Identification of macrotrabecular-massive hepatocellular carcinoma through multiphasic CT-based representation learning method.

BACKGROUND: Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) represents an aggressive subtype of HCC and is associated with poor survival. PURPOSE: To investigate the performance of a representation learning-based feature fusion strategy that employs a multiphase contrast-enhanced CT (mpCECT)-based latent feature fusion (MCLFF) model for MTM-HCC identification. METHODS: A total of 206 patients (54 MTM HCC, 152 non-MTM HCC) who underwent preoperative mpCECT with surgically confirmed HCC between July 2017 and December 2022 were retrospectively included from two medical centers. Multiphasic radiomics features were extracted from manually delineated volume of interest (VOI) of all lesions on each mpCECT phase. Representation learning based MCLFF model was built to fuse multiphasic features for MTM HCC prediction, and compared with competing models using other fusion methods. Conventional imaging features and clinical factors were also evaluated and analyzed. Prediction performance was validated by ROC analysis and statistical comparisons on an internal validation and an external testing dataset. RESULTS: Fusion of radiomics features from the arterial phase (AP) and portal venous phase (PAP) using MCLFF demonstrated superior performance in MTM HCC prediction, with a higher AUC of 0.857 compared with all competing models in the internal validation set. Integration of multiple radiological or clinical features further improved the overall performance, with the highest AUCs of 0.857 and 0.836 respectively achieved in the internal validation and external testing set. CONCLUSIONS: Multiphasic radiomics features of AP and PVP fused by the MCLFF have demonstrated substantial potential in the accurate prediction of MTM HCC. Clinical factors and Radiological features in mpCECT contribute incremental values to the developed MCLFF strategy.

Mediator complex subunit 1 promotes oral squamous cell carcinoma progression by activating MMP9 transcription and suppressing CD8+ T cell antitumor immunity.

BACKGROUND: The role of Mediator complex subunit 1 (MED1), a pivotal transcriptional coactivator implicated in diverse biological pathways, remains unexplored in the context of oral squamous cell carcinoma (OSCC). This study aims to elucidate the contributory mechanisms and potential impact of MED1 on the progression of OSCC. METHODS: The expression and clinical significance of MED1 in OSCC tissues were evaluated through the bioinformatics analyses. The effects of MED1 on the biological behavior of OSCC cancer cells were assessed both in vitro and in vivo. Dual-luciferase reporter assay, chromatin immunoprecipitation (ChIP) assay, bioinformatic analysis, CD8+ T cell isolation experiment, coculture experiment, enzyme-linked immunosorbent assay (ELISA), and flow cytometric analysis were employed to elucidate the underlying mechanism through which MED1 operates in the progression of OSCC. RESULTS: MED1 exhibited upregulation in both OSCC tissues and multiple OSCC cell lines, which correlated with decreased overall survival in patients. In vitro experiments demonstrated that knockdown of MED1 in metastatic OSCC cell lines SCC-9 and UPCI-SCC-154 hindered cell migration and invasion, while overexpression of MED1 promoted these processes. Whereas, MED1 knockdown had no impact on proliferation of cell lines mentioned above. In vivo studies further revealed that downregulation of MED1 effectively suppressed distant metastasis in OSCC. Mechanistically, MED1 enhanced the binding of transcription factors c-Jun and c-Fos to the matrix metalloprotein 9 (MMP9) promoters, resulting in a significant upregulation of MMP9 transcription. This process contributes to the migration and invasion of SCC-9 and UPCI-SCC-154 cells. Furthermore, MED1 modulated the expression of programmed death-ligand 1 (PD-L1) through the Notch signaling pathway, consequently impacting the tumor-killing capacity of CD8+ T cells in the tumor microenvironment. CONCLUSIONS: Our findings indicate that MED1 plays a pivotal role in OSCC progression through the activation of MMP9 transcription and suppression of CD8+ T cell antitumor immunity, suggesting that MED1 may serve as a novel prognostic marker and therapeutic target in OSCC.

iRGD-mediated liposomal nanoplatforms for improving hepatocellular carcinoma targeted combination immunotherapy and monitoring tumor response via IVIM-MRI.

