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Bone metastasis is associated with cancer‐related death in patients with prostate cancer (PCa). Long noncoding RNAs (lncRNAs) play critical roles in tumor progression of PCa. Nevertheless, the biological function of lncRNAs in PCa bone metastasis remains unclear. PCAT7 was identified as a bone metastasis‐related lncRNA via analyzing TCGA dataset. Meanwhile, PCAT7 was found to be elevated in primary PCa tissues with bone metastasis and associated with bone metastasis status and poor prognosis of patients with PCa. Functionally, our results reveal that PCAT7 overexpression promotes PCa bone metastasis in vivo, as well as migration, invasion, and EMT of PCa cells in vitro; on the contrary, PCAT7 knockdown has an inverse effect. Mechanistically, PCAT7 activates TGF‐β/SMAD signaling by upregulating TGFBR1 expression via sponging miR‐324‐5p. In turn, TGF‐β signaling forms a positive feedback loop with PCAT7 via SMAD3/SP1 complex‐induced PCAT7 upregulation. Finally, the clinical positive correlation between PCAT7 and TGFBR1 and TGF‐β signaling activity, and the negative association with miR‐324‐5p are further demonstrated in PCa tissues and clinical primary PCa cells. This study reveals a novel mechanism that is responsible for the constitutive activation of TGF‐β signaling in PCa bone metastasis, implying that PCAT7 can act as a potential therapeutic target against bone metastasis of PCa via disrupting the constitutive active loop between PCAT7 and TGF‐β signaling.

Cervical spondylotic myelopathy (CSM) is a degenerative condition of the spine that caused by static and dynamic compression of the spinal cord. However, the mechanisms of motor and somatosensory conduction, as well as pathophysiological changes at dynamic neck positions remain unclear. This study aims to investigate the interplay between neurophysiological and hemodynamic responses at dynamic neck positions in the CSM condition, and the pathological basis behind. We first demonstrated that CSM patients had more severe dynamic motor evoked potentials (DMEPs) deteriorations upon neck flexion than upon extension, while their dynamic somatosensory evoked potentials (DSSEPs) deteriorated to a similar degree upon extension and flexion. We therefore generated a CSM rat model which developed similar neurophysiological characteristics within a 4-week compression period. At 4 weeks-post-injury, these rats presented decreased spinal cord blood flow (SCBF) and oxygen saturation (SO2) at the compression site, especially upon cervical flexion. The dynamic change of DMEPs was significantly correlated with the change in SCBF from neutral to flexion, suggesting they were more sensitive to ischemia compared to DSSEPs. We further demonstrated significant vascular redistribution in the spinal cord parenchyma, caused by angiogenesis mainly concentrated in the anterior part of the compressed site. In addition, the comparative ratio of vascular densities at the anterior and posterior parts of the cord was significantly correlated with the perfusion decrease at neck flexion. This exploratory study revealed that the motor and somatosensory conductive functions of the cervical cord changed differently at dynamic neck positions in CSM conditions. Compared with somatosensory conduction, the motor conductive function of the cervical cord suffered more severe deteriorations upon cervical flexion, which could partly be attributed to its higher susceptibility to spinal cord ischemia. The uneven angiogenesis and vascular distribution in the spinal cord parenchyma might underlie the transient ischemia of the cord at flexion.

Fibrostenosis is a serious complication of Crohn’s disease (CD), affecting approximately one-half of all patients. Surgical resection is the typical clinical end due to ineffective antifibrotic therapy mainly through anti-inflammatory treatment and fibrosis can be reverted only at early stages. Mover, human fibrotic disorders is known to be associated with aging process. Thus, accurate monitoring of the progression of fibrosis is crucial for CD management as well as can be benefit to aging related fibrosis. The excessive deposition of type I collagen (ColI) is the core point in major complications of fibrosis, including that in patients with CD and aging related fibrosis. Therefore, a MR imaging probe (EP-3533) targeted ColI was employed to stage bowel fibrosis in CD using a rat model and to compare its efficiency with the common MR imaging contrast medium gadopentetatedimeglumine (Gd-DTPA). The bowel fibrotic rat model was established with different degrees of bowel fibrosis, were scanned using a 3.0-T MRI scanner with a specialized animal coil. MRI sequence including T1 mapping and T1-weighed imaging were performed before and after injecting the MRI probe (EP-3533 or Gd-DTPA). The T1 relaxation time (T1 value) and change in the contrast-to-noise ratio (ΔCNR) were measured to evaluate bowel fibrosis. Masson’s trichrome staining was performed to determine the severity of fibrosis. EP-3533 offered a better longitudinal relaxivity (r1) with 67.537 L/mmol·s, which was approximately 13 times that of Gd-DTPA. The T1 value on bowel segments was reduced in the images from EP-3533 compared to that from Gd-DTPA (F = 16.478; p < 0.001). Additionally, a better correlation between ΔCNR calculated from EP-3533 imaging and bowel fibrosis (AUC = 0.846) was determined 10 min after enhanced media administration than with Gd-DTPA (AUC = 0.532). The 10th-minute ΔCNR performed using the ColI probe showed the best correlation with the severity of bowel fibrosis (r = 0.538; p = 0.021). Our results demonstrates that targeted MRI probe (EP-3533) supplies a better enhanced effect compared to Gd-DTPA and could be a promising method to evaluate the progression and monitor the therapeutic response of bowel fibrosis.

