Relative quantification of protein expression in metastatic renal cell carcinoma using iTRAQ LC-MS/MS analysis reveals galectin-1 as a potential prognostic marker and therapeutic target.
Bibliographic record
Abstract
412 Background: Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant cancers. Identification of proteins involved in tumor progression will help gain a better understanding of the disease and will form the basis for the identification of novel therapeutic targets. Methods: Using six fresh-frozen primary and six unmatched metastatic RCC tumors, we used iTRAQ labeling and LC-MS/MS analysis to identify proteins differentially expressed in metastatic versus primary RCC. We verified protein expression by western blot and immunohistochemical analyses and the measured the effect of dysregulated protein expression on biological processes with RCC cell line models. Results: After analysis, we identified 29 proteins differentially expressed in metastatic versus primary RCC. We verified expressions of profilin-1, 14-3-3 zeta/delta, and galectin-1 (Gal-1) on two independent tissue sets by western blot (10 primary and 10 metastatic RCC tissues) and immunohistochemistry (22 primary and 23 metastatic tissues). Overexpression of Gal-1 in CAKI-1 cells lead to decreased actin, increased vimentin expression, and increased cellular migration. Additionally, when Gal-1 was decreased via siRNA, cells showed decreased cellular migration. Protein array analysis showed expression of cell motility-related proteins HSP27, JNK, and RSK, were altered after siRNA transfection. We also showed that Gal-1 expression was increased in response to HIF-1alpha. Furthermore, we analyzed the expression of Gal-1 mRNA in 404 RCC patients using the Cancer Genome Anatomy Project, and found that patients who had higher Gal-1 expression in the primary RCC had significantly decreased overall survival (41 vs. 78 months; p < 0.01). Conclusions: Gal-1 is increased in metastatic RCC and can effect cell migration by targeting proteins involved in cell motility. This may be a downstream effect of HIF-1α dysregulation. Decreased Gal-1 significantly decreased cellular migration suggesting Gal-1 may serve as a potential therapeutic target. Additionally, we showed that increased Gal-1 expression was associated with decreased overall survival.
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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 | 0.003 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 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".