Gene expression profile of A549 cells from tissue of 4D model predicts poor prognosis in lung cancer patients

Dhruva K. Mishra, Chad J. Creighton, Yiqun Zhang, Don L. Gibbons, Jonathan M. Kurie, Min P. Kim

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

The tumor microenvironment plays an important role in regulating cell growth and metastasis. Recently, we developed an ex vivo lung cancer model (four dimensional, 4D) that forms perfusable tumor nodules on a lung matrix that mimics human lung cancer histopathology and protease secretion pattern. We compared the gene expression profile (Human OneArray v5 chip) of A549 cells, a human lung cancer cell line, grown in a petri dish (two-dimensional, 2D), and of the same cells grown in the matrix of our ex vivo model (4D). Furthermore, we obtained gene expression data of A549 cells grown in a petri dish (2D) and matrigel (three-dimensional, 3D) from a previous study and compared the 3D expression profile with that of 4D. Expression array analysis showed 2,954 genes differentially expressed between 2D and 4D. Gene ontology (GO) analysis showed upregulation of several genes associated with extracellular matrix, polarity and cell fate and development. Moreover, expression array analysis of 2D vs. 3D showed 1,006 genes that were most differentially expressed, with only 36 genes (4%) having similar expression patterns as observed between 2D and 4D. Finally, the differential gene expression signature of 4D cells (vs. 2D) correlated significantly with poor survival in patients with lung cancer (n = 1,492), while the expression signature of 3D vs. 2D correlated with better survival in lung cancer patients with lung cancer. As patients with larger tumors have a worse rate of survival, the ex vivo 4D model may be a good mimic of natural progression of tumor growth in lung cancer patients. What's new? This study aimed to investigate whether a previously-developed ex vivo lung cancer 4D model - which forms perfusable tumor nodules on a lung matrix that mimics human lung cancer histopathology and protease secretion pattern - is a better mimic of the natural history of lung cancer growth in patients. The authors found that the 4D model leads to change in gene expression in the human lung cancer A549 cell line that correlates with poor survival in patients. Since patients with larger tumors have a worse rate of survival, the 4D model may be a good mimic of natural progression of tumor growth.

Original languageEnglish (US)
Pages (from-to)789-798
Number of pages10
JournalInternational Journal of Cancer
Volume134
Issue number4
DOIs
StatePublished - Feb 15 2014

Keywords

  • Adenocarcinoma
  • Animals
  • Animals, Newborn
  • Biomarkers, Tumor
  • Blotting, Western
  • Carcinoma, Basal Cell
  • Cell Culture Techniques
  • Disease Models, Animal
  • Gene Expression Profiling
  • Humans
  • Immunoenzyme Techniques
  • Lung Neoplasms
  • Oligonucleotide Array Sequence Analysis
  • Prognosis
  • RNA, Messenger
  • Rats
  • Real-Time Polymerase Chain Reaction
  • Reverse Transcriptase Polymerase Chain Reaction
  • Survival Rate
  • Tumor Cells, Cultured

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

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