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Metabolites
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Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and...
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Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Endocrinology and Clinical Metabolic Research".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 24461

Special Issue Editor

Dr. Madhu Basetti

E-Mail Website
Guest Editor
Cancer Research UK Cambridge Institute, University of Cambridge, Robinson way, Cambridge CB2 ORE, UK
Interests: NMR; MRI; molecular imaging; cancer; metabolomics; bioinformatics; system biology; tumor metabolism
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Spatial and structural information of internal body tissues can be obtained by various imaging modalities, whereas spectroscopy methods are commonly used to probe their functional biochemistry and metabolism.

Multiscale imaging and spectroscopy modalities span the whole of the electromagnetic spectrum: Gamma rays (PET and SPECT), x-rays (X-ray and CT), the ultraviolet and optical region (bioluminescence, fluorescence and opto-acoustic imaging), infrared (thermal imaging, Raman imaging and spectroscopy), micro-waves (ESR/EPR) and radio-waves (NMR spectroscopy and MRI). Hyperpolarised 13C MRI and PET methods are used to study certain metabolic pathways in tissues depending on the tracers. For example, FDG-PET images are based on glycolytic pathway functions, while FLT-PET shows cell proliferation. DCE-MRI methods are useful in investigating the function of vasculature of the tumour. Several imaging modalities can probe tumour heterogeneity and their microenvironments. Many of these imaging modalities are now widely used in preclinical research and routine clinical diagnosis. NMR and Mass spectroscopy methods are commonly applied to study the biochemistry and metabolism of tumours. Other optical, infrared and Raman spectroscopy methods also used to study metabolism in cells and tissues.

Artificial intelligence methods, which have been gaining wide usage and popularity in recent times in various fields of science and technology, are also being used for imaging data analysis to evaluate a robust and unambiguous diagnosis of the disease.

This Special Issue of Metabolites is dedicated to state-of-the-art developments in imaging and spectroscopic methods and their applications in cancer research to better understand cancer biology and metabolism. These studies will be helpful for the prediction, early detection of cancer, tumour diagnosis, tumour progression (including metastasis) and prognosis of therapy.

Dr. Madhu Basetti
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • PET
  • CT
  • MRI
  • NMR
  • molecular imaging
  • optical imaging
  • opto-acoustic imaging
  • Raman imaging and spectroscopy
  • mass spectroscopy imaging
  • tumours
  • cancer
  • cancer metabolism
  • cancer biology
  • tumour microenvironment
  • tumour heterogeneity
  • metabolic pathways

Published Papers (9 papers)

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Editorial

Jump to: Research, Review, Other

6 pages, 1026 KiB  
Editorial
Imaging and Spectroscopic-Based Methods to Understand Cancer Metabolism and Biology
by Basetti Madhu
Metabolites 2023, 13(8), 940; https://doi.org/10.3390/metabo13080940 - 12 Aug 2023
Viewed by 838
Abstract
The results of publications in PubMed with the MeSH terms “cancer”, “biology”, “imaging and cancer”, “metabolism” and “spectroscopy” are shown in Figure 1 in the form of a Venn diagram [...] Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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Research

