Expression and Functions of Formyl Peptide Receptor 1 in Drug-Resistant Bladder Cancer

Construction of monocyte-related prognosis model based on comprehensive analysis of bulk RNA-seq and single-cell RNA-seq in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is a common subtype of ovarian cancer with high mortality. Finding a new biomarker is useful for the diagnosis and treatment of HGSOC. The scRNA and bulk RNA data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The monocyte-related clusters were identified and annotated by Seruat and SingleR package. The Kaplan-Meier and receiver operating characteristic curve was used to determine the prognosis. The differentially expressed genes were determined by limma. The single sample Gene Set Enrichment Analysis, Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes were used for the enrichment function. The correlation between drug activity and gene expression was assessed by rcellminer and rcellminer Data package. We identified 9 cell types and obtained 37 differentially expressed marker genes of monocyte. A2M, CD163, and FPR1 were screened out as hub genes and used to construct risk model in HGSOC through univariate and multivariate cox analysis. Single sample Gene Set Enrichment Analysis showed risk score was related to B cell and T cell signal pathways, and further analysis showed most immune checkpoint genes expressions were upregulated in high-risk score group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis exhibited that hub gene related genes were involved in signal receptor binding and cytokine-cytokine interaction. Low A2M expression and high expression of CD163 and FPR1 were associated with poor prognosis. Gene Set Enrichment Analysis revealed that A2M promoted tumor development through enhancing immune cell related signal pathways, while CD163 and FPR1 inhibited tumor development through activated carcinogenic signal pathways. Drug sensitivity analysis revealed that these hub genes could be potential therapeutic targets for the treatment of HGSOC. We constructed a risk model for the overall survival and explored the potential mechanism of monocyte in HGSOC.

Advances in the bladder cancer research using 3D culture models

Bladder cancer represents the most common malignancy of the urinary system, posing a significant threat to patients' life. Animal models and two-dimensional (2D) cell cultures, among other traditional models, have been used for years to study various aspects of bladder cancer. However, these methods are subject to various limitations when mimicking the tumor microenvironment in vivo, thus hindering the further improvement of bladder cancer treatments. Recently, three-dimensional (3D) culture models have attracted extensive attention since they overcome the shortcomings of their traditional counterparts. Most importantly, 3D culture models more accurately reproduce the tumor microenvironment in the human body because they can recapitulate the cell-cell and cell-extracellular matrix interactions. 3D culture models can thereby help us gain deeper insight into the bladder cancer. The 3D culture models of tumor cells can extend the culture duration and allow for co-culturing with different cell types. Study of patient-specific bladder cancer mutations and subtypes is made possible by the ability to preserve cells isolated from particular patients in 3D culture models. It will be feasible to develop customized treatments that target relevant signaling pathways or biomarkers. This article reviews the development, application, advantages, and limitations of traditional modeling systems and 3D culture models used in the study of bladder cancer and discusses the potential application of 3D culture models.

An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

To explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.

An Exploration of the Tumor Microenvironment Identified a Novel Five-Gene Model for Predicting Outcomes in Bladder Cancer

Bladder cancer (BC) is one of the top ten most common cancer types globally, accounting for approximately 7% of all male malignancies. In the last few decades, cancer research has focused on identifying oncogenes and tumor suppressors. Recent studies have revealed that the interplay between tumor cells and the tumor microenvironment (TME) plays an important role in the initiation and development of cancer. However, the current knowledge regarding its effect on BC is scarce. This study aims to explore how the TME influences the development of BC. We focused on immune and stromal components, which represent the major components of TME. We found that the proportion of immune and stromal components within the TME was associated with the prognosis of BC. Furthermore, based on the scores of immune and stromal components, 811 TME-related differentially expressed genes were identified. Three subclasses with distinct biological features were divided based on these TME-genes. Finally, five prognostic genes were identified and used to develop a prognostic prediction model for BC patients based on TME-related genes. Additionally, we validated the prognostic value of the five-gene model using three independent cohorts. By further analyzing features based on the five-gene signature, higher CD8+ T cells, higher tumor mutational burden, and higher chemosensitivity were found in the low-risk group, which presented a better prognosis. In conclusion, our exploration comprehensively analyzed the TME and identified TME-related prognostic genes for BC, providing new insights into potential therapeutic targets.

