Novel insights into paclitaxel's role on tumor-associated macrophages in enhancing PD-1 blockade in breast cancer treatment.

BACKGROUND: Triple-negative breast cancer (TNBC) poses unique challenges due to its complex nature and the need for more effective treatments. Recent studies showed encouraging outcomes from combining paclitaxel (PTX) with programmed cell death protein-1 (PD-1) blockade in treating TNBC, although the exact mechanisms behind the improved results are unclear. METHODS: We employed an integrated approach, analyzing spatial transcriptomics and single-cell RNA sequencing data from TNBC patients to understand why the combination of PTX and PD-1 blockade showed better response in TNBC patients. We focused on toll-like receptor 4 (TLR4), a receptor of PTX, and its role in modulating the cross-presentation signaling pathways in tumor-associated macrophages (TAMs) within the tumor microenvironment. Leveraging insights obtained from patient-derived data, we conducted in vitro experiments using immunosuppressive bone marrow-derived macrophages (iBMDMs) to validate if PTX could augment the cross-presentation and phagocytosis activities. Subsequently, we extended our study to an in vivo murine model of TNBC to ascertain the effects of PTX on the cross-presentation capabilities of TAMs and its downstream impact on CD8+ T cell-mediated immune responses. RESULTS: Data analysis from TNBC patients revealed that the activation of TLR4 and cross-presentation signaling pathways are crucial for the antitumor efficacy of PTX. In vitro studies showed that PTX treatment enhances the cross-presentation ability of iBMDMs. In vivo experiments demonstrated that PTX activates TLR4-dependent cross-presentation in TAMs, improving CD8+ T cell-mediated antitumor responses. The efficacy of PTX in promoting antitumor immunity was elicited when combined with PD-1 blockade, suggesting a complementary interaction. CONCLUSIONS: This study reveals how PTX boosts the effectiveness of PD-1 inhibitors in treating TNBC. We found that PTX activates TLR4 signaling in TAMs. This activation enhances their ability to present antigens, thereby boosting CD8+ T cell antitumor responses. These findings not only shed light on PTX's immunomodulatory role in TNBC but also underscore the potential of targeting TAMs' antigen presentation capabilities in immunotherapy approaches.

Clinical Factors Affecting Discrepancy Between Predicted and Long-term Actual Lung Function Following Surgery.

PURPOSE: Lung cancer surgery outcomes depend heavily on preoperative pulmonary reserve, with forced expiratory volume in 1 second (FEV1) being a critical preoperative evaluation factor. Our study investigates the discrepancies between predicted and long-term actual postoperative lung function, focusing on clinical factors affecting these outcomes. METHODS: This retrospective observational study encompassed lung cancer patients who underwent preoperative lung perfusion SPECT/CT between 2015 and 2021. We evaluated preoperative and postoperative pulmonary function tests, considering factors such as surgery type, resected volume, and patient history including tuberculosis. Predicted postoperative lung function was calculated using SPECT/CT imaging. RESULTS: From 216 patients (men:women, 150:66; age, 67.9 ± 8.7 years), predicted postoperative FEV1% (ppoFEV1%) showed significant correlation with actual postoperative FEV1% (r = 0.667; P < 0.001). Paired t test revealed that ppoFEV1% was significantly lower compared with actual postoperative FEV1% (P < 0.001). The study identified video-assisted thoracic surgery (VATS) (odds ratio [OR], 3.90; 95% confidence interval [CI], 1.98-7.69; P < 0.001) and higher percentage of resected volume (OR per 1% increase, 1.05; 95% CI, 1.01-1.09; P = 0.014) as significant predictors of postsurgical lung function improvement. Conversely, for the decline in lung function postsurgery, significant predictors included lower percentage of resected lung volume (OR per 1% increase, 0.92; 95% CI, 0.86-0.98; P = 0.011), higher preoperative FEV1% (OR, 1.03; 95% CI, 1.01-1.07; P = 0.009), and the presence of tuberculosis (OR, 5.19; 95% CI, 1.48-18.15; P = 0.010). Additionally, in a subgroup of patients with borderline lung function, VATS was related with improvement. CONCLUSIONS: Our findings demonstrate that in more than half of the patients, actual postsurgical lung function exceeded predicted values, particularly following VATS and with higher volume of lung resection. It also identifies lower resected lung volume, higher preoperative FEV1%, and tuberculosis as factors associated with a postsurgical decline in lung function. The study underscores the need for precise preoperative lung function assessment and tailored postoperative management, with particular attention to patients with relevant clinical factors. Future research should focus on validation of clinical factors and exploring tailored approaches to lung cancer surgery and recovery.

