Computed tomography perfusion deficit volume predicts the functional outcome of endovascular therapy for basilar artery occlusion

OBJECTIVES

To investigate the relationship between baseline computed tomography perfusion deficit volumes and functional outcomes in patients with basilar artery occlusion (BAO) undergoing endovascular therapy.

METHODS

This was a single-center study in which the data of 64 patients with BAO who underwent endovascular therapy were retrospectively analyzed. All the patients underwent multi-model computed tomography on admission. The posterior-circulation Acute Stroke Prognosis Early Computed Tomography Score was applied to assess the ischemic changes. Perfusion deficit volumes were obtained using Syngo.via software. The primary outcome of the analysis was a good functional outcome (90-day modified Rankin Scale score ≤ 3). Logistic regression and receiver operating characteristic curves were used to explore predictors of functional outcome.

RESULTS

A total of 64 patients (median age, 68 years; 72 % male) were recruited, of whom 26 (41 %) patients achieved good functional outcomes, while 38 (59 %) had poor functional outcomes. Tmax > 10 s, Tmax > 6 s, and rCBF < 30 % volume were independent predictors of good functional outcomes (odds ratio range, 1.0-1.2; 95 % confidence interval [CI], 1.0-1.4]) and performed well in the receiver operating characteristic curve analyses, exhibiting positive prognostic value; the areas under the curve values were 0.85 (95 % CI, 0.75-0.94), 0.81 (95 % CI, 0.70-0.90), and 0.78 (95 % CI, 0.67-0.89).

CONCLUSION

Computed tomography perfusion deficit volume represents a valuable tool in predicting high risk of disability and mortality in patients with BAO after endovascular treatment.

Prediction of the Ki-67 expression level in head and neck squamous cell carcinoma with machine learning-based multiparametric MRI radiomics: a multicenter study

BACKGROUND

This study aimed to develop and validate a machine learning (ML)-based fusion model to preoperatively predict Ki-67 expression levels in patients with head and neck squamous cell carcinoma (HNSCC) using multiparametric magnetic resonance imaging (MRI).

METHODS

A total of 351 patients with pathologically proven HNSCC from two medical centers were retrospectively enrolled in the study and divided into training (n = 196), internal validation (n = 84), and external validation (n = 71) cohorts. Radiomics features were extracted from T2-weighted images and contrast-enhanced T1-weighted images and screened. Seven ML classifiers, including k-nearest neighbors (KNN), support vector machine (SVM), logistic regression (LR), random forest (RF), linear discriminant analysis (LDA), naive Bayes (NB), and eXtreme Gradient Boosting (XGBoost) were trained. The best classifier was used to calculate radiomics (Rad)-scores and combine clinical factors to construct a fusion model. Performance was evaluated based on calibration, discrimination, reclassification, and clinical utility.

RESULTS

Thirteen features combining multiparametric MRI were finally selected. The SVM classifier showed the best performance, with the highest average area under the curve (AUC) of 0.851 in the validation cohorts. The fusion model incorporating SVM-based Rad-scores with clinical T stage and MR-reported lymph node status achieved encouraging predictive performance in the training (AUC = 0.916), internal validation (AUC = 0.903), and external validation (AUC = 0.885) cohorts. Furthermore, the fusion model showed better clinical benefit and higher classification accuracy than the clinical model.

CONCLUSIONS

The ML-based fusion model based on multiparametric MRI exhibited promise for predicting Ki-67 expression levels in HNSCC patients, which might be helpful for prognosis evaluation and clinical decision-making.

Acidic/hypoxia dual-alleviated nanoregulators for enhanced treatment of tumor chemo-immunotherapy

Chemotherapy plays a crucial role in triple-negative breast cancer (TNBC) treatment as it not only directly kills cancer cells but also induces immunogenic cell death. However, the chemotherapeutic efficacy was strongly restricted by the acidic and hypoxic tumor environment. Herein, we have successfully formulated PLGA-based nanoparticles concurrently loaded with doxorubicin (DOX), hemoglobin (Hb) and CaCO3 by a CaCO3-assisted emulsion method, aiming at the effective treatment of TNBC. We found that the obtained nanomedicine (DHCaNPs) exhibited effective drug encapsulation and pH-responsive drug release behavior. Moreover, DHCaNPs demonstrated robust capabilities in neutralizing protons and oxygen transport. Consequently, DHCaNPs could not only serve as oxygen nanoshuttles to attenuate tumor hypoxia but also neutralize the acidic tumor microenvironment (TME) by depleting lactic acid, thereby effectively overcoming the resistance to chemotherapy. Furthermore, DHCaNPs demonstrated a notable ability to enhance antitumor immune responses by increasing the frequency of tumor-infiltrating effector lymphocytes and reducing the frequency of various immune-suppressive cells, therefore exhibiting a superior efficacy in suppressing tumor growth and metastasis when combined with anti-PD-L1 (αPD-L1) immunotherapy. In summary, this study highlights that DHCaNPs could effectively attenuate the acidic and hypoxic TME, offering a promising strategy to figure out an enhanced chemo-immunotherapy to benefit TNBC patients.

Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study

RATIONALE AND OBJECTIVES

This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images to evaluate non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer (BC) patients who underwent total mastectomy (TM) and had 1-2 positive sentinel lymph nodes (SLNs).

MATERIALS AND METHODS

In total, 494 patients were retrospectively enrolled from two hospitals, and were divided into the training (n = 286), internal validation (n = 122), and external validation (n = 86) cohorts. Features were extracted from DCE-MRI images for each patient and screened. Six ML classifies were trained and the best classifier was evaluated to calculate radiomics (Rad)-scores. A combined model was developed based on Rad-scores and clinical risk factors, then the calibration, discrimination, reclassification, and clinical usefulness were evaluated.

RESULTS

14 radiomics features were ultimately selected. The random forest (RF) classifier showed the best performance, with the highest average area under the curve (AUC) of 0.833 in the validation cohorts. The combined model incorporating RF-based Rad-scores, tumor size, lymphovascular invasion, and proportion of positive SLNs resulted in the best discrimination ability, with AUCs of 0.903, 0.890, and 0.836 in the training, internal validation, and external validation cohorts, respectively. Furthermore, the combined model significantly improved the classification accuracy and clinical benefit for NSLN metastasis prediction.

CONCLUSION

A RF-based combined model using DCE-MRI images exhibited a promising performance for predicting NSLN metastasis in Chinese BC patients who underwent TM and had 1-2 positive SLNs, thereby aiding in individualized clinical treatment decisions.

Bronchial arterial chemoembolization with Drug-Eluting beads plus sequential chemotherapy for the treatment of stage III and IV lung squamous cell carcinoma

PURPOSE

This retrospective study aimed to investigate the effectiveness and safety of bronchial arterial chemoembolization with drug-eluting beads (DEB-BACE) plus chemotherapy versus chemotherapy alone in patients with stage III and IV lung squamous cell carcinoma (LSCC) who are not appropriate candidates for radiochemotherapy.

MATERIALS AND METHODS

In this retrospective analysis, we screened all adult patients undergoing either DEB-BACE plus chemotherapy or chemotherapy alone for stage III or IV LCSS at authors' center from January 2018 to August 2021. Each 21-day chemotherapy cycle consisted of intravenous injection of gemcitabine (1.0 g/m2) on days 1 and 8 and cisplatin 75 (mg/m2) on day 1. The planned cycles were 4. DEB-BACE consisted of microcatheter infusion of CalliSpheres beads carrying cisplatin (75 mg/m2) and gemcitabine (1.0 g/m2), at 3 weeks prior to chemotherapy. The primary outcome was overall survival (OS). The secondary outcomes included progression-free survival (PFS), pulmonary response, and adverse events (AEs).

RESULTS

The final analysis included 95 patients in the chemotherapy group and 41 patients in the combination treatment group. The median OS was 14 months (95 % CI 11.0-17.0) in the chemotherapy group and 19 months (95 % CI 18.0-24.0) in the combination group (P = 0.015). In multivariate Cox regression analysis, DEB-BACE plus chemotherapy was associated with lower risk of death versus chemotherapy only (HR 0.16, 95 % CI 0.05-0.52; log rank test P = 0.003). The median PFS was 6 months (95 % CI 4.0-7.0) in the chemotherapy group and 8 months (95 % CI 6.0-8.0) in the combination group (P = 0.015). The pulmonary objective response rate (ORR) and disease control rate (DCR) were 48.4 % and 62.1 % in chemotherapy group versus 82.9 % and 90.2 % in combination group (P < 0.001 and = 0.001, respectively). AEs occurred in 133 patients (97.8 %). The rate of bone marrow suppression was 48.4 % (46/95) in the chemotherapy group versus 7.3 % (3/41) in the combination group (P < 0.001).

