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CTEP 10492, a phase 1/1b study of the AKT inhibitor ipatasertib with chemoradiation for locally advanced head and neck squamous cell carcinoma.

2024· article· en· W4400272633 on OpenAlexaff
Malcolm D. Mattes, Henning Willers, Yong Lin, Laila A. Gharzai, Erin R. Alesi, C.E. Lominska, Sung Joon Kim, Missak Haigentz, Varinder Kaur, Susanne M. Arnold, Timothy W. Synold, J. Silvio Gutkind, Lori J. Wirth, Ariella B. Hanker, Rabih Said, Lillian L. Siu, Salma K. Jabbour

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineHead and neckHead and neck squamous-cell carcinomaBasal cellOncologyCancer researchInternal medicineSquamous cell cancerHead and neck cancerRadiation therapySurgery

Abstract

fetched live from OpenAlex

TPS6127 Background: Locally advanced head and neck squamous cell carcinoma (HNSCC) is commonly treated with definitive chemoradiation therapy (CRT). However, locoregional recurrence rates of approximately 50% may occur in high risk patients. As such, there is an unmet need for up-front treatment intensification in this patient population. Preclinical evidence suggests that both radiation therapy (RT) and cisplatin activate the PI3K/AKT pathway, leading to treatment resistance through multiple processes, including increased DNA repair, decreased apoptosis, and modulation of the tumor microenvironment by promoting angiogenesis, immune escape and hypoxia. Furthermore, AKT inhibitors have been shown to sensitize a subset of HNSCC models to RT and platinum chemotherapy in vitro and in vivo. However, radiosensitization using a specific AKT inhibitor has not yet been studied in humans. This phase I studywill bethe first to establish safety and preliminary efficacy of ipatasertib combined with standard of care definitive CRT for HNSCC. Methods: The primary objective of this study is to determine the maximum tolerated dose and recommended Phase 2 dose (RP2D) of ipatasertib in combination with definitive CRT in locally advanced HNSCC based on dose-limiting toxicities (DLTs). Secondary objectives include assessment of acute and late toxicities, long term swallowing function, and a preliminary assessment of efficacy. Eligible subjects must have pathologically confirmed, previously untreated, non-metastatic HNSCC that is either human papilloma virus (HPV)-negative clinical stage III-IVB, or HPV-positive clinical stage III. The study schema includes dose escalation and expansion cohorts. All subjects will receive RT for a standard 70 Gy in 7-week course, with concurrent weekly cisplatin. Two 28-day cycles of orally administered ipatasertib will be given concurrently with CRT. The four dose levels of ipatasertib range from 100-400 mg daily. Dose escalation of ipatasertib will follow a Time-to-Event Bayesian Optimal Interval (TITE-BOIN) design, with DLT window extending from the start of CRT, through 28 days after completion of RT. The expansion cohort will enroll an additional 10 subjects at the RP2D, and incorporate pharmacodynamic biopsies for each subject to evaluate whether the addition of ipatasertib to CRT will result in increased gamma-H2AX, consistent with radiosensitization, and also decreased pS6 and pPRAS40 to evaluate AKT pathway inhibition. Additional correlative studies include assessment of the pharmacokinetic profile of ipatasertib with CRT, as well as correlation of efficacy with tumor genotype, based on whole exome sequencing of pre-treatment biopsy specimens. Enrollment is currently at dose level 2 in the escalation phase, and is expected to complete accrual in 2025. Clinical trial information: NCT05172245 .

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)0.002
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0080.002

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 head0.043
GPT teacher head0.412
Teacher spread0.369 · 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 designNon-randomized trial
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

Citations2
Published2024
Admission routes1
Has abstractyes

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