The combination therapy of targeted treatments and immune checkpoint blockade (ICB) holds great promise for hepatocellular carcinoma (HCC) treatment. However, challenges such as immunogenicity, off-target toxicity of ICB antibodies, low drug co-delivery efficiency, and lack of effective biomarkers to monitor treatment response limit the efficacy of existing targeted immunotherapies. Herein, we synthesized iRGD-modified pH-sensitive liposomal nanoparticles co-encapsulating lenvatinib (Len) and the small molecule PD-1/PD-L1 inhibitor BMS-202 (iRGD-lip@Len/BMS-202) to address issues related to inadequate tumor enrichment and distinct pharmacokinetics of these drugs. Furthermore, intravoxel incoherent motion-magnetic resonance imaging (IVIM-MRI), which is calculated using a biexponential model, can simultaneously reflect both the diffusion of water molecules within the tissue and the microcirculatory perfusion of capillaries. Consequently, we further assessed the feasibility of using IVIM-MRI to monitor the cancer treatment response in nanodrug therapy. These results demonstrated that the iRGD-targeted liposomal nanodrug effectively accumulated in tumors and released in acidic microenvironments. The sustained release of Len facilitated tumor vascular normalization, decreased the presence of Tregs and MDSCs and activated the IFN-γ signaling pathway. This led to increased PD-L1 expression in tumor cells, enhancing the sensitivity of BMS-202. Consequently, there was a synergistic amplification of antitumor immune therapy, resulting in the shrinkage of subcutaneous and orthotopic HCC and inhibition of lung metastasis. Furthermore, IVIM-MRI technology facilitated the non-invasive monitoring of the tumor microenvironment (TME), revealing critical therapeutic response indicators such as the normalization of tumor blood vessels and the degree of hypoxia. Collectively, the combination of Food and Drug Administration (FDA)-approved drugs with iRGD-modified liposomes presents a promising strategy for HCC treatment. Simultaneously, IVIM-MRI provides a non-invasive method to accurately predict the response to this nanodrug.

Analysis of the risk factors of the radiation-induced encephalopathy in nasopharyngeal carcinoma: A retrospective cohort study.

To analyze the related factors of radiation-induced encephalopathy in nasopharyngeal carcinoma (NPC) to identify the risk factors and their clinical significance. This retrospective cohort study included 707 NPC patients. They had undergone conventional and enhanced computed tomography or magnetic resonance imaging scans. They were divided into the radiation-induced encephalopathy group and the no encephalopathy group according to the imaging examination. Detailed clinical information was collected. The incidence of radiation-induced encephalopathy in NPC was 22.2%, in which 124 were radiation-induced encephalopathy and 33 were reirradiation patients. We found that age, pathological type, radiation method, hypertension, radiation course, relapse, carotid/cerebral arteriosclerosis, clinical stage, and radiotherapy dose were statistically significant between the two groups (p < 0.05). Multiple logistic regression showed that clinical stage, age, radiotherapy method, hypertension, carotid/cerebral arteriosclerosis, and radiation courses after a reoccurrence of NPC were risk factors for radiation-induced encephalopathy. The more advanced the clinical stage was and the older the patient, the greater the risk. Radiotherapy method, radiation course, hypertension, carotid/cerebral arteriosclerosis, age, and clinical stage were the risk factors associated with radiation-induced encephalopathy in NPC.

Androgen receptor deficiency-induced TUG1 in suppressing ferroptosis to promote benign prostatic hyperplasia through the miR-188-3p/GPX4 signal pathway.

Benign prostatic hyperplasia (BPH), characterized by the non-malignant enlargement of the prostate, exhibits a pronounced association with inflammation resulting from androgen receptor (AR) deficiency. Ferroptosis, a cell death mechanism triggered by iron-dependent lipid peroxidation and closely linked to inflammation, has yet to be fully understood in the context of BPH. Using RNA sequencing, we observed a significant elevation of taurine-upregulated gene 1 (TUG1) long noncoding RNA (lncRNA) in BPH tissues compared to normal prostate tissue. High levels of TUG1 exhibited a discernible correlation with both prostate volume and the extent of inflammatory infiltration in BPH patients. The suppression of TUG1 not only led to a reduction in prostate size but also ameliorated AR-deficiency-induced prostatic hyperplasia. Mechanistically, a decrease in AR in prostate luminal cells prompted macrophage aggregation and the release of IL-1ß, subsequently fostering the transcription of TUG1 via MYC. Induced TUG1, through competitive binding with miR-188-3p, facilitated the expression of GPX4, thereby diminishing intracellular ROS levels and impeding ferroptosis in prostate luminal cells. Notably, the ferroptosis inducer JKE-1674 alleviated inflammation-induced prostatic hyperplasia in vivo. Together, these findings suggest that AR deficiency crucially inhibits ferroptosis, promoting BPH via the TUG1/miR-188-3p/GPX4 signaling axis, and making ferroptosis induction a promising therapeutic strategy for BPH patients with AR deficiency.

TSHR Variant Screening and Phenotype Analysis in 367 Chinese Patients With Congenital Hypothyroidism.