CONCLUSION

Compared with chemotherapy alone, DEB-BACE plus chemotherapy was associated with longer survival outcomes and lower rate of bone marrow suppression.

Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics

OBJECTIVES

Accurate axillary evaluation plays an important role in prognosis and treatment planning for breast cancer. This study aimed to develop and validate a dynamic contrast-enhanced (DCE)-MRI-based radiomics model for preoperative evaluation of axillary lymph node (ALN) status in early-stage breast cancer.

METHODS

A total of 410 patients with pathologically confirmed early-stage invasive breast cancer (training cohort, N = 286; validation cohort, N = 124) from June 2018 to August 2022 were retrospectively recruited. Radiomics features were derived from the second phase of DCE-MRI images for each patient. ALN status-related features were obtained, and a radiomics signature was constructed using SelectKBest and least absolute shrinkage and selection operator regression. Logistic regression was applied to build a combined model and corresponding nomogram incorporating the radiomics score (Rad-score) with clinical predictors. The predictive performance of the nomogram was evaluated using receiver operator characteristic (ROC) curve analysis and calibration curves.

RESULTS

Fourteen radiomic features were selected to construct the radiomics signature. The Rad-score, MRI-reported ALN status, BI-RADS category, and tumour size were independent predictors of ALN status and were incorporated into the combined model. The nomogram showed good calibration and favourable performance for discriminating metastatic ALNs (N + (≥1)) from non-metastatic ALNs (N0) and metastatic ALNs with heavy burden (N + (≥3)) from low burden (N + (1-2)), with the area under the ROC curve values of 0.877 and 0.879 in the training cohort and 0.859 and 0.881 in the validation cohort, respectively.

CONCLUSIONS

The DCE-MRI-based radiomics nomogram could serve as a potential non-invasive technique for accurate preoperative evaluation of ALN burden, thereby assisting physicians in the personalized axillary treatment for early-stage breast cancer patients.

ADVANCES IN KNOWLEDGE

This study developed a potential surrogate of preoperative accurate evaluation of ALN status, which is non-invasive and easy-to-use.

[Association between congenital hypothyroidism and in-hospital adverse outcomes in very low birth weight infants]

Objective: To investigate the association between congenital hypothyroidism (CH) and the adverse outcomes during hospitalization in very low birth weight infants (VLBWI). Methods: This prospective, multicenter observational cohort study was conducted based on the data from the Sino-northern Neonatal Network (SNN). Data of 5 818 VLBWI with birth weight <1 500 g and gestational age between 24-<37 weeks that were admitted to the 37 neonatal intensive care units from January 1st, 2019 to December 31st, 2022 were collected and analyzed. Thyroid function was first screened at 7 to 10 days after birth, followed by weekly tests within the first 4 weeks, and retested at 36 weeks of corrected gestational age or before discharge. The VLBWI were assigned to the CH group or non-CH group. Chi-square test, Fisher exact probability method, Wilcoxon rank sum test, univariate and multivariate Logistic regression were used to analyze the relationship between CH and poor prognosis during hospitalization in VLBWI. Results: A total of 5 818 eligible VLBWI were enrolled, with 2 982 (51.3%) males and the gestational age of 30 (29, 31) weeks. The incidence of CH was 5.5% (319 VLBWI). Among the CH group, only 121 VLBWI (37.9%) were diagnosed at the first screening. Univariate Logistic regression analysis showed that CH was associated with increased incidence of extrauterine growth retardation (EUGR) (OR=1.31(1.04-1.64), P<0.05) and retinopathy of prematurity (ROP) of stage Ⅲ and above (OR=1.74(1.11-2.75), P<0.05). However, multivariate Logistic regression analysis showed no significant correlation between CH and EUGR, moderate to severe bronchopulmonary dysplasia, grade Ⅲ to Ⅳ intraventricular hemorrhage, neonatal necrotizing enterocolitis in stage Ⅱ or above, and ROP in stage Ⅲ or above (OR=1.04 (0.81-1.33), 0.79 (0.54-1.15), 1.15 (0.58-2.26), 1.43 (0.81-2.53), 1.12 (0.70-1.80), all P>0.05). Conclusion: There is no significant correlation between CH and in-hospital adverse outcomes, possibly due to timely diagnosis and active replacement therapy.

Manganese molybdate nanodots with dual amplification of STING activation for "cycle" treatment of metalloimmunotherapy

Certain types of cationic metal ions, such as Mn2+ are able to activate immune functions via the stimulator of interferon genes (STING) pathway, showing potential applications in eliciting antitumor immunity. How anionic ions interact with immune cells remains largely unknown. Herein, selecting from a range of cationic and anionic ions, we were excited to discover that MoO42- could act as a cGAS-STING agonist and further confirmed the capability of Mn2+ to activate the cGAS-STING pathway. Inspired by such findings, we synthesized manganese molybdate nanoparticles with polyethylene glycol modification (MMP NDs) for cancer metalloimmunotherapy. Meanwhile, MMP NDs could consume glutathione (GSH) over-expressed in tumors and induce ferroptosis owing to high-valence Mo and Mn to elicit tumor-specific immune responses, which was further amplified by MMP-triggered the cGAS-STING activation. In turn, activated CD8+ T cells to secrete high levels of interferon γ (IFN-γ) and reduced GPX4 expression in tumor cells to trigger ferroptosis-specific lipid peroxidation, which constituted a "cycle" of therapy. As a result, the metalloimmunotherapy with systemic administration of MMP NDs offered a remarkable tumor inhibition effect for a variety of tumor models. Our work for the first time discovered the ability of anionic metal ions to activate the immune system and rationally designed bimetallic oxide nanostructures as a multifunctional therapeutic nanoplatform for tumor immunotherapy.

Development and Validation of a Dual-Energy CT-Based Model for Predicting the Number of Central Lymph Node Metastases in Clinically Node-Negative Papillary Thyroid Carcinoma

RATIONALE AND OBJECTIVES

This study aimed to develop and validate a dual-energy CT (DECT)-based model for preoperative prediction of the number of central lymph node metastases (CLNMs) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC) patients.

MATERIALS AND METHODS

Between January 2016 and January 2021, 490 patients who underwent lobectomy or thyroidectomy, CLN dissection, and preoperative DECT examinations were enrolled and randomly allocated into the training (N = 345) and validation cohorts (N = 145). The patients' clinical characteristics and quantitative DECT parameters obtained on primary tumors were collected. Independent predictors of> 5 CLNMs were identified and integrated to construct a DECT-based prediction model, for which the area under the curve (AUC), calibration, and clinical usefulness were assessed. Risk group stratification was performed to distinguish patients with different recurrence risks.

RESULTS

More than 5 CLNMs were found in 75 (15.3%) cN0 PTC patients. Age, tumor size, normalized iodine concentration (NIC), normalized effective atomic number (nZeff) and the slope of the spectral Hounsfield unit curve (λHu) in the arterial phase were independently associated with> 5 CLNMs. The DECT-based nomogram that incorporated predictors demonstrated favorable performance in both cohorts (AUC: 0.842 and 0.848) and significantly outperformed the clinical model (AUC: 0.688 and 0.694). The nomogram showed good calibration and added clinical benefit for predicting> 5 CLNMs. The KaplanMeier curves for recurrence-free survival showed that the high- and low-risk groups stratified by the nomogram were significantly different.

CONCLUSION

The nomogram based on DECT parameters and clinical factors could facilitate preoperative prediction of the number of CLNMs in cN0 PTC patients.

MEX3A determines in vivo hepatocellular carcinoma progression and induces resistance to sorafenib in a Hippo-dependent way

BACKGROUND

Hepatocellular carcinoma (HCC) is most common malignant tumor worldwide, and one of the most lethal malignancies. MEX3A, RNA-binding protein, is profoundly implicated in tumor initiation and progression. But its role and potential mechanism in HCC remains fully unclear.

