RGS1 and related genes as potential targets for immunotherapy in cervical cancer: computational biology and experimental validation

Cellular and molecular determinants of bacterial burden in leprosy granulomas revealed by single-cell multimodal omics

BACKGROUND

Which cell populations that determine the fate of bacteria in infectious granulomas remain unclear. Leprosy, a granulomatous disease with a strong genetic predisposition, caused by Mycobacterium leprae infection, exhibits distinct sub-types with varying bacterial load and is considered an outstanding disease model for studying host-pathogen interactions.

METHODS

We performed single-cell RNA and immune repertoire sequencing on 11 healthy controls and 20 patients with leprosy, and integrated single-cell data with genome-wide genetic data on leprosy. Multiplex immunohistochemistry, and in vitro and in vivo infection experiments were conducted to confirm the multimodal omics findings.

FINDINGS

Lepromatous leprosy (L-LEP) granulomas with high bacterial burden were characterised by exhausted CD8+ T cells, and high RGS1 expression in CD8+ T cells was associated with L-LEP. By contrast, tuberculoid leprosy (T-LEP) granulomas with low bacterial burden displayed enrichment in resident memory IFNG+ CD8+ T cells (CD8+ Trm) with high GNLY expression. This enrichment was potentially attributable to the communication between IL1B macrophages and CD8+ Trm via CXCL10-CXCR3 signalling. Additionally, IL1B macrophages in L-LEP exhibited anti-inflammatory phenotype, with high APOE expression contributing to high bacterial burden. Conversely, IL1B macrophages in T-LEP were distinguished by interferon-γ induced GBP family genes.

INTERPRETATION

The state of IL1B macrophages and functional CD8+ T cells, as well as the relationship between them, is crucial for controlling bacterial persistence within granulomas. These insights may indicate potential targets for host-directed immunotherapy in granulomatous diseases caused by mycobacteria and other intracellular bacteria.

FUNDING

The Key research and development program of Shandong Province (2021LCZX07), Natural Science Foundation of Shandong Province (ZR2023MH046), Youth Science Foundation Cultivation Funding Plan of Shandong First Medical University (Shandong Academy of Medical Sciences) (202201-123), National Natural Science Foundation of China (82471800, 82230107, 82273545, 82304039), the China Postdoctoral Science Foundation (2023M742162), Shandong Province Taishan Scholar Project (tspd20230608), Joint Innovation Team for Clinical & Basic Research (202410), Central guidance for local scientific and technological development projects of Shandong Province (YDZX2023058).

RGS1 and CREB5 are direct and common transcriptional targets of ZNF384-fusion proteins

BACKGROUND

ZNF384-fusion (Z-fusion) genes were recently identified in B-cell acute lymphoblastic leukemia (B-ALL) and are frequent in Japanese adult patients. The frequency is about 20% in those with Philadelphia chromosome-negative B-ALL. ZNF384 is a transcription factor and Z-fusion proteins have increased transcriptional activity; however, the detailed mechanisms of leukemogenesis of Z-fusion proteins have yet to be clarified.

METHODS

We established three transfectants of cell lines expressing different types of Z-fusion proteins, and analyzed their gene expression profile (GEP) by RNA-seq. We also analyzed the GEP of clinical ALL samples using our previous RNA-seq data of 323 Japanese ALL patients. We selected upregulated genes in both Z-fusion gene-expressing transfectants and Z-fusion gene-positive ALL samples, and investigated the binding of Z-fusion proteins to regulatory regions of the candidate genes by ChIP-qPCR.

RESULTS

We selected six commonly upregulated genes. After the investigation by ChIP-qPCR, we finally identified CREB5 and RGS1 as direct and common target genes. RGS1 is an inhibitor of CXCL12-CXCR4 signaling that is required for the homing of hematopoietic progenitor cells to the bone marrow microenvironment and development of B cells. Consistent with this, Z-fusion gene transfectants showed impaired migration toward CXCL12.

CONCLUSIONS

We identified CREB5 and RGS1 as direct and common transcriptional targets of Z-fusion proteins. The present results provide novel insight into the aberrant transcriptional regulation by Z-fusion proteins.

