Prognostic significance of diffuse increased fluorine-18-fluorodeoxyglucose (18F-FDG) uptake within the reticuloendothelial system in lymphoma patients.

Background: As constituents of the reticuloendothelial system, the spleen and bone marrow (BM) have been recognized as integral components of the systemic inflammatory response in cancer contexts, thereby serving as predictive indicators for assessing cancer prognosis. Fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) has attained widespread utilization for staging, assessing treatment response, and prognostication in lymphoma patients. Several investigations have proposed that focal increased 18F-FDG uptake in the BM or spleen may correlate with malignant involvement in lymphoma. However, scant data exist regarding the implications of diffuse BM and splenic uptake. This study aimed to explore the relationships between metabolic parameters of the spleen and BM on 18F-FDG PET/CT and inflammatory markers, and to assess their prognostic value in patients with lymphoma. Methods: A retrospective analysis was conducted on 118 patients newly diagnosed with malignant lymphoma, who underwent 18F-FDG PET/CT and exhibited diffuse increased splenic or BM uptake in 18F-FDG PET/CT imaging. The mean standardized uptake value (SUV) of the spleen, BM, and liver was calculated. The association between metabolic variables and systemic inflammatory markers was investigated, and the prognostic significance of clinicopathological and PET parameters was assessed using overall survival (OS) and progression-free survival (PFS). Results: A statistically significant correlation was found between the spleen-to-liver SUV ratio (SLR) and inflammatory markers such as C-reactive protein (r=0.264, P=0.007) and platelet-to-lymphocyte ratio (r=0.227, P=0.021). No significant correlation was observed between BM-to-liver SUV ratio (BLR) and hematologic parameters, while concordance analysis revealed a fair agreement between BLR and bone marrow biopsy (BMB) (Cohen's Kappa-κ =0.271, P=0.002). In patients with aggressive non-Hodgkin lymphoma, both SLR [P=0.017, HR 2.715, 95% confidence interval (CI): 0.875-8.428] and BLR (P=0.044, HR 0.795, 95% CI: 0.348-1.813) were significantly linked to OS, while SLR (P=0.019, HR 2.223, 95% CI: 1.139-4.342) emerged as a significant prognostic factor for PFS. Conclusions: This study highlighted that diffuse increased splenic 18F-FDG uptake in lymphoma patients was closely associated with inflammation, whereas diffuse BM uptake was likely attributable to BM infiltration rather than inflammatory changes. Furthermore, both parameters held promise as prognostic indicators for patients with aggressive lymphoma.

A cutting-edge 68Ga-labeled bicyclic peptide PET molecular probe for noninvasive assessment of Nectin4 expression.

The diagnosis and treatment of triple negative breast cancer (TNBC) are huge challenges due to the lack of identifiable molecular targets. The high expression of Nectin4 in a variety of tumors, including TNBC, is associated with the occurrence, invasion, progression and poor prognosis of tumors. Therefore, Nectin4 is an emerging biomarker for the diagnosis and treatment of TNBC. A PET imaging method to non-invasively quantify Nectin4 expression levels may aid in TNBC diagnosis and classification. In this study, a novel bicyclic peptide molecular probe [68Ga]Ga-DN68 was used to evaluate the expression of Nectin4 in tumors. The radiolabeling rate of [68Ga]Ga-DN68 was over 97 %, while maintaining more than 99 % radiochemical purity. In vitro experiments showed that [68Ga]Ga-DN68 could effectively target Nectin4 in tumor cells, and the cellular uptake of MC38-Nectin4 cells (Nectin4+) was significantly higher than that of MC38 cells (Nectin4-). Biodistribution and PET imaging studies consistently showed that [68Ga]Ga-DN68 was specifically accumulated in MC38-Nectin4 and MDA-MB-468 tumors, which was significantly higher than that of MC38. When co-injected with cold DN68, the specific accumulation could block the tumor uptake of MDA-MB-468. Notably, the signal-to-noise ratio at the tumor site gradually increased over time, reaching a peak at 1 h. These results strongly suggest that [68Ga]Ga-DN68 has broad application prospects as a PET tracer in TNBC imaging.

Imaging and Monitoring HER2 Expression in Tumors during HER2 Antibody-Drug Conjugate Therapy Utilizing a Radiolabeled Site-Specific Single-Domain Antibody Probe: 68Ga-NODAGA-SNA004-GSC.

