A Targetable EGFR-Dependent Tumor-Initiating Program in Breast Cancer
Bibliographic record
Abstract
Therapies targeting epidermal growth factor receptor (EGFR) have variable and unpredictable responses in breast cancer. Screening triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), we identify a subset responsive to EGFR inhibition by gefitinib, which displays heterogeneous expression of wild-type EGFR. Deep single-cell RNA sequencing of 3,500 cells from an exceptional responder identified subpopulations displaying distinct biological features, where elevated EGFR expression was significantly enriched in a mesenchymal/stem-like cellular cluster. Sorted EGFRhi subpopulations exhibited enhanced stem-like features, including ALDH activity, sphere-forming efficiency, and tumorigenic and metastatic potential. EGFRhi cells gave rise to EGFRhi and EGFRlo cells in primary and metastatic tumors, demonstrating an EGFR-dependent expansion and hierarchical state transition. Similar tumorigenic EGFRhi subpopulations were identified in independent PDXs, where heterogeneous EGFR expression correlated with gefitinib sensitivity. This provides new understanding for an EGFR-dependent hierarchy in TNBC and for patient stratification for therapeutic intervention.
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 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 | 0.000 | 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 | 0.000 |
| 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 teacher head, 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".