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Record W4412110327 · doi:10.1158/1535-7163.mct-24-0995

KRAS Codon-Specific Mutations Differentially Toggle PI3K Pathway Signaling and Alter Sensitivity to Inavolisib (GDC-0077)

2025· article· en· W4412110327 on OpenAlexaff
K S Song, Christy C. Ong, Eva Lin, Jeffrey Lau, Nicole M. Sodir, Dexter X. Jin, Katherine E. Hutchinson, Shiqi Xie, Jenille Tan, Yuxin Liang, Zora Modrušan, Scott E. Martin, Danilo Maddalo, Marc Hafner, Anwesha Dey

Bibliographic record

VenueMolecular Cancer Therapeutics · 2025
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsDiscovery Centre
FundersBroad Institute
KeywordsKRASMAPK/ERK pathwayPI3K/AKT/mTOR pathwayColorectal cancerCancer researchIn vivoBiologySignal transductionMutationCancerGeneticsGene

Abstract

fetched live from OpenAlex

PIK3CA and KRAS are among the most frequently mutated oncogenes and often co-mutated in colorectal cancers. Understanding the impact of KRAS codon-specific mutations on cross-talks between the PI3K and MAPK pathways and response to targeted therapies, such as the p110α-specific inhibitor inavolisib (GDC-0077), is critical for advancing precision oncology. Focusing on colorectal PIK3CA + KRAS co-mutated models, we found that KRASG12D-mutated cells were more sensitive to inavolisib than models with KRASG13D, or other MAPK pathway mutations, even though the PI3K and MAPK pathways were active in both genotypes. In most co-mutated models, regardless of the type of KRAS alteration, the combination of inavolisib with MAPK pathway inhibitors showed synergy in vitro and in vivo. Our work highlights how specific codon substitutions in KRAS differentially toggle pathway activity and alter sensitivity to inavolisib, which could inform whether patients would benefit more from single-agent inavolisib or combination with MAPK pathway inhibitors.

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)0.000
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 score0.205
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.306
Teacher spread0.281 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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