ArticleJournal of the Egyptian National Cancer Institute2021
The integrative bioinformatic analysis deciphers the predicted molecular target gene and pathway from curcumin derivative CCA-1.1 against triple-negative breast cancer (TNBC).
Article in Journal of the Egyptian National Cancer Institute, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 12 citations in OpenAlex.
- Article
- Demystifying the Role of Prognostic Biomarkers in Breast Cancer through Integrated Transcriptome and Pathway Enrichment Analyses.Diagnostics (Basel, Switzerland) · 2023Article
- Identification of potential targets of the curcumin analog CCA-1.1 for glioblastoma treatment : integrated computational analysis and in vitro study.Scientific reports · 2022Article
- Chemoprevention curcumin analog 1.1 promotes metaphase arrest and enhances intracellular reactive oxygen species levels on TNBC MDA-MB-231 and HER2-positive HCC1954 cells.Research in pharmaceutical sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe poor outcomes from triple-negative breast cancer (TNBC) therapy are mainly because of TNBC cells' heterogeneity, and chemotherapy is the current approach in TNBC treatment. A previous study reported that CCA-1.1, the alcohol-derivative from monocarbonyl PGV-1, exhibits anticancer activities against several cancer cells, as well as in TNBC. This time, we utilized an integrative bioinformatics approach to identify potential biomarkers and molecular mechanisms of CCA-1.1 in inhibiting proliferation in TNBC cells.
methodsGenomics data expression were collected through UALCAN, derived initially from TCGA-BRCA data, and selected for TNBC-only cases. We predict CCA-1.1 potential targets using SMILES-based similarity functions across six public web tools (BindingDB, DINIES, Swiss Target Prediction, Polypharmacology browser/PPB, Similarity Ensemble Approach/SEA, and TargetNet). The overlapping genes between the CCA-1.1 target and TNBC (CPTGs) were selected and used in further assessment. Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) network analysis were generated in WebGestalt. The protein-protein interaction (PPI) network was established in STRING-DB, and then the hub-genes were defined through Cytoscape. The hub-gene's survival analysis was processed via CTGS web tools using TCGA database.
resultsKEGG pathway analysis pointed to cell cycle process which enriched in CCA-1.1 potential targets. We also identified nine CPTGs that are responsible in mitosis, including AURKB, PLK1, CDK1, TPX2, AURKA, KIF11, CDC7, CHEK1, and CDC25B.
conclusionWe suggested CCA-1.1 possibly regulated cell cycle process during mitosis, which led to cell death. These findings needed to be investigated through experimental studies to reinforce scientific data of CCA-1.1 therapy against TNBC.
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.