Jump to: Editorial, Review, Other

13 pages, 2159 KiB  
Article
Effect of Esomeprazole Treatment on Extracellular Tumor pH in a Preclinical Model of Prostate Cancer by MRI-CEST Tumor pH Imaging
by Pietro Irrera, Miriam Roberto, Lorena Consolino, Annasofia Anemone, Daisy Villano, Victor Navarro-Tableros, Antonella Carella, Walter Dastrù, Silvio Aime and Dario Livio Longo
Metabolites 2023, 13(1), 48; https://doi.org/10.3390/metabo13010048 - 28 Dec 2022
Cited by 5 | Viewed by 2529
Abstract
Novel anticancer treatments target the pH regulating system that plays a major role in tumor progression by creating an acidic microenvironment, although few studies have addressed their effect on tumor acidosis. In this study, we investigated in vivo several proton pump inhibitors (PPIs) [...] Read more.
Novel anticancer treatments target the pH regulating system that plays a major role in tumor progression by creating an acidic microenvironment, although few studies have addressed their effect on tumor acidosis. In this study, we investigated in vivo several proton pump inhibitors (PPIs) targeting NHE-1 (Amiloride and Cariporide) and V-ATPase (Esomeprazole and Lansoprazole) proton transporters in the DU145 androgen-insensitive human prostate cancer model. In cellulo results showed that DU145 are sensitive, with decreasing efficacy, to Amiloride, Esomeprazole and Lansoprazole, with marked cell toxicity both in normoxia and in hypoxia, with almost any change in pH. In vivo studies were performed upon administration of Esomeprazole to assess both the acute and chronic effects, and Iopamidol-based tumor pH imaging was performed to evaluate tumor acidosis. Although statistically significant tumor pH changes were observed a few hours after Esomeprazole administration in both the acute study and up to one week of treatment in the chronic study, longer treatment resulted in a lack of changes in tumor acidosis, which was associated to similar tumor growth curves between treated and control groups in both the subcutaneous and orthotopic models. Overall, this study highlights MRI-CEST tumor pH imaging as a valid approach to monitoring treatment response to PPIs. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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19 pages, 4054 KiB  
Article
Multiparametric Magnetic Resonance Imaging and Metabolic Characterization of Patient-Derived Xenograft Models of Clear Cell Renal Cell Carcinoma
by Joao Piraquive Agudelo, Deepti Upadhyay, Dalin Zhang, Hongjuan Zhao, Rosalie Nolley, Jinny Sun, Shubhangi Agarwal, Robert A. Bok, Daniel B. Vigneron, James D. Brooks, John Kurhanewicz, Donna M. Peehl and Renuka Sriram
Metabolites 2022, 12(11), 1117; https://doi.org/10.3390/metabo12111117 - 15 Nov 2022
Cited by 2 | Viewed by 1495
Abstract
Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are [...] Read more.
Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are needed to evaluate novel imaging and therapeutic approaches targeting metabolism. We characterized 5 PDX from high-grade or metastatic ccRCC by multiparametric magnetic resonance imaging (MRI) and steady state metabolic profiling and flux analysis. Similar to MRI of clinical ccRCC, T2-weighted images of orthotopic tumors of most PDX were homogeneous. The increased hyperintense (cystic) areas observed in one PDX mimicked the cystic phenotype typical of some RCC. The negligible hypointense (necrotic) areas of PDX grown under the highly vascularized renal capsule are beneficial for preclinical studies. Mean apparent diffusion coefficient (ADC) values were equivalent to those of ccRCC in human patients. Hyperpolarized (HP) [1-13C]pyruvate MRI of PDX showed high glycolytic activity typical of high-grade primary and metastatic ccRCC with considerable intra- and inter-tumoral variability, as has been observed in clinical HP MRI of ccRCC. Comparison of steady state metabolite concentrations and metabolic flux in [U-13C]glucose-labeled tumors highlighted the distinctive phenotypes of two PDX with elevated levels of numerous metabolites and increased fractional enrichment of lactate and/or glutamate, capturing the metabolic heterogeneity of glycolysis and the TCA cycle in clinical ccRCC. Culturing PDX cells and reimplanting to generate xenografts (XEN), or passaging PDX in vivo, altered some imaging and metabolic characteristics while transcription remained like that of the original PDX. These findings show that PDX are realistic models of ccRCC for imaging and metabolic studies but that the plasticity of metabolism must be considered when manipulating PDX for preclinical studies. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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10 pages, 1409 KiB  
