BackgroundCircadian rhythm is an internal timing system generated by circadian-related genes (CRGs). Disruption in this rhythm has been associated with a heightened risk of breast cancer (BC) and regulation of the immune microenvironment of tumors. This study aimed to investigate the clinical significance of CRGs in BC and the immune microenvironment.MethodsCRGs were identified using the GeneCards and MSigDB databases. Through unsupervised clustering, we identified two circadian-related subtypes in patients with BC. We constructed a prognostic model and nomogram for circadian-related risk scores using LASSO and Cox regression analyses. Using multi-omics analysis, the mutation profile and immunological microenvironment of tumors were investigated, and the immunotherapy response in different groups of patients was predicted based on their risk strata.ResultsThe two circadian-related subtypes of BC that were identified differed significantly in their prognoses, clinical characteristics, and tumor immune microenvironments. Subsequently, we constructed a circadian-related risk score (CRRS) model containing eight signatures (SIAH2, EZR, GSN, TAGLN2, PRDX1, MCM4, EIF4EBP1, and CD248) and a nomogram. High-risk individuals had a greater burden of tumor mutations, richer immune cell infiltration, and higher expression of immune checkpoint genes, than low-risk individuals, indicating a "hot tumor" immune phenotype and a more favorable treatment outcome.ConclusionsTwo circadian-related subtypes of BC were identified and used to establish a CRRS prognostic model and nomogram. These will be valuable in providing guidance for forecasting prognosis and developing personalized treatment plans for BC.
The JAK-STAT signaling pathway is a common pathway of many cytokine signal transductions, closely related to cell proliferation, apoptosis, differentiation, and inflammatory response. It is essential for inhibiting the inflammatory response, initiating innate immunity, and coordinating adaptive immune mechanisms. Owing to the nature of this pathway and its potential cross-epitopes with multiple alternative pathways, the long-term efficacy of monotherapy-based adaptive targeting therapy is limited, and the majority of drugs targeting STATs are still in the preclinical phase. Meanwhile, curcumin, quercetin, and several kinds of plant polyphenol chemicals play roles in multiple sites of the JAK-STAT pathway to suppress abnormal activation. Polyphenol compounds have shown remarkable effects by acting on the JAK-STAT pathway in anti-inflammatory, antitumor, and cardiovascular disease control. This review summarizes the pharmacological effects of more than 20 kinds of phytochemicals on JAK-STAT signaling pathway according to the chemical structure of polyphenolic phytochemicals.
Abstract Background : There are difffferences in survival between high-and low-grade Upper Tract Urothelial Carcinoma (UTUC). Our study aimed to develop a nomogram to predict overall survival (OS) of patients with high- and low- grade UTUC after tumor resection, and to explore the difffference between high-and low-grade patients. Methods : Patients confifirmed to have UTUC between 2004 and 2015 were selected from the Surveillance, Epidemiology and End Results (SEER) database. The UTUCs were identifified and classifified as high- and low-grade, and 1-, 3-and 5-year nomograms were established. The nomogram was then validated using the Chinese multicenter dataset (patients diagnosed in Shandong, China between January 2010 and October 2020). Findings : In the high-grade UTUC patients, nine important factors related to survival after tumor resection were identifified to construct nomogram. The ability of the model to distinguish between UTUC grades was verifified using two datasets (internal validation dataset, C index(95% CI):0.729[0.707-0.754];Chinese multicenter validation dataset: C index(95% CI):0.763[0.656-0.869]).On the other hand, Two independent predictors were identifified to construct nomogram of low-grade UTUC. The C index was 0.714 (95% CI: 0.671-0.758) for the training set,0.731(95% CI:0.670-0.791) for the internal validation dataset, and 0.825 (95% CI:0.689-1.00) for the Chinese multicenter dataset. Encouragingly, the nomogram was clinically useful and had a good discriminative ability to identify patients at high risk. Interpretation : We constructed a nomogram and a corresponding risk classifification system predicting the OS of patients with an initial diagnosis of high-and low-grade UTUC.
