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FAS Mutations Accelerate Lymphoma Growth and Induce Therapeutic Resistance

2014· article· en· W2553666848 on OpenAlexaff
Stephanie Totten, Denis Gaucher, Ryan D. Morin, Sarit Assouline, Joseph M. Connors, Marco A. Marra, David W. Scott, Randy D. Gascoyne, Jerry Pelletier, Koren K. Mann, Nathalie A. Johnson

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsSimon Fraser UniversitySpinal Cord Injury BCMcGill UniversityBC Cancer AgencyJewish General Hospital
Fundersnot available
KeywordsFas ligandFas receptorCancer researchApoptosisLymphomaImmunologyChemotherapyMedicineBiologyRituximabProgrammed cell deathInternal medicineGenetics

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Rituximab-based chemotherapy is effective in inducing remissions in ~85% patients with untreated follicular lymphoma (FL). Primary treatment failure or an early relapse after first-line therapy is associated with a very poor prognosis. Recent sequencing efforts have been successful at identifying recurrent genetic events that contribute to the pathogenesis of FL, but the clinical significance of most of these events, in particular those contributing to therapeutic resistance, remain unknown. We identified a mutation in FAS (Y232*) in a patient with primary-refractory FL. FAS, a key death receptor in the extrinsic apoptotic pathway, plays a fundamental role in immune homeostasis by initiating apoptosis in lymphocytes once activated by FAS ligand (FASL) from neighboring cells. Herein, we show that mutations in FAS contribute to therapeutic resistance in FL. METHODS: We determined the incidence and clinical significance of FAS mutations in an extended cohort of 214 clinically-annotated FL biopsies. We determined the impact of the recurrent FAS(Y232*) mutation on FAS-mediated and chemotherapy-induced apoptosis in lymphoma cell lines. We measured the change in FAS and FASL expression in primary human T and B lymphocytes after exposure to chemotherapy. Finally, we cloned the murine equivalent of FAS(Y232*), Fas(Y224*), in Eu-Myc lymphoma cells and determined its effect on lymphoma growth and response to chemotherapy in immunocompetent C57BL/6 mice (n=36). RESULTS: FAS mutations were identified in 6% of FL patients. Coding FAS mutations were associated with a trend towards an earlier median time to progression (1 y versus 2.8 y, p=0.08) and an increased risk of histological transformation (p=0.036). The recurrent FAS(Y232*) mutation inhibited FAS-mediated apoptosis in cell lines but, unexpectedly, did not inhibit chemotherapy-mediated apoptosis. We hypothesized that in patients, chemotherapy induced a FAS-mediated immune response that was not modeled in vitro. Supporting this concept, we observed an increase in FASL and FAS expression on normal T and B lymphocytes, respectively, after exposure to etoposide. We injected three groups of mice with Eu-Myc lymphoma cells that differed only in their Fas genotype (Fas WT, Fas(Y224*) and an empty vector control) and monitored lymph node volumes before and after therapy. Fas(Y224*) dramatically accelerated lymphoma growth. Lymph node volumes exceeded those measured in Fas wild-type and control mice at all time points beyond the day of injection. The average maximal lymph node volume for the Fas(Y224*) group was 59.9 mm3 compared to 18.9 mm3 and 34.5 mm3 for the Fas WT and control groups, respectively (p < 0.001). Fas mutant lymphomas had an inferior response to doxorubicin and none of the mice in this group achieved a complete remission. Remarkably, the opposite phenotype was observed in the Fas WT group, where the addition of Fas WT inhibited lymphoma growth and induced earlier remissions. CONCLUSION: Mutations in FAS can be clinically important in patients with FL by promoting lymphoma growth and inducing therapeutic resistance. The full malignant phenotype of FAS mutant lymphomas could only be elicited in vivo, and not in vitro, suggesting that a FAS-mediated immune response controls lymphoma growth and actively participates in chemotherapy-induced cell death. Disclosures Connors: Seattle Genetics, Inc.: Research Funding; Roche: 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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)0.0020.000

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 head0.017
GPT teacher head0.249
Teacher spread0.232 · 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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Citations1
Published2014
Admission routes1
Has abstractyes

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