Gastroenteropancreatic neuroendocrine neoplasms: current development, challenges, and clinical perspectives.

Neuroendocrine neoplasms (NENs) are highly heterogeneous and potentially malignant tumors arising from secretory cells of the neuroendocrine system. Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are the most common subtype of NENs. Historically, GEP-NENs have been regarded as infrequent and slow-growing malignancies; however, recent data have demonstrated that the worldwide prevalence and incidence of GEP-NENs have increased exponentially over the last three decades. In addition, an increasing number of studies have proven that GEP-NENs result in a limited life expectancy. These findings suggested that the natural biology of GEP-NENs is more aggressive than commonly assumed. Therefore, there is an urgent need for advanced researches focusing on the diagnosis and management of patients with GEP-NENs. In this review, we have summarized the limitations and recent advancements in our comprehension of the epidemiology, clinical presentations, pathology, molecular biology, diagnosis, and treatment of GEP-NETs to identify factors contributing to delays in diagnosis and timely treatment of these patients.

The Efficacy of Pretreatment 18F-FDG PET-CT-Based Deep Learning Network Structure to Predict Survival in Nasopharyngeal Carcinoma.

Background: Previous studies have shown that the 5-year survival rates of patients with nasopharyngeal carcinoma (NPC) were still not ideal despite great improvement in NPC treatments. To achieve individualized treatment of NPC, we have been looking for novel models to predict the prognosis of patients with NPC. The objective of this study was to use a novel deep learning network structural model to predict the prognosis of patients with NPC and to compare it with the traditional PET-CT model combining metabolic parameters and clinical factors. Methods: A total of 173 patients were admitted to 2 institutions between July 2014 and April 2020 for the retrospective study; each received a PET-CT scan before treatment. The least absolute shrinkage and selection operator (LASSO) was employed to select some features, including SUVpeak-P, T3, age, stage II, MTV-P, N1, stage III and pathological type, which were associated with overall survival (OS) of patients. We constructed 2 survival prediction models: an improved optimized adaptive multimodal task (a 3D Coordinate Attention Convolutional Autoencoder and an uncertainty-based jointly Optimizing Cox Model, CACA-UOCM for short) and a clinical model. The predictive power of these models was assessed using the Harrell Consistency Index (C index). Overall survival of patients with NPC was compared by Kaplan-Meier and Log-rank tests. Results: The results showed that CACA-UOCM model could estimate OS (C index, 0.779 for training, 0.774 for validation, and 0.819 for testing) and divide patients into low and high mortality risk groups, which were significantly associated with OS (P < .001). However, the C-index of the model based only on clinical variables was only 0.42. Conclusions: The deep learning network model based on 18F-FDG PET/CT can serve as a reliable and powerful predictive tool for NPC and provide therapeutic strategies for individual treatment.

SRPK1/AKT axis promotes oxaliplatin-induced anti-apoptosis via NF-κB activation in colon cancer.

BACKGROUND: Colorectal cancer is the third most common diagnosis. Oxaliplatin is used as first-line treatment of colon cancer. However, oxaliplatin resistance greatly reduces its therapeutic effect. SRPK1 involves in pre-mRNA splicing and tumorigenesis. How SRPK1 mediates drug resistance in colon cancer is unknown. METHODS: The expression of SRPK1 was analyzed in the TCGA and the CPTAC pan-cancer samples and detected in colon cancer cell lines and tissues by IHC and western blot. The MTT and TUNEL assay were used to verify the anti-apoptosis ability of colon cancer cell. The activation of NF-κB was determined by luciferase assay and qRT-PCR. AKT, IKK, IκB and their phosphorylation level were verified by western blot. RESULTS: We found that SRPK1 expression was the second highest in TCGA and the CPTAC pan-cancer samples. The mRNA and protein levels of SRPK1 were increased in tissues from patients with colon cancer. SRPK1 was associated with clinical stage and TNM classifications in 148 cases of colon cancer patients. High SRPK1 levels correlated with poor prognosis (p < 0.001). SRPK1 overexpression enhanced the anti-apoptosis ability of colon cancer cells, whereas SRPK1 silencing had the opposite effect under oxaliplatin treatment. Mechanistically, SRPK1 enhances IKK kinase and IκB phosphorylation to promote NF-κB nuclear translocation to confer oxaliplatin resistance. CONCLUSIONS: Our findings suggest that SRPK1 participates in colon cancer progression and enhances the anti-apoptosis capacity to induce drug resistance in colon cancer cells via NF-κB pathway activation, and thus might be a potential pharmaceutically target for colon cancer treatment.

The relationship between expression of PD-L1 and HIF-1α in glioma cells under hypoxia.

Hypoxia inducible factor-1α (HIF-1α) up-regulates the expression of programmed death ligand-1 (PD-L1) in some extracranial malignancies. However, whether it could increase PD-L1 expression in intracranial tumor is still unknown. Here, we explored the relationship between HIF-1α and PD-L1 expression in glioma, and investigated their clinical significance. In glioma patients, HIF-1α and PD-L1 were overexpressed in high grade glioma tissues and were significantly associated with poor survival. In glioma cells, PD-L1 expression was induced under hypoxia condition, and the enhanced PD-L1 expression was abrogated by either HIF-1α knock-down or HIF-1α inhibitor treatment. Furthermore, ChIP-qPCR analysis showed the direct binding of HIF-1α to PD-L1 proximal promoter region, providing evidence that HIF-1α up-regulates PD-L1 in glioma. In glioma murine model, the combination treatment with HIF-1α inhibitor and anti-PD-L1 antibody caused a more pronounced suppressive effect on tumor growth compared to either monotherapy. Immunologically, the combination treatment improved both dendritic cell (DC) and CD8+ T cell activation. Overall, our results demonstrated that positive correlation between PD-L1 and HIF-1α in glioma, and provide an alternative strategy, inhibiting HIF-1α, as combination therapies with immunotherapies to advance glioma treatment.

Alleviation of cancerous pain by external compress with Xiaozheng Zhitong Paste.

OBJECTIVE: To observe the clinical effectiveness of a topical application of Xiaozheng Zhitong: Paste (, XZP) in alleviating the cancerous pain of patients with middle/late stage cancer METHODS: By: adopting a random number table, 124 patients enrolled were randomized into the treatment group (64 patients) and the control group (60 patients). In addition to the basic therapy [including the three-ladder (3L) analgesia] used in both groups, topical application of XZP was given to patients in the treatment group for pain alleviation. The analgesic efficacy was recorded in terms of pain intensity, analgesia initiating time and sustaining time, and the optimal analgesic effect revealing time. Meanwhile, the quality of life (QOL) and adverse reactions that occurred in patients were recorded as well. RESULTS: The total effective rate in the treatment group was: 84.38% (54/64), and in the control group it was 88.33% (53/60), showing no significant difference between them (P>0.05), but the analgesia initiating time and the optimal analgesia effect revealing time in the treatment group were significantly shorter (both P<0.01). Moreover, XZP was better in improving patients' QOL, showing more significant improvements in the treatment group than those in the control group in aspects of mental condition, walking capacity, working capacity, social acceptability, sleep and joy of living (P<0.05 or P<0.01). Lower incidence of adverse reactions, such as nausea, vomiting, mouth dryness, dizziness, etc., especially constipation, was noted in the treatment group (P<0.05 or P<0.01). CONCLUSION: Applying an external compress: of XZP showed a synergistic action with 3L analgesia for shortening the initiating time and the optimal effect revealing time, and could evidently enhance patients' QOL with fewer adverse reactions.