MicroRNAs (miRNAs) have been reported to serve as potential biomarkers in bladder cancer and play important roles in cancer progression. This study aimed to investigate the biological role of ...miR-205-3p in bladder cancer. We showed that miR-205-3p was significantly down-regulated in bladder cancer tissues and cells. Moreover, overexpression of miR-205-3p inhibited bladder cancer progression in vitro. Then we confirmed that GLO1, a downstream target of miR-205-3p, mediated the effect of miR-205-3p on bladder cancer cells. In addition, we found that miR-205-3p inhibits P38/ERK activation through repressing GLO1. Eventually, we confirmed that miR-205-3p inhibits the occurrence and progress of bladder cancer by targeting GLO1 in vivo by nude mouse tumorigenesis and immunohistochemistry. In a word, miR-205-3p inhibits proliferation and metastasis of bladder cancer cells by activating the GLO1 mediated P38/ERK signaling pathway and that may be a potential therapeutic target for bladder cancer.
Objectives
We aimed to develop and validate a deep convolutional neural network (DCNN) model for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and its ...clinical outcomes using contrast-enhanced computed tomography (CECT) in a large population of candidates for surgery.
Methods
This retrospective study included 1116 patients with HCC who had undergone preoperative CECT and curative hepatectomy. Radiological (R), DCNN, and combined nomograms were constructed in a training cohort (
n
= 892) respectively based on clinicoradiological factors, DCNN probabilities, and all factors; the performance of each model was confirmed in a validation cohort (
n
= 244). Accuracy and the AUC to predict MVI were calculated. Disease-free survival (DFS) and overall survival (OS) after surgery were recorded.
Results
The proportion of MVI-positive patients was respectively 38.8% (346/892) and 35.7 % (87/244) in the training and validation cohorts. The AUCs of the R, DCNN, and combined nomograms were respectively 0.809, 0.929, and 0.940 in the training cohorts and 0.837, 0.865, and 0.897 in the validation cohort. The combined nomogram outperformed the R nomogram in the training (
p
< 0.001) and validation (
p
= 0.009) cohorts. There was a significant difference in DFS and OS between the R, DCNN, and combined nomogram-predicted groups with and without MVI (
p
< 0.001).
Conclusions
The combined nomogram based on preoperative CECT performs well for preoperative prediction of MVI and outcome.
Key Points
•
A combined nomogram based on clinical information, preoperative CECT, and DCNN can predict MVI and clinical outcomes of patients with HCC.
•
DCNN provides added diagnostic ability to predict MVI.
•
The AUCs of the combined nomogram are 0.940 and 0.897 in the training and validation cohorts, respectively.
Purpose: No previous researches have extracted radiomics features from susceptibility weighted imaging (SWI) for biomedical applications. This research aimed to explore the correlation between ...histopathology of hepatocellular carcinoma (HCC) and radiomics features extracted from SWI.Methods: A total of 53 patients were ultimately enrolled into this retrospective study with MR examinations undertaken at a 3T scanner. About 107 radiomics features were extracted from SWI images of each patient. Then, the Spearman correlation test was performed to evaluate the correlation between the SWI-derived radiomics features and histopathologic indexes including histopathologic grade, microvascular invasion (MVI) as well as the expression status of cytokeratin 7 (CK-7), cytokeratin 19 (CK-19) and Glypican-3 (GPC-3). With SWI-derived radiomics features utilized as independent variables, four logistic regression-based diagnostic models were established for diagnosing patients with positive CK-7, CK-19, GPC-3 and high histopathologic grade, respectively. Then, receiver operating characteristic analysis was performed to evaluate the diagnostic performance.Results: A total of 11, 32, 18 and one SWI-derived radiomics features were significantly correlated with histopathologic grade, the expression of CK-7, the expression of CK-19 and the expression of GPC-3 (P < 0.05), respectively. None of the SWI-derived radiomics features was correlated with MVI status. The areas under the curve were 0.905, 0.837, 0.800 and 0.760 for diagnosing patients with positive CK-19, positive CK-7, high histopathologic grade and positive GPC-3.Conclusion: Extracting the radiomics features from SWI images was feasible to evaluate multiple histopathologic indexes of HCC.
