Down-Regulation of Ribosomal Protein RPS21 Inhibits Invasive Behavior of Osteosarcoma Cells Through the Inactivation of MAPK Pathway

Identification of ribosomal protein S21 as a potential prognostic and immunotherapy biomarker for hepatocellular carcinoma

BACKGROUND

Recent studies show that ribosomal protein S21 (RPS21) plays a role in the development and progression of various malignancies. However, the biological value of RPS21 in hepatocellular carcinoma (HCC) and its association with immunotherapy remain unknown.

METHODS

Here, we examined the differential expression of RPS21 between HCC and normal liver tissues, using the TCGA, ICGC and GEO databases, followed by verification by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) in LO2, SMMC7721, HepG2, and MHCC-97H cell lines. Kaplan-Meier and Cox regression analyses were applied to investigate how RPS21 expression influenced overall survival, and a nomogram was established to predict prognosis among HCC patients. We further analyzed how RPS21 expression was related to tumor immune microenvironment, immunotherapy efficiency, and genomic alterations, and investigated potential underlying mechanisms.

RESULTS

RPS21 upregulation was observed in HCC tissues and cell lines, compared to normal controls. Survival analysis revealed that RPS21 overexpression was significantly associated with poor clinical outcomes (all p < 0.05). Functional enrichment analyses indicated that differentially expressed genes relative to RPS21 expression were mainly involved in tumor response, proliferation, and metabolism. Additionally, RPS21 expression was positively correlated with the infiltration of activated CD4+ T cells and tumor mutational burden (all p < 0.05). Moreover, RPS21 was co-expressed with immune-related genes and immune checkpoint genes. Analyses of drug sensitivity predict that HCC patients with low RPS21 expression were more sensitive to targeted immunotherapy.

CONCLUSIONS

The present results suggested that RPS21 might be a promising prognostic marker and a potential immunotherapy target for patients with HCC.

TGF-β2 Induces Ribosome Activity, Alters Ribosome Composition and Inhibits IRES-Mediated Translation in Chondrocytes

Alterations in cell fate are often attributed to (epigenetic) regulation of gene expression. An emerging paradigm focuses on specialized ribosomes within a cell. However, little evidence exists for the dynamic regulation of ribosome composition and function. Here, we stimulated a chondrocytic cell line with transforming growth factor beta (TGF-β2) and mapped changes in ribosome function, composition and ribosomal RNA (rRNA) epitranscriptomics. 35S Met/Cys incorporation was used to evaluate ribosome activity. Dual luciferase reporter assays were used to assess ribosomal modus. Ribosomal RNA expression and processing were determined by RT-qPCR, while RiboMethSeq and HydraPsiSeq were used to determine rRNA modification profiles. Label-free protein quantification of total cell lysates, isolated ribosomes and secreted proteins was done by LC-MS/MS. A three-day TGF-β2 stimulation induced total protein synthesis in SW1353 chondrocytic cells and human articular chondrocytes. Specifically, TGF-β2 induced cap-mediated protein synthesis, while IRES-mediated translation was not (P53 IRES) or little affected (CrPv IGR and HCV IRES). Three rRNA post-transcriptional modifications (PTMs) were affected by TGF-β2 stimulation (18S-Gm1447 downregulated, 18S-ψ1177 and 28S-ψ4598 upregulated). Proteomic analysis of isolated ribosomes revealed increased interaction with eIF2 and tRNA ligases and decreased association of eIF4A3 and heterogeneous nuclear ribonucleoprotein (HNRNP)s. In addition, thirteen core ribosomal proteins were more present in ribosomes from TGF-β2 stimulated cells, albeit with a modest fold change. A prolonged stimulation of chondrocytic cells with TGF-β2 induced ribosome activity and changed the mode of translation. These functional changes could be coupled to alterations in accessory proteins in the ribosomal proteome.

