MicroRNA-376b-3p targets RGS1 mRNA to inhibit proliferation, metastasis, and apoptosis in osteosarcoma

The general transcription factor TFIIB is a target for transcriptome control during cellular stress and viral infection

Many stressors, including viral infection, induce a widespread suppression of cellular RNA polymerase II (RNAPII) transcription, yet the mechanisms underlying transcriptional repression are not well understood. Here we find that a crucial component of the RNA polymerase II holoenzyme, general transcription factor IIB (TFIIB), is targeted for post-translational turnover by two pathways, each of which contribute to its depletion during stress. Upon DNA damage, translational stress, apoptosis, or replication of the oncogenic Kaposi's sarcoma-associated herpesvirus (KSHV), TFIIB is cleaved by activated caspase-3, leading to preferential downregulation of pro-survival genes. TFIIB is further targeted for rapid proteasome-mediated turnover by the E3 ubiquitin ligase TRIM28. KSHV counteracts proteasome-mediated turnover of TFIIB, thereby preserving a sufficient pool of TFIIB for transcription of viral genes. Thus, TFIIB may be a lynchpin for transcriptional outcomes during stress and a key target for nuclear replicating DNA viruses that rely on host transcriptional machinery.

Significance Statement

Transcription by RNA polymerase II (RNAPII) synthesizes all cellular protein-coding mRNA. Many cellular stressors and viral infections dampen RNAPII activity, though the processes underlying this are not fully understood. Here we describe a two-pronged degradation strategy by which cells respond to stress by depleting the abundance of the key RNAPII general transcription factor, TFIIB. We further demonstrate that an oncogenic human gammaherpesvirus antagonizes this process, retaining enough TFIIB to support its own robust viral transcription. Thus, modulation of RNAPII machinery plays a crucial role in dictating the outcome of cellular perturbation.

Aberrant non-canonical NF-κB signalling reprograms the epigenome landscape to drive oncogenic transcriptomes in multiple myeloma

In multiple myeloma, abnormal plasma cells establish oncogenic niches within the bone marrow by engaging the NF-κB pathway to nurture their survival while they accumulate pro-proliferative mutations. Under these conditions, many cases eventually develop genetic abnormalities endowing them with constitutive NF-κB activation. Here, we find that sustained NF-κB/p52 levels resulting from such mutations favours the recruitment of enhancers beyond the normal B-cell repertoire. Furthermore, through targeted disruption of p52, we characterise how such enhancers are complicit in the formation of super-enhancers and the establishment of cis-regulatory interactions with myeloma dependencies during constitutive activation of p52. Finally, we functionally validate the pathological impact of these cis-regulatory modules on cell and tumour phenotypes using in vitro and in vivo models, confirming RGS1 as a p52-dependent myeloma driver. We conclude that the divergent epigenomic reprogramming enforced by aberrant non-canonical NF-κB signalling potentiates transcriptional programs beneficial for multiple myeloma progression.

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.

Immune activity score to assess the prognosis, immunotherapy and chemotherapy response in gastric cancer and experimental validation

Background

Gastric cancer (GC) is an extremely heterogeneous malignancy with a complex tumor microenvironment (TME) that contributes to unsatisfactory prognosis.

Methods

The overall activity score for assessing the immune activity of GC patients was developed based on cancer immune cycle activity index in the Tracking Tumor Immunophenotype (TIP). Genes potentially affected by the overall activity score were screened using weighted gene co-expression network analysis (WGCNA). Based on the expression profile data of GC in The Cancer Genome Atlas (TCGA) database, COX analysis was applied to create an immune activity score (IAS). Differences in TME activity in the IAS groups were analyzed. We also evaluated the value of IAS in estimating immunotherapy and chemotherapy response based on immunotherapy cohort. Gene expression in IAS model and cell viability were determined by real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) and Cell Counting Kit-8 (CCK-8) assay, respectively.

Results

WGCAN analysis screened 629 overall activity score-related genes, which were mainly associated with T cell response and B cell response. COX analysis identified AKAP5, CTLA4, LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 as critical genes affecting the prognosis of GC, based on which the IAS was developed. Further RT-qPCR analysis data showed that the expression of AKAP5 and CTLA4 was downregulated, while that of LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 was significantly elevated in GC cell lines. Inhibition of AKAP5 increased cell viability but siAOAH-IT1 promoted viability of GC cells. IAS demonstrated excellent robustness in predicting immunotherapy outcome and GC prognosis, with low-IAS patients having better prognosis and immunotherapy. In addition, resistance to Erlotinib, Rapamycin, MG-132, Cyclopamine, AZ628, and Sorafenib was reduced in patients with low IAS.

