First-in-Human PET Imaging and Estimated Radiation Dosimetry of l-[5-11C]-Glutamine in Patients with Metastatic Colorectal Cancer

Clinical research framework proposal for ketogenic metabolic therapy in glioblastoma

Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with a universally lethal prognosis despite maximal standard therapies. Here, we present a consensus treatment protocol based on the metabolic requirements of GBM cells for the two major fermentable fuels: glucose and glutamine. Glucose is a source of carbon and ATP synthesis for tumor growth through glycolysis, while glutamine provides nitrogen, carbon, and ATP synthesis through glutaminolysis. As no tumor can grow without anabolic substrates or energy, the simultaneous targeting of glycolysis and glutaminolysis is expected to reduce the proliferation of most if not all GBM cells. Ketogenic metabolic therapy (KMT) leverages diet-drug combinations that inhibit glycolysis, glutaminolysis, and growth signaling while shifting energy metabolism to therapeutic ketosis. The glucose-ketone index (GKI) is a standardized biomarker for assessing biological compliance, ideally via real-time monitoring. KMT aims to increase substrate competition and normalize the tumor microenvironment through GKI-adjusted ketogenic diets, calorie restriction, and fasting, while also targeting glycolytic and glutaminolytic flux using specific metabolic inhibitors. Non-fermentable fuels, such as ketone bodies, fatty acids, or lactate, are comparatively less efficient in supporting the long-term bioenergetic and biosynthetic demands of cancer cell proliferation. The proposed strategy may be implemented as a synergistic metabolic priming baseline in GBM as well as other tumors driven by glycolysis and glutaminolysis, regardless of their residual mitochondrial function. Suggested best practices are provided to guide future KMT research in metabolic oncology, offering a shared, evidence-driven framework for observational and interventional studies.

Recent advancements in new tracers from first-in-human studies

Recent advancements in the development of positron emission tomography (PET) tracers have significantly enhanced our ability to image neuroinflammatory processes and neurotransmitter systems, which are vital for understanding and treating neurodegenerative and psychiatric disorders. Similarly, innovative tracers in oncology provide detailed images of the metabolic and molecular characteristics of tumors, which are crucial for tailoring targeted therapies and monitoring responses, including radiotherapy. Notable advancements include programmed death ligand 1 (PD-L1)-targeting agents for lung cancer, prostate-specific membrane antigen-based tracers for prostate cancer, chemokine receptor-targeting agents for hematological malignancies, human epidermal growth factor receptor 2 (HER2)-targeting tracers for various cancers, Claudin 18 based tracers for epithelial tumors, glutamine tracers for colorectal cancer, and ascorbic acid analogs for assessing cancer metabolism and therapy efficacy. Additionally, novel tracers have been developed for non-neurological and non-oncological applications, including adrenal imaging, amyloidosis, and human immunodeficiency virus (HIV) infection. This overview focuses on the newly developed tracers, particularly those used in neurology and oncology.

Identification of glutamine metabolism-related gene signature to predict colorectal cancer prognosis

Backgrounds: Colorectal cancer (CRC) is a highly malignant gastrointestinal malignancy with a poor prognosis, which imposes a significant burden on patients and healthcare providers globally. Previous studies have established that genes related to glutamine metabolism play a crucial role in the development of CRC. However, no studies have yet explored the prognostic significance of these genes in CRC. Methods: CRC patient data were downloaded from The Cancer Genome Atlas (TCGA), while glutamine metabolism-related genes were obtained from the Molecular Signatures Database (MSigDB) database. Univariate COX regression analysis and LASSO Cox regression were utilized to identify 15 glutamine metabolism-related genes associated with CRC prognosis. The risk scores were calculated and stratified into high-risk and low-risk groups based on the median risk score. The model's efficacy was assessed using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curve analysis. Cox regression analysis was employed to determine the risk score as an independent prognostic factor for CRC. Differential immune cell infiltration between the high-risk and low-risk groups was assessed using the ssGSEA method. The clinical applicability of the model was validated by constructing nomograms based on age, gender, clinical staging, and risk scores. Immunohistochemistry (IHC) was used to detect the expression levels of core genes. Results: We identified 15 genes related to glutamine metabolism in CRC: NLGN1, RIMKLB, UCN, CALB1, SYT4, WNT3A, NRCAM, LRFN4, PHGDH, GRM1, CBLN1, NRG1, GLYATL1, CBLN2, and VWC2. Compared to the high-risk group, the low-risk group demonstrated longer overall survival (OS) for CRC. Clinical correlation analysis revealed a positive correlation between the risk score and the clinical stage and TNM stage of CRC. Immune correlation analysis indicated a predominance of Th2 cells in the low-risk group. The nomogram exhibited excellent discriminatory ability for OS in CRC. Immunohistochemistry revealed that the core gene CBLN1 was expressed at a lower level in CRC, while GLYATL1 was expressed at a higher level. Conclusions: In summary, we have successfully identified and comprehensively analyzed a gene signature associated with glutamine metabolism in CRC for the first time. This gene signature consistently and reliably predicts the prognosis of CRC patients, indicating its potential as a metabolic target for individuals with CRC.

