Abstract 4339: Glucosinolates selectively target cancer cell types and exhibit antineoplastic effects
Notice bibliographique
Résumé
Abstract Introduction: Glucosinolates are organic compounds found in high concentrations within cruciferous vegetables. Plant tissue damage initiates the release of myrosinase, which breaks down glucosinolates into the biologically active compounds indole-3-carbinol (I3C) and sulforaphane. In vitro studies have suggested that I3C and sulforaphane can mitigate cancer progression via hormone regulation and antioxidant mechanisms, respectively. However, there has yet to be a systematic analysis of these two glucosinolates against a wide range of human cancer cell lines. We hypothesized that I3C would differentially affect cancer cell growth depending on cell line of origin, and that sulforaphane would induce a genetic signature similar to compounds and genetic perturbations with anticancer properties. Methods: Cell survival data was obtained from the NCI-60 human tumor cell lines screen. 59 tumor cell lines were seeded into 96-well microtiter plates. 100 µL of 5 different I3C 10-fold dilutions (0.01 - 100 µM) were added to the wells and incubated for 48 hours. After staining with sulforhodamine, absorbance was measured, and percent growth was calculated relative to the no-drug control and number of cells at baseline. Genetic profiling data was obtained from the Broad Institute’s L1000 assay. Sulforaphane was added to 9 cell lines in 384-well plates. mRNA was extracted and expression levels of 978 landmark genes were measured. This provided a transcriptomic signature that was compared to signatures from other compounds and genetic perturbations. A Connectivity Score was then developed to measure the similarity of each signature to the one induced by sulforaphane. Results: I3C was most potent in the KM12 cell line (IC50 = 14.9 µM; colon cancer) where it inhibited ∼90% of growth at a 100 µM concentration. Cancers of the colon and skin were most sensitive to I3C (median IC50 values of 28.3 µM and 36.1 µM, respectively), while breast and myeloid tissue cancers were least sensitive. Gene expression induced by sulforaphane was most similar to that induced by isoliquiritigenin, a flavonoid compound that exhibits antiproliferative and anti-inflammatory effects. Transcriptomic changes caused by sulforaphane were highly similar to NFE2L2 overexpression (tau score = +97.87), and SLC7A5 knockdown (tau score = +97.16). The NFE2L2 gene encodes a transcription factor (NRF2) that regulates antioxidant enzymes, and the SLC7A5 gene encodes an amino acid transporter that is often overexpressed in many cancer types. Conclusion: Glucosinolates, specifically I3C and sulforaphane, demonstrate anticancer properties by inducing cell survival and gene expression changes in several cancer cell lines. In the future, identifying the genes and proteins targeted by I3C, as well as the pathway through which sulforaphane acts, will be crucial to further elucidate the effects of glucosinolates on cancer. Citation Format: Katerina Carrozzi, Adin Aggarwal, Kenneth W. Yip. Glucosinolates selectively target cancer cell types and exhibit antineoplastic effects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4339.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».