SpiderLearner: An ensemble approach to Gaussian graphical model estimation

Gaussian graphical models (GGMs) are a popular form of network model in which nodes represent features in multivariate normal data and edges reflect conditional dependencies between these features. GGM estimation is an active area of research. Currently available tools for GGM estimation require investigators to make several choices regarding algorithms, scoring criteria, and tuning parameters. An estimated GGM may be highly sensitive to these choices, and the accuracy of each method can vary based on structural characteristics of the network such as topology, degree distribution, and density. Because these characteristics are a priori unknown, it is not straightforward to establish universal guidelines for choosing a GGM estimation method. We address this problem by introducing SpiderLearner, an ensemble method that constructs a consensus network from multiple estimated GGMs. Given a set of candidate methods, SpiderLearner estimates the optimal convex combination of results from each method using a likelihood-based loss function.K $$ K $$ -fold cross-validation is applied in this process, reducing the risk of overfitting. In simulations, SpiderLearner performs better than or comparably to the best candidate methods according to a variety of metrics, including relative Frobenius norm and out-of-sample likelihood. We apply SpiderLearner to publicly available ovarian cancer gene expression data including 2013 participants from 13 diverse studies, demonstrating our tool's potential to identify biomarkers of complex disease. SpiderLearner is implemented as flexible, extensible, open-source code in the R package ensembleGGM at https://github.com/katehoffshutta/ensembleGGM.

Integrated bioinformatics analysis of the transcription factor-mediated gene regulatory networks in the formation of spermatogonial stem cells

Background: In vitro induction of spermatogonial stem cells (SSCs) from embryonic stem cells (ESCs) provides a promising tool for the treatment of male infertility. A variety of molecules are involved in this complex process, which needs to be further clarified. Undoubtedly, the increased knowledge of SSC formation will be beneficial to facilitate the currently complex induction process. Methods: Based on ATAC-seq, DNase-seq, RNA-seq, and microarray data from GEO datasets, chromatin property data (ATAC-seq, DNase-seq) and gene expression data (RNA-seq, microarray data) were combined to search for SSC-specific transcription factors (TFs) and hub SSC-specific genes by using the WGCNA method. Then, we applied RNA-seq and microarray data screening for key SSC-specific TFs and constructed key SSC-specific TF-mediated gene regulatory networks (GRNs) using ChIP-seq data. Results: First, after analysis of the ATAC-seq and DNase-seq data of mouse ESCs, primordial germ cells (PGCs), and SSCs, 33 SSC-specific TFs and 958 targeting genes were obtained. RNA-seq and WGCNA revealed that the key modules (turquoise and red) were the most significantly related to 958 SSC-specific genes, and a total of 10 hub SSC-specific genes were identified. Next, when compared with the cell-specific TFs in human ESCs, PGCs, and SSCs, we obtained five overlapping SSC-specific TF motifs, including the NF1 family TF motifs (NFIA, NFIB, NFIC, and NFIX), GRE, Fox:Ebox, PGR, and ARE. Among these, Nfib and Nfix exhibited abnormally high expression levels relative to mouse ESCs and PGCs. Moreover, Nfib and Nfix were upregulated in the testis sample with impaired spermatogenesis when compared with the normal group. Finally, the ChIP-seq data results showed that NFIB most likely targeted the hub SSC-specific genes of the turquoise module (Rpl36al, Rps27, Rps21, Nedd8, and Sec61b) and the red module (Vcam1 and Ccl2). Conclusion: Our findings preliminarily revealed cell-specific TFs and cell-specific TF-mediated GRNs in the process of SSC formation. The hub SSC-specific genes and the key SSC-specific TFs were identified and suggested complex network regulation, which may play key roles in optimizing the induction efficiency of the differentiation of ESCs into SSCs in vitro.

Effects of metformin on modulating the expression of brain-related genes of APP/PS1 transgenic mice based on Single Cell Sequencing

BACKGROUND

Alzheimer's disease is the most common form of dementia, affecting millions of people worldwide.

