BackgroundErythropoietin (EPO) is a hypoxia-inducible stimulator of erythropoiesis. Besides its traditional application in anemia therapy, it offers an effective treatment in the cancer patients, especially those who receive chemotherapy. Several reports indicated that it could promote the tumor cell proliferation through its specific receptor (EPOR). Unfortunately, the role of EPO/EPOR in hepatocellular carcinoma (HCC) progressing is still uncertain.MethodsProtein in tumor tissue from HCC patients or H22 tumor-bearing mice was detected with immunohistochemistry. Cells were cultured under 1% oxygen to establish hypoxia. RT-PCR and western blotting were used to measure mRNA and protein of EPO/EPOR, respectively. MTT, flow cytometry and PCNA staining were used to detect cell proliferation. Immunofluorescence staining was applied to study the expression and location of cellular EPOR. The EPOR binding studies were performed with 125I-EPO radiolabeling assay.ResultsEPO and EPOR protein were up-regulated in HCC tissue of patients and H22-bearing mice. These were positively correlated with hypoxia-inducible factor -1 α and ki-67. Hypoxia up-regulated the expression of EPO and EPOR in HepG2 cells. It also induced the proliferation and increased the percentage of divided cells after 24, 48 and 72 h treatment. These were inhibited in cells pre-treated with 0.5 μg/mL soluble-EPOR. Immunofluorescence staining presented that EPOR was obviously translocated from nucleus to cytoplasm and membrane under hypoxia. EPOR binding activity was also increased after exposure to hypoxia. Recombinant human erythropoietin obviously elevated cell proliferation rate and the percentage of divided under hypoxia but not normoxia, which were also inhibited by soluble-EPOR.ConclusionsOur result indicated for the first time that EPO promoted the proliferation of HCC cells through hypoxia induced translocation of it specific receptor. Trial registration TJC20141113, retrospectively registered

Primary high-grade gliomas possess invasive growth and lead to unfavorable survival outcome. The investigation of biomarkers for prediction of survival outcome in patients with gliomas is important for clinical assessment. The DEAD (Asp-Glu-Ala-Asp) box helicase 3, X-linked (DDX3X) controls tumor migration, proliferation, and progression. However, the role of DDX3X in defining the pathological grading and survival outcome in patients with human gliomas is not yet clarified. We analyzed the DDX3X gene expression, WHO pathological grading, and overall survival from de-linked data. Further validation was done using quantitative RT-PCR of cDNA from normal brain and glioma, and immunohistochemical (IHC) staining of tissue microarray. Statistical analysis of GEO datasets showed that DDX3X mRNA expression demonstrated statistically higher in WHO grade IV (n = 81) than in non-tumor controls (n = 23, p = 1.13 × 10−10). Moreover, DDX3X level was also higher in WHO grade III (n = 19) than in non-tumor controls (p = 2.43 × 10−5). Kaplan–Meier survival analysis showed poor survival in patients with high DDX3X mRNA levels (n = 24) than in those with low DDX3X expression (n = 53) (median survival, 115 vs. 58 weeks, p = 0.0009, by log-rank test, hazard ratio: 0.3507, 95% CI: 0.1893–0.6496). Furthermore, DDX3X mRNA expression and protein production significantly increased in glioma cells compared with normal brain tissue examined by quantitative RT-PCR, and Western blot. IHC staining showed highly staining of high-grade glioma in comparison with normal brain tissue. Taken together, DDX3X expression level positively correlates with WHO pathologic grading and poor survival outcome, indicating that DDX3X is a valuable biomarker in human gliomas.

Accurate glioma subtype classification is critical for the treatment management of patients with brain tumors. Developing an automatically computer-aided algorithm for glioma subtype classification is challenging due to many factors. One of the difficulties is the label constraint. Specifically, each case is simply labeled the glioma subtype without precise annotations of lesion regions information. In this paper, we propose a novel hybrid fully convolutional neural network (CNN)-based method for glioma subtype classification using both whole slide imaging (WSI) and multiparametric magnetic resonance imagings (mpMRIs). It is comprised of two methods: a WSI-based method and a mpMRIs-based method. For the WSI-based method, we categorize the glioma subtype using a 2D CNN on WSIs. To overcome the label constraint issue, we extract the truly representative patches for the glioma subtype classification in a weakly supervised fashion. For the mpMRIs-based method, we develop a 3D CNN-based method by analyzing the mpMRIs. The mpMRIs-based method consists of brain tumor segmentation and classification. Finally, to enhance the robustness of the predictions, we fuse the WSI-based and mpMRIs-based results guided by a confidence index. The experimental results on the validation dataset in the competition of CPM-RadPath 2020 show the comprehensive judgments from both two modalities can achieve better performance than the ones by solely using WSI or mpMRIs. Furthermore, our result using the proposed method ranks the third place in the CPM-RadPath 2020 in the testing phase. The proposed method demonstrates a competitive performance, which is creditable to the success of weakly supervised approach and the strategy of label agreement from multi-modality data.