Kristine Glunde

Choline metabolism in malignant transformation

Abnormal choline metabolism is emerging as a metabolic hallmark that is associated with oncogenesis and tumour progression. Following transformation, the modulation of enzymes that control anabolic and catabolic pathways causes increased levels of choline-containing precursors and breakdown products of membrane phospholipids. These increased levels are associated with proliferation, and recent studies emphasize the complex reciprocal interactions between oncogenic signalling and choline metabolism. Because choline-containing compounds are detected by non-invasive magnetic resonance spectroscopy (MRS), increased levels of these compounds provide a non-invasive biomarker of transformation, staging and response to therapy. Furthermore, enzymes of choline metabolism, such as choline kinase, present novel targets for image-guided cancer therapy.

Molecular Causes of the Aberrant Choline Phospholipid Metabolism in Breast Cancer

Proton magnetic resonance spectroscopy (1H MRS) consistently detects significant differences in choline phospholipid metabolites of malignant versus benign breast lesions. It is critically important to understand the molecular causes underlying these metabolic differences, because this may identify novel targets for attack in cancer cells. In this study, differences in choline membrane metabolism were characterized in breast cancer cells and normal human mammary epithelial cells (HMECs) labeled with [1,2-13C]choline, using 1H and 13C magnetic resonance spectroscopy. Metabolic fluxes between membrane and water-soluble pool of choline-containing metabolites were assessed by exposing cells to [1,2-13C]choline for long and short periods of time to distinguish between catabolic and anabolic pathways in choline metabolism. Gene expression analysis using microarrays was performed to understand the molecular mechanisms underlying these changes. Breast cancer cells exhibited increased phosphocholine (PC; P < 0.001), total choline-containing metabolites (P < 0.01), and significantly decreased glycerophosphocholine (P < 0.05) compared with normal HMECs. Decreased 13C-enrichment was detected in choline (P < 0.001) and phosphocholine (P < 0.05, P < 0.001) of breast cancer cells compared with HMECs, indicating a higher metabolic flux from membrane phosphatidylcholine to choline and phosphocholine in breast cancer cells. Choline kinase and phospholipase C were significantly overexpressed, and lysophospholipase 1, phospholipase A2, and phospholipase D were significantly underexpressed, in breast cancer cells compared with HMECs. The magnetic resonance spectroscopy data indicated that elevated phosphocholine in breast cancer cells was primarily attributable to increased choline kinase activity and increased catabolism mediated by increased phospholipase C activity. These observations were consistent with the overexpression of choline kinase and phospholipase C detected in the microarray analyses.

Choline phospholipid metabolism: A target in cancer cells?

The experience of treating cancer over the past several decades overwhelmingly demonstrates that the disease continues to evade the vast array of drugs and treatment modalities available in the twenty‐first century. This is not surprising in view of the complexity of this disease, and the multiplicities of pathways available to the cancer cell to enable its survival. Although the progression of cancer arrives at a common end point of cachexia, organ failure, and death, common pathways are rare in cancer. Identifying and targeting common pathways that would act across these levels of multiplicity is essential for the successful treatment of this disease. Over the past decade, one common characteristic consistently revealed by magnetic resonance spectroscopic studies is the elevation of phosphocholine and total choline‐containing compounds in cancer cells and solid tumors. This elevation has been observed in almost every single cancer type studied with NMR spectroscopy and can be used as an endogenous biomarker of cancer. In this article, we have summarized some of the observations on the choline phospholipid metabolism of cancer cells and tumors, and make a case for targeting the aberrant choline phospholipid metabolism of cancer cells.

RNA Interference–Mediated Choline Kinase Suppression in Breast Cancer Cells Induces Differentiation and Reduces Proliferation

Choline kinase is overexpressed in breast cancer cells and activated by oncogenes and mitogenic signals, making it a potential target for cancer therapy. Here, we have examined, for the first time, the effects of RNA interference (RNAi)-mediated down-regulation of choline kinase in nonmalignant and malignant human breast epithelial cell lines using magnetic resonance spectroscopy (MRS) as well as molecular analyses of proliferation and differentiation markers. RNAi knockdown of choline kinase reduced proliferation, as detected by proliferating cell nuclear antigen and Ki-67 expression, and promoted differentiation, as detected by cytosolic lipid droplet formation and expression of galectin-3. The functional importance of RNAi-mediated choline kinase down-regulation on choline phospholipid metabolism was confirmed by the significant reduction of phosphocholine detected by MRS. These results strongly support the targeting of choline kinase in breast cancer cells with RNAi and show the potential ability of noninvasive MRS to detect and evaluate future treatments incorporating such strategies.