Conclusion

IAS was a reliable prognostic indicator. For GC patients, IAS showed excellent robustness in predicting GC prognosis, immune activity status, immunotherapy response, and chemotherapeutic drug resistance. Our study provided novel insights into the prognostic assessment in GC.

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

Background

Effective treatment is needed for advanced, inoperable, or chemotherapy-resistant cervical cancer patients. Immunotherapy has become a new treatment modality for cervical cancer patients, and there is an urgent need to identify additional targets for cervical cancer immunotherapy.

Methods

In this study the core gene, RGS1, which affects immune status and the FIGO stage of cervical cancer patients was identified by WGCNA analysis and differential analysis using TCGA database. 10 related genes interacting with RGS1 were identified using PPI network, and the functional and immune correlations were analyzed. Based on the expression of RGS1 and related genes, the consensus clustering method was used to divide CESC patients into two groups (group 1, high expression of RGS1; group 2, low expression of RGS1). Then, the functional enrichment analysis was used to search for the functional differences in differentially expressed genes (DEGs) between group 1 and group 2. Immune infiltration analysis was performed using ESTIMATE, CIBERSORT, and ssGSEA, and the differences in expression of immune checkpoint inhibitors (ICIs) targets were assessed between the two groups. We investigated the effect of RGS1 on the clinical relevance of CESC patients, and experimentally verified the differences in RGS1 expression between cervical cancer patient tissues and normal cervical tissues, the role of RGS1 in cell function, and the effect on tumor growth in tumor-bearing mice.

Results

We found that RGS1 was associated with CD4, GNAI3, RGS2, GNAO1, GNAI2, RGS20, GNAZ, GNAI1, HLA-DRA and HLA-DRB1, especially CD4 and RGS2. Functional enrichment of DEGs was associated with T cell activation. Compared with group 2, group 1 had stronger immune infiltration and higher ICI target expression. RGS1 had higher expression in cervical cancer tissues than normal tissues, especially in HPV-E6 positive cancer tissues. In cervical cancer cell lines, knockdown of RGS1 can inhibited cell proliferation, migration, invasion, and tumor growth in nude mice and promoted apoptosis.

Conclusions

RGS1, as an oncogenic gene of cervical cancer, affects the immune microenvironment of patients with cervical cancer and may be a target of immunotherapy.

miRNA-mRNA analysis of sheep adrenal glands reveals the network regulating reproduction

Background

The adrenal gland participates in the process of sheep reproduction. MicroRNAs (miRNAs), endogenous small noncoding RNAs, regulate gene expression at the posttranscriptional level. However, the miRNA-mRNA network profile of adrenal glands relating to reproduction in sheep is still not well-studied. As sheep with FecB^BB genotype show higher lambing number compare with the sheep with FecB⁺⁺ genotype. This research aims to compare gene expression by small RNA-seq in adrenal tissues at follicular (F) and luteal (L) phases in FecB^BB (MM) and FecB⁺⁺ (ww) sheep. After analysis of gene expression, significant differentially expressed microRNAs (DEMs) and corresponding target genes were identified.

Results

A total of 180 miRNAs were found in this study, of which 19 DEMs were expressed in the four comparison groups (MM_F_A vs. MM_L_A, MM_F_A vs. ww_F_A, MM_L_A vs. ww_L_A, ww_F_A vs. ww_L_A). Subsequently, 354 target genes of 19 DEMs were predicted by integrated analysis. Cluster analysis was performed by K_means_cluster, and the expression patterns of these DEMs were separated into four subclusters. Functional analysis of target genes was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The results indicated that the target genes were involved mainly in the Notch signaling pathway, signal transduction, cell communication, innate immune response and amino acid metabolism. Specifically, the Notch signaling pathway, biosynthetic process and metabolic process of pyrimidine nucleotide and amino acid metabolism appear to play key regulatory roles in the sheep fertility trait. Furthermore, miRNA-mRNA interaction networks were constructed by differentially expressed genes combined with our previous study of transcriptome data. The results showed that several key genes, including TDRD3, ANAPC7, CCNL2, BRD2 and MUT, were related to the transformation from the follicular phase to the luteal phase. PLAC8L1, NFAT5, DDX24 and MBD1 were related to the high fecundity of small tail Han sheep.

Conclusions

In this study, the miRNA transcriptome profile was identified, and miRNA-mRNA interaction networks were constructed in adrenal gland tissue of small tail Han sheep, the interaction between miR-370-3p and its targets were considered to play a major role in the reproduction regulation process. The results enriched the number of known miRNAs in adrenal glands and provided novel ideas and further information to demonstrate posttranscriptional regulation mechanisms at follicular and luteal phases in different genotypes of small tail Han sheep.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01060-y.

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.