Raman Microspectroscopic Evidence for the Metabolism of a Tyrosine Kinase Inhibitor, Neratinib, in Cancer Cells

Aljakouch, Karim; Lechtonen, Tatjana; Yosef, Hesham K.; Hammoud, Mohamad K.; Alsaidi, Wissam; Kötting, Carsten; Mügge, Carolin; Kourist, Robert; El-Mashtoly, Samir F.; Gerwert, Klaus

doi:10.1002/anie.201803394

Cited by 69 publications

(65 citation statements)

References 37 publications

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“…[6] By investigating the evolution of the Raman bands of the drug, the drug metabolites and the rest of the components, one can establish the composition ratio of the drug and the molecules which are affected by the drug. [7][8][9][10] Different biomolecules (i.e. proteins, carbohydrates, nucleic acids and lipids), as well as drugs, can present highly overlapped Raman signatures and thus, the spectra can be used for extracting information about the drug uptake and the phenotypic responses induced by the drug.…”

Section: Introductionmentioning

confidence: 99%

Data mining Raman microspectroscopic responses of cells to drugs in vitro using multivariate curve resolution-alternating least squares

Pérez-Guaita

Quintás

Farhane

et al. 2020

Talanta

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Raman microspectroscopy is gaining popularity for the analysis of time-dependent biological processes such as drug uptake and cellular response. It is a label-free technique which acquires signals from a large variety of components, including cell biomolecules and exogenous compounds such as drugs and nanoparticles, and is commonly employed for in vitro analysis of cells and cell populations with no labelling or staining required. By monitoring the changes to the Raman spectra of the cell as a result of a perturbing agent (e.g. inoculation of a drug or toxic agent), one can study the associated changes in cell biochemistry involved in both, the disruption and the subsequent cellular response. The main challenge is that the Raman spectra should be data mined in order to extract the information corresponding to the different actors involved on the process. Here, we study the application of multivariate curve resolution-alternating least squares (MCR-ALS) for extracting kinetic and biochemical information of time-dependent cellular processes. The technique allows the elucidation of the concentration profiles as well as the pure spectra of the components involved. Initially, we used Ordinary Differential Equations (ODE) to simulate drug uptake and 2 responses, which were employed to simulate perturbations to experimental control spectra, creating a dataset containing 36 simulated Raman spectra. Four different scenarios governing the drug exposure-response were evaluated: an undetectable disruption (e.g. radiation), a detectable disruption (e.g. a drug) and disruption with a signal significantly larger than the biological changes induced (e.g. a resonant drug), as well as simultaneous and asynchronous responses. Subsequently, data acquired from the exposure of a pulmonary adenocarcinoma cell line (A549) to Doxorubicin was analysed. The results indicate that MCR-ALS can independently identify and isolate both the spectra of the drug and the cell 2 responses under the different scenarios. The predicted concentrations map out the drug uptake and cellular response curves. The technique shows great potential to investigate non-linear kinetics and modes of action. Advantages and limitations of the technique are discussed, providing guidelines for future analysis strategies.

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Section: Introductionmentioning

confidence: 99%

Data mining Raman microspectroscopic responses of cells to drugs in vitro using multivariate curve resolution-alternating least squares

Pérez-Guaita

Quintás

Farhane

et al. 2020

Talanta

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“…However, the impedance magnitude is dependent not only on the number of cells but also the cell size and shape, and the cell-substrate attachment quality and may lead to misleading results 85 . In addition, Raman micro-spectroscopy has an advantage in comparison with RTCA, where Raman micro-spectroscopy can provide pharmacokinetic information such as label-free drug distribution and metabolism in cells 31 , 33 – 35 , 37 , 86 .…”

Section: Resultsmentioning

confidence: 99%

“…Raman micro-spectroscopy has been used for the diagnosis of cancer using tissue biopsies and body fluids 19 – 28 . It is also used to image cellular components and monitor the localization of drugs in cells 29 – 37 . Confocal Raman microscopy can provide a read-out of the integral and physiological biochemical status of cancer cells 10 – 17 .…”

Section: Introductionmentioning

confidence: 99%

Raman micro-spectroscopy monitors acquired resistance to targeted cancer therapy at the cellular level

Hammoud

Yosef

Lechtonen

et al. 2018

Sci Rep

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Monitoring the drug efficacy or resistance in vitro is usually carried out by measuring the response of single few proteins. However, observation of single proteins instead of an integral cell response may lead to results that are not consistent with patient’s response to a drug. We present a Raman spectroscopic method that detects the integral cell response to drugs such as tyrosine kinase inhibitors (TKIs). Non-small cell lung cancer (NSCLC) patients with EGFR mutations develop acquired resistance to first (erlotinib)- and third (osimertinib)-generation TKIs. Large erlotinib-induced differences were detected by Raman micro-spectroscopy in NSCLC cells without T790M EGFR mutation but not in cells with this mutation. Additionally, Raman difference spectra detected the response of NSCLC cells with T790M EGFR mutation to second- (neratinib) and third-generation (osimertinib) TKIs, and the resistance of cells with T790M/C797S EGFR mutation to osimertinib. Thus, the in vitro Raman results indicated that NSCLC cells with T790M and T790M/C797S EGFR mutations are resistant to erlotinib- and osimertinib, respectively, consistent with the observed responses of patients. This study shows the potential of Raman micro-spectroscopy to monitor drug resistance and opens a new door to in vitro companion diagnostics for screening personalized therapies.

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“…Alternatively to the (radio)labelled chemical probes, Raman spectroscopy, which observes the specific vibrational and rotational modes characteristic of a given small molecule, has been applied recently as a label-free imaging method to study the distribution and metabolism pathway of the tyrosine kinase inhibitor Neratinib in cancer cells [67]. As a result, applying this strategy to determine target engagement in cells is potentially feasible and should be observed in the near future.…”

Section: Raman and Fluorescence Spectroscopymentioning

confidence: 99%

Labelled Chemical Probes for Demonstrating Direct Target Engagement in Living Systems

Prevet

Collins

2019

Future Med. Chem.

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Demonstrating target engagement in living systems can help drive successful drug discovery. Target engagement and occupancy studies in cells confirm direct binding of a ligand to its intended target protein and provide the binding affinity. Combined with biomarkers to measure the functional consequences of target engagement, these experiments can increase confidence in the relationship between in vitro pharmacology and observed biological effects. In this review, we focus on chemically and radioactively labelled probes as key reagents for performing such experiments. Using recent examples, we examine how the labelled probes have been employed in combination with unlabelled ligands to quantify target engagement in cells and in animals. Finally, we consider future developments of this emerging methodology.

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Raman Microspectroscopic Evidence for the Metabolism of a Tyrosine Kinase Inhibitor, Neratinib, in Cancer Cells

Cited by 69 publications

References 37 publications

Data mining Raman microspectroscopic responses of cells to drugs in vitro using multivariate curve resolution-alternating least squares

Data mining Raman microspectroscopic responses of cells to drugs in vitro using multivariate curve resolution-alternating least squares

Raman micro-spectroscopy monitors acquired resistance to targeted cancer therapy at the cellular level

Labelled Chemical Probes for Demonstrating Direct Target Engagement in Living Systems

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