Hypoxia Attenuates Trastuzumab Uptake and Trastuzumab-Emtansine (T-DM1) Cytotoxicity through Redistribution of Phosphorylated Caveolin-1
Bibliographic record
Abstract
Abstract The antibody–drug conjugate trastuzumab-emtansine (T-DM1) offers an additional treatment option for patients with HER2-amplified tumors. However, primary and acquired resistance is a limiting factor in a significant subset of patients. Hypoxia, a hallmark of cancer, regulates the trafficking of several receptor proteins with potential implications for tumor targeting. Here, we have investigated how hypoxic conditions may regulate T-DM1 treatment efficacy in breast cancer. The therapeutic effect of T-DM1 and its metabolites was evaluated in conjunction with biochemical, flow cytometry, and high-resolution imaging studies to elucidate the functional and mechanistic aspects of hypoxic regulation. HER2 and caveolin-1 expression was investigated in a well-annotated breast cancer cohort. We find that hypoxia fosters relative resistance to T-DM1 in HER2+ cells (SKBR3 and BT474). This effect was not a result of deregulated HER2 expression or resistance to emtansine and its metabolites. Instead, we show that hypoxia-induced translocation of caveolin-1 from cytoplasmic vesicles to the plasma membrane contributes to deficient trastuzumab internalization and T-DM1 chemosensitivity. Caveolin-1 depletion mimicked the hypoxic situation, indicating that vesicular caveolin-1 is indispensable for trastuzumab uptake and T-DM1 cytotoxicity. In vitro studies suggested that HER2 and caveolin-1 are not coregulated, which was supported by IHC analysis in patient tumors. We find that phosphorylation-deficient caveolin-1 inhibits trastuzumab internalization and T-DM1 cytotoxicity, suggesting a specific role for caveolin-1 phosphorylation in HER2 trafficking. Implications: Together, our data for the first time identify hypoxic regulation of caveolin-1 as a resistance mechanism to T-DM1 with potential implications for individualized treatment of breast cancer.
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 | 0.000 |
| 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 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".