[18F]FDOPA PET/CT in Solid Pseudopapillary Tumor of the Pancreas: a Recurred Tumor Mimicking Splenosis.

Solid pseudopapillary tumor (SPT) of the pancreas is a neoplasm with low malignant potential. It is often challenging to diagnose SPT due to its nonspecific clinical and radiological features, and [18F]FDOPA is effective in diagnosing SPT, particularly in differentiating SPT from benign conditions such as splenosis. A 55-year-old woman underwent distal pancreatectomy and splenectomy for histologically confirmed SPT. She was also initially diagnosed with splenosis. During follow-up, sizes of multiple nodular lesions were increased, raising the possibility of peritoneal seeding of SPT. For diagnosis, a spleen scan and SPECT/CT were performed using 99mTc-labeled damaged red blood cells, which showed no uptake in the peritoneal nodules. Subsequent [18F]FDOPA PET/CT revealed [18F]FDOPA-avidity of the nodules. The patient underwent tumor resection surgery, and the nodules were pathologically confirmed as SPT.

Preoperative evaluation of mediastinal lymph nodes in non-small cell lung cancer using [68Ga]FAPI-46 PET/CT: a prospective pilot study.

PURPOSE: Mediastinal nodal staging is crucial for surgical candidate selection in non-small cell lung cancer (NSCLC), but conventional imaging has limitations often necessitating invasive staging. We investigated the additive clinical value of fibroblast activation protein inhibitor (FAPI) PET/CT, an imaging technique targeting fibroblast activation protein, for mediastinal nodal staging of NSCLC. METHODS: In this prospective pilot study, we enrolled patients scheduled for surgical resection of NSCLC based on specific criteria designed to align with indications for invasive staging procedures. Patients were included when meeting at least one of the following: (1) presence of FDG-positive N2 lymph nodes, (2) clinical N1 stage, (3) central tumor location or tumor diameter of ≥ 3 cm, and (4) adenocarcinoma exhibiting high FDG uptake. [68Ga]FAPI-46 PET/CT was performed before surgery after a staging workup including [18F]FDG PET/CT. The diagnostic accuracy of [68Ga]FAPI-46 PET/CT for "N2" nodes was assessed through per-patient visual assessment and per-station quantitative analysis using histopathologic results as reference standards. RESULTS: Twenty-three patients with 75 nodal stations were analyzed. Histopathologic examination confirmed that nine patients (39.1%) were N2-positive. In per-patient assessment, [68Ga]FAPI-46 PET/CT successfully identified metastasis in eight patients (sensitivity 0.89 (0.52-1.00)), upstaging three patients compared to [18F]FDG PET/CT. [18F]FDG PET/CT detected FDG-avid nodes in six (42.8%) of 14 N2-negative patients. Among them, five were considered non-metastatic based on calcification and distribution pattern, and one was considered metastatic. In contrast, [68Ga]FAPI-46 PET/CT correctly identified all non-metastatic patients solely based on tracer avidity. In per-station analysis, [68Ga]FAPI-46 PET/CT discriminated metastasis more effectively compared to [18F]FDG PET/CT-based (AUC of ROC curve 0.96 (0.88-0.99) vs. 0.68 (0.56-0.78), P < 0.001). CONCLUSION: [68Ga]FAPI-46 PET/CT holds promise as an imaging tool for preoperative mediastinal nodal staging in NSCLC, with improved sensitivity and the potential to reduce false-positive results, optimizing the need for invasive staging procedures.

Comprehensive characterization of early-programmed tumor microenvironment by tumor-associated macrophages reveals galectin-1 as an immune modulatory target in breast cancer.