The overexpression of HER2 is pivotal in the initiation and progression of breast cancer. Developing HER2-targeted radiotracers is crucial for noninvasive assessment of HER2 expression, patient selection for HER2-targeted therapy, monitoring treatment response, and identifying resistance. Here, we reported a nonsite-specific coupled radiotracer, 68Ga-NOTA-SNA004-His6, and a site-specific coupled radiotracer, 68Ga-NODAGA-SNA004-GSC, based on a novel HER2 nanobody, SNA004. Both radiotracers exhibited high affinity, specific targeting, and rapid clearance in vitro and in vivo. Additionally, these tracers and trastuzumab showed noncompetitive binding to HER2. Compared to 68Ga-NOTA-SNA004-His6, 68Ga-NODAGA-SNA004-GSC demonstrated significantly reduced renal and liver uptake. PET/CT imaging with 68Ga-NODAGA-SNA004-GSC sensitively detected the responsiveness of various tumor models to trastuzumab and its antibody-drug conjugates (ADCs). Overall, the site-specific coupled radiotracer 68Ga-NODAGA-SNA004-GSC offered significant advantages in biodistribution and signal-to-noise ratio, making it a valuable tool for monitoring HER2 expression levels before, during, and after trastuzumab and ADC treatment.

Clinical significance of 18F-FDG-PET/CT for detection of incidental pre-malignant and malignant colonic lesions: correlation with colonoscopic and histopathological results.

BACKGROUND: Incidental colorectal fluorodeoxyglucose (FDG) uptake, observed during positron emission tomography/computed tomography (PET/CT) scans, attracts particular attention due to its potential to represent both benign and pre-malignant/malignant lesions. Early detection and excision of these lesions are crucial for preventing cancer development and reducing mortality. This research aims to evaluate the correlation between incidental colorectal FDG uptake on PET/CT with colonoscopic and histopathological results. METHODS: Retrospective analysis was performed on data from all patients who underwent PET/CT between December 2019 and December 2023 in our hospital. The study included 79 patients with incidental colonic FDG uptake who underwent endoscopy. Patient characteristics, imaging parameters, and the corresponding colonoscopy and histopathological results were studied. A comparative analysis was performed among the findings from each of these modalities. The optimal cut-off value of SUVmax for 18F-FDG PET/CT diagnosis of premalignant and malignant lesions was determined by receiver operating characteristic (ROC) curves. The area under the curve (AUC) of SUVmax and the combined parameters of SUVmax and colonic wall thickening (CWT) were analyzed. RESULTS: Among the 79 patients with incidental colorectal FDG uptake, histopathology revealed malignancy in 22 (27.9%) patients and premalignant polyps in 22 (27.9%) patients. Compared to patients with benign lesions, patients with premalignant and malignant lesions were more likely to undergo a PET/CT scan for primary evaluation (p = 0.013), and more likely to have focal GIT uptake (p = 0.001) and CWT (p = 0.001). A ROC curve analysis was made and assesed a cut-off value of 7.66 SUVmax (sensitivity: 64.9% and specificity: 82.4%) to distinguish premalignant and malignant lesions from benign lesions. The AUCs of the SUVmax and the combined parameters of SUVmax and CWT were 0.758 and 0.832 respectively. CONCLUSION: For patients undergo PET/CT for primary evaluation, imaging features of colorectal focal FDG uptake and CWT were more closely associated with premalignant and malignant lesions. The SUVmax helps determine benign and premalignant/malignant lesions of the colorectum. Moreover, the combination of SUVmax and CWT parameters have higher accuracy in estimating premalignant and malignant lesions than SUVmax.

Application of 18F-FDG PET/CT imaging radiomics in the differential diagnosis of single-nodule pulmonary metastases and second primary lung cancer in patients with colorectal cancer.

