A bioinformatics analysis and an experimental validation of the hypoxia-related prognostic model.

Background: Hypoxia plays an important role in the development of pancreatic cancer (PCA). However, there is few research on the application of hypoxia molecules in predicting the prognosis of PCA. We aimed to establish a prognostic model based on hypoxia-related genes (HRGs) for PCA to discover new biomarkers, and to reveal the potential of this prognostic model for evaluating the tumor microenvironment (TME). Methods: Univariate Cox regression analysis was used to identify HRGs associated with overall survival (OS) of PCA samples. A hypoxia-related prognostic model was established based on least absolute shrinkage and selection operator (LASSO) regression analysis in The Cancer Genome Atlas (TCGA) cohort. The model was validated in the Gene Expression Omnibus (GEO) datasets. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to estimate the infiltration of immune cells. A wound healing assay and transwell invasion assay were used to explore the biological functions of target genes in PCA. Results: A total of 18 HRGs were differentially expressed between the tumor and normal pancreatic tissue, 4 (BHLHE40, ENO1, SDC4, and TGM2) of which were selected to construct a prognostic model. According to this model, patients in the high-risk group had a less favorable prognosis. Furthermore, the proportion of M0 macrophages was significantly higher in high-risk tissue-type patients, whereas naïve B cells, plasma cells, CD8+ T cells, and activated CD4+ memory T cells were significantly lower. The expression of BHLHE40 in PCA cells was significantly up-regulated under hypoxic conditions. Moreover, BHLHE40 was shown to regulate the transcription and expression of the downstream target gene TLR3. The wound healing assay and transwell invasion assay indicated that BHLHE40 mediated PCA cell migration and invasion by targeting the downstream gene TLR3. Conclusions: The hypoxia-related prognostic model established by the expression pattern of 4 HRGs can be used to predict the prognosis and assess the TME of PCA patients. Mechanically, activation of the BHLHE40/TLR3 axis is responsible for the promoted invasion and migration of PCA cells in a hypoxic environment.

[The Effect of Ena/VASP Family on the Expression of GPIb-IX Complex in Human Megakaryoblastic Leukemia Dami Cells].

OBJECTIVE: To explore the effects of Ena/VASP gene family on the expression of glycoprotein (GP) Ib-IX complex in human megakaryoblastic leukemia Dami cells. METHODS: SiRNAs targeting Ena/VASP gene family were designed and synthesized to interfere Enah, EVL and VASP gene expression. When the siRNAs were transfected into Dami cells by using LipofectamineTM 2000 for 48 h, the expression of GPIb-IX complex was detected by quantitative real-time PCR, Western blot and flow cytometry. RESULTS: We successfully established siVASP , siEVL and si Enah Dami cell lines. And it was found that the expression of GPIb-IX complex had no evident reduction in siEVL or siVASP Dami cells at both mRNA and protein level, while the total protein and membrane protein of GPIb-IX complex were obviously reduced when Enah was knocked down. CONCLUSION: Enah could affect the expression of GPIb-IX complex in human megakaryoblastic leukemia Dami cells, but the underlying mechanism still needs to be further explored.

M2-phenotype tumour-associated macrophages upregulate the expression of prognostic predictors MMP14 and INHBA in pancreatic cancer.

Pancreatic cancer is one of the most lethal gastrointestinal tumours, the most common pathological type is pancreatic adenocarcinoma (PAAD). In recent year, immune imbalanced in tumour microenvironment has been shown to play an important role in the evolution of tumours progression, and the efficacy of immunotherapy has been gradually demonstrated in clinical practice. In this study, we propose to construct an immune-related prognostic risk model based on immune-related genes MMP14 and INHBA expression that can assess the prognosis of pancreatic cancer patients and identify potential therapeutic targets for pancreatic cancer, to provide new ideas for the treatment of pancreatic cancer. We also investigate the correlation between macrophage infiltration and MMP14 and INHBA expression. First, the gene expression data of pancreatic cancer and normal pancreatic tissue were obtained from The Cancer Genome Atlas Program (TCGA) and The Genotype-Tissue Expression public database (GTEx). The differentially expressed immune-related genes between pancreatic cancer samples and normal sample were screened by R software. Secondly, univariate Cox regression analysis were used to evaluate the relationship between immune-related genes and the prognosis of pancreatic cancer patients. A polygenic risk score model was constructed by Cox regression analysis. The prognostic nomogram was constructed, and its performance was evaluated comprehensively by internal calibration curve and C-index. Using the risk model, each patient gets a risk score, and was divided into high- or low- risk groups. The proportion of 22 types of immune cells infiltration in pancreatic cancer samples was inferred by CIBERSOFT algorithm, correlation analysis (Pearson method) was used to analyse the correlation between the immune-related genes and immunes cells. Then, we applied macrophage conditioned medium to culture pancreatic cancer cell line PANC1, detected the expression of MMP14 and INHBA by qRT-PCR and Western blot methods. Knock-down MMP14 and INHBA in PANC1 cells by transfected with shRNA lentiviruses. Detection of migration ability of pancreatic cells was done by trans-well cell migration assay. A subcutaneous xenograft tumour model of human pancreatic cancer in nude mice was constructed. In conclusion, an immune-related gene prognostic model was constructed, patients with high-risk scores have poorer survival status, M2-phenotype tumour-associated macrophages (TAMs) up-regulate two immune-related genes, MMP14 and INHBA, which were used to establish the prognostic model. Knock-down of MMP14 and INHBA inhibited invasion of pancreatic cancer.