Emodin enhances cisplatin sensitivity in non-small cell lung cancer through Pgp downregulation

Cisplatin resistance is one of the main causes of chemotherapy failure and tumor progression in non-small cell lung cancer (NSCLC). Emodin has been demonstrated to induce NSCLC cell apoptosis and act as a potential cancer therapeutic agent. However, whether emodin could affect NSCLC cell sensitivity toward cisplatin remains unclear. The present study aimed to determine the effect of emodin and cisplatin combination on the chemosensitivity of NSCLC cells. A549 and H460 cells were treated with different concentrations of cisplatin and/or emodin. Cell Counting Kit-8, fluorescence microscopy, immunofluorescence assays and flow cytometry were used to determine cell proliferation, drug efflux, DNA damage level and cell apoptosis, respectively. P-glycoprotein (Pgp) and multidrug resistance-associated protein 1 (MRP1) expression was detected by western blotting. The results demonstrated that emodin and cisplatin inhibited the proliferation of A549 and H460 cells. Furthermore, emodin inhibited the drug efflux in A549 and H460 cells in a dose-dependent manner. In addition, emodin enhanced cisplatin-induced apoptosis and DNA damage in A549 and H460 cells. Emodin also decreased Pgp expression in A549 and H460 cells in a dose-dependent manner; however, it had no effect on MRP1 expression. Taken together, the results from the present study demonstrated that emodin can increase A549 and H460 cell sensitivity to cisplatin by inhibiting Pgp expression. Emodin may therefore be considered as an effective adjuvant for cisplatin treatment.

The G-Protein Coupled Formyl Peptide Receptors and Their Role in the Progression of Digestive Tract Cancer

Chronic inflammation is a causative factor of many cancers, although it originally acts as a protective host response to the loss of tissue homeostasis. Many inflammatory conditions predispose susceptible cells, most of which are of epithelial origin, to neoplastic transformation. There is a close correlation between digestive tract (DT) cancer and chronic inflammation, such as esophageal adenocarcinoma associated with Barrett’s esophagus, helicobacter pylori infection as the cause of stomach cancer, hepatitis leading to liver cirrhosis and subsequent cancer, and colon cancer linking to inflammatory bowel diseases and schistosomiasis. A prominent feature of malignant transformation of DT tract epithelial cells is their adoption of somatic gene mutations resulting in abnormal expression of proteins that endow the cells with unlimited proliferation as well as increased motility and invasive capabilities. Many of these events are mediated by Gi-protein coupled chemoattractant receptors (GPCRs) including formyl peptide receptors (FPRs in human, Fprs in mice). In this article, we review the current understanding of FPRs (Fprs) and their function in DT cancer types as well as their potential as therapeutic targets.

Application of small molecule FPR1 antagonists in the treatment of cancers

The formylpeptide receptor-1 (FPR1) is a member of the chemotactic GPCR-7TM formyl peptide receptor family, whose principle function is in trafficking of various leukocytes into sites of bacterial infection and inflammation. More recently, FPR1 has been shown to be expressed in different types of cancer and in this context, plays a significant role in their expansion, resistance and recurrence. ICT12035 is a selective and potent (30 nM in calcium mobilisation assay) small molecule FPR1 antagonist. Here, we demonstrate the efficacy of ICT12035, in a number of 2D and 3D proliferation and invasion in vitro assays and an in vivo model. Our results demonstrate that targeting FPR1 by a selective small molecule antagonist, such as ICT12035, can provide a new avenue for the treatment of cancers.

LLCLPLDA: a novel model for predicting lncRNA-disease associations

Long noncoding RNAs play a significant role in the occurrence of diseases. Thus, studying the relationship prediction between lncRNAs and disease is becoming more popular. Researchers hope to determine effective treatments by revealing the occurrence and development of diseases at the molecular level. However, the traditional biological experimental way to verify the association between lncRNAs and disease is very time-consuming and expensive. Therefore, we developed a method called LLCLPLDA to predict potential lncRNA-disease associations. First, locality-constrained linear coding (LLC) is leveraged to project the features of lncRNAs and diseases to local-constraint features, and then, a label propagation (LP) strategy is used to mix up the initial association matrix and the obtained features of lncRNAs and diseases. To demonstrate the performance of our method, we compared LLCLPLDA with five methods in the leave-one-out cross-validation and fivefold cross-validation scheme, and the experimental results show that the proposed method outperforms the other five methods. Additionally, we conducted case studies on three diseases: cervical cancer, gliomas, and breast cancer. The top five predicted lncRNAs for cervical cancer and gliomas were verified, and four of the five lncRNAs for breast cancer were also confirmed.