Expression of Insulin-Like Growth Factor Pathway Proteins in Rhabdomyosarcoma: IGF-2 Expression is Associated with Translocation-Negative Tumors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent studies have shown a significant involvement of insulin-like growth factor (IGF) signaling components in the pathogenesis of rhabdomyosarcoma (RMS). Furthermore, there has been some evidence to indicate that differential expression of IGF pathway genes can distinguish RMS subtypes. The present study utilized immunohistochemistry to determine the expression patterns of IGF1, IGF2, IGF binding protein 2 (IGFBP2), IGF receptor 1 (IGF1R), and IGF receptor 2 (IGF2R) in 24 embryonal RMS (ERMS) and 8 alveolar RMS (ARMS). A majority of tumors were positive for IGF2, IGFBP2, IGF1R, and IGF2R and negative for IGF1 expression. However, only IGF2 showed a significant difference in expression between the ERMS and ARMS subtypes, with higher levels of expression in ERMS (P = 0.0003). Within the ARMS subtype, IGF2 positivity was limited to PAX/FKHR translocation-negative tumors. The staining pattern for all 5 proteins was diffuse cytoplasmic in the majority of tumors. Analysis of RMS cell lines by real-time reverse transcriptase-polymerase chain reaction for IGF2 expression revealed significantly higher mean expression levels in ERMS and translocation-negative ARMS cell lines when compared to translocation-positive ARMS cell lines (P = 0.0027). Stable introduction of PAX3/FKHR into an ERMS cell line also demonstrated a significant reduction in IGF2 expression. The results of this study show that expression of the IGF2 ligand is associated with translocation-negative tumors and may serve as a diagnostic aid in distinguishing RMS subtypes. Furthermore, the in vitro results are supportive of a role for the PAX3/FKHR fusion gene in the inhibition of IGF2 expression.
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.
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 | 0.000 |
| 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 it