Single-cell view into the role of microbiota shaping host immunity in the larynx

Microbiota play a critical role in the development and training of host innate and adaptive immunity. We present the cellular landscape of the upper airway, specifically the larynx, by establishing a reference single-cell atlas, while dissecting the role of microbiota in cell development and function at single-cell resolution. We highlight the larynx's cellular heterogeneity with the identification of 16 cell types and 34 distinct subclusters. Our data demonstrate that commensal microbiota have extensive impact on the laryngeal immune system by regulating cell differentiation, increasing the expression of genes associated with host defense, and altering gene regulatory networks. We uncover macrophages, innate lymphoid cells, and multiple secretory epithelial cells, whose cell proportions and expressions vary with microbial exposure. These cell types play pivotal roles in maintaining laryngeal and upper airway health and provide specific guidance into understanding the mechanism of immune system regulation by microbiota in laryngeal health and disease.

Cervical extracellular matrix hydrogel optimizes tumor heterogeneity of cervical squamous cell carcinoma organoids

Cervical cancer, primarily squamous cell carcinoma, is the most prevalent gynecologic malignancy. Organoids can mimic tumor development in vitro, but current Matrigel inaccurately replicates the tissue-specific microenvironment. This limitation compromises the accurate representation of tumor heterogeneity. We collected para-cancerous cervical tissues from patients diagnosed with cervical squamous cell carcinoma (CSCC) and prepared uterine cervix extracellular matrix (UCEM) hydrogels. Proteomic analysis of UCEM identified several tissue-specific signaling pathways including human papillomavirus, phosphatidylinositol 3-kinase-AKT, and extracellular matrix receptor. Secreted proteins like FLNA, MYH9, HSPA8, and EEF1A1 were present, indicating UCEM successfully maintained cervical proteins. UCEM provided a tailored microenvironment for CSCC organoids, enabling formation and growth while preserving tumorigenic potential. RNA sequencing showed UCEM-organoids exhibited greater similarity to native CSCC and reflected tumor heterogeneity by exhibiting CSCC-associated signaling pathways including virus protein-cytokine, nuclear factor κB, tumor necrosis factor, and oncogenes EGR1, FPR1, and IFI6. Moreover, UCEM-organoids developed chemotherapy resistance. Our research provides insights into advanced organoid technology through native matrix hydrogels.

Endothelial cell dynamics in sepsis-induced acute lung injury and acute respiratory distress syndrome: pathogenesis and therapeutic implications

Sepsis, a prevalent critical condition in clinics, continues to be the leading cause of death from infections and a global healthcare issue. Among the organs susceptible to the harmful effects of sepsis, the lungs are notably the most frequently affected. Consequently, patients with sepsis are predisposed to developing acute lung injury (ALI), and in severe cases, acute respiratory distress syndrome (ARDS). Nevertheless, the precise mechanisms associated with the onset of ALI/ARDS remain elusive. In recent years, there has been a growing emphasis on the role of endothelial cells (ECs), a cell type integral to lung barrier function, and their interactions with various stromal cells in sepsis-induced ALI/ARDS. In this comprehensive review, we summarize the involvement of endothelial cells and their intricate interplay with immune cells and stromal cells, including pulmonary epithelial cells and fibroblasts, in the pathogenesis of sepsis-induced ALI/ARDS, with particular emphasis placed on discussing the several pivotal pathways implicated in this process. Furthermore, we discuss the potential therapeutic interventions for modulating the functions of endothelial cells, their interactions with immune cells and stromal cells, and relevant pathways associated with ALI/ARDS to present a potential therapeutic strategy for managing sepsis and sepsis-induced ALI/ARDS.

Unraveling the prognostic significance of RGS gene family in gastric cancer and the potential implication of RGS4 in regulating tumor-infiltrating fibroblast

Regulator of G-protein signaling (RGS) proteins are regulators of signal transduction mediated by G protein-coupled receptors (GPCRs). Current studies have shown that some molecules in the RGS gene family are related to the occurrence, development and poor prognosis of malignant tumors. However, the RGS gene family has been rarely studied in gastric cancer. In this study, we explored the mutation and expression profile of RGS gene family in gastric cancer, and evaluated the prognostic value of RGS expression. Then we established a prognostic model based on RGS gene family and performed functional analysis. Further studies showed that RGS4, as an independent prognostic predictor, may play an important role in regulating fibroblasts in the immune microenvironment. In conclusion, this study explores the value of RGS gene family in gastric cancer, which is of great significance for predicting the prognosis and guiding the treatment of gastric cancer.

