ArticleJournal of cancer research and clinical oncology2009
Comparative proteomics and molecular mechanical analysis in CDA-II induced therapy of LCI-D20 hepatocellular carcinoma model.
Article in Journal of cancer research and clinical oncology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Article
- Construction and experimental verification of user-friendly molecular subtypes mediated by immune-associated genes in hepatocellular carcinoma.Frontiers in oncology · 2022Article
- Predictive proteomic biomarkers for inflammatory bowel disease-associated cancer: where are we now in the era of the next generation proteomics?World journal of gastroenterology · 2014Review
- Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance.Molecular & cellular proteomics : MCP · 2013Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo investigate the differential proteins and related molecular mechanism of CDA-II (cell differentiation agent-II) induced therapy on a human hepatocellular carcinoma model in nude mice with high metastatic potential (LCI-D20).
methodsAfter tumors were transplanted 11 days, mice were intraperitoneally injected with CDA-II (1,800 mg/kg) for 20 days continuously. The tumor growth-inhibitory efficiency in CDA-II treated groups was calculated. Proteins extracted from tumor tissue were separated by two-dimensional gel electrophoresis (2DE) and the differential proteins were identified by matrix assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS). Western blotting (WB) was performed to verify the expression of certain candidate proteins. Reverse transcription-polymerase chain reaction (RT-PCR) was engaged to study the molecular mechanism of the therapy.
resultsCDA-II suppressed the growth and metastasis of tumor. The tumor growth-inhibitory efficiency was 41.8%. In total, 27 differentially expressed proteins were identified, including HSP27, UGDH, CK8, Hsp60, ENOA and AnxA5, with functions involved in oncogene expression and/or cell differentiation. In addition, apparent alternations of HSP60 and beta-actin expression levels and their different posttranslational modifications (PTMs) were investigated. RT-PCR analysis confirmed that the cancer related genes c-myc, N-ras and MMP-9 were significantly down-regulated.
conclusionOur results demonstrate that CDA-II presence can change the proteome profiling and favors of the tumor suppression in LCI-D20 cell differentiation. Our results also suggest that the dynamic PTM of HSP60 expression levels could be used to predict HCC and might be a promising and useful biomarker to prognosticate CDA-II therapeutic efficacy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.