Construction and Validation of a Novel Nomogram for Predicting the Risk of Metastasis in a Luminal B Type Invasive Ductal Carcinoma Population.

Background: Postoperative distant metastasis is the main cause of death in breast cancer patients. We aimed to construct a nomogram to predict the risk of metastasis of luminal B type invasive ductal carcinoma. Methods: We applied the data of 364 luminal B type breast cancer patients between 2008 and 2013. Patients were categorized into modeling group and validation group randomly (1:1). The breast cancer metastasis nomogram was developed from the logistic regression model using clinicopathological variables. The area under the receiver-operating characteristic curve (AUC) was calculated in modeling group and validation group to evaluate the predictive accuracy of the nomogram. Results: The multivariate logistic regression analysis showed that tumor size, No. of the positive level 1 axillary lymph nodes, human epidermal growth factor receptor 2 (HER2) status and Ki67 index were the independent predictors of the breast cancer metastasis. The AUC values of the modeling group and the validation group were 0.855 and 0.818, respectively. The nomogram had a well-fitted calibration curve. The positive and negative predictive values were 49.3% and 92.7% in the modeling group, and 47.9% and 91.0% in the validation group. Patients who had a score of 60 or more were thought to have a high risk of breast cancer metastasis. Conclusions: The nomogram has a great predictive accuracy of predicting the risk of breast cancer metastasis. If patients had a score of 60 or more, necessary measures, like more standard treatment methods and higher treatment adherence of patients, are needed to take to lower the risk of metastasis and improve the prognosis.

Cytokine-driven positive feedback loop organizes fibroblast transformation and facilitates gastric cancer progression

BackgroundGastric cancer (GC) is a malignancy that belongs to one of the most common leading causes of cancer death. Cancer-associated fibroblasts (CAFs) promote the GC cells’ malignant behavior. It is still unknown how GC converts normal fibroblasts (NFs) to CAFs.MethodsGC cells were co-cultured with NFs. Bioinformatics was used to analyze the genes and signaling pathways that were changed in fibroblast. RT-PCR, western blot, and Elisa assays were used to detect the expression of cytokines in fibroblast and condition medium. Western blot and immunofluorescence demonstrated activation of relevant pathways in CAFs-like cells. Transwell, scrape, colony formation, and CCK-8 assays were performed to reveal the feedback effect of CAFs-like cells on GC cells.ResultsGC promoted the conversion of NFs to CAFs by secreting Interleukin 17A (IL-17). It included both morphological and molecular marker changes. This process was achieved by activating the nuclear factor-κB (NF-κB) pathway. On the other hand, CAFs cells could secrete C-X-C Motif Chemokine Ligand 8 (IL-8, IL-8), which promoted the malignant phenotype of GC cells. In this way, a feedback loop of mutual influence was constructed in the GC and tumor microenvironment (TME).ConclusionsOur research proved a novel model of GC-educated NFs. GC-IL-17-fibroblast-IL-8-GC axis might be a potential pathway of the interaction between GC and TME.

Cytokine-driven positive feedback loop organizes fibroblast transformation and facilitates gastric cancer progression.

BACKGROUND: Gastric cancer (GC) is a malignancy that belongs to one of the most common leading causes of cancer death. Cancer-associated fibroblasts (CAFs) promote the GC cells' malignant behavior. It is still unknown how GC converts normal fibroblasts (NFs) to CAFs. METHODS: GC cells were co-cultured with NFs. Bioinformatics was used to analyze the genes and signaling pathways that were changed in fibroblast. RT-PCR, western blot, and Elisa assays were used to detect the expression of cytokines in fibroblast and condition medium. Western blot and immunofluorescence demonstrated activation of relevant pathways in CAFs-like cells. Transwell, scrape, colony formation, and CCK-8 assays were performed to reveal the feedback effect of CAFs-like cells on GC cells. RESULTS: GC promoted the conversion of NFs to CAFs by secreting Interleukin 17A (IL-17). It included both morphological and molecular marker changes. This process was achieved by activating the nuclear factor-κB (NF-κB) pathway. On the other hand, CAFs cells could secrete C-X-C Motif Chemokine Ligand 8 (IL-8, IL-8), which promoted the malignant phenotype of GC cells. In this way, a feedback loop of mutual influence was constructed in the GC and tumor microenvironment (TME). CONCLUSIONS: Our research proved a novel model of GC-educated NFs. GC-IL-17-fibroblast-IL-8-GC axis might be a potential pathway of the interaction between GC and TME.

Co-combination of islets with bone marrow mesenchymal stem cells promotes angiogenesis.

BACKGROUND: Islet transplantation is a commonly therapeutic strategy for diabetes mellitus. However, avascular phase and the poor formation of blood vessels in the late period lead to islet allograft loss which contributed to inefficiency and short-acting of islet transplantation. Recently, to speed up new angiogenesis and increase the density of blood vessels around transplanted islets became the hotspot in research of islet transplantation. METHODS: In this study, we undergone co-combination transplantation of allogeneic islet and bone marrow mesenchymal stem cells (BM-MSCs) into non-obese diabetic (NOD) mice and investigated the influence of BM-MSCs in transplanted islet function and neovascularization. RESULTS: In mice of co-combination transplantation of islet with BM-MSCs, level of blood glucose was improved compared with only BM-MSCs transplanted mice; proliferation of islet cell was enhanced while apoptosis of islet cell was reduced; 2, 4, and 8 weeks post transplantation, peripheral vascular density of islet grafts were significantly more than the islet transplantation group alone; donor lymphocytic chimerism in graft was increased. In result of immunofluorescence analysis, we observed that BM-MSCs can migrate to transplanted islet, differentiate into vascular smooth muscle cells (VSMC) and vascular endothelial cells (VEC), and also secrete vascular endothelial growth factor (VEGF). CONCLUSION: BM-MSCs can migrate to transplanted islet and promote neovascularization. Also, it enhanced allograft immune tolerance of islet grafts via increasing donor lymphocytic chimerism.