MétaCan
Menu
← Back to cohort

Plasma arginine as a candidate predictive biomarker for response to immune checkpoint inhibition (ICI) in metastatic colorectal cancer (mCRC): Analysis of the CCTG CO.26 trial.

2023· article· en· W4379282347 on OpenAlexaff
Lucy Xiaolu, Jonathan M. Loree, Derek J. Jonker, Hagen F. Kennecke, Scott Berry, Félix Couture, Chaudhary E. Ahmad, John R. Goffin, Petr Kavan, Mohammed Harb, Bruce Colwell, Setareh Samimi, Benoit Samson, Tahir Abbas, Nathalie Aucoin, Sheryl Koski, Dongsheng Tu, Christopher J. O’Callaghan, Eric X. Chen

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsCentre Hospitalier de l’Université de MontréalBausch Health (Canada)Hôpital du Sacré-Cœur de MontréalJewish General HospitalJuravinski Cancer CentreHôpital Charles-Le MoyneSt. John’s Health Sciences CentreBC Cancer AgencyHôtel-Dieu de QuébecSaskatchewan Cancer AgencyUniversity Health NetworkOttawa HospitalPrincess Margaret Cancer CentreQueen's UniversityDalhousie UniversityMoncton Hospital
Fundersnot available
KeywordsMedicineOncologyInternal medicineHazard ratioBiomarkerImmune systemColorectal cancerPost-hoc analysisProportional hazards modelCancerGastroenterologyCancer researchImmunologyConfidence intervalBiology

Abstract

fetched live from OpenAlex

3545 Background: Nutritional stress is one of the mechanisms used by tumour cells to evade the immune system. Arginine (ARG), an amino acid involved in several cellular functions including immunomodulation, is important in regulating T-lymphocyte cell activity and the anti-tumour response. ARG deficiency in the tumour microenvironment has been shown to impair T-cell response while ARG supplementation may promote anti-tumour immune activity. In this exploratory post-hoc analysis of the Phase II CO.26 trial (NCT02870920), we investigated the role of plasma ARG in predicting response to ICI in patients (pts) with refractory mCRC. Methods: CO.26 was a phase II trial which randomized pts with refractory mCRC to durvalumab plus tremelimumab (D+T) versus best supportive care (BSC). Plasma ARG concentrations were determined from blood samples pre-treatment using HPLC-tandem mass spectrometry. The median plasma ARG value was used as a cut-off stratifying pts into ARG-high (≥10650 ng/ml) versus ARG-low ( < 10650 ng/ml) groups. Progression-free (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared between groups using the log-rank test. Cox proportional hazard models were used to analyze prognostic and predictive impacts of ARG on PFS and OS. Results: Of 180 pts enrolled in CO.26, 162 pts (N = 115 treated with D+T and 47 BSC) had pre-treatment blood samples for baseline ARG analysis. There were no significant differences in baseline characteristics between pts included in this analysis and the total study pts, or between ARG-high and ARG-low pts. In pts treated with D+T, ARG-high was associated with more favourable prognosis (ARG-high median OS 7.62 months vs. ARG-low 5.49 months, multivariable hazard ratio [HR] 0.60, 95% confidence interval [CI] 0.40-0.91, p = 0.016). In ARG-high pts, D+T significantly improved OS (median OS 7.62 months with D+T vs 3.61 months BSC; HR 0.61, 95% CI 0.37-0.99, p = 0.04). In ARG-low pts there was no OS benefit with D+T (median OS 5.49 months D+T vs 4.27 months BSC; HR 0.84, 95% CI 0.50-1.41, p = 0.51. Interaction p = 0.037). Baseline ARG values had no association with PFS or disease control rate. Conclusions: Baseline plasma ARG was prognostic in pts with mCRC treated with D+T, and high ARG was predictive of improved OS with ICI. Prospective studies should be done to validate ARG as a biomarker identifying mCRC pts likely to derive benefit from ICI. Therapeutic approaches targeting the ARG pathway should be investigated in future studies.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.105
GPT teacher head0.475
Teacher spread0.370 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicCancer Immunotherapy and Biomarkers→French-language works237,207→