Abstract 1576: Molecular targeting of histone deacetylase 2 for treatment of human hepatocellular carcinoma
Bibliographic record
Abstract
Abstract Development of targeted therapeutics for hepatocellular carcinoma (HCC) remains a major challenge. We have recently identified an elevated expression of histone deacetylase 2 (HDAC2) in primary human hepatocellular carcinoma (HCC) and HCC derived cell lines. In this study, we have tested if the downregulation of HDAC2 by siRNA can affect the course of HCC progression in vitro and in vivo. To inactivate HDAC2 gene expression, three HDAC2-specific siRNAs (HDAC2-1, HDAC2-2 and HDAC2-3) were designed and tested for growth inhibition in Huh7 and HepG2 HCC cell lines as determined by MTT assay, FACS analysis and microscopy. To obtain insights into molecular changes caused by HDAC2 silencing, global changes in gene expression were examined by illumina microarray. For in vivo evaluation of HDAC2 as a therapeutic target, we employed orthotopic xenograft model using luciferase-expressing HCC reporter cell line Huh7-luc+ and stable-nucleic-acid-lipid-particle (SNALP) as an optimal carrier of siRNA into liver. The HDAC2-1siRNA was the most effective in inhibiting Huh7 and HepG2 cell growth (68% and 71%, respectively) which was paralleled by a similar decrease in the levels of target mRNA and protein. HDAC2-deficient cells also exhibited a 1.9-fold increase in apoptosis through activation of caspase-3. The comparison of gene expression profiles in HepG2 cells treated with either control siRNA or HDAC2-1siRNA identified 299 differentially expressed genes. Consistent with in vitro observations, genes functionally involved in apoptosis, such as CDKN1A, SOCS2, TP53I3, and BTG2, were up-regulated while genes associated with cellular metabolic process (e.g. HOXD1, PAK2, SMAD9, CDK4, PCK2 and SKP2) were down-regulated. HDAC2 3/7siRNA, a chemically modified variant of HDAC2-1siRNA displaying a minimal induction of IL-6 in murine Flt3L dendricite cultures, was selected for in vivo treatment of Huh7-luc+-derived HCC. Administration of SNALP- HDAC2 3/7siRNA effectively suppressed xenograft growth as compared to the SNALP-control siRNA treatment. Taken together, these results indicate that HDAC2 is an important regulator of HCC cell growth and survival, and may be an attractive target for systemic therapy of HCC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1576.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.003 | 0.002 |
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".