METHODS

The expression of MEX3A in HCC was analysis using the data derived from the Cancer Genome Atlas (TCGA) dataset and further confirmed by HCC samples and cells lines. The roles of MEX3A in the proliferation, migration and sorafenib resistance were detected both in vitro and vivo. In addition, the underline mechanism was investigated.

RESULTS

In this study, MEX3A expression was upregulated in HCC tissue and cell lines. Knockdown or overexpression of MEX3A disturbed the proliferation, migration and apoptosis of HCC cells by modulating the activation of Hippo signaling pathway. The expression of MEX3A was negatively associated with sorafenib sensitivity and upregulated in sorafenib resistant HCC cells. MEX3A knockdown facilitated the expression of WWC1, a negative modulator of Hippo signaling pathway, and led to increase of the phosphorylation of LATS1 and YAP1. Pharmacological inhibition of LATS1 or WWC1 overexpression alleviated the proliferative and migrated suppression and increased sorafenib sensitivity, whereas WWC1 inhibition using genetic interference strategy showed opposite trend in MEX3A knockdown HCC cells. Importantly, MEX3A knockdown led to growth and lung metastasis inhibition using xenograft model established by means of subcutaneous or tail vein injection. In addition, a combination of MEX3A knockdown and WWC1 overexpression dramatically enhances the growth inhibition of sorafenib in vivo.

CONCLUSION

MEX3A may facilitate HCC progression and hinder sorafenib sensitivity via inactivating Hippo signaling. The present study suggested that targeting MEX3A can be served as a novel therapeutic strategy for HCC.

Machine Learning Classifier for Preoperative Prediction of Early Recurrence After Bronchial Arterial Chemoembolization Treatment in Lung Cancer Patients

RATIONALE AND OBJECTIVES

Bronchial arterial chemoembolization (BACE) was deemed as an effective and safe approach for advanced standard treatment-ineligible/rejected lung cancer patients. However, the therapeutic outcome of BACE varies greatly and there is no reliable prognostic tool in clinical practice. This study aimed to investigate the effectiveness of radiomics features in predicting tumor recurrence after BACE treatment in lung cancer patients.

MATERIALS AND METHODS

A total of 116 patients with pathologically confirmed lung cancer who received BACE treatment were retrospectively recruited. All patients underwent contrast-enhanced CT within 2 weeks before BACE treatment and were followed up for more than 6 months. We conducted a machine learning-based characterization of each lesion on the preoperative contrast-enhanced CT images. In the training cohort, recurrence-related radiomics features were screened by least absolute shrinkage and selection operator (LASSO) regression. Three predictive radiomics signatures were built with linear discriminant analysis (LDA), support vector machine (SVM) and logistic regression (LR) algorithms, respectively. Univariate and multivariate LR analyses were performed to select the independent clinical predictors for recurrence. The radiomics signature with best predictive performance was integrated with the clinical predictors to form a combined model, which was visualized as a nomogram. The performance of the combined model was assessed by receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

RESULTS

Nine recurrence-related radiomics features were screened out, and three radiomics signatures (RadscoreLDA, RadscoreSVM and RadscoreLR) were built based on these features. Patients were classified into the low-risk and high-risk groups based on the optimal threshold of three signatures. Progression-free survival (PFS) analysis showed that patients of low-risk group achieved longer PFS than patients of high-risk group (P < 0.05). The combined model including RadscoreLDA and independent clinical predictors (tumor size, carcinoembryonic antigen and pro-gastrin releasing peptide) achieved the best predictive performance for recurrence after BACE treatment. It yields AUCs of 0.865 and 0.867 in the training and validation cohorts, with accuracy (ACC) of 0.804 and 0.750, respectively. Calibration curves indicated that the probability of recurrence predicted by the model fits well with the actual recurrence probability. DCA showed that the radiomics nomogram was clinically useful.

CONCLUSION

The radiomics and clinical predictors-based nomogram can predict tumor recurrence after BACE treatment effectively, which allowing oncologists to identify potential recurrence and enable better patient management and clinical decision-making.

The value of computed tomography perfusion deficit volumes in acute isolated brainstem infarction

Purpose

Diagnosis of acute isolated brainstem infarction is challenging owing to non-specific, variable symptoms, and the effectiveness of non-contrast computed tomography (NCCT) is poor owing to limited spatial resolution and artifacts. Computed tomography perfusion (CTP) imaging parameters are significantly associated with functional outcomes in posterior circulation acute ischemic stroke; however, the role of CTP in isolated brainstem infarction remains unclear. We aimed to determine the value of CTP imaging parameters in predicting functional outcomes for affected patients.

Methods

In total, 116 consecutive patients with isolated pontine/midbrain hypoperfusion who underwent CTP and follow-up by magnetic resonance imaging (MRI) between January 2018 and March 2022, were retrospectively analyzed. Perfusion deficit volumes on all maps, and the final infarction volume (FIV) on MRI were quantified. "Good" functional outcome was defined as a 90-day modified Rankin Scale score of 0 and 1. Statistical analysis included uni- and multivariate regression analyses, binary logistic regressions, and receiver operating characteristics (ROC) analyses.

Results

In total, 113 patients had confirmed isolated pontine/midbrain infarction on follow-up MRI. Onset-to-scan time, visibility of ischemic lesions on NCCT, the baseline National Institutes of Health Stroke Scale (NIHSS) score, and perfusion deficit volumes on all CTP maps were significantly associated with FIV (p < 0.05). In a multivariate linear regression model, adjusted for age, sex, NIHSS score, onset-to-scan time, and visibility of NCCT, perfusion deficit volumes remained significantly associated with FIV. In binary logistic regression analyses, perfusion deficit volumes on all CTP maps remained independent predictors of a good functional outcome. In ROC analyses, the cerebral blood flow deficit volume showed a slightly higher discriminatory value with the largest area under the curve being 0.683 [(95% CI, 0.587-0.780), p = 0.001].

Conclusion

Perfusion deficit volumes of CTP imaging could reflect the FIV and contain prognostic information on functional outcomes in patients with acute isolated brainstem infarction.

macJNet: weakly-supervised multimodal image deformable registration using joint learning framework and multi-sampling cascaded MIND

Deformable multimodal image registration plays a key role in medical image analysis. It remains a challenge to find accurate dense correspondences between multimodal images due to the significant intensity distortion and the large deformation. macJNet is proposed to align the multimodal medical images, which is a weakly-supervised multimodal image deformable registration method using a joint learning framework and multi-sampling cascaded modality independent neighborhood descriptor (macMIND). The joint learning framework consists of a multimodal image registration network and two segmentation networks. The proposed macMIND is a modality-independent image structure descriptor to provide dense correspondence for registration, which incorporates multi-orientation and multi-scale sampling patterns to build self-similarity context. It greatly enhances the representation ability of cross-modal features in the registration network. The semi-supervised segmentation networks generate anatomical labels to provide semantics correspondence for registration, and the registration network helps to improve the performance of multimodal image segmentation by providing the consistency of anatomical labels. 3D CT-MR liver image dataset with 118 samples is built for evaluation, and comprehensive experiments have been conducted to demonstrate that macJNet achieves superior performance over state-of-the-art multi-modality medical image registration methods.

Positive Chemotaxis of CREKA-Modified Ceria@Polydopamine Biomimetic Nanoswimmers for Enhanced Penetration and Chemo-photothermal Tumor Therapy

Tumor interstitial pressure represents the greatest barrier against drug diffusion into the depth of the tumor. Biometric nanomotors highlight the possibility of enhanced deep penetration and improve cellular uptake. However, control of their directionality remains difficult to achieve. Herein, we report cysteine-arginine-glutamic acid-lysine-alanine (CREKA)-modified ceria@polydopamine nanobowls as tumor microenvironment-fueled nanoscale motors for positive chemotaxis into the tumor depth or toward tumor cells. Upon laser irradiation, this nanoswimmer rapidly depletes the tumor microenvironment-specific hydrogen peroxide (H2O2) in the nanobowl, contributing to a self-generated gradient and subsequently propulsion (9.5 μm/s at 46 °C). Moreover, the asymmetrical modification of CREKA on nanobowls could automatically reconfigure the motion direction toward tumor depth or tumor cells in response to receptor-ligand interaction, leading to a deep penetration (70 μm in multicellular spheroids) and enhanced antitumor effects over conventional nanomedicine-induced chemo-photothermal therapy (tumor growth inhibition rate: 84.2% versus 56.9%). Thus, controlling the direction of nanomotors holds considerable potential for improved antitumor responses, especially in solid tumors with high tumor interstitial pressure.

