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.

Repression of YEATS2 induces cellular senescence in hepatocellular carcinoma and inhibits tumor growth.

Hepatocellular carcinoma (HCC) stands as the third leading cause of cancer-related fatalities globally. In this study, we observed a significant increase in the expression level of the YEATS2 gene in HCC patients, and it is negatively correlated with the patients' survival rate. While we have previously identified the association between YEATS2 and the survival of pancreatic cancer cells, the regulatory mechanisms and significance in HCC are still to be fully elucidated. Our study shows that knockdown (KD) of YEATS2 expression leads to DNA damage, which in turn results in an upregulation of γ-H2A.X expression and activation of the canonical senescence-related pathway p53/p21Cip1. Moreover, our transcriptomic analysis reveals that YEATS2 KD cells can enhance the expression of p21Cip1 via the c-Myc/miR-93-5p pathway, consequently fostering the senescence of HCC cells. The initiation of cellular senescence through dual-channel activation suggests that YEATS2 plays a pivotal regulatory role in the process of cell proliferation. Ultimately, our in vivo research utilizing a nude mouse tumor model revealed a notable decrease in both tumor volume and weight after the suppression of YEATS2 expression. This phenomenon is likely attributable to the attenuation of proliferative cell activity, coupled with a concurrent augmentation in the population of natural killer (NK) cells. In summary, our research results have supplemented the understanding of the regulatory mechanisms of HCC cell proliferation and indicated that targeting YEATS2 may potentially inhibit liver tumor growth.

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.

MicroRNA-377-3p exacerbates chronic obstructive pulmonary disease through suppressing ZFP36L1 expression and inducing lung fibroblast senescence.

Chronic obstructive pulmonary disease (COPD) is a leading aging related cause of global mortality. Small airway narrowing is recognized as an early and significant factor for COPD development. Senescent fibroblasts were observed to accumulate in lung of COPD patients and promote COPD progression through aberrant extracellular matrix (ECM) deposition and senescence-associated secretory phenotype (SASP). On the basis of our previous study, we further investigated the the causes for the increased levels of miR-377-3p in the blood of COPD patients, as well as its regulatory function in the pathological progression of COPD. We found that the majority of up-regulated miR-377-3p was localized in lung fibroblasts. Inhibition of miR-377-3p improved chronic smoking-induced COPD in mice. Mechanistically, miR-377-3p promoted senescence of lung fibroblasts, while knockdown of miR-377-3p attenuated bleomycin-induced senescence in lung fibroblasts. We also identified ZFP36L1 as a direct target for miR-377-3p that likely mediated its pro senescence activity in lung fibroblasts. Our data reveal that miR-377-3p is crucial for COPD pathogenesis, and may serve as a potential target for COPD therapy.

Simple, sensitive, colorimetric detection of pyrophosphate via the analyte-triggered decomposition of metal-organic frameworks regulating their adaptive multi-color Tyndall effect.

This paper describes initially the application of the Tyndall effect (TE) of metal-organic framework (MOF) materials as a colorimetric signaling strategy for the sensitive detection of pyrophosphate ion (PPi). The used MOF NH2-MIL-101(Fe) was prepared with Fe3+ ions and fluorescent ligands of 2-amino terephthalic acid (NH2-BDC). The fluorescence of NH2-BDC in MOF is quenched due to the ligand-to-metal charge transfer effect, while the NH2-MIL-101(Fe) suspension shows a strong TE. In the presence of PPi analyte, the MOFs will undergo decomposition because of the competitive binding of Fe3+ by PPi over NH2-BDC, resulting in a significant decrease in the TE signal and fluorescence restoration from the released ligands. The results demonstrate that the new method only requires a laser pointer pen (for TE creation) and a smartphone (for portable quantitative readout) to detect PPi in a linear concentration range of 1.25-800 µM, with a detection limit of ~210 nM (3σ) which is ~38 times lower than that obtained from traditional fluorescence with a spectrophotometer (linear concentration range, 50-800 µM; detection limit, 8.15 µM). Moreover, the acceptable recovery of PPi in several real samples (i.e., pond water, black tea, and human serum and urine) ranges from 97.66 to 119.15%.

