Increasing Tumor Extracellular pH by an Oral Alkalinizing Agent Improves Antitumor Responses of Anti-PD-1 Antibody: Implication of Relationships between Serum Bicarbonate Concentrations, Urinary pH, and Therapeutic Outcomes
Bibliographic record
Abstract
Acidic extracellular pH (pHe) is characteristic of the tumor microenvironment. Several reports suggest that increasing pHe improves the response of immune checkpoint inhibitors in murine models. To increase pHe, either sodium bicarbonate (NaHCO3) or citric acid/potassium-sodium citrate (KNa-cit) was chronically administered to mice. It is hypothesized that bicarbonate ions (HCO3−), produced from these alkalinizing agents in vivo, increased pHe in the tumor, and excess HCO3− eliminated into urine increased urinary pH values. However, there is little published information on the effect of changing serum HCO3− concentrations, urinary HCO3− concentrations and urinary pH values on the therapeutic outcomes of immunotherapy. In this study, we report that oral administration of either NaHCO3 or KNa-cit increased responses to anti-programmed cell death-1 (PD-1) antibody, an immune checkpoint inhibitor, in a murine B16 melanoma model. In addition, we report that daily oral administration of an alkalinizing agent increased blood HCO3− concentrations, corresponding to increasing the tumor pHe. Serum HCO3− concentrations also correlated with urinary HCO3− concentrations and urinary pH values. There was a clear relationship between urinary pH values and the antitumor effects of immunotherapy with anti-PD-1 antibody. Our results imply that blood HCO3− concentrations, corresponding to tumor pHe and urinary pH values, may be important factors that predict the clinical outcomes of an immunotherapeutic agent, when combined with alkalinizing agents such as NaHCO3 and KNa-cit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".