Biomaterials evolution: from inert to instructive

The field of biomaterials has experienced substantial evolution in recent years, driven by advancements in materials science and engineering. This has led to an expansion of the biomaterials definition to include biocompatibility, bioactivity, bioderived materials, and biological tissues. Consequently, the intended performance of biomaterials has shifted from a passive role wherein a biomaterial is merely accepted by the body to an active role wherein a biomaterial instructs its biological environment. In the future, the integration of bioinspired designs and dynamic behavior into fabrication technologies will revolutionize the field of biomaterials. This perspective presents the recent advances in the evolution of biomaterials in fabrication technologies and provides a brief insight into smart biomaterials.

Unsupervised registration for liver CT-MR images based on the multiscale integrated spatial-weight module and dual similarity guidance

PURPOSE

Multimodal registration is a key task in medical image analysis. Due to the large differences of multimodal images in intensity scale and texture pattern, it is a great challenge to design distinctive similarity metrics to guide deep learning-based multimodal image registration. Besides, since the limitation of the small receptive field, existing deep learning-based methods are mainly suitable for small deformation, but helpless for large deformation. To address the above issues, we present an unsupervised multimodal image registration method based on the multiscale integrated spatial-weight module and dual similarity guidance.

METHODS

In this method, a U-shape network with our multiscale integrated spatial-weight module is embedded into a multi-resolution image registration architecture to achieve end-to-end large deformation registration, where the spatial-weight module can effectively highlight the regions with large deformation and aggregate discriminative features, and the multi-resolution architecture further helps to solve the optimization problem of the network in a coarse-to-fine pattern. Furthermore, we introduce a special loss function based on dual similarity, which represents both global gray-scale similarity and local feature similarity, to optimize the unsupervised multimodal registration network.

RESULTS

We verified the effectiveness of the proposed method on liver CT-MR images. Experimental results indicate that the proposed method achieves the optimal DSC value and TRE value of 92.70 ± 1.75(%) and 6.52 ± 2.94(mm), compared with other state-of-the-art registration algorithms.

CONCLUSION

The proposed method can accurately estimate the large deformation field by aggregating multiscale features, and achieve higher registration accuracy and fast registration speed. Comparative experiments also demonstrate the effectiveness and generalization ability of the algorithm.

Development and validation of convolutional neural network-based model to predict the risk of sentinel or non-sentinel lymph node metastasis in patients with breast cancer: a machine learning study

Background

For patients with sentinel lymph node (SLN) metastasis and low risk of residual non-SLN (NSLN) metastasis, axillary lymph node (ALN) dissection could lead to overtreatment. This study aimed to develop and validate an automated preoperative deep learning-based tool to predict the risk of SLN and NSLN metastasis in patients with breast cancer (BC) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images.

Methods

In this machine learning study, we retrospectively enrolled 988 women with BC from three hospitals in Zhejiang, China between June 1, 2013 to December 31, 2021, June 1, 2017 to December 31, 2021, and January 1, 2019 to June 30, 2023, respectively. Patients were divided into the training set (n = 519), internal validation set (n = 129), external test set 1 (n = 296), and external test set 2 (n = 44). A convolutional neural network (CNN) model was proposed to predict the SLN and NSLN metastasis and was compared with clinical and radiomics approaches. The performance of different models to detect ALN metastasis was measured by the area under the curve (AUC), accuracy, sensitivity, and specificity. This study is registered at ChiCTR, ChiCTR2300070740.

Findings

For SLN prediction, the top-performing model (i.e., the CNN algorithm) achieved encouraging predictive performance in the internal validation set (AUC 0.899, 95% CI, 0.887-0.911), external test set 1 (AUC 0.885, 95% CI, 0.867-0.903), and external test set 2 (AUC 0.768, 95% CI, 0.738-0.798). For NSLN prediction, the CNN-based model also exhibited satisfactory performance in the internal validation set (AUC 0.800, 95% CI, 0.783-0.817), external test set 1 (AUC 0.763, 95% CI, 0.732-0.794), and external test set 2 (AUC 0.728, 95% CI, 0.719-0.738). Based on the subgroup analysis, the CNN model performed well in tumour group smaller than 2.0 cm, with the AUC of 0.801 (internal validation set) and 0.823 (external test set 1). Of 469 patients with BC, the false positive rate of SLN prediction declined from 77.9% to 32.9% using CNN model.

Interpretation

The CNN model can predict the SLN status of any detectable lesion size and condition of NSLN in patients with BC. Overall, the CNN model, employing ready DCE-MRI images could serve as a potential technique to assist surgeons in the personalized axillary treatment of in patients with BC non-invasively.

Funding

National Key Research and Development projects intergovernmental cooperation in science and technology of China, National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province, and Zhejiang Medical and Health Science Project.

Chinese expert consensus on the diagnosis and treatment of malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a malignant tumor originating from the pleura, and its incidence has been increasing in recent years. Due to the insidious onset and strong local invasiveness of MPM, most patients are diagnosed in the late stage and early screening and treatment for high-risk populations are crucial. The treatment of MPM mainly includes surgery, chemotherapy, and radiotherapy. Immunotherapy and electric field therapy have also been applied, leading to further improvements in patient survival. The Mesothelioma Group of the Yangtze River Delta Lung Cancer Cooperation Group (East China LUng caNcer Group, ECLUNG; Youth Committee) developed a national consensus on the clinical diagnosis and treatment of MPM based on existing clinical research evidence and the opinions of national experts. This consensus aims to promote the homogenization and standardization of MPM diagnosis and treatment in China, covering epidemiology, diagnosis, treatment, and follow-up.

Recombinant supercharged polypeptides for safe and efficient heparin neutralization

Heparin is a widely used anticoagulant agent in the clinic. After application, its anticoagulant effect must be reversed to prevent potential side effects. Protamine sulfate (PS) is the only clinically licensed antidote that has been used for this purpose in the last 80 years, which, however, provokes severe adverse effects, such as systemic hypotension and even death. Herein, we demonstrate the potential of supercharged polypeptides as a promising alternative for protamine sulfate. A series of supercharged polypeptides with multiple positive charges was recombinantly produced, and the heparin-neutralizing performance of the polypeptides was evaluated in comparison with PS. It was found that increasing the number of charges significantly enhanced the ability to neutralize heparin and resist the screening effect induced by salt. In particular, the polypeptide bearing 72 charges (K72) exhibited an excellent heparin-neutralizing behavior that was comparable to that of PS. Further in vivo studies revealed that the heparin-triggered bleeding was almost completely alleviated by K72 while a negligible toxic effect was observed. Therefore, such recombinant supercharged polypeptides might replace protamine sulfate as heparin-reversal agents.

Prediction of placenta accreta spectrum with nomogram combining radiomic and clinical factors: A novel developed and validated integrative model

OBJECTIVE

To develop and validate a clinicoradiomic nomogram based on sagittal T2WI images to predict placenta accreta spectrum (PAS).

METHODS

Between October 2016 and April 2022, women suspected of PAS by ultrasound were enrolled. After taking into account exclusion criteria, 132 women were retrospectively included in the study. The variance threshold SelectKBest and the least absolute shrinkage and selection operator were applied to select radiomic features, which was further used to calculate the Rad-score. Multivariable logistic regression was used to screen clinical factor.

RESULTS

Based on 13 radiomic features, five radiomic models were constructed. A clinical factor of intraplacental T2-hypointense bands was obtained by multivariate logistic regression. The area under the curve (AUC) value of the stochastic gradient descent (SGD) radiomic model was 0.82 in the training cohort and 0.78 in the test cohort. After adding clinical factors to the SGD radiomic model, the AUC value of the clinicoradiomic model was significantly increased from 0.82 and 0.78 to 0.84 in both the training and test cohorts. The nomogram of the clinicoradiomic model was constructed, which had good performance verified by calibration and a decision curve.