Choline metabolism in cancer: implications for diagnosis and therapy

Magnetic resonance studies from the last 10 years have conclusively demonstrated that choline metabolism is altered in a wide variety of cancers. In cancer, the choline metabolite profile is characterized by an elevation of phosphocholine and total choline-containing compounds. This elevation is increasingly being used as an endogenous biomarker of cancer. Importantly, the enzymes and pathways resulting in these distinct alterations in phosphocholine and total choline may provide novel molecular targets for specific, targeted anticancer therapies. In this article, we have summarized some of the magnetic resonance spectroscopy and positron emission tomography techniques that are currently available, or will be in the near future, for choline metabolism-based diagnosis, staging and therapy assessment in cancer patients. This review also outlines currently known molecular alterations that cause the aberrant choline metabolite profile in cancers and concludes with a summary of recent research findings that may, in the future, lead to novel anticancer therapies targeting choline metabolism.

Activation of Phosphatidylcholine Cycle Enzymes in Human Epithelial Ovarian Cancer Cells

Altered phosphatidylcholine (PC) metabolism in epithelial ovarian cancer (EOC) could provide choline-based imaging approaches as powerful tools to improve diagnosis and identify new therapeutic targets. The increase in the major choline-containing metabolite phosphocholine (PCho) in EOC compared with normal and nontumoral immortalized counterparts (EONT) may derive from (a) enhanced choline transport and choline kinase (ChoK)-mediated phosphorylation, (b) increased PC-specific phospholipase C (PC-plc) activity, and (c) increased intracellular choline production by PC deacylation plus glycerophosphocholine-phosphodiesterase (GPC-pd) or by phospholipase D (pld)-mediated PC catabolism followed by choline phosphorylation. Biochemical, protein, and mRNA expression analyses showed that the most relevant changes in EOC cells were (a) 12-fold to 25-fold ChoK activation, consistent with higher protein content and increased ChoKalpha (but not ChoKbeta) mRNA expression levels; and (b) 5-fold to 17-fold PC-plc activation, consistent with higher, previously reported, protein expression. PC-plc inhibition by tricyclodecan-9-yl-potassium xanthate (D609) in OVCAR3 and SKOV3 cancer cells induced a 30% to 40% reduction of PCho content and blocked cell proliferation. More limited and variable sources of PCho could derive, in some EOC cells, from 2-fold to 4-fold activation of pld or GPC-pd. Phospholipase A2 activity and isoform expression levels were lower or unchanged in EOC compared with EONT cells. Increased ChoKalpha mRNA, as well as ChoK and PC-plc protein expression, were also detected in surgical specimens isolated from patients with EOC. Overall, we showed that the elevated PCho pool detected in EOC cells primarily resulted from upregulation/activation of ChoK and PC-plc involved in PC biosynthesis and degradation, respectively.

Metabolic Tumor Imaging Using Magnetic Resonance Spectroscopy

The adaptability and the genomic plasticity of cancer cells, and the interaction between the tumor microenvironment and co-opted stromal cells, coupled with the ability of cancer cells to colonize distant organs, contribute to the frequent intractability of cancer. It is becoming increasingly evident that personalized molecular targeting is necessary for the successful treatment of this multifaceted and complex disease. Noninvasive imaging modalities such as magnetic resonance (MR), positron emission tomography (PET), and single-photon emission computed tomography (SPECT) are filling several important niches in this era of targeted molecular medicine, in applications that span from bench to bedside. In this review we focus on noninvasive magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) and their roles in future personalized medicine in cancer. Diagnosis, the identification of the most effective treatment, monitoring treatment delivery, and response to treatment are some of the broad areas into which MRS techniques can be integrated to improve treatment outcomes. The development of novel probes for molecular imaging--in combination with a slew of functional imaging capabilities--makes MRS techniques, especially in combination with other imaging modalities, valuable in cancer drug discovery and basic cancer research.

