Spatial heterogeneity of radiolabeled choline positron emission tomography in tumors of patients with non-small cell lung cancer: first-in-patient evaluation of [18F]fluoromethyl-(1,2-2H4)-choline

Bench to Bedside Development of [18F]Fluoromethyl-(1,2-2H4)choline ([18F]D4-FCH)

Malignant transformation is characterised by aberrant phospholipid metabolism of cancers, associated with the upregulation of choline kinase alpha (CHKα). Due to the metabolic instability of choline radiotracers and the increasing use of late-imaging protocols, we developed a more stable choline radiotracer, [18F]fluoromethyl-[1,2-2H4]choline ([18F]D4-FCH). [18F]D4-FCH has improved protection against choline oxidase, the key choline catabolic enzyme, via a 1H/2D isotope effect, together with fluorine substitution. Due to the promising mechanistic and safety profiles of [18F]D4-FCH in vitro and preclinically, the radiotracer has transitioned to clinical development. [18F]D4-FCH is a safe positron emission tomography (PET) tracer, with a favourable radiation dosimetry profile for clinical imaging. [18F]D4-FCH PET/CT in lung and prostate cancers has shown highly heterogeneous intratumoral distribution and large lesion variability. Treatment with abiraterone or enzalutamide in metastatic castrate-resistant prostate cancer patients elicited mixed responses on PET at 12-16 weeks despite predominantly stable radiological appearances. The sum of the weighted tumour-to-background ratios (TBRs-wsum) was associated with the duration of survival.

Discovering metabolic vulnerability using spatially resolved metabolomics for antitumor small molecule-drug conjugates development as a precise cancer therapy strategy

Against tumor-dependent metabolic vulnerability is an attractive strategy for tumor-targeted therapy. However, metabolic inhibitors are limited by the drug resistance of cancerous cells due to their metabolic plasticity and heterogeneity. Herein, choline metabolism was discovered by spatially resolved metabolomics analysis as metabolic vulnerability which is highly active in different cancer types, and a choline-modified strategy for small molecule-drug conjugates (SMDCs) design was developed to fool tumor cells into indiscriminately taking in choline-modified chemotherapy drugs for targeted cancer therapy, instead of directly inhibiting choline metabolism. As a proof-of-concept, choline-modified SMDCs were designed, screened, and investigated for their druggability in vitro and in vivo. This strategy improved tumor targeting, preserved tumor inhibition and reduced toxicity of paclitaxel, through targeted drug delivery to tumor by highly expressed choline transporters, and site-specific release by carboxylesterase. This study expands the strategy of targeting metabolic vulnerability and provides new ideas of developing SMDCs for precise cancer therapy.

Dynomics: A Novel and Promising Approach for Improved Breast Cancer Prognosis Prediction

Traditional imaging techniques for breast cancer (BC) diagnosis and prediction, such as X-rays and magnetic resonance imaging (MRI), demonstrate varying sensitivity and specificity due to clinical and technological factors. Consequently, positron emission tomography (PET), capable of detecting abnormal metabolic activity, has emerged as a more effective tool, providing critical quantitative and qualitative tumor-related metabolic information. This study leverages a public clinical dataset of dynamic ¹⁸F-Fluorothymidine (FLT) PET scans from BC patients, extending conventional static radiomics methods to the time domain-termed as 'Dynomics'. Radiomic features were extracted from both static and dynamic PET images on lesion and reference tissue masks. The extracted features were used to train an XGBoost model for classifying tumor versus reference tissue and complete versus partial responders to neoadjuvant chemotherapy. The results underscored the superiority of dynamic and static radiomics over standard PET imaging, achieving accuracy of 94% in tumor tissue classification. Notably, in predicting BC prognosis, dynomics delivered the highest performance, achieving accuracy of 86%, thereby outperforming both static radiomics and standard PET data. This study illustrates the enhanced clinical utility of dynomics in yielding more precise and reliable information for BC diagnosis and prognosis, paving the way for improved treatment strategies.

Involvement of CHRNA6 in the Immune Response in Lung Squamous Cell Carcinoma and its Potential as a Drug Target for the Disease

BACKGROUND

Lung squamous cell carcinoma (LUSC) is a subtype of lung cancer with a poor prognosis and limited treatment options. Previous studies show that some components of the cholinergic pathway may play important roles in the tumorigenesis of lung cancer, including LUSC.

OBJECTIVE

The purpose of this study is to investigate the involvement of cholinergic genes in immune infiltration in LUSC, and identify the key genes in the pathway and analyze their potential as targets for LUSC treatment and novel drugs.

METHODS

We first screened the cholinergic genes associated with immune infiltration in LUSC based on transcriptomic samples and explored the correlation between the key genes and immune infiltrating cells and immune pathways. Then, we assessed the effect of immunotherapeutic response in the high and low-expression groups of key genes in vitro. And finally, we screened potential drugs for the treatment of LUSC.

RESULTS

We found that the expression of CHRNA6, the gene encoding the α6 subunit of nicotinic acetylcholine receptors (nAChR), was significantly correlated with the proportion of immune infiltrating cells in LUSC, and the high expression level of the gene was associated with poor prognosis of the disease. Also, the proportion of Tregs, M1 macrophages, and resting mast cells was correlated with the expression of CHRNA6. In addition, LUSC patients with higher CHRNA6 expression levels had better immunotherapy responses. Furthermore, we found that the drugs, i.e., adavosertib, varbulin and pyrazoloacridine, had a strong affinity with CHRNA6, with adavosertib binding most stably with the protein.