Background: In recent years, there has been considerable interest in the therapeutic targeting of tumor-associated macrophages (TAMs) to modulate the tumor microenvironment (TME), resulting in antitumoral phenotypes. However, key mediators suitable for TAM-mediated remodeling of the TME remain poorly understood. Methods: In this study, we used single-cell RNA sequencing analyses to analyze the landscape of the TME modulated by TAMs in terms of a protumor microenvironment during early tumor development. Results: Our data revealed that the depletion of TAMs leads to a decreased epithelial-to-mesenchymal transition (EMT) signature in cancer cells and a distinct transcriptional state characterized by CD8+ T cell activation. Moreover, notable alterations in gene expression were observed upon the depletion of TAMs, identifying Galectin-1 (Gal-1) as a crucial molecular factor responsible for the observed effect. Gal-1 inhibition reversed immune suppression via the reinvigoration of CD8+ T cells, impairing tumor growth and potentiating immune checkpoint inhibitors in breast tumor models. Conclusion: These results provide comprehensive insights into TAM-mediated early tumor microenvironments and reveal immune evasion mechanisms that can be targeted by Gal-1 to induce antitumor immune responses.

Deep Learning-Based Feature Extraction from Whole-Body PET/CT Employing Maximum Intensity Projection Images: Preliminary Results of Lung Cancer Data.

Purpose: Deep learning (DL) has been widely used in various medical imaging analyses. Because of the difficulty in processing volume data, it is difficult to train a DL model as an end-to-end approach using PET volume as an input for various purposes including diagnostic classification. We suggest an approach employing two maximum intensity projection (MIP) images generated by whole-body FDG PET volume to employ pre-trained models based on 2-D images. Methods: As a retrospective, proof-of-concept study, 562 [18F]FDG PET/CT images and clinicopathological factors of lung cancer patients were collected. MIP images of anterior and lateral views were used as inputs, and image features were extracted by a pre-trained convolutional neural network (CNN) model, ResNet-50. The relationship between the images was depicted on a parametric 2-D axes map using t-distributed stochastic neighborhood embedding (t-SNE), with clinicopathological factors. Results: A DL-based feature map extracted by two MIP images was embedded by t-SNE. According to the visualization of the t-SNE map, PET images were clustered by clinicopathological features. The representative difference between the clusters of PET patterns according to the posture of a patient was visually identified. This map showed a pattern of clustering according to various clinicopathological factors including sex as well as tumor staging. Conclusion: A 2-D image-based pre-trained model could extract image patterns of whole-body FDG PET volume by using anterior and lateral views of MIP images bypassing the direct use of 3-D PET volume that requires large datasets and resources. We suggest that this approach could be implemented as a backbone model for various applications for whole-body PET image analyses.

FDG uptake reflects an immune-enriched subtype of thyroid cancer: Clinical implications of imaging-based molecular characterization.

INTRODUCTION: Iodine and FDG uptakes have been established as methods to define the biological properties of thyroid cancer. As various cells in the tumor microenvironment (TME) affect tumor metabolism, we investigated the association between glucose metabolism in thyroid cancer and the TME using transcriptomic analyses. METHODS: We used F-18 FDG PET and RNA sequencing data of thyroid cancer to find associations between TME cell types and glucose metabolism. In addition, publicly available single-cell RNA sequencing data of papillary thyroid cancer was used to investigate glucose metabolism in cell types of the TME. The correlations between the FDG uptake and biological properties of the TME, including glucose metabolism and tumor differentiation score (TDS) were evaluated. Estimation of the proportions of immune and cancer cells (EPIC) was performed. The biological properties of each cell type were also assessed in the single-cell RNA sequencing data. RESULTS: FDG uptake showed a positive correlation with the enrichment score of macrophages and glycolysis activity. In single-cell RNA sequencing, immune cells had both high glucose transporters (GLUTs) and glycolysis signatures, while thyrocytes including cancer cells showed relatively low GLUTs and glycolysis signatures, suggesting that FDG uptake mainly occurred in immune cells of the TME. Moreover, the high GLUTs of myeloid cells were negatively associated with TDS. CONCLUSIONS: Our findings suggest that thyroid cancer with high FDG uptake can be mediated by enriched immune cells of the TME. We suggest that FDG uptake in thyroid cancer could be a marker for the immune-rich type and provide clinical implications for treatment stratification.