Background: Genetic defects in the human thyroid-stimulating hormone (TSH) receptor (TSHR) gene can cause congenital hypothyroidism (CH). However, the biological functions and comprehensive genotype-phenotype relationships for most TSHR variants associated with CH remain unexplored. We aimed to identify TSHR variants in Chinese patients with CH, analyze the functions of the variants, and explore the relationships between TSHR genotypes and clinical phenotypes. Methods: In total, 367 patients with CH were recruited for TSHR variant screening using whole-exome sequencing. The effects of the variants were evaluated by in-silico programs such as SIFT and polyphen2. Furthermore, these variants were transfected into 293T cells to detect their Gs/cyclic AMP and Gq/11 signaling activity. Results: Among the 367 patients with CH, 17 TSHR variants, including three novel variants, were identified in 45 patients, and 18 patients carried biallelic TSHR variants. In vitro experiments showed that 10 variants were associated with Gs/cyclic AMP and Gq/11 signaling pathway impairment to varying degrees. Patients with TSHR biallelic variants had lower serum TSH levels and higher free triiodothyronine and thyroxine levels at diagnosis than those with DUOX2 biallelic variants. Conclusions: We found a high frequency of TSHR variants in Chinese patients with CH (12.3%), and 4.9% of cases were caused by TSHR biallelic variants. Ten variants were identified as loss-of-function variants. The data suggest that the clinical phenotype of CH patients caused by TSHR biallelic variants is relatively mild. Our study expands the TSHR variant spectrum and provides further evidence for the elucidation of the genetic etiology of CH.

Nanoparticle-mediated blockade of CXCL12/CXCR4 signaling enhances glioblastoma immunotherapy: Monitoring early responses with MRI radiomics.

The limited therapeutic efficacy of checkpoint blockade immunotherapy against glioblastoma is closely related to the blood-brain barrier (BBB) and tumor immunosuppressive microenvironment, where the latter is driven primarily by tumor-associated myeloid cells (TAMCs). Targeting the C-X-C motif chemokine ligand-12/C-X-C motif chemokine receptor-4 (CXCL12/CXCR4) signaling orchestrates the recruitment of TAMCs and has emerged as a promising approach for alleviating immunosuppression. Herein, we developed an iRGD ligand-modified polymeric nanoplatform for the co-delivery of CXCR4 antagonist AMD3100 and the small-molecule immune checkpoint inhibitor BMS-1. The iRGD peptide facilitated superior BBB crossing and tumor-targeting abilities both in vitro and in vivo. In mice bearing orthotopic GL261-Luc tumor, co-administration of AMD3100 and BMS-1 significantly inhibited tumor proliferation without adverse effects. A reprogramming of immunosuppression upon CXCL12/CXCR4 signaling blockade was observed, characterized by the reduction of TAMCs and regulatory T cells, and an increased proportion of CD8+T lymphocytes. The elevation of interferon-γ secreted from activated immune cells upregulated PD-L1 expression in tumor cells, highlighting the synergistic effect of BMS-1 in counteracting the PD-1/PD-L1 pathway. Finally, our research unveiled the ability of MRI radiomics to reveal early changes in the tumor immune microenvironment following immunotherapy, offering a powerful tool for monitoring treatment responses. STATEMENT OF SIGNIFICANCE: The insufficient BBB penetration and immunosuppressive tumor microenvironment greatly diminish the efficacy of immunotherapy for glioblastoma (GBM). In this study, we prepared iRGD-modified polymeric nanoparticles, loaded with a CXCR4 antagonist (AMD3100) and a small-molecule checkpoint inhibitor of PD-L1 (BMS-1) to overcome physical barriers and reprogram the immunosuppressive microenvironment in orthotopic GBM models. In this nanoplatform, AMD3100 converted the "cold" immune microenvironment into a "hot" one, while BMS-1 synergistically counteracted PD-L1 inhibition, enhancing GBM immunotherapy. Our findings underscore the potential of dual-blockade of CXCL12/CXCR4 and PD-1/PD-L1 pathways as a complementary approach to maximize therapeutic efficacy for GBM. Moreover, our study revealed that MRI radiomics provided a clinically translatable means to assess immunotherapeutic efficacy.

Multiparametric MR-based feature fusion radiomics combined with ADC maps-based tumor proliferative burden in distinguishing TNBC versus non-TNBC.

