Targeting SLC1A5 and SLC3A2/SLC7A5 as a Potential Strategy to Strengthen Anti-Tumor Immunity in the Tumor Microenvironment
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Bibliographic record
Abstract
Cancer cells are metabolically vigorous and are superior in the uptake of nutrients and in the release of the tumor microenvironment (TME)-specific metabolites. They create an acidic, hypoxic, and nutrient-depleted TME that makes it difficult for the cytotoxic immune cells to adapt to the metabolically hostile environment. Since a robust metabolism in immune cells is required for optimal anti-tumor effector functions, the challenges caused by the TME result in severe defects in the invasion and destruction of the established tumors. There have been many recent developments in NK and T cell-mediated immunotherapy, such as engineering them to express chimeric antigen receptors (CARs) to enhance tumor-recognition and infiltration. However, to defeat the tumor and overcome the limitations of the TME, it is essential to fortify these novel therapies by improving the metabolism of the immune cells. One potential strategy to enhance the metabolic fitness of immune cells is to upregulate the expression of nutrient transporters, specifically glucose and amino acid transporters. In particular, the amino acid transporters SLC1A5 and SLC7A5 as well as the ancillary subunit SLC3A2, which are required for efficient uptake of glutamine and leucine respectively, could strengthen the metabolic capabilities and effector functions of tumor-directed CAR-NK and T cells. In addition to enabling the influx and efflux of essential amino acids through the plasma membrane and within subcellular compartments such as the lysosome and the mitochondria, accumulating evidence has demonstrated that the amino acid transporters participate in sensing amino acid levels and thereby activate mTORC1, a master metabolic regulator that promotes cell metabolism, and induce the expression of c-Myc, a transcription factor essential for cell growth and proliferation. In this review, we discuss the regulatory pathways of these amino acid transporters and how we can take advantage of these processes to strengthen immunotherapy against cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it