Article
In Vivo Renal Lipid Quantification by Accelerated Magnetic Resonance Spectroscopic Imaging at 3T: Feasibility and Reliability Study
by Ahmad A. Alhulail, Mahsa Servati, Nathan Ooms, Oguz Akin, Alp Dincer, M. Albert Thomas, Ulrike Dydak and Uzay E. Emir
Metabolites 2022, 12(5), 386; https://doi.org/10.3390/metabo12050386 - 23 Apr 2022
Cited by 3 | Viewed by 2553
Abstract
A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used for accelerating the acquisition [...] Read more.
A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used for accelerating the acquisition of 48 × 48 voxels (each of 0.25 mL spatial resolution) without respiratory navigation implementations. The data were collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid–water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test–reposition–retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test–retest measurements showed a high degree of repeatability of MRSI-FF (CV = 4.3 ± 2.5%). Additionally, the matching level of the spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ± 6.4%). The MRSI acquisition duration was ~3 min only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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21 pages, 3277 KiB  
Article
A Spectroscopic Technique to Simultaneously Characterize Fatty Acid Uptake, Mitochondrial Activity, Vascularity, and Oxygen Saturation for Longitudinal Studies In Vivo
by Riley J. Deutsch, Victoria W. D’Agostino, Enakshi D. Sunassee, Michelle Kwan, Megan C. Madonna, Gregory Palmer, Brian T. Crouch and Nimmi Ramanujam
Metabolites 2022, 12(5), 369; https://doi.org/10.3390/metabo12050369 - 19 Apr 2022
Cited by 3 | Viewed by 2233
Abstract
Aggressive breast cancer has been shown to shift its metabolism towards increased lipid catabolism as the primary carbon source for oxidative phosphorylation. In this study, we present a technique to longitudinally monitor lipid metabolism and oxidative phosphorylation in pre-clinical tumor models to investigate [...] Read more.
Aggressive breast cancer has been shown to shift its metabolism towards increased lipid catabolism as the primary carbon source for oxidative phosphorylation. In this study, we present a technique to longitudinally monitor lipid metabolism and oxidative phosphorylation in pre-clinical tumor models to investigate the metabolic changes with mammary tissue development and characterize metabolic differences between primary murine breast cancer and normal mammary tissue. We used optical spectroscopy to measure the signal of two simultaneously injected exogenous fluorescent metabolic reporters: TMRE (oxidative phosphorylation surrogate) and Bodipy FL C16 (lipid catabolism surrogate). We leverage an inverse Monte Carlo algorithm to correct for aberrations resulting from tissue optical properties and to extract vascular endpoints relevant to oxidative metabolism, specifically oxygen saturation (SO2) and hemoglobin concentration ([Hb]). We extensively validated our optical method to demonstrate that our two fluorescent metabolic endpoints can be measured without chemical or optical crosstalk and that dual measurements of both fluorophores in vivo faithfully recapitulate the measurements of each fluorophore independently. We then applied our method to track the metabolism of growing 4T1 and 67NR breast tumors and aging mammary tissue, all highly metabolic tissue types. Our results show the changes in metabolism as a function of mammary age and tumor growth, and these changes can be best distinguished through the combination of endpoints measured with our system. Clustering analysis incorporating both Bodipy FL C16 and TMRE endpoints combined with either SO2 or [Hb] proved to be the most effective in minimizing intra-group variance and maximizing inter-group differences. Our platform can be extended to applications in which long-term metabolic flexibility is important to study, for example in tumor regression, recurrence following dormancy, and responses to cancer treatment. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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Review