Noninvasive Stratification of Colon Cancer by Multiplex PET Imaging

PURPOSE

The current approach for molecular subtyping of colon cancer relies on gene expression profiling, which is invasive and has limited ability to reveal dynamics and spatial heterogeneity. Molecular imaging techniques, such as PET, present a noninvasive alternative for visualizing biological information from tumors. However, the factors influencing PET imaging phenotype, the suitable PET radiotracers for differentiating tumor subtypes, and the relationship between PET phenotypes and tumor genotype or gene expression-based subtyping remain unknown.

EXPERIMENTAL DESIGN

In this study, we conducted 126 PET scans using four different metabolic PET tracers, [18F]fluorodeoxy-D-glucose ([18F]FDG), O-(2-[18F]fluoroethyl)-l-tyrosine ([18F]FET), 3'-deoxy-3'-[18F]fluorothymidine ([18F]FLT), and [11C]acetate ([11C]ACE), using a spectrum of five preclinical colon cancer models with varying genetics (BMT, AKPN, AK, AKPT, KPN), at three sites (subcutaneous, orthograft, autochthonous) and at two tumor stages (primary vs. metastatic).

RESULTS

The results demonstrate that imaging signatures are influenced by genotype, tumor environment, and stage. PET imaging signatures exhibited significant heterogeneity, with each cancer model displaying distinct radiotracer profiles. Oncogenic Kras and Apc loss showed the most distinctive imaging features, with [18F]FLT and [18F]FET being particularly effective, respectively. The tissue environment notably impacted [18F]FDG uptake, and in a metastatic model, [18F]FET demonstrated higher uptake.

CONCLUSIONS

By examining factors contributing to PET-imaging phenotype, this study establishes the feasibility of noninvasive molecular stratification using multiplex radiotracer PET. It lays the foundation for further exploration of PET-based subtyping in human cancer, thereby facilitating noninvasive molecular diagnosis.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Radiosynthesis, Preclinical, and Clinical Positron Emission Tomography Studies of Carbon-11 Labeled Endogenous and Natural Exogenous Compounds

The presence of positron emission tomography (PET) centers at most major hospitals worldwide, along with the improvement of PET scanner sensitivity and the introduction of total body PET systems, has increased the interest in the PET tracer development using the short-lived radionuclides carbon-11. In the last few decades, methodological improvements and fully automated modules have allowed the development of carbon-11 tracers for clinical use. Radiolabeling natural compounds with carbon-11 by substituting one of the backbone carbons with the radionuclide has provided important information on the biochemistry of the authentic compounds and increased the understanding of their in vivo behavior in healthy and diseased states. The number of endogenous and natural compounds essential for human life is staggering, ranging from simple alcohols to vitamins and peptides. This review collates all the carbon-11 radiolabeled endogenous and natural exogenous compounds synthesised to date, including essential information on their radiochemistry methodologies and preclinical and clinical studies in healthy subjects.

18F-Fluciclovine PET Imaging of Glutaminase Inhibition in Breast Cancer Models

Aggressive cancers such as triple-negative breast cancer (TNBC) avidly metabolize glutamine as a feature of their malignant phenotype. The conversion of glutamine to glutamate by the glutaminase enzyme represents the first and rate-limiting step of this pathway and a target for drug development. Indeed, a novel glutaminase inhibitor (GLSi) has been developed and tested in clinical trials but with limited success, suggesting the potential for a biomarker to select patients who could benefit from this novel therapy. Here, we studied a nonmetabolized amino acid analog, ¹⁸F-fluciclovine, as a PET imaging biomarker for detecting the pharmacodynamic response to GLSi. Methods: Uptake of ¹⁸F-fluciclovine into human breast cancer cells was studied in the presence and absence of inhibitors of glutamine transporters and GLSi. To allow ¹⁸F-fluciclovine PET to be performed on mice, citrate in the tracer formulation is replaced by phosphate-buffered saline. Mice bearing triple-negative breast cancer (TNBC) xenografts (HCC38, HCC1806, and MBA-MD-231) and estrogen receptor-positive breast cancer xenografts (MCF-7) were imaged with dynamic PET at baseline and after a 2-d treatment of GLSi (CB839) or vehicle. Kinetic analysis suggested reversible uptake of the tracer, and the distribution volume (V_D) of ¹⁸F-fluciclovine was estimated by Logan plot analysis. Results: Our data showed that cellular uptake of ¹⁸F-fluciclovine is mediated by glutamine transporters. A significant increase in V_D was observed after CB839 treatment in TNBC models exhibiting high glutaminase activity (HCC38 and HCC1806) but not in TNBC or MCF-7 exhibiting low glutaminase. Changes in V_D were corroborated with changes in GLS activity measured in tumors treated with CB839 versus vehicle, as well as with changes in V_D of ¹⁸F-(2S,R4)-fluoroglutamine, which we previously validated as a measure of cellular glutamine pool size. A moderate, albeit significant, decrease in ¹⁸F-FDG PET signal was observed in HCC1806 tumors after CB839 treatment. Conclusion: ¹⁸F-fluciclovine PET has potential to serve as a clinically translatable pharmacodynamic biomarker of GLSi.

