Cancer metabolism, stemness and tumor recurrence
Bibliographic record
Abstract
Here, we interrogated head and neck cancer (HNSCC) specimens (n = 12) to examine if different metabolic compartments (oxidative vs. glycolytic) co-exist in human tumors. A large panel of well-established biomarkers was employed to determine the metabolic state of proliferative cancer cells. Interestingly, cell proliferation in cancer cells, as marked by Ki-67 immunostaining, was strictly correlated with oxidative mitochondrial metabolism (OXPHOS) and the uptake of mitochondrial fuels, as detected via MCT1 expression (p < 0.001). More specifically, three metabolic tumor compartments were delineated: (1) proliferative and mitochondrial-rich cancer cells (Ki-67+/TOMM20+/COX+/MCT1+); (2) non-proliferative and mitochondrial-poor cancer cells (Ki-67-/TOMM20-/COX-/MCT1-); and (3) non-proliferative and mitochondrial-poor stromal cells (Ki-67-/TOMM20-/COX-/MCT1-). In addition, high oxidative stress (MCT4+) was very specific for cancer tissues. Thus, we next evaluated the prognostic value of MCT4 in a second independent patient cohort (n = 40). Most importantly, oxidative stress (MCT4+) in non-proliferating epithelial cancer cells predicted poor clinical outcome (tumor recurrence; p < 0.0001; log-rank test), and was functionally associated with FDG-PET avidity (p < 0.04). Similarly, oxidative stress (MCT4+) in tumor stromal cells was specifically associated with higher tumor stage (p < 0.03), and was a highly specific marker for cancer-associated fibroblasts (p < 0.001). We propose that oxidative stress is a key hallmark of tumor tissues that drives high-energy metabolism in adjacent proliferating mitochondrial-rich cancer cells, via the paracrine transfer of mitochondrial fuels (such as L-lactate and ketone bodies). New antioxidants and MCT4 inhibitors should be developed to metabolically target "three-compartment tumor metabolism" in head and neck cancers. It is remarkable that two "non-proliferating" populations of cells (Ki-67-/MCT4+) within the tumor can actually determine clinical outcome, likely by providing high-energy mitochondrial "fuels" for proliferative cancer cells to burn. Finally, we also show that in normal mucosal tissue, the basal epithelial "stem cell" layer is hyper-proliferative (Ki-67+), mitochondrial-rich (TOMM20+/COX+) and is metabolically programmed to use mitochondrial fuels (MCT1+), such as ketone bodies and L-lactate. Thus, oxidative mitochondrial metabolism (OXPHOS) is a common feature of both (1) normal stem cells and (2) proliferating cancer cells. As such, we should consider metabolically treating cancer patients with mitochondrial inhibitors (such as Metformin), and/or with a combination of MCT1 and MCT4 inhibitors, to target "metabolic symbiosis."
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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 | 0.000 |
| 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".