PCSK9 facilitates melanoma pathogenesis via a network regulating tumor immunity
Bibliographic record
Abstract
Abstract Background PCSK9 regulates cholesterol homeostasis and promotes tumorigenesis. However, the relevance of these two actions and the mechanisms underlying PCSK9’s oncogenic roles in melanoma and other cancers remain unclear. Methods PCSK9’s association with melanoma was analysed using the TCGA dataset. Empty vector (EV), PCSK9, gain-of-function (D374Y), and loss-of-function (Q152H) PCSK9 mutant were stably-expressed in murine melanoma B16 cells and studied for impact on B16 cell-derived oncogenesis in vitro and in vivo using syngeneic C57BL/6 and Pcsk9−/− mice. Intratumoral accumulation of cholesterol was determined. RNA-seq was performed on individual tumor types. Differentially-expressed genes (DEGs) were derived from the comparisons of B16 PCSK9, B16 D374Y, or B16 Q152H tumors to B16 EV allografts and analysed for pathway alterations. Results PCSK9 expression and its network negatively correlated with the survival probability of patients with melanoma. PCSK9 promoted B16 cell proliferation, migration, and growth in soft agar in vitro, formation of tumors in C57BL/6 mice in vivo, and accumulation of intratumoral cholesterol in a manner reflecting its regulation of the low-density lipoprotein receptor (LDLR): Q152H, EV, PCSK9, and D374Y. Tumor-associated T cells, CD8 + T cells, and NK cells were significantly increased in D374Y tumors along with upregulations of multiple immune checkpoints, IFNγ, and 143 genes associated with T cell dysfunction. Overlap of 36 genes between the D374Y DEGs and the PCSK9 DEGs predicted poor prognosis of melanoma and resistance to immune checkpoint blockade (ICB) therapy. CYTH4, DENND1C, AOAH, TBC1D10C, EPSTI1, GIMAP7, and FASL (FAS ligand) were novel predictors of ICB therapy and displayed high level of correlations with multiple immune checkpoints in melanoma and across 30 human cancers. We observed FAS ligand being among the most robust biomarkers of ICB treatment and constructed two novel and effective multigene panels predicting response to ICB therapy. The profiles of allografts produced by B16 EV, PCSK9, D374Y, and Q152H remained comparable in C57BL/6 and Pcsk9−/− mice. Conclusions Tumor-derived PCSK9 plays a critical role in melanoma pathogenesis. PCSK9’s oncogenic actions are associated with intratumoral cholesterol accumulation. PCSK9 systemically affects the immune system, contributing to melanoma immune evasion. Novel biomarkers derived from the PCSK9-network effectively predicted ICB therapy responses.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".