METHODS

Here, we analyzed the effects of metformin on APP/PS1 transgenic mice by behavioral test and single-cell sequencing. Results showed that metformin can improve the spatial learning, memory function, and anxiety mood of APP/PS1 transgenic mice. We identified transcriptionally distinct subpopulations of nine major brain cell types. Metformin increased the differentiation of stem cells, decreased the proportion of cells in the G2 phase, enhanced the generation of neural stem cells and oligodendrocyte progenitor cells, and the tendency of neural stem cells to differentiate into astrocytes. Notably, 253 genes expressed abnormally in APP/PS1 transgenic mice and were reversed by metformin. Ttr, Uba52, and Rps21 are the top 3 genes in the cell-gene network with the highest node degree. Moreover, histochemistry showed the expressions of RPS15, UBA52, and RPL23a were consistent with the data from single-cell sequencing. Pathway and biological process enrichment analysis indicated metformin was involved in nervous system development and negative regulation of the apoptotic process.

CONCLUSION

Overall, metformin might play an important role in the differentiation and development and apoptotic process of the central nervous system by regulating the expression of Ttr, Uba52, Rps21, and other genes to improve cognition of APP/PS1 transgenic mice. These results provided a clue for elaborating on the molecular and cellular basis of metformin on AD.

Comparative proteomic analysis of insulin receptor isoform A and B signaling

The insulin receptor (IR) gene undergoes differential splicing generating two IR isoforms, IR-A and IR-B. The roles of IR-A in cancer and of IR-B in metabolic regulation are well known but the molecular mechanisms responsible for their different biological effects are poorly understood. We aimed to identify different or similar protein substrates and signaling linked to each IR isoforms. We employed mouse fibroblasts lacking IGF1R gene and expressing exclusively either IR-A or IR-B. By proteomic analysis a total of 2530 proteins were identified and quantified. Proteins and pathways mostly associated with insulin-activated IR-A were involved in cancer, stemness and interferon signaling. Instead, proteins and pathways associated with insulin-stimulated IR-B-expressing cells were mostly involved in metabolic or tumor suppressive functions. These results show that IR-A and IR-B recruit partially different multiprotein complexes in response to insulin, suggesting partially different functions of IR isoforms in physiology and in disease.

A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell

The sense of smell helps us navigate the environment, but its molecular architecture and underlying logic remain understudied. The spatial location of odorant receptor genes (Olfrs) in the nose is thought to be independent of the structural diversity of the odorants they detect. Using spatial transcriptomics, we create a genome-wide 3D atlas of the mouse olfactory mucosa (OM). Topographic maps of genes differentially expressed in space reveal that both Olfrs and non-Olfrs are distributed in a continuous and overlapping fashion over at least five broad zones in the OM. The spatial locations of Olfrs correlate with the mucus solubility of the odorants they recognize, providing direct evidence for the chromatographic theory of olfaction. This resource resolves the molecular architecture of the mouse OM and will inform future studies on mechanisms underlying Olfr gene choice, axonal pathfinding, patterning of the nervous system, and basic logic for the peripheral representation of smell.

Targeting Ribosome Biogenesis to Combat Tamoxifen Resistance in ER+ve Breast Cancer

Breast cancer is a heterogeneous disease. Around 70% of breast cancers are estrogen receptor-positive (ER+ve), with tamoxifen being most commonly used as an adjuvant treatment to prevent recurrence and metastasis. However, half of the patients will eventually develop tamoxifen resistance. The overexpression of c-MYC can drive the development of ER+ve breast cancer and confer tamoxifen resistance through multiple pathways. One key mechanism is to enhance ribosome biogenesis, synthesising mature ribosomes. The over-production of ribosomes sustains the demand for proteins necessary to maintain a high cell proliferation rate and combat apoptosis induced by therapeutic agents. c-MYC overexpression can induce the expression of eIF4E that favours the translation of structured mRNA to produce oncogenic factors that promote cell proliferation and confer tamoxifen resistance. Either non-phosphorylated or phosphorylated eIF4E can mediate such an effect. Since ribosomes play an essential role in c-MYC-mediated cancer development, suppressing ribosome biogenesis may help reduce aggressiveness and reverse tamoxifen resistance in breast cancer. CX-5461, CX-3543 and haemanthamine have been shown to repress ribosome biogenesis. Using these chemicals might help reverse tamoxifen resistance in ER+ve breast cancer, provided that c-MYC-mediated ribosome biogenesis is the crucial factor for tamoxifen resistance. To employ these ribosome biogenesis inhibitors to combat tamoxifen resistance in the future, identification of predictive markers will be necessary.

