Pattern identification of lung cancer patients based on body constitution questionnaires (BCQ) and glycoproteomics for precision medicine

Wonryeon Cho, Ji Hye Kim, Miseon Jeong, Myeong-Sun Kim, Jinwook Lee, Hyoungwoo Son, Chunhoo Cheon, Sunju Park, Seong-Gyu Ko, Wonryeon Cho, Ji Hye Kim, Miseon Jeong, Myeong-Sun Kim, Jinwook Lee, Hyoungwoo Son, Chunhoo Cheon, Sunju Park, Seong-Gyu Ko

Abstract

Background: The patient's pattern identification has been used for personalized medicine in traditional Korean medicine (TKM) and aims for patient-specific therapy by Korean medical doctors. The pattern identification in this trial will be diagnosed from body constitution questionnaire (BCQ) with a more objective diagnosis of it but this method still needs a more concrete scientific basis. Glycoproteins are well-known to be associated with diseases (especially cancers) so glycoproteomics can be applied to differentiate pattern identification types of lung cancer patients. Thus, for the first time proteomics approach will be applied to the pattern identification by comparing BCQ assessment in order to establish a scientific basis with clinical proteomics for precision medicine.

Methods: This observational trial will at first diagnose the pattern identification types of lung cancer patients with BCQ assessment and then elucidate their relationships with proteomics. Blood samples will be collected before surgery along with clinical information of participants. The patients' pattern identification in TKM will be diagnosed from BCQ assessment. Then, lung cancer patients will be divided and pooled into 3 lung cancer entire (LCE) groups according to their pattern identification types (Xu, Stasis, or Gentleness). Three lung cancer representative (LCR) groups will be selected and pooled from each LCE group by selecting those with the same control factors. The 3 LCE groups and the 3 LCR groups from lung cancer patients will be independently analyzed through the glycoproteomics approach based on the patients' pattern identification. Glycoproteins from the 6 groups will be identified through proteomics approach and then categorized for analysis.

Discussion: This study intends to diagnose pattern identification of patients in TKM with BCQ assessment and proteomics approach. The identification of the glycoproteins in each group will lead to the scientific foundation of personalized medicine in TKM according to patients' pattern identification for lung cancer therapy. We intend to(1) diagnose the pattern identification types of lung cancer patients with BCQ under the framework of TKM;(2) evaluate BCQ assessment with glycoproteomics approach for precision medicine.

Trial registration: ClinicalTrials.gov NCT03384680. Registered 27 December 2017. Retrospectively registered.

Conflict of interest statement

The authors have no conflicts of interest to disclose.

Figures

Figure 1
Figure 1
Flow chart of the experimental methodology.
Figure 2
Figure 2
Flow chart for protein identification and classification using statistical analysis with database searches. ∗At least 2 MS/MS data will be obtained from each sample.

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