Peiwen Zhang,1,* Yahong Xu,1,* Yimeng Zhang,1 Jing Yang,2 Shuyun Liu,1 Yujia Yuan,1 Younan Chen,1 Chunhong Li,3 Yanrong Lu,1 Hui Wang,4 Jingping Liu11Department of General Surgery and NHC Key Laboratory of Transplant Engineering and Immunology, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China; 2Laboratory of Omics Technology and Bioinformatics, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China; 3Department of Pharmaceutical Sciences, School of Pharmacy, Southwest Medical University, Luzhou, 646000, People’s Republic of China; 4Department of Periodontics, State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hui Wang, Department of Periodontics, State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, People’s Republic of China, Email hwang02@scu.edu.cn Jingping Liu, Department of General Surgery, NHC Key Laboratory of Transplant Engineering and Immunology, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, No. 2222 Xinchuan Road, Chengdu, 610041, People’s Republic of China, Tel +86-28-85164029, Fax +86-28-85164030, Email liujingping@scu.edu.cnIntroduction: Severe skeletal muscle injury is a serious disease worldwide, but current clinical treatments are unsatisfactory because of the limited ability of these treatments to repair muscle; thus, novel therapies that can efficiently promote muscle regeneration are desirable.Methods: Nanoengineered GATA3+ macrophages (nanoGM&phis;s) were constructed by loading IL-33-induced GATA3+ M&phis;s with PLGA nanoparticles encapsulating the efferocytosis agonist (aEffero) VU534 (a small molecule that enhances efferocytosis by activating the N-acyl phosphatidylethanolamine phospholipase D (NAPE-PLD) pathway), and their ability to reestablish the pro-regenerative muscle stem cell (MuSC) niche was evaluated both in vitro and in vivo.Results: Our data revealed that dysregulation of GATA3⁺ macrophage subsets and the accumulation of harmful dead cells compromised the MuSC niche after severe skeletal muscle injury. In vitro, GATA3+ M&phis;s promoted MuSC activation (eg, proliferation, migration, and differentiation) via metabolic regulation. The average diameter of the VU534-loaded PLGA nanoparticles was ~200 nm, with an encapsulation efficiency of ~94.7% and a drug-loading capacity of ~7.3%. Moreover, nanoGM&phis;s secrete EVs that regulate the immune microenvironment locally. In vivo, adoptive nanoGM&phis; transplantation effectively promoted MuSC activation and the clearance of dead cells and debris, thereby enhancing MuSC niche restoration and skeletal muscle regeneration in two models of acute chemically induced muscle injury. On day 7, the proportions of centrally nucleated myofibers in the nanoGM&phis;-treated muscles were 1.52 and 1.38 times greater than those in the untreated controls in the CTX and BaCl2 models, respectively. On day 21, compared with the control treatment, the nanoGM&phis; treatment increased the mean myofiber CSA by 29.38% and 17.42% in the CTX and BaCl2 models, respectively.Conclusion: This study highlights that the tailored design of engineered immune cell therapy is a promising strategy for promoting MuSC niche restoration and regeneration following acute chemically induced skeletal muscle injury.Keywords: skeletal muscle injury, macrophage, regenerative medicine, efferocytosis, drug delivery