Few studies have focused on the prognosis of patients with hepatocellular carcinoma (HCC) of Barcelona Clinic Liver Cancer (BCLC) stage 0‒C in terms of early recurrence and 5-years overall survival ...(OS). We sought to develop nomograms for predicting 5-year OS and early recurrence after curative resection of HCC, based on a clinicopathological‒radiological model. We also investigated whether different treatment methods influenced the OS of patients with early recurrence.
Retrospective data, including clinical pathology, radiology, and follow-up data, were collected for 494 patients with HCC who underwent hepatectomy. Nomograms estimating OS and early recurrence were constructed using multivariate Cox regression analysis, based on the random survival forest (RSF) model. We evaluated the discrimination and calibration abilities of the nomograms using concordance indices (C-index), calibration curves, and Kaplan‒Meier curves. OS curves of different treatments for patients who had recurrence within 2 years after curative surgery were depicted and compared using the Kaplan-Meier method and the log-rank test.
Multivariate Cox regression revealed that BCLC stage, non-smooth margin, maximum tumor diameter, age, aspartate aminotransferase levels, microvascular invasion, and differentiation were prognostic factors for OS and were incorporated into the nomogram with good predictive performance in the training (C-index: 0.787) and testing cohorts (C-index: 0.711). A nomogram for recurrence-free survival was also developed based on four prognostic factors (BCLC stage, non-smooth margin, maximum tumor diameter, and microvascular invasion) with good predictive performance in the training (C-index: 0.717) and testing cohorts (C-index: 0.701). In comparison to the BCLC staging system, the C-index (training cohort: 0.787 vs. 0.678, 0.717 vs. 0.675; external cohort 2: 0.748 vs. 0.624, 0.729 vs. 0.587 respectively, for OS and RFS; external cohort1:0.716 vs. 0.627 for RFS, all p value<0.05), and model calibration curves all showed improved performance. Patients who underwent surgery after tumor recurrence had a higher reOS than those who underwent comprehensive treatments and supportive care.
The nomogram, based on clinical, pathological, and radiological factors, demonstrated good accuracy in estimating OS and recurrence, which can guide follow-up and treatment of individual patients. Reoperation may be the best option for patients with recurrence in good condition.
Background
The accurate identification of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) is of great clinical importance.
Purpose
To develop a radiomics nomogram based ...on susceptibility-weighted imaging (SWI) and T2-weighted imaging (T2WI) for predicting MVI in early-stage (Barcelona Clinic Liver Cancer stages 0 and A) HCC patients.
Materials and methods
A prospective cohort of 189 participants with HCC was included for model training and testing, and an additional 34 participants were enrolled for external validation. ITK-SNAP was used to manually segment the tumour, and PyRadiomics was used to extract radiomic features from the SWI and T2W images. Variance filtering, student’s
t
test, least absolute shrinkage and selection operator regression and random forest (RF) were applied to select meaningful features. Four machine learning classifiers, including
K
-nearest neighbour, RF, logistic regression and support vector machine-based models, were established. Independent clinical and radiological risk factors were also determined to establish a clinical model. The best radiomics and clinical models were further evaluated in the validation set. In addition, a nomogram was constructed from the radiomic model and independent clinical factors. Diagnostic efficacy was evaluated by receiver operating characteristic curve analysis with fivefold cross-validation.
Results
AFP levels greater than 400 ng/mL odds ratio (OR) 2.50; 95% confidence interval (CI) 1.239–5.047, tumour diameter greater than 5 cm (OR 2.39; 95% CI 1.178–4.839), and absence of pseudocapsule (OR 2.053; 95% CI 1.007–4.202) were found to be independent risk factors for MVI. The areas under the curve (AUCs) of the best radiomic model were 1.000 and 0.882 in the training and testing cohorts, respectively, while those of the clinical model were 0.688 and 0.6691. In the validation set, the radiomic model achieved better diagnostic performance (AUC = 0.888) than the clinical model (AUC = 0.602). The combination of clinical factors and the radiomic model yielded a nomogram with the best diagnostic performance (AUC = 0.948).