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.

HRadNet: A Hierarchical Radiomics-Based Network for Multicenter Breast Cancer Molecular Subtypes Prediction.

Breast cancer is a heterogeneous disease, where molecular subtypes of breast cancer are closely related to the treatment and prognosis. Therefore, the goal of this work is to differentiate between luminal and non-luminal subtypes of breast cancer. The hierarchical radiomics network (HRadNet) is proposed for breast cancer molecular subtypes prediction based on dynamic contrast-enhanced magnetic resonance imaging. HRadNet fuses multilayer features with the metadata of images to take advantage of conventional radiomics methods and general convolutional neural networks. A two-stage training mechanism is adopted to improve the generalization capability of the network for multicenter breast cancer data. The ablation study shows the effectiveness of each component of HRadNet. Furthermore, the influence of features from different layers and metadata fusion are also analyzed. It reveals that selecting certain layers of features for a specified domain can make further performance improvements. Experimental results on three data sets from different devices demonstrate the effectiveness of the proposed network. HRadNet also has good performance when transferring to other domains without fine-tuning.

Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer.

OBJECTIVE: This study aimed to establish a MRI-based deep learning radiomics (DLR) signature to predict the human epidermal growth factor receptor 2 (HER2)-low-positive status and further verified the difference in prognosis by the DLR model. METHODS: A total of 481 patients with breast cancer who underwent preoperative MRI were retrospectively recruited from two institutions. Traditional radiomics features and deep semantic segmentation feature-based radiomics (DSFR) features were extracted from segmented tumors to construct models separately. Then, the DLR model was constructed to assess the HER2 status by averaging the output probabilities of the two models. Finally, a Kaplan‒Meier survival analysis was conducted to explore the disease-free survival (DFS) in patients with HER2-low-positive status. The multivariate Cox proportional hazard model was constructed to further determine the factors associated with DFS. RESULTS: First, the DLR model distinguished between HER2-negative and HER2-overexpressing patients with AUCs of 0.868 and 0.763 in the training and validation cohorts, respectively. Furthermore, the DLR model distinguished between HER2-low-positive and HER2-zero patients with AUCs of 0.855 and 0.750, respectively. Cox regression analysis showed that the prediction score obtained using the DLR model (HR, 0.175; p = 0.024) and lesion size (HR, 1.043; p = 0.009) were significant, independent predictors of DFS. CONCLUSIONS: We successfully constructed a DLR model based on MRI to noninvasively evaluate the HER2 status and further revealed prospects for predicting the DFS of patients with HER2-low-positive status. CLINICAL RELEVANCE STATEMENT: The MRI-based DLR model could noninvasively identify HER2-low-positive status, which is considered a novel prognostic predictor and therapeutic target. KEY POINTS: • The DLR model effectively distinguished the HER2 status of breast cancer patients, especially the HER2-low-positive status. • The DLR model was better than the traditional radiomics model or DSFR model in distinguishing HER2 expression. • The prediction score obtained using the model and lesion size were significant independent predictors of DFS.

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.

TAF1B depletion leads to apoptotic cell death by inducing nucleolar stress and activating p53-miR-101 circuit in hepatocellular carcinoma.

