A3 TARGETING PROLINE METABOLISM TO OVERCOME TREATMENT RESISTANCE IN ESOPHAGEAL CANCER
Bibliographic record
Abstract
Abstract Background Patients with esophageal malignancy have a 5-year survival rate of only 14% in Canada. This high mortality rate is due to three factors: late diagnosis, difficulty to surgically remove the tumor due to its localization and treatment resistance. Treatment resistance has been ascribed to the presence of cancer stem cells (CSCs) inside the tumor. However, no treatment specifically directed against CSCs is available to patients. Therefore, targeting CSCs is a promising strategy to improve survival of patients with esophageal squamous cell carcinoma (ESCC), the most common type of esophageal cancer worldwide. Aims Herein, we developed an unbiased approach to identify new players in chemotherapy and radiotherapy resistance in ESCC. Methods We established radioresistant (RR), chemoresistant (CR) and radiochemoresistant (RCR) human ESCC cell lines using weekly radiation and/or continuous treatment with increasing doses of chemotherapeutic agent 5-FU. We validated that the process of resistance acquisition correlates with enrichment in CSCs as revealed by higher ALDH1 expression, and increased proportion of ALDH1high cells and CD24high/CD44high cells in flow cytometry. We then used a proteomic approach to identify new players in treatment resistance. Results Interestingly, pathway analysis demonstrated enrichment in energy metabolism as well as amino acid metabolism. Seahorse assays showed a more quiescent metabolism in all three types of resistant cells compared to the control cell line. More precisely, resistant cell lines have a lower respiration rate than control cell line, while glycolysis remains unchanged. Surprisingly, our results show a metabolic rewiring very different from the well-known Warburg effect. To further characterise these metabolic changes, we performed an unbiased metabolomic pilot study and confirmed a decrease in amino acid levels such as proline, in resistant cell lines. Preliminary data show that when cultured in DMEM with proline addition, CD44high/CD24high cell proportion is decreased in control and RR cell lines suggesting that proline is a key regulator of CSC population in ESCC. Conclusions To conclude, our results suggest an important role of metabolism in ESCC treatment resistance. This study is a first step towards the identification of new targets to fight treatment resistance in ESCC patients. Funding Agencies CAG, CIHRCanada research chair TIER 2
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".