BACKGROUND:Hypertension represents one of the most prevalent risk factors associated with ischemic stroke (IS). METHODS:A total of 102 essential hypertension (EH) patients without IS and 155 EH patients with IS were enrolled. Logistic regression analysis was performed to identify independent risk factors influencing IS. Kaplan-Meier survival analysis was used to evaluate the association between miR-127-3p expression and no recurrence in IS patients. Cox regression was applied to determine independent predictors of recurrence in IS patients. The BV-2 microglia cell line was utilized to construct an oxygen-glucose deprivation/reoxygenation (OGD/R) model, simulating ischemic injury in vitro. Flow cytometry was employed to measure cell apoptosis, while enzyme-linked immunosorbent assay was used to quantify inflammatory cytokine levels. Biochemical assay kits were applied to detect the levels of superoxide dismutase, reactive oxygen species, and malondialdehyde. Dual-luciferase reporter assays were conducted to confirm the targeting relationship. RESULTS:miR-127-3p was significantly upregulated in EH+IS patients and demonstrated high diagnostic value. Patients with high miR-127-3p expression exhibited a significantly increased risk of recurrence. Mechanistically, miR-127-3p played a critical role in promoting inflammation, oxidative stress, and apoptosis in OGD/R-induced neuronal injury. Akt3 was identified as a direct functional target of miR-127-3p. Suppression of miR-127-3p relieved its inhibitory effect on Akt3, thereby activating the neuroprotective function of Akt3. When Akt3 was knocked down, the protective effects mediated by the miR-127-3p inhibitor were reversed. CONCLUSIONS:The miR-127-3p/Akt3 axis played a critical role in the regulatory mechanisms associated with EH complicated by IS.

Individuals with hypertension carry a high risk of stroke, which endangers human health. The study systematically elucidated the dynamic expression, functional effects, and molecular mechanisms of the circular RNA LPAR3 in ischemic stroke (IS). 300 essential-hypertension (EH) patients were enrolled, comprising 165 cases diagnosed with IS. mRNA abundance was quantified via RT-qPCR. C57BL/6 mice treated with MACO and Neuro-2a cells receiving oxygen-glucose deprivation/reoxygenation (OGD/R) were applied for functional experiments. Neurological deficits and infarct volume of mice were evaluated. Besides, key cellular behaviors encompassing proliferative capacity, apoptotic rate, and inflammatory response were monitored. The putative binding event was interrogated through luciferase reporter and RIP coupled to qPCR assays. A diminished level of circLPAR3 was evidenced in the plasma of IS patients, which can distinguish IS cases from EH and remains an independent predictor of patients' poor prognosis. In vivo, overexpression of circLPAR3 alleviated MACO-mediated neurological deficit and cerebral infarction. In vitro, OGD/R triggered the surge in cell apoptosis and pro-inflammatory cytokine release, but it was attenuated by circLPAR3 upregulation. Mechanistically, the neuro-rescue driven by circLPAR3 was offset by miR-634, whose plasma expression was negatively correlated with circLPAR3. KLB expression was significantly downregulated in cellular models and co-regulated by circLPAR3 and miR-634. circLPAR3/miR-634 modulates the pathological progression of IS by directly regulating neuronal apoptosis and orchestrating inflammatory responses, and KLB may serve as a key downstream target mediating the biological functions.

The optimal adjuvant management of pathologically node-positive (pN1) prostate cancer following radical prostatectomy remains controversial, with conflicting retrospective evidence regarding the survival benefit of postoperative radiotherapy. This study aimed to evaluate the association between postoperative radiotherapy and long-term cancer-specific survival (CSS) and overall survival (OS) in a large population-based cohort. Patients with pN1 prostate adenocarcinoma who underwent radical prostatectomy between 2010 and 2022 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were stratified into radical prostatectomy alone (RP-only) and radical prostatectomy plus postoperative radiotherapy (RP + RT) groups. Propensity score matching (1:1) was performed to balance baseline covariates. Multivariable Cox regression, propensity score–matched analyses, and inverse probability of treatment weighting (IPTW) were used to estimate hazard ratios (HRs) for CSS and OS. Competing risk and subgroup analyses were conducted as sensitivity analyses. A total of 7,250 eligible patients were included, comprising 5,006 in the RP-only group and 2,244 in the RP + RT group. Propensity score matching yielded 1,702 well-balanced pairs. In the matched cohort, postoperative radiotherapy was significantly associated with improved CSS (HR = 0.786, 95