Correlations Between the Characteristics of Alternative Splicing Events, Prognosis, and the Immune Microenvironment in Breast Cancer

Objective

Alternative splicing (AS) is the mechanism by which a few genes encode numerous proteins, and it redefines the concept of gene expression regulation. Recent studies showed that dysregulation of AS was an important cause of tumorigenesis and microenvironment formation. Therefore, we performed a systematic analysis to examine the role of AS in breast cancer (Breast Cancer, BrCa) progression.

Methods

The present study included 993 BrCa patients from The Cancer Genome Atlas (TCGA) database in the genome-wide analysis of AS events. We used differential and prognostic analyses and found differentially expressed alternative splicing (DEAS) events and independent prognostic factors related to patients' overall survival (OS) and disease-free survival (DFS). We divided the patients into two groups based on these AS events and analyzed their clinical features, molecular subtyping and immune characteristics. We also constructed a splicing factor (SF) regulation network for key AS events and verified the existence of AS events in tissue samples using real-time quantitative PCR.

Results

A total of 678 AS events were identified as differentially expressed, of which 13 and 10 AS events were independent prognostic factors of patients' OS and DFS, respectively. Unsupervised clustering analysis based on these prognostic factors indicated that the Cluster 1 group had a better prognosis and more immune cell infiltration. SFs were significantly related to the expression of AS events, and AA-RPS21 was significantly upregulated in tumors.

Conclusion

Alternative splicing expands the mechanism of breast cancer progression from a new perspective. Notably, alternative splicing may affect the patient's prognosis by affecting the infiltration of immune cells. Our research provides important guidance for subsequent studies of AS in breast cancer.

Disruption of entire Cables2 locus leads to embryonic lethality by diminished Rps21 gene expression and enhanced p53 pathway

In vivo function of CDK5 and Abl enzyme substrate 2 (Cables2), belonging to the Cables protein family, is unknown. Here, we found that targeted disruption of the entire Cables2 locus (Cables2d) caused growth retardation and enhanced apoptosis at the gastrulation stage and then induced embryonic lethality in mice. Comparative transcriptome analysis revealed disruption of Cables2, 50% down-regulation of Rps21 abutting on the Cables2 locus, and up-regulation of p53-target genes in Cables2d gastrulas. We further revealed the lethality phenotype in Rps21-deleted mice and unexpectedly, the exon 1-deleted Cables2 mice survived. Interestingly, chimeric mice derived from Cables2d ESCs carrying exogenous Cables2 and tetraploid wild-type embryo overcame gastrulation. These results suggest that the diminished expression of Rps21 and the completed lack of Cables2 expression are intricately involved in the embryonic lethality via the p53 pathway. This study sheds light on the importance of Cables2 locus in mouse embryonic development.

Exploiting codon usage identifies intensity-specific modifiers of Ras/MAPK signaling in vivo

Signal transduction pathways are intricately fine-tuned to accomplish diverse biological processes. An example is the conserved Ras/mitogen-activated-protein-kinase (MAPK) pathway, which exhibits context-dependent signaling output dynamics and regulation. Here, by altering codon usage as a novel platform to control signaling output, we screened the Drosophila genome for modifiers specific to either weak or strong Ras-driven eye phenotypes. Our screen enriched for regions of the genome not previously connected with Ras phenotypic modification. We mapped the underlying gene from one modifier to the ribosomal gene RpS21. In multiple contexts, we show that RpS21 preferentially influences weak Ras/MAPK signaling outputs. These data show that codon usage manipulation can identify new, output-specific signaling regulators, and identify RpS21 as an in vivo Ras/MAPK phenotypic regulator.

Cellular communication is critical in controlling the growth of organs and must be carefully regulated to prevent disease. The Ras signaling pathway is frequently used for cellular communication of tissue growth regulation but can operate at different signaling strengths. Here, we used a novel strategy to identify genes that specifically tune weak or strong Ras signaling states. We find that the gene RpS21 preferentially tunes weak Ras signaling states.