Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years. Moreover, the 5-year overall survival rate of glioma patients is < 35%. Different locations, grades, and molecular characteristics of gliomas can lead to different behavioral deficits and prognosis, which are closely related to patients' quality of life and associated with neuroplasticity. Some advanced magnetic resonance imaging (MRI) technologies can explore the neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms, which may contribute to the improvement of prognosis and function in glioma patients. In this review, we summarized the studies conducted on structural and topological plasticity of glioma patients through different MRI technologies and discussed future research directions. Previous studies have found that glioma itself and related functional impairments can lead to structural and topological plasticity using multimodal MRI. However, neuroplasticity caused by highly heterogeneous gliomas is not fully understood, and should be further explored through multimodal MRI. In addition, the individualized prediction of functional prognosis of glioma patients from the functional level based on machine learning (ML) is promising. These approaches and the introduction of ML can further shed light on the neuroplasticity and related mechanism of the brain, which will be helpful for management of glioma patients.
e16094 Background: Hepatoid adenocarcinoma (HAC) is a rare pathological subtype of extrahepatic tumor, featured by hepatoid differentiation and α-fetoprotein (AFP)-production. Hepatoid adenocarcinoma of the stomach (HAS), accounting for 0.17 to 15% of gastric cancers, is the most common subtype of HAC, and has attracted increasing attention duo to its high degree of malignancy. Compared with classic gastric cancer (GC), HAS showed a higher rate of vascular invasion, lymph node metastasis, and liver metastasis, with only 9% survival at 5 years. In this study, we aim to investigate the molecular features of HAS and identify the potential therapeutic targets for HAS. Methods: We conducted whole-exome sequencing (WES) of 40 paired tumor and normal samples, including 25 HAS, 6 HAC of other organ and 9 AFP-producing gastric cancer (AFPGC). All patients underwent radical surgery at Shanghai Zhongshan Hospital between July 2013 and September 2017. qRT-PCR, Western blot and immunohistochemistry were detected to explore MUC19 expression in HAS. CCK8 assay, Transwell assay, immunofluorescence assay and subcutaneous xenograft tumor model were used to detect functional effects and the mechanism of MUC19. Results: In HAS patients, the top 5 frequently mutated genes were TP53 (44%), TTN (44%), MUC19 (40%), CCNE1 (28%) and CDC27 (28%). Further compared with TCGA datasets, MUC19, CCNE1, CDC27 mutations were almost undetectable in STAD, CRC and HCC. In terms of CNV analysis, VSTM2B, PLEKHF1, POP4, URI1 and TERT were the most frequently amplificated genes in HAS tumor tissues. Interestingly, amplification of 4 genes (VSTM2B, CCNE1, LEKHF1, POP4), which located in chr19q12, was significantly associated with poor prognosis. The tumor mutational burden (TMB) levels and AFP expression of HAS and AFPGC patients were no significantly different, while patients with higher TMB had a remarkably longer overall survival ( p= 0.0065). Moreover, we found MUC19 expression was positively correlated with AFP levels in HAS and MUC19 promoted the transcription of AFP in GC cells. Mechanistically, MUC19 contributed to the aggressive malignancy phenotypes of GC cells through activating the Wnt/β-catenin signaling pathway. Conclusions: MUC19 may be a potential target for HAS diagnosis and treatment. Amplification of genes located in chr19q12 occurred frequently in HAS and were associate with poor prognosis. TMB was sensitive for the overall survival of HAS patients.
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