TY - JOUR
T1 - The utility of differential scanning calorimetry curves of blood plasma for diagnosis, subtype differentiation and predicted survival in lung cancer
AU - Schneider, Gabriela
AU - Kaliappan, Alagammai
AU - Nguyen, Taylor Q.
AU - Buscaglia, Robert
AU - Brock, Guy N.
AU - Hall, Melissa Barousse
AU - Despirito, Crissie
AU - Wilkey, Daniel W.
AU - Merchant, Michael L.
AU - Klein, Jon B.
AU - Wiese, Tanya A.
AU - Rivas-Perez, Hiram L.
AU - Kloecker, Goetz H.
AU - Garbett, Nichola C.
N1 - Funding Information:
Funding: This work was supported by grants to N.C.G. from the National Cancer Institute under award number R21CA187345, the Department of Defense Lung Cancer Research Program under award number W81XWH-15-1-0178, the Kentucky Science and Technology Corporation under award number COMMFUND-1517-RFP-017 and the National Institute of Allergy and Infectious Diseases under award number R01AI129959. G.N.B. is supported in part by the Ohio State University (OSU) Center for Clinical and Translational Science under award number UL1TR002733 from the National Center for Advancing Translational Sciences and by the OSU Comprehensive Cancer Center Support Grant from the National Cancer Institute under award number P30CA016058. This work was supported by grants to M.L.M. from the National Institute of General Medical Sciences under award number P20 GM113226, the National Institute of Environmental Health Sciences under award number P30 ES030283, and the National Institute of Alcohol Abuse and Alcoholism under award number AA028436. This work was supported by James Graham Brown Research Foundation, Endowed Chair in Proteomics to J.B.K. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/11/1
Y1 - 2021/11/1
N2 - Early detection of lung cancer (LC) significantly increases the likelihood of successful treatment and improves LC survival rates. Currently, screening (mainly low-dose CT scans) is recommended for individuals at high risk. However, the recent increase in the number of LC cases unrelated to the well-known risk factors, and the high false-positive rate of low-dose CT, indicate a need to develop new, non-invasive methods for LC detection. Therefore, we evaluated the use of differential scanning calorimetry (DSC) for LC patients’ diagnosis and predicted survival. Addition-ally, by applying mass spectrometry, we investigated whether changes in O-and N-glycosylation of plasma proteins could be an underlying mechanism responsible for observed differences in DSC curves of LC and control subjects. Our results indicate selected DSC curve features could be useful for differentiation of LC patients from controls with some capable of distinction between subtypes and stages of LC. DSC curve features also correlate with LC patients’ overall/progression free survival. Moreover, the development of classification models combining patients’ DSC curves with selected plasma protein glycosylation levels that changed in the presence of LC could improve the sensitivity and specificity of the detection of LC. With further optimization and development of the classification method, DSC could provide an accurate, non-invasive, radiation-free strategy for LC screening and diagnosis.
AB - Early detection of lung cancer (LC) significantly increases the likelihood of successful treatment and improves LC survival rates. Currently, screening (mainly low-dose CT scans) is recommended for individuals at high risk. However, the recent increase in the number of LC cases unrelated to the well-known risk factors, and the high false-positive rate of low-dose CT, indicate a need to develop new, non-invasive methods for LC detection. Therefore, we evaluated the use of differential scanning calorimetry (DSC) for LC patients’ diagnosis and predicted survival. Addition-ally, by applying mass spectrometry, we investigated whether changes in O-and N-glycosylation of plasma proteins could be an underlying mechanism responsible for observed differences in DSC curves of LC and control subjects. Our results indicate selected DSC curve features could be useful for differentiation of LC patients from controls with some capable of distinction between subtypes and stages of LC. DSC curve features also correlate with LC patients’ overall/progression free survival. Moreover, the development of classification models combining patients’ DSC curves with selected plasma protein glycosylation levels that changed in the presence of LC could improve the sensitivity and specificity of the detection of LC. With further optimization and development of the classification method, DSC could provide an accurate, non-invasive, radiation-free strategy for LC screening and diagnosis.
KW - DSC curve
KW - Diagnosis
KW - Differential scanning calorimetry (DSC)
KW - Lung cancer
KW - Overall survival
KW - Progression-free survival
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U2 - 10.3390/cancers13215326
DO - 10.3390/cancers13215326
M3 - Article
AN - SCOPUS:85117582848
SN - 2072-6694
VL - 13
JO - Cancers
JF - Cancers
IS - 21
M1 - 5326
ER -