Mass spectrometry images acylcarnitines, phosphatidylcholines, and sphingomyelin in MDA-MB-231 breast tumor models

The lipid compositions of different breast tumor microenvironments are largely unknown due to limitations in lipid imaging techniques. Imaging lipid distributions would enhance our understanding of processes occurring inside growing tumors, such as cancer cell proliferation, invasion, and metastasis. Recent developments in MALDI mass spectrometry imaging (MSI) enable rapid and specific detection of lipids directly from thin tissue sections. In this study, we performed multimodal imaging of acylcarnitines, phosphatidylcholines (PC), a lysophosphatidylcholine (LPC), and a sphingomyelin (SM) from different microenvironments of breast tumor xenograft models, which carried tdTomato red fluorescent protein as a hypoxia-response element-driven reporter gene. The MSI molecular lipid images revealed spatially heterogeneous lipid distributions within tumor tissue. Four of the most-abundant lipid species, namely PC(16:0/16:0), PC(16:0/18:1), PC(18:1/18:1), and PC(18:0/18:1), were localized in viable tumor regions, whereas LPC(16:0/0:0) was detected in necrotic tumor regions. We identified a heterogeneous distribution of palmitoylcarnitine, stearoylcarnitine, PC(16:0/22:1), and SM(d18:1/16:0) sodium adduct, which colocalized primarily with hypoxic tumor regions. For the first time, we have applied a multimodal imaging approach that has combined optical imaging and MALDI-MSI with ion mobility separation to spatially localize and structurally identify acylcarnitines and a variety of lipid species present in breast tumor xenograft models

Concise Representation of Mass Spectrometry Images by Probabilistic Latent Semantic Analysis

Imaging mass spectrometry (IMS) is a promising technology which allows for detailed analysis of spatial distributions of (bio)molecules in organic samples. In many current applications, IMS relies heavily on (semi)automated exploratory data analysis procedures to decompose the data into characteristic component spectra and corresponding abundance maps, visualizing spectral and spatial structure. The most commonly used techniques are principal component analysis (PCA) and independent component analysis (ICA). Both methods operate in an unsupervised manner. However, their decomposition estimates usually feature negative counts and are not amenable to direct physical interpretation. We propose probabilistic latent semantic analysis (pLSA) for non-negative decomposition and the elucidation of interpretable component spectra and abundance maps. We compare this algorithm to PCA, ICA, and non-negative PARAFAC (parallel factors analysis) and show on simulated and real-world data that pLSA and non-negative PARAFAC are superior to PCA or ICA in terms of complementarity of the resulting components and reconstruction accuracy. We further combine pLSA decomposition with a statistical complexity estimation scheme based on the Akaike information criterion (AIC) to automatically estimate the number of components present in a tissue sample data set and show that this results in sensible complexity estimates.

Molecular and functional imaging of cancer: Advances in MRI and MRS

Publisher Summary This chapter presents an overview of the endogenous and exogenous magnetic resonance (MR) contrast mechanisms utilized in characterizing tumor vasculature. Every contrast mechanism for probing the tumor vasculature, including the use of exogenous MR contrast agents, is in some way a result of the changes in the MR signal intensity brought about by changes in tissue relaxation times. Noninvasive multinuclear magnetic resonance imaging (MRI) and MR spectroscopic imaging (MRSI) provide a wealth of spatial and temporal information on tumor vasculature, metabolism, and physiology. The most commonly used MR contrast agents (CA) are paramagnetic gadolinium chelates. These agents are tightly bound complexes of the rare earth element gadolinium and various chelating agents. A simple linear compartment model, describing uptake of the contrast agent from plasma, postulates a negligible reflux of the contrast agent from the interstitium back to the blood compartment. Blood concentrations of the CA can be approximated to be constant for the duration of the MR experiment, and under these conditions, contrast uptake is a linear function of time. The MR detection of cellular targets is also elaborated.