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Lipid MALDI profile classifies non-small cell lung cancers according to the histologic type

  • Geon Kook Lee
  • , Hee Seok Lee
  • , Young Seung Park
  • , Jeong Hwa Lee
  • , Seok Cheol Lee
  • , Jong Ho Lee
  • , Soo Jae Lee
  • , Selina Rahman Shanta
  • , Hye Min Park
  • , Hyo Rim Kim
  • , In Hoo Kim
  • , Young Hwan Kim
  • , Jae Ill Zo
  • , Kwang Pyo Kim
  • , Hark Kyun Kim

Research output: Contribution to journalArticlepeer-review

92 Citations (Scopus)

Abstract

We investigated whether direct tissue matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) analysis on lipid may assist with the histopathologic diagnosis of non-small cell lung cancers (NSCLCs). Twenty-one pairs of frozen, resected NSCLCs and adjacent normal tissue samples were initially analyzed using histology-directed, MALDI MS. 2,5-dihydroxybenzoic acid/α-cyano-4-hydroxycinnamic acid were manually deposited on areas of each tissue section enriched in epithelial cells to identify lipid profiles, and mass spectra were acquired using a MALDI-time of flight instrument. A lipid profile that could differentiate cancer and adjacent normal samples with a median accuracy of 92.9% was discovered. Several phospholipids including phosphatidylcholines (PC) {34:1} were overexpressed in lung cancer.Squamous cell carcinomas and adenocarcinomas were found to have different lipid profiles. Discriminatory lipids correctly classified the histology of 80.4% of independent NSCLC surgical tissue samples (41 out of 51) in validation set. MALDI MS image of 11 discriminatory lipids validated their differential expression according to the histologic type in cancer cells of bronchoscopic biopsy samples. PC {32:0} [M+Na]+ (m/z 756.68) and ST-OH {42:1} [M-H]- (m/z 906.89) were overexpressed in adenocarcinomas. Thus, lipid profiles accurately distinguish tumor from adjacent normal tissue and classify non-small cell lung cancers according to the histologic type.

Original languageEnglish
Pages (from-to)197-203
Number of pages7
JournalLung Cancer
Volume76
Issue number2
DOIs
Publication statusPublished - May 2012

Bibliographical note

Funding Information:
The authors thank Dr. Byung Ho Nam for help with statistical analysis. The work was supported by Converging Research Center Program through the Ministry of Education, Science and Technology of Korea (2011K000888).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Histologic type
  • Histology-directed MALDI
  • Lipid
  • Lung cancer
  • Phosphatidylcholine

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