Correlation between standardized uptake value of 18F-FDG PET/CT and conductivity with pathologic prognostic factors in breast cancer.

We investigated the correlation between standardized uptake value (SUV) of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) and conductivity parameters in breast cancer and explored the feasibility of conductivity as an imaging biomarker. Both SUV and conductivity have the potential to reflect the tumors' heterogeneous characteristics, but their correlations have not been investigated until now. Forty four women diagnosed with breast cancer who underwent breast MRI and 18F-FDG PET/CT at the time of diagnosis were included. Among them, 17 women received neoadjuvant chemotherapy followed by surgery and 27 women underwent upfront surgery. For conductivity parameters, maximum and mean values of the tumor region-of-interests were examined. For SUV parameters, SUVmax, SUVmean, and SUVpeak of the tumor region-of-interests were examined. Correlations between conductivity and SUV were evaluated, and among them, the highest correlation was observed between mean conductivity and SUVpeak (Spearman's correlation coefficient = 0.381). In a subgroup analysis for 27 women with upfront surgery, tumors with lymphovascular invasion (LVI) showed higher mean conductivity than those without LVI (median: 0.49 S/m vs 0.06 S/m, p < 0.001). In conclusion, our study shows a low positive correlation between SUVpeak and mean conductivity in breast cancer. Furthermore, conductivity showed a potential to noninvasively predict LVI status.

99mTc-MAA accumulation within tumor in preoperative lung perfusion SPECT/CT associated with occult lymph node metastasis in patients with clinically N0 non-small cell lung cancer.

BACKGROUND: 99mTc-MAA accumulation within the tumor representing pulmonary arterial perfusion, which is variable and may have a clinical significance. We evaluated the prognostic significance of 99mTc-MAA distribution within the tumor in non-small cell lung cancer (NSCLC) patients in terms of detecting occult nodal metastasis and lymphovascular invasion, as well as predicting the recurrence-free survival (RFS). METHODS: Two hundred thirty-nine NSCLC patients with clinical N0 status who underwent preoperative lung perfusion SPECT/CT were retrospectively evaluated and classified according to the visual grading of 99mTc-MAA accumulation in the tumor. Visual grade was compared with the quantitative parameter, standardized tumor to lung ratio (TLR). The predictive value of 99mTc-MAA accumulation with occult nodal metastasis, lymphovascular invasion, and RFS was assessed. RESULTS: Eighty-nine (37.2%) patients showed 99mTc-MAA accumulation and 150 (62.8%) patients showed the defect on 99mTc-MAA SPECT/CT. Among the accumulation group, 45 (50.5%) were classified as grade 1, 40 (44.9%) were grade 2, and 4 (4.5%) were grade 3. TLR gradually and significantly increased from grade 0 (0.009 ± 0.005) to grade 1 (0.021 ± 0.005, P < 0.05) and to grade 2-3 (0.033 ± 0.013, P < 0.05). The following factors were significant predictors for occult nodal metastasis in univariate analysis: central location, histology different from adenocarcinoma, tumor size greater than 3 cm representing clinical T2 or higher, and the absence of 99mTc-MAA accumulation within the tumor. Defect in the lung perfusion SPECT/CT remained significant at the multivariate analysis (Odd ratio 3.25, 95%CI [1.24 to 8.48], p = 0.016). With a median follow-up of 31.5 months, the RFS was significantly shorter in the defect group (p = 0.008). Univariate analysis revealed that cell type of non-adenocarcinoma, clinical stage II-III, pathologic stage II-III, age greater than 65 years, and the 99mTc-MAA defect within tumor as significant predictors for shorter RFS. However, only the pathologic stage remained statistically significant, in multivariate analysis. CONCLUSION: The absence of 99mTc-MAA accumulation within the tumor in preoperative lung perfusion SPECT/CT represents an independent risk factor for occult nodal metastasis and is relevant as a poor prognostic factor in clinically N0 NSCLC patients. 99mTc-MAA tumor distribution may serve as a new imaging biomarker reflecting tumor vasculatures and perfusion which can be associated with tumor biology and prognosis.

spSeudoMap: cell type mapping of spatial transcriptomics using unmatched single-cell RNA-seq data.

