Distinctive Histogenesis and Immunological Microenvironment Based on Transcriptional Profiles of Follicular Dendritic Cell Sarcomas
Bibliographic record
Abstract
Abstract Follicular dendritic cell (FDC) sarcomas are rare mesenchymal tumors with variable clinical, morphologic, and phenotypic characteristics. Transcriptome analysis was performed on multiple FDC sarcomas and compared with other mesenchymal tumors, microdissected Castleman FDCs, and normal fibroblasts. Using unsupervised analysis, FDC sarcomas clustered with microdissected FDCs, distinct from other mesenchymal tumors and fibroblasts. The specific endowment of FDC-related gene expression programs in FDC sarcomas emerged by applying a gene signature of differentially expressed genes (n = 1,289) between microdissected FDCs and fibroblasts. Supervised analysis comparing FDC sarcomas with microdissected FDCs and other mesenchymal tumors identified 370 and 2,927 differentially expressed transcripts, respectively, and on the basis of pathway enrichment analysis ascribed to signal transduction, chromatin organization, and extracellular matrix organization programs. As the transcriptome of FDC sarcomas retained similarity with FDCs, the immune landscape of FDC sarcoma was investigated by applying the CIBERSORT algorithm to FDC sarcomas and non-FDC mesenchymal tumors and demonstrated that FDC sarcomas were enriched in T follicular helper (TFH) and T regulatory (TREG) cell populations, as confirmed in situ by immunohistochemistry. The enrichment in specific T-cell subsets prompted investigating the mRNA expression of the inhibitory immune receptor PD-1 and its ligands PD-L1 and PD-L2, which were found to be significantly upregulated in FDC sarcomas as compared with other mesenchymal tumors, a finding also confirmed in situ. Here, it is demonstrated for the first time the transcriptional relationship of FDC sarcomas with nonmalignant FDCs and their distinction from other mesenchymal tumors. Implications: The current study provides evidence of a peculiar immune microenvironment associated with FDC sarcomas that may have clinical utility. Mol Cancer Res; 15(5); 541–52. ©2017 AACR.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".