Małgorzata Ros-Mazurczyk1, Karol Jelonek2, Michał Marczyk3, Franciszek Binczyk4, Monika Pietrowska5, Joanna Polanska6, Rafał Dziadziuszko7, Jacek Jassem8, Witold Rzyman9, Piotr Widlak10. 1. Maria Sklodowska-Curie Institute - Oncology Center, Gliwice Branch, ul. Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland. Electronic address: malgorzata.ros@io.gliwice.pl. 2. Maria Sklodowska-Curie Institute - Oncology Center, Gliwice Branch, ul. Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland. Electronic address: karol.jelonek@io.gliwice.pl. 3. Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland. Electronic address: michal.marczyk@polsl.pl. 4. Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland. Electronic address: franciszek.e.binczyk@polsl.pl. 5. Maria Sklodowska-Curie Institute - Oncology Center, Gliwice Branch, ul. Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland. Electronic address: monika.pietrowska@io.gliwice.pl. 6. Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland. Electronic address: joanna.polanska@polsl.pl. 7. Medical University of Gdansk, ul. Debinki 7, 80-211 Gdansk, Poland. Electronic address: rafald@gumed.edu.pl. 8. Medical University of Gdansk, ul. Debinki 7, 80-211 Gdansk, Poland. Electronic address: jjassem@gumed.edu.pl. 9. Medical University of Gdansk, ul. Debinki 7, 80-211 Gdansk, Poland. Electronic address: wrzyman@gumed.edu.pl. 10. Maria Sklodowska-Curie Institute - Oncology Center, Gliwice Branch, ul. Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland. Electronic address: piotr.widlak@io.gliwice.pl.
Abstract
OBJECTIVES: The role of a low-dose computed tomography lung cancer screening remains a matter of controversy due to its low specificity and high costs. Screening complementation with blood-based biomarkers may allow a more efficient pre-selection of candidates for imaging tests or discrimination between benign and malignant chest abnormalities detected by low-dose computed tomography (LD-CT). We searched for a molecular signature based on a serum lipid profile distinguishing individuals with early lung cancer from healthy participants of the lung cancer screening program. MATERIALS AND METHODS: Blood samples were collected from 100 patients with early stage lung cancer (including 31 screen-detected cases) and from a matched group of 300 healthy participants of the lung cancer screening program. MALDI-ToF mass spectrometry was used to analyze the molecular profile of lipid-containing organic extract of serum samples in the 320-1000Da range. RESULTS: Several components of the serum lipidome were detected, with abundances discriminating patients with early lung cancer from high-risk smokers. An effective cancer classifier was built with an area under the curve of 0.88. Corresponding negative predictive value was 98% and a positive predictive value was 42% when the classifier was tuned for maximum negative predictive value. Furthermore, the downregulation of a few lysophosphatidylcholines (LPC18:2, LPC18:1 and LPC18:0) in samples from cancer patients was confirmed using a complementary LC-MS approach (a reasonable cancer discrimination was possible based on LPC18:2 alone with 25% total weighted error of classification). CONCLUSIONS: Lipid-based serum signature showed potential usefulness in discriminating early lung cancer patients from healthy individuals.
OBJECTIVES: The role of a low-dose computed tomography lung cancer screening remains a matter of controversy due to its low specificity and high costs. Screening complementation with blood-based biomarkers may allow a more efficient pre-selection of candidates for imaging tests or discrimination between benign and malignant chest abnormalities detected by low-dose computed tomography (LD-CT). We searched for a molecular signature based on a serum lipid profile distinguishing individuals with early lung cancer from healthy participants of the lung cancer screening program. MATERIALS AND METHODS: Blood samples were collected from 100 patients with early stage lung cancer (including 31 screen-detected cases) and from a matched group of 300 healthy participants of the lung cancer screening program. MALDI-ToF mass spectrometry was used to analyze the molecular profile of lipid-containing organic extract of serum samples in the 320-1000Da range. RESULTS: Several components of the serum lipidome were detected, with abundances discriminating patients with early lung cancer from high-risk smokers. An effective cancer classifier was built with an area under the curve of 0.88. Corresponding negative predictive value was 98% and a positive predictive value was 42% when the classifier was tuned for maximum negative predictive value. Furthermore, the downregulation of a few lysophosphatidylcholines (LPC18:2, LPC18:1 and LPC18:0) in samples from cancerpatients was confirmed using a complementary LC-MS approach (a reasonable cancer discrimination was possible based on LPC18:2 alone with 25% total weighted error of classification). CONCLUSIONS:Lipid-based serum signature showed potential usefulness in discriminating early lung cancerpatients from healthy individuals.
Authors: Sneha Sundaram; Petr Žáček; Michael R Bukowski; Aaron A Mehus; Lin Yan; Matthew J Picklo Journal: Front Oncol Date: 2018-05-11 Impact factor: 6.244
Authors: Lun Zhang; Jiamin Zheng; Rashid Ahmed; Guoyu Huang; Jennifer Reid; Rupasri Mandal; Andrew Maksymuik; Daniel S Sitar; Paramjit S Tappia; Bram Ramjiawan; Philippe Joubert; Alessandro Russo; Christian D Rolfo; David S Wishart Journal: Cancers (Basel) Date: 2020-03-07 Impact factor: 6.639