Abstract 1815: Optimization of Lin28 inhibitors: A promising therapeutic approach for the suppression of cancer cell proliferation, stemness properties, and spheroid growth
Bibliographic record
Abstract
Abstract Background: The pluripotency factor known as Lin28 plays a crucial role in the regulation of cancer cell stem-like characteristics, hence facilitating the formation of cancer and the evolution of therapy-resistant tumors. The protein exerts its function by utilizing its cold shock domain and zinc knuckle domain (ZKD) to engage with the Let-7 pre-microRNA and impede the process of Let-7 production. The implementation of chemical agents to hinder the interaction between Lin28 and Let-7 has been proven as a therapeutic approach for treating aggressive tumors. Methods: Computer-aided drug design techniques were employed in the development of a novel series of small molecule inhibitors, which are derivatives of our previously identified lead compounds Ln115, Ln15, and Ln7. Fluorescent Polarization Assay (FP), and Electrophoretic Mobility Shift Assay (EMSA) were used to screen the chemicals as Lin28-Let7 interaction disruptors using Lin28A/B ZKD domain. To further screen the chemicals, the Incucyte cell proliferation assay was performed using two Lin28A and Lin28B positive cells, IGROV-1, and DuNE cells, respectively. The inhibition of Lin28 activity was subsequently evaluated by measuring Let-7 micro-RNA and Lin28 protein levels using RT-PCR and Western Blot. Then, the metabolism profile was explored using Microsomal Stability Assay. Incucyte proliferation assay and MTS assay determined the IC50 of lead compound in Lin28 positive cells. The anti-stemness properties of the lead compound were subsequently evaluated through assays for stem gene expression levels and colony formation. To evaluate the potential of the lead compound to further move into animal studies, we tested it on a newly developed 3D Neuroendocrine Prostate Cancer (NEPC) model. Results: In this study, we provide a novel set of derivatives, within which, Ln268 was chosen as the lead compound. Ln268 shows higher metabolic stability with a half-life time of 462 min and clearance rate of 5 ul/min/mg, compared to its father compound at 347 min and 46 ul/min/mg, respectively. Ln268 treatment resulted in a time-dependent inhibition of cell growth with an IC50 of 2.5 uM at 72 hrs. Ln268 reduces mRNA levels of stemness and neurodifferentiation markers such as CHGA, CHG, SYP, SCGN, OCT3/4, NANOG, ID4, FOXC1, ALDH1A2, and FOXO3. In the 3D NEPC model, Ln268 suppresses spheroid growth in a dose- and time-dependent manner. Ln268 achieved 100% spheroid growth inhibition at the concentration of 100 uM, while the current commercially available C1632 only reached 50%. Conclusion: We discovered a novel Ln15 derivative named Ln268, which has a better metabolism profile and increased inhibitory activity to distrust Lin28-Let7 interaction and cancer cell proliferation. Ln268 has the potential to be improved and used as an anti-cancer treatment for a variety of malignancies, such as prostate cancer. Citation Format: Victor M. Matias-Barrios, Mariia Radaeva, Graciella Rosellinny, Artem Cherkasov, Xuesen Dong. Optimization of Lin28 inhibitors: A promising therapeutic approach for the suppression of cancer cell proliferation, stemness properties, and spheroid growth [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1815.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".