Purpose:The aim of this study was to evaluate the value of different multiparametric MRI-based radiomics models in differentiating stage IA endometrial cancer (EC) from benign endometrial lesions. Methods:This retrospective study included 787 patients with stage IA endometrial cancer (EC) or benign endometrial lesions from four centers. Tumor regions of interest (ROIs) were manually delineated on MRI. Employing Python, the following peritumoral ROIs were automatically generated: 3-mm dilated and eroded peritumoral loops (LDE3), 3-mm eroded peritumoral loops (LE3), and intratumoral regions merged with 3-mm dilated peritumoral loops (RD3) Habitat clustering was performed using K-means and Gaussian Mixture Model (GMM) algorithms. Logistic regression was utilized to identify independent predictors and construct habitat-only and combined (clinical + habitat) models. Performance was evaluated using the area under the curve (AUC). Results:Age (P = 0.002) and vaginal bleeding (P < 0.001) were identified as independent clinical predictors of stage IA EC. Habitat-based models outperformed the clinical model in some external validation cohorts. Peritumoral features, particularly K-means_RD3, exhibited favorable robustness, achieving an average external validation AUC of 0.740. The integration of habitat features with clinical predictors yielded synergistic improvements, with the Clinical+K-means_RD3 model achieving the highest diagnostic performance (peak AUC: 0.921). Notably, this combined framework effectively mitigated the limitations of clinical factors in challenging subsets, elevating the AUC from 0.644 to 0.850 in validation group D. K-means demonstrated superior robustness and stability compared to GMM. Conclusion:Intratumoral and peritumoral habitat imaging based on multiparametric MRI can non-invasively reveal the microstructural characteristics of stage IA EC. Integrating clinical predictors with habitat models showed good diagnostic performance. The peritumoral habitat model exceeded the intratumoral habitat model.

RATIONALE AND OBJECTIVES:To develop and validate a foundation model (FM)-empowered multimodal framework to predict platinum resistance in patients with high-grade serous ovarian cancer (HGSOC). MATERIALS AND METHODS:This multicenter retrospective cohort study included 744 HGSOC patients who underwent primary debulking surgery across four centers. Perioperative multimodal data were collected, including clinical variables, preoperative pelvic magnetic resonance imaging (MRI), and postoperative hematoxylin and eosin (H&E)-stained whole slide images (WSIs). Pretrained radiology and pathology FMs were used as frozen feature extractors, and attention-based aggregation was applied to summarize variable-length MRI slices and WSI tiles. A cross-modal fusion module integrated modalities and supported missing-modality inference. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and compared with late-fusion (LF) baselines. RESULTS:In the internal validation cohort, unimodal and multimodal FM variants achieved AUCs ranging from 0.708 to 0.780, and in external test cohorts A, B, and C achieved AUCs ranging from 0.653 to 0.790. The trimodal FM (clinical+MRI+WSI) achieved the highest AUC in all cohorts (internal validation: 0.780; external cohorts A, B, and C: 0.779, 0.781, and 0.790, respectively), outperforming the trimodal LF model (internal validation: 0.753; external cohorts A, B, and C: 0.729, 0.715, and 0.730, respectively). CONCLUSION:A FM-empowered multimodal model integrating clinical, MRI, and pathological data was constructed to predict platinum resistance in HGSOC, demonstrating superior and stable performance across centers.

The development of innovative therapeutic strategies that combine multiple treatment modalities is essential for effective cancer therapy. In this study, we engineered berberine (BER)-loaded mesoporous polydopamine (MPDA) nanoparticles (BER-MPDA) to enhance anti-tumor efficacy through synergistic chemotherapy and photothermal therapy (PTT). The mesoporous structure of MPDA allowed for a high loading capacity of BER, a natural isoquinoline alkaloid with known anticancer properties. Upon near-infrared laser irradiation, BER-MPDA exhibited marked photothermal conversion efficiency, leading to effective tumor cell ablation. Both in vitro and in vivo experiments indicated that the combined treatment of BER-MPDA with near-infrared laser irradiation resulted in superior tumor inhibition compared to monotherapy. The synergistic effect was attributed to the enhanced cellular uptake and the simultaneous induction of chemo- and photothermal cytotoxicity. Our findings suggest that BER-MPDA represents a promising platform for multimodal cancer therapy, offering a potent approach to overcoming the limitations of conventional chemotherapy and PTT.

