Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Gastric cancer (GC) is a malignant tumor with poor survival outcomes. Immunotherapy can improve the prognosis of many cancers, including GC. However, in clinical practice, not all cancer patients are sensitive to immunotherapy. Therefore, it is essential to identify effective biomarkers for predicting the prognosis and immunotherapy sensitivity of GC. In recent years, chemokines have been widely reported to regulate the tumor microenvironment, especially the immune landscape. However, whether chemokine-related lncRNAs are associated with the prognosis and immune landscape of GC remains unclear. In this study, we first constructed a novel chemokine-related lncRNA risk model to predict the prognosis and immune landscape of GC patients. By using various algorithms, we identified 10 chemokine-related lncRNAs to construct the risk model. Then, we determined the prognostic efficiency and accuracy of the risk model. The effectiveness and accuracy of the risk model were further validated in the testing set and the entire set. In addition, our risk model exerted a crucial role in predicting the infiltration of immune cells, immune checkpoint genes expression, immunotherapy scores and tumor mutation burden of GC patients. In conclusion, our risk model has preferable prognostic performance and may provide crucial clues to formulate immunotherapy strategies for GC.

GLYCOCONJUGATES IN PROGNOSTIC ANALYSIS AGAINST INFECTIONS AND PATHOGENS: THE KEYS TO APPLICATION

The overview focuses on our own data on the use of water-soluble glycoconjugates (www.lectinity.com) based on a linear polyacrylamide chain in relation to recombinant therapeutic human protein hormones and probiotic recognition proteins such as enzymes and lectins. The results obtained characterize the basic principles of multilevel relationships between proteins and glycoconjugates, including the assembly of complexes and nanoparticles on the solid phase. Prospects for the application of these principles and cases of interaction of proteins and glycoconjugates, including taking into account the participation of enzymes, in the study of human proteins and viruses, are noted. The presented data can help in development of the protective network communication systems as well as new combined preparations against infections and pathogens. These data can serve the keys to be applied in medical biotechnology.

Comprehensive Analysis of The Clinical Significance and Prognostic Value of The CBX Family in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC)

Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is the second most common type of cancer among gynecologic malignancies worldwide. Chromobox (CBX) family proteins are associated with the regulation of tumorigenesis, metastasis, and evolution of various cancers.Methods: The clinical features, expression levels, and prognostic value of CBXs in CESC were analyzed through several databases, including ONCOMINE, GEPIA, HPA, UALCAN, cBioPortal,Kaplan-Meier plotter and .Results: We concluded that the expression level of CBX2/4/8 was upregulated, while the expression level of CBX6/7 was downregulated in CESC specimens. Immune infiltration analysis revealed that CBX1/2/3/4/5/6/8 proteins were downregulated in normal cervical tissues, and upregulated in CESC specimens. In contrast, CBX7 protein expression was significantly higher in normal adjacent cervical tissues and was not detected in CESC tissues. CBX1/3/6 mRNA expression was significantly correlated with the pathological stage of CESC. Prognostic analysis showed that patients with high CBX7 levels of CESC had a favorable prognosis.Conclusions: Our study indicated that CBX7 could be an attractive biomarker for the prognosis of CESC.

Prediction of high-risk liver cancer patients from their mutation profile: Benchmarking of mutation calling techniques

Identification of somatic mutations with high precision is one of the major challenges in prediction of high-risk liver-cancer patients. In the past number of mutation calling techniques have been developed that include MuTect2, MuSE, Varscan2, and SomaticSniper. In this study an attempt has been made to benchmark potential of these techniques in predicting prognostic biomarkers for liver cancer. In this study, we extracted somatic mutations in liver-cancer patients using VCF and MAF files from the cancer genome atlas. In terms of size, the MAF files are 42 times smaller than VCF files and containing only high-quality somatic mutations. Secondly, machine learning based models have been developed for predicting high-risk cancer patients using mutations obtain from different techniques. The performance of different techniques and data files have been compared based on their potential to discriminate high and low risk liver-cancer patients. Further, univariate survival analysis revealed the prognostic role of highly mutated genes. Based on correlation analysis, we selected 80 genes negatively associated with the overall survival of the liver cancer patients. Single-gene based analysis showed that MuTect2 technique based MAF file has achieved maximum HRLAMC3 9.25 with p-value 1.78E-06. Finally, we developed various prediction models using selected genes for each technique, and the results indicate that MuTect2 technique based VCF files outperform all other methods with maximum AUROC of 0.72 and HR 4.50 (p-value 3.83E-15). Based on overall analysis, VCF file generated using MuTect2 technique performs better among other mutation calling techniques to explore the prognostic potential of mutations in liver cancer. We hope that our findings will provide a useful and comprehensive comparison of various mutation calling techniques for the prognostic analysis of cancer patients.

Clinical Treatment and Prognostic Analysis of Patients with Aneurysmal Subarachnoid Hemorrhage

Subarachnoid hemorrhage (SAH) is a serious disease caused by blood flow into the subarachnoid space due to rupture of blood vessels. All diseases that cause intracranial hemorrhage are the cause of subarachnoid hemorrhage. Among them, due to the particularity of intracranial blood vessels, intracranial blood vessels are more prone to aneurysms than other parts. Therefore, the incidence of aneurysmal subarachnoid hemorrhage (aSAH) is extremely high. The purpose of this article is to study the clinical treatment and prognosis analysis of aSAH patients. This article first summarizes the current status of SAH research at home and abroad and summarizes its potential value and significance. On this basis, an in-depth study of the clinical treatment of aSAH patients has been carried out. The physiological mechanism and clinical general differences of aSAH were studied and analyzed. This article systematically describes the application of CTP in the treatment and prognosis analysis of aSAH patients. Then, it will use a comparative analysis method, interdisciplinary method, and other research forms to carry out experimental research on the theme of this article. Research shows that rebleeding and blood sodium are the main factors for cerebral ischemia caused by aSAH.

