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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Oncol. | doi: 10.3389/fonc.2019.00804

Accurate classification of non-small cell lung cancer (NSCLC) pathology and mapping of EGFR mutation spatial distribution by ambient mass spectrometry imaging

 Min Zhang1, 2,  Jiuming He3, Tiegang Li3, Haixu Hu1, Xiaofei Li4, Hao Xing4, Jun Wang5, Fan Yang5, Qunfeng Ma1, Bing Liu1, Chuanhao Tang6, Zeper Abliz3, 7* and Xiaoqing Liu1*
  • 1Fifth Medical Center of the PLA General Hospital, China
  • 2Academy of Military Medical Sciences (AMMS), China
  • 3State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica (IMM), China
  • 4Department of Thoracic Surgery, Tangdu Hospital, China
  • 5Peking University People's Hospital, China
  • 6Peking University International Hospital, China
  • 7Minzu University of China, China

Tumor pathology examination especially epidermal growth factor receptor (EGFR) mutations molecular testing has been integral part of lung cancer clinical practices. However, the EGFR mutations spatial distribution characteristics remains poorly investigated, which is critical to tumor heterogeneity analysis and precision diagnosis. Here, we conducted an exploratory study for label-free lung cancer pathology diagnosis and mapping of EGFR mutation spatial distribution using ambient mass spectrometry imaging (MSI).
Materials and methods:
MSI analysis were performed in 55 post-operative non-small cell lung cancer (NSCLC) tumor and paired normal tissues to distinguish tumor from normal and classify pathology. We then compared diagnostic sensitivity of MSI and ADx-amplification refractory mutation system (ARMS) for the detection of EGFR mutation in pathological confirmed lung adenocarcinoma (AC) and explored EGFR mutations associated biomarkers to depict EGFR spatial distribution base on ambient MSI.
Of 55 pathological confirmed NSCLC, MSI achieved a diagnostic sensitivity of 85.2% (23/27) and 82.1% (23/28) for AC and squamous cell carcinoma (SCC), respectively. Among 27 AC, there were 17 EGFR-wild-type and 10 EGFR-mutated-positive samples detected by ARMS, and MSI achieved a diagnostic sensitivity of 82.3% (14/17) and 80% (8/10) for these two groups. Several phospholipids were specially enriched in AC compared with SCC tissues, with the higher ions intensity of phospholipids in EGFR-mutated-positive compared with EGFR-wild-type AC tissues. We also found EGFR mutations distribution was heterogeneous in different regions of same tumor by multi-regions ARMS detection, and only the regions with higher ions intensity of phospholipids were EGFR-mutated-positive.
MSI method could accurately distinguish tumor pathology and subtypes, and phospholipids were reliable EGFR mutations associated biomarkers, phospholipids imaging could intuitively visualize EGFR mutations spatial distribution, may facilitate our understanding of tumor heterogeneity

Keywords: tumor heterogeneity, Mass spectrometry imaging, Lipids, Non small cell lung cancer (NSCLC), epidermal growth factor receptor (EGFR)

Received: 12 May 2019; Accepted: 07 Aug 2019.

Copyright: © 2019 Zhang, He, Li, Hu, Li, Xing, Wang, Yang, Ma, Liu, Tang, Abliz and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Prof. Zeper Abliz, State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica (IMM), Beijing, 100050, China,
Mx. Xiaoqing Liu, Fifth Medical Center of the PLA General Hospital, Beijing, 100049, Beijing Municipality, China,