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

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.

SUBMITTER: Park JW

PROVIDER: S-EPMC4457153 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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

Park Ji-Won JW Jeong Hyobin H Kang Byeongsoo B Kim Su Jin SJ Park Sang Yoon SY Kang Sokbom S Kim Hark Kyun HK Choi Joon Sig JS Hwang Daehee D Lee Tae Geol TG

Scientific reports 20150605

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 ...[more]

PMID: 26046669

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Project description:Performance improvements in DNA-modified surfaces required for microarray and biosensor applications rely on improved capabilities to accurately characterize the chemistry and structure of immobilized DNA molecules on micropatterned surfaces. Recent innovations in imaging X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) now permit more detailed studies of micropatterned surfaces. We have exploited the complementary information provided by imaging XPS and imaging TOF-SIMS to detail the chemical composition, spatial distribution, and hybridization efficiency of amine-terminated single-stranded DNA (ssDNA) bound to commercial polyacrylamide-based, amine-reactive microarray slides, immobilized in both macrospot and microarray diagnostic formats. Combinations of XPS imaging and small spot analysis were used to identify micropatterned DNA spots within printed DNA arrays on slide surfaces and quantify DNA elements within individual microarray spots for determination of probe immobilization and hybridization efficiencies. This represents the first report of imaging XPS of DNA immobilization and hybridization efficiencies for arrays fabricated on commercial microarray slides. Imaging TOF-SIMS provided distinct analytical data on the lateral distribution of DNA within single array microspots before and after target hybridization. Principal component analysis (PCA) applied to TOF-SIMS imaging datasets demonstrated that the combination of these two techniques provides information not readily observable in TOF-SIMS images alone, particularly in identifying species associated with array spot nonuniformities (e.g., "halo" or "donut" effects often observed in fluorescence images). Chemically specific spot images were compared to conventional fluorescence scanned images in microarrays to provide new information on spot-to-spot DNA variations that affect current diagnostic reliability, assay variance, and sensitivity.

Project description:Imaging time-of-flight secondary ion mass spectrometry (ToF-SIMS) and principal component analysis (PCA) were used to investigate two sets of pre- and post-chemotherapy human breast tumor tissue sections to characterize lipids associated with tumor metabolic flexibility and response to treatment. The micron spatial resolution imaging capability of ToF-SIMS provides a powerful approach to attain spatially-resolved molecular and cellular data from cancerous tissues not available with conventional imaging techniques. Three ca. 1 mm(2) areas per tissue section were analyzed by stitching together 200 μm × 200 μm raster area scans. A method to isolate and analyze specific tissue regions of interest by utilizing PCA of ToF-SIMS images is presented, which allowed separation of cellularized areas from stromal areas. These PCA-generated regions of interest were then used as masks to reconstruct representative spectra from specifically stromal or cellular regions. The advantage of this unsupervised selection method is a reduction in scatter in the spectral PCA results when compared to analyzing all tissue areas or analyzing areas highlighted by a pathologist. Utilizing this method, stromal and cellular regions of breast tissue biopsies taken pre- versus post-chemotherapy demonstrate chemical separation using negatively-charged ion species. In this sample set, the cellular regions were predominantly all cancer cells. Fatty acids (i.e. palmitic, oleic, and stearic), monoacylglycerols, diacylglycerols and vitamin E profiles were distinctively different between the pre- and post-therapy tissues. These results validate a new unsupervised method to isolate and interpret biochemically distinct regions in cancer tissues using imaging ToF-SIMS data. In addition, the method developed here can provide a framework to compare a variety of tissue samples using imaging ToF-SIMS, especially where there is section-to-section variability that makes it difficult to use a serial hematoxylin and eosin (H&E) stained section to direct the SIMS analysis.

Dataset Information

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

Publications

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

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