Direct GDP-KRAS <sup>G12C</sup> inhibitors and mechanisms of resistance: the tip of the iceberg
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Kirsten rat sarcoma viral oncogene homolog mutations are observed in 25% of lung adenocarcinoma and 40% of these are G12C mutations. Historically, no approved targeted agents were available for patients with any KRAS mutation, and response rates to standard-of-care therapies were suboptimal. Newly developed inhibitors directed toward KRAS G12C have been successful in clinical trials with overall response rates ranging between 32% and 46%, and two FDA approvals were granted in May 2021 and December 2022 as second-line or later monotherapies. However, rapid tumor resistance complicates their use as a monotherapy. With the rapid development of this novel class of inhibitors, it is important to discern the different types of tumor resistance that may arise and how each can differently contribute to tumor growth and survival. G12C inhibitor resistance is under investigation and combinations of therapies with G12C inhibitors have been proposed. Much of this insight is gleaned from preclinical investigations, as our knowledge of clinical resistance is in its infancy. In this review, we summarize the preclinical development of KRAS G12C inhibitors, their clinical evaluations, different types of resistance mechanisms to these compounds, and ways of overcoming them. Finally, we underscore the importance of basic and translational investigations of these molecules in a landscape where their clinical evaluations garner the most attention, and we set the stage for what is to come.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it