Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface

Ji Won Park, Hyobin Jeong, Byeongsoo Kang, Su Jin Kim, Sang Yoon Park, Sokbom Kang, Hark Kyun Kim, Joon Sig Choi, Daehee Hwang, Tae Geol Lee

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Abstract

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) emerges as a promising tool to identify the ions (small molecules) indicative of disease states from the surface of patient tissues. In TOF-SIMS analysis, an enhanced ionization of surface molecules is critical to increase the number of detected ions. Several methods have been developed to enhance ionization capability. However, how these methods improve identification of disease-related ions has not been systematically explored. Here, we present a multi-dimensional SIMS (MD-SIMS) that combines conventional TOF-SIMS and metal-assisted SIMS (MetA-SIMS). Using this approach, we analyzed cancer and adjacent normal tissues first by TOF-SIMS and subsequently by MetA-SIMS. In total, TOF- and MetA-SIMS detected 632 and 959 ions, respectively. Among them, 426 were commonly detected by both methods, while 206 and 533 were detected uniquely by TOF- and MetA-SIMS, respectively. Of the 426 commonly detected ions, 250 increased in their intensities by MetA-SIMS, whereas 176 decreased. The integrated analysis of the ions detected by the two methods resulted in an increased number of discriminatory ions leading to an enhanced separation between cancer and normal tissues. Therefore, the results show that MD-SIMS can be a useful approach to provide a comprehensive list of discriminatory ions indicative of disease states.

Original languageEnglish
Article number11077
JournalScientific Reports
Volume5
DOIs
StatePublished - 5 Jun 2015

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Secondary Ion Mass Spectrometry
Ions
Metals
Neoplasms

Cite this

Park, Ji Won ; Jeong, Hyobin ; Kang, Byeongsoo ; Kim, Su Jin ; Park, Sang Yoon ; Kang, Sokbom ; Kim, Hark Kyun ; Choi, Joon Sig ; Hwang, Daehee ; Lee, Tae Geol. / Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface. In: Scientific Reports. 2015 ; Vol. 5.
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abstract = "Time-of-flight secondary ion mass spectrometry (TOF-SIMS) emerges as a promising tool to identify the ions (small molecules) indicative of disease states from the surface of patient tissues. In TOF-SIMS analysis, an enhanced ionization of surface molecules is critical to increase the number of detected ions. Several methods have been developed to enhance ionization capability. However, how these methods improve identification of disease-related ions has not been systematically explored. Here, we present a multi-dimensional SIMS (MD-SIMS) that combines conventional TOF-SIMS and metal-assisted SIMS (MetA-SIMS). Using this approach, we analyzed cancer and adjacent normal tissues first by TOF-SIMS and subsequently by MetA-SIMS. In total, TOF- and MetA-SIMS detected 632 and 959 ions, respectively. Among them, 426 were commonly detected by both methods, while 206 and 533 were detected uniquely by TOF- and MetA-SIMS, respectively. Of the 426 commonly detected ions, 250 increased in their intensities by MetA-SIMS, whereas 176 decreased. The integrated analysis of the ions detected by the two methods resulted in an increased number of discriminatory ions leading to an enhanced separation between cancer and normal tissues. Therefore, the results show that MD-SIMS can be a useful approach to provide a comprehensive list of discriminatory ions indicative of disease states.",
author = "Park, {Ji Won} and Hyobin Jeong and Byeongsoo Kang and Kim, {Su Jin} and Park, {Sang Yoon} and Sokbom Kang and Kim, {Hark Kyun} and Choi, {Joon Sig} and Daehee Hwang and Lee, {Tae Geol}",
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Park, JW, Jeong, H, Kang, B, Kim, SJ, Park, SY, Kang, S, Kim, HK, Choi, JS, Hwang, D & Lee, TG 2015, 'Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface', Scientific Reports, vol. 5, 11077. https://doi.org/10.1038/srep11077

Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface. / Park, Ji Won; Jeong, Hyobin; Kang, Byeongsoo; Kim, Su Jin; Park, Sang Yoon; Kang, Sokbom; Kim, Hark Kyun; Choi, Joon Sig; Hwang, Daehee; Lee, Tae Geol.

In: Scientific Reports, Vol. 5, 11077, 05.06.2015.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Park, Ji Won

AU - Jeong, Hyobin

AU - Kang, Byeongsoo

AU - Kim, Su Jin

AU - Park, Sang Yoon

AU - Kang, Sokbom

AU - Kim, Hark Kyun

AU - Choi, Joon Sig

AU - Hwang, Daehee

AU - Lee, Tae Geol

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N2 - Time-of-flight secondary ion mass spectrometry (TOF-SIMS) emerges as a promising tool to identify the ions (small molecules) indicative of disease states from the surface of patient tissues. In TOF-SIMS analysis, an enhanced ionization of surface molecules is critical to increase the number of detected ions. Several methods have been developed to enhance ionization capability. However, how these methods improve identification of disease-related ions has not been systematically explored. Here, we present a multi-dimensional SIMS (MD-SIMS) that combines conventional TOF-SIMS and metal-assisted SIMS (MetA-SIMS). Using this approach, we analyzed cancer and adjacent normal tissues first by TOF-SIMS and subsequently by MetA-SIMS. In total, TOF- and MetA-SIMS detected 632 and 959 ions, respectively. Among them, 426 were commonly detected by both methods, while 206 and 533 were detected uniquely by TOF- and MetA-SIMS, respectively. Of the 426 commonly detected ions, 250 increased in their intensities by MetA-SIMS, whereas 176 decreased. The integrated analysis of the ions detected by the two methods resulted in an increased number of discriminatory ions leading to an enhanced separation between cancer and normal tissues. Therefore, the results show that MD-SIMS can be a useful approach to provide a comprehensive list of discriminatory ions indicative of disease states.

AB - Time-of-flight secondary ion mass spectrometry (TOF-SIMS) emerges as a promising tool to identify the ions (small molecules) indicative of disease states from the surface of patient tissues. In TOF-SIMS analysis, an enhanced ionization of surface molecules is critical to increase the number of detected ions. Several methods have been developed to enhance ionization capability. However, how these methods improve identification of disease-related ions has not been systematically explored. Here, we present a multi-dimensional SIMS (MD-SIMS) that combines conventional TOF-SIMS and metal-assisted SIMS (MetA-SIMS). Using this approach, we analyzed cancer and adjacent normal tissues first by TOF-SIMS and subsequently by MetA-SIMS. In total, TOF- and MetA-SIMS detected 632 and 959 ions, respectively. Among them, 426 were commonly detected by both methods, while 206 and 533 were detected uniquely by TOF- and MetA-SIMS, respectively. Of the 426 commonly detected ions, 250 increased in their intensities by MetA-SIMS, whereas 176 decreased. The integrated analysis of the ions detected by the two methods resulted in an increased number of discriminatory ions leading to an enhanced separation between cancer and normal tissues. Therefore, the results show that MD-SIMS can be a useful approach to provide a comprehensive list of discriminatory ions indicative of disease states.

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