ATRT-09. IDENTIFICATION OF POTENTIAL GENETIC DRIVERS OF METHOTREXATE (MTX) RESISTANCE IN ATYPICAL TERATOID RHABDOID TUMOURS (ATRT) THROUGH A GENOME-WIDE RNAI SCREEN
Bibliographic record
Abstract
Abstract ATRT of the CNS constitute a group of rare and aggressive early childhood tumors with poor prognosis. While there are differing chemotherapeutic regimens for ATRT, high-dose MTX is a crucial component of many therapeutic protocols. Currently, the biological mechanisms contributing to the generation of MTX resistance in ATRT are unknown. To identify genes involved in MTX resistance in ATRT, an unbiased genome-wide RNAi screen on ATRT cell lines was conducted using 24,000 distinct shRNAs covering 8,000 genes. ATRT cells were transfected with a retrovirus containing pRS-shRNA vectors and treated with puromycin for selection. The resulting cells were treated with MTX to identify resistant clones and resistant colonies were then isolated and amplified individually. Presence of shRNA inserts in each colony was determined by PCR using pRS forward and reverse primers. PCR products within each of the three resistant colonies were sequenced, leading to the identification of three distinct genes, TGIF1, HIF3A and PGAM2, as potential indicators of resistance. Western blotting verified depletion of these proteins in their respective colonies. Proliferation assays were then conducted on cells from each resistant colony alongside control cells to confirm that the identified drivers conferred resistance. Sensitivity to MTX was significantly lower in TGIF1-depleted (IC50=212±8.48nM, n=3), HIF3A-depleted (IC50=52±4.68nM, n=3) and PGAM2-depleted (IC50=41±4.13nM, n=3) cells compared to control cells (IC50=19±2.87nM, n=3), (p<0.001). In addition, more than 60% of TGIF1, HIF3A, and PGAM2-depleted cells survived the maximum MTX treatment (100nM), while less than 20% of control cells survived this treatment. Our study using an unbiased genome-wide RNAi screen approach has shown that depletion of TGIF1, HIF3A and PGAM2 are potential molecular markers of MTX resistance in ATRT. Screening for their occurrence may help to identify patients at high risk of MTX resistance and may also serve as targets for future novel therapeutics development.
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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 | 0.000 | 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) | 0.003 | 0.001 |
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".