DHX36 is an ATP-dependent DNA/RNA helicase that unwinds the guanine-quadruplexes (G4s) of DNA or RNA and regulates their metabolism for key biological functions. Breast cancer is a malignant tumor and effective targeted therapy drugs are limited, even though chemotherapy is generally used. In this study, we found that overexpression of DHX36 promotes breast cancer cell growth, migration, and invasion in vitro, while knocking down or knocking out reversed in vitro and in vivo. Moreover, DHX36 was highly expressed in most clinical breast tumor tissues compared with the matched healthy tissues. Accordingly, higher DHX36 expression correlated with poor recurrence-free survival (RFS) in the patients of breast cancer. These results substantiate that DHX36 might be a diagnostic and prognostic biomarker and is a proto-oncogene that promotes the growth and metastasis of breast cancer. Thus, targeting DHX36-associated G4s in genes, particularly in proto-oncogenes, might be a novel anticancer strategy.

High-grade serous ovarian cancer (HGSOC) presents challenges in prognostic prediction. This study aimed to develop a universal foundation model-driven multimodal model (FoMu model) to assess the prognosis of HGSOC patients. We conducted a retrospective cohort study involving 712 eligible patients across four centers, collecting clinical, MRI, and hematoxylin and eosin (H&E)-stained whole slide images (WSIs) data. Pre-trained radiological and pathological foundation models were employed for feature precoding. Subsequently, we introduced unimodal and cross-modal adaptive aggregation networks to comprehensively model the features derived from each modality. Our findings revealed that both unimodal and cross-modal FoMu models exhibited superior and stable predictive capabilities for overall survival (OS) and progression-free survival (PFS). In summary, our study successfully developed a FoMu model that effectively integrates multimodal data to assess the prognoses of HGSOC patients, highlighting its potential for improving individualized patient management and clinical decision-making in future applications.

PurposeTo evaluate the effectiveness of magnetic resonance imaging (MRI)-based intratumoral and peritumoral radiomics models for predicting deep myometrial invasion (DMI) of early-stage endometrioid adenocarcinoma (EAC).MethodsThe data of 459 EAC patients from three centers were retrospectively collected. Radiomics features were extracted separately from the intratumoral and peritumoral regions expanded by 0 mm, 5 mm, and 10 mm on unimodal and multimodal MRI. Then, various radiomics models were developed and validated, and the optimal model was confirmed. Integrated models were constructed by ensemble and stacking algorithms based on the above radiomics models. The models’ performance was evaluated using the area under the curve (AUC).ResultsThe multimodal MRI-based radiomics model, which included both intratumoral and peritumoral regions expanded by 5 mm, was the optimal radiomics model, with an AUC of 0.74 in the validation group. When the same integrated algorithm was utilized, the integrated models with 5-mm expansion presented higher AUCs than those with 0-mm and 10-mm expansion in the validation group. The performance of the stacking model and ensemble model with 5-mm expansion was similar, and their AUCs were 0.74 and 0.75, respectively.ConclusionThe multimodal radiomics model from the intratumoral and peritumoral regions expanded by 5 mm has the potential to improve the performance for detecting DMI of early-stage EAC. The integrated models are of little value in increasing the prediction.

Hypertension is a common risk factors for ischemic stroke (IS), with the widely involvement of long non-coding RNAs (lncRNAs). The expression pattern and clinical significance of lncRNA PSMB8-AS1 was examined in essential hypertension (EH) patients with or without IS, as well as its role and mechanism in IS-induced neuron cell injury. Serum PSMB8-AS1 levels in 260 EH cases without IS and 280 participants with IS were detected via reverse transcription - quantitative polymerase chain reaction (RT-qPCR). The outcome during 12-month follow-up period was recorded. Receiver operating characteristic (ROC) curve and Kaplan - Meier (K-M) plot were drawn to evaluate diagnostic and prognostic values. HT22 cells were exposed to oxygen-glucose deprivation/reoxygenation (OGD/R) condition for cell function experiments. The cell viability, apoptosis, and inflammatory response were detected. Elevated expression of PSMB8-AS1 can differentiate IS from EH patients, and was independently related to the poor functional prognosis. Patients with high PSMB8-AS1 expression were likely to relapse during the 12-month follow-up period. In vitro, PSMB8-AS1 knockdown attenuated OGD/R-induced neuron cell apoptosis and inflammatory response, which was returned by microRNA-22-3p downregulation. PI3K-Akt signaling was of significance during the progress based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. PSMB8-AS1 acts as a novel biomarker for the diagnosis of IS in EH patients. Elevated PSMB8-AS1 is associated with worse neurological outcomes and higher recurrence rates of IS patients. LncRNA PSMB8-AS1 knockdown might have a promising role in attenuating OGD/R-induced neuron cell injury, that might be related to miR-22-3p.