OBJECTIVE: It is crucially essential to differentially diagnose single-nodule pulmonary metastases (SNPMs) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC), which has important clinical implications for treatment strategies. In this study, we aimed to establish a feasible differential diagnosis model by combining 18F-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) radiomics, computed tomography (CT) radiomics, and clinical features. MATERIALS AND METHODS: CRC patients with SNPM or SPLC who underwent 18F-FDG PET/CT from January 2013 to July 2022 were enrolled in this retrospective study. The radiomic features were extracted by manually outlining the lesions on PET/CT images, and the radiomic modeling was realized by various screening methods and classifiers. In addition, clinical features were analyzed by univariate analysis and logistic regression (LR) analysis to be included in the combined model. Finally, the diagnostic performances of these models were illustrated by the receiver operating characteristic (ROC) curves and the area under the curve (AUC). RESULTS: We studied data from 61 patients, including 36 SNPMs and 25 SPLCs, with an average age of 65.56 ± 10.355 years. Spicule sign and ground-glass opacity (GGO) were significant independent predictors of clinical features (P = 0.012 and P < 0.001, respectively) to build the clinical model. We achieved a PET radiomic model (AUC = 0.789), a CT radiomic model (AUC = 0.818), and a PET/CT radiomic model (AUC = 0.900). The PET/CT radiomic models were combined with the clinical model, and a well-performing model was established by LR analysis (AUC = 0.940). CONCLUSIONS: For CRC patients, the radiomic models we developed had good performance for the differential diagnosis of SNPM and SPLC. The combination of radiomic and clinical features had better diagnostic value than a single model.

Effect of Cyclosporin H on ischemic injury and neutrophil infiltration in cerebral infarct model of rats via PET imaging.

BACKGROUND: Brain ischemia-reperfusion injury is a complex process, and neuroinflammation is an important secondary contributing pathological event. Neutrophils play major roles in ischemic neuroinflammation. Once activated, neutrophils express formyl peptide receptors (FPRs), which are special receptors of a class of chemoattractants and may be potential targets to regulate the activity of neutrophils and control cerebral ischemic injury. This study was aimed to explore the ameliorating effect of Cyclosporin H (CsH), a potent FPR antagonist, on brain ischemic injury by inhibiting the activation and migration of neutrophils, and improving cerebral blood flow. METHODS: We employed a middle cerebral artery occlusion (MCAO) Model on rats and performed behavioral, morphological, and microPET imaging assays to investigate the potential restoring efficacy of CsH on cerebral ischemic damages. Peptide N-cinnamoyl-F-(D)L-F-(D)L-F (cFLFLF), an antagonist to the neutrophil FPR with a high binding affinity, was used for imaging neutrophil distribution. RESULTS: We found that CsH had similar effect with edaravone on improving the neurobehavioral deficient symptoms after cerebral ischemia-reperfusion, and treatment with CsH also alleviated ischemic cerebral infarction. Compared with the MCAO Model group, [18F]FDG uptake ratios of the CsH and edaravone treatment groups were significantly higher. The CsH-treated groups also showed significant increases in [18F]FDG uptake at 144 h when compared with that of 24 h. This result indicates that like edaravone, treatment with both doses of CsH promoted the recovery of blood supply after cerebral ischemic event. Moreover, MCAO-induced cerebral ischemia significantly increased the radiouptake of [68Ga]Ga-cFLFLF at 72 h after ischemia-reperfusion operation. Compared with MCAO Model group, radiouptake values of [68Ga]-cFLFLF in both doses of CsH and edaravone groups were all decreased significantly. These results showed that both doses of CsH resulted in a similar therapeutic effect with edaravone on inhibiting neutrophil infiltration in cerebral infarction. CONCLUSION: Potent FPR antagonist CsH is promisingly beneficial in attenuating neuroinflammation and improving neurobehavioral function against cerebral infarction. Therefore, FPR may become a novel target for regulating neuroinflammation and improving prognosis for ischemic cerebrovascular disorders.

Pancreatic Cancer: An Exocrine Tumor with Endocrine Characteristics.

OBJECTIVE: To examine the characteristics of pancreatic cancer patients with long-term survival. BACKGROUND: Although pancreatic cancer is a highly lethal malignancy, a minority of patients experience long-term survival. The characteristics of these patients remain largely unidentified. METHODS: An indolent subgroup was established using carbohydrate antigen 19-9 (CA19-9), which is the best-validated biomarker for pancreatic cancer. Of 1558 patients, 13.9% were included in the CA19-9-normal (≤ 37 U/mL) subgroup. RESULTS: A normal A19-9 level was an independent variable for overall survival (median survival, 18.1 vs. 9.7 months, hazard ratio = 0.53, P < 0.001). The 5-year survival of patients with stage IV CA19-9-normal cancer was higher than that of patients with stage I-IV CA19-9-high cancer (22.4% vs. 6.8%, P = 0.034). The CA19-9-normal subgroup exhibited reduced levels of circulating glucose (P < 0.001) and increased expression of insulin (P < 0.001) compared with the CA19-9-high subgroup. Glucose was a substrate for CA19-9 biosynthesis through the hexosamine biosynthesis pathway. In addition, in pancreatic cancer animal models of diabetes, glucose control decreased CA19-9 levels and improved overall survival. In a clinical trial (NCT05306028) of patients before undergoing major anticancer treatments, glucose control decreased CA19-9 levels in 90.9% of the patients. CONCLUSIONS: CA19-9-normal pancreatic cancer is a strikingly indolent subgroup with low glucose and high insulin. Glucose control is a promising therapeutic strategy for pancreatic cancer.

