The integrated stress response is tumorigenic and constitutes a therapeutic liability in KRAS-driven lung cancer
Bibliographic record
Abstract
The integrated stress response (ISR) is an essential stress-support pathway increasingly recognized as a determinant of tumorigenesis. Here we demonstrate that ISR is pivotal in lung adenocarcinoma (LUAD) development, the most common histological type of lung cancer and a leading cause of cancer death worldwide. Increased phosphorylation of the translation initiation factor eIF2 (p-eIF2α), the focal point of ISR, is related to invasiveness, increased growth, and poor outcome in 928 LUAD patients. Dissection of ISR mechanisms in KRAS-driven lung tumorigenesis in mice demonstrated that p-eIF2α causes the translational repression of dual specificity phosphatase 6 (DUSP6), resulting in increased phosphorylation of the extracellular signal-regulated kinase (p-ERK). Treatments with ISR inhibitors, including a memory-enhancing drug with limited toxicity, provides a suitable therapeutic option for KRAS-driven lung cancer insofar as they substantially reduce tumor growth and prolong mouse survival. Our data provide a rationale for the implementation of ISR-based regimens in LUAD treatment.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".