PLAU and GREM1 are prognostic biomarkers for predicting immune response in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common malignant tumor. Identification of biomarkers and understanding their potential functions will facilitate the treatment and diagnosis in LUAD patients. The yellow module (cor = 0.31, P = 2e-6) was selected as the core module based on weighted gene co-expression network analysis (WGCNA) by integrating RNA-seq data and tumor stage. Two upregulated genes (PLAU and GREM1) in yellow module were identified to be biomarkers. Kaplan-Meier curve analysis displayed that high expression levels of them had a poor overall survival (OS). And, their high expression levels revealed higher tumor stage and relapse possibility in LUAD patients, and could be a prognostic parameter. Both biomarkers showed similar immune cell expression profiles in low- and high-expression groups. Strongly positive correlation between both biomarkers and biomarkers of tumor-infiltrating lymphocytes were also clarified in TCGA-LUAD cohort. Importantly, single gene GSEA showed that transcriptional mis-regulation in cancer and microRNAs in cancer were enriched in LUAD patients. Therefore, a miRNA-mRNA-transcription factors (TFs) co-expression regulatory networks was constructed for each biomarker, various miRNAs and TFs were related to PLAU and GREM1. Among which, 6 downstream TFs were overlapped genes for both biomarkers. Notably, 2 of these TFs (FOXF1 and TFAP2A) exhibited significantly abnormal expression levels. Among which, FOXF1 was downregulated and TFAP2A was upregulated in TCGA-LUAD cohort. Both TFs showed a significantly positive correlation with the expression level of PLAU. In conclusion, we identified 2 biomarkers related to immune response and achieved a good accuracy in predicting OS in patients with LUAD.

Regulator of G protein signaling-1 regulates immune infiltration and macrophage polarization in clear cell renal cell carcinoma

OBJECTIVE

To better understand how to clear cell renal cell cancer (ccRCC) is affected by the regulator of G protein signaling-1 (RGS1), its effect on immune infiltration, macrophage polarization, tumor proliferation migration, and to explore whether RGS1 may serve as a marker and therapeutic target for ccRCC.

PATIENTS AND METHODS

In this study, a total of 20 surgical specimens of patients with pathological diagnosis of ccRCC admitted to the Department of Urology of the Second Affiliated Hospital of Anhui Medical University from November 2021 to June 2022 were selected for pathological and protein testing, while the expression of RGS1 in tumors, immune infiltration, and macrophage polarization, particularly M2 macrophage linked to the development of tumor microenvironment (TME), were combined with TGCA database and GO analysis. We also further explored and studied the expression and function of RGS1 in TME, investigated how RGS1 affected tumor growth, migration, apoptosis, and other traits, and initially explored the signaling pathways and mechanisms that RGS1 may affect.

RESULTS

RGS1 was found to be expressed at higher quantities in ccRCC than in normal cells or tissues, according to bioinformatics analysis and preliminary experimental data from this work. Using the TCGA database and GO analysis to describe the expression of RGS1 in a range of tumors, it was found that ccRCC had a much higher level of RGS1 expression than other tumor types. The results of gene enrichment analysis indicated that overexpression of RGS1 may be associated with immune infiltration. The outcomes of in vitro tests revealed that RGS1 overexpression in ccRCC did not significantly alter the proliferation and migration ability of ccRCC, but RGS1 overexpression promoted apoptosis in ccRCC. By in vitro co-culture experiments, RGS1 overexpression inhibited M2 macrophage polarization and also suppressed the Jagged-1/Notch signaling pathway.

CONCLUSIONS

RGS1 is highly expressed in ccRCC, while overexpression of RGS1 may increase immune infiltration in the TME and reduce the polarization of M2 macrophages while promoting apoptosis in ccRCC.

Blood regulator of G protein signalling 1 as a potential prognostic biomarker in surgical nonsmall cell lung cancer patients: Correlation with clinical features and survival

INTRODUCTION

Regulator of G protein signalling 1 (RGS1) closely regulates malignant phenotypes and tumour immunity in several cancers, while its clinical value in nonsmall cell lung cancer (NSCLC) is by far rarely reported. Consequently, this study aimed to explore the linkage of blood RGS1 with clinical features and prognosis in surgical NSCLC patients.

METHODS

Two-hundred and ten surgical NSCLC patients were consecutively enrolled in this study, whose RGS1 in peripheral blood mononuclear cells was determined before treatment via reverse transcriptional-quantitative polymerase chain reaction. Additionally, the blood RGS1 was also collected from 30 healthy controls (HCs).