Since many single-cell RNA-seq (scRNA-seq) data are obtained after cell sorting, such as when investigating immune cells, tracking cellular landscape by integrating single-cell data with spatial transcriptomic data is limited due to cell type and cell composition mismatch between the two datasets. We developed a method, spSeudoMap, which utilizes sorted scRNA-seq data to create virtual cell mixtures that closely mimic the gene expression of spatial data and trains a domain adaptation model for predicting spatial cell compositions. The method was applied in brain and breast cancer tissues and accurately predicted the topography of cell subpopulations. spSeudoMap may help clarify the roles of a few, but crucial cell types.

Automatic Lung Cancer Segmentation in [18F]FDG PET/CT Using a Two-Stage Deep Learning Approach.

Purpose: Since accurate lung cancer segmentation is required to determine the functional volume of a tumor in [18F]FDG PET/CT, we propose a two-stage U-Net architecture to enhance the performance of lung cancer segmentation using [18F]FDG PET/CT. Methods: The whole-body [18F]FDG PET/CT scan data of 887 patients with lung cancer were retrospectively used for network training and evaluation. The ground-truth tumor volume of interest was drawn using the LifeX software. The dataset was randomly partitioned into training, validation, and test sets. Among the 887 PET/CT and VOI datasets, 730 were used to train the proposed models, 81 were used as the validation set, and the remaining 76 were used to evaluate the model. In Stage 1, the global U-net receives 3D PET/CT volume as input and extracts the preliminary tumor area, generating a 3D binary volume as output. In Stage 2, the regional U-net receives eight consecutive PET/CT slices around the slice selected by the Global U-net in Stage 1 and generates a 2D binary image as the output. Results: The proposed two-stage U-Net architecture outperformed the conventional one-stage 3D U-Net in primary lung cancer segmentation. The two-stage U-Net model successfully predicted the detailed margin of the tumors, which was determined by manually drawing spherical VOIs and applying an adaptive threshold. Quantitative analysis using the Dice similarity coefficient confirmed the advantages of the two-stage U-Net. Conclusion: The proposed method will be useful for reducing the time and effort required for accurate lung cancer segmentation in [18F]FDG PET/CT.

Mannosylated-serum albumin nanoparticle imaging to monitor tumor-associated macrophages under anti-PD1 treatment.

BACKGROUND: Immune checkpoint inhibitors such as anti-programmed cell death protein 1 (PD1) block tumor growth by reinvigorating the immune system; however, determining their efficacy only by the changes in tumor size may prove inaccurate. As the immune cells including macrophages in the tumor microenvironment (TME) are associated with the response to anti-PD1 therapy, tumor-associated macrophages (TAMs) imaging using nanoparticles can noninvasively provide the immune enrichment status of TME. Herein, the mannosylated-serum albumin (MSA) nanoparticle was labeled with radioactive isotope 68Ga to target the mannose receptors on macrophages for noninvasive monitoring of the TME according to anti-PD1 therapy. RESULTS: B16F10-Luc and MC38-Luc tumor-bearing mice were treated with anti-PD1, and the response to anti-PD1 was determined by the tumor volume. According to the flow cytometry, the responders to anti-PD1 showed an increased proportion of TAMs, as well as lymphocytes, and the most enriched immune cell population in the TME was also TAMs. For noninvasive imaging of TAMs as a surrogate of immune cell augmentation in the TME via anti-PD1, we acquired [68Ga] Ga-MSA positron emission tomography. According to the imaging study, an increased number of TAMs in responders at the early phase of anti-PD1 treatment was observed in both B16F10-Luc and MC38-Luc tumor-bearing mice models. CONCLUSION: As representative immune cells in the TME, non-invasive imaging of TAMs using MSA nanoparticles can reflect the immune cell enrichment status in the TME closely associated with the response to anti-PD1. As non-invasive imaging using MSA nanoparticles, this approach shows a potential to monitor and evaluate anti-tumor response to immune checkpoint inhibitors.

