A novel multigene panel (Sig27) robustly predicts poor prognosis of renal cell carcinoma via high-level associations with immunosuppressive features
Bibliographic record
Abstract
BACKGROUND: We investigated a 27-gene panel (Sig27), derived from prostate cancer, for risk stratification of RCC (clear cell RCC/ccRCC, papillary RCC/pRCC, and chromophobe RCC/chRCC). METHODS: Sig27 gene expressions were examined in 960 RCC and 201 kidney tissues. Sig27 was evaluated for predicting overall survival (OS), association with immune checkpoints (IC), regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSC), and tumor-associated macrophages (TAM) in RCC. RESULTS: Sig27 robustly predicts OS of ccRCC, pRCC, and chRCC. Sig27 stratifies high-risk ccRCCs: median survival month (MSM) 19.3 and 80.4% of deaths and high-risk pRCCs (MSM 19.6 and 58.6% of death) compared to low-risk ccRCCs (2.9% of death) and pRCCs (2.7% of fatality). Sig27 contains several novel genes related to the RCC immunosuppressive features. FPR3, NOD2, MCTP1, LAMP3, TFEC, and FAM65B are highly correlated with MDSC, Treg, TAM and multiple (≥12) ICs in RCCs. FPR3 and NOD2 are pattern recognition receptors and initiate proinflammatory responses via sensing pathogen-associated molecular patterns and damage-associated molecular patterns; their upregulations may contribute to chronic inflammation in RCC. The Sig27 metagene is expressed in ccRCC-associated immune cells: exhausted CD8T cells, TAM, Treg, and others. CONCLUSIONS: Sig27 is a novel and effective pan-RCC biomarker with high-level associations with RCC immunosuppressive features.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".