CONCLUSION

The presented nomogram could be useful for predicting PAS.

TACE responser NDRG1 acts as a guardian against ferroptosis to drive tumorgenesis and metastasis in HCC

BACKGROUND

The treatment efficacy of transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) varies widely between individuals. The aim of this study was to identify subtype landscapes and responser related to TACE, and further clarify the regulatory effect and corresponding mechanism of NDRG1 on HCC tumorgenesis and metastasis.

METHODS

The principal component analysis (PCA) algorithm was used to construct a TACE response scoring (TRscore) system. The random forest algorithm was applied to identify the TACE response-related core gene NDRG1 of HCC, and its role in the prognosis of HCC was explored. The role of NDRG1 in the progression and metastasis of HCC and functional mechanism were confirmed using several experimental methods.

RESULTS

Based on the GSE14520 and GSE104580 cohorts, we identified 2 TACE response-related molecular subtypes for HCC with significant differences in clinical features, and the TACE prognosis of Cluster A was significantly better than that of Cluster B (p < 0.0001). We then established the TRscore system and found that the low TRscore group showed a higher probability of survival and a lower rate of recurrence than the high TRscore group (p < 0.05) in both the HCC and TACE-treated HCC cohorts within the GSE14520 cohort. NDRG1 was determined to be the the hub gene associated with the TACE response of HCC and its high expression suggested a poor prognosis. Furthermore, The suppression of NDRG1 konckdown in tumorgenesis and metastasis of HCC was clarified in both vivo and vitro, which was importantly achieved through inducing ferroptosis in HCC cells, especially contributing to RLS3-induced ferroptosis.

CONCLUSION

The constructed TACE response-related molecular subtypes and TRscores can specifically and accurately predict TACE prognosis for HCC. In addition, the TACE response-related hub gene NDRG1 may act as a guardian against ferroptosis to drive tumorgenesis and metastasis in HCC, which laid a new foundation for the development of new potential targeted therapy strategies to improve disease prognosis in HCC patients.

Proteomic analysis of DZIP3 interactome and its role in proliferation and metastasis in gastric cancer cells

Gastric cancer is a serious malignant tumor in the world, accounting for the third cause of cancer death worldwide. The pathogenesis of gastric cancer is very complex, in which epigenetic inheritance plays an important role. In our study, we found that DZIP3 was significantly up-regulated in gastric cancer tissues as compared to adjacent normal tissue, which suggested it may be play a crucial part in gastric cancer. To clarify the mechanism of it, we further analyzed the interacting proteome and transcriptome of DZIP3. An association between DZIP3 and some epigenetic regulators, such as CUL4B complex, was verified. We also present the first proteomic characterization of the protein-protein interaction (PPI) network of DZIP3. Then, the transcriptome analysis of DZIP3 demonstrated that knockdown DZIP3 increased a cohort of genes, including SETD7 and ZBTB4, which have essential role in tumors. We also revealed that DZIP3 promotes proliferation and metastasis of gastric cancer cells. And the higher expression of DZIP3 is positively associated with the poor prognosis of several cancers. In summary, our study revealed a mechanistic role of DZIP3 in promoting proliferation and metastasis in gastric cancer, supporting the pursuit of DZIP3 as a potential target for gastric cancer therapy.

Preparation and characterization of PLGA-based magnetic polymer nanoparticles for targeting pancreatic adenocarcinoma

Aims:

This study aims to develop a novel tumor-targeted molecular probe for pancreatic cancer imaging. The objective of this is to prepare a CKAAKN peptide-conjugated poly (lactic-co-glycolic acid)–poly (ethylene glycol) amphiphilic polymer (CKAAKN-PEG-PLGA) for the tumor-targeted delivery of magnetic resonance imaging (MRI) contrast agent ultrasmall superparamagnetic iron oxide (USPIO).

background:

The early diagnosis of pancreatic cancer is crucial for improving its prognosis, but the clinical application of many diagnostic methods is limited owing to lack of specificity and sensitivity.

Background:

The early diagnosis of pancreatic cancer is crucial for improving its prognosis, but the clinical application of many diagnostic methods is limited owing to a lack of specificity and sensitivity.

Methods:

CKAAKN-PEG-PLGA was synthesized by the amidation reaction. USPIO-loaded polymeric magnetic nanoparticles (USPIO@CKAAKN-PEG-PLGA) were prepared by the emulsion solvent evaporation method. The in vitro tumor targeting and bio-safety of nanoparticles were evaluated by targeted cellular uptake, MR imaging and MTT assay.

method:

CKAAKN-PEG-PLGA was synthesized by the amidation reaction. USPIO-loaded polymeric magnetic nanoparticles (USPIO@CKAAKN-PEG-PLGA) were prepared by the emulsion solvent evaporation method. The in vitro tumor targeting and bio-safety of nanoparticles were evaluated by targeted cellular uptake, MR imaging and MTT assay.

Results:

USPIO@CKAAKN-PEG-PLGA nanoparticles showed excellent biosafety with an average diameter of 104.5 ± 4.1 nm. Modification of CKAAKN peptide could improve USPIO binding ability to internalize into CKAAKN-positive BxPC-3 cells compared with non-targeting nanoparticles and the control group. The relative fluorescence intensity in BxPC-3 and HPDE6-C7 cells was 23.77 ± 4.18 and 6.44 ± 2.10 (p＜0.01), and respectively became 16.13 ± 0.83 and 11.74 ± 1.74 after the addition of free CKAAKN peptide. In vitro MR imaging studies showed that an obvious decrease in the signal intensity was observed in the targeted nanoparticles group incubated with BxPC-3 and HPDE6-C7 cells (P<0.05).

Conclusion:

USPIO@CKAAKN-PEG-PLGA nanoparticles could significantly enhance the tumor specificity of USPIO in CKAAKN-positive pancreatic cancer cell BxPC-3, which is expected as a promising candidate of MRI contrast enhancement for the early diagnosis of pancreatic cancer.

conclusion:

USPIO@CKAAKN-PEG-PLGA nanoparticles could significantly enhance the tumor specificity of USPIO in CKAAKN-positive pancreatic cancer cell BxPC-3, which is expected as a promising candidate of MRI contrast enhancement for the early diagnosis of pancreatic cancer.

Chinese expert consensus on the diagnosis and treatment of thymic epithelial tumors

Thymic epithelial tumors (TETs) are a relatively rare type of thoracic tumor, accounting for less than 1% of all tumors. The incidence of TETs is about 3.93/10000 in China, slightly higher than that of European and American countries. For resectable TETs, complete surgical resection is recommended. Radiotherapy or chemotherapy may be used as postoperative adjuvant treatment. Treatment for advanced, unresectable TETs consist mainly of radiotherapy and chemotherapy, but there is a lack of standard first- and second-line treatment regimens. Recently, targeted therapies and immune checkpoint inhibitors have shown promising outcomes in TETs. Based on the currently available clinical evidences and the opinions of the national experts, the Thymic Oncology Group of Yangtze River Delta Lung Cancer Cooperation Group (East China LUng caNcer Group, ECLUNG; Youth Committee) established this Chinese expert consensus on the clinical diagnosis and treatment of TETs, covering the epidemiology, diagnosis, treatment, prognosis and follow-up of TETs.

Precise prediction of the sensitivity of platinum chemotherapy in SCLC: Establishing and verifying the feasibility of a CT-based radiomics nomogram

Objectives

To develop and validate a CT-based radiomics nomogram that can provide individualized pretreatment prediction of the response to platinum treatment in small cell lung cancer (SCLC).

Materials

A total of 134 SCLC patients who were treated with platinum as a first-line therapy were eligible for this study, including 51 patients with platinum resistance (PR) and 83 patients with platinum sensitivity (PS). The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were applied for feature selection and model construction. The selected texture features were calculated to obtain the radiomics score (Rad-score), and the predictive nomogram model was composed of the Rad-score and the clinical features selected by multivariate analysis. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were used to assess the performance of the nomogram.

