Abstract 3951: Unprecedented forward genetic screens reveal mechanisms of action, drug resistances, and hidden efficacies at amino acid resolution: combination of 5-ALA and Artesunate as a treatment option for glioblastoma multiforme
Bibliographic record
Abstract
Abstract Forward genetic screens have revolutionized the field of target discovery, target deconvolution, and target validation, particularly in the cancer field. However, most approaches are limited to the interrogation of non-essential factors and identify gene networks rather than direct target structures. Inspired from work in the nematode C. elegans, we perform forward genetic screens based on chemical mutagenesis. This approach randomly introduces single nucleotide variants into the entire genome resulting in cell populations which carry substitutions in statistically more than 90% of all amino acids. Challenging such mutagenized cell populations with a drug candidate of interest, followed by next generation sequencing and analysis, reveals drug resistance mechanism, direct drug target interactions, and potential concealed efficacies. The alteration of single amino acids thereby allows interrogation of non-essential as well as most essential factors and increases screening resolution to the amino acid level. From such screens we inferred and tested a novel treatment option for glioblastoma multiforme. The natural compound Artemisinin and its derivative Artesunate are widely used anti-malarial drugs. Based on theircytotoxic activity, they are also tested as anti-cancer therapies, while the definite mechanism of action and critical host cell targets have remained largely elusive. Using forward genetic screening approaches, we demonstrate that porphyrin biosynthesis governs Artemisinin’s cytotoxicity. Genetic or pharmacological modulation of porphyrin production is sufficient to alter Artemisinin cytotoxicity in multiple eukaryotic cells, including human cancer cells. Combining Artesunate with 5-ALA treatment we translated the screening results to clinically relevant model systems of brain tumor development, such as glioblastomas in engineered cerebral organoids, patient-derived brain tumor spheroids, and orthotopic xenograft models. 5-ALA is a clinically approved photodynamic porphyrin enhancer and surgical fluorescence marker, which specifically marks tumorigenic brain areas. With this additional level of selectivity, we demonstrate a strong antineoplastic effect of the 5-ALA-Artesunatecombination in all tested model systems. These findings extend to the triple combination with temozolomide and urgently await further testing in clinical setups. Citation Format: Michael Orthofer, Jasmin Taubenschmid-Stowers, Marianna Rozsova, Anna Laemmerer, Daniela Loetsch, Johannes Gojo, Andreas Peyrl, Walter Berger, Ullrich Elling, Moritz Horn, Josef M. Penninger. Unprecedented forward genetic screens reveal mechanisms of action, drug resistances, and hidden efficacies at amino acid resolution: combination of 5-ALA and Artesunate as a treatment option for glioblastoma multiforme. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3951.
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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) | 0.002 | 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".