Overexpression of HER-2 in MDA-MB-435/LCC6 Tumours is Associated with Higher Metabolic Activity and Lower Energy Stress
Bibliographic record
Abstract
Overexpresssion of HER-2 in the MDA-MB-435/LCC6 (LCC6(HER-2)) tumour model is associated with significantly increased hypoxia and reduced necrosis compared to isogenic control tumours (LCC6(Vector)); this difference was not related to tumour size or changes in vascular architecture. To further evaluate factors responsible for HER-2-associated changes in the tumour microenvironment, small animal magnetic resonance imaging (MRI) and positron emission tomography (PET) were used to measure tumour tissue perfusion and metabolism, respectively. The imaging data was further corroborated by analysis of molecular markers pertaining to energy homeostasis, and measurements of hypoxia and glucose consumption. The results showed a strong trend towards higher perfusion rates (~58% greater, p = 0.14), and significantly higher glucose uptake in LCC6(HER-2) (~2-fold greater; p = 0.025), relative to control tumours. The expression of proteins related to energy stress (P-AMPK, P-ACC) and glucose transporters (GLUT1) were lower in LCC6(HER-2) tumours (~2- and ~4-fold, respectively). The in vitro analysis showed that LCC6(HER-2) cells become more hypoxic in 1% oxygen and utilise significantly more glucose in normoxia compared to LCC6(Vector)cells (p < 0.005). Amalgamation of all the data points suggests a novel metabolic adaptation driven by HER-2 overexpression where higher oxygen and glucose metabolic rates produce rich energy supply but also a more hypoxic tumour mass.
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) | 0.002 | 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".