The objective of this study was the development of a gene/protein interaction network for primary myelofibrosis based on gene expression, and the enrichment analysis of KEGG pathways underlying the molecular complexes in this network. To achieve this, genes involved in primary myelofibrosis were selected from the OMIM database. A gene/protein interaction network for primary myelofibrosis was obtained through Cytoscape with the literature mining performed using the Agilent Literature Search plugin. The molecular complexes in the network were detected by ClusterViz plugin and KEGG pathway enrichment of molecular complexes was performed using DAVID online. We found 75 genes associated with primary myelofibrosis in the OMIM database. The gene/protein interaction network of primary myelofibrosis contained 608 nodes, 2086 edges, and 4 molecular complexes with a correlation integral value greater than 4. Molecular complexes involved in KEGG pathways are related to cytokine regulation, immune function regulation, ECM-receptor interaction, focal adhesion, actin cytoskeleton regulation, cell adhesion molecules, and other biological behavior of tumors, which can provide a reliable direction for the treatment of primary myelofibrosis and the bioinformatic foundation for further understanding the molecular mechanisms of this disease.
Due to the unique characteristics of breast cancer initiation sites and significant alterations in tumor metabolism, breast cancer cells rely on lipid metabolic reprogramming to effectively regulate metabolic programs during the disease progression cascade.This adaptation enables them to meet the energy demands required for proliferation, invasion, metastasis, and responses to signaling molecules in the breast cancer microenvironment.In this review, we comprehensively examined the distinctive features of lipid metabolic reprogramming in breast cancer and elucidated the underlying mechanisms driving aberrant behavior of tumor cells.Additionally, we emphasize the potential role and adaptive changes in lipid metabolism within the breast cancer microenvironment, while summarizing recent preclinical studies.Overall, precise control over lipid metabolism rewiring and understanding of plasticity within the breast cancer microenvironment hold promising implications for developing targeted treatment strategies against this disease.Therefore, interventions targeting the lipid metabolism in breast cancer may facilitate innovative advancements in clinical applications.
Additional file 5. All relevant methylated sites of the five methylation-driven genes obtained from the TCGA database. (1–16) methylated sites of the gene CCDC181; (17–33) methylated sites of the gene ELF3; (34–47) methylated sites of the gene KLHDC9; (48) methylated site of the gene PLAU; (49–57) methylated sites of the gene S1PR1.
Breast cancer (BRCA) has traditionally been considered as having poor immunogenicity and is characterized by relatively low tumor mutational burden (TMB). Improving immunogenicity may improve the response to clinical immunotherapy of BRCA. However, the relationship between TMB, immune infiltration, and prognosis in BRCA remains unclear. We aimed to explore their interrelations and potential biomarkers. In this study, based on somatic mutation data of BRCA from The Cancer Genome Atlas (TCGA), patients were categorized into high and low TMB groups utilizing the TMB values. CIBERSOFT algorithm indicated significant infiltration of activated partial immune cells in high TMB group. Besides, ADRB1 had been identified as a prognosis-related immune gene in the mutant genes by the combination of the ImmPort database and the univariate Cox analysis. ADRB1 mutation was associated with lower TMB and manifested a satisfactory clinical prognosis. Various database applications (Gene Set Enrichment Analysis, Tumor IMmune Estimation Resource, Connectivity Map, KnockTF) supported the selection of treatment strategies targeting ADRB1. In conclusion, TMB was not an independent prognostic factor for BRCA and high TMB was more likely to activate a partial immune response. ADRB1 was identified as a potential biomarker and may provide new insights for co-therapy of BRCA.
Growing evidence has shown that a large number of miRNAs are abnormally expressed in cervical cancer (CC) tissues and play irreplaceable roles in tumorigenesis, progression, and metastasis. This study aimed to identify new biomarkers and pivotal genes associated with CC prognosis through comprehensive bioinformatics analysis. At first, the data of gene expression microarray (GSE30656) was downloaded from GEO database and differential miRNAs were obtained. Additionally, 4 miRNAs associated with the survival time of patients with CC were screened through TCGA differential data analysis, Kaplan-Meier, and Landmark analysis. Among them, the low expression of miR-188 and high expression of miR-223 correlated with the short survival of CC patients, while the down-regulation of miR-99a and miR-125b was closely related to the 5-year survival rate of patients. Then, based on the correspondence between the differentially expressed genes (DEGs) in CC from the TCGA data and the 4 miRNAs target genes, 58 target genes were screened to perform the analysis of function enrichment and the visualization of protein-protein interaction (PPI) networks. The seven pivotal genes of the PPI network as the target genes of four miRNAs related to prognosis, they were directly or indirectly involved in the development of CC. In this study, based on high-throughput data mining, differentially expressed miRNAs and related target genes were analyzed to provide an effective bioinformatics basis for further understanding of the pathogenesis and prognosis of CC. And the results may be a promising biomarker for the early screening of high-risk populations and early diagnosis of cervical cancer.
