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Record W4379981853 · doi:10.1002/hon.3164_189

Prognostic impact of HLA‐I neoantigen‐specific CD8+ T cells in limited‐stage follicular lymphoma

2023· article· en· W4379981853 on OpenAlexaffabout
Joshua W.D. Tobin, Hennes Tsang, Ann‐Marie Patch, Colm Keane, Soi Cheng Law, Jay Gunawardana, Piers Blombery, Ella R. Thompson, Muhammed B. Sabdia, Lilia Merida de Long, Karthik Nath, Stephen H. Kazakoff, Chan Y. Cheah, Benhur Amanuel, Tara Cochrane, Jason Butler, Anna Johnston, Mohamed Shanavas, Li Li, Victoria Shelton, Samantha Hershenfeld, Robert Kridel, John F. Seymour, Michael MacManus, Maher K. Gandhi

Bibliographic record

VenueHematological Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersMedical Research CouncilNational Health and Medical Research CouncilMater Foundation
KeywordsStage (stratigraphy)MedicineCD8Follicular lymphomaInternal medicineLymphomaCohortOncologyHuman leukocyte antigenImmunologyBiologyAntigen

Abstract

fetched live from OpenAlex

Introduction: Follicular lymphoma (FL) is the most common indolent NHL. Recently, we demonstrated in limited and advanced stage FL (LSFL, ASFL), that patients with longer remissions had raised clonally expanded intratumoral CD8+ T cells (Tobin, JCO 2019). Durable remissions occur in ∼50% of LSFL patients whereas ASFL is incurable. However, little is known regarding the immunological features associated with this difference. We hypothesized HLA-I neoantigen (neoAg)-specific CD8+ T cells may play a role. Methods: The discovery cohort comprised 101 patients with diagnostic paraffin embedded tissue from the TROG99.03 LSFL clinical trial (MacManus, JCO 2018), in which stage I/II patients were randomized to involved field radiation (IFRT) only or combined modality therapy between 2000 and 2012 (PET from 2006). Contemporaneous validation cohorts were (a) AusLSFL: 60 PET staged, stage I FL patients from Australia (treatment miscellaneous), and (b) CanLSFL: 60 PET staged, stage I FL patients drawn principally from Canada (IFRT only). Digital gene expression (NanoString), targeted sequencing (330 genes), and germline HLA-typing was performed. Mutations observed by sequencing were used to predict neoAgs in TROG99.03 tissues using 8 algorithms (PVACseq) and filtered according to strong binding affinity to HLA-I over wild-type (TESLA consortium guidelines; Wells, Cell 2020). Results: CD8A gene expression was tested for prognostic significance. In TROG99.03, elevated intratumoral CD8A (by MaxStat) was associated with ∼2-fold improvement in PFS for all patients: HR 0.45 (CI: 0.77–0.26, p = 0.0053) and stage I only patients: HR 2.4 (CI: 1.2–4.6, p = 0.036). In keeping with a relationship between CD8+ T cell infiltration and tumor antigen presentation, raised expression of NLRC5 (a transcriptional HLA-I activator) was also associated with superior PFS: HR 0.48 (CI: 0.99–0.24, p = 0.024). CD8A significance was confirmed in both validation cohorts (whereas NLRC5 was validated in AusLSFL only). In keeping with recent IHC CD8 protein data (Los-de Vries, Bld Adv 2022), CD8A gene expression was raised in stage I LSFL vs. 68 ASFL patients treated with immunochemotherapy (p = 0.02). Mutational profiling was concordant with published LSFL data, with CREBBP and KMT2DA most frequent. NeoAg calling methods including functional assays for neoAg peptide binding were confirmed in a separate cohort of fresh FL tissues. 59% of TROG99.03 tissues had ≥1 neoantigens detected. Importantly, unsupervised hierarchical clustering showed 2-fold enrichment of samples with neoantigens among those with high vs. low HLA-I. Conclusions: Raised CD8A is associated with favorable prognosis in LSFL. Our data suggests disease control involves populations of expanded HLA-I neoAg-specific T cells. These findings have implications for novel immunotherapeutic strategies designed to increase the rate of durable remissions. The research was funded by: National Health and Medical Research Council, Australia; Leukaemia Foundation; Mater Foundation Keywords: Diagnostic and Prognostic Biomarkers, Indolent non-Hodgkin lymphoma, Microenvironment Conflicts of interests pertinent to the abstract. C. Keane Honoraria: Takeda, Roche, AZ, MSD, Beigene C. Cheah Consultant or advisory role: Roche, Janssen, Gilead, AstraZenecca, Lilly, TG therapeutics, Beigene, Novartis, Menarini, Daizai, Abbvie, Genmab. BMS Honoraria: BMS, Roche, Abbvie; MSD, Lilly R. Kridel Research funding: Abbvie Educational grants: Eisai M. K. Gandhi Research funding: Beigene, Janssen

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.047
GPT teacher head0.339
Teacher spread0.292 · 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 teacher head, not a consensus.

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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Citations0
Published2023
Admission routes2
Has abstractyes

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