A novel 68Ga-labeled cyclic peptide molecular probe based on the computer-aided design for noninvasive imaging of PD-L1 expression in tumors.

Programmed death-ligand 1 (PD-L1) serves as a crucial biomarker for guiding the screening of cancer patients and the stratification of immunotherapy. However, due to the high heterogeneity of tumors, the current gold standard for detecting PD-L1 expression (immunohistochemistry) fails to comprehensively evaluate the overall PD-L1 expression levels in the body. Fortunately, the use of PD-L1 targeted radiotracers enables quantitative, real-time, and noninvasive assessment of PD-L1 expression levels and dynamics in tumors. Notably, analyzing the binding mode between the precursor and the target protein to find linker binding sites that do not affect the activity of the target molecule can greatly enhance the successful development of molecular probes. This study introduced a groundbreaking cyclic peptide molecular probe called 68Ga-DOTA-PG1. It was derived from the BMS-71 cyclic peptide and was specifically designed to evaluate the expression of PD-L1 in tumors. The radiolabeling yield of 68Ga-DOTA-PG1 surpassed 97% while maintaining a radiochemical purity of over 99%. In vitro experiments demonstrated the effective targeting of PD-L1 in tumor cells by 68Ga-DOTA-PG1, with significantly higher cellular uptake observed in A375-hPD-L1 cells (PD-L1 + ) compared to A375 cells (PD-L1-). Biodistribution and PET imaging studies consistently showed specific accumulation of 68Ga-DOTA-PG1 in A375-hPD-L1 tumors, with a maximum uptake of 11.06 ± 1.70% ID/g at 2 h, significantly higher than the tumor uptake in A375 cells (1.70 ± 0.17% ID/g). These results strongly indicated that 68Ga-DOTA-PG1 held great promise as a PET radiotracer for imaging PD-L1-positive tumors.

Radiomic signatures based on pretreatment 18F-FDG PET/CT, combined with clinicopathological characteristics, as early prognostic biomarkers among patients with invasive breast cancer.

Purpose: The aim of this study was to investigate the predictive role of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in the prognostic risk stratification of patients with invasive breast cancer (IBC). To achieve this, we developed a clinicopathologic-radiomic-based model (C-R model) and established a nomogram that could be utilized in clinical practice. Methods: We retrospectively enrolled a total of 91 patients who underwent preoperative 18F-FDG PET/CT and randomly divided them into training (n=63) and testing cohorts (n=28). Radiomic signatures (RSs) were identified using the least absolute shrinkage and selection operator (LASSO) regression algorithm and used to compute the radiomic score (Rad-score). Patients were assigned to high- and low-risk groups based on the optimal cut-off value of the receiver operating characteristic (ROC) curve analysis for both Rad-score and clinicopathological risk factors. Univariate and multivariate Cox regression analyses were performed to determine the association between these variables and progression-free survival (PFS) or overall survival (OS). We then plotted a nomogram integrating all these factors to validate the predictive performance of survival status. Results: The Rad-score, age, clinical M stage, and minimum standardized uptake value (SUVmin) were identified as independent prognostic factors for predicting PFS, while only Rad-score, age, and clinical M stage were found to be prognostic factors for OS in the training cohort. In the testing cohort, the C-R model showed superior performance compared to single clinical or radiomic models. The concordance index (C-index) values for the C-R model, clinical model, and radiomic model were 0.816, 0.772, and 0.647 for predicting PFS, and 0.882, 0.824, and 0.754 for OS, respectively. Furthermore, decision curve analysis (DCA) and calibration curves demonstrated that the C-R model had a good ability for both clinical net benefit and application. Conclusion: The combination of clinicopathological risks and baseline PET/CT-derived Rad-score could be used to evaluate the prognosis in patients with IBC. The predictive nomogram based on the C-R model further enhanced individualized estimation and allowed for more accurate prediction of patient outcomes.

Assessment of androgen receptor expression in breast cancer patients using 18 F-FDG PET/CT radiomics and clinicopathological characteristics.

