Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers
Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cance...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Biomolecules |
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| Online Access: | https://www.mdpi.com/2218-273X/12/12/1815 |
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| author | Shanshan Guo Gongxiang Wei Wenqiang Chen Chengbin Lei Cong Xu Yu Guan Te Ji Fuli Wang Huiqiang Liu |
| author_facet | Shanshan Guo Gongxiang Wei Wenqiang Chen Chengbin Lei Cong Xu Yu Guan Te Ji Fuli Wang Huiqiang Liu |
| author_sort | Shanshan Guo |
| collection | DOAJ |
| description | Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cancers (DTC) to detect abundant changes and select specific markers in a broad spectrum of molecular species. Here, we present a diagnostic protocol of DTC in which the in-situ blood-based ATR-FTIR spectroscopic data mining pathway was designed for the identification of DTC triages in 252 blood serum samples, divided into the following groups: liver cancer (LC), gastric cancer (GC), colorectal cancer (CC), and their different three stages respectively. The infrared molecular fingerprints (IMFs) of DTC were measured and used to build a 2-dimensional second derivative spectrum (2D-SD-IR) feature dataset for classification, including absorbance and wavenumber shifts of FTIR vibration peaks. By comparison, the Partial Least-Squares Discriminant Analysis (PLS-DA) and backpropagation (BP) neural networks are suitable to differentiate DTCs and pathological stages with a high sensitivity and specificity of 100% and averaged more than 95%. Furthermore, the measured IMF data was mutually validated via clinical blood biochemistry testing, which indicated that the proposed 2D-SD-IR-based machine learning protocol greatly improved DTC classification performance. |
| first_indexed | 2024-03-09T17:17:07Z |
| format | Article |
| id | doaj.art-47dcea33b2154abc9c017de45788c05f |
| institution | Directory Open Access Journal |
| issn | 2218-273X |
| language | English |
| last_indexed | 2024-03-09T17:17:07Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomolecules |
| spelling | doaj.art-47dcea33b2154abc9c017de45788c05f2023-11-24T13:33:49ZengMDPI AGBiomolecules2218-273X2022-12-011212181510.3390/biom12121815Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract CancersShanshan Guo0Gongxiang Wei1Wenqiang Chen2Chengbin Lei3Cong Xu4Yu Guan5Te Ji6Fuli Wang7Huiqiang Liu8School of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo 255000, ChinaSchool of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo 255000, ChinaDepartment of Clinical Laboratory, Zibo Central Hospital, Zibo 255000, ChinaDepartment of Clinical Laboratory, Zibo Central Hospital, Zibo 255000, ChinaSchool of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo 255000, ChinaSchool of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo 255000, ChinaShanghai Synchrotron Radiation Facility, Shanghai 201204, ChinaDepartment of Oncology, Zibo Central Hospital, Zibo 255000, ChinaSchool of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo 255000, ChinaAttenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cancers (DTC) to detect abundant changes and select specific markers in a broad spectrum of molecular species. Here, we present a diagnostic protocol of DTC in which the in-situ blood-based ATR-FTIR spectroscopic data mining pathway was designed for the identification of DTC triages in 252 blood serum samples, divided into the following groups: liver cancer (LC), gastric cancer (GC), colorectal cancer (CC), and their different three stages respectively. The infrared molecular fingerprints (IMFs) of DTC were measured and used to build a 2-dimensional second derivative spectrum (2D-SD-IR) feature dataset for classification, including absorbance and wavenumber shifts of FTIR vibration peaks. By comparison, the Partial Least-Squares Discriminant Analysis (PLS-DA) and backpropagation (BP) neural networks are suitable to differentiate DTCs and pathological stages with a high sensitivity and specificity of 100% and averaged more than 95%. Furthermore, the measured IMF data was mutually validated via clinical blood biochemistry testing, which indicated that the proposed 2D-SD-IR-based machine learning protocol greatly improved DTC classification performance.https://www.mdpi.com/2218-273X/12/12/1815infrared spectroscopyblood-based molecular biologyinfrared molecular fingerprintmachine learningdigestive tract cancers |
| spellingShingle | Shanshan Guo Gongxiang Wei Wenqiang Chen Chengbin Lei Cong Xu Yu Guan Te Ji Fuli Wang Huiqiang Liu Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers Biomolecules infrared spectroscopy blood-based molecular biology infrared molecular fingerprint machine learning digestive tract cancers |
| title | Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers |
| title_full | Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers |
| title_fullStr | Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers |
| title_full_unstemmed | Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers |
| title_short | Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers |
| title_sort | fast and deep diagnosis using blood based atr ftir spectroscopy for digestive tract cancers |
| topic | infrared spectroscopy blood-based molecular biology infrared molecular fingerprint machine learning digestive tract cancers |
| url | https://www.mdpi.com/2218-273X/12/12/1815 |
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