The gene expression profile of extraskeletal myxoid chondrosarcoma
Bibliographic record
Abstract
Extraskeletal myxoid chondrosarcoma (EMC) is a soft tissue tumour that occurs primarily in the extremities and is characterized by a balanced translocation most commonly involving t(9;22) (q22;q12). The morphological spectrum of EMC is broad and thus a diagnosis based on histology alone can be difficult. Currently, no systemic therapy exists that improves survival in patients with EMC. In the present study, gene expression profiling has been performed to discover new diagnostic markers and potential therapeutic targets for this tumour type. Global gene expression profiling of ten EMCs and 26 other sarcomas using 42,000 spot cDNA microarrays revealed that the cases of EMC were closely related to each other and distinct from the other tumours profiled. Significance analysis of microarrays (SAM) identified 86 genes that distinguished EMC from the other sarcomas with 0.25% likelihood of false significance. NMB, DKK1, DNER, CLCN3, and DEF6 were the top five genes in this analysis. In situ hybridization for NMB gene expression on tissue microarrays (TMAs) containing a total of 1164 specimens representing 62 different sarcoma types and 15 different carcinoma types showed that NMB was highly expressed in 17 of 22 EMC cases and very rarely expressed in other tumours and thus could function as a novel diagnostic marker. High levels of expression of PPARG and the gene encoding its interacting protein, PPARGC1A, in most EMCs suggest activation of lipid metabolism pathways in this tumour. Small molecule inhibitors for PPARG exist and PPARG could be a potential therapeutic target for EMC.
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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) | 0.000 | 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 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".