Immune checkpoint inhibitors targeting the programmed cell death protein 1 (PD‑1)/programmed death ligand 1 (PD‑L1) axis have achieved marked and durable efficacy in patients with different solid tumors and have improved their survival. However, the presence of primary or acquired resistance to immune checkpoint blockades results in only a small fraction of patients benefiting from the treatment. An increasing number of preclinical studies have reported that PD‑L1 expression in tumor cells is involved in a number of epigenetic changes, including histone modifications, non‑coding RNA regulation and DNA methylation. In addition, multiple epigenetic targeting drugs have been demonstrated to directly or indirectly interfere with PD‑L1 expression in various cancer models. This provides opportunities to better characterize the regulatory mechanisms of PD‑L1 expression and explore novel therapeutic strategies to improve immunosuppressant response rates and overcome drug resistance. The present review focuses on the latest findings and evidence on the epigenetic mechanism regulating PD‑L1 expression and discusses the biological and clinical implications of this regulatory mechanism in solid tumors. A rational combination of epigenetic regulation and PD‑1/PD‑L1 axis blockade may improve the prognosis of patients with solid tumors.
// Cun Liu 1,* , Lu Wang 1,* Jinhui Tian 2 , Lijuan Liu 3 , Linxiang Guo 4 , Guowen Ge 5 , Liang Zheng 6 , Fubin Feng 3 , Jinmei Zhang 7 , Tingting Zhang 1 and Changgang Sun 3,8 1 College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China 2 Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, PR China 3 Department of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong Province, PR China 4 School of Foreign Language Education, Qingdao University, Qingdao, Shandong, PR China 5 Clinical College, Weifang Medical University, Weifang, Shandong, PR China 6 Department of Cardiovascular Medicine, Research Center for Translational Medicine, Dongfang Hospital, Tongji University, Shanghai, PR China 7 Department of Endocrinology, Weifang Traditional Chinese Hospital, Weifang, Shandong, PR China 8 Department of Oncology, Affilited Hospital of Weifang Medical University, Weifang, Shandong, PR China * Cun Liu and Lu Wang contributed equally to this paper and are co-first authors Correspondence to: Changgang Sun, email: zhongliuyike@163.com Keywords : breast cancer; Parkinson’s disease; meta-analysis; risk Received: October 11, 2017 Accepted: December 05, 2017 Epub: January 12, 2018 Abstract Objective: We performed a meta-analysis to explore the association between breast cancer and Parkinson’s disease (PD). Methods: Specific literature searches were performed systematically using PubMed, Cochrane Library and EMBASE. Studies about the related risk estimates of breast cancer and PD were included in the meta-analysis. Results: A total of 22 sets of research data from 16 studies were analyzed. The combined odds ratio (OR) of the results was 1.13 (95% CI: 1.09–1.17). When stratified by PD diagnosis time, the ORs for the occurrence of breast cancer before and after PD diagnosis were 0.99 (95% CI: 0.89–1.09) and 1.15 (95% CI: 1.10–1.20). Subgroup analysis showed that the ORs for the cohort studies and for Caucasians were 1.13 (95% CI: 1.09,1.08) and 1.13 (95% CI: 1.09–1.17), respectively. No statistically significant risk estimates were found for studies in Asian and mixed populations as well as for case-control studies ( P > 0.05). Conclusion: The current evidence demonstrates a positive correlation between breast cancer and PD, especially following a diagnosis of PD and in Caucasians. Further studies are needed to determine the pathophysiologic mechanisms of this relationship.
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