Results

The Rad-score was calculated using 10 radiomic features, and the resulting radiomics signature demonstrated good discrimination in both the training set (area under the curve [AUC], 0.727; 95% confidence interval [CI], 0.627–0.809) and the validation set (AUC, 0.723; 95% CI, 0.562–0.799). To improve diagnostic effectiveness, the Rad-score created a novel prediction nomogram by combining CA125 and CA72-4. The radiomics nomogram showed good calibration and discrimination in the training set (AUC, 0.900; 95% CI, 0.844-0.947) and the validation set (AUC, 0.838; 95% CI, 0.534-0.735). The radiomics nomogram proved to be clinically beneficial based on decision curve analysis.

Conclusion

We developed and validated a radiomics nomogram model for predicting the response to platinum in SCLC patients. The outcomes of this model can provide useful suggestions for the development of tailored and customized second-line chemotherapy regimens.

Monodisperse CaCO3-loaded gelatin microspheres for reversing lactic acid-induced chemotherapy resistance during TACE treatment

Transarterial chemoembolization (TACE) is an important approach for the treatment of unresectable hepatocellular carcinoma (HCC). However, the lactic acid-induced acidic tumor microenvironment (TME) may reduce the therapeutic outcome of TACE. Herein, monodispersed gelatin microspheres loaded with calcium carbonate nanoparticles (CaNPs@Gel-MS) as novel embolic agents were prepared by a simplified microfluidic device. It was found that the particle size and homogeneity of as-prepared CaNPs@Gel-MS were strongly dependent on the flow rates of continuous and dispersed phases, and the inner diameter of syringe needle. The introduction of CaNPs provided the gelatin microspheres with an enhanced ability to encapsulate the chemotherapeutic drug of DOX, as well as a pH-responsive sustained drug release behavior. In vitro results revealed that CaNPs@Gel-MS could largely increase the cellular uptake and chemotoxicity of DOX by neutralizing the lactic acid in the culture medium. In addition, CaNPs@Gel-MS exhibited an excellent and persistent embolic efficiency in a rabbit renal model. Finally, we found that TACE treatment with DOX-loaded CaNPs@Gel-MS (DOX/CaNPs@Gel-MS) had a much stronger ability to inhibit tumor growth than the DOX-loaded gelatin microspheres without CaNPs (DOX@Gel-MS). Overall, CaNPs@Gel-MS could be a promising embolic microsphere that can significantly improve anti-HCC ability by reversing lactic acid-induced chemotherapy resistance during TACE treatment.

Rational Design of Biomaterials to Potentiate Cancer Thermal Therapy

Cancer thermal therapy, also known as hyperthermia therapy, has long been exploited to eradicate mass lesions that are now defined as cancer. With the development of corresponding technologies and equipment, local hyperthermia therapies such as radiofrequency ablation, microwave ablation, and high-intensity focused ultrasound, have has been validated to effectively ablate tumors in modern clinical practice. However, they still face many shortcomings, including nonspecific damages to adjacent normal tissues and incomplete ablation particularly for large tumors, restricting their wide clinical usage. Attributed to their versatile physiochemical properties, biomaterials have been specially designed to potentiate local hyperthermia treatments according to their unique working principles. Meanwhile, biomaterial-based delivery systems are able to bridge hyperthermia therapies with other types of treatment strategies such as chemotherapy, radiotherapy and immunotherapy. Therefore, in this review, we discuss recent progress in the development of functional biomaterials to reinforce local hyperthermia by functioning as thermal sensitizers to endow more efficient tumor-localized thermal ablation and/or as delivery vehicles to synergize with other therapeutic modalities for combined cancer treatments. Thereafter, we provide a critical perspective on the further development of biomaterial-assisted local hyperthermia toward clinical applications.

The role of metabolic reprogramming of oxygen-induced macrophages in the dynamic changes of atherosclerotic plaques

Atherosclerosis (As) is a chronic vascular inflammatory disease. Macrophages are the most important immune cells in atherosclerotic plaques, and the phenotype of plaque macrophages shifts dynamically to adapt to changes in the plaque microenvironment. The aerobic microenvironment of early atherosclerotic plaques promotes the transformation of M2/alternatively activated macrophages mainly through oxidative phosphorylation; the anoxic microenvironment of advanced atherosclerotic plaques mainly promotes the formation of M1/classically activated macrophages through anaerobic glycolysis; and the adventitia angiogenesis of aged atherosclerotic plaques leads to an increase in the proportion of M2/M1 macrophages. Therefore, this review deeply elucidates the dynamic change mechanism of plaque macrophages and the regulation of plaque oxygen content and immune metabolism to find new targets for the treatment of As.

Multi-algorithms analysis for pre-treatment prediction of response to transarterial chemoembolization in hepatocellular carcinoma on multiphase MRI

OBJECTIVES

This study compared the accuracy of predicting transarterial chemoembolization (TACE) outcomes for hepatocellular carcinoma (HCC) patients in the four different classifiers, and comprehensive models were constructed to improve predictive performance.

METHODS

The subjects recruited for this study were HCC patients who had received TACE treatment from April 2016 to June 2021. All participants underwent enhanced MRI scans before and after intervention, and pertinent clinical information was collected. Registry data for the 144 patients were randomly assigned to training and test datasets. The robustness of the trained models was verified by another independent external validation set of 28 HCC patients. The following classifiers were employed in the radiomics experiment: machine learning classifiers k-nearest neighbor (KNN), support vector machine (SVM), the least absolute shrinkage and selection operator (Lasso), and deep learning classifier deep neural network (DNN).

RESULTS

DNN and Lasso models were comparable in the training set, while DNN performed better in the test set and the external validation set. The CD model (Clinical & DNN merged model) achieved an AUC of 0.974 (95% CI: 0.951-0.998) in the training set, superior to other models whose AUCs varied from 0.637 to 0.943 (p < 0.05). The CD model generalized well on the test set (AUC = 0.831) and external validation set (AUC = 0.735).

CONCLUSIONS

DNN model performs better than other classifiers in predicting TACE response. Integrating with clinically significant factors, the CD model may be valuable in pre-treatment counseling of HCC patients who may benefit the most from TACE intervention.

Inactivation of KDM5A suppresses growth and enhances chemosensitivity in liver cancer by modulating ROCK1/PTEN/AKT pathway

Liver cancer is a kind of malignant tumor with poor sensitivity to chemotherapy. It is urgent to investigate approaches to improve the outcome of chemotherapy. KDM5A has been reported to be an oncogene in various cancers and is associated with drug resistance. However, the functions of KDM5A in chemotherapeutic sensitivity of liver cancer not been well illustrated. In this study, we found that KDM5A was upregulated in liver cancer tissue and cell lines. KDM5A knockdown using a gene interference strategy suppressed the growth of liver cancer in vitro and in vivo. CPI-455, a pharmacological inactivation of KDM5A enhanced the cytotoxicity of cisplatin (CDDP) in liver cells. CPI-455 and CDDP cotreatment resulted in apoptosis and mitochondrial dysfunction. We also found that knockdown or inactivation of KDM5A resulted in the downregulation of ROCK1, an oncogene regulating the activation of the PTEN/AKT signaling pathway. In particular, overexpression of ROCK1 or SF1670, a pharmacological inhibitor of PTEN, alleviated the cytotoxicity of CPI-455 and CDDP cotreatment. In HCCLM3 xenografts, CPI-455 and CDDP cotreatment dramatically inhibited the growth of xenograft tumor compared to CPI-455 or CDDP treatment alone. In conclusion, this study suggested that targeting the inactivation of KDM5A is an efficient strategy to enhance the chemosensitivity of liver cancer cells to CDDP by modulating the ROCK1/PTEN/AKT signaling pathway.

Macrophage xCT deficiency drives immune activation and boosts responses to immune checkpoint blockade in lung cancer

Tumor-associated macrophages (TAMs) play an important role in remodeling the tumor microenvironment (TME), which promotes tumor growth, immunosuppression and angiogenesis. Because of the high plasticity of macrophages and the extremely complex tumor microenvironment, the mechanism of TAMs in cancer progression is still largely unknown. In this study, we found that xCT (SLC7A11) was overexpressed in lung cancer-associated macrophages. Higher xCT in TAMs was associated with poor prognosis and was an independent predictive factor in lung cancer. In addition, lung cancer growth and progression was inhibited in xCT knockout mice, especially macrophage-specific xCT knockout mice. We also found that the deletion of macrophage xCT inhibited AKT/STAT6 signaling activation and reduced M2-type polarization of TAMs. Macrophage xCT deletion recruited more CD8⁺ T cells and activated the lung cancer cell-mediated and IFN-γ-induced JAK/STAT1 axis and increased the expression of its target genes, including CXCL10 and CD274. The combination of macrophage xCT deletion and anti-PDL1 antibody achieved better tumor inhibition. Finally, combining the xCT inhibitor erastin with an anti-PDL1 antibody was more potent in inhibiting lung cancer progression. Therefore, suppression of xCT may overcome resistance to cancer immunotherapy.