RESULTS

Blood RGS1 was increased in NSCLC patients compared with HCs (P < 0.001). Elevated blood RGS1 was related to lymph node (LYN) metastasis (P = 0.001), higher tumour-nodes-metastasis (TNM) stage (P = 0.004), neoadjuvant chemotherapy administration (P = 0.044), shortened accumulative disease-free survival (DFS) (P = 0.008) and overall survival (OS) (P = 0.013) in NSCLC patients. A multivariate Cox's regression analysis showed that blood RGS1 high expression could independently reflect shortened DFS (hazard ratio = 1.499, P = 0.023), whereas it could not independently predict OS (P > 0.050). Furthermore, blood RGS1 high expression was associated with shortened OS (P = 0.020) in patients with neoadjuvant therapy and with worse DFS (P = 0.028) and OS (P = 0.026) in patients with adjuvant therapy, while blood RGS1 was not linked with DFS or OS in patients without neoadjuvant or adjuvant therapy (all P > 0.050).

CONCLUSION

Elevated blood RGS1 correlates with LYN metastasis, neoadjuvant chemotherapy administration, worse DFS and OS, which might serve as a useful prognostic biomarker for surgical NSCLC patients.

Personalized tumor combination therapy optimization using the single-cell transcriptome

BACKGROUND

The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment.

METHODS

Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization.

RESULTS

We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples.

CONCLUSIONS

Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

RGS1 mediates renal interstitial fibrosis through activation of the inflammatory response

Renal interstitial fibrosis (RIF) is considered as a common pathway for all patients with chronic kidney disease (CKD) to progress to end-stage kidney disease (ESRD). The basic pathological manifestation is the increase of matrix component in the tubular interstitium, while the injury of tubular epithelial cells in the renal interstitium and the excessive accumulation of matrix will eventually lead to tubular atrophy and obstruction, loss of effective renal units, and finally impaired renal filtration function. The relevant mechanism of RIF remains unclear. The present study will investigate the function and relevant mechanism of RGS1 in RIF. The RIF-related microarrays GSE22459 and GSE76882 were downloaded and analyzed. Renal parenchymal atrophic calyx tissues were collected from clinical RIF patients. Cellular inflammation, fibrosis and animal RIF models were constructed using Lipopolysaccharide (LPS), TGF-β1 and unilateral ureteral occlusion (UUO). HE and Masson staining were performed to detect morphological alterations of renal tissue samples. qRT-PCR, Western blot and ELISA were carried out to detect the expression of relevant genes/proteins. RGS1 is a gene co-differentially expressed by GSE22459 and GSE76882. RGS1 expression was elevated in renal tissues of RIF patients, cells and animal RIF models. Knockdown of RGS1 inhibited renal cell inflammatory response, fibrosis and renal fibrosis in RIF mice. Overexpression of RGS1 plays the opposite role. Knockdown of RGS1 inhibited the inflammatory response in the RIF cell and mouse model. Targeting RGS1 might be a potential therapeutic strategy for RIF treatment.

Integrated single-cell and bulk RNA sequencing analysis identifies a neoadjuvant chemotherapy-related gene signature for predicting survival and therapy in breast cancer

Neoadjuvant chemotherapy (NAC) is a well-established treatment modality for locally advanced breast cancer (BC). However, it can also result in severe toxicities while controlling tumors. Therefore, reliable predictive biomarkers are urgently needed to objectively and accurately predict NAC response. In this study, we integrated single-cell and bulk RNA-seq data to identify nine genes associated with the prognostic response to NAC: NDRG1, CXCL14, HOXB2, NAT1, EVL, FBP1, MAGED2, AR and CIRBP. Furthermore, we constructed a prognostic risk model specifically linked to NAC. The clinical independence and generalizability of this model were effectively demonstrated. Additionally, we explore the underlying cancer hallmarks and microenvironment features of this NAC response-related risk score, and further assess the potential impact of risk score on drug response. In summary, our study constructed and validated a nine-gene signature associated with NAC prognosis, which was accomplished through the integration of single-cell and bulk RNA data. The results of our study are of crucial significance in the prediction of the efficacy of NAC in BC, and may have implications for the clinical management of this disease.

