CXCL3 belongs to the CXC-type chemokine family and is known to play a multifaceted role in various human malignancies. While its clinical significance and mechanisms of action in uterine cervical cancer (UCC) remain unclear. This investigation demonstrated that the UCC cell line HeLa expressed CXCL3, and strong expression of CXCL3 was detected in UCC tissues relative to nontumor tissues. In addition, CXCL3 expression was strongly correlated with CXCL5 expression in UCC tissues. In vitro, HeLa cells overexpressing CXCL3, HeLa cells treated with exogenous CXCL3 or treated with conditioned medium from WPMY cells overexpressing CXCL3, exhibited enhanced proliferation and migration activities. In agreement with these findings, CXCL3 overexpression was also associated with the generation of HeLa cell tumor xenografts in athymic nude mice. Subsequent mechanistic studies demonstrated that CXCL3 overexpressing influenced the expression of extracellular signal-regulated kinase (ERK) signaling pathway associated genes, including ERK1/2, Bcl-2, and Bax, whereas the CXCL3-induced proliferation and migration effects were attenuated by exogenous administration of the ERK1/2 blocker PD98059. The data of the current investigation support that CXCL3 appears to hold promise as a potential tumor marker and interference target for UCC. K E Y W O R D Scervical cancer, CXCL3, ERK, malignant behavior, upregulation
Background: To classify triple-negative breast cancer (TNBC) immunotyping using the public database, analyze the differences between subtypes in terms of clinical characteristics and explore the role and clinical significance of immune subtypes in TNBC immunotherapy.Methods: We downloaded TNBC data from the cBioPortal and GEO databases. The immune genes were grouped to obtain immune gene modules and annotate their biological functions. Log-rank tests and Cox regression were used to evaluate the prognosis of immune subtypes (IS). Drug sensitivity analysis was also performed for the differences among immune subtypes in immunotherapy and chemotherapy. In addition, dimension reduction analysis based on graph learning was utilized to reveal the internal structure of the immune system and visualize the distribution of patients.Results: Significant differences in prognosis were observed between subtypes (IS1, IS2, and IS3), with the best in IS3 and the worst in IS1. The sensitivity of IS3 to immunotherapy and chemotherapy was better than the other two subtypes. In addition, Immune landscape analysis found the intra-class heterogeneity of immune subtypes and further classified IS3 subtypes (IS3A and IS3B). Immune-related genes were divided into seven functional modules (The turquoise module has the worst prognosis). Five hub genes (RASSF5, CD8A, ICOS, IRF8, and CD247) were screened out as the final characteristic genes related to poor prognosis by low expression.Conclusions: The immune subtypes of TNBC were significantly different in prognosis, gene mutation, immune infiltration, drug sensitivity, and heterogeneity. We validated the independent role of immune subtypes in tumor progression and immunotherapy for TNBC. This study provides a new perspective for personalized immunotherapy and the prognosis evaluation of TNBC patients in the future.
BackgroundTBC1 domain family member 24 (TBC1D24) pathogenic mutations affect its binding to ARF6 and then result in severe impairment of neuronal development. However, there are no reports about the expression and function of TBC1D24 in cancer. The aim of the present study was to evaluate the effect of proliferation, migration, and invasion after silencing TBC1D24 expression in breast cancer MCF-7 cells, and to elucidate the potential mechanism of TBC1D24 in breast cancer.Material/MethodsThe expression of TBC1D24 in breast cancer tissues and the adjacent non-tumor tissues was determined by S-P immunohistochemistry. The malignant behavior, including proliferation, migration, and invasion ability, was determined after silencing TBC1D24 in breast cancer MCF-7 cells. The expression of IGF1R was determined after silencing TBC1D24. The expression of TBC1D24 and IGF1R was detected after transfecting miR-30a mimics or inhibitors. The effect of TBC1D24 on MCF-7 cells growth in vivo was evaluated by a tumor xenograft study.ResultsTBC1D24 expression was elevated and was associated with poor outcome in breast carcinoma. TBC1D24 high expression was significantly correlated with unfavorable OS and RFS for breast cancer patients (p<0.05). Silencing TBC1D24 inhibited the proliferation, migration, and invasion ability of MCF-7 cells. TBC1D24 and IGF1R expression were decreased when transfected with miR-30a mimics. However, TBC1D24 and IGF1R expression were increased when transfected with miR-30a inhibitors (p<0.05). Knockdown of TBC1D24 inhibited the expression of IGF1R, PI3K, and p-AKT (p<0.05). Knockdown of TBC1D24 abolished tumorigenicity of MCF-7 cells. The average volume and weight of tumors was lower after silencing TBC1D24 expression (P<0.05).ConclusionsSilencing TBC1D24 inhibited MCF-7 cells growth in vitro and in vivo. TBC1D24 promoted breast carcinoma growth through the IGF1R/PI3K/AKT pathway. TBC1D24 is a potential therapeutic target for breast cancer.
Multiple previous studies have demonstrated that the dysregulation of microRNAs (miRNAs) is implicated in the occurrence and development of pancreatic cancer. Therefore, a further characterisation of deregulated miRNAs in pancreatic cancer may provide novel insight into the oncogenesis and progression of pancreatic cancer, which may facilitate the identification of effective therapeutic targets for treating patients with this disease. In the present study, reverse transcription-quantitative polymerase chain reaction analysis demonstrated that the expression level of miRNA-584-5p (miR-584) was significantly decreased in pancreatic cancer tissues and cell lines. It was demonstrated that restoration of miR-584 expression significantly suppressed the proliferative and invasive ability of pancreatic cancer cells. Bioinformatics analysis predicted that cyclin D1 (CCND1) was a putative target of miR-584. Subsequent experiments demonstrated that CCND1 was a direct target gene of miR-584 in pancreatic cancer cells. Furthermore, the inhibition of CCND1 mimicked the suppressive effect of miR-584 overexpression in pancreatic cancer cells. The restoration of CCND1 expression significantly abolished the inhibitory effects of miR-584 overexpression on pancreatic cancer cells. Collectively, the present results demonstrated that miR-584 inhibited the development of pancreatic cancer by directly targeting CCND1, suggesting that this miRNA may represent a potential therapeutic target for this fatal disease.
Non-coding RNAs such as long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been found to be indispensable factors in carcinogenesis and cancer development. Numerous studies have explored the regulatory functions of these molecules and identified the synergistic interactions among lncRNAs or miRNAs, while those between lncRNAs and miRNAs remain to be investigated. In this study, we constructed and characterized an lncRNA–miRNA synergistic network following a four-step approach by integrating the regulatory pairs and expression profiles. The synergistic interactions with more shared regulatory mRNAs were found to have higher interactional intensity. Through the analysis of nodes in the network, we found that lncRNAs played roles that are more central and had similar synergistic interactions with their neighbors when compared with miRNAs. In addition, known colon adenocarcinoma (COAD)-related RNAs were found to be enriched in this synergistic network, with higher degrees, betweenness, and closeness. Finally, we proposed a risk score model to predict the clinical outcome for COAD patients based on two prognostic hub lncRNAs, MEG3 and ZEB1-AS1. Moreover, the hierarchical networks of these two lncRNAs could contribute to the understanding of the biological mechanism of tumorigenesis. For each lncRNA–miRNA interaction in the hub-related subnetwork and two hierarchical networks, we performed RNAup method to evaluate their binding energy. Our results identified two important lncRNAs with prognostic roles in colon cancer and dissected their regulatory mechanism involving synergistic interaction with miRNAs.
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