OBJECTIVE: In the present study, we mainly aimed to predict the expression of androgen receptor (AR) in breast cancer (BC) patients by combing radiomic features and clinicopathological factors in a non-invasive machine learning way. MATERIALS AND METHODS: A total of 48 BC patients, who were initially diagnosed by 18F-FDG PET/CT, were retrospectively enrolled in this study. LIFEx software was used to extract radiomic features based on PET and CT data. The most useful predictive features were selected by the LASSO (least absolute shrinkage and selection operator) regression and t-test. Radiomic signatures and clinicopathologic characteristics were incorporated to develop a prediction model using multivariable logistic regression analysis. The receiver operating characteristic (ROC) curve, Hosmer-Lemeshow (H-L) test, and decision curve analysis (DCA) were conducted to assess the predictive efficiency of the model. RESULTS: In the univariate analysis, the metabolic tumor volume (MTV) was significantly correlated with the expression of AR in BC patients (p < 0.05). However, there only existed feeble correlations between estrogen receptor (ER), progesterone receptor (PR), and AR status (p = 0.127, p = 0.061, respectively). Based on the binary logistic regression method, MTV, SHAPE_SphericityCT (CT Sphericity from SHAPE), and GLCM_ContrastCT (CT Contrast from grey-level co-occurrence matrix) were included in the prediction model for AR expression. Among them, GLCM_ContrastCT was an independent predictor of AR status (OR = 9.00, p = 0.018). The area under the curve (AUC) of ROC in this model was 0.832. The p-value of the H-L test was beyond 0.05. CONCLUSIONS: A prediction model combining radiomic features and clinicopathological characteristics could be a promising approach to predict the expression of AR and noninvasively screen the BC patients who could benefit from anti-AR regimens.

Development of a radiomic-clinical nomogram for prediction of survival in patients with diffuse large B-cell lymphoma treated with chimeric antigen receptor T cells.

BACKGROUND: In our current work, an 18F-FDG PET/CT radiomics-based model was developed to assess the progression-free survival (PFS) and overall survival (OS) of patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who received chimeric antigen receptor (CAR)-T cell therapy. METHODS: A total of 61 DLBCL cases receiving 18F-FDG PET/CT before CAR-T cell infusion were included in the current analysis, and these patients were randomly assigned to a training cohort (n = 42) and a validation cohort (n = 19). Radiomic features from PET and CT images were obtained using LIFEx software, and radiomics signatures (R-signatures) were then constructed by choosing the optimal parameters according to their PFS and OS. Subsequently, the radiomics model and clinical model were constructed and validated. RESULTS: The radiomics model that integrated R-signatures and clinical risk factors showed superior prognostic performance compared with the clinical models in terms of both PFS (C-index: 0.710 vs. 0.716; AUC: 0.776 vs. 0.712) and OS (C-index: 0.780 vs. 0.762; AUC: 0.828 vs. 0.728). For validation, the C-index of the two approaches was 0.640 vs. 0.619 and 0.676 vs. 0.699 for predicting PFS and OS, respectively. Moreover, the AUC was 0.886 vs. 0.635 and 0.778 vs. 0.705, respectively. The calibration curves indicated good agreement, and the decision curve analysis suggested that the net benefit of radiomics models was higher than that of clinical models. CONCLUSIONS: PET/CT-derived R-signature could be a potential prognostic biomarker for R/R DLBCL patients undergoing CAR-T cell therapy. Moreover, the risk stratification could be further enhanced when the PET/CT-derived R-signature was combined with clinical factors.

Analysis of Positive Results of 18F-FDG PET/CT Imaging after Hematopoietic Stem Cell Transplantation in Lymphoma.

