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Overexpression of RhoV in lung adenocarcinoma promotes the progression and EGFR-TKI resistance, suggesting RhoV is a promising prognosis and therapeutic target of lung adenocarcinoma.

Overexpression of RhoV in lung adenocarcinoma promotes the progression and EGFR-TKI resistance, suggesting RhoV is a promising prognosis and therapeutic target of lung adenocarcinoma.

Skin Cutaneous Melanoma (SKCM) is a tumor of the epidermal melanocytes induced by gene activation or mutation. It is the result of the interaction between genetic, constitutional, and environmental factors. SKCM is highly aggressive and is the most threatening skin tumor. The incidence of the disease is increasing year by year, and it is the main cause of death in skin tumors around the world. CXC chemokines in the tumor microenvironment can regulate the transport of immune cells and the activity of tumor cells, thus playing an anti-tumor immunological role and affecting the prognosis of patients. However, the expression level of CXC chemokine in SKCM and its effect on prognosis are still unclear.

Oncomine, UALCAN, GEPIA, STRING, GeneMANIA, cBioPortal, TIMER, TRRUST, DAVID 6.8, and Metascape were applied in our research.

The transcription of CXCL1, CXCL5, CXCL8, CXCL9, CXCL10, and CXCL13 in SKCM tissues were significantly higher than those in normal tissues. The pathological stage of SKCM patients is closely related to the expression of CXCL4, CXCL9, CXCL10, CXCL11, CXCL12, and CXCL13. The prognosis of SKCM patients with low transcription levels of CXCL4, CXCL9, CXCL10, CXCL11, and CXCL13 is better. The differential expression of CXC chemokines is mainly associated with inflammatory response, immune response, and cytokine mediated signaling pathways. Our data indicate that the key transcription factors of CXC chemokines are RELA, NF-κB1 and SP1. The targets of CXC chemokines are mainly LCK, LYN, SYK, MAPK2, MAPK12, and ART. The relationship between CXC chemokine expression and immune cell infiltration in SKCM was closed.

Our research provides a basis for screening SKCM biomarkers, predicting prognosis, and choosing immunotherapy.

Our research provides a basis for screening SKCM biomarkers, predicting prognosis, and choosing immunotherapy.microRNAs (miRNAs) are of great significance in cancer treatment, which may have a desirable result on the regulation of tumorigenesis, progression, recurrence, and chemo-resistance of ovarian cancer. However, the research on the further potential application of miR-4461 in ovarian cancer is little and limited. Therefore, the study in this paper focus on the investigation of the of miR-4461 in ovarian cancer progression and chemo-resistance. The phenomenon that the proliferation and metastasis of ovarian cancer cells can be promoted by miR4461 is revealed in functional assays. Through the bioinformatics and luciferase reporter analysis, the PTEN is validated to be the direct target of miR-4461 in ovarian. The association between the expression of miR-4461 and PTEN is negative in in human ovarian cancer tissues. The distinction of growth and metastasis capacity between miR-4461 knockdown ovarian cancer cells and control cells is partially abolished by si-PTEN. Moreover, it was found that cisplatin treatment has obvious effect on the miR-4461 knockdown ovarian cancer cells. In summary, the data given in this paper indicate that the miR-4461 can be regarded as a potential onco-miRNA in ovarian cancer by targeting PTEN.Breast cancer is one of the most prevalent types of malignant tumors in the world, resulting in a high incidence of death. The development of new molecules and technologies aiming to apply more effective and safer therapy strategies has been intensively explored to overcome this situation. The association of nanoparticles with known antitumor compounds (including plant-derived molecules such as curcumin) has been considered an effective approach to enhance tumor growth suppression and reduce adverse effects. Therefore, the objective of this systematic review was to summarize published data regarding evaluations about efficacy and toxicity of curcumin nanoparticles (Cur-NPs) in in vivo models of breast cancer. The search was carried out in the databases CINAHL, Cochrane, LILACS, Embase, FSTA, MEDLINE, ProQuest, BSV regional portal, PubMed, ScienceDirect, Scopus, and Web of Science. Studies that evaluated tumor growth in in vivo models of breast cancer and showed outcomes related to Cur-NP treatment (without asroposal that Cur-NP is an effective and safe therapeutic approach in in vivo models of breast cancer, reinforcing the currently available evidence that it should be further analyzed in clinical trials for breast cancer treatments.Purpose We aimed to investigate whether Epstein-Barr virus (EBV) could produce differences on MRI by examining the histogram and texture imaging features. Caspase Inhibitor VI We also sought to determine the predictive value of pretreatment MRI texture analyses incorporating with EBV status for disease progression (PD) in patients with primary nasopharyngeal carcinoma (NPC). Materials and Methods Eighty-one patients with primary T2-T4 NPC and known EBV status who underwent contrast-enhanced MRI were included in this retrospective study. Whole-tumor-based histogram and texture features were extracted from pretreatment T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and contrast-enhanced (CE)-T1WI images. Mann-Whitney U-tests were performed to identify the differences in histogram and texture parameters between EBV DNA-positive and EBV DNA-negative NPC images. The effects of clinical variables as well as histogram and texture features were estimated by using univariate and multivariate logistic regression analyses. Receiver sensitivity and specificity of 93.8 and 66.2%, respectively (AUC, 0.800; 95% CI 0.700-0.900). Conclusion This study demonstrates that MRI-based radiological features and EBV status can be used as an aid tool for the evaluation of PD, in order to develop tailored treatment targeting specific characteristics of individual patients.Intraductal papillary mucinous neoplasms (IPMNs) are a heterogeneous group of neoplasms and represent the most common identifiable precursor lesions of pancreatic cancer. Clinical decision-making of the risk for malignant disease, including high-grade dysplasia and invasive carcinoma, is challenging. Moreover, discordance on the indication for resection exists between the contemporary guidelines. Furthermore, most of the current nomogram models for predicting malignant disease depend on endoscopic ultrasonography to evaluate the precise size of mural nodules. Thus, this study aimed to propose a model to predict malignant disease using variables from a noninvasive examination. We evaluated patients who underwent resection of pathologically confirmed IPMNs between November 2010 and December 2018 and had preoperative clinical data available for review. Based on binary multivariable logistic regression analysis, we devised a nomogram model to predict malignant IPMNs. The area under the receiver operating characteristics curve (AUC) was used to evaluate the discrimination power of the model.