Genetic screen identifies suppressor of morphogenesis in genitalia-1 (SMG-1) as a modulator of sorafenib resistance in hepatocellular carcinoma cell lines
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is an aggressive malignancy with a poor prognosis and a very complex dysregulated molecular etiology. Furthermore, conventional therapy thus far has had only limited success. A recently developed oral multikinase inhibitor, sorafenib, has been used to improve survival in HCC patients, however, follow‑up studies have revealed a high rate of cancer recurrence. Therefore, identification of genes involved in sorafenib resistance is urgently required. RNA interference (RNAi) is a powerful tool for performing loss-of-function genetic screens and can facilitate the identification of components of the cellular signaling pathway. This study describes the results of an unbiased genomic screening using RNAi in an HCC cell line to elucidate genes related to sorafenib non-responsiveness or resistance. A genome-wide in vitro RNA interference screen revealed the role of suppressor of morphogenesis in genitalia-1 (SMG-1) as a determinant of sorafenib resistance. The inhibition of SMG-1 reduced sorafenib sensitivity in the studied HCC cell lines. An immunohistochemical comparison of cancerous and non‑cancerous regions showed strong staining in the non‑neoplastic hepatocyte regions of HCC. SMG-1 may warrant investigation as an agent to reverse sorafenib resistance.
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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) | 0.000 | 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) | 0.000 | 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".