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24 pages, 5134 KiB  
Review
EPR and Related Magnetic Resonance Imaging Techniques in Cancer Research
by Yoichi Takakusagi, Ryoma Kobayashi, Keita Saito, Shun Kishimoto, Murali C. Krishna, Ramachandran Murugesan and Ken-ichiro Matsumoto
Metabolites 2023, 13(1), 69; https://doi.org/10.3390/metabo13010069 - 01 Jan 2023
Cited by 4 | Viewed by 2296
Abstract
Imaging tumor microenvironments such as hypoxia, oxygenation, redox status, and/or glycolytic metabolism in tissues/cells is useful for diagnostic and prognostic purposes. New imaging modalities are under development for imaging various aspects of tumor microenvironments. Electron Paramagnetic Resonance Imaging (EPRI) though similar to NMR/MRI [...] Read more.
Imaging tumor microenvironments such as hypoxia, oxygenation, redox status, and/or glycolytic metabolism in tissues/cells is useful for diagnostic and prognostic purposes. New imaging modalities are under development for imaging various aspects of tumor microenvironments. Electron Paramagnetic Resonance Imaging (EPRI) though similar to NMR/MRI is unique in its ability to provide quantitative images of pO2 in vivo. The short electron spin relaxation times have been posing formidable challenge to the technology development for clinical application. With the availability of the narrow line width trityl compounds, pulsed EPR imaging techniques were developed for pO2 imaging. EPRI visualizes the exogenously administered spin probes/contrast agents and hence lacks the complementary morphological information. Dynamic nuclear polarization (DNP), a phenomenon that transfers the high electron spin polarization to the surrounding nuclear spins (1H and 13C) opened new capabilities in molecular imaging. DNP of 13C nuclei is utilized in metabolic imaging of 13C-labeled compounds by imaging specific enzyme kinetics. In this article, imaging strategies mapping physiologic and metabolic aspects in vivo are reviewed within the framework of their application in cancer research, highlighting the potential and challenges of each of them. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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16 pages, 2435 KiB  
Review
Review on Multispectral Photoacoustic Analysis of Cancer: Thyroid and Breast
by Seongyi Han, Haeni Lee, Chulhong Kim and Jeesu Kim
Metabolites 2022, 12(5), 382; https://doi.org/10.3390/metabo12050382 - 22 Apr 2022
Cited by 12 | Viewed by 2435
Abstract
In recent decades, photoacoustic imaging has been used widely in biomedical research, providing molecular and functional information from biological tissues in vivo. In addition to being used for research in small animals, photoacoustic imaging has also been utilized for in vivo human studies, [...] Read more.
In recent decades, photoacoustic imaging has been used widely in biomedical research, providing molecular and functional information from biological tissues in vivo. In addition to being used for research in small animals, photoacoustic imaging has also been utilized for in vivo human studies, achieving a multispectral photoacoustic response in deep tissue. There have been several clinical trials for screening cancer patients by analyzing multispectral responses, which in turn provide metabolomic information about the underlying biological tissues. This review summarizes the methods and results of clinical photoacoustic trials available in the literature to date to classify cancerous tissues, specifically of the thyroid and breast. From the review, we can conclude that a great potential exists for photoacoustic imaging to be used as a complementary modality to improve diagnostic accuracy for suspicious tumors, thus significantly benefitting patients’ healthcare. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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23 pages, 3088 KiB  
Review
Magnetic Resonance Imaging (MRI) and MR Spectroscopic Methods in Understanding Breast Cancer Biology and Metabolism
by Uma Sharma and Naranamangalam R. Jagannathan
Metabolites 2022, 12(4), 295; https://doi.org/10.3390/metabo12040295 - 27 Mar 2022
Cited by 18 | Viewed by 5555
Abstract
A common malignancy that affects women is breast cancer. It is the second leading cause of cancer-related death among women. Metabolic reprogramming occurs during cancer growth, invasion, and metastases. Functional magnetic resonance (MR) methods comprising an array of techniques have shown potential for [...] Read more.
A common malignancy that affects women is breast cancer. It is the second leading cause of cancer-related death among women. Metabolic reprogramming occurs during cancer growth, invasion, and metastases. Functional magnetic resonance (MR) methods comprising an array of techniques have shown potential for illustrating physiological and molecular processes changes before anatomical manifestations on conventional MR imaging. Among these, in vivo proton (1H) MR spectroscopy (MRS) is widely used for differentiating breast malignancy from benign diseases by measuring elevated choline-containing compounds. Further, the use of hyperpolarized 13C and 31P MRS enhanced the understanding of glucose and phospholipid metabolism. The metabolic profiling of an array of biological specimens (intact tissues, tissue extracts, and various biofluids such as blood, urine, nipple aspirates, and fine needle aspirates) can also be investigated through in vitro high-resolution NMR spectroscopy and high-resolution magic angle spectroscopy (HRMAS). Such studies can provide information on more metabolites than what is seen by in vivo MRS, thus providing a deeper insight into cancer biology and metabolism. The analysis of a large number of NMR spectral data sets through multivariate statistical methods classified the tumor sub-types. It showed enormous potential in the development of new therapeutic approaches. Recently, multiparametric MRI approaches were found to be helpful in elucidating the pathophysiology of cancer by quantifying structural, vasculature, diffusion, perfusion, and metabolic abnormalities in vivo. This review focuses on the applications of NMR, MRS, and MRI methods in understanding breast cancer biology and in the diagnosis and therapeutic monitoring of breast cancer. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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Other

23 pages, 1837 KiB  
Hypothesis
Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives
by Ana Paula Candiota and Carles Arús
Metabolites 2022, 12(3), 243; https://doi.org/10.3390/metabo12030243 - 14 Mar 2022
Cited by 2 | Viewed by 2780
Abstract
This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the [...] Read more.
This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients. Full article
(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)
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