MLL4 Regulates the Progression of Non-Small-Cell Lung Cancer by Regulating the PI3K/AKT/SOX2 Axis

Purpose

Mixed-lineage leukemia protein 4 (MLL4/KMT2D) is a histone methyltransferase, and its mutation has been reported to be associated with a poor prognosis in many cancers, including lung cancer. We investigated the function of MLL4 in lung carcinogenesis.

Materials and Methods

RNA sequencing (RNA-seq) in A549 cells transfected with control siRNA or MLL4 siRNA was performed. Also, we used EdU incorporation assay, colony formation assays, growth curve analysis, transwell invasion assays, immunohistochemical staining and in vivo bioluminescence assay to investigate the function of MLL4 in lung carcinogenesis.

Results

We found that MLL4 expression was down-regulated in non-small cell lung cancer (NSCLC) tissues compared to adjacent normal tissues and tended to decrease with disease stage progression. We analyzed the transcriptomes in control and MLL4-deficient cells using high-throughput RNA deep sequencing (RNA-seq) and identified a cohort of target genes, such as SOX2, ATF1, FOXP4, PIK3IP1, SIRT4, TENT5B, and LFNG, some of which are related to proliferation and metastasis. Our results showed that low expression of MLL4 promotes NSCLC cell proliferation and metastasis and is required for the maintenance of non-small cell lung cancer stem cell properties.

Conclusion

Our findings identify an important role of MLL4 in lung carcinogenesis through transcriptional regulation of PIK3IP1, affecting the PI3K/AKT/SOX2 axis, and suggest that MLL4 could be a potential prognostic indicator and target for non-small cell lung cancer therapy.

Predictive Models for Colon Adenocarcinoma Diagnosis, Prognosis, and Immune Microenvironment Based on 2 Hypoxia-Related Genes: KDM3A and ENO3

Background: Hypoxia is known to play a critical role in tumor occurrence, progression, prognosis, and therapy resistance. However, few studies have investigated hypoxia markers for diagnosing and predicting prognosis in colon adenocarcinoma (COAD). This study aims to identify a hypoxia genes-based biomarker for predicting COAD patients' prognosis and response to immunotherapy on an individual basis. Methods: Hypoxia-related genes were extracted from the Molecular Signatures Database. Gene expression, clinical data, and mutation data of COAD were collected retrospectively from the Cancer Genome Atlas, the Gene Expression Omnibus, and the International Cancer Genome Consortium databases. Univariate and multivariate cox regression, and the least absolute shrinkage and selection operator method were used to select the genes most associated with the prognosis of COAD patients. Kaplan-Meier survival analysis, receiver operating characteristic curves, calibration curves, and decision curve analyses were performed to validate the efficacy of the signature in predicting the prognosis of COAD patients. EdU incorporation assays, cell survival assays, western blot assays, and trans-well invasion assays were performed to further confirm the function of the screened genes in tumorigenesis. Results: ENO3 and KDM3A were identified as key genes for constructing prognostic and diagnostic signatures, which were found to be independent risk factors for predicting the prognosis and diagnosis of COAD patients. Using these signatures, COAD patients could be stratified into high-risk and low-risk groups, with the latter exhibiting better overall survival outcomes. Moreover, the high-risk group displayed elevated levels of immune checkpoint genes and tumor mutation burden, indicating that these patients may benefit from immune checkpoint inhibitor therapy. Conclusion: The signature developed in this study demonstrates excellent efficacy in prognosticating the outcomes of COAD patients. Moreover, it can serve as a valuable tool for clinicians to identify COAD patients who are suitable for ICI therapy.

Targeted xCT-mediated Ferroptosis and Protumoral Polarization of Macrophages Is Effective against HCC and Enhances the Efficacy of the Anti-PD-1/L1 Response

Tumor-associated macrophages (TAMs) play an essential role in tumor progression, metastasis, and antitumor immunity. Ferroptosis has attracted extensive attention for its lethal effect on tumor cells, but the role of ferroptosis in TAMs and its impact on tumor progression have not been clearly defined. Using transgenic mouse models, this study determines that xCT-specific knockout in macrophages is sufficient to limit tumorigenicity and metastasis in the mouse HCC models, achieved by reducing TAM recruitment and infiltration, inhibiting M2-type polarization, and activating and enhancing ferroptosis activity within TAMs. The SOCS3-STAT6-PPAR-γ signaling may be a crucial pathway in macrophage phenotypic shifting, and activation of intracellular ferroptosis is associated with GPX4/RRM2 signaling regulation. Furthermore, that xCT-mediated macrophage ferroptosis significantly increases PD-L1 expression in macrophages and improves the antitumor efficacy of anti-PD-L1 therapy is unveiled. The constructed Man@pSiNPs-erastin specifically targets macrophage ferroptosis and protumoral polarization and combining this treatment with anti-PD-L1 exerts substantial antitumor efficacy. xCT expression in tumor tissues, especially in CD68+ macrophages, can serve as a reliable factor to predict the prognosis of HCC patients. These findings provide further insight into targeting ferroptosis activation in TAMs and regulating TAM infiltration and functional expression to achieve precise tumor prevention and improve therapeutic efficacy.

SMYD3 associates with the NuRD (MTA1/2) complex to regulate transcription and promote proliferation and invasiveness in hepatocellular carcinoma cells

BACKGROUND

SMYD3, a member of the SET and MYND domain-containing (SMYD) family, is a histone methyltransferase (HMT) and transcription factor that plays an important role in transcriptional regulation in human carcinogenesis.

RESULTS

Using affinity purification and mass spectrometry assays to identify SMYD3-associated proteins in hepatocellular carcinoma (HCC) cells, we found several previously undiscovered SMYD3-interacting proteins, including the NuRD (MTA1/2) complex, the METTL family, and the CRL4B complex. Transcriptomic analysis of the consequences of knocking down SMYD3, MTA1, or MTA2 in HCC cells showed that SMYD3/NuRD complex targets a cohort of genes, some of which are critically involved in cell growth and migration. qChIP analyses showed that SMYD3 knockdown led to a significant reduction in the binding of MTA1 or MTA2 to the promoters of IGFBP4 and led to a significant decrease in H4K20me3 and a marked increase in H4Ac at the IGFBP4 promoter. In addition, we demonstrated that SMYD3 promotes cell proliferation, invasion, and tumorigenesis in vivo and in vitro and found that its expression is markedly upregulated in human liver cancer. Knockdown of MTA1 or MTA2 had the same effect as knockdown of SMYD3 on proliferation and invasion of hepatocellular carcinoma cells. Catalytic mutant SMYD3 could not rescue the phenotypic effects caused by knockdown of SMYD3. Inhibitors of SMYD3 effectively inhibited the proliferation and invasiveness of HCC cells.

CONCLUSIONS

These findings revealed that SMYD3 could transcriptionally repress a cohort of target genes expression by associating with the NuRD (MTA1/2) complex, thereby promoting the proliferation and invasiveness of HCC cells. Our results support the case for pursuing SMYD3 as a practical prognostic marker or therapeutic target against HCC.

Ferritin-Hijacking Nanoparticles Spatiotemporally Directing Endogenous Ferroptosis for Synergistic Anticancer Therapy

Existing ferroptosis as an iron-dependent form of regulated cell death primarily relies on importing exogenous iron. However, the excessive employment of toxic materials may cause potential adverse effects on human health. Herein, a ferritin-hijacking nanoparticle (Ce6-PEG-HKN₁₅ ) is fabricated, by conjugating the ferritin-homing peptide HKN₁₅ with the photosensitizer chlorin e6 (Ce6) for endogenous ferroptosis without introducing Fenton-reactive metals. Once internalized, the designed Ce6-PEG-HKN₁₅ NPs can specifically accumulate around ferritin. With laser irradiation, the activated Ce6 in nanoparticles potently generates reactive oxygen species (ROS) surrounding ferritin. Abundant ROS not only helps to destroy the iron storage protein and activate endogenous ferroptosis but also directly kill tumor cells. In turn, the released iron partially interacts with intracellular excess H₂ O₂ to produce O₂ , thereby enhancing photodynamic therapy and further amplifying oxidative stress. Overall, this work highlights the possibility of endogenous ferroptosis via spatiotemporally destroying ferritin, offering a paradigm for synergistic ferroptosis-photodynamic antitumor therapy.