Objective.To investigate the incremental value of quantitative stratified apparent diffusion coefficient (ADC) defined tumor habitats for differentiating triple negative breast cancer (TNBC) from non-TNBC on multiparametric MRI (mpMRI) based feature-fusion radiomics (RFF) model.Approach.466 breast cancer patients (54 TNBC, 412 non-TNBC) who underwent routine breast MRIs in our hospital were retrospectively analyzed. Radiomics features were extracted from whole tumor on T2WI, diffusion-weighted imaging, ADC maps and the 2nd phase of dynamic contrast-enhanced MRI. Four models including the RFFmodel (fused features from all MRI sequences), RADCmodel (ADC radiomics feature), StratifiedADCmodel (tumor habitas defined on stratified ADC parameters) and combinational RFF-StratifiedADCmodel were constructed to distinguish TNBC versus non-TNBC. All cases were randomly divided into a training (n= 337) and test set (n= 129). The four competing models were validated using the area under the curve (AUC), sensitivity, specificity and accuracy.Main results.Both the RFFand StratifiedADCmodels demonstrated good performance in distinguishing TNBC from non-TNBC, with best AUCs of 0.818 and 0.773 in the training and test sets. StratifiedADCmodel revealed significant different tumor habitats (necrosis/cysts habitat, chaotic habitat or proliferative tumor core) between TNBC and non-TNBC with its top three discriminative parameters (p <0.05). The integrated RFF-StratifiedADCmodel demonstrated superior accuracy over the other three models, with higher AUCs of 0.832 and 0.784 in the training and test set, respectively (p <0.05).Significance.The RFF-StratifiedADCmodel through integrating various tumor habitats' information from whole-tumor ADC maps-based StratifiedADCmodel and radiomics information from mpMRI-based RFFmodel, exhibits tremendous promise for identifying TNBC.

A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI.

PURPOSE: To explore a subregion-based RadioFusionOmics (RFO) model for discrimination between adult-type grade 4 astrocytoma and glioblastoma according to the 2021 WHO CNS5 classification. METHODS: 329 patients (40 grade 4 astrocytomas and 289 glioblastomas) with histologic diagnosis was retrospectively collected from our local institution and The Cancer Imaging Archive (TCIA). The volumes of interests (VOIs) were obtained from four multiparametric MRI sequences (T1WI, T1WI + C, T2WI, T2-FLAIR) using (1) manual segmentation of the non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE), and (2) K-means clustering of four habitats (H1: high T1WI + C, high T2-FLAIR; (2) H2: high T1WI + C, low T2-FLAIR; (3) H3: low T1WI + C, high T2-FLAIR; and (4) H4: low T1WI + C, low T2-FLAIR). The optimal VOI and best MRI sequence combination were determined. The performance of the RFO model was evaluated using the area under the precision-recall curve (AUPRC) and the best signatures were identified. RESULTS: The two best VOIs were manual VOI3 (putative peritumoral edema) and clustering H34 (low T1WI + C, high T2-FLAIR (H3) combined with low T1WI + C and low T2-FLAIR (H4)). Features fused from four MRI sequences ([Formula: see text]) outperformed those from either a single sequence or other sequence combinations. The RFO model that was trained using fused features [Formula: see text] achieved the AUPRC of 0.972 (VOI3) and 0.976 (H34) in the primary cohort (p = 0.905), and 0.971 (VOI3) and 0.974 (H34) in the testing cohort (p = 0.402). CONCLUSION: The performance of subregions defined by clustering was comparable to that of subregions that were manually defined. Fusion of features from the edematous subregions of multiple MRI sequences by the RFO model resulted in differentiation between grade 4 astrocytoma and glioblastoma.

Integrated Diffusion Tensor Imaging and Renal Parenchymal Volume for Early Detection and Grading of Split Renal Functional Impairment in Lupus Nephritis.

RATIONALE AND OBJECTIVES: To investigate the effectiveness of combining split diffusion tensor imaging (DTI) measurements with split renal parenchymal volume (RPV) for assessing split renal functional impairment in patients with lupus nephritis (LN). MATERIALS AND METHODS: Seventy-four participants [48 LN patients and 26 healthy volunteers (HV)] were included in the study. All participant underwent conventional MR and DTI (b = 0, 400, and 600 s/mm2) examinations using a 3.0 T MRI scanner to determine the split renal DTI measurements and split RPV. In LN patients, renography glomerular filtration rate (rGFR) was measured using 99mTc-DTPA scintigraphy based on Gates' method, serving as the reference standard to categorize all split kidneys of LN patients into LN with mild impairment (LNm, n = 65 kidneys) and LN with moderate to severe (LNms, n = 31 kidneys) groups according to the threshold of 30 ml/min in spilt rGFR. All statistical analyses were performed using SPSS 25.0 and MedCalc 20.0 software packages. RESULTS: Only split medullary fractional anisotropy (FA) and the product of split medullary FA and RPV could distinguish pairwise subgroups among the HV and each LN subgroup (all p < 0.05). ROC curve analysis demonstrated that split medullary FA (AUC = 0.866) significantly outperformed other parameters in differentiating HV from LNm groups, while the product of split medullary FA and split RPV was superior in distinguishing LNm and LNms groups (AUC = 0.793) than other parameters. The combination of split medullary FA and split RPV showed best correlation with split rGFR (r = 0.534, p < 0.001). CONCLUSION: Split medullary FA, and its combination with split RPV, are valuable biomarkers for detecting early functional changes in renal alterations and predicting disease progression in patients with LN.