Conclusion
SWI and T2WI-derived radiomic features are valuable for noninvasively and accurately identifying MVI in early-stage HCC. Furthermore, the integration of radiomics and clinical factors yielded a predictive nomogram with satisfactory diagnostic performance and potential clinical benefits.
Patients with a deep burn injury are characterized by losing the function of perspiration and being unable to regenerate the sweat glands. Because of their easy accession, multipotency, and lower ...immunogenicity, bone marrow-derived mesenchymal stem cells (BM-MSCs) represent as an ideal biological source for cell therapy. The aim of this study was to identify whether targeting the promotor of ectodysplasin (EDA) by CRISPR/dCas9-effector (dCas9-E) could induce the BM-MSCs to differentiate into sweat gland-like cells (SGCs).
Activation of EDA transcription in BM-MSCs was attained by transfection of naive BM-MSCs with the lenti-CRISPR/dCas9-effector and single-guide RNAs (sgRNAs). The impact of dCas9-E BM-MSCs on the formation of SGCs and repair of burn injury was identified and evaluated both in vitro and in a mouse model.
After transfection with sgRNA-guided dCas9-E, the BM-MSCs acquired significantly higher transcription and expression of EDA by doxycycline (Dox) induction. Intriguingly, the specific markers (CEA, CK7, CK14, and CK19) of sweat glands were also positive in the transfected BM-MSCs, suggesting that EDA plays a critical role in promoting BM-MSC differentiation into sweat glands. Furthermore, when the dCas9-E BM-MSCs with Dox induction were implanted into a wound in a laboratory animal model, iodine-starch perspiration tests revealed that the treated paws were positive for perspiration, while the paws treated with saline showed a negative manifestation. For the regulatory mechanism, the expression of downstream genes of NF-κB (Shh and cyclin D1) was also enhanced accordingly.
These results suggest that EDA is a pivotal factor for sweat gland regeneration from BM-MSCs and may also offer a new approach for destroyed sweat glands and extensive deep burns.
Purpose
Restriction spectrum imaging (RSI) is a novel diffusion MRI model that separates water diffusion into several microscopic compartments. The restricted compartment correlating to the tumor ...cellularity is expected to be a potential indicator of rectal cancer aggressiveness. Our aim was to assess the ability of RSI model for rectal tumor grading.
Methods
Fifty-eight patients with different rectal cancer grading confirmed by biopsy were involved in this study. DWI acquisitions were performed using single-shot echo-planar imaging (SS-EPI) with multi-
b
-values at 3 T. We applied a three-compartment RSI model, along with ADC model and diffusion kurtosis imaging (DKI) model, to DWI images of 58 patients. ROC and AUC were used to compare the performance of the three models in differentiating the low grade (G1 + G2) and high grade (G3). Mean ± standard deviation, ANOVA, ROC analysis, and correlation analysis were used in this study.
Results
The volume fraction of restricted compartment
C
1
from RSI was significantly correlated with grades (
r
= 0.403,
P
= 0.002). It showed significant difference between G1 and G3 (
P
= 0.008) and between G2 and G3 (
P
= 0.01). As for the low-grade and high-grade discrimination, significant difference was found in
C
1
(
P
< 0.001). The AUC of
C
1
for differentiation between low-grade and high-grade groups was 0.753 with a sensitivity of 72.0% and a specificity of 70.0%.
Conclusion
The three-compartment RSI model was able to discriminate the rectal cancer of low and high grades. The results outperform the traditional ADC model and DKI model in rectal cancer grading.