In vivo characterization of glutamine metabolism identifies therapeutic targets in clear cell renal cell carcinoma

Targeting metabolic vulnerabilities has been proposed as a therapeutic strategy in renal cell carcinoma (RCC). Here, we analyzed the metabolism of patient-derived xenografts (tumorgrafts) from diverse subtypes of RCC. Tumorgrafts from VHL-mutant clear cell RCC (ccRCC) retained metabolic features of human ccRCC and engaged in oxidative and reductive glutamine metabolism. Genetic silencing of isocitrate dehydrogenase-1 or isocitrate dehydrogenase-2 impaired reductive labeling of tricarboxylic acid (TCA) cycle intermediates in vivo and suppressed growth of tumors generated from tumorgraft-derived cells. Glutaminase inhibition reduced the contribution of glutamine to the TCA cycle and resulted in modest suppression of tumorgraft growth. Infusions with [amide-15N]glutamine revealed persistent amidotransferase activity during glutaminase inhibition, and blocking these activities with the amidotransferase inhibitor JHU-083 also reduced tumor growth in both immunocompromised and immunocompetent mice. We conclude that ccRCC tumorgrafts catabolize glutamine via multiple pathways, perhaps explaining why it has been challenging to achieve therapeutic responses in patients by inhibiting glutaminase.

Lipid droplets and ferroptosis as new players in brain cancer glioblastoma progression and therapeutic resistance

A primary brain tumor glioblastoma is the most lethal of all cancers and remains an extremely challenging disease. Apparent oncogenic signaling in glioblastoma is genetically complex and raised at any stage of the disease's progression. Many clinical trials have shown that anticancer drugs for any specific oncogene aberrantly expressed in glioblastoma show very limited activity. Recent discoveries have highlighted that alterations in tumor metabolism also contribute to disease progression and resistance to current therapeutics for glioblastoma, implicating an alternative avenue to improve outcomes in glioblastoma patients. The roles of glucose, glutamine and tryptophan metabolism in glioblastoma pathogenesis have previously been described. This article provides an overview of the metabolic network and regulatory changes associated with lipid droplets that suppress ferroptosis. Ferroptosis is a newly discovered type of nonapoptotic programmed cell death induced by excessive lipid peroxidation. Although few studies have focused on potential correlations between tumor progression and lipid droplet abundance, there has recently been increasing interest in identifying key players in lipid droplet biology that suppress ferroptosis and whether these dependencies can be effectively exploited in cancer treatment. This article discusses how lipid droplet metabolism, including lipid synthesis, storage, and use modulates ferroptosis sensitivity or tolerance in different cancer models, focusing on glioblastoma.

Application of Metabolic Reprogramming to Cancer Imaging and Diagnosis

Cellular metabolism governs the signaling that supports physiological mechanisms and homeostasis in an individual, including neuronal transmission, wound healing, and circadian clock manipulation. Various factors have been linked to abnormal metabolic reprogramming, including gene mutations, epigenetic modifications, altered protein epitopes, and their involvement in the development of disease, including cancer. The presence of multiple distinct hallmarks and the resulting cellular reprogramming process have gradually revealed that these metabolism-related molecules may be able to be used to track or prevent the progression of cancer. Consequently, translational medicines have been developed using metabolic substrates, precursors, and other products depending on their biochemical mechanism of action. It is important to note that these metabolic analogs can also be used for imaging and therapeutic purposes in addition to competing for metabolic functions. In particular, due to their isotopic labeling, these compounds may also be used to localize and visualize tumor cells after uptake. In this review, the current development status, applicability, and limitations of compounds targeting metabolic reprogramming are described, as well as the imaging platforms that are most suitable for each compound and the types of cancer to which they are most appropriate.