Reliability and feasibility of visual grading systems and quantitative indexes on [99mTc]Tc-DPD imaging for cardiac amyloidosis.

We aimed to evaluate the reliability and feasibility of visual grading systems and various quantitative indexes of [99mTc]Tc-DPD imaging for cardiac amyloidosis (CA). Patients who underwent [99mTc]Tc-DPD imaging with suspicion of CA were enrolled. On the planar image, myocardial uptake was visually graded using Perugini's and Dorbala's methods (PS and DS). As [99mTc]Tc-DPD indexes, heart-to-whole body ratio (H/WB) and heart-to-contralateral lung ratio (H/CL) were measured on planar image. SUVmax, SUVmean, total myocardial uptake (TMU), and C-index were measured on SPECT/CT. Inter-observer agreement of the indexes and their association with visual grading and clinical factors were evaluated. A total of 152 [99mTc]Tc-DPD images, of which 18 were positive, were analyzed. Inter-observer agreement was high for both DS (κ = 0.95) and PS (κ = 0.96). However, DS showed a higher correlation with quantitative indexes than PS. Inter-observer agreement was also high for SPECT/CT indexes, particularly SUVmax. SUVmax was significantly different between different DS groups (P = 0.014-0.036), and showed excellent correlations with H/WB and H/CL (r = 0.898 and 0.910). SUVmax also showed significant differences between normal, AL, and ATTR pathology (P = 0.022-0.037), and a significant correlation with extracellular volume on cardiac MRI (r = 0.772, P < 0.001). DS is a visual grading system for CA that is more significantly matched with quantitative indexes than PS. SUVmax is a reliable quantitative index on SPECT/CT, with a high inter-observer agreement, correlations with the visual grade, and potential association with cardiac MRI findings.

Association of androgen receptor expression with glucose metabolic features in triple-negative breast cancer.

BACKGROUND: Androgen receptor (AR) is a potential therapeutic target in triple-negative breast cancer (TNBC). We aimed to elucidate the association of AR expression with glucose metabolic features in TNBC. METHODS: Two independent datasets were analyzed: FDG PET data of our institution and a public dataset of GSE135565. In PET analysis, patients with TNBC who underwent pretreatment PET between Jan 2013 and Dec 2017 were retrospectively enrolled. Clinicopathologic features and maximum standardized uptake value (SUVmax) of tumors were compared with AR expression. In GSE135565 dataset, glycolysis score was calculated by the pattern of glycolysis-related genes, and of which association with SUVmax and AR gene expression were analyzed. RESULTS: A total of 608 female patients were included in the PET data of our institution. SUVmax was lower in AR-positive tumors (P < 0.001) and correlated with lower AR expression (rho = -0.26, P < 0.001). In multivariate analysis, AR was a deterministic factor for low SUVmax (P = 0.012), along with other key clinicopathologic features. In the GSE135565 dataset, AR expression also exhibited a negative correlation with SUVmax (r = -0.34, P = 0.001) and the glycolysis score (r = -0.27, P = 0.013). CONCLUSIONS: Low glucose metabolism is a signature of AR expression in TNBC. It is suggested that evaluation of AR expression status needs to be considered in clinical practice particularly in TNBC with low glucose metabolism.

Spatial Transcriptomics-Based Identification of Molecular Markers for Nanomedicine Distribution in Tumor Tissue.

The intratumoral accumulation of nanomedicine has been considered a passive process, referred to as the enhanced permeability and retention effect. Recent studies have suggested that the tumor uptake of nanomedicines follows an energy-dependent pathway rather than being a passive process. Herein, to explore the factor candidates that are associated with nanomedicine tumor uptake, a molecular marker identification platform is developed by integrating microscopic fluorescence images of a nanomedicine distribution with spatial transcriptomics information. When this approach is applied to PEGylated liposomes, molecular markers related to hypoxia, glycolysis, and apoptosis can be identified as being related to the intratumoral distribution of the nanomedicine. It is expected that the method can be applied to explain the distribution of a wide range of nanomedicines and that the data obtained from this analysis can enhance the precise utilization of nanomedicines.

