Transcriptional profiling of mesothelioma using microarrays

Our plain-English summary of Transcriptional profiling of mesothelioma using microarrays, by G.J. Gordon (Lung Cancer, 2005).

The study

• Author: G.J. Gordon
• Journal: Lung Cancer
• Published: 2005;49 Suppl 1:S99-S103
• Type of article: Review
• Cited by: 16 articles, as counted by NIH iCite
• Read it: PubMed · Publisher

Abstract

Mesothelioma is an asbestos-related neoplasm of the thoracic pleura about which little is known and for which effective therapy is lacking. Large-scale transcriptional profiling using microarrays is frequently a part of studies to explore gene expression patterns in cancer and other diseases. In general, microarray based experiments can facilitate the identification of tumor molecular markers, provide clues relating to mechanisms carcinogenesis, as well as aid in the discovery of candidate targets for therapy. Relatively few studies of this sort have been attempted for mesothelioma, likely due to its relatively rare incidence and by extension the difficulty in acquiring suitable tissues for analysis. Microarray analysis of mesothelioma will likely lead to a better understanding of a highly lethal malignancy and result in the identification of potential therapeutic targets to ultimately affect better treatment options and patient clinical outcome. This mini-review will address general issues pertaining to all expression profiling experiments (e.g., data interpretation) and summarize similar studies that have been attempted for mesothelioma.

In plain English

This article was a mini-review, not a new study. It explained how microarrays, which measure the activity of thousands of genes at once, have been used to study malignant pleural mesothelioma. It summarized the few published studies, most of which used small numbers of tissues or cell lines. The author described technical pitfalls: with 12,000 genes and a cut-off of P = 0.05, up to 600 genes could be falsely called significant. The studies reviewed included work on rat mesothelial cells exposed to asbestos (fiber type not stated), a study of 16 human tumors, and a study that used 21 tumors to build a 27-gene classifier that predicted clinical outcome with moderate accuracy. The author's laboratory used 31 tumors to develop and validate diagnostic and prognostic tests, then profiled 40 more to study molecular pathways and further validate prognostic tests. The author cautioned that cell lines and real tumors can differ and that there is no accepted normal control tissue. The author concluded that these studies will drive gene discovery and likely positively impact patient survival.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: narrative mini-review of published microarray gene expression studies in mesothelioma
• Who was studied: Published microarray studies of malignant pleural mesothelioma (MPM), using mesothelioma cell lines, small numbers of human tumor specimens, normal pleura, and rat mesothelial cells. Most used small numbers of tissues or cell lines.
• Exposure: Not an exposure study. One reviewed study (Ramos-Nino and colleagues) exposed rat mesothelial cells to asbestos; the fiber type is not stated in this article.
• Main results:
  • Technical point made by the author: using 12,000-gene microarrays with a significance cut-off of P = 0.05 could theoretically produce up to 600 genes falsely called statistically significant.
  • Reviewed study (Ramos-Nino and colleagues, rat model): when the gene fra-1 was switched off, mRNA levels of CD44 and c-met were substantially lower in the knockdown cell lines.
  • Reviewed study (Singhal and colleagues): 16 MPM patient tumors and four normal pleura tissues were profiled.
  • Reviewed study (Pass and colleagues, 21 MPM patient tumors): a 27-gene neural network classifier predicted clinical outcome with moderate accuracy.
  • The author's laboratory profiled 31 MPM tumors to develop and validate diagnostic and prognostic genomics-based tests for MPM using a relatively small number of genes.
  • In later work, the author's laboratory profiled an additional 40 independent MPM tumors, plus normal lung and pleural tissues (n = 9) and cell lines (n = 5), to better characterize molecular pathways in MPM and to further validate prognostic genes and tests.
  • Cell lines and tumors could disagree: in the author's laboratory, c-fos mRNA levels were relatively low or absent in human MPM cell lines but highly expressed in human MPM specimens.
• The authors' conclusion: The author concluded that microarray expression profiling studies will drive gene discovery and likely positively impact patient survival by identifying molecular markers, pathways and potential therapy targets in MPM.
• Limitations the authors state:
  • The author noted that microarrays remain susceptible to technical issues that can cause excessive variability and a lack of reproducibility.
  • The author noted inherent differences between species, and between cell lines and actual tumor specimens.
  • The author noted that there is no standard, universally accepted normal control tissue or cell line for MPM.
  • The author described the cell-line studies as purely descriptive.

Topics

The National Library of Medicine indexes this study under subjects our site covers: Mesothelioma.

Medical terms in this study, explained in our Lexicon: Mesothelioma, Neoplasm, Pleura, Carcinogenesis, Discovery.

Related studies

• Identification of novel candidate oncogenes and tumor suppressors in malignant pleural mesothelioma using large-scale transcriptional profiling — G.J. Gordon, G.N. Rockwell, et al. (2005)
• CDKN2A, NF2, and JUN are dysregulated among other genes by miRNAs in malignant mesothelioma -A miRNA microarray analysis — M. Guled, L. Lahti, et al. (2009)
• Expression profiling stratifies mesothelioma tumors and signifies deregulation of spindle checkpoint pathway and microtubule network with therapeutic implications — M.B. Suraokar, M.I. Nunez, et al. (2014)
• Differential microRNA expression profiling of mesothelioma and expression analysis of miR-1 and miR-214 in mesothelioma — V.J. Amatya, A.S. Mawas, et al. (2016)
• Gene expression profiling and gene copy-number changes in malignant mesothelioma cell lines — C. Zanazzi, R. Hersmus, et al. (2007)
• Cell protection, resistance and invasiveness of two malignant mesotheliomas as assessed by 10K-microarray — S. Mohr, G. Keith, et al. (2004)

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