Gene expression profiling of non-small-cell lung cancer
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Updated: Jul 6, 2026
Exosomal miRNA Analysis in Non-small Cell Lung Cancer (NSCLC) Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
Published on: May 27, 2016
Ludovic Lacroix1, Frédéric Commo, Jean-Charles Soria
1Institut de Cancérologie Gustave Roussy, Translational Research Laboratory, 39 rue Camille Desmoulins, 94805 Villejuif Cedex, France. ludovic.lacroix@igr.fr
Abstract:
Lung cancer is the leading cause of cancer worldwide. Despite recent advances in the management of resected lung cancer tumors (i.e., the use of adjuvant therapy) and more effective treatments in the metastatic setting (i.e., molecular targeted agents), the cure rate of lung cancer remains low. Successful molecular testing of lung cancer requires the identification and understanding of events that take place during the multistep tumorigenic process of lung cancer. As with other solid tumors, lung cancer is the result of the accumulation of genetic and epigenetic alterations over a long course of exposure to a carcinogen, such as tobacco smoke. Discovering new prognostic or predictive biomarkers or developing new detection tools for lung cancer is one of the major areas of translational cancer research. However, given our current understanding of the multifactorial process of lung carcinogenesis and the heterogeneous nature of the disease, monitoring of one or a few genes is limited. A pangenomic analysis seems more efficient for deciphering the complexity of lung cancer. The prospect of identifying specific events in lung carcinogenesis is significantly brightened by the recent development of high-throughput gene expression analysis. Since 2000, several studies have reported on the molecular classification of human lung carcinomas on the basis of gene expression and have described numerous putative biological markers of cancer. At this time, improving the biological significance of microarray data appears to be an important challenge. The most recent studies propose refining molecular classification of non-small-cell lung cancer on the basis of mRNA expression profiles. Other studies described new prognostic biomarkers that will be useful for the therapeutic management of patient's bearing lung cancer (non-small-cell lung cancer). The present review summarizes the main recent advances associated with gene expression analysis in the field of lung cancer and, notably, non-small-cell lung tumors.
Insights
Lung cancer remains a leading cause of death globally. Advances in gene expression analysis offer new ways to understand lung cancer complexity and identify biomarkers for better patient treatment.
Area of Science:
- Oncology
- Genomics
- Translational Cancer Research
Background:
- Lung cancer is the leading global cause of cancer mortality.
- Despite advances in adjuvant therapy and molecular targeted agents, cure rates remain low.
- Understanding the genetic and epigenetic alterations in lung carcinogenesis is crucial.
Purpose of the Study:
- To review recent advances in gene expression analysis for lung cancer.
- To highlight the importance of pangenomic analysis for deciphering lung cancer complexity.
- To discuss the refinement of molecular classification and identification of prognostic biomarkers.
Main Methods:
- Review of studies reporting molecular classification of human lung carcinomas based on gene expression since 2000.
- Analysis of high-throughput gene expression data, including mRNA expression profiles.
- Examination of research focused on identifying new prognostic and predictive biomarkers.
Main Results:
- Gene expression analysis has enabled molecular classification of lung carcinomas.
- Numerous putative biological markers for lung cancer have been identified.
- Recent studies focus on refining molecular classification of non-small-cell lung cancer (NSCLC) using mRNA profiles.
Conclusions:
- Pangenomic analysis, particularly gene expression profiling, is essential for understanding lung cancer.
- Improved molecular classification and biomarker discovery are key to advancing lung cancer treatment.
- Gene expression analysis holds significant promise for improving therapeutic management of lung cancer patients, especially in non-small-cell lung tumors.