PURPOSE: The purpose of this study was to differentiate between false-positive and true-positive positron emission tomography (PET) results after hematopoietic stem cell transplantation (SCT) for lymphoma involvement by analyzing several clinical variables and specific imaging features. PATIENTS AND METHODS: Patients with lymphoma who received SCT and underwent post-transplantation 18F-FDG PET/CT scans between January 2013 and April 2021 at our institution were included. Associations between PET positivity and related clinical information were assessed using t-tests and χ2 tests. The significance of variables differentiating benign lesions from malignant FDG-avid lesions was evaluated by logistic regression analysis. Survival probabilities were derived from Kaplan-Meier curves and compared using the log-rank test. RESULTS: A total of 185 patients (235 post-transplantation PET/CT scans) were enrolled in our present study. Compared with those with true-positive PET results, patients with false-positive PET results exhibited a better prognosis. For the autologous SCT group, false-positive cases were more commonly seen when FDG-avid foci appeared outside the sites of the original disease (p = 0.004), and the integrated CT imaging showed negative results (p = 0.000). In multivariate logistic regression analysis, integrated CT results were the only significant factor. For the allogeneic SCT group, false-positive cases were significantly more commonly seen when DS = 4 (p = 0.046), FDG-avid foci appeared outside the sites of the original disease (p = 0.022), and the integrated CT imaging showed negative results (p = 0.001). In a multivariate logistic regression analysis, whether FDG-avid foci were in the sites of the original disease and integrated CT results were both significant factors. CONCLUSION: False-positive FDG uptake in post-transplantation PET was not uncommon. Several variables could provide an important reference to differentiate false-positive from true-positive post-SCT PET results for lymphoma involvement. TRIAL REGISTRATION NUMBER: ChiCTR2300067355.

The Differential Diagnostic Value of Radiomics Signatures Between Single-Nodule Pulmonary Metastases and Second Primary Lung Cancer in Patients with Colorectal Cancer.

BACKGROUND: Differential diagnosis of single-nodule pulmonary metastasis (SNPM) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC) prior to lung surgery is relatively complex. Radiomics is an emerging technique for image information analysis, while it has not yet been applied to construct a differential diagnostic model between SNPM and SPLC in patients with CRC. In the present study, we aimed to extract radiomics signatures from thin-section computed tomography (CT) images of the chest. These radiomics signatures were combined with clinical features to construct a composite differential diagnostic model. METHOD: A total of 91 patients with CRC, including 66 patients with SNPM and 25 patients with SPLC, were enrolled in this study. Patients were randomly assigned to the training cohort (n = 63) and validation cohort (n = 28) at a ratio of 7 to 3. Moreover, 107 radiomics features were extracted from the chest thin-section CT images. The least absolute shrinkage and selection operator (LASSO) regression was used to filter these features, and clinical features were screened by univariate analysis. The screened radiomics and clinical features were combined to construct a multifactorial logistic regression composite model. The receiver operating characteristic (ROC) curves were adopted to evaluate the models, and the corresponding nomograms were created. RESULTS: A series of 6 radiomics characteristics was screened by LASSO. After univariate logistic regression analysis, the composite model finally included 4 radiomics features and 4 clinical features. In the training cohort, the area under the curve scores of ROC curves were 0.912 (95% confidence interval [CI]: 0.813-0.969), 0.884 (95% CI: 0.778-0.951), and 0.939 (95% CI: 0.848-0.984) for models derived from radiomics, clinical, and combined features, respectively. Similarly, these values were 0.756 (95% CI: 0.558-0.897), 0.888 (95% CI: 0.711-0.975), and 0.950 (95% CI: 0.795-0.997) in the validation cohort, respectively. CONCLUSIONS: We constructed a model for differential diagnosis of SNPM and SPLC in patients with CRC using radiomics and clinical features. Moreover, our findings provided a new assessment tool for patients with CRC in the future.

EGFR is a potential therapeutic target for highly glycosylated and aggressive pancreatic neuroendocrine neoplasms.

pNENs are relative indolent tumors with heterogeneous clinical presentation at diagnosis. It is important to establish aggressive subgroups of pNENs and identify potential therapeutic targets. Patients with pNEN (322 cases) were included to examine the association between glycosylation biomarkers and clinical/pathological traits. The molecular and metabolic features stratified by glycosylation status were assessed by RNA-seq/whole exome sequencing and immunohistochemistry. A considerable proportion of patients had elevated glycosylation biomarkers (carbohydrate antigen [CA] 19-9, 11.9%; CA125, 7.5%; carcinoembryonic antigen [CEA], 12.8%). CA19-9 (hazard ratio [HR] = 2.26, P = .019), CA125 (HR = 3.79, P = .004) and CEA (HR = 3.16, P = .002) were each independent prognostic variables for overall survival. High glycosylation group, defined as pNENs with elevated level of circulating CA19-9, CA125 or CEA, accounted for 23.4% of all pNENs. High glycosylation (HR = 3.14, P = .001) was an independent prognostic variable for overall survival and correlated with G3 grade (P < .001), poor differentiation (P = .001), perineural invasion (P = .004) and distant metastasis (P < .001). Epidermal growth factor receptor (EGFR) was enriched in high glycosylation pNENs using RNA-seq. EGFR was expressed in 21.2% of pNENs using immunohistochemistry and associated with poor overall survival (P = .020). A clinical trial focusing on EGFR expressed pNENs was initiated (NCT05316480). Thus, pNEN with aberrant glycosylation correlates with a dismal outcome and suggests potential therapeutic target of EGFR.