BackgroundColon cancer is a prevalent malignancy that significantly threatens human health. In recent years, mRNA cancer vaccines have demonstrated considerable potential and distinct advantages in colon cancer treatment. Thus, This study identifies CUL7, ENO2, and MPP2 as potential antigens for colon cancer mRNA vaccines. Through multi-omics analysis, we classify COAD into three immune subtypes (C1-C3) with distinct molecular and clinical features.MethodsData from TCGA and GEO databases were analyzed using bioinformatics tools. Prognostic indices were calculated with GEPIA2, and TIMER assessed antigen-presenting cell infiltration. Survival analysis was performed using Kaplan-Meier curves and Cox proportional hazards models. Immune subtypes were classified via non-negative matrix factorization (NMF) clustering, with k=3 determined by cophenetic correlation (0.92) and silhouette width (average = 0.85). Drug sensitivity, immune cell infiltration, and gene set variation were analyzed using R packages such as “pRRophetic,” CIBERSORT, and GSVA. Functional enrichment analysis was performed with GO, KEGG, and GSEA. Experimental validation included immunohistochemistry and RT-PCR to confirm gene expression.ResultsAnalysis of TCGA-COAD data revealed copy number variants in 16,354 genes, with CUL7, ENO2, and MPP2 showing significant antigen-presenting cell infiltration and associations with overall survival (OS) and relapse-free survival (RFS). Based on molecular mechanisms, cellular features, and clinical characteristics, colon cancer was categorized into three immune subtypes (C1, C2, and C3) distinct from Thorsson’s pan-cancer subtypes (C1-C6) in pathway enrichment, with the C2 subtype exhibited significantly longer overall survival (OS) than C1 and C3 (median OS: C2 = 68 months vs. C1 = 42 months, C3 = 37 months; log-rank P < 0.001). The distribution of these immune subtypes showed disparities in immune patterns, and a correlation between key components and immune cells was observed. Prognostic correlation analysis indicated that the gray and turquoise modules were closely linked to colorectal cancer prognosis. Additionally, RT-PCR confirmed the association of CUL7, ENO2, and MPP2 expression levels with colon cancer.ConclusionsCUL7, ENO2, and MPP2 were identified as potential antigens for colon cancer mRNA vaccines, with MPP2 showing particular immunological relevance. This study provides a foundation for mRNA vaccine development and patient stratification for vaccination in colon cancer.

Abstract Background: Osteosarcoma can affect the function of the lower limbs when found in the distal femur and proximal tibia. Following total knee arthroplasty, patient may exhibit instability, limited range of motion, difficulty walking, reduced ability to bear weight, joint pain, joint dysfunction, and a decrease in daily life performance. This study aims to evaluate the efficacy of a computer vision-based intelligent rehabilitation program to manage patients post-operatively. Method: 96 patients with osteosarcoma requiring knee arthroplasty were recruited. Patients were randomized into either the intelligent rehabilitation group (IRG) or natural rehabilitation group (NRG) with an equal distribution. The main endpoints included the range of motion (ROM) of the knee joint and Knee injury and Osteoarthritis Outcome Score (KOOS). Secondary outcomes include 6-minute walk test (6MWT), Timed Up and Go test (TUG), the Toronto Extremity Salvage Score (TESS), SF-36 Scale Role Limitations due to Emotional Problems (RE), and Mental Health (MH) at three months and six months post-operatively. Results: In a 6-month study periodl, participants successfully concluded the trial.The IRG showed significant improvement in ROM (p=0.015), KOOS, 6-minute walk test (6MWT) (p=0.037), Timed Up and Go (TUG) test (p=0.041), Treatment Effectiveness and Satisfaction Survey (TESS) score (p=0.039), SF-36 Role Limitations due to Emotional Problems (RE) score (p<0.001) , and SF-36 Mental Health (MH) score (p<0.001) . Conclusion: This study provided evidence that the participants in the IRG showed considerable enhancements in joint function relative to the NRG. These findings confirmed the effectiveness of the computer vision-based intelligent rehabilitation in the post-surgery recovery of knee arthroplasty in osteosarcoma.

