Abstract 4339: Glucosinolates selectively target cancer cell types and exhibit antineoplastic effects
Bibliographic record
Abstract
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.
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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) | 0.005 | 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".