Quantitative Measurement on Contrast-Enhanced CT Distinguishes Small Clear Cell Renal Cell Carcinoma From Benign Renal Tumors: A Multicenter Study.

RATIONALE AND OBJECTIVES: To evaluate the potential of quantitative measurements on contrast-enhanced CT (CECT) in differentiating small (≤4 cm) clear cell renal cell carcinoma (ccRCC) from benign renal tumors, including fat-poor angiomyolipoma (fpAML) and renal oncocytoma (RO). MATERIALS AND METHODS: 244 patients with pathologically confirmed ccRCC (n = 184) and benign renal tumors (fpAML, n = 50; RO, n = 10) were randomly assigned into training cohort (n = 193) and test cohort 1 (n = 51), while external test cohort 2 (n = 50) was from another hospital. Quantitative parameters were obtained from CECT (unenhanced phase, UP; corticomedullary phase, CMP; nephrographic phase, NP; excretory phase, EP) by measuring attenuation of renal mass and cortex and subsequently calculated. Univariable and multivariable logistic regression analyses were performed to evaluate the association between these parameters and ccRCC. Finally, the constructed models were compared with radiologists' diagnoses. RESULTS: In univariable analysis, UP-related parameters, particularly UPC-T (cortex minus tumor attenuation on UP), demonstrated AUC of 0.766 in training cohort, 0.901 in test cohort 1, 0.805 in test cohort 2. The heterogeneity-related parameter SD (standard deviation) showed AUC of 0.781, 0.834, and 0.875 respectively. In multivariable analysis, model 1 incorporating UPC-T, NPC-T (cortex minus tumor attenuation on NP), CMPT-UPT (tumor attenuation on CMP minus UP), and SD yielded AUC of 0.866, 0.923, and 0.949 respectively. When compared with radiologists, multivariate models demonstrated higher accuracy (0.800-0.860) and sensitivity (0.794-0.971) than radiologists' assessments (accuracy: 0.700-0.720, sensitivity: 0.588-0.706). CONCLUSION: Quantitative measurements on CECT, particularly UP- and heterogeneity-related parameters, have potential to discriminate ccRCC and benign renal tumors (fpAML, RO).

Dual-Modality Imaging-Guided Manganese-Based Nanotransformer for Enhanced Gas-Photothermal Therapy Combined Immunotherapeutic Strategy Against Triple-Negative Breast Cancer.

Activating the stimulator of the interferon gene (STING) is a promising immunotherapeutic strategy for converting "cold" tumor microenvironment into "hot" one to achieve better immunotherapy for malignant tumors. Herein, a manganese-based nanotransformer is presented, consisting of manganese carbonyl and cyanine dye, for MRI/NIR-II dual-modality imaging-guided multifunctional carbon monoxide (CO) gas treatment and photothermal therapy, along with triggering cGAS-STING immune pathway against triple-negative breast cancer. This nanosystem is able to transfer its amorphous morphology into a crystallographic-like formation in response to the tumor microenvironment, achieved by breaking metal-carbon bonds and forming coordination bonds, which enhances the sensitivity of magnetic resonance imaging. Moreover, the generated CO and photothermal effect under irradiation of this nanotransformer induce immunogenic death of tumor cells and release damage-associated molecular patterns. Simultaneously, the Mn acts as an immunoactivator, potentially stimulating the cGAS-STING pathway to augment adaptive immunity, resulting in promoting the secretion of type I interferon, the proliferation of cytotoxic T lymphocytes and M2-macrophages repolarization. This nanosystem-based gas-photothermal treatment and immunoactivating therapy synergistic effect exhibit excellent antitumor efficacy both in vitro and in vivo, reducing the risk of triple-negative breast cancer recurrence and metastasis; thus, this strategy presents great potential as multifunctional immunotherapeutic agents for cancer treatment.

Evaluation of molecular receptors status in breast cancer using an mpMRI-based feature fusion radiomics model: mimicking radiologists' diagnosis.

