Dual Targeting of Sorafenib-Resistant HCC-Derived Cancer Stem Cells
Bibliographic record
Abstract
Sorafenib, an oral multi-tyrosine kinase inhibitor, has been the first-line therapy for the treatment of patients with advanced HCC, providing a survival benefit of only three months in approximately 30% of patients. Cancer stem cells (CSCs) are a rare tumour subpopulation with self-renewal and differentiation capabilities, and have been implicated in tumour growth, recurrence and drug resistance. The process of epithelial-to-mesenchymal transition (EMT) contributes to the generation and maintenance of the CSC population, resulting in immune evasion and therapy resistance in several cancers, including HCC. The aim of this study is to target the chemoresistant CSC population in HCC by assessing the effectiveness of a combination treatment approach with Sorafenib, an EMT inhibitor and an immune checkpoint inhibitor (ICI). A stem-cell-conditioned serum-free medium was utilised to enrich the CSC population from the human HCC cell lines Hep3B, PLC/PRF/5 and HepG2. The anchorage independent spheres were characterised for CSC features. The human HCC-derived spheres were assessed for EMT status and expression of immune checkpoint molecules. The effect of combination treatment with SB431542, an EMT inhibitor, and siRNA-mediated knockdown of programmed cell death protein ligand-1 (PD-L1) or CD73 along with Sorafenib on human HCC-derived CSCs was examined with cell viability and apoptosis assays. The three-dimensional spheres enriched from human HCC cell lines demonstrated CSC-like features. The human HCC-derived CSCs also exhibited the EMT phenotype along with the upregulation of immune checkpoint molecules. The combined treatment with SB431542 and siRNA-mediated PD-L1 or CD73 knockdown effectively enhanced the cytotoxicity of Sorafenib against the CSC population compared to Sorafenib alone, as evidenced by the reduced size and proliferation of spheres. Furthermore, the combination treatment of Sorafenib with SB431542 and PD-L1 or CD73 siRNA resulted in an increased proportion of an apoptotic population, as evidenced by flow cytometry analysis. In conclusion, the combined targeting of EMT and immune checkpoint molecules with Sorafenib can effectively target the CSC tumour subpopulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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 teacher head, 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".