Transcriptional Profiling Identifies Gene Expression Changes Associated with IFN-α Tolerance in Hepatitis C–Related Hepatocellular Carcinoma Cells
Bibliographic record
Abstract
Abstract Purpose: Treatment with IFN-α therapy has been shown to exhibit antitumor effects on patients with hepatocellular carcinoma (HCC). However, individual responses remained unpredictable because of the frequent presence of intrinsic or acquired IFN-α resistance. Hence, delineation of molecular targets implicated in the resistant pathway holds value in refining the therapeutic benefits of IFN-α. Experimental Design: The current study analyzed the effect of IFN-α in human HCC cells. Three hepatitis C virus (HCV)–related, five hepatitis B virus (HBV)–related and two non-B non-C–related cell lines were subjected to IFN-α treatment and the cytotoxic effect on cell viability was measured. Further analysis by cDNA microarray and quantitative reverse transcription-PCR were conducted to examine the gene expression changes that mediated the IFN-α resistance observed. Results: According to the IC50 values determined, HCV-related cell lines indicated distinct resistance (IC50, 389-1468 units/mL) compared with the HBV-related (IC50, 11-77 units/mL) and non-B non-C–related cell lines (IC50, 24-108 units/mL). Unsupervised hierarchical clustering on array data indicated three HCV-related cell lines to cluster independently from the sensitive cell lines, suggesting discrete features in association with IFN-α tolerance. Moreover, Significance Analysis of Microarrays analysis indicated the differential expression of 149 expressed sequence tags that represented 51 up-regulated and 98 down-regulated genes in the resistant cell lines. Comparing the temporal pattern of gene expression between 6- and 24-hour treatments, candidate genes that were considerably induced with time were further highlighted in the tolerant HCV-related cell lines. These candidates were verified by quantitative reverse transcription-PCR, which confirmed the down-regulation of UBA2, ZNF185, and FOXF1 and up-regulation of UBE4B in the drug-tolerant cells. Conclusions: Our present study showed that the insensitivity to IFN-α therapy in HCC cells is associated with drug-inducible transcriptional alterations. Furthermore, our investigation highlighted potential candidate genes in conferring an anti-apoptotic effect toward IFN-α treatment.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".