Glutamine deprivation induces ferroptosis in pancreatic cancer cells.

Ferroptosis is a type of programmed cell death closely related to amino acid metabolism. Pancreatic cancer cells have a strong dependence on glutamine, which serves as a carbon and nitrogen substrate to sustain rapid growth. Glutamine also aids in self-protection mechanisms. However, the effect of glutamine on ferroptosis in pancreatic cancer remains largely unknown. Here, we aim to explore the association between ferroptosis and glutamine deprivation in pancreatic cancer. The growth of pancreatic cancer cells in culture media with or without glutamine is evaluated using Cell Counting Kit-8. Reactive oxygen species (ROS) are measured by 2',7'-dichlorodihydrofluorescein diacetate staining. Ferroptosis is assessed by BODIPY-C11 dye using confocal microscopy and flow cytometry. Amino acid concentrations are measured using ultrahigh-performance liquid chromatography-tandem mass spectrometry. Isotope-labelled metabolic flux analysis is performed to track the metabolic flow of glutamine. Additionally, RNA sequencing is performed to analyse the genetic alterations. Glutamine deprivation inhibits pancreatic cancer growth and induces ferroptosis both in vitro and in vivo. Additionally, glutamine decreases ROS formation via glutathione production in pancreatic cancer cells. Interestingly, glutamine inhibitors (diazooxonorleucine and azaserine) promotes ROS formation and ferroptosis in pancreatic cancer cells. Furthermore, ferrostatin, a ferroptosis inhibitor, rescues ferroptosis in pancreatic cancer cells. Glutamine deprivation leads to changes in molecular pathways, including cytokine-cytokine receptor interaction pathways ( CCL5, CCR4, LTA, CXCR4, IL-6R, and IL-7R). Thus, exogenous glutamine is required for the detoxification of ROS in pancreatic cancer cells, thereby preventing ferroptosis.

Glutamine is a substrate for glycosylation and CA19-9 biosynthesis through hexosamine biosynthetic pathway in pancreatic cancer.

BACKGROUND: Carbohydrate antigen 19-9 (CA19-9) is the most widely used biomarker for pancreatic cancer. Since CA19-9 closely correlates with patient outcome and tumor stage in pancreatic cancer, the deciphering of CA19-9 biosynthesis provides a potential clue for treatment. METHODS: Concentration of amino acids was detected by ultrahigh-performance liquid chromatography tandem mass spectrometry. Metabolic flux of glutamine was examined by isotope tracing untargeted metabolomics. Label-free quantitative N-glycosylation proteomics was used to examine N-glycosylation alterations. RESULTS: Among all amino acids, glutamine was higher in CA19-9-high pancreatic cancers (> 37 U/mL, 66 cases) than in CA19-9-normal clinical specimens (≤ 37 U/mL, 37 cases). The glutamine concentration in clinical specimens was positively correlated with liver metastasis or lymphovascular invasion. Glutamine blockade using diazooxonorleucine suppressed pancreatic cancer growth and intraperitoneal and lymphatic metastasis. Glutamine promotes O-GlcNAcylation, protein glycosylation, and CA19-9 biosynthesis through the hexosamine biosynthetic pathway. UDP-N-acetylglucosamine (UDP-GlcNAc) levels correlated with the glutamine influx through hexosamine biosynthetic pathway and supported CA19-9 biosynthesis. CONCLUSIONS: Glutamine is a substrate for CA19-9 biosynthesis in pancreatic cancer. Glutamine blockade may be a potential therapeutic strategy for pancreatic cancer.

Modality-Specific Segmentation Network for Lung Tumor Segmentation in PET-CT Images.