Tumor-associated macrophages promote the metastasis and growth of non-small-cell lung cancer cells through NF-κB/PP2Ac-positive feedback loop.

Non-small-cell lung cancer (NSCLC), with its aggressive biological behavior, is one of the most diagnosed cancers. Tumor-associated inflammatory cells play important roles in the interaction between chronic inflammation and lung cancer, however the mechanisms involved are far from defined. In the present study, by developing an orthotopic NSCLC mouse model based on chronic inflammation, we proved that an inflammatory microenvironment accelerated the growth of orthotopic xenografts in vivo. Tumor-associated macrophages, the most abundant population of inflammatory cells, were identified. Treatment with macrophage-conditioned medium (MCM) promoted the growth and migration of NSCLC cells. Using bioinformatics analysis, we identified downregulated PP2Ac expression in NSCLC cells upon treatment with MCM. We further confirmed that this downregulation was executed in an NF-κB pathway-dependent manner. As IκB kinase (IKK) has been proved to be a substrate of PP2Ac, inhibition on PP2Ac could result in amplification of NF-κB pathway signaling. Overexpression of PP2Ac, or the dominant-negative forms of IKK or IκB, attenuated the acceleration of growth and metastasis by MCM. Using bioinformatics analysis, we further identified that CXCL1 and COL6A1 could be downstream of NF-κB/PP2Ac pathway. Luciferase assay and ChIP assay further confirmed the location of response elements on the promoter regions of CXCL1 and COL6A1. Elevated CXCL1 facilitated angiogenesis, whereas upregulated COL6A1 promoted proliferation and migration.

The prognostic roles of red blood cell-associated indicators in patients with resectable gastric cancers.

BACKGROUND: Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. This study was designed to investigate the prognostic values of red blood cell (RBC)-associated indicators, including RBC, hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and RBC distribution width (RDW) in resectable GC patients. METHODS: In this retrospective study, a total of 104 pathologically confirmed GC patients were recruited. These cases were divided into two groups according to the median values of pretreatment RBC, HGB, HCT, MCV, MCH, MCHC, or RDW. To evaluate the changes in RBC-associated indicators values after treatment, we introduced the concept of post-/pre-treatment ratios (≤1 suggested RBC, HGB, HCT, MCV, MCH, MCHC, or RDW values were not increased after therapy, while >1 represented those in increased levels). RESULTS: The lower pretreatment MCHC levels were correlated with worse overall survival (OS), while pretreatment levels of RBC, HGB, HCT, MCV, MCH, or RDW were not. The whole course of treatment (surgery plus adjuvant chemotherapy) significantly decreased the values of MCHC, and increased the values of MCV and RDW, whereas it had no obvious effects on the values of RBC, HGB, HCT, or MCH. Patients with post-/pre-treatment MCV ratio >1 had an increased survival ratio. Meanwhile, post-/pre-treatment RBC, HGB, HCT, MCH, MCHC, or RDW ratios were not correlated with outcomes. Multivariate Cox regression analysis revealed that the American Joint Committee on Cancer (AJCC) stage (III), and lower pretreatment MCHC levels were independent risk factors affecting OS. The receiver operating characteristic (ROC) curve analysis showed that an MCHC value of 341.98 g/L was the optimal cutoff value for prognosis, with a sensitivity of 58.3% and a specificity of 75.0%. CONCLUSIONS: Pretreatment MCHC levels could become a potential prognostic factor for resectable GC.

Prognostic values of platelet-associated indicators in advanced breast cancer.

BACKGROUND: Breast cancer is the leading cause of cancer death in the female population. Platelet-related indicators can be used as prognostic markers of cancers. The present study investigated the potential values of platelet count (PLT), plateletcrit (PCT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet to lymphocyte ratio (PLR) in the prognosis of advanced breast cancer (ABC). METHODS: This retrospective study recruited 94 locally advanced or metastatic breast cancer cases who had histologic and cytologic evidence. The patients were divided into two groups according to the median baseline values of PLT, PCT, MPV, PDW, and PLR. To evaluate the individual value changes after treatment, we introduced the concept of post/pre-treatment ratio (≤1 indicated value was not increased after treatment, while >1 suggested increased value). Responses to chemotherapy, including partial response (PR), stable disease (SD), and progressive disease (PD), were recorded. Kaplan-Meier curves were constructed to show overall survival (OS). Univariate and multivariate Cox regression analysis models were employed to identify the independent risk factors. RESULTS: A lower baseline PCT level was correlated with a better OS. A lower baseline PLT level and a higher baseline PDW level were related to better chemotherapeutic efficacy of breast cancer patients. Univariate analysis and multivariate analysis both revealed that a higher baseline PCT level was an independent prognostic factor for OS. CONCLUSIONS: PCT level may be a potential prognosis factor for ABC.