Integrated molecular characterization reveals the pathogenesis and therapeutic strategies of pulmonary blastoma
Bibliographic record
Abstract
Background: Pulmonary blastoma (PB) is a rare subtype of lung cancer. Currently, the underlying pathogenesis mechanisms of PB have not been fully illustrated, and the therapeutic approach for this entity is limited. Methods: Whole-exome sequencing (WES), RNA sequencing, and DNA methylation profiling are applied to seven PB patients. Multi-omics data of pulmonary sarcomatoid carcinoma (PSC) and pituitary blastoma (PitB) from previous studies are invoked to illuminate the associations among PB and these malignacies. Results: alterations, Wnt signaling pathway dysregulation and IGF2 imprinting dysregulation are the potential pathogenesis mechanisms of PB. Moreover, we reveal that the integrated molecular features of PB are distinct from PSC, and the molecular characteristics of PB are more similar to PitB than to PSC. Pancancer analysis show that the tumor mutation burden (TMB) and leukocyte fraction (LF) of PB are low, while some cases are positive for PD-L1 or have CD8-positive focal areas, implying the potential applicability of immunotherapy in selected PB patients. Conclusion: This study depicts the integrated molecular characteristics of PB and offers novel insights into the pathogenesis and therapeutic strategies of PB.
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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 | 0.000 |
| 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".