Glucose-Thymidine Ratio as a Metabolism Index Using 18F-FDG and 18F-FLT PET Uptake as a Potential Imaging Biomarker for Evaluating Immune Checkpoint Inhibitor Therapy.

Immune checkpoint inhibitors (ICIs) are widely used in cancer immunotherapy, requiring effective methods for response monitoring. This study evaluated changes in 18F-2-fluoro-2-deoxy-D-glucose (FDG) and 18F-fluorothymidine (FLT) uptake by tumors following ICI treatment as potential imaging biomarkers in mice. Tumor uptakes of 18F-FDG and 18F-FLT were measured and compared between the ICI treatment and control groups. A combined imaging index of glucose-thymidine uptake ratio (GTR) was defined and compared between groups. In the ICI treatment group, tumor growth was effectively inhibited, and higher proportions of immune cells were observed. In the early phase, 18F-FDG uptake was higher in the treatment group, whereas 18F-FLT uptake was not different. There was no difference in 18F-FDG uptake between the two groups in the late phase. However, 18F-FLT uptake of the control group was markedly increased compared with the ICI treatment group. GTR was consistently higher in the ICI treatment group in the early and late phases. After ICI treatment, changes in tumor cell proliferation were observed with 18F-FLT, whereas 18F-FDG showed altered metabolism in both tumor and immune cells. A combination of 18F-FLT and 18F-FDG PET, such as GTR, is expected to serve as a potentially effective imaging biomarker for monitoring ICI treatment.

Circulation Time-Optimized Albumin Nanoplatform for Quantitative Visualization of Lung Metastasis via Targeting of Macrophages.

The development of molecular imaging probes to identify key cellular changes within lung metastases may lead to noninvasive detection of metastatic lesions in the lung. In this study, we constructed a macrophage-targeted clickable albumin nanoplatform (CAN) decorated with mannose as the targeting ligand using a click reaction to maintain the intrinsic properties of albumin in vivo. We also modified the number of mannose molecules on the CAN and found that mannosylated serum albumin (MSA) harboring six molecules of mannose displayed favorable pharmacokinetics that allowed high-contrast imaging of the lung, rendering it suitable for in vivo visualization of lung metastases. Due to the optimized control of functionalization and surface modification, MSA enhanced blood circulation time and active/passive targeting abilities and was specifically incorporated by mannose receptor (CD206)-expressing macrophages in the metastatic lung. Moreover, extensive in vivo imaging studies using single-photon emission computed tomography (SPECT)/CT and positron emission tomography (PET) revealed that blood circulation of time-optimized MSA can be used to discern metastatic lesions, with a strong correlation between its signal and metastatic burden in the lung.

Prognostic impact of an integrative analysis of [18F]FDG PET parameters and infiltrating immune cell scores in lung adenocarcinoma.

BACKGROUND: High levels of 18F-fluorodeoxyglucose (18F-FDG) tumor uptake are associated with worse prognosis in patients with non-small cell lung cancer (NSCLC). Meanwhile, high levels of immune cell infiltration in primary tumor have been linked to better prognosis in NSCLC. We conducted this study for precisely stratified prognosis of the lung adenocarcinoma patients using the integration of 18F-FDG positron emission tomography (PET) parameters and infiltrating immune cell scores as assessed by a genomic analysis. RESULTS: Using an RNA sequencing dataset, the patients were divided into three subtype groups. Additionally, 24 different immune cell scores and cytolytic scores (CYT) were obtained. In 18F-FDG PET scans, PET parameters of the primary tumors were obtained. An ANOVA test, a Chi-square test and a correlation analysis were also conducted. A Kaplan-Meier survival analysis with the log-rank test and multivariable Cox regression test was performed to evaluate prognostic values of the parameters. The terminal respiratory unit (TRU) group demonstrated lower 18F-FDG PET parameters, more females, and lower stages than the other groups. Meanwhile, the proximal inflammatory (PI) group showed a significantly higher CYT score compared to the other groups (P = .001). Also, CYT showed a positive correlation with tumor-to-liver maximum standardized uptake value ratio (TLR) in the PI group (P = .027). A high TLR (P = .01) score of 18F-FDG PET parameters and a high T follicular helper cell (TFH) score (P = .005) of immune cell scores were associated with prognosis with opposite tendencies. Furthermore, TLR and TFH were predictive of overall survival even after adjusting for clinicopathologic features and others (P = .024 and .047). CONCLUSIONS: A high TLR score was found to be associated with worse prognosis, while high CD8 T cell and TFH scores predicted better prognosis in lung adenocarcinoma. Furthermore, TLR and TFH can be used to predict prognosis independently in patients with lung adenocarcinoma.