CONCLUSION

CHRNA6 may be associated with immune infiltration in LUSC and affects patient prognosis and immunotherapeutic response by regulating immune cells and immune pathways. In addition, adavosertib may be a potential drug for the treatment of LUSC.

Spatiotemporal learning of dynamic positron emission tomography data improves diagnostic accuracy in breast cancer

Positron emission tomography (PET) can reveal metabolic activity in a voxelwise manner. PET analysis is commonly performed in a static manner by analyzing the standardized uptake value (SUV) obtained from the plateau region of PET acquisitions. A dynamic PET acquisition can provide a map of the spatiotemporal concentration of the tracer in vivo, hence conveying information about radiotracer delivery to tissue, its interaction with the target and washout. Therefore, tissue-specific biochemical properties are embedded in the shape of time activity curves (TACs), which are generally used for kinetic analysis. Conventionally, TACs are employed along with information about blood plasma activity concentration, i.e., the arterial input function (AIF), and specific compartmental models to obtain a full quantitative analysis of PET data. The main drawback of this approach is the need for invasive procedures requiring arterial blood sample collection during the whole PET scan. In this paper, we address the challenge of improving PET diagnostic accuracy through an alternative approach based on the analysis of time signal intensity patterns. Specifically, we demonstrate the diagnostic potential of tissue TACs provided by dynamic PET acquisition using various deep learning models. Our framework is shown to outperform the discriminative potential of classical SUV analysis, hence paving the way for more accurate PET-based lesion discrimination without additional acquisition time or invasive procedures. Clinical Relevance- The diagnostic accuracy of dynamic PET data exploited by deep-learning based time signal intensity pattern analysis is superior to that of static SUV imaging.

New PET Tracers: Current Knowledge and Perspectives in Lung Cancer

PET/CT with the tracer 2-[¹⁸F]fluoro-2-deoxy-D-glucose ([¹⁸F]FDG) has improved diagnostic imaging in cancer and is routinely used for diagnosing, staging and treatment planning in lung cancer patients. However, pitfalls of [¹⁸F]FDG-PET/CT limit the use in specific settings. Additionally, lung cancer is still the leading cause of cancer associated death and has high risk of recurrence after curative treatment. These circumstances have led to the continuous search for more sensitive and specific PET tracers to optimize lung cancer diagnosis, staging, treatment planning and evaluation. The objective of this review is to present and discuss current knowledge and perspectives of new PET tracers for use in lung cancer. A literature search was performed on PubMed and clinicaltrials.gov, limited to the past decade, excluding case reports, preclinical studies and studies on established tracers such as [¹⁸F]FDG and DOTATE. The most relevant papers from the search were evaluated. Several tracers have been developed targeting specific tumor characteristics and hallmarks of cancer. A small number of tracers have been studied extensively and evaluated head-to-head with [¹⁸F]FDG-PET/CT, whereas others need further investigation and validation in larger clinical trials. At this moment, none of the tracers can replace [¹⁸F]FDG-PET/CT. However, they might serve as supplementary imaging methods to provide more knowledge about biological tumor characteristics and visualize intra- and inter-tumoral heterogeneity.

Molecular Imaging of Renal Cell Carcinoma in Precision Medicine

Renal cell carcinoma (RCC) is the sixth most common cancer among men and the ninth among women, and its prognosis is closely correlated with metastasis. Targeted therapy and immunotherapy are the main adjuvant treatments for advanced RCC and require early diagnosis, precise assessment, and prediction of the therapeutic responses. Current conventional imaging methods of RCC only provide structural information rather than biological processes. Noninvasive diagnostic tools are therefore needed to image RCC early and accurately at the molecular level. Nuclear medicine imaging combines the high sensitivity of radionuclides with the high resolution of structural imaging to visualize the metabolic processes and specific targets of RCC for more accurate and reliable diagnosis, staging, prognosis prediction, and response assessment. This review summarizes the most recent applications of nuclear medicine receptor imaging and metabolic imaging in RCC and highlights future development perspectives in the field.

Consideration of Metabolite Efflux in Radiolabelled Choline Kinetics

Hypoxia is a complex microenvironmental condition known to regulate choline kinase α (CHKA) activity and choline transport through transcription factor hypoxia-inducible factor-1α (HIF-1α) and, therefore, may confound the uptake of choline radiotracer [18F]fluoromethyl-[1,2-2H4]-choline ([18F]-D4-FCH). The aim of this study was to investigate how hypoxia affects the choline radiotracer dynamics. Three underlying mechanisms by which hypoxia could potentially alter the uptake of the choline radiotracer, [18F]-D4-FCH, were investigated: 18F-D4-FCH import, CHKA phosphorylation activity, and the efflux of [18F]-D4-FCH and its phosphorylated product [18F]-D4-FCHP. The effects of hypoxia on [18F]-D4-FCH uptake were studied in CHKA-overexpressing cell lines of prostate cancer, PC-3, and breast cancer MDA-MB-231 cells. The mechanisms of radiotracer efflux were assessed by the cell uptake and immunofluorescence in vitro and examined in vivo (n = 24). The mathematical modelling methodology was further developed to verify the efflux hypothesis using [18F]-D4-FCH dynamic PET scans from non-small cell lung cancer (NSCLC) patients (n = 17). We report a novel finding involving the export of phosphorylated [18F]-D4-FCH and [18F]-D4-FCHP via HIF-1α-responsive efflux transporters, including ABCB4, when the HIF-1α level is augmented. This is supported by a graphical analysis of human data with a compartmental model (M2T6k + k5) that accounts for the efflux. Hypoxia/HIF-1α increases the efflux of phosphorylated radiolabelled choline species, thus supporting the consideration of efflux in the modelling of radiotracer dynamics.