Lung tumor segmentation in PET-CT images plays an important role to assist physicians in clinical application to accurately diagnose and treat lung cancer. However, it is still a challenging task in medical image processing field. Due to respiration and movement, the lung tumor varies largely in PET images and CT images. Even the two images are almost simultaneously collected and registered, the shape and size of lung tumors in PET-CT images are different from each other. To address these issues, a modality-specific segmentation network (MoSNet) is proposed for lung tumor segmentation in PET-CT images. MoSNet can simultaneously segment the modality-specific lung tumor in PET images and CT images. MoSNet learns a modality-specific representation to describe the inconsistency between PET images and CT images and a modality-fused representation to encode the common feature of lung tumor in PET images and CT images. An adversarial method is proposed to minimize an approximate modality discrepancy through an adversarial objective with respect to a modality discriminator and reserve modality-common representation. This improves the representation power of the network for modality-specific lung tumor segmentation in PET images and CT images. The novelty of MoSNet is its ability to produce a modality-specific map that explicitly quantifies the modality-specific weights for the features in each modality. To demonstrate the superiority of our method, MoSNet is validated in 126 PET-CT images with NSCLC. Experimental results show that MoSNet outperforms state-of-the-art lung tumor segmentation methods.

Prognostic value of 18F-FDG PET/CT radiomic model based on primary tumor in patients with non-small cell lung cancer: A large single-center cohort study.

Objectives: In the present study, we aimed to determine the prognostic value of the 18F-FDG PET/CT-based radiomics model when predicting progression-free survival (PFS) and overall survival (OS) in patients with non-small cell lung cancer (NSCLC). Methods: A total of 368 NSCLC patients who underwent 18F-FDG PET/CT before treatment were randomly assigned to the training (n = 257) and validation (n = 111) cohorts. Radiomics signatures from PET and CT images were obtained using LIFEx software, and then clinical and complex models were constructed and validated by selecting optimal parameters based on PFS and OS to construct radiomics signatures. Results: In the training cohort, the C-index of the clinical model for predicting PFS and OS in NSCLC patients was 0.748 and 0.834, respectively, and the AUC values ​​were 0.758 and 0.846, respectively. The C-index of the complex model for predicting PFS and OS was 0.775 and 0.881, respectively, and the AUC values ​​were 0.780 and 0.891, respectively. The C-index of the clinical model for predicting PFS and OS in the validation group was 0.729 and 0.832, respectively, and the AUC values ​​were 0.776 and 0.850, respectively. The C-index of the complex model for predicting PFS and OS was 0.755 and 0.867, respectively, and the AUC values ​​were 0.791 and 0.874, respectively. Moreover, decision curve analysis showed that the complex model had a higher net benefit than the clinical model. Conclusions: 18F-FDG PET/CT radiomics before treatment could predict PFS and OS in NSCLC patients, and the predictive power was higher when combined with clinical factors.

A Rare Case of Thymic Rosai-Dorfman Disease Mimicking Malignancy on 18F-FDG PET/CT.

Background Rosai-Dorfman disease (RDD), the massive lymphadenopathy characterized by the proliferation of sinus histiocytosis, is a relatively idiopathic benign disease with unknown etiology. We reported a rare case of thymic RDD detected by 18F-FDG PET/CT. A 23-year-old man with right-sided chest pain underwent 18F-FDG PET/CT scan, showing increased 18F-FDG uptake in an anterior mediastinal mass corresponding to a thymic lesion at an enhanced CT scan. The patient was referred to surgery with the clinical suspicion of thymic malignancy. The histological examination and immunohistochemical results confirmed RDD. Conclusions This was the first case report of RDD isolated to the thymus and initially presented with chest pain. Moreover, there was no characteristic painless neck lymphadenopathy at any stage of the disease course. Thus, for young patients with thymus mass, RDD should be considered a rare but possible diagnosis.

Cross modality fusion for modality-specific lung tumor segmentation in PET-CT images.

Although positron emission tomography-computed tomography (PET-CT) images have been widely used, it is still challenging to accurately segment the lung tumor. The respiration, movement and imaging modality lead to large modality discrepancy of the lung tumors between PET images and CT images. To overcome these difficulties, a novel network is designed to simultaneously obtain the corresponding lung tumors of PET images and CT images. The proposed network can fuse the complementary information and preserve modality-specific features of PET images and CT images. Due to the complementarity between PET images and CT images, the two modality images should be fused for automatic lung tumor segmentation. Therefore, cross modality decoding blocks are designed to extract modality-specific features of PET images and CT images with the constraints of the other modality. The edge consistency loss is also designed to solve the problem of blurred boundaries of PET images and CT images. The proposed method is tested on 126 PET-CT images with non-small cell lung cancer, and Dice similarity coefficient scores of lung tumor segmentation reach 75.66 ± 19.42 in CT images and 79.85 ± 16.76 in PET images, respectively. Extensive comparisons with state-of-the-art lung tumor segmentation methods have also been performed to demonstrate the superiority of the proposed network.