Graphical abstract
Gastric cancer (GC) is the fifth leading cause of cancer-related death worldwide and is accompanied by low diagnosis and survival rates. The molecular mechanism of GC must be elucidated to improve ...treatment strategies. Recent research has shown that the expression of myelin and lymphocyte (MAL) protein is reduced in a variety of adenocarcinomas and has the function of suppressing tumor growth. However, the mechanism by which MAL regulates the epithelial-mesenchymal transition (EMT) in GC remains unclear. Here, we showed that MAL expression was downregulated in specimens from patients with GC and was negatively correlated with the clinical stage. Gain- and loss-of function assays showed that interference with MAL significantly increased tumor cell proliferation, metastasis, invasion and the EMT. Overexpression of MAL significantly inhibited the malignant behavior of GC cells. Moreover, MAL suppressed the malignant behavior of GC cells by inhibiting STAT3 phosphorylation in vitro and in vivo. Our data indicate that MAL suppresses the malignant behavior of GC cells via the STAT3/EMT axis. This study also provides insights into the pathophysiological process of GC and a reference for diagnosis and treatment.
Restoration of sweat glands (SwGs) represents a great issue in patients with extensive skin defects. Recent methods combining organoid technology with cell fate reprogramming hold promise for ...developing new regenerative methods for SwG regeneration. Here, a practical strategy for engineering functional human SwGs in vitro and in vivo is provided. First, by forced expression of the ectodysplasin‐A in human epidermal keratinocytes (HEKs) combined with specific SwG culture medium, HEKs are efficiently converted into SwG cells (iSwGCs). The iSwGCs show typical morphology, gene expression pattern, and functions resembling human primary SwG cells. Second, by culturing the iSwGCs in a special 3D culturing system, SwG organoids (iSwGOs) that exhibit structural and biological features characteristic of native SwGs are obtained. Finally, these iSwGOs are successfully transplanted into a mouse skin damage model and they develop into fully functioning SwGs in vivo. Regeneration of functional SwG organoids from reprogrammed HEKs highlights the great translational potential for personalized SwG regeneration in patients with large skin defects.
An engineering strategy is shown to generate organoids from reprogrammed human epidermal keratinocytes (HEKs) for the regeneration of human sweat glands (SwGs). The technology enables efficient conversion of HEKs into SwG cell lineages and allows a large‐scale production of tissue‐relevant organoids for personalized SwG regeneration in patients with large skin defects.
Abstract
Background
The stromal antigen 3 (STAG3) gene encodes an adhesion complex subunit that can regulate sister chromatid cohesion during cell division. Chromosome instability caused by STAG3 ...gene mutation may potentially promote tumor progression, but the effect of STAG3 on hepatocellular carcinoma (HCC) and the related molecular mechanism are not reported in the literature. The mechanism of the occurrence and development of HCC is not adequately understood. Therefore, the biological role of STAG3 in HCC remains to be studied, and whether STAG3 might be a sensitive therapeutic target in HCC remains to be determined.
Methods
The expression and clinical significance of STAG3 in HCC tissues and cell lines were determined by RT–qPCR and immunohistochemistry analyses. The biological functions of STAG3 in HCC were determined through in vitro and in vivo cell function tests. The molecular mechanism of STAG3 in HCC cells was then investigated by western blot assay.
Results
The mRNA expression of STAG3 was lower in most HCC cells than in normal cells. Subsequently, an immunohistochemical analysis of STAG3 was performed with 126 samples, and lower STAG3 expression was associated with worse overall survival in HCC patients. Moreover, cytofunctional tests revealed that the lentivirus-mediated overexpression of STAG3 in HCC cells inhibited cell proliferation, migration, and invasion; promoted apoptosis; induced G1/S phase arrest in vitro; and inhibited tumor growth in vivo. Furthermore, studies of the molecular mechanism suggested that the overexpression of STAG3 increased Smad3 expression and decreased CDK4, CDK6, cyclin D1, CXCR4 and RhoA expression.
Conclusion
STAG3 exhibits anticancer effects against HCC, and these effects involve the Smad3-CDK4/CDK6-cyclin D1 and CXCR4/RhoA pathways. STAG3 is a tumor-suppressor gene that may serve as a potential target for molecular therapy, which provides a new idea for the treatment of HCC.
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