The prime issue derived from prostate cancer (PCa) is its high prevalence to metastasize to bone. MicroRNA-204-5p (miR-204-5p) has been reported to be involved in the development and metastasis in a variety of cancers. However, the clinical significance and biological functions of miR-204-5p in bone metastasis of PCa are still not reported yet. In this study, we find that miR-204-5p expression is reduced in PCa tissues and serum sample with bone metastasis compared with that in PCa tissues and serum sample without bone metastasis, which is associated with advanced clinicopathological characteristics and poor bone metastasis-free survival in PCa patients. Moreover, upregulation of miR-204-5p inhibits the migration and invasion of PCa cells in vitro, and importantly, upregulating miR-204-5p represses bone metastasis of PCa cells in vivo. Our results further demonstrated that miR-204-5p suppresses invasion, migration, and bone metastasis of PCa cells via inactivating nuclear factor κB (NF-κB) signaling by simultaneously targeting TRAF1, TAB3, and MAP3K3. In clinical PCa samples, miR-204-5p expression negatively correlates with TRAF1, TAB3, and MAP3K3 expression and NF-κB signaling activity. Therefore, our findings reveal a new mechanism underpinning the bone metastasis of PCa, as well as provide evidence that miR-204-5p might serve as a novel serum biomarker in bone metastasis of PCa.This study identifies a novel functional role of miR-204-5p in bone metastasis of prostate cancer and supports the potential clinical value of miR-204-5p as a serum biomarker in bone metastasis of PCa.

Abstract Background Clinically, prostate cancer (PCa) exhibits a high avidity to metastasize to bone. Myc-associated zinc-finger protein (MAZ) is a well-documented oncogene involved in the progression and metastasis of multiple cancer types, even in PCa. However, the clinical significance and biological roles of MAZ in bone metastasis of PCa remain unclear. Methods MAZ expression was examined in PCa tissues with bone metastasis, PCa tissues without bone metastasis and metastatic bone tissues by real-time PCR and immunohistochemistry (IHC), respectively. Statistical analysis was performed to evaluate the clinical correlation between MAZ expression and clinicopathological features and bone metastasis-free survival in PCa patients. Biological roles of MAZ in bone metastasis of PCa were investigated both in vitro by transwell assay, and in vivo by a mouse model of left cardiac ventricle inoculation. The bioinformatics analysis, western blot, pull-down assays, chromatin immunoprecipitation (ChIP) and luciferase reporter assays were applied to demonstrate and examine the relationship between MAZ and its potential downstream signalling pathway. TaqMan copy number assay was performed to identify the underlying mechanism responsible for MAZ overexpression in PCa tissues. Results MAZ expression is elevated in PCa tissues with bone metastasis compared with that in PCa tissues without bone metastasis, and is further increased in metastatic bone tissues. High expression of MAZ positively correlates with poor overall and bone metastasis-free survival in PCa patients. Upregulating MAZ elevates, while silencing MAZ represses the invasion and migration abilities of PCa cells in vitro and bone metastasis ability in vivo. Our results further reveal that MAZ promotes bone metastasis of PCa dependent on KRas signalling, although MAZ transcriptionally upregulates KRas and HRas expression, where the Ral guanine nucleotide exchange factor (RalGEF) signaling is responsible for the different roles of KRas and HRas in mediating the pro-bone metastasis of MAZ in PCa. Finally, our results indicate that recurrent gains contribute to MAZ overexpression in a small portion of PCa tissues. Conclusion These results indicate that the MAZ/Kras/ RalGEF signalling axis plays a crucial role in promoting PCa cell bone metastasis, suggesting a potential therapeutic utility of MAZ in bone metastasis of PCa.

ObjectiveTo investigate whether radiomics features extracted from multi-parametric MRI combining machine learning approach can predict molecular subtype and androgen receptor (AR) expression of breast cancer in a non-invasive way.Materials and MethodsPatients diagnosed with clinical T2–4 stage breast cancer from March 2016 to July 2020 were retrospectively enrolled. The molecular subtypes and AR expression in pre-treatment biopsy specimens were assessed. A total of 4,198 radiomics features were extracted from the pre-biopsy multi-parametric MRI (including dynamic contrast-enhancement T1-weighted images, fat-suppressed T2-weighted images, and apparent diffusion coefficient map) of each patient. We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). The performances of binary classification models were assessed via the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). And the performances of multiclass classification models were assessed via AUC, overall accuracy, precision, recall rate, and F1-score.ResultsA total of 162 patients (mean age, 46.91 ± 10.08 years) were enrolled in this study; 30 were low-AR expression and 132 were high-AR expression. HR+/HER2− cancers were diagnosed in 56 cases (34.6%), HER2+ cancers in 81 cases (50.0%), and TNBC in 25 patients (15.4%). There was no significant difference in clinicopathologic characteristics between low-AR and high-AR groups (P > 0.05), except the menopausal status, ER, PR, HER2, and Ki-67 index (P = 0.043,

