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Hepatitis B virus reactivation (HBVr) in patients with gastrointestinal stromal tumors (GISTs) have not been sufficiently characterized. This study aimed to review the possible mechanism of HBVr induced by imatinib and explore appropriate measures for patient management and monitoring.

The clinical data of GIST patients who experienced HBVr due to treatment with imatinib at Xiangya Hospital (Changsha, Hunan, China) were retrospectively analyzed. A literature review was also conducted.

Five cases were analyzed, including 3 cases in this study. The average age of the patients was 61.8 y, with male preponderance (4 of 5 vs. 1 of 5). These patients received imatinib as adjuvant treatment (n=4) or as neoadjuvant treatment (n=1). Primary tumors were mostly located in the stomach (n=4) or rectum (n=1). High (n=3) or intermediate (n=1) recurrence risk was categorized using the postoperative pathological results (n=4). Imatinib was then started at 400 (n=4) or 200 mg (n=1) daily. Patients first reported abnormalpt antiviral treatment and cessation of imatinib are also necessary.Delivering optimal cancer care to children, adolescents and adults with ASD has recently become a healthcare priority and represents a major challenge for all providers involved. In this review, and after consideration of the available evidence, we concisely deliver key information on this heterogenous group of neurodevelopmental disorders, as well as recommendations and concrete tools for the enhanced oncological care of this vulnerable population of patients.Intrahepatic cholangiocarcinoma (ICC) is a heterogeneous hepatobiliary tumor with poor prognosis, and it lacks reliable prognostic biomarkers and effective therapeutic targets. Long non-coding RNAs (lncRNAs) have been documented to be involved in the progression of various cancers. However, the role of lncRNAs in ICC remains largely unknown. In the present work, we used bioinformatics analysis to identify the differentially expressed lncRNAs in human ICC tissues, among which lncRNA-PAICC was found to be an independent prognostic marker in ICC. Moreover, lncRNA-PAICC promoted the proliferation and invasion of ICC cells. Mechanistically, lncRNA-PAICC acted as a competitive endogenous RNA (ceRNA) that directly sponged the tumor suppressive microRNAs miR-141-3p and miR-27a-3p. The competitive binding property was essential for lncRNA-PAICC to promote tumor growth and metastasis through activating the Hippo pathway. In summary, our results highlighted the important role of the lncRNA-PAICC-miR-141-3p/27a-3p-Yap1 axis in ICC, which offers a novel perspective on the molecular pathogenesis and may serve as a potential target for antimetastatic molecular therapies of ICC.Cerebral radiation necrosis (CRN) is one of the most prominent sequelae following radiation therapy for nasopharyngeal carcinoma (NPC), which might have devastating effects on patients' quality of life (QOL). Advances in histopathology and neuro-radiology have shed light on the management of CRN more comprehensively, yet effective therapeutic interventions are still lacking. CRN was once regarded as progressive and irreversible, however, in the past 20 years, with the application of intensity-modulated radiation therapy (IMRT), both the incidence and severity of CRN have declined. In addition, newly developed medical agents including bevacizumab-a humanized monoclonal antibody against vascular endothelial growth factor (VEGF), nerve growth factor (NGF), monosialotetrahexosylganglioside (GM1), etc., have shown great potency in successfully reversing radiation-induced CRN. As temporal lobes are most frequently compromised in NPC patients, this review will summarize the state-of-the-art progress regarding the incidence, pathophysiology, prevention, treatment, and prognosis of temporal lobe necrosis (TLN) after IMRT in NPC.

Clear cell meningioma (CCM) is a rare subtype of meningioma, accounting for approximately 0.2% of all meningiomas. The present study aimed to analyze the epidemiology and outcome of CCMs using the Surveillance, Epidemiology, and End Results (SEER) database.

Patients diagnosed with central nervous system CCM between 2004 and 2016 were identified from the SEER database. Descriptive analyses were performed to evaluate the distribution of patients and tumor-related characteristics. The survival analysis was performed using Kaplan-Meier curves. The Cox proportional hazards model was used for the univariate and multivariate analyses.

The age-adjusted incidence rate was 0.032 per 1,000,000 person-years. The median age was 52 years. Most of the CCMs were intracranial CCMs that were larger than 3cm. The overall cumulative survival rates at 1, 3, and 5 years were 97.6, 93.2, and 86.9%, respectively. read more The log-rank test and Cox proportional hazards regression analysis revealed that age at diagnosis and primary site of the tumor were independent prognostic factors.

CCM is an extremely rare entity with a favorable survival rate. CCMs usually affect patients during the fourth to fifth decades of life. Patients diagnosed at 21-60 years old and patients with spinal CCMs have a better prognosis.

CCM is an extremely rare entity with a favorable survival rate. CCMs usually affect patients during the fourth to fifth decades of life. Patients diagnosed at 21-60 years old and patients with spinal CCMs have a better prognosis.Survival analysis is important for guiding further treatment and improving lung cancer prognosis. It is a challenging task because of the poor distinguishability of features and the missing values in practice. A novel multi-task based neural network, SurvNet, is proposed in this paper. The proposed SurvNet model is trained in a multi-task learning framework to jointly learn across three related tasks input reconstruction, survival classification, and Cox regression. It uses an input reconstruction mechanism cooperating with incomplete-aware reconstruction loss for latent feature learning of incomplete data with missing values. Besides, the SurvNet model introduces a context gating mechanism to bridge the gap between survival classification and Cox regression. A new real-world dataset of 1,137 patients with IB-IIA stage non-small cell lung cancer is collected to evaluate the performance of the SurvNet model. The proposed SurvNet achieves a higher concordance index than the traditional Cox model and Cox-Net. The difference between high-risk and low-risk groups obtained by SurvNet is more significant than that of high-risk and low-risk groups obtained by the other models.