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Abstract A017-PR013: Alectinib in children and adolescents with solid or CNS tumors harboring ALK-fusions: An update from the iMATRIX alectinib phase I/II open-label, multi-center study

2025· article· en· W4414501656 on OpenAlexaff
François Doz, Michela Casanova, Kyung‐Nam Koh, Karsten Nysom, Adela Cañete, Hyoung Jin Kang, Matthias A. Karajannis, Darren Hargrave, Nadège Corradini, Yeming Wu, Huanmin Wang, David S. Ziegler, Nicolas Prud'homme, Carla Manzitti, Quentin Campbell-Hewson, Carolina Sturm‐Pellanda, Tao Xu, Dhruvitkumar S. Sutaria, Livingstone Fultang, Clare Devlin, Francis Mussai, Amar Gajjar

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsAlectinibAnaplastic lymphoma kinasePhases of clinical researchPleomorphic xanthoastrocytomaLymphomaHematopathologyCrizotinib

Abstract

fetched live from OpenAlex

Abstract Background: Alectinib is a next generation, oral, ALK inhibitor being investigated in children and adolescents with ALK-fusion bearing tumors. Here we present updated safety and efficacy data from iMATRIX Alectinib phase I-II study (NCT04774718). Methods: Patients, less than 18 years of age, with ALK fusion-positive CNS and non-CNS tumors for whom prior treatment had proven to be ineffective or for whom there was no satisfactory treatment available were eligible. Patients were recruited to Part 1 to confirm the recommended phase 2 dose (RP2D) and to study drug pharmacokinetics. Alectinib was administered as an oral tablet or suspension twice a day according to initial weight. Investigators reported Best Overall Response according to RANO (CNS tumors) or RECIST v1.1 (solid tumors) criteria (data cut off February 2025). Results: In total 25 patients with a median age of 7.5 years (range 0-17 years) were enrolled. Fifteen patients were diagnosed with solid tumors: inflammatory myofibroblastic tumor (n = 10), renal cell carcinoma (n = 2), mesothelioma (n = 1), nephroblastoma (n = 1), and atypical melanocytic tumor (n = 1). Eight patients were diagnosed with CNS tumors: high grade glioma (n = 7) and pleomorphic xanthoastrocytoma (n = 1). Two patients had ineligible conditions: histiocytosis (n = 1) and anaplastic large cell lymphoma (n = 1). Ten of 25 patients had received prior systemic therapy. ALK fusion partners were EML4 and CLTC in 3 patients, TPM3, KIF5C, PPP1CB and FN1 in 2 patients, and DCTN1, KIF5B, NPM, STRN, CLIP1, RANBP2, ZEB2, PLEKHA7, CDC42BPB, HNRNPA3, and ZNF397 in 1 patient each. In the 24 safety evaluable patients, only 1 Dose Limiting Toxicity (DLT) of Grade 3 increased alanine aminotransferase, during multiple viral infections, was reported. The DLT resolved after treatment interruption and Alectinib was successfully tolerated at a reduced dose level. Twenty patients (83%) experienced at least one Adverse Event (AE) reported as related to Alectinib, mostly Grade 1 or 2. Grade ≥ 3 AEs assessed as related to alectinib by the investigator were reported for 6 patients (25%) and consisted of increases in CPK,AST, ALT, bilirubin; neutropenia, optic neuropathy, encephalopathy and weight gain. Of these the increased ALT (DLT) and optic neuropathy/ encephalopathy in 2 patients were serious AEs. No new safety signals were detected. Investigator reported Best Overall Response rate in 19 patients was 89.5%; (3 CRs, 14 PRs) and 2 patients were reported to have confirmed stable disease. One complete response and 5 partial responses were observed in 6/6 evaluable patients with CNS tumors. Two complete responses and 9 partial responses were seen in 11 evaluable patients with solid tumours. Four patients were excluded from the efficacy analysis due to ineligible tumor type (n = 2), not dosed (n = 1), no measurable disease according to RANO criteria (n = 1). Conclusions: Alectinib continues to have a favourable safety profile in pediatric patients. Clinical efficacy results are highly encouraging with most patients experiencing a tumor response. Citation Format: Francois Doz, Michela Casanova, Kyung-Nam Koh, Karsten Nysom, Adela Canete, Hyoung Jin Kang, Matthias Karajannis, Darren Hargrave, Nadege Corradini, Yeming Wu, Huanmin Wang, David Ziegler, Nicolas Prud'homme, Carla Manzitti, Quentin Campbell-Hewson, Carolina Sturm-Pellanda, Tao Xu, Dhruvitkumar S. Sutaria, Livingstone Fultang, Clare Devlin, Francis Mussai, Amar J Gajjar. Alectinib in children and adolescents with solid or CNS tumors harboring ALK-fusions: An update from the iMATRIX alectinib phase I/II open-label, multi-center study [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Discovery and Innovation in Pediatric Cancer— From Biology to Breakthrough Therapies; 2025 Sep 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_2):Abstract nr A017-PR013.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.098
GPT teacher head0.513
Teacher spread0.415 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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