Function and regulation of RGS family members in solid tumours: a comprehensive review

G protein-coupled receptors (GPCRs) play a key role in regulating the homeostasis of the internal environment and are closely associated with tumour progression as major mediators of cellular signalling. As a diverse and multifunctional group of proteins, the G protein signalling regulator (RGS) family was proven to be involved in the cellular transduction of GPCRs. Growing evidence has revealed dysregulation of RGS proteins as a common phenomenon and highlighted the key roles of these proteins in human cancers. Furthermore, their differential expression may be a potential biomarker for tumour diagnosis, treatment and prognosis. Most importantly, there are few systematic reviews on the functional/mechanistic characteristics and clinical application of RGS family members at present. In this review, we focus on the G-protein signalling regulator (RGS) family, which includes more than 20 family members. We analysed the classification, basic structure, and major functions of the RGS family members. Moreover, we summarize the expression changes of each RGS family member in various human cancers and their important roles in regulating cancer cell proliferation, stem cell maintenance, tumorigenesis and cancer metastasis. On this basis, we outline the molecular signalling pathways in which some RGS family members are involved in tumour progression. Finally, their potential application in the precise diagnosis, prognosis and treatment of different types of cancers and the main possible problems for clinical application at present are discussed. Our review provides a comprehensive understanding of the role and potential mechanisms of RGS in regulating tumour progression. Video Abstract.

Prognostic value of RGS1 and mTOR Immunohistochemical expression in Egyptian multiple myeloma patients; A single center study

INTRODUCTION

Prognostic factors in plasma cell myeloma were proved to be related to signaling pathways and associated transcription factors. RGS1 and mTOR were known to play an important role in the pathogenesis of multiple myeloma. The aim of the study was to evaluate the expression and the prognostic value of RGS1 and mTOR and their relation to clinical as well as other diagnostic criteria in multiple myeloma.

PATIENTS AND METHODS

The present study included 44 denovo Myeloma patients, recruited from the Medical Oncology Department, National Cancer Institute, Cairo University. Detection of RGS1 and mTOR expression was performed using Immunohistochemical staining on bone marrow biopsy sections.

RESULTS

The median age was 51 years with male to female ratio 1.58:1. There was a positive highly statistically significant correlation between RGS1 and mTOR among all studied cases (p value <0.001). Regarding their prognostic value, there was a highly statistically significant association of the expression levels of RGS1 and mTOR with treatment response (p <0.001). Finally, there was a significant influence of RGS1 and mTOR on overall survival probability (p value <0.001 and <0.002 respectively) with better survival for those having low expression.

CONCLUSION

RGS1 and mTOR were suggested as poor prognostic markers in MM patients, being associated with lower response rate and inferior OS. We recommend considering RGS1 and mTOR as one of the prognostic criteria in different risk stratification and staging classifications. Further trials for RGS1 and mTOR targeting in multiple myeloma are recommended.

Enrichr-KG: bridging enrichment analysis across multiple libraries

Gene and protein set enrichment analysis is a critical step in the analysis of data collected from omics experiments. Enrichr is a popular gene set enrichment analysis web-server search engine that contains hundreds of thousands of annotated gene sets. While Enrichr has been useful in providing enrichment analysis with many gene set libraries from different categories, integrating enrichment results across libraries and domains of knowledge can further hypothesis generation. To this end, Enrichr-KG is a knowledge graph database and a web-server application that combines selected gene set libraries from Enrichr for integrative enrichment analysis and visualization. The enrichment results are presented as subgraphs made of nodes and links that connect genes to their enriched terms. In addition, users of Enrichr-KG can add gene-gene links, as well as predicted genes to the subgraphs. This graphical representation of cross-library results with enriched and predicted genes can illuminate hidden associations between genes and annotated enriched terms from across datasets and resources. Enrichr-KG currently serves 26 gene set libraries from different categories that include transcription, pathways, ontologies, diseases/drugs, and cell types. To demonstrate the utility of Enrichr-KG we provide several case studies. Enrichr-KG is freely available at: https://maayanlab.cloud/enrichr-kg.

TIME Is Ticking for Cervical Cancer

Cervical cancer (CC) is a major health problem among reproductive-age females and comprises a leading cause of cancer-related deaths. Human papillomavirus (HPV) is the major risk factor associated with CC incidence. However, lifestyle is also a critical factor in CC pathogenesis. Despite HPV vaccination introduction, the incidence of CC is increasing worldwide. Therefore, it becomes critical to understand the CC tumor immune microenvironment (TIME) to develop immune cell-based vaccination and immunotherapeutic approaches. The current article discusses the immune environment in the normal cervix of adult females and its role in HPV infection. The subsequent sections discuss the alteration of different immune cells comprising CC TIME and their targeting as future therapeutic approaches.