Bone is one of the most frequent sites for metastasis in breast cancer patients. Bone metastasis significantly reduces the survival time and the life quality of breast cancer patients. Germacrone (GM) can serve humans as an anti-cancer and anti-inflammation agent, but its effect on breast cancer-induced osteolysis remains unclear. This study aims to investigate the functions and mechanisms of GM in alleviating breast cancer-induced osteolysis. The effects of GM on osteoclast differentiation, bone resorption, F-actin ring formation, and gene expression were examined in vitro. RNA-sequencing and Western Blot were conducted to explore the regulatory mechanisms of GM on osteoclastogenesis. The effects of GM on breast cancer-induced osteoclastogenesis, and breast cancer cell malignant behaviors were also evaluated. The in vivo efficacy of GM in the ovariectomy model and breast cancer bone metastasis model with micro-CT and histomorphometry. GM inhibited osteoclastogenesis, bone resorption and F-actin ring formation in vitro. Meanwhile, GM inhibited the expression of osteoclast-related genes. RNA-seq analysis and Western Blot confirmed that GM inhibited osteoclastogenesis via inhibition of MAPK/NF-κB signaling pathways. The in vivo mouse osteoporosis model further confirmed that GM inhibited osteolysis. In addition, GM suppressed the capability of proliferation, migration, and invasion and promoted the apoptosis of MDA-MB-231 cells. Furthermore, GM could inhibit MDA-MB-231 cell-induced osteoclastogenesis in vitro and alleviate breast cancer-associated osteolysis in vivo human MDA-MB-231 breast cancer bone metastasis-bearing mouse models. Our findings identify that GM can be a promising therapeutic agent for patients with breast cancer osteolytic bone metastasis.

Purpose The aim of this study was to evaluate the diagnostic value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived kinetic parameters with high spatiotemporal resolution in discriminating malignant from normal prostate tissues. Methods Fifty patients with suspicious of malignant diseases in prostate were included in this study. Regions of interest (ROI) were manually delineated by experienced radiologists. Voxel-wise kinetic parameters were produced with the following tracer kinetic models (TKMs): Tofts model, extended Tofts model (ETM), Brix's conventional two-compartment model (Brix), adiabatic tissue homogeneity model (ATH), and distributed parameter model (DP). The initial area under the signal-time curve (IAUC) with an uptake integral approach was also included. Mann-Whitney U test and receiver operating characteristic (ROC) curves were used to evaluate the capability of distinguishing tumor lesions from normal tissues. A p-value of 0.05 or less is considered statistically significant. ROI based parameters correlation analysis between DP and ETM were performed. Results 624 lesions and 269 normal tissue ROIs were obtained. Thirty parameters were derived from the six kinetic models. Except for PS from Brix, statistically significant differences between lesions and normal tissues (P<0.05) were observed in other parameters.Ve from DP, ATH and Brix and PS from ATH have AUC values less than 0.6 in the ROC analysis. MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, IAUC parameters and F from Brix have AUC values larger than 0.8. Ve and Vp from DP and ETM are correlated (r> 0.65). The correlation coefficient between Ktrans from ETM and PS from DP is 0.751. Conclusion MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, F from Brix and IAUC parameters can be used to differentiate malignant lesions from normal tissues in the prostate.