Objective: To investigate the performance of a novel feature fusion radiomics (RFF) model that incorporates features from multiparametric MRIs (mpMRI) in distinguishing different statuses of molecular receptors in breast cancer (BC) preoperatively. Methods: 460 patients with 466 pathology-confirmed BCs who underwent breast mpMRI at 1.5T in our center were retrospectively included hormone receptor (HR) positive (HR+) (n=336) and HR negative (HR-) (n=130). The HR- patients were further categorized into human epidermal growth factor receptor 2 (HER-2) enriched BC (HEBC) (n=76) and triple negative BC (TNBC) (n=54). All lesions were divided into a training/validation cohort (n=337) and a test cohort (n=129). Volumes of interest (VOIs) delineation, followed by radiomics feature extraction, was performed on T2WI, DWI600 (b=600 s/mm2), DWI800 (b=800 s/mm2), ADC map, and DCE1-6 (six continuous DCE-MRI) images of each lesion. Simulating a radiologist's work pattern, 150 classification base models were constructed and analyzed to determine the top four optimum sequences for classifying HR+ vs. HR-, TNBC vs. HEBC, TNBC vs. non-TNBC in a random selected training cohort (n=337). Building upon these findings, the optimal single sequence models (Rss) and combined sequences models (RFF) were developed. The AUC, sensitivity, accuracy and specificity of each model for subtype differentiation were evaluated. The paired samples Wilcoxon signed rank test was used for performance comparison. Results: During the three classification tasks, the optimal single sequence for classifying HR+ vs. HR- was DWI600, while the ADC map, derived from DWI800 performed the best in distinguishing TNBC vs. HEBC, as well as identifying TNBC vs. non-TNBC, with corresponding training AUC values of 0.787, 0.788, and 0.809, respectively. Furthermore, the integration of the top four sequences in RFF models yielded improved performance, achieving AUC values of 0.809, 0.805 and 0.847, respectively. Consistent results was observed in both the training/validation and testing cohorts, with AUC values of 0.778, 0.787, 0.818 and 0.726, 0.773, 0.773, respectively (all p < 0.05 except HR+ vs. HR-). Conclusion: The RFF model, integrating mpMRI radiomics features, demonstrated promising ability to mimic radiologists' diagnosis for preoperative identification of molecular receptors of BC.

Myeloid cells interact with a subset of thyrocytes to promote their migration and follicle formation through NF-κB.

The pathogenesis of thyroid dysgenesis (TD) is not well understood. Here, using a combination of single-cell RNA and spatial transcriptome sequencing, we identify a subgroup of NF-κB-activated thyrocytes located at the center of thyroid tissues in postnatal mice, which maintained a partially mesenchymal phenotype. These cells actively protruded out of the thyroid primordium and generated new follicles in zebrafish embryos through continuous tracing. Suppressing NF-κB signaling affected thyrocyte migration and follicle formation, leading to a TD-like phenotype in both mice and zebrafish. Interestingly, during thyroid folliculogenesis, myeloid cells played a crucial role in promoting thyrocyte migration by maintaining close contact and secreting TNF-α. We found that cebpa mutant zebrafish, in which all myeloid cells were depleted, exhibited thyrocyte migration defects. Taken together, our results suggest that myeloid-derived TNF-α-induced NF-κB activation plays a critical role in promoting the migration of vertebrate thyrocytes for follicle generation.

Preoperative prediction model for macrotrabecular-massive hepatocellular carcinoma based on contrast-enhanced CT and clinical characteristics: a retrospective study.

Objective: To investigate the predictive value of contrast-enhanced computed tomography (CECT) imaging features and clinical factors in identifying the macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) preoperatively. Methods: This retrospective study included 101 consecutive patients with pathology-proven HCC (35 MTM subtype vs. 66 non-MTM subtype) who underwent liver surgery and preoperative CECT scans from January 2017 to November 2021. The imaging features were evaluated by two board-certified abdominal radiologists independently. The clinical characteristics and imaging findings were compared between the MTM and non-MTM subtypes. Univariate and multivariate logistic regression analyses were performed to investigate the association of clinical-radiological variables and MTM-HCCs and develop a predictive model. Subgroup analysis was also performed in BCLC 0-A stage patients. Receiver operating characteristic (ROC) curves analysis was used to determine the optimal cutoff values and the area under the curve (AUC) was employed to evaluate predictive performance. Results: Intratumor hypoenhancement (odds ratio [OR] = 2.724; 95% confidence interval [CI]: 1.033, 7.467; p = .045), tumors without enhancing capsules (OR = 3.274; 95% CI: 1.209, 9.755; p = .03), high serum alpha-fetoprotein (AFP) (≥ 228 ng/mL, OR = 4.101; 95% CI: 1.523, 11.722; p = .006) and high hemoglobin (≥ 130.5 g/L; OR = 3.943; 95% CI: 1.466, 11.710; p = .009) were independent predictors for MTM-HCCs. The clinical-radiologic (CR) model showed the best predictive performance, achieving an AUC of 0.793, sensitivity of 62.9% and specificity of 81.8%. The CR model also effectively identify MTM-HCCs in early-stage (BCLC 0-A stage) patients. Conclusion: Combining CECT imaging features and clinical characteristics is an effective method for preoperatively identifying MTM-HCCs, even in early-stage patients. The CR model has high predictive performance and could potentially help guide decision-making regarding aggressive therapies in MTM-HCC patients.

