Reflection and Reaction

Choline kinase alpha in cancer prognosis and treatment

Fine needle aspiration (FNA) cytology has been widely used for pathologic assessment of breast lesions. However, the examination suffers a risk of false-negative results owing to insufficient sample volumes, inaccurate sampling positions, nondefinitive cytologic features, or suboptimal cell preservation. One approach to improve its accuracy is using modern mass spectrometry to detect disease biomarkers, of which the tissue samples are collected through FNA.

The biological compounds in the FNA tissue samples were extracted and characterized by matrix-assisted laser desorption ionization time-of-flight/mass spectrometry (MALDI-TOF/MS). The results were further analyzed by principal component analysis. Distribution of lipid biomarkers on tissues was explored by imaging mass spectrometry.

Lipid profiles of the tissue samples collected by FNA were rapidly obtained through MALDI-TOF/MS analysis. Phosphatidylcholines and triacylglycerols were detected as the predominant compounds in cancerous and normal regions, respectively. The samples were clearly classified by principal component analysis, based on the differences in their lipid profiles. Different lipid patterns were clearly viewed through the molecular imaging of normal and tumorous regions of breast tissue samples.

The FNA-MALDI-TOF/MS approach can provide complementary information for pathological examinations and improve the accuracy of breast cancer diagnoses. Owing to the ease of operation and automation, it is possible to efficiently screen the lipid biomarkers in a large number of tissue samples by means of MALDI-TOF/MS.

Lung cancer is currently the leading cause of cancer-related mortality worldwide. It is, therefore, important to enhance understanding and add a new auxiliary detection tool of lung cancer. In this work, serum metabolic characteristics of lung cancer were investigated with a non-targeted metabolomics method. The metabolic profiling of 23 patients with lung cancer and 23 healthy controls were analyzed using ultra high performance liquid chromatography/quadrupole time of flight mass spectrometry (UPLC/Q-TOF MS). Partial least squares discriminant analysis (PLS-DA) model of the metabolic data allowed the clear separation of the lung cancer patients from the healthy controls. In total, 27 differential metabolites were identified, which were mostly related to the perturbation of lipid metabolism, including choline, free fatty acids, lysophosphatidylcholines, etc. Choline and linoleic acid were defined as one combinational biomarker using binary logistic regression, which was supported by the validation with a smaller sample-set (9 patients and 9 healthy controls). These findings show that LC/MS-based serum metabolic profiling has potential application in complementary identification of lung cancer patients, and could be a powerful tool for cancer research.

Magic angle spinning nuclear magnetic resonance (MAS-NMR) spectroscopy offers a convenient means for the rapid determination of metabolic profiles from intact malignant tissues with high resolution. The implementation of MAS-NMR spectroscopy requires minimal sample processing, hence being compatible with complementary histological or biochemical analyses. The metabolites routinely detected in ¹H MAS-NMR spectra can simultaneously inform on many of the metabolic alterations that characterize malignant cells, including altered choline metabolism and the so-called Warburg effect. Clinical MAS-NMR profiles have been attributed with diagnostic or prognostic value, correlating to disease subtype, tumor stage/grade, response to chemotherapy, and patient survival. Herein, the scientific rationale behind MAS-NMR and its utility for translational cancer research and patient stratification is summarized. Moreover, a basic protocol for the analysis of tumor samples by MAS-NMR spectroscopy is detailed.

To investigate which transmembrane choline transporters and intracellular choline kinases play a prominent role at gene expression level in the rise of the total choline (tCho) peak at proton MR spectra in a rodent rhabdomyosarcoma model.

Twenty-two rats bearing grafted bilateral syngenic rhabdomyosarcoma were examined on a clinical 3 T MR system. Total choline concentration was measured from proton MR spectra using cubic centimeter volumes of interest (VOIs) located contiguously along the greater axis of the tumour. After euthanasia, cubic centimetre tissue specimens corresponding to Proton magnetic resonance spectroscopy (H-MRS) VOIs were frozen in liquid nitrogen. Out of 89 H-MRS voxels, only 39 with a corresponding tissue specimen suitable for biochemical processing were included in the analysis. RNA was extracted from all the 39 samples and reverse-transcribed into cDNA. Choline kinase α and β gene expression as well as genes of the transmembrane transporters OCT1, OCT2, OCT3, CTL1, CTL3, CTL4 and CHT1 were studied using reverse transcriptase polymerase chain reaction. The expression level of each gene (ΔCt), was normalized referred to that of the RPL19 gene. The Spearman rank correlation coefficient was used to analyse variables.

There was no overexpression of genes coding for kinases; however, significant correlation was observed between kinase α sub-type and the tCho peak (P=.002; r=0.51). OCT1 was the most overexpressed transporter gene. Less overexpressed CTL1 gene was significantly correlated with the tCho peak (P=.02; r=0.38).

Choline transporters seem to play a predominant role in the increase in total choline concentration at the gene expression level in our model.

Positron emission tomography (PET) is a nuclear medicine modality which provides quantitative images of biological processes in vivo at the molecular level. Several PET radiopharmaceuticals labeled with short-lived isotopes such as ¹⁸F and ¹¹C were developed in order to trace specific cellular and molecular pathways with the aim of enhancing clinical applications. Among these [¹¹C]radiopharmaceuticals are N-[¹¹C]methyl-choline ([¹¹C]choline), l-(S-methyl-[¹¹C])methionine ([¹¹C]methionine) and 1-[¹¹C]acetate ([¹¹C]acetate), which have gained an important role in oncology where the application of 2-[¹⁸F]fluoro-2-deoxy-d-glucose ([¹⁸F]FDG) is suboptimal. Nevertheless, the production of these radiopharmaceuticals did not reach the same level of standardization as for [¹⁸F]FDG synthesis. This review describes the most recent developments in the synthesis of the above-mentioned [¹¹C]radiopharmaceuticals aiming to increase the availability and hence the use of [¹¹C]choline, [¹¹C]methionine and [¹¹C]acetate in clinical practice.

Mass spectrometric imaging allows the investigation of the spatial distribution of molecules at complex surfaces. The combination of molecular speciation with local analysis renders a chemical microscope that can be used for the direct biomolecular characterization of histological tissue surfaces. MS based imaging advantageously allows label-free detection and mapping of a wide-range of biological compounds whose presence or absence can be the direct result of disease pathology. Successful detection of the analytes of interest at the desired spatial resolution requires careful attention to several steps in the mass spectrometry imaging protocol. This review will describe and discuss a selected number of crucial developments in ionization, instrumentation, and application of this innovative technology. The focus of this review is on the latest developments in imaging MS. Selected biological applications are employed to illustrate some of the novel features discussed. Two commonly used MS imaging techniques, secondary ion mass spectrometric (SIMS) imaging and matrix-assisted laser desorption ionization (MALDI) mass spectrometric imaging, center this review. New instrumental developments are discussed that extend spatial resolution, mass resolving power, mass accuracy, tandem-MS capabilities, and offer new gas-phase separation capabilities for both imaging techniques. It will be shown how the success of MS imaging is crucially dependent on sample preparation protocols as they dictate the nature and mass range of detected biomolecules that can be imaged. Finally, developments in data analysis strategies for large imaging datasets will be briefly discussed.