Prostate cancer screening using chemometric processing of GC–MS profiles obtained in the headspace above urine samples

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Prostate cancer screening using chemometric processing of GC–MS profiles obtained in the headspace above urine samples. / Deev, Vladislav ; Solovieva, Svetlana; Andreev, Evgeny; Protoshchak, Vladimir; Karpushchenko, Evgeny; Sleptsov, Aleksander; Kartsova, Liudmila ; Bessonova, Elena; Legin, Andrey; Kirsanov, Dmitry.

In: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, Vol. 1155, 122298, 15.10.2020.

Research output: Contribution to journal › Article › peer-review

Author

Deev, Vladislav ; Solovieva, Svetlana ; Andreev, Evgeny ; Protoshchak, Vladimir ; Karpushchenko, Evgeny ; Sleptsov, Aleksander ; Kartsova, Liudmila ; Bessonova, Elena ; Legin, Andrey ; Kirsanov, Dmitry. / Prostate cancer screening using chemometric processing of GC–MS profiles obtained in the headspace above urine samples. In: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences. 2020 ; Vol. 1155.

BibTeX

@article{de12a3885b9044c1b34e13a7931a2221,

title = "Prostate cancer screening using chemometric processing of GC–MS profiles obtained in the headspace above urine samples",

abstract = "The development of screening methods for various types of cancer is of utmost importance as the early diagnostics of these diseases significantly increases the chances for patient's successful medical treatment and recovery. In this study we have developed the procedure for chromatographic profiling of urine samples based on solid-phase microextraction and GC–MS. 50 urine samples (20 from the patients with biopsy conformed prostate cancer and 30 from control group) were studied in the optimized experimental conditions. Application of chemometric classification algorithms such as k-nearest neighbors and partial least squares-discriminant analysis allowed construction of predictive models yielding very high sensitivity, specificity and accuracy values all close to 100%. This gives a good promise for further validation of this approach with a broader sample sets.",

keywords = "Chemometrics, GC–MS, Prostate cancer, Screening, VOC, DIAGNOSIS, MANAGEMENT, SERUM, MASS-SPECTROMETRY, DERIVATIZATION, GC-MS, MAGNETIC-RESONANCE-SPECTROSCOPY, HUMAN-BODY FLUIDS, GAS, VOLATILE ORGANIC-COMPOUNDS",

author = "Vladislav Deev and Svetlana Solovieva and Evgeny Andreev and Vladimir Protoshchak and Evgeny Karpushchenko and Aleksander Sleptsov and Liudmila Kartsova and Elena Bessonova and Andrey Legin and Dmitry Kirsanov",

year = "2020",

month = oct,

day = "15",

doi = "10.1016/j.jchromb.2020.122298",

language = "English",

volume = "1155",

journal = "Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences",

issn = "1570-0232",

publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Prostate cancer screening using chemometric processing of GC–MS profiles obtained in the headspace above urine samples

AU - Deev, Vladislav

AU - Solovieva, Svetlana

AU - Andreev, Evgeny

AU - Protoshchak, Vladimir

AU - Karpushchenko, Evgeny

AU - Sleptsov, Aleksander

AU - Kartsova, Liudmila

AU - Bessonova, Elena

AU - Legin, Andrey

AU - Kirsanov, Dmitry

PY - 2020/10/15

Y1 - 2020/10/15

N2 - The development of screening methods for various types of cancer is of utmost importance as the early diagnostics of these diseases significantly increases the chances for patient's successful medical treatment and recovery. In this study we have developed the procedure for chromatographic profiling of urine samples based on solid-phase microextraction and GC–MS. 50 urine samples (20 from the patients with biopsy conformed prostate cancer and 30 from control group) were studied in the optimized experimental conditions. Application of chemometric classification algorithms such as k-nearest neighbors and partial least squares-discriminant analysis allowed construction of predictive models yielding very high sensitivity, specificity and accuracy values all close to 100%. This gives a good promise for further validation of this approach with a broader sample sets.

AB - The development of screening methods for various types of cancer is of utmost importance as the early diagnostics of these diseases significantly increases the chances for patient's successful medical treatment and recovery. In this study we have developed the procedure for chromatographic profiling of urine samples based on solid-phase microextraction and GC–MS. 50 urine samples (20 from the patients with biopsy conformed prostate cancer and 30 from control group) were studied in the optimized experimental conditions. Application of chemometric classification algorithms such as k-nearest neighbors and partial least squares-discriminant analysis allowed construction of predictive models yielding very high sensitivity, specificity and accuracy values all close to 100%. This gives a good promise for further validation of this approach with a broader sample sets.

KW - Chemometrics

KW - GC–MS

KW - Prostate cancer

KW - Screening

KW - VOC

KW - DIAGNOSIS

KW - MANAGEMENT

KW - SERUM

KW - MASS-SPECTROMETRY

KW - DERIVATIZATION

KW - GC-MS

KW - MAGNETIC-RESONANCE-SPECTROSCOPY

KW - HUMAN-BODY FLUIDS

KW - GAS

KW - VOLATILE ORGANIC-COMPOUNDS

UR - http://www.scopus.com/inward/record.url?scp=85089083408&partnerID=8YFLogxK

U2 - 10.1016/j.jchromb.2020.122298

DO - 10.1016/j.jchromb.2020.122298

M3 - Article

C2 - 32771969

AN - SCOPUS:85089083408

VL - 1155

JO - Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences

JF - Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences

SN - 1570-0232

M1 - 122298

ER -

ID: 61635306