It's in your blood: spectral biomarker candidates for urinary bladder cancer from automated FTIR spectroscopy

Ollesch, Julian; Heinze, Margot; Heise, H. M.; Behrens, Thomas; Brüning, Thomas; Gerwert, Klaus

doi:10.1002/jbio.201300163

Cited by 70 publications

(78 citation statements)

References 37 publications

(53 reference statements)

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“…For instance, recording spectra at 16 cm −1 rather than 4 cm −1 improves SNR by a factor 4 or, for a given SNR, decreases the measurement time by a factor of 16. Yet, as shown by Ollesch et al [48], in some specific instances, higher resolutions provide better results.…”

Section: Spectral Resolutionmentioning

confidence: 77%

Infrared imaging in histopathology: Is a unified approach possible?

Goormaghtigh

2017

BSI

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Abstract.BACKGROUND: infrared imaging has emerged as a new promising tool in histopathology to provide label free analysis of tissue sections. Interestingly, infrared imaging has the potential to measure many markers at the same time, on one section, without staining. It has been demonstrated to deliver accurate results in numerous cancer pathologies. Yet, today, it is not used in routine diagnostics. The gap between the demonstrated potential and the applications is striking. The reasons why FTIR imaging is not used in the clinics are multiple but one of them is a major obstacle: the diversity of sample preparation, image recording parameters and pre-analytical methods used by the different research groups. This diversity prevents comparison of data and thereby the large scale validation necessary to enter the medical world. OBJECTIVE: we will briefly review here the main aspects of data acquisition and processing used in infrared imaging of tissue sections for which a common approach should be considered. RESULTS: considering requirement for spectral histopathology, the development of the technology and the literature on this topic, guidelines ruling sample preparation and pre-analytical methods do emerge. CONCLUSIONS: consensus values are proposed for most parameters whose current diversity prevents the exchange of data among institutions and thereby the validation of the method on a large scale.

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Section: Spectral Resolutionmentioning

confidence: 77%

Infrared imaging in histopathology: Is a unified approach possible?

Goormaghtigh

2017

BSI

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“…Thus, the selection of the first patients of a group equals a random selection among the participants. A selection of equally powered groups was necessary to prevent classifier distortion [21,22].…”

Section: Patient Collectivementioning

confidence: 99%

“…The automated HT-FTIRmeasurements (Vertex 70v FTIR spectrometer, HTS-XT extension, Twister robotic plate feeder, Bruker Optics GmbH, Ettlingen, Germany) of robotically spotted samples (50 nl per well) (instrumentTwo, M2 Automation GmbH, Berlin, Germany) on 384 well silicon MTPs (Bruker) were performed as described with 4 cm −1 resolution [21,22].…”

Section: Spectroscopic Analysismentioning

confidence: 99%

“…One computationally efficient algorithm with low requirements for processing power is termed maximum relevance, minimum redundancy (MRMR). It is based on data discretization and z-testing [23] and was successfully applied to nonlinear multivariate classification problems [6,[21][22][23]. The basic algorithm can be downloaded from http://www.mathworks.com/matlabcentral/fileexchange/ 14,916 (October 16,2015).…”

Section: Feature Selectionmentioning

confidence: 99%

“…Here, we report the application of a widely automated high-throughput FTIR-spectroscopic instrumentation, which has performed well in the detection of urinary bladder cancer from blood samples [21,22]. Now, the system was applied to the blood-based prediction of primary NSCLC from serum, EDTA-and citrate-stabilized blood plasma.…”

Section: Introductionmentioning

confidence: 99%

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An infrared spectroscopic blood test for non-small cell lung carcinoma and subtyping into pulmonary squamous cell carcinoma or adenocarcinoma

Ollesch

Theegarten

Altmayer

et al. 2016

BSI

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Abstract. BACKGROUND:Lung cancer is the leading cause of death for male and female cancer patients alike. Early diagnosis improves prognosis. A blood test would be a valuable support. OBJECTIVE: Infrared spectroscopy provides a label-free biochemical fingerprint of a sample. A study was conducted on 161 patients with initial cancer suspicion to identify and verify spectral biomarker candidate patterns to detect non-small cell lung carcinoma (NSCLC). METHODS: Blood serum and plasma samples were analysed with an automated FTIR spectroscopic system. Two pattern recognition algorithms and two classifiers were applied. Monte Carlo cross validation was performed with linear discriminant analysis and random forest classification. RESULTS: Marker patterns for the discrimination of cancer from clinically relevant disease control patients were identified in FTIR spectra of blood samples. An accuracy of up to 79% was achieved. Squamous cell and adenocarcinoma patients were separable with an accuracy of 80%. CONCLUSIONS: The study demonstrates the applicability of FTIR spectroscopic blood testing for lung cancer detection. Evidence for cancer subtype discrimination is given. With an improved performance, the method could be developed as a routine diagnostic tool for blood testing detecting NSCLC.

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Molecular Origin of Blood‐Based Infrared Spectroscopic Fingerprints**

et al. 2021

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Infrared spectroscopy of liquid biopsies is a timeand cost-effective approach that may advance biomedical diagnostics. However, the molecular nature of disease-related changes of infrared molecular fingerprints (IMFs) remains poorly understood, impeding the methods applicability. Here we probe 148 human blood sera and reveal the origin of the variations in their IMFs. To that end, we supplemented infrared spectroscopy with biochemical fractionation and proteomic profiling, providing molecular information about serum composition. Using lung cancer as an example of a medical condition, we demonstrate that the disease-related differences in IMFs are dominated by contributions from twelve highly abundant proteins-that, if used as a pattern, may be instrumental for detecting malignancy. Tying proteomic to spectral information and machine learning advances our understanding of the infrared spectra of liquid biopsies, a framework that could be applied to probing of any disease.

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It's in your blood: spectral biomarker candidates for urinary bladder cancer from automated FTIR spectroscopy

Cited by 70 publications

References 37 publications

Infrared imaging in histopathology: Is a unified approach possible?

Infrared imaging in histopathology: Is a unified approach possible?

An infrared spectroscopic blood test for non-small cell lung carcinoma and subtyping into pulmonary squamous cell carcinoma or adenocarcinoma

Molecular Origin of Blood‐Based Infrared Spectroscopic Fingerprints**

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