PET Oncological Radiopharmaceuticals: Current Status and Perspectives

Molecular imaging is the visual representation of biological processes that take place at the cellular or molecular level in living organisms. To date, molecular imaging plays an important role in the transition from conventional medical practice to precision medicine. Among all imaging modalities, positron emission tomography (PET) has great advantages in sensitivity and the ability to obtain absolute imaging quantification after corrections for photon attenuation and scattering. Due to the ability to label a host of unique molecules of biological interest, including endogenous, naturally occurring substrates and drug-like compounds, the role of PET has been well established in the field of molecular imaging. In this article, we provide an overview of the recent advances in the development of PET radiopharmaceuticals and their clinical applications in oncology.

Positron emission tomography molecular imaging-based cancer phenotyping

During the past several decades, numerous studies have provided insights into biological characteristics of cancer cells and identified various hallmarks of cancer acquired in the tumorigenic processes. However, it is still challenging to image these distinctive traits of cancer to facilitate the management of patients in clinical settings. The rapidly evolving field of positron emission tomography (PET) imaging has provided opportunities to investigate cancer's biological characteristics in vivo. This article reviews the current status of PET imaging on characterizing hallmarks of cancer and discusses the future directions of PET imaging strategies facilitating in vivo cancer phenotyping.

Aspirin sensitivity of PIK3CA-mutated Colorectal Cancer: potential mechanisms revisited

PIK3CA mutations are amongst the most prevalent somatic mutations in cancer and are associated with resistance to first-line treatment along with low survival rates in a variety of malignancies. There is evidence that patients carrying PIK3CA mutations may benefit from treatment with acetylsalicylic acid, commonly known as aspirin, particularly in the setting of colorectal cancer. In this regard, it has been clarified that Class IA Phosphatidylinositol 3-kinases (PI3K), whose catalytic subunit p110α is encoded by the PIK3CA gene, are involved in signal transduction that regulates cell cycle, cell growth, and metabolism and, if disturbed, induces carcinogenic effects. Although PI3K is associated with pro-inflammatory cyclooxygenase-2 (COX-2) expression and signaling, and COX-2 is among the best-studied targets of aspirin, the mechanisms behind this clinically relevant phenomenon are still unclear. Indeed, there is further evidence that the protective, anti-carcinogenic effect of aspirin in this setting may be mediated in a COX-independent manner. However, until now the understanding of aspirin's prostaglandin-independent mode of action is poor. This review will provide an overview of the current literature on this topic and aims to analyze possible mechanisms and targets behind the aspirin sensitivity of PIK3CA-mutated cancers.

Structured reporting of computed tomography in the staging of colon cancer: a Delphi consensus proposal

BACKGROUND

Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in colon cancer during the staging phase in order to improve communication between the radiologist, members of multidisciplinary teams and patients.

MATERIALS AND METHODS

A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation.

RESULTS

The final SR version was built by including n = 18 items in the "Patient Clinical Data" section, n = 7 items in the "Clinical Evaluation" section, n = 9 items in the "Imaging Protocol" section and n = 29 items in the "Report" section. Overall, 63 items were included in the final version of the SR. Both in the first and second round, all sections received a higher than good rating: a mean value of 4.6 and range 3.6-4.9 in the first round; a mean value of 5.0 and range 4.9-5 in the second round. In the first round, Cronbach's alpha (Cα) correlation coefficient was a questionable 0.61. In the first round, the overall mean score of the experts and the sum of scores for the structured report were 4.6 (range 1-5) and 1111 (mean value 74.07, STD 4.85), respectively. In the second round, Cronbach's alpha (Cα) correlation coefficient was an acceptable 0.70. In the second round, the overall mean score of the experts and the sum of score for structured report were 4.9 (range 4-5) and 1108 (mean value 79.14, STD 1.83), respectively. The overall mean score obtained by the experts in the second round was higher than the overall mean score of the first round, with a lower standard deviation value to underline greater agreement among the experts for the structured report reached in this round.

CONCLUSIONS

A wide implementation of SR is of critical importance in order to offer referring physicians and patients optimum quality of service and to provide researchers with the best quality data in the context of big data exploitation of available clinical data. Implementation is a complex procedure, requiring mature technology to successfully address the multiple challenges of user-friendliness, organization and interoperability.

Glutamine Imaging: A New Avenue for Glioma Management

The glutamine pathway is emerging as an important marker of cancer prognosis and a target for new treatments. In gliomas, the most common type of brain tumors, metabolic reprogramming leads to abnormal consumption of glutamine as an energy source, and increased glutamine concentrations are associated with treatment resistance and proliferation. A key challenge in the development of glutamine-based biomarkers and therapies is the limited number of in vivo tools to noninvasively assess local glutamine metabolism and monitor its changes. In this review, we describe the importance of glutamine metabolism in gliomas and review the current landscape of translational and emerging imaging techniques to measure glutamine in the brain. These techniques include MRS, PET, SPECT, and preclinical methods such as fluorescence and mass spectrometry imaging. Finally, we discuss the roadblocks that must be overcome before incorporating glutamine into a personalized approach for glioma management.