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Novel potent and selective fourth-generation inhibitors targeting EGFR for NSCLC therapy.

2025· article· en· W4410803029 on OpenAlexaff
Gauthier Errasti, Thomas Delacroix, Kalpana Ghoshal, Robert J. Lee, Anisha Ghosh, Raj Chakrabarti

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineTargeted therapyCancer researchErlotinibGefitinibOncologyPharmacologyEpidermal growth factor receptorInternal medicineCancer

Abstract

fetched live from OpenAlex

8622 Background: Epidermal growth factor receptor (EGFR)-activating mutations (Del19 or L858R) are oncogenic drivers of non-small cell lung cancer (NSCLC). Most patients treated with tyrosine kinase inhibitors (TKIs) will eventually develop resistance mutations including the T790M gatekeeper mutation. Osimertinib, a third-generation covalent TKI, is efficacious against the T790M resistance mutation and prevents its onset. However, treatment with Osimertinib inevitably induces additional mutations, especially the C797S mutation, as well as various off-target resistance mechanisms. To date, there are no approved therapies capable of overcoming mutational or non-mutational resistance to third-generation EGFR TKIs. Methods: We have characterized the efficacy of two novel fourth-generation EGFR inhibitors, CCM-205 and CCM-308, which are potent against both mutational and non-mutational tumor resistance to Osimertinib. Enzymatic binding affinities were determined by KdELECT assay. Cell-Titer-Glo (CTG) assay was used to assess cytotoxicity (cellular IC 50 ) of CCM-205 and CCM-308 in vitro on EGFR triple mutant and other Osimertinib-resistant cell lines, with comparison to both Osimertinib and fourth-generation EGFR inhibitor BLU-945. In vivo tumor growth inhibition (TGI) was determined in Osimertinib-resistant xenografts including the triple mutant PC9-DTC (Del19/T790M/C797S) model. Results: In Ba/F3 EGFR DTC and LTC cells, CCM-205 / CCM-308 inhibit proliferation with IC 50 s of 137 nM / 40 nM and 198 nM / 61 nM respectively, while Osimertinib antiproliferation is limited to 1.225 µM and 1.562 µM respectively. Moreover, CCM-205 / CCM-308 spare Ba/F3 EGFR WT better than Osimertinib with IC 50 s of 577 nM / 294 nM (182 nM for Osimertinib). CCM-205 / CCM-308 also bind tightly to double mutants targeted by Osimertinib with K d s for EGFR LT (L858R/T790M) of 4.9 nM / 1.2 nM. CCM-205 and CCM-308 are more potent against PC9 DTC cells (IC 50 s: 1.02 µM and 220 nM, respectively) than Osimertinib (4.10 µM) and are comparable to BLU-945 (559 nM). In addition, CCM-205 / CCM-308 are highly potent against Osimertinib-resistant PC9 (IC 50 s: 728 nM / 321 nM) and H1975 (IC 50 s: 1.716 µM / 684 nM) cell lines generated through 8-week treatment with 1 µM Osimertinib (Osimertinib IC 50 = 3.81 µM and 4.70 µM, respectively), while EGFR-specific fourth-generation inhibitors targeting C797S such as BLU-945 lose potency (IC 50 s: 7.96 µM and > 10 µM, respectively). In the PC9-DTC xenograft, CCM-205 completely inhibited tumor growth and induced tumor regression (> 100% TGI) exceeding that of BLU-945, while the tumor was resistant to Osimertinib (< 20% TGI), when agents were delivered orally at similar fractions of their maximum tolerated doses (MTDs). Conclusions: Novel fourth-generation EGFR inhibitors have been developed that can potentially overcome both on-target and off-target resistance in NSCLC and have potential clinical applications.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.095
GPT teacher head0.498
Teacher spread0.403 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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