Related Experiment Video
Updated: Jun 4, 2026
A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Expression-based in silico screening of candidate therapeutic compounds for lung adenocarcinoma
Guiping Wang1, Yun Ye, Xiaoqin Yang
1Bioinformatics Group, Institute of Genetic Engineering, Southern Medical University, Guangzhou, People's Republic of China.
Background:
Lung adenocarcinom (AC) is the most common form of lung cancer. Currently, the number of medical options to deal with lung cancer is very limited. In this study, we aimed to investigate potential therapeutic compounds for lung adenocarcinoma based on integrative analysis.
Methodology/Principal Findings:
The candidate therapeutic compounds were identified in a two-step process. First, a meta-analysis of two published microarray data was conducted to obtain a list of 343 differentially expressed genes specific to lung AC. In the next step, expression profiles of these genes were used to query the Connectivity-Map (C-MAP) database to identify a list of compounds whose treatment reverse expression direction in various cancer cells. Several compounds in the categories of HSP90 inhibitor, HDAC inhibitor, PPAR agonist, PI3K inhibitor, passed our screening to be the leading candidates. On top of the list, three HSP90 inhibitors, i.e. 17-AAG (also known as tanespimycin), monorden, and alvespimycin, showed significant negative enrichment scores. Cytotoxicity as well as effects on cell cycle regulation and apoptosis were evaluated experimentally in lung adenocarcinoma cell line (A549 or GLC-82) with or without treatment with 17-AAG. In vitro study demonstrated that 17-AAG alone or in combination with cisplatin (DDP) can significantly inhibit lung adenocarcinoma cell growth by inducing cell cycle arrest and apoptosis.
Conclusions/Significance:
We have used an in silico screening to identify compounds for treating lung cancer. One such compound 17-AAG demonstrated its anti-lung AC activity by inhibiting cell growth and promoting apoptosis and cell cycle arrest.
Insights
This study identified 17-AAG as a potential therapeutic for lung adenocarcinoma (AC). It effectively inhibits cancer cell growth by inducing apoptosis and cell cycle arrest, offering new hope for AC treatment.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Lung adenocarcinoma (AC) is the most prevalent form of lung cancer.
- Limited therapeutic options currently exist for treating lung cancer.
- Investigating novel therapeutic compounds for AC is crucial.
Purpose of the Study:
- To identify potential therapeutic compounds for lung adenocarcinoma (AC) using an integrative analysis approach.
- To screen for compounds that can reverse gene expression patterns specific to lung AC.
- To validate the efficacy of identified compounds in preclinical models.
Main Methods:
- Performed a meta-analysis of microarray data to identify differentially expressed genes in lung AC.
- Utilized the Connectivity-Map (C-MAP) database to screen for compounds reversing these gene expression profiles.
- Conducted in vitro experiments to evaluate the effects of candidate compounds on lung adenocarcinoma cell lines.
Main Results:
- Identified several classes of compounds, including HSP90 inhibitors, as potential candidates.
- Three HSP90 inhibitors (17-AAG, monorden, alvespimycin) showed significant negative enrichment scores.
- 17-AAG demonstrated significant inhibition of lung adenocarcinoma cell growth, induced cell cycle arrest, and promoted apoptosis, both alone and with cisplatin.
Conclusions:
- An in silico screening approach successfully identified potential therapeutic compounds for lung cancer.
- The compound 17-AAG exhibits significant anti-lung AC activity.
- 17-AAG's mechanism involves inhibiting cell growth, promoting apoptosis, and inducing cell cycle arrest in lung adenocarcinoma.
