Intrinsic bioenergetic adaptations compensate for reduced mitochondrial content in HER2-driven mammary tumors
Bibliographic record
Abstract
Abstract It is now recognized that mitochondria play a crucial role in tumorigenesis, however, it has become clear that tumor metabolism varies significantly between cancer types. The failure of recent clinical trials attempting to directly target tumor respiration with inhibitors of oxidative phosphorylation has highlighted the critical need for additional studies comprehensively assessing mitochondrial bioenergetics. Therefore, we systematically assessed the bulk tumor and mitochondrial metabolic phenotype between murine HER2-driven mammary cancer tumors and paired benign mammary tissue. Transcriptomic and proteomic profiling revealed that HER2-driven mammary tumors are characterized by a downregulation of mitochondrial genes/proteins compared to benign mammary tissue, including a general downregulation of OXPHOS subunits comprising Complexes I-IV. Despite this observation, mitochondrial respiration supported by both carbohydrate-derived substrates (pyruvate) and lipids (palmitoyl-carnitine) was several-fold higher in HER2-driven tumors which persisted regardless of normalization method (i.e. wet weight, total protein content and when corrected for mitochondrial content). This upregulated respiratory capacity could not be explained by OXPHOS uncoupling; however, several subunits/regulators of Complex V function were not downregulated in the tumors, suggesting possible compensatory effects may contribute to high respiratory rates. Furthermore, tumor mitochondria displayed a smaller and more punctate morphology, aligning with a general reduction in mitochondrial fusion and increase in mitochondrial fission markers, which could contribute to improved OXPHOS efficiency. Together, this data highlights that the typical correlation of mitochondrial content and respiratory capacity may not apply to all tumor types and implicates the activation of mitochondrial respiration supporting tumorigenesis in this model.
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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".