Ectopic Expression of Cancer–Testis Antigens in Cutaneous T-cell Lymphoma Patients
Bibliographic record
Abstract
PURPOSE: The pathogenesis of cutaneous T-cell lymphoma (CTCL) remains only partially understood. A number of recent studies attempted to identify novel diagnostic markers and future therapeutic targets. One group of antigens, cancer-testis (CT) antigens, normally present solely in testicular germ cells, can be ectopically expressed in a variety of cancers. Currently, only a few studies attempted to investigate the expression of CT antigens in CTCL. EXPERIMENTAL DESIGN: In the present work, we test the expression of CT genes in a cohort of patients with CTCL, normal skin samples, skin from benign inflammatory dermatoses, and in patient-derived CTCL cells. We correlate such expression with the p53 status and explore molecular mechanisms behind their ectopic expression in these cells. RESULTS: Our findings demonstrate that SYCP1, SYCP3, REC8, SPO11, and GTSF1 genes are heterogeneously expressed in patients with CTCL and patient-derived cell lines, whereas cTAGE1 (cutaneous T-cell lymphoma-associated antigen 1) was found to be robustly expressed in both. Mutated p53 status did not appear to be a requirement for the ectopic expression of CT antigens. While T-cell stimulation resulted in a significant upregulation of STAT3 and JUNB expression, it did not significantly alter the expression of CT antigens. Treatment of CTCL cells in vitro with vorinostat or romidepsin histone deacetylase inhibitors resulted in a significant dose-dependent upregulation of mRNA but not protein. Further expression analysis demonstrated that SYCP1, cTAGE1, and GTSF1 were expressed in CTCL, but not in normal skin or benign inflammatory dermatoses. CONCLUSIONS: A number of CT genes are ectopically expressed in patients with CTCL and can be used as biomarkers or novel targets for immunotherapy.
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 | 0.001 | 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) | 0.001 | 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".