Acidosis significantly alters immune checkpoint expression profiles of T cells from oesophageal adenocarcinoma patients
Bibliographic record
Abstract
Abstract Tumour acidosis contributes to cancer progression by inhibiting anti-tumour immunity. However, the effect of acidosis on anti-tumour T cell phenotypes in oesophageal adenocarcinoma (OAC) is unknown. Therefore, this study investigated the effect of acidosis on anti-tumour T cell profiles and if immune checkpoint blockade (ICB) could enhance anti-tumour T cell immunity under acidosis. Acidic conditions substantially altered immune checkpoint expression profiles of OAC patient-derived T cells, upregulating TIM-3, LAG-3 and CTLA-4. Severe acidosis (pH 5.5) significantly decreased the percentage of central memory CD4+ T cells, an effect that was attenuated by ICB treatment. ICB increased T cell production of IFN-γ under moderate acidosis (pH 6.6) but not severe acidosis (pH 5.5) and decreased IL-10 production by T cells under severe acidic conditions only. A link between lactate and metastasis was also depicted; patients with nodal metastasis had higher serum lactate levels (p = 0.07) which also positively correlated with circulating levels of pro-angiogenic factor Tie-2. Our findings establish that acidosis-induced upregulation of immune checkpoints on T cells may potentially contribute to immune evasion and disease progression in OAC. However, acidic conditions curtailed ICB efficacy, supporting a rationale for utilizing systemic oral buffers to neutralize tumour acidity to improve ICB efficacy. Graphical abstract Study schematic—PBMCs were isolated from OAC patients (A) and expanded ex vivo for 7 days using anti-CD3/28 +IL-2 T cell activation protocol (B) and further cultured for 48 h under increasing acidic conditions in the absence or presence of immune checkpoint blockade (nivolumab, ipilimumab or dual nivolumab + ipilimumab) (C). Immunophenotyping was then carried out to assess immune checkpoint expression profiles and anti-tumour T cell phenotypes (D). Serum lactate was assessed in OAC patients (E–F) and levels were correlated with patient demographics (G) and the levels of circulating immune/pro-angiogenic cytokines that were determined by multiplex ELISA (H). Key Findings—severe acidic conditions upregulated multiple immune checkpoints on T cells (I). Efficacy of ICB was curtailed under severe acidic conditions (J). Circulating lactate levels positively correlated with circulating levels of pro-angiogenic factor tie-2 and higher serum lactate levels were found in patients who had nodal metastasis (K).
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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) | 0.006 | 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".