Immune-related biomarkers predict the prognosis and immune response of breast cancer based on bioinformatic analysis and machine learning

Breast cancer (BC) is the malignancy with the highest mortality rate among women, identification of immune-related biomarkers facilitates precise diagnosis and improvement of the survival rate in early-stage BC patients. 38 hub genes significantly positively correlated with tumor grade were identified based on weighted gene coexpression network analysis (WGCNA) by integrating the clinical traits and transcriptome analysis. Six candidate genes were screened from 38 hub genes basing on least absolute shrinkage and selection operator (LASSO)-Cox and random forest. Four upregulated genes (CDC20, CDCA5, TTK and UBE2C) were identified as biomarkers with the log-rank p < 0.05, in which high expression levels of them showed a poor overall survival (OS) and recurrence-free survival (RFS). A risk model was finally constructed using LASSO-Cox regression coefficients and it possessed superior capability to identify high risk patients and predict OS (p < 0.0001, AUC at 1-, 3- and 5-years are 0.81, 0.73 and 0.79, respectively). Decision curve analysis demonstrated risk score was the best prognostic predictor, and low risk represented a longer survival time and lower tumor grade. Importantly, multiple immune cell types and immunotherapy targets were observed increase in expression levels in high-risk group, most of which were significantly correlated with four genes. In summary, the immune-related biomarkers could accurately predict the prognosis and character the immune responses in BC patients. In addition, the risk model is conducive to the tiered diagnosis and treatment of BC patients.

RGS proteins and their roles in cancer: friend or foe?

As negative modulators of G-protein-coupled receptors (GPCRs) signaling, regulators of G protein signaling (RGS) proteins facilitate various downstream cellular signalings through regulating kinds of heterotrimeric G proteins by stimulating the guanosine triphosphatase (GTPase) activity of G-protein α (Gα) subunits. The expression of RGS proteins is dynamically and precisely mediated by several different mechanisms including epigenetic regulation, transcriptional regulation -and post-translational regulation. Emerging evidence has shown that RGS proteins act as important mediators in controlling essential cellular processes including cell proliferation, survival -and death via regulating downstream cellular signaling activities, indicating that RGS proteins are fundamentally involved in sustaining normal physiological functions and dysregulation of RGS proteins (such as aberrant expression of RGS proteins) is closely associated with pathologies of many diseases such as cancer. In this review, we summarize the molecular mechanisms governing the expression of RGS proteins, and further discuss the relationship of RGS proteins and cancer.

Identification of DNA methylation-regulated differentially expressed genes in RA by integrated analysis of DNA methylation and RNA-Seq data

OBJECTIVE

To identify novel DNA methylation-regulated differentially expressed genes (MeDEGs) in RA by integrated analysis of DNA methylation and RNA-Seq data.

METHODS

The transcription and DNA methylation profiles of 9 RA and 15 OA synovial tissue were generated by RNA-Seq and Illumina 850K DNA methylation BeadChip. Gene set enrichment analysis (GSEA) and Weighted gene co-expression network analysis (WGCNA) were used to analyze methylation-regulated expressed genes by R software. The differentially expressed genes (DEGs), differentially methylated probes (DMPs), differentially methylated genes (DMGs) were analyzed by DESeq and ChAMP R package. The functional correlation of MeDEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction (PPI) network of MeDEGs was constructed by STRING and Reactome FI Cytoscape Plugin. Correlation analysis between methylation level and mRNA expression was conducted with R software.

RESULTS

A total of 17,736 genes, 25,578 methylated genes and 755,852 methylation probes were detected. A total of 16,421 methylation-regulated expressed genes were obtained. The GSEA showed that these genes are associated with activation of immune response, adaptive immune response, Inflammatory response in C5 (ontology gene sets). For KEGG analysis, these genes are associated with rheumatoid arthritis, NF-kappa B signaling pathway, T cell receptor signaling pathway. The WGCNA showed that the turquoise module exhibited the strongest correlation with RA (R = 0.78, P = 1.27 × 10^- 05), 660 genes were screened in the turquoise module. A total of 707 MeDEGs were obtained. GO analysis showed that MeDEGs were enriched in signal transduction, cell adhesion for BP, enriched in plasma membrane, integral component of membrane for CC, and enriched in identical protein binding, calcium ion binding for MF. The KEGG pathway analysis showed that the MeDEGs were enriched in calcium signaling pathway, T cell receptor signaling pathway, NF-kappa B signaling pathway, Rheumatoid arthritis. The PPI network containing 706 nodes and 882 edges, and the enrichment p value < 1.0 × 10^- 16. With Cytoscape, based on the range of more than 10 genes, a total of 8 modules were screened out. Spearman correlation analysis showed RGS1(cg10718027), RGS1(cg02586212), RGS1(cg10861751) were significantly correlated with RA.

CONCLUSIONS

RGS1 can be used as novel methylated biomarkers for RA.