an aberrant T cell immunophenotype. For the 36 AITL cases with an aberrant immunophenotype, 21 (58%) demonstrated loss of CD3 and 29 (80%) demonstrated loss of CD7. The majority of cases were CD4+ (30, or 83%) including 21 (58%) that exhibited a TFH-like phenotype, while the remaining were either CD8+ (4, or 11%) or CD4-CD8- (2, or 6%). TFH-like cells were also identified in 7 of 19 (37%) cases lacking an aberrant T cell immunophenotype. Similar to other patient cohorts, the 5 y PFS and 5 y OS was 21% and 40%, respectively, for PTCL NOS and 17% and 28%, respectively, for AITL. The presence of an aberrant phenotype, CD3 status, and CD4/CD8 status were not associated with prognosis in either PTCL subtype. A preliminary analysis suggests loss of CD7 expression in PTCL NOS is associated with an inferior outcome. Analysis of archival material and exploration in a validation cohort is ongoing. Discussion: An aberrant population of varying abundance was detected in >65% of specimens for PTCL NOS and AITL. The aberrant immunophenotype in PTCL NOS was evenly split between CD4+CD8- and CD4-CD8- cases. Interestingly, nearly half of CD4+ cases showed evidence of TFH-like differentiation, possibly corresponding to the TFH-like variant of PTCL NOS. The aberrant immunophenotype in AITL was typically CD4+ and often with co-expression of TFH-associated markers. Loss of CD7 and CD3 were the most common abnormalities. Loss of CD7 may demonstrate a poor-risk group of patients with inferior outcomes in PTCL NOS. Disclosures Savage: Seattle Genetics: Honoraria, Speakers Bureau; BMS: Honoraria; Infinity: Honoraria; Roche: Other: Institutional 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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.021
GPT teacher head0.229
Teacher spread0.208 · 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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Citations3
Published2015
Admission routes1
Has abstractyes

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