Paper Spray Ionization Mass Spectrometry as a Potential Tool for Early Diagnosis of Cervical Cancer

Mendes, Thais P. P.; Vaz, Boniek Gontijo; Lima, Leomir A.S. de; Morais, Camilo L. M.; Neves, Ana Carolina de Oliveira; Martin, Francis; Lima, Kássio M. G.

doi:10.1021/jasms.0c00111

Cited by 21 publications

(16 citation statements)

References 59 publications

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“…Among the various techniques belonging to this group, there is the speed and versatility of Paper Spray Ionization (PSI) 11 . In PSI, the sample (liquid 12 or solid 13 ) is deposited on the surface of a triangular paper followed by the application of a high voltage and solvent, forming a spray on the tip of this paper containing sample droplets that are sent to the MS 14 . This method facilitates the analysis of biofluids quickly and quantitatively 15 .…”

Section: Introductionmentioning

confidence: 99%

Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia

Alves

Maciel

Ramalho

et al. 2021

Sci Rep

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Fibromyalgia is a rheumatological disorder that causes chronic pain and other symptomatic conditions such as depression and anxiety. Despite its relevance, the disease still presents a complex diagnosis where the doctor needs to have a correct clinical interpretation of the symptoms. In this context, it is valid to study tools that assist in the screening of this disease, using chemical work techniques such as mass spectroscopy. In this study, an analytical method is proposed to detect individuals with fibromyalgia (n = 20, 10 control samples and 10 samples with fibromyalgia) from blood plasma samples analyzed by mass spectrometry with paper spray ionization and subsequent multivariate classification of the spectral data (unsupervised and supervised), in addition to the treatment of selected variables with possible associations with metabolomics. Exploratory analysis with principal component analysis (PCA) and supervised analysis with successive projections algorithm with linear discriminant analysis (SPA-LDA) showed satisfactory results with 100% accuracy for sample prediction in both groups. This demonstrates that this combination of techniques can be used as a simple, reliable and fast tool in the development of clinical diagnosis of Fibromyalgia.

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Section: Introductionmentioning

confidence: 99%

Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia

Alves

Maciel

Ramalho

et al. 2021

Sci Rep

Self Cite

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“…Based on these metabolic differences, the method was able to differentiate malignant and premalignant samples from healthy samples with an accuracy of 86.7%. PSI has also been applied in the diagnosis of cervical cancer 33 . A total of 86 plasma samples from patients with cervical cancer and healthy controls were collected, and 10 μL of untreated plasma was analyzed by PSI‐MS.…”

Section: Applications Of Ambient Ionization Mass Spectrometrymentioning

confidence: 99%

Applications of ambient ionization mass spectrometry in 2020: An annual review

Rankin‐Turner

Heaney

2021

Analytical Science Advances

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Recent developments in mass spectrometry (MS) analyses have seen a concerted effort to reduce the complexity of analytical workflows through the simplification (or removal) of sample preparation and the shortening of run‐to‐run analysis times. Ambient ionization mass spectrometry (AIMS) is an exemplar MS‐based technology that has swiftly developed into a popular and powerful tool in analytical science. This increase in interest and demonstrable applications is down to its capacity to enable the rapid analysis of a diverse range of samples, typically in their native state or following a minimalistic sample preparation approach. The field of AIMS is constantly improving and expanding, with developments of powerful and novel techniques, improvements to existing instrumentation, and exciting new applications added with each year that passes. This annual review provides an overview of applications of AIMS techniques over the past year (2020), with a particular focus on the application of AIMS in a number of key fields of research including biomedical sciences, forensics and security, food sciences, the environment, and chemical synthesis. Novel ambient ionization techniques are introduced, including picolitre pressure‐probe electrospray ionization and fiber spray ionization, in addition to modifications and improvements to existing techniques such as hand‐held devices for ease of use, and USB‐powered ion sources for on‐site analysis. In all, the information provided in this review supports the view that AIMS has become a leading approach in MS‐based analyses and that improvements to existing methods, alongside the development of novel approaches, will continue across the foreseeable future.

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“…Given the 106 characteristic metabolites previously studied in salivary metabolic profiling, 18 the extent of their changes in serum between OSCC and HC group were investigated. For this inter-specimen validation purpose only, the serum samples from two cohorts were combined to implement the rank-sum test.…”

Section: Expression Of Salivary Metabolite Markers In Serummentioning

confidence: 99%

“…Combined with machine learning for high-dimension data interpretation, it can be performed with comparable accuracy at way less cost. [15][16][17][18][19][20] In previous work we have reported the practical value of conductive polymer spray ionization mass spectrometry combined with machine learning (CPSI-MS/ML) in the discrimination of OSCC with premalignant lesion (PML) and healthy contrast (HC). 21 CPSI-MS/ML has shown its advantage in directly collecting hundreds of metabolites abundance information from a trace dried biofluid spot within a few seconds under atmospheric conditions, 22 and in identifying key salivary metabolites and pathways involved in the progression from the PML to OSCC stage.…”

Section: Introductionmentioning

confidence: 99%

Metabolomic Profiling of Serum for Large Cohort Oral Squamous Cell Carcinoma Diagnosis

Yang

Song

Yang

et al. 2021

Preprint

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Background: Oral squamous cell carcinoma (OSCC) accounts for 90 % of oral cancers. If a necessary intervention before tumorigenesis could be conducted, the current 60% 5-year survival rate would be expected to be majorly improved. This fact motivates the search for developing a highly sensitive and specific in vitro diagnostic method to conduct rapid OSCC screening. Method: Serum samples from 819 volunteers, consisted of 241 healthy contrast (HC) and 578 OSCC patients, were collected, and their metabolic profiles were acquired using conductive polymer spray ionization mass spectrometry (CPSI-MS). Univariate analysis was used to select significantly changed metabolite ions in the OSCC group compared to the HC group. Identities of these metabolite ions were determined by MS/MS experiments and reconfirmed at the tissue level by desorption electrospray ionization mass spectrometry (DESI-MS). The supporting vector machine (SVM) algorithm was employed as the machine learning model to implement the automatic prediction of OSCC. Results: Through statistical analysis, 65 metabolites were selected as potential characteristic marker candidates for serum OSCC screening. In situ validation by DESI-MSI revealed that 8 out of top 10 metabolites showed the same trends of change in tissue and serum. With the aid of machine learning, OSCC can be distinguished from HC with an accuracy of 98.0 % by cross-validation in the discovery cohort and 89.2% accuracy in the validation cohort. Furthermore, orthogonal partial least square-discriminant analysis (OPLS-DA) also showed the potential for recognizing OSCC stages. Conclusion: Using CPSI-MS combined with SVM, it is possible to distinguish OSCC from HC in a few minutes with high specificity and sensitivity, making this rapid diagnostic procedure a promising approach for high-risk population screening.

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Paper Spray Ionization Mass Spectrometry as a Potential Tool for Early Diagnosis of Cervical Cancer

Cited by 21 publications

References 59 publications

Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia

Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia

Applications of ambient ionization mass spectrometry in 2020: An annual review

Metabolomic Profiling of Serum for Large Cohort Oral Squamous Cell Carcinoma Diagnosis

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