Background: TAF1B (TATA Box Binding Protein (TBP)-Associated Factor) is an RNA polymerase regulating rDNA activity, stress response, and cell cycle. However, the function of TAF1B in the progression of hepatocellular carcinoma (HCC) is unknown. Objective: In this study, we intended to characterize the crucial role and molecular mechanisms of TAF1B in modulating nucleolar stress in HCC. Methods: We analyzed the differential expression and prognostic value of TAF1B in hepatocellular carcinoma based on The Cancer Genome Atlas (TCGA) database, tumor and paraneoplastic tissue samples from clinical hepatocellular carcinoma patients, and typical hepatocellular carcinoma. We detected cell proliferation and apoptosis by lentiviral knockdown of TAF1B expression levels in HepG2 and SMMC-7721 cells using clone formation, apoptosis, and Western blotting (WB) detection of apoptosis marker proteins. Simultaneously, we investigated the influence of TAF1B knockdown on the function of the pre-initiation complex (PIC) by WB, and co-immunoprecipitation (Co-IP) and chromatin immunoprecipitation (ChIP) assays verified the interaction between the complexes and the effect on rDNA activity. Immunofluorescence assays measured the expression of marker proteins of nucleolus stress, fluorescence in situ hybridization (FISH) assays checked the rDNA activity, and qRT-PCR assays tested the pre-rRNA levels. Regarding molecular mechanisms, we investigated the role of p53 and miR-101 in modulating nucleolar stress and apoptosis. Finally, the impact of TAF1B knockdown on tumor growth, apoptosis, and p53 expression was observed in xenograft tumors. Result: We identified that TAF1B was highly expressed in hepatocellular carcinoma and associated with poor prognosis in HCC patients. TAF1B depletion modulated nucleolar stress and apoptosis in hepatocellular carcinoma cells through positive and negative feedback from p53-miR-101. RNA polymerase I transcription repression triggered post-transcriptional activation of miR-101 in a p53-dependent manner. In turn, miR-101 negatively feeds back through direct inhibition of the p53-mediated PARP pathway. Conclusion: These findings broaden our comprehension of the function of TAF1B-mediated nucleolar stress in hepatocellular carcinoma and may offer new biomarkers for exploring prospective therapeutic targets in HCC.

Diffusion basis spectrum imaging detects pathological alterations in substantia nigra and white matter tracts with early-stage Parkinson's disease.

OBJECTIVES: Using diffusion basis spectrum imaging (DBSI) to examine the microstructural changes in the substantia nigra (SN) and global white matter (WM) tracts of patients with early-stage PD. METHODS: Thirty-seven age- and sex-matched patients with early-stage PD and 22 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessments and diffusion-weighted MRI scans, analyzed by diffusion tensor imaging (DTI) and DBSI to assess the pathologies of PD in SN and global WM tracts. RESULTS: The lower DTI fraction anisotropy (FA) was seen in SN of PD patients (PD: 0.316 ± 0.034 vs HCs: 0.331 ± 0.019, p = 0.015). The putative cells marker-DBSI-restricted fraction (PD: 0.132 ± 0.051 vs HCs: 0.105 ± 0.039, p = 0.031) and the edema/extracellular space marker-DBSI non-restricted-fraction (PD: 0.150 ± 0.052 vs HCs: 0.122 ± 0.052, p = 0.020) were both significantly higher and the density of axons/dendrites marker-DBSI fiber-fraction (PD: 0.718 ± 0.073 vs HCs: 0.773 ± 0.071, p = 0.003) was significantly lower in SN of PD patients. DBSI-restricted fraction in SN was negatively correlated with HAMA scores (r = - 0.501, p = 0.005), whereas DTI-FA was not correlated with any clinical scales. In WM tracts, only higher DTI axial diffusivity (AD) among DTI metrics was found in multiple WM regions in PD, while lower DBSI fiber-fraction and higher DBSI non-restricted-fraction were detected in multiple WM regions. DBSI non-restricted-fraction in both left fornix (cres)/stria terminalis (r = -0.472, p = 0.004) and right posterior thalamic radiation (r = - 0.467, p = 0.005) was negatively correlated with MMSE scores. CONCLUSION: DBSI could potentially detect and quantify the extent of inflammatory cell infiltration, fiber/dendrite loss, and edema in both SN and WM tracts in patients with early-stage PD, a finding remains to be further investigated through more extensive longitudinal DBSI analysis. CLINICAL RELEVANCE STATEMENT: Our study shows that DBSI indexes can potentially detect early-stage PD's pathological changes, with a notable ability to distinguish between inflammation and edema. This implies that DBSI has the potential to be an imaging biomarker for early PD diagnosis. KEY POINTS: • Diffusion basis spectrum imaging detected higher restricted-fraction in Parkinson's disease, potentially reflecting inflammatory cell infiltration. • Diffusion basis spectrum imaging detected higher non-restricted-fraction and lower fiber-fraction in Parkinson's disease, indicating the presence of edema and/or dopaminergic neuronal/dendritic loss. • Diffusion basis spectrum imaging metrics correlated with non-motor symptoms, suggesting its potential diagnostic role to detect early-stage PD dysfunctions.