Single-Cell Radiotracer Allocation via Immunomagnetic Sorting to Disentangle PET Signals at Cellular Resolution.

With great interest, our independent groups of scientists located in Korea and Germany recognized the use of a very similar methodologic approach to quantify the uptake of radioactive glucose (18F-FDG) at the cellular level. The focus of our investigations was to disentangle microglial 18F-FDG uptake. To do so, CD11b immunomagnetic cell sorting was applied to isolate microglia cells after in vivo 18F-FDG injection, to allow simple quantification via a γ-counter. Importantly, this technique reveals a snapshot of cellular glucose uptake in living mice at the time of injection since 18F-FDG is trapped by hexokinase phosphorylation without a further opportunity to be metabolized. Both studies indicated high 18F-FDG uptake of single CD11b-positive microglia cells and a significant increase in microglial 18F-FDG uptake when this cell type is activated in the presence of amyloid pathology. Furthermore, another study noticed that immunomagnetic cell sorting after tracer injection facilitated determination of high 18F-FDG uptake in myeloid cells in a range of tumor models. Here, we aim to discuss the rationale for single-cell radiotracer allocation via immunomagnetic cell sorting (scRadiotracing) by providing examples of promising applications of this innovative technology in neuroscience, oncology, and radiochemistry.

Investigating the Clinico-Molecular and Immunological Evolution of Lung Adenocarcinoma Using Pseudotime Analysis.

Introduction: As the molecular features of lung adenocarcinoma (LUAD) have been evaluated as a cross-sectional study, the course of tumor characteristics has not been modeled. The temporal evolution of the tumor immune microenvironment (TIME), as well as the clinico-molecular features of LUAD, could provide a precise strategy for immunotherapy and surrogate biomarkers for the course of LUAD. Methods: A pseudotime trajectory was constructed in patients with LUAD from the Cancer Genome Atlas and non-small cell lung cancer radiogenomics datasets. Correlation analyses were performed between clinical features and pseudotime. Genes associated with pseudotime were selected, and gene ontology analysis was performed. F-18 fluorodeoxyglucose positron emission tomography images of subjects were collected, and imaging parameters, including standardized uptake value (SUV), were obtained. Correlation analyses were performed between imaging parameters and pseudotime. Correlation analyses were performed between the enrichment scores of various immune cell types and pseudotime. In addition, correlation analyses were performed between the expression of PD-L1, tumor mutation burden, and pseudotime. Results: Pseudotime trajectories of LUAD corresponded to clinical stages. Molecular profiles related to cell division and natural killer cell activity were changed along the pseudotime. The maximal SUV of LUAD tumors showed a positive correlation with pseudotime. Type 1 helper T (Th1) cells showed a positive correlation, whereas M2 macrophages showed a negative correlation with pseudotime. PD-L1 expression showed a negative correlation, whereas tumor mutation burden showed a positive correlation with pseudotime. Conclusion: The estimated pseudotime associated with the stage suggested that it could reflect the clinico-molecular evolution of LUAD. Specific immune cell types in the TIME as well as cell division and glucose metabolism were dynamically changed according to the progression of the pseudotime. As a molecular progression of LUAD, different cellular targets should be considered for immunotherapy.