Safety and immunogenicity of COVID-19 vaccination in patients with hepatocellular carcinoma (CHESS-NMCID 2101): A multicenter prospective study

Data on safety and immunogenicity of coronavirus disease 2019 (COVID-19) vaccinations in hepatocellular carcinoma (HCC) patients are limited. In this multicenter prospective study, HCC patients received two doses of inactivated whole-virion COVID-19 vaccines. The safety and neutralizing antibody were monitored. Totally, 74 patients were enrolled from 10 centers in China, and 37 (50.0%), 25 (33.8%), and 12 (16.2%) received the CoronaVac, BBIBP-CorV, and WIBP-CorV, respectively. The vaccines were well tolerated, where pain at the injection site (6.8% [5/74]) and anorexia (2.7% [2/74]) were the most frequent local and systemic adverse events. The median level of neutralizing antibody was 13.5 (interquartile range [IQR]: 6.9-23.2) AU/ml at 45 (IQR: 19-72) days after the second dose of vaccinations, and 60.8% (45/74) of patients had positive neutralizing antibody. Additionally, lower γ-glutamyl transpeptidase level was related to positive neutralizing antibody (odds ratio = 1.022 [1.003-1.049], p = 0.049). In conclusion, this study found that inactivated COVID-19 vaccinations are safe and the immunogenicity is acceptable or hyporesponsive in patients with HCC. Given that the potential benefits may outweigh the risks and the continuing emergences of novel severe acute respiratory syndrome coronavirus 2 variants, we suggest HCC patients to be vaccinated against COVID-19. Future validation studies are warranted.

Fucoidan-based dual-targeting mesoporous polydopamine for enhanced MRI-guided chemo-photothermal therapy of HCC via P-selectin-mediated drug delivery

The development of novel theranostic agents with outstanding diagnostic and therapeutic performances is still strongly desired in the treatment of hepatocellular carcinoma (HCC). Here, a fucoidan-modified mesoporous polydopamine nanoparticle dual-loaded with gadolinium iron and doxorubicin (FMPDA/Gd³⁺/DOX) was prepared as an effective theranostic agent for magnetic resonance imaging (MRI)-guided chemo-photothermal therapy of HCC. It was found that FMPDA/Gd³⁺/DOX had a high photothermal conversion efficiency of 33.4% and excellent T₁-MRI performance with a longitudinal relaxivity (r₁) value of 14.966 mM^-1·s ^- 1. Moreover, the results suggested that FMPDA/Gd³⁺/DOX could effectively accumulate into the tumor foci by dual-targeting the tumor-infiltrated platelets and HCC cells, which resulted from the specific interaction between fucoidan and overexpressed p-selectin receptors. The excellent tumor-homing ability and MRI-guided chemo-photothermal therapy therefore endowed FMPDA/Gd³⁺/DOX with a strongest ability to inhibit tumor growth than the respective single treatment modality. Overall, our study demonstrated that FMPDA/Gd³⁺/DOX could be applied as a potential nanoplatform for safe and effective cancer theranostics.

Intraplacental T2-hypointense bands may help predict placental invasion depth and postpartum hemorrhage in placenta accrete spectrum disorders in high-risk gravid patients

INTRODUCTION

Accurate noninvasive prenatal diagnosis of placenta accreta spectrum (PAS) disorder is critical for delivery management.

PURPOSE

To evaluate the diagnostic ability of MRI features in predicting the PAS, invasive depth and postpartum hemorrhage (PPH) in high-risk gravid patients.

MATERIALS AND METHODS

Between February 2019 and November 2020, women with ultrasound (US)-suspected PAS were enrolled. With the exclusion criteria, 80 women were included in the study. Two experienced genitourinary radiologists reviewed and recorded the MRI features. The chi square test was used to compare the effectiveness of MRI features. Relative risk ratios were computed to test the association of intraplacental T2-hypointense bands with poor outcomes of cesarean section. Receiver operating characteristic (ROC) analyses based on the number and area of intraplacental T2-hypointense bands were used to predict PAS, invasion depth, and PPH.

RESULTS

PAS was diagnosed in 56 of 80 women (70%). At delivery, 24 of 80 women (30%) experienced PPH (≥1000 mL). Intraplacental T2-hypointense bands were detected at MRI in 28 of 56 women with PAS (50%). The relative risk ratio of intraplacental T2-hypointense bands was 1.51 for PAS, 3.17 for depth of PAS invasiveness and 4.74 for PPH. The largest areas of intraplacental T2-hypointense bands for predicting PAS, invasion depth and PPH were 0.66 cm², 1.68 cm² and 1.99 cm², respectively.

DISCUSSION

The appearance of intraplacental T2-hypointense bands has important diagnostic value for PAS, its invasion depth and PPH. The area of the largest T2-hypointense band in the placenta can predict poor outcomes of cesarean section.

Predicting adverse cardiac events in sarcoidosis: deep learning from automated characterization of regional myocardial remodeling

Recognizing early cardiac sarcoidosis (CS) imaging phenotypes can help identify opportunities for effective treatment before irreversible myocardial pathology occurs. We aimed to characterize regional CS myocardial remodeling features correlating with future adverse cardiac events by coupling automated image processing and data analysis on cardiac magnetic resonance (CMR) imaging datasets. A deep convolutional neural network (DCNN) was used to process a CMR database of a 10-year cohort of 117 consecutive biopsy-proven sarcoidosis patients. The maximum relevance - minimum redundancy method was used to select the best subset of all the features-24 (from manual processing) and 232 (from automated processing) left ventricular (LV) structural/functional features. Three machine learning (ML) algorithms, logistic regression (LogR), support vector machine (SVM) and multi-layer neural networks (MLP), were used to build classifiers to categorize endpoints. Over a median follow-up of 41.8 (inter-quartile range 20.4-60.5) months, 35 sarcoidosis patients experienced a total of 43 cardiac events. After manual processing, LV ejection fraction (LVEF), late gadolinium enhancement, abnormal segmental wall motion, LV mass (LVM), LVMI index (LVMI), septal wall thickness, lateral wall thickness, relative wall thickness, and wall thickness of 9 (out of 17) individual LV segments were significantly different between patients with and without endpoints. After automated processing, LVEF, end-diastolic volume, end-systolic volume, LV mass and wall thickness of 92 (out of 216) individual LV segments were significantly different between patients with and without endpoints. To achieve the best predictive performance, ML algorithms selected lateral wall thickness, abnormal segmental wall motion, septal wall thickness, and increased wall thickness of 3 individual segments after manual image processing, and selected end-diastolic volume and 7 individual segments after automated image processing. LogR, SVM and MLP based on automated image processing consistently showed better predictive accuracies than those based on manual image processing. Automated image processing with a DCNN improves data resolution and regional CS myocardial remodeling pattern recognition, suggesting that a framework coupling automated image processing with data analysis can help clinical risk stratification.

Emerging Mechanisms and Targeted Therapy of Ferroptosis in Neurological Diseases and Neuro-oncology

Ferroptosis is a novel type of cell death characterized by iron-dependent lipid peroxidation that involves a variety of biological processes, such as iron metabolism, lipid metabolism, and oxidative stress. A growing body of research suggests that ferroptosis is associated with cancer and neurodegenerative diseases, such as glioblastoma, Alzheimer's disease, Parkinson's disease, and stroke. Building on these findings, we can selectively induce ferroptosis for the treatment of certain cancers, or we can treat neurodegenerative diseases by inhibiting ferroptosis. This review summarizes the relevant advances in ferroptosis, the regulatory mechanisms of ferroptosis, the participation of ferroptosis in brain tumors and neurodegenerative diseases, and the corresponding drug therapies to provide new potential targets for its treatment.