Aim: After neoadjuvant chemotherapy (NACT), tumor shrinkage pattern is a more reasonable outcome to decide a possible breast-conserving surgery (BCS) than pathological complete response (pCR). The aim of this article was to establish a machine learning model combining radiomics features from multiparametric MRI (mpMRI) and clinicopathologic characteristics, for early prediction of tumor shrinkage pattern prior to NACT in breast cancer.Materials and Methods: This study included 199 patients with breast cancer who successfully completed NACT and underwent following breast surgery. For each patient, 4,198 radiomics features were extracted from the segmented 3D regions of interest (ROI) in mpMRI sequences such as T1-weighted dynamic contrast-enhanced imaging (T1-DCE), fat-suppressed T2-weighted imaging (T2WI), and apparent diffusion coefficient (ADC) map. The feature selection and supervised machine learning algorithms were used to identify the predictors correlated with tumor shrinkage pattern as follows: (1) reducing the feature dimension by using ANOVA and the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation, (2) splitting the dataset into a training dataset and testing dataset, and constructing prediction models using 12 classification algorithms, and (3) assessing the model performance through an area under the curve (AUC), accuracy, sensitivity, and specificity. We also compared the most discriminative model in different molecular subtypes of breast cancer.Results: The Multilayer Perception (MLP) neural network achieved higher AUC and accuracy than other classifiers. The radiomics model achieved a mean AUC of 0.975 (accuracy = 0.912) on the training dataset and 0.900 (accuracy = 0.828) on the testing dataset with 30-round 6-fold cross-validation. When incorporating clinicopathologic characteristics, the mean AUC was 0.985 (accuracy = 0.930) on the training dataset and 0.939 (accuracy = 0.870) on the testing dataset. The model further achieved good AUC on the testing dataset with 30-round 5-fold cross-validation in three molecular subtypes of breast cancer as following: (1) HR+/HER2–: 0.901 (accuracy = 0.816), (2) HER2+: 0.940 (accuracy = 0.865), and (3) TN: 0.837 (accuracy = 0.811).Conclusions: It is feasible that our machine learning model combining radiomics features and clinical characteristics could provide a potential tool to predict tumor shrinkage patterns prior to NACT. Our prediction model will be valuable in guiding NACT and surgical treatment in breast cancer.

Abstract Background Cortical vein thrombosis (CVT) receives little attention in adult patients with cerebral venous sinus thrombosis (CVST). This study aimed to investigate the clinical and radiological features of adult CVST patients with concomitant CVT. Methods From May 2009 to May 2016, we recruited 44 adult CVST patients (diagnosed within 1 month of onset; 33.8 ± 14.0 years of age, 28 males). CVT was primarily confirmed using computed tomography venography and magnetic resonance imaging sequence of contrast enhanced three dimensions magnetization prepared rapid acquisition with gradient echo. Patients with concomitant CVT were divided into the CVT group; otherwise, the patients were placed into the non-CVT group. The clinico-radiological characteristics were compared between the two groups. Results The CVT group included 27 patients (61.4%), and the non-CVT group included 17 patients (38.6%). Seizure (63.0% versus 11.8%), focal neurological deficits (44.4% versus 5.9%), and consciousness disorders (33.3% versus 0) occurred more frequently in the patients in the CVT group than in those of the non-CVT group (P

In this study, we investigated the utility of native T1 mapping in differentiating between various grades of fibrosis and compared its diagnostic accuracy to magnetization transfer imaging (MTI) in a rat model of CD. Bowel specimens (64) from 46 CD model rats undergoing native T1 mapping and MTI were enrolled. The longitudinal relaxation time (T1 value) and normalized magnetization transfer ratio (MTR) were compared between none-to-mild and moderate-to-severe fibrotic bowel walls confirmed by pathological assessments. The results showed that the correlation between the T1 value and fibrosis (r = 0.438, p < 0.001) was lower than that between the normalized MTR and fibrosis (r = 0.623, p < 0.001). Overall, the T1 values (t = −3.066, p = 0.004) and normalized MTRs (z = 0.081, p < 0.001) in none-to-mild fibrotic bowel walls were lower than those in moderate-to-severe fibrotic bowel walls. The area under the curve (AUC) of the T1 value (AUC = 0.716, p = 0.004) was significantly lower than that of the normalized MTR (AUC = 0.881, p < 0.001) in differentiating moderate-to-severe fibrosis from none-to-mild fibrosis (z = −2.037, p = 0.042). Our results support the view that the T1 value could be a promising imaging biomarker in grading the fibrosis severity of CD. However, the diagnostic performance of native T1 mapping was not superior to MTI.