Human SP-D Acts as an Innate Immune Surveillance Molecule Against Androgen-Responsive and Androgen-Resistant Prostate Cancer Cells
Bibliographic record
Abstract
Surfactant Protein D (SP-D), a pattern recognition innate immune molecule, has been implicated in the immune surveillance against cancer. Recently, an association between decreased SP-D expression in human prostate adenocarcinoma and an increased Gleason score and severity has been reported. In the present study, we evaluated the SP-D expression in primary prostate epithelial cells (PrEC) and prostate cancer cell lines. LNCaP, an androgen dependent prostate cancer cell line, exhibited significantly lower mRNA and protein levels of SP-D than PrEC and the androgen-independent cell lines (PC3 and DU145). A recombinant fragment of human SP-D (rfhSP-D), composed of trimeric neck and carbohydrate recognition domains, showed a dose- and time- dependent binding to prostate cancer cells via its CRD region. rfhSP-D induced significantly apoptosis in tumour explants and primary tumor cells isolated from tissue biopsies of metastatic prostate cancer patients. While the viability of PrEC was not altered by rfhSP-D, the rfhSP-D LNCaP (p53+/+) and PC3 (p53-/-) cells showed reduced cell viability in a dose- and time- dependent manner, as they were arrested in G2/M and G1/G0 phase of the cell cycle, respectively. The rfhSP-D treated LNCaP cells showed a significant upregulation of p53 whereas a significant downregulation of pAkt was observed in both PC3 and LNCaP cell lines. The rfhSP-D-induced apoptosis signalling cascade involved upregulation of Bax:Bcl2 ratio, cytochrome c and cleaved products of caspase 7. Thus, rfhSP-D induced apoptosis in prostate tumor explants as well as in androgen-responsive and androgen-resistant prostate cancer cells via p53 and pAkt pathways. Thus, by exploiting multiple apoptotic pathways, rfhSP-D treatment can overcome tumorigenesis of varied forms of prostate cancer.
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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) | 0.001 | 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".