Antibody-drug conjugate T-DM1 treatment for HER2+ breast cancer induces ROR1 and confers resistance through activation of Hippo transcriptional coactivator YAP1
Bibliographic record
Abstract
BACKGROUND: A newly developed drug trastuzumab emtansine (T-DM1) has improved the survival of breast cancer (BC) patients. Despite an impressive initial clinical response, a subgroup of patient develop resistance and present therapeutic challenges. The underlying resistance mechanisms are not fully investigated. We report that T-DM1 treatment modulates the expression of ROR1 (type 1 receptor tyrosine kinase-like orphan receptor) and induces self-renewal of cancer stem cells (CSCs) leading to therapeutic resistance. METHODS: Using BC patient tumor samples, and BC cell lines we gained insight into the T-DM1 treatment induced ROR1 overexpression and resistance. In vitro sphere forming assays and in vivo extreme dilution assays were employed to analyze the stemness and self-renewal capacity of the cells. A series of molecular expression and protein assays including qRT-PCR, FACS-sorting, ELISA, immunostaining, Western blotting were used to provide evidence. FINDINGS: Exposure of cells to T-DM1 shifted ROR1 expression from low to high, enriched within the CSC subpopulation, coincident with increased Bmi1 and stemness factors. T-DM1 induced ROR1 cells showed high spheroid and tumor forming efficiency in vitro and in an animal model exhibiting shorter tumor-free time. Mechanistically, the overexpression of ROR1 is partly induced by the activation of YAP1 and its target genes. Silencing of ROR1 and YAP1 by pharmacologic inhibitors and/or sh/siRNA inhibited spheroid formation, the initiation of tumors and the capacity for self-renewal and ROR1 overexpression. INTERPRETATIONS: The results presented here indicate that simultaneous targeting of ROR1 and YAP1 may suppress CSC self-renewal efficacy and inhibit tumor progression in BC. In this manner such treatments may overcome the T-DM1 mediated therapeutic resistance and improve clinical outcome. FUND: This study was supported by Neurogen Technologies for interdisciplinary research.
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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) | 0.000 | 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 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".