ROS-responsive self-activatable photosensitizing agent for photodynamic-immunotherapy of cancer.

Photodynamic therapy (PDT), as a non-invasive and spatiotemporally controllable modality, exhibits great potential in cancer treatment. However, the efficiency of reactive oxygen species (ROS) production was restricted to the hydrophobic characteristics and aggregation-caused quenching (ACQ) of photosensitizers. Herein, we designed a ROS self-activatable nano system (denoted as PTKPa) based on poly(thioketal) conjugated with photosensitizers (PSs) pheophorbide A (Ppa) on the polymer side chains for suppressing ACQ and enhancing PDT. The process of self-activation is that ROS, which is derived from laser irradiated PTKPa, as an activating agent accelerates poly(thioketal) cleavage with the release of Ppa from PTKPa. This in turn generates abundant ROS, accelerates degradation of the remaining PTKPa and amplifies the efficacy of PDT with more tremendous ROS generated. Moreover, these abundant ROS can amplify PDT-induced oxidative stress, cause irreversible damage to tumor cells and achieve immunogenic cell death (ICD), thereby boosting the efficacy of photodynamic-immunotherapy. These findings provide new insights into ROS self-activatable strategy for enhancing cancer photodynamic- immunotherapy. STATEMENT OF SIGNIFICANCE: This work described an approach to utilize ROS-responsive self-activatable poly(thioketal) conjugated with pheophorbide A (Ppa) for suppressing aggregation-caused quenching (ACQ) and enhancing photodynamic-immunotherapy. The ROS, generated from the conjugated Ppa upon 660nm laser irradiation, as a triggering agent which initiates the release of Ppa with poly(thioketal) degradation. That in turn generates abundant ROS and facilitates degradation of the remaining PTKPa, resulting in oxidative stress to tumor cells and achieving immunogenic cell death (ICD). This work provides a promising solution to improve tumor photodynamic therapeutic effects.

A manganese-phenolic network platform amplifying STING activation to potentiate MRI guided cancer chemo-/chemodynamic/immune therapy.

Low immune infiltration severely hinders the efficacy of cancer immunotherapy. Here, we developed a manganese-phenolic network platform (TMPD) to boost antitumor immunity via a stimulator of interferon gene (STING)-amplified activation cascade. TMPD is based on doxorubicin (DOX)-loaded PEG-PLGA nanoparticles and further coated with manganese (Mn2+)-tannic acid (TA) networks. Mechanistically, DOX-based chemotherapy and Mn2+-mediated chemodynamic therapy effectively promoted immunogenic cell death (ICD), characterized by abundant damage-associated molecular pattern (DAMP) exposure, which subsequently enhanced dendritic cells' (DCs) presentation of antigens. DOX-elicited DNA damage simultaneously caused cytoplasmic leakage of intracellular double-stranded DNA (dsDNA) as the STING signal initiator, while Mn2+ mediated significant upregulation in the expression of a STING pathway-related protein thereby amplifying the STING signal. Systemic intravenous administration of TMPD remarkably promoted DC maturation and CD8+ T cell infiltration, thus eliciting strong antitumor effects. Meanwhile, the released Mn2+ could serve as a contrast agent for tumor-specific T1-weighted magnetic resonance imaging (MRI). Moreover, TMPD combined with immune checkpoint blockade (ICB) immunotherapy significantly inhibited tumor growth and lung metastasis. Collectively, these findings indicate that TMPD has great potential in activating robust innate and adaptive immunity for MRI guided cancer chemo-/chemodynamic/immune therapy.

The isl2a transcription factor regulates pituitary development in zebrafish.