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.

Ferrocene-Based Polymeric Nanoparticles Carrying Doxorubicin for Oncotherapeutic Combination of Chemotherapy and Ferroptosis.

Mono-chemotherapy has significant side effects and unsatisfactory efficacy, limiting its clinical application. Therefore, a combination of multiple treatments is becoming more common in oncotherapy. Chemotherapy combined with the induction of ferroptosis is a potential new oncotherapy. Furthermore, polymeric nanoparticles (NPs) can improve the antitumor efficacy and decrease the toxicity of drugs. Herein, a polymeric NP, mPEG-b-PPLGFc@Dox, is synthesized to decrease the toxicity of doxorubicin (Dox) and enhance the efficacy of chemotherapy by combining it with the induction of ferroptosis. First, mPEG-b-PPLGFc@Dox is oxidized by endogenous H2 O2 and releases Dox, which leads to an increase of H2 O2 by breaking the redox balance. The Fe(II) group of ferrocene converts H2 O2 into ·OH, inducing subsequent ferroptosis. Furthermore, glutathione peroxidase 4, a biomarker of ferroptosis, is suppressed and the lipid peroxidation level is elevated in cells incubated with mPEG-b-PPLGFc@Dox compared to those treated with Dox alone, indicating ferroptosis induction by mPEG-b-PPLGFc@Dox. In vivo, the antitumor efficacy of mPEG-b-PPLGFc@Dox is higher than that of free Dox. Moreover, the loss of body weight in mice treated mPEG-b-PPLGFc@Dox is lower than in those treated with free Dox, indicating that mPEG-b-PPLGFc@Dox is less toxic than free Dox. In conclusion, mPEG-b-PPLGFc@Dox not only has higher antitumor efficacy but it reduces the damage to normal tissue.

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.

MTHFR C677T polymorphism and cerebrovascular lesions in elderly patients with CSVD: A correlation analysis.

Plasma homocysteine (Hcy) has been identified as a potential risk factor for cerebral small vessel disease. Cerebral small vessel disease (CSVD) leads to cognitive impairment, depression, and other symptoms and is a common disease in middle-aged and elderly people. To investigate the relationship between 5,10-methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism and CSVD in elderly patients, plasma levels of homocysteine (Hcy) and MTHFR genotyping were assessed. MRI and MRA were performed at the same time to analyze the relationship between different genotypes and cerebrovascular lesions. We showed that Hcy plasma levels in the TT group were significantly higher than those in the CC and CT groups. Moreover, we observed that the severity of white matter lesions was associated with women and positively correlated with age, previous coronary heart disease, luminal infarction, and MTHFR polymorphism. The multivariate logistic regression analysis showed that age, TT genotype, and lacunar infarction were independent risk factors for white matter hyperintensity (WMH). Importantly, we showed that there was a significant correlation between Hcy plasma levels and MTHFR gene polymorphism, with the TT genotype constituting an independent risk factor for WMH. Therefore, we recommended early detection of MTHFR gene polymorphisms with concomitant early intervention concerning risk factors to delay the occurrence of cognitive impairment in CSVD elderly patients.

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.