M2 macrophages secrete CXCL13 to promote renal cell carcinoma migration, invasion, and EMT

Objective M2 macrophages are associated with a poor prognosis in a variety of malignancies. There are, however, few relevant investigations in clear cell renal cell carcinoma (ccRCC). Methods The expression of M2 macrophages in ccRCC tissues was first discovered using immunohistochemistry in this study. Then, M2 macrophages were created in vitro to see how they affected the proliferation, migration, invasion, and EMT of ccRCC cells. Using qPCR and prognostic analysis identifies important chemokine. Antibody neutralization tests confirmed the chemokine’s involvement and function. Pathway inhibitors confirmed the main pathway of M2 macrophages in ccRCC. Finally, qPCR and IHC were used to confirm the expression of chemokine receptors in ccRCC tissues. Results The presence of M2 macrophages was linked to a poor outcome in ccRCC. M2 macrophages enhanced the proliferation, migration, invasion, and EMT of ccRCC lines in vitro. CXCL13 was identified as the main chemokine by prognostic analysis and qPCR tests. CXCL13 neutralizing antibodies can inhibit the stimulation of M2 macrophages in ccRCC lines’ proliferation, migration, invasion, and EMT. M2 macrophages and CXCL13 may activate the Akt pathway in ccRCC lines, and Akt inhibitors decrease ccRCC lines proliferation, migration, invasion, and EMT. CXCR5 expression is a poor prognostic factor for renal cell carcinoma, according to qPCR and immunohistochemistry. In vivo experiments further proved that CXCL13 secreted by M2 macrophages can promote tumor proliferation. Conclusions M2 macrophages in the immunological milieu secrete CXCL13, which promotes ccRCC proliferation, migration, invasion, and EMT. Our findings contribute to a better understanding of the function of the tumor microenvironment in the incidence and progression of ccRCC, and they may point to novel therapeutic targets for ccRCC.

Interaction Between Macrophage Extracellular Traps and Colon Cancer Cells Promotes Colon Cancer Invasion and Correlates With Unfavorable Prognosis

BackgroundMacrophage extracellular traps (METs) and tumor-infiltrating macrophages contribute to the progression of several diseases. But the role of METs and tumor-infiltrating macrophages in colon cancer (CC) has not been illuminated. In this study, we aimed to clarify the prognostic value of METs for CC patients and to explore the interaction between CC cells and METs in vitro and in vivo.MethodsA training cohort consisting of 116 patients and a validation cohort of 94 patients were enrolled in this study. Immunofluorescence (IF) staining was conducted to determine METs formation in CC patients. Cox regression was used to perform prognostic analysis and screen out the best prognostic model. A nomogram was established to predict 5-year overall survival (OS). The correlation between METs with clinicopathological features and inflammatory markers was analyzed. The formation of METs in vitro was detected by SYTOX® green and IF staining, and the effect of METs on CC cells was detected by transwell assays. PAD2-IN-1, a selective inhibitor of peptidylarginine deiminase 2 (PAD2), was introduced to destroy the crosstalk between CC cells and METs in vitro and in vivo.ResultsMETs levels were higher in CC tissues and were an independent prognostic factor for CC patients. The prognostic model consisting of age, tumors local invasion, lymph node metastasis and METs were confirmed to be consistent and accurate for predicting the 5-year OS of CC patients. Besides, METs were correlated with distant metastasis and inflammation. Through in vitro experiments, we confirmed that there was a positive feedback loop between CC cells and METs, in that METs promoted the invasion of CC cells and CC cells enhanced the production of METs, in turn. This interaction could be blocked by PAD2-IN-1 inhibitors. More importantly, animal experiments revealed that PAD2-IN-1 inhibited METs formation and CC liver metastasis in vivo.ConclusionsMETs were the potential biomarker of CC patient prognosis. PAD2-IN-1 inhibited the crosstalk between CC cells and METs in vitro and in vivo, which should be emphasized in CC therapy.

MPC-10 Prognostic analysis in IDH mutant astrocytoma patient with CDKN2A/B homozygous deletion

background: IDH mutant astrocytoma has good prognosis compared with IDH wildtype one. In IDH mutant astrocytoma, However, patients with CDKN2A/B homozygous deletion (HD) are worse prognosis than non CDKN2A/B HD. Here we analyzed the prognosis of glioma patients identified with CDKN2A/B HD in our hospital. method: There were 62 cases, and female was 26. Mean age of all cases was 41.2 and median age was 38. In IDH gene status, R132H was 59 cases (95.2%), R172K 2 (3.2%) and R132S 1 (1.6%). All 62 cases were TERT wildtype. CDKN2A/B HD were 12 cases (19.4%). In log-rank test, the group of CDKN2A/B HD was poor prognosis than non HD. In astrocytoma grade 3, CDKN2A/B HD had significantly poor prognosis (p=0.002). In Cox proportional hazard model analysis, CDKN2A/B HD was effective predictive prognostic factor as well as age and grading (p=0.03). discussion/conclusion: We showed that CDKN2A/B HD was good predictive prognostic factor in IDH mutant astrocytoma.