Background: ISL LIM homeobox 2, also known as insulin gene enhancer protein ISL-2 (ISL2), is a transcription factor gene that participates in a wide range of developmental events. However, the role of ISL2 in the hypothalamus-pituitary-thyroid axis is largely unknown. In the present study, we characterized the expression patterns of ISL2 and revealed its regulative role during embryogenesis using zebrafish. Methods: We used the CRISPR/Cas9 system to successfully establish homozygous ISL2-orthologue (isl2a and isl2b) knockout zebrafish. Moreover, we utilized these knockout zebrafish to analyze the pituitary and thyroid phenotypes in vivo. For further molecular characterization, in situ hybridization and immunofluorescence were performed. Results: The isl2a mutant zebrafish presented with thyroid hypoplasia, reduced whole-body levels of thyroid hormones, increased early mortality, gender imbalance, and morphological retardation during maturity. Additionally, thyrotropes, a pituitary cell type, was notably decreased during development. Importantly, the transcriptional levels of pituitary-thyroid axis hormones-encoding genes, such as tshba, cga, and tg, were significantly decreased in isl2a mutants. Finally, the thyroid dysplasia in isl2a mutant larvae may be attributed to a reduction in proliferation rather than changes in apoptosis. Conclusions: In summary, isl2a regulates the transcriptional levels of marker genes in hypothalamus-pituitary-thyroid axis, and isl2a knockout causing low thyroid hormone levels in zebrafish. Thus, isl2a identified by the present study, is a novel regulator for pituitary cell differentiation in zebrafish, resulting in thyroid gland hypoplasia and phenotypes of hypothyroidism.

Optimizing CT and MRI criteria for differentiating intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma.

BACKGROUND: Accurate diagnosis of intrahepatic mass-forming cholangiocarcinoma (IMCC) is crucial with regard to the choice of patient management and treatment options. PURPOSE: To evaluate the feasibility and diagnostic performance of the LI-RADS M (LR-M) targetoid criteria on computed tomography (CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in differentiating IMCC from hepatocellular carcinoma (HCC). MATERIAL AND METHODS: A total of 118 patients with IMCC and HCC were included who underwent CT and EOB-MRI examinations. Multivariate analysis was used to determine the strongest predictors differentiating IMCC from HCC. Using these predictors, a predictive model for differentiating IMCC from HCC was constructed and the performance of the model was confirmed using the receiver operating characteristic curve. RESULTS: Multivariate analyses revealed rim-like arterial phase hyperenhancement (rim APHE) on CT and rim APHE, delayed central enhancement (DCE), and targetoid hepatobiliary phase (HBP) on MRI as independent variables significantly differentiating IMCC from HCC. The multivariate logistic regression model incorporating the three variables on EOB-MRI was constructed with an area under the curve (AUC) of 0.946, sensitivity of 87.80%, specificity of 92.21%, and accuracy of 94.60%. Per the DeLong test, the multivariate logistic regression model showed significantly higher AUC than rim APHE on CT (0.946 vs. 0.871; P = 0.008) and MRI (0.946 vs. 0.876; P = 0.003), whereas rim APHE on CT and MRI did not differ significantly (P = 0.809). CONCLUSION: The multivariate logistic regression model based on rim APHE, DCE, and targetoid HBP on EOB-MRI can effectively distinguish IMCC from HCC and is superior to any other targetoid appearance criterion of LI-RADS on CT and EOB-MRI.

Radiomics can differentiate high-grade glioma from brain metastasis: a systematic review and meta-analysis.

OBJECTIVE: (1) To evaluate the diagnostic performance of radiomics in differentiating high-grade glioma from brain metastasis and how to improve the model. (2) To assess the methodological quality of radiomics studies and explore ways of embracing the clinical application of radiomics. METHODS: Studies using radiomics to differentiate high-grade glioma from brain metastasis published by 26 July 2021 were systematically reviewed. Methodological quality and risk of bias were assessed using the Radiomics Quality Score (RQS) system and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, respectively. Pooled sensitivity and specificity of the radiomics model were also calculated. RESULTS: Seventeen studies combining 1,717 patients were included in the systematic review, of which 10 studies without data leakage suspicion were employed for the quantitative statistical analysis. The average RQS was 5.13 (14.25% of total), with substantial or almost perfect inter-rater agreements. The inclusion of clinical features in the radiomics model was only reported in one study, as was the case for publicly available algorithm code. The pooled sensitivity and specificity were 84% (95% CI, 80-88%) and 84% (95% CI, 81-87%), respectively. The performances of feature extraction from the volume of interest (VOI) or (semi) automatic segmentation in the radiomics models were superior to those of protocols employing region of interest (ROI) or manual segmentation. CONCLUSION: Radiomics can accurately differentiate high-grade glioma from brain metastasis. The adoption of standardized workflow to avoid potential data leakage as well as the integration of clinical features and radiomics are advised to consider in future studies. KEY POINTS: • The pooled sensitivity and specificity of radiomics for differentiating high-grade gliomas from brain metastasis were 84% and 84%, respectively. • Avoiding potential data leakage by adopting an intensive and standardized workflow is essential to improve the quality and generalizability of the radiomics model. • The application of radiomics in combination with clinical features in differentiating high-grade gliomas from brain metastasis needs further validation.