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Record W3202999930 · doi:10.1136/jitc-2021-003476

Antitumor immune effects of preoperative sitravatinib and nivolumab in oral cavity cancer: SNOW window-of-opportunity study

2021· article· en· W3202999930 on OpenAlexafffund
Marc Oliva, Douglas B. Chepeha, Daniel Vilarim Araújo, J. Javier Díaz-Mejía, Peter Olson, Amy Prawira, Anna Spreafico, Scott V. Bratman, Tina Shek, John R. de Almeida, Aaron R. Hansen, Andrew Hope, David P. Goldstein, Ilan Weinreb, Stephen Smith, Bayardo Perez‐Ordoñez, Jonathan Irish, Dax Torti, Jeffrey P. Bruce, Ben X. Wang, Anthony J. Fortuna, Trevor J. Pugh, Hirak Der‐Torossian, Ronald Shazer, Nickolas Attanasio, Qingyan Au, Antony Tin, Jordan Feeney, Himanshu Sethi, Alexey Aleshin, Isan Chen, Lillian L. Siu

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsOntario Institute for Cancer ResearchUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersCanadian Institutes of Health ResearchGenentechAstellas PharmaEisaiNational Cancer InstituteNateraMacroGenicsMirati TherapeuticsRegeneron PharmaceuticalsArray BioPharmaMorphoSysCelgeneSymphogenBristol-Myers SquibbAstraZenecaAmgenPfizerAgios PharmaceuticalsGlaxoSmithKline
KeywordsNivolumabMedicineOncologyCancerTumor microenvironmentInternal medicineGastroenterologyImmunotherapyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Sitravatinib, a tyrosine kinase inhibitor that targets TYRO3, AXL, MERTK and the VEGF receptor family, is predicted to increase the M1 to M2-polarized tumor-associated macrophages ratio in the tumor microenvironment and have synergistic antitumor activity in combination with anti-programmed death-1/ligand-1 agents. SNOW is a window-of-opportunity study designed to evaluate the immune and molecular effects of preoperative sitravatinib and nivolumab in patients with oral cavity squamous cell carcinoma. METHODS: Patients with newly-diagnosed untreated T2-4a, N0-2 or T1 >1 cm-N2 oral cavity carcinomas were eligible. All patients received sitravatinib 120 mg daily from day 1 up to 48 hours pre-surgery and one dose of nivolumab 240 mg on day 15. Surgery was planned between day 23 and 30. Standard of care adjuvant radiotherapy was given based on clinical stage. Tumor photographs, fresh tumor biopsies and blood samples were collected at baseline, at day 15 after sitravatinib alone, and at surgery after sitravatinib-nivolumab combination. Tumor flow cytometry, multiplex immunofluorescence staining and single-cell RNA sequencing (scRNAseq) were performed on tumor biopsies to study changes in immune-cell populations. Tumor whole-exome sequencing and circulating tumor DNA and cell-free DNA were evaluated at each time point. RESULTS: Ten patients were included. Grade 3 toxicity occurred in one patient (hypertension); one patient required sitravatinib dose reduction, and one patient required discontinuation and surgery delay due to G2 thrombocytopenia. Nine patients had clinical-to-pathological downstaging, with one complete response. Independent pathological treatment response (PTR) assessment confirmed a complete PTR and two major PTRs. With a median follow-up of 21 months, all patients are alive with no recurrence. Circulating tumor DNA and cell-free DNA dynamics correlated with clinical and pathological response and distinguished two patient groups with different tumor biological behavior after sitravatinib alone (1A) versus sitravatinib-nivolumab (1B). Tumor immunophenotyping and scRNAseq analyses revealed differential changes in the expression of immune cell populations and sitravatinib-targeted and hypoxia-related genes in group 1A vs 1B patients. CONCLUSIONS: The SNOW study shows sitravatinib plus nivolumab is safe and leads to deep clinical and pathological responses in oral cavity carcinomas. Multi-omic biomarker analyses dissect the differential molecular effects of sitravatinib versus the sitravatinib-nivolumab and revealed patients with distinct tumor biology behavior. TRIAL REGISTRATION NUMBER: NCT03575598.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.338
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.019
GPT teacher head0.326
Teacher spread0.307 · 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.

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

Citations52
Published2021
Admission routes2
Has abstractyes

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