Abstract P013: Germinal center hypoxia in tumor-draining lymph nodes negatively regulates humoral immune responses and affects the activation of tumor-infiltrating T cells
Bibliographic record
Abstract
Abstract Efforts to understand intrinsic and acquired resistance to anti-tumor immunotherapies have largely focused on characterizing factors within the primary tumor. However, lymph nodes are specialized hubs of immune response development, and an improved understanding of the microenvironmental conditions impacting immune cell activation in tumor-draining lymph nodes (TDLNs) may yield novel approaches for enhancing responses to anti-tumor immunotherapies. Using mouse models of breast cancer, we identified hypoxic regions amongst the B cell germinal center reactions of TDLNs. Injection of lethally irradiated tumor cells was sufficient to induce GC hypoxia, and hypoxia in TDLNs associated with the frequency of antibody- secreting cells. In vitro, hypoxia impaired the proliferation of activated B cells, and inhibited class-switching to IgG1 and IgA immunoglobulin isotypes. To assess the role of the hypoxic response in tumor-reactive GCs in vivo, we deleted von Hippel- Lindau factor (VHL) in class-switched B cells and found decreased GC B cells in TDLNs, and reduced class-switched and tumor-specific antibodies in the circulation, indicating that the hypoxic response negatively-regulates tumor-induced humoral immune responses. pVHL deletion in class-switched B cells also reduced the expression of activation markers amongst tumor-infiltrating T cells and increased the presence of M2-like macrophages within the primary tumor. We detected the hypoxia marker carbonic anhydrase IX in the GCs of LNs from breast cancer patients, providing the first line of evidence that hypoxia develops within human GCs and validating our observations of hypoxia in TDLNs of pre-clinical mammary tumor models. We conclude that GC hypoxia develops in TDLNs, and that the hypoxic response negatively regulates tumor-induced humoral immune responses in pre-clinical models, with consequent impacts on the phenotype tumor-infiltrating T cells and macrophages. Citation Format: Natalie Firmino, Kevin Bennewith. Germinal center hypoxia in tumor-draining lymph nodes negatively regulates humoral immune responses and affects the activation of tumor-infiltrating T cells [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2021 Oct 5-6. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(1 Suppl):Abstract nr P013.
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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) | 0.006 | 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".