PET Imaging of l-Type Amino Acid Transporter (LAT1) and Cystine-Glutamate Antiporter (xc−) with [18F]FDOPA and [18F]FSPG in Breast Cancer Models

Exploration of Imaging Biomarkers for Metabolically-Targeted Osteosarcoma Therapy in a Murine Xenograft Model

Background: Osteosarcoma (OS) is an aggressive pediatric cancer with unmet therapeutic needs. Glutaminase 1 (GLS1) inhibition, alone and in combination with metformin, disrupts the bioenergetic demands of tumor progression and metastasis, showing promise for clinical translation. Materials and Methods: Three positron emission tomography (PET) clinical imaging agents, [18F]fluoro-2-deoxy-2-D-glucose ([18F]FDG), 3'-[18F]fluoro-3'-deoxythymidine ([18F]FLT), and (2S, 4R)-4-[18F]fluoroglutamine ([18F]GLN), were evaluated in the MG63.3 human OS xenograft mouse model, as companion imaging biomarkers after treatment for 7 d with a selective GLS1 inhibitor (CB-839, telaglenastat) and metformin, alone and in combination. Imaging and biodistribution data were collected from tumors and reference tissues before and after treatment. Results: Drug treatment altered tumor uptake of all three PET agents. Relative [18F]FDG uptake decreased significantly after telaglenastat treatment, but not within control and metformin-only groups. [18F]FLT tumor uptake appears to be negatively affected by tumor size. Evidence of a flare effect was seen with [18F]FLT imaging after treatment. Telaglenastat had a broad influence on [18F]GLN uptake in tumor and normal tissues. Conclusions: Image-based tumor volume quantification is recommended for this paratibial tumor model. The performance of [18F]FLT and [18F]GLN was affected by tumor size. [18F]FDG may be useful in detecting telaglenastat's impact on glycolysis. Exploration of kinetic tracer uptake protocols is needed to define clinically relevant patterns of [18F]GLN uptake in patients receiving telaglenastat.

The role of metabolic ecosystem in cancer progression — metabolic plasticity and mTOR hyperactivity in tumor tissues

Despite advancements in cancer management, tumor relapse and metastasis are associated with poor outcomes in many cancers. Over the past decade, oncogene-driven carcinogenesis, dysregulated cellular signaling networks, dynamic changes in the tissue microenvironment, epithelial-mesenchymal transitions, protein expression within regulatory pathways, and their part in tumor progression are described in several studies. However, the complexity of metabolic enzyme expression is considerably under evaluated. Alterations in cellular metabolism determine the individual phenotype and behavior of cells, which is a well-recognized hallmark of cancer progression, especially in the adaptation mechanisms underlying therapy resistance. In metabolic symbiosis, cells compete, communicate, and even feed each other, supervised by tumor cells. Metabolic reprogramming forms a unique fingerprint for each tumor tissue, depending on the cellular content and genetic, epigenetic, and microenvironmental alterations of the developing cancer. Based on its sensing and effector functions, the mechanistic target of rapamycin (mTOR) kinase is considered the master regulator of metabolic adaptation. Moreover, mTOR kinase hyperactivity is associated with poor prognosis in various tumor types. In situ metabolic phenotyping in recent studies highlights the importance of metabolic plasticity, mTOR hyperactivity, and their role in tumor progression. In this review, we update recent developments in metabolic phenotyping of the cancer ecosystem, metabolic symbiosis, and plasticity which could provide new research directions in tumor biology. In addition, we suggest pathomorphological and analytical studies relating to metabolic alterations, mTOR activity, and their associations which are necessary to improve understanding of tumor heterogeneity and expand the therapeutic management of cancer.

Integrating metabolic reprogramming and metabolic imaging to predict breast cancer therapeutic responses

Metabolic reprogramming is not only an emerging hallmark of cancer, but also an essential regulator of cancer cell adaptation to the microenvironment. Metabolic imaging targeting metabolic signatures has been widely used for breast cancer diagnosis. However, limited implications have been explored for monitoring breast cancer therapy response, although metabolic plasticity is notably associated with therapy resistance. In this review, we focus on the metabolic alterations upon breast cancer therapy and their potential for evaluating breast cancer therapeutic responses. We summarize the metabolic network and regulatory changes upon breast cancer therapy in terms of cancer pathological and genetic differences and discuss the implications of metabolic imaging with various probes in selecting target beneficiaries for precision treatment.