Rationale and Objectives: This study aims to explore the feasibility of MRI-based habitat radiomics for predicting response of platinum-based chemotherapy in patients with high-grade serous ovarian carcinoma (HGSOC), and compared to conventional radiomics deep learning models. Materials and Methods: A retrospective study was conducted on HGSOC patients from three hospitals. K-means algorithm was used perform clustering on T2-weighted images (T2WI), contrast-enhanced T1-weighted images (CE-T1WI), and apparent diffusion coefficient (ADC) maps. After feature extraction and selection, the radiomics model, habitat model, and deep learning model were constructed respectively to identify platinum-resistant and platinum-sensitive patients. A nomogram was developed by integrating the optimal model and clinical independent predictors. The model performance and benefit was assessed using the area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI). Results: A total of 394 eligible patients were incorporated. Three habitats were clustered, a significant difference in habitat 2 (weak enhancement, high ADC values, and moderate T2WI signal) was found between the platinum-resistant and platinum-sensitive groups 0.05). Compared to the radiomics model (0.640) and deep learning model (0.603), the habitat model had a higher AUC (0.710). The nomogram, combining habitat signatures with a clinical independent predictor (neoadjuvant chemotherapy), yielded a highest AUC (0.721) among four models, with positive NRI and IDI. Conclusion: MRI-based habitat radiomics had the potential to predict response of platinum-based chemotherapy in patients with HGSOC. nomogram combining with habitat signature had a best performance and good model gains for identifying platinum-resistant patients.

Background We aimed to develop a predictive model constituted with the ALBI grade, the ascites, and tumor burden related parameters in patients with BCLC stage B HCC. Methods Patients diagnosed as the BCLC stage B HCC were collected from a retrospective database. Construction and validation of the predictive model were performed based on multivariate Cox regression analysis. Predictive accuracy, discrimination (c-index), and fitness performance (calibration curve) of the model were compared with the other eight models. The decision curve analysis (DCA) was used to evaluate the clinical utility. Results A total of 1773 patients diagnosed as BCLC stage B HCC between 2007 and 2016 were included in the present study. The ALBI-AS grade, the AFP level, and the 8-and-14 grade were used for the development of a prognostic prediction model after multivariate analysis. The area under the receiver operator characteristic curve (AUROC) for overall survival at 1, 2, and 3 years predicted by the present model were 0.73, 0.69, and 0.67 in the training cohort. The concordance index (c-index) and the Aiken information criterion (AIC) were 0.68 and 6216.3, respectively. In the internal and external validation cohorts, the present model still revealed excellent predictive accuracy, discrimination, and fitness performance. Then the ALBI-AS based model was evaluated to be superior to other prognostic models with the highest AUROC, c-index, and lowest AIC values. Moreover, DCA also demonstrated that the present model was clinically beneficial. Conclusion The ALBI-AS grade is a novel predictor of survival for patients with BCLC stage B HCC.

MicroRNAs (miRNAs) are widely present in many organisms and regulate the expression of genes in various biological processes such as cell differentiation, metabolism, and development. Numerous studies have shown that miRNAs are abnormally expressed in tumor tissues and are closely associated with tumorigenesis. MiRNA-based cancer gene therapy has consistently shown promising anti-tumor effects and is recognized as a new field in cancer treatment. So far, some clinical trials involving the treatment of malignancies have been carried out; however, studies of miRNA-based cancer gene therapy are still proceeding slowly. Therefore, furthering our understanding of the regulatory mechanisms of miRNA can bring substantial benefits to the development of miRNA-based gene therapy or other combination therapies and the clinical outcome of patients with cancer. Recent studies have revealed that the aberrant expression of miRNA in tumors is associated with promoter sequence mutation, epigenetic alteration, aberrant RNA modification, etc., showing the complexity of aberrant expression mechanisms of miRNA in tumors. In this paper, we systematically summarized the regulation mechanisms of miRNA expression in tumors, with the aim of providing assistance in the subsequent elucidation of the role of miRNA in tumorigenesis and the development of new strategies for tumor prevention and treatment.

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