Alterations of Ceramide Synthesis Induce PD-L1 Internalization and Signaling to Regulate Tumor Metastasis and Immunotherapy Response 2131
Bibliographic record
Abstract
Abstract Description Programmed death-ligand 1, PD-L1 (CD274) facilitates immune evasion and exerts pro-survival functions in cancer cells. Here, we report a mechanism whereby internalization of PD-L1 in response to alterations of bioactive lipid/ceramide metabolism by ceramide synthase 4 (CerS4) induces sonic-hedgehog (Shh) and TGF-b receptor signaling to enhance tumor metastasis in triple-negative breast cancers (TNBC), exhibiting immunotherapy resistance. Mechanistically, data showed that internalized PD-L1 interacts with an RNA-binding protein Caprin-1 to stabilize Shh/TGFBR1/Wnt mRNAs to induce b-catenin signaling and TNBC growth/metastasis, consistent with increased infiltration of FoxP3+ T regs and resistance to immunotherapy. While mammary tumors developed in MMTV-PyMT/CerS4-/- were highly metastatic, targeting the Shh/PD-L1 axis using Sonidegib and anti-PD-L1 antibody vastly decreased tumor growth and metastasis, consistent with the inhibition of PD-L1 internalization and Shh/Wnt signaling, restoring anti-tumor immune response. These data, validated in clinical samples and databases, provide a mechanism-based therapeutic strategy to improve immunotherapy responses in metastatic TNBCs. Our recent and unpublished data also revealed that attenuation of CerS4 expression and increased intracellular PD-L1 signaling in TNBC tumors result in resistance to anti-PD-1 or anti-PD-L1-based immunotherapy in TNBCs. Inhibition of intracellular PD-L1 signaling resensitized resistant TNBCs in vivo. Funding Sources This work was supported by research funding from the National Institutes of Health (CA214461, DE016572, and P01 CA203628 to BO). Topic Categories Tumor Immunology: Checkpoints, Prevention, and Treatment (TIPT)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".