Real-time analysis of living animals and rapid screening of human fluid samples using remote sampling electrospray ionization mass spectrometry

Yoshimura, Kenichi; Yamada, Yuki; Ninomiya, Satoshi; Chung, Wen Yuan; Chang, Yu-Ting; Dennison, Ashley R.; Hiraoka, Kenzo; Takeda, Sén; Chen, Lee Chuin

doi:10.1016/j.jpba.2019.04.050

Cited by 7 publications

(7 citation statements)

References 27 publications

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“…This would also be applicable for extracts of breast cancer tissue. As PESI‐MS is available for solid and liquid samples, the combination of MS analysis with existing procedures such as core‐needle biopsy and liquid biopsy will be more useful and more accurate for breast cancer screening in the future. Before clinical implementation, rigorous validation studies with different MS methods will be mandatory.…”

Section: Resultsmentioning

confidence: 99%

Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry

Iwano

Yoshimura

Inoue³

et al. 2020

British Journal of Surgery

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Probe electrospray ionization mass spectrometry (PESI‐MS) is an ambient ionization‐based mass spectrometry method that surpasses the original electrospray ionization technique in features such as the rapidity of analysis, simplicity of the equipment and procedure, and lower cost. This study found that the PESI‐MS system with machine learning has the potential to establish a lipid‐based diagnosis of breast cancer with higher accuracy, using a simpler approach. Rapid mass spectrometry for breast cancer

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Section: Resultsmentioning

confidence: 99%

Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry

Iwano

Yoshimura

Inoue³

et al. 2020

British Journal of Surgery

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“…We used a DPiMS‐8060 PESI unit from Shimadzu (Kyoto, Japan), and a brief explanation of the methodology is as follows: (i) sample preparation: 2.5 mg of tissue was homogenized in 100 μL of 50% ethanol using a disposal pestle (Argos Technologies, Vernon Hills, IL, USA). (ii) The homogenate was centrifuged at 15 000 g for 5 min, and the supernatant was diluted fourfold by adding 50% ethanol 16 . (iii) A 9 μL sample of solution was placed in the sample plate (Shimadzu Corp).…”

Section: Methodsmentioning

confidence: 99%

“…The measurement methodology of PESI-MS was described previously. 15,16 We used a DPiMS-8060 PESI unit from Shimadzu (Kyoto, Japan), and a brief explanation of the methodology is as follows: (i) sample preparation: 2.5 mg of tissue was homogenized in 100 μL of 50% ethanol using a disposal pestle (Argos Technologies, Vernon Hills, IL, USA). (ii) The homogenate was centrifuged at 15 000 g for 5 min, and the supernatant was diluted fourfold by adding 50% ethanol.…”

Section: Probementioning

confidence: 99%

Probe electrospray ionization mass spectrometry‐based rapid diagnosis of liver tumors

Hakoda

Kiritani

Kobayashi

et al. 2022

J of Gastro and Hepatol

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Background and Aim: Prompt differential diagnosis of liver tumors is clinically important and sometimes difficult. A new diagnostic device that combines probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning may help provide the differential diagnosis of liver tumors. Methods: We evaluated the diagnostic accuracy of this new PESI-MS device using tissues obtained and stored from previous surgically resected specimens. The following cancer tissues (with collection dates): hepatocellular carcinoma (HCC, 2016-2019), intrahepatic cholangiocellular carcinoma (ICC, 2014(ICC, -2019, and colorectal liver metastasis (CRLM, 2014-2019) from patients who underwent hepatic resection were considered for use in this study. Non-cancerous liver tissues (NL) taken from CRLM cases were also incorporated into the analysis. Each mass spectrum provided by PESI-MS was tested using support vector machine, a type of machine learning, to evaluate the discriminatory ability of the device. Results: In this study, we used samples from 91 of 139 patients with HCC, all 24 ICC samples, and 103 of 202 CRLM samples; 80 NL from CRLM cases were also used. Each mass spectrum was obtained by PESI-MS in a few minutes and was evaluated by machine learning. The sensitivity, specificity, and diagnostic accuracy of the PESI-MS device for discriminating HCC, ICC, and CRLM from among a mix of all three tumors and from NL were 98.9%, 98.1%, and 98.3%; 87.5%, 93.1%, and 92.6%; and 99.0%, 97.9%, and 98.3%, respectively. Conclusion: This study demonstrated that PESI-MS and machine learning could discriminate liver tumors accurately and rapidly.

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“…The PESI‐MS analysis was performed using a triple quadrupole mass spectrometer (DPiMS‐8060; Shimadzu Corp.), which has a PESI ion source that replaces the ESI module of the original LCMS‐8060 spectrometer. The mass spectra were acquired for nonneoplastic and PDAC specimens in the positive ion mode, and all subsequent analyses were performed as previously described previously 5–9 …”

Section: Methodsmentioning

confidence: 99%

New strategy for evaluating pancreatic tissue specimens from endoscopic ultrasound‐guided fine needle aspiration and surgery

et al. 2021

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Background and Aim Preoperative histological evaluation of pancreatic neoplasms is important for guiding the resection strategy and preventing postoperative adverse events. However, conventional endoscopic methods have technical limitations that reduce the accuracy of the histopathological examination. Probe electrospray ionization mass spectrometry (PESI‐MS) may be a useful technique for rapidly evaluating small specimens. Methods This single‐center prospective study included patients with pancreatic neoplasms between October 2018 and December 2019. Pancreatic ductal adenocarcinoma (PDAC) specimens were obtained via endoscopic ultrasound‐guided fine needle aspiration (EUS‐FNA) and non‐neoplastic tissue was obtained via surgery. Specimens were subjected to PESI‐MS and the mass spectra were analyzed using partial least squares regression‐discriminant analysis. Results The study included 40 patients with 20 nonneoplastic specimens and 19 PDAC specimens (1 case of neuroendocrine carcinoma was omitted). All nonneoplastic specimens were sufficient for PESI‐MS analysis, although only 7 of 19 PDAC specimens were sufficient for PESI‐MS analysis because of poor sample quality or insufficient quantity (<1 mg). Among the 27 analyzed cases, the mass spectra clearly differentiated between the PDAC and nonneoplastic specimens. Conclusions This study revealed that PESI‐MS could differentiate between PDAC and nonneoplastic specimens, even in cases where EUS‐FNA produced very small specimens.

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Real-time analysis of living animals and rapid screening of human fluid samples using remote sampling electrospray ionization mass spectrometry

Cited by 7 publications

References 27 publications

Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry

Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry

Probe electrospray ionization mass spectrometry‐based rapid diagnosis of liver tumors

New strategy for evaluating pancreatic tissue specimens from endoscopic ultrasound‐guided fine needle aspiration and surgery

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