Lactic Acid and an Acidic Tumor Microenvironment suppress Anticancer Immunity
Bibliographic record
Abstract
Immune evasion and altered metabolism, where glucose utilization is diverted to increased lactic acid production, are two fundamental hallmarks of cancer. Although lactic acid has long been considered a waste product of this alteration, it is now well accepted that increased lactic acid production and the resultant acidification of the tumor microenvironment (TME) promotes multiple critical oncogenic processes including angiogenesis, tissue invasion/metastasis, and drug resistance. We and others have hypothesized that excess lactic acid in the TME is responsible for suppressing anticancer immunity. Recent studies support this hypothesis and provide mechanistic evidence explaining how lactic acid and the acidic TME impede immune cell functions. In this review, we consider lactic acid's role as a critical immunoregulatory molecule involved in suppressing immune effector cell proliferation and inducing immune cell de-differentiation. This results in the inhibition of antitumor immune responses and the activation of potent, negative regulators of innate and adaptive immune cells. We also consider the role of an acidic TME in suppressing anticancer immunity. Finally, we provide insights to help translate this new knowledge into impactful anticancer immune therapies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".