The Transcriptome of BT-20 Breast Cancer Cells Exposed to Curcumin Analog NC2603 Reveals a Relationship between EGR3 Gene Modulation and Cell Migration Inhibition
Bibliographic record
Abstract
Breast cancer represents a critical global health issue, accounting for a substantial portion of cancer-related deaths worldwide. Metastasis, the spread of cancer cells to distant organs, is the primary cause of approximately 90% of breast cancer-related fatalities. Despite advances in cancer treatment, conventional chemotherapeutic drugs often encounter resistance and demonstrate limited efficacy against metastasis. Natural products have emerged as promising sources for innovative cancer therapies, with curcumin being one such example. However, despite its therapeutic potential, curcumin exhibits several limitations. Analogous compounds possessing enhanced bioavailability, potency, or specificity offer a promising avenue for overcoming these challenges and demonstrate potent anti-tumor activities. Our study investigates the antimetastatic potential of the curcumin analog NC2603 in breast cancer cells, utilizing BT-20 cells known for their migratory properties. Cell viability assessments were performed using the MTT reduction method, while migration inhibition was evaluated through scratch and Transwell migration assays. Transcriptome analysis via next-generation sequencing was employed to elucidate gene modulation and compound mechanisms, with subsequent validation using RT-qPCR. The IC50 of NC2603 was determined to be 3.5 μM, indicating potent inhibition of cell viability, and it exhibited greater specificity for BT-20 cells compared with non-cancerous HaCaT cells, surpassing the efficacy of doxorubicin. Notably, NC2603 demonstrated superior inhibition of cell migration in both scratch and Transwell assays compared with curcumin. Transcriptome analysis identified 10,620 modulated genes. We validated the expression of six: EGR3, ATF3, EMP1, SOCS3, ZFP36, and GADD45B, due to their association with migration inhibition properties. We hypothesize that the curcumin analog induces EGR3 expression, which subsequently triggers the expression of ATF3, EMP1, SOCS3, ZFP36, and GADD45B. In summary, this study significantly advances our comprehension of the intricate molecular pathways involved in cancer metastasis, while also examining the mechanisms of analog NC2603 and underscoring its considerable potential as a promising candidate for adjuvant therapy.
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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) | 0.001 | 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".