An integrated mass spectrometry imaging and digital pathology workflow for objective detection of colorectal tumours by unique atomic signatures

Paul, Bence; Kysenius, Kai; Hilton, James B.; Jones, Michael W. M.; Hutchinson, R. L.; Buchanan, Daniel D.; Rosty, Christophe; Fryer, Fred; Bush, Ashley I.; Hergt, Janet M; Woodhead, Jon; Bishop, David; Doble, Philip; Hill, Michelle M.; Crouch, Peter J.; Hare, Dominic J.

doi:10.1039/d1sc02237g

Cited by 13 publications

(10 citation statements)

References 80 publications

(104 reference statements)

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“…It has been reported that the level of trace elements in the human body influences the occurrence of gastrointestinal tumors in humans, which is accompanied by an increase in serum copper and a decrease in serum zinc during the formation of tumors (20). It has also been reported that serum copper and copper/zinc ratios are higher in patients with gastrointestinal tumors than in normal subjects (21,22), while zinc and calcium in the same cases are lower than in normal subjects (23), indicating that elevated serum copper and copper/zinc ratios may be risk factors for gastrointestinal tumors, while elevated serum zinc and calcium reduce the incidence of gastrointestinal tumors (24). Thus， both zinc and calcium were regarded as protective factors against the development of gastrointestinal tumors (25,26).…”

Section: Discussionmentioning

confidence: 90%

Serum zinc in patients with colorectal cancer might contribute to the prediction of tumor clinical staging scores： a prospective single-center clinical study

Zhang

Wang

et al. 2023

Preprint

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Background: Diagnosis for colorectal cancer is infrequently diagnosed and not accurate staging. Trace elements may be involved in the whole process of intestinal tumors. Can trace elements be used to predict condition and staging scores for colorectal cancer? Methods: Patients(n=74) and the control group (n=32) were enrolled. Data from the first acceptance were recorded including age, gender, clinical staging scores of tumors, and tumor biomarkers. The serological specimens were tested for magnesium, iron, copper, zinc, calcium, and selenium with ICP-MS. T-test was used to analyze serum trace elements in patients and the control group, and LASSO regression was executed to screen which factors contributed most to clinical staging scores. Results: The level of copper in the control group is lower than in the patients (p=0.0004, ∆mean±SEM=210.7±57.79, and 95%CI=96.14to325.4). For the other five trace elements in the control group is higher than in the patients, respectively manganese (p=0.0003, ∆ mean±SEM=-1.658±0.4470, 95%CI=-2.544to-0.7713), iron (p=0.0343, ∆ mean=-0.3672±0.1712, 95%CI=-0.7068to-0.02761), zinc (p=0.0059, ∆ mean=-0.1348±0.04794, 95%CI=-0.2298to-0.03968), calcium (p<0.0001, ∆ mean=-15.10±3.482, 95%CI=-22.00to-8.195), selenium (p=0.0216, ∆mean=-12.23±5.242, 95%CI=-22.62to-1.832). The results of LASSO regression show variables selected are Ca125 （ coefficient=5.8e-04 ） , Ca199 （coefficient=7.4e-05）, zinc（coefficient=-0.2047）， and intercept（3.1951）, which are regarded as the most contributing to the clinical staging scores， the coefficients for other factors are zero. Conclusions: Ca125 and Ca199 are positively contributing to the clinical staging scores, and zinc is negatively correlated with them. Therefore, we suggest that serum zinc might be used to predict the clinical staging scores of patients with colorectal cancer.

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Section: Discussionmentioning

confidence: 90%

Serum zinc in patients with colorectal cancer might contribute to the prediction of tumor clinical staging scores： a prospective single-center clinical study

Zhang

Wang

et al. 2023

Preprint

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“…Nonlinear supervised learning models such as support vector machine (SVM), [ 128 , 129 , 130 ] random forest (RF), [ 131 , 132 , 133 ] and deep learning [ 134 , 135 , 136 , 137 , 138 , 139 ] are also widely used for classifying spectral data for spatial segmentation. The SVM algorithm finds a hyperplane with maximum margin to classify data.…”

Section: Computational Methods For Msi Data Analysismentioning

confidence: 99%

“…Data from other modalities provide complementary molecular or spatial information, which may be used to enhance the quality of MSI data or provide additional insights using more targeted analytical tools. MSI data have been coupled with histology, [ 91 , 133 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 ] fluorescence microscopy, [ 188 , 189 , 190 , 191 ] Allen brain atlas, [ 107 , 192 ] topology, [ 193 , 194 , 195 ] electron microscopy, [ 196 , 197 ] Raman spectroscopy, [ 198 , 199 , 200 , 201 ] infrared spectroscopy, [ 202 ] magnetic resonance imaging, [ 93 , 203 ] and microsampling LC‐MS/MS analysis of proteins, transcripts, and genes. [ 164 , 204 , 205 , 206 , 207 , 208 , 209 , 210 ] In these studies, computational approaches have been used for registration of the multimodal data.…”

Section: Computational Methods For Msi Data Analysismentioning

confidence: 99%

Emerging Computational Methods in Mass Spectrometry Imaging

Laskin

2022

Advanced Science

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Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.

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“…Quantitative imaging can also be achieved using the appropriate matrix-matched standard materials, either certified standard materials 91 or in-house standards. 92,93 Finally, many open-source or commercial software packages have been developed to process and reconstruct the enormous spatial imaging data from LA-ICP-MS. 94,95 Owing to these advances, new methods have been developed. Three-dimensional (3D) quantitative imaging of metals and metalloids has been realized by imaging successive slices of a sample with LA-ICP-MS and reconstructing the images into three dimensions.…”

Section: Single Cell Analysismentioning

confidence: 99%

ICP-MS-Based Methodology In Metallomics: Towards Single Particle Analysis, Single Cell Analysis, And Spatial Metallomics

Chen¹,

Wang²

2022

At.Spectrosc.

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As an emerging interdisciplinary science, metallomics aims to integrate research fields related to metals and metalloids in biological systems from a systematic perspective. Inductively coupled plasma mass spectrometry (ICP-MS) is considered one of the most versatile tools for metallomics research. This review presents a brief overview of ICP-MS and describes recent advances in ICP-MS instrumentation. Then, ICP-MS-based methods and applications are discussed, focusing on single particle analysis, single cell analysis, and spatial metallomics. With the rapid developments in instrumentation and methodology, ICP-MS-based methodologies will evolve further and play a dominant role in metallomics research.

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An integrated mass spectrometry imaging and digital pathology workflow for objective detection of colorectal tumours by unique atomic signatures

Abstract: Tumours are abnormal growths of cells that reproduce by redirecting essential nutrients and resources from surrounding tissue. Changes to cell metabolism that trigger the growth of tumours are reflected in...

Cited by 13 publications

References 80 publications

Serum zinc in patients with colorectal cancer might contribute to the prediction of tumor clinical staging scores： a prospective single-center clinical study

Serum zinc in patients with colorectal cancer might contribute to the prediction of tumor clinical staging scores： a prospective single-center clinical study

Emerging Computational Methods in Mass Spectrometry Imaging

ICP-MS-Based Methodology In Metallomics: Towards Single Particle Analysis, Single Cell Analysis, And Spatial Metallomics

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