Tryptophanyl-tRNA synthetase (WARS) expression in uveal melanoma - possible contributor during uveal melanoma progression

Diagnostic, prognostic, and immunological roles of CDSN in ovarian cancer

Globally, ovarian cancer (OC) ranks as a principal cause of cancer-related mortality in females. Immunotherapy has revolutionized the treatment of OC, but the efficacy of immunotherapy is often limited by different immune microenvironments. The objective of this research was to pinpoint and validate candidate genes with potential value as diagnostic and prognostic biomarkers and therapeutic targets in OC. Data on genes associated with gene mutation, prognostic survival, and immune infiltration in OC were procured from the Cancer Genome Atlas (TCGA). Gene differential analysis, mutation site analysis, prognosis and survival analysis, and functional and signaling pathway enrichment analysis were conducted to identify and evaluate key genes. The genes were further investigated using immune infiltration analysis, receiver operating characteristic curves, and immunohistochemistry. The impact of CDSN on OC cell proliferation was investigated utilizing CCK-8, colony formation, and apoptosis detection assays. We identified a set of genes (CDSN, WARS, and CD38) that were highly expressed in OC and significantly associated with mutations and prognosis. Immune infiltration analysis and immunohistochemistry results indicated a correlation with immune infiltration in the tumor microenvironment, particularly in antigen-presenting cells. Receiver operating characteristic curve analysis demonstrated the diagnostic potential of these three genes in OC, with all three genes showing the area under the curve (AUC) above 0.8. In vitro studies suggested that knocked down CDSN expression resulted in a marked lower in the proliferative capacity of OC cells. The candidate gene CDSN identified through bioinformatics analysis and in vitro experiments is associated with mutation and immune infiltration, showing promise as a diagnostic and prognostic biomarker, as well as a therapeutic objective in OC.

Prognostic prediction using a gene signature developed based on exhausted T cells for liver cancer patients

Background

Liver hepatocellular carcinoma (LIHC) is a solid primary malignancy with poor prognosis. This study discovered key prognostic genes based on T cell exhaustion and used them to develop a prognostic prediction model for LIHC.

Methods

SingleR's annotations combined with Seurat was used to automatically annotate the single-cell clustering results of the LIHC dataset GSE166635 downloaded from the Gene Expression Omnibus (GEO) database and to identify clusters related to exhausted T cells. Patients were classified using ConsensusClusterPlus package. Next, weighted gene co-expression network analysis (WGCNA) package was employed to distinguish key gene module, based on which least absolute shrinkage and selection operator (Lasso) and multi/univariate cox analysis were performed to construct a RiskScore system. Kaplan-Meier (KM) analysis and receiver operating characteristic curve (ROC) were employed to evaluate the efficacy of the model. To further optimize the risk model, a nomogram capable of predicting immune infiltration and immunotherapy sensitivity in different risk groups was developed. Expressions of genes were measured by quantitative real-time polymerase chain reaction (qRT-PCR), and immunofluorescence and Cell Counting Kit-8 (CCK-8) were performed for analyzing cell functions.

Results

We obtained 18,413 cells and clustered them into 7 immune and non-immune cell subpopulations. Based on highly variable genes among T cell exhaustion clusters, 3 molecular subtypes (C1, C2 and C3) of LIHC were defined, with C3 subtype showing the highest score of exhausted T cells and a poor prognosis. The Lasso and multivariate cox analysis selected 7 risk genes from the green module, which were closely associated with the C3 subtype. All the patients were divided into low- and high-risk groups based on the medium value of RiskScore, and we found that high-risk patients had higher immune infiltration and immune escape and poorer prognosis. The nomogram exhibited a strong performance for predicting long-term LIHC prognosis. In vitro experiments revealed that the 7 risk genes all had a higher expression in HCC cells, and that both liver HCC cell numbers and cell viability were reduced by knocking down MMP-9.

Conclusion

We developed a RiskScore model for predicting LIHC prognosis based on the scRNA-seq and RNA-seq data. The RiskScore as an independent prognostic factor could improve the clinical treatment for LIHC patients.

First Report of FARSA in the Regulation of Cell Cycle and Survival in Mantle Cell Lymphoma Cells via PI3K-AKT and FOXO1-RAG1 Axes

Cancer-associated factors have been largely identified in the understanding of tumorigenesis and progression. However, aminoacyl-transfer RNA (tRNA) synthetases (aaRSs) have so far been neglected in cancer research due to their canonical activities in protein translation and synthesis. FARSA, the alpha subunit of the phenylalanyl-tRNA synthetase is elevated across many cancer types, but its function in mantle cell lymphoma (MCL) remains undetermined. Herein, we found the lowest levels of FARSA in patients with MCL compared with other subtypes of lymphomas, and the same lower levels of FARSA were observed in chemoresistant MCL cell lines. Unexpectedly, despite the essential catalytic roles of FARSA, knockdown of FARSA in MCL cells did not lead to cell death but resulted in accelerated cell proliferation and cell cycle, whereas overexpression of FARSA induced remarkable cell-cycle arrest and overwhelming apoptosis. Further RNA sequencing (RNA-seq) analysis and validation experiments confirmed a strong connection between FARSA and cell cycle in MCL cells. Importantly, FARSA leads to the alteration of cell cycle and survival via both PI3K-AKT and FOXO1-RAG1 axes, highlighting a FARSA-mediated regulatory network in MCL cells. Our findings, for the first time, reveal the noncanonical roles of FARSA in MCL cells, and provide novel insights into understanding the pathogenesis and progression of B-cell malignancies.

Etodolac improves collagen induced rheumatoid arthritis in rats by inhibiting synovial inflammation, fibrosis and hyperplasia

Synovial hyperplasia is the main cause of chronic rheumatoid arthritis (RA), but the mechanism of synovial hyperplasia is still unclear. Etodolac (ETD) is a selective COX-2 inhibitor for relieving pain and stiffness in RA, but the disease modifying effect is still lack of evidence. Proteomics method was used to study the differential proteome of synovial tissue in collagen induced arthritis (CIA) in rats. With the help of STRING analysis, the upregulated proteins enriched in the cluster of complement and coagulation cascades and platelet degranulation were highlighted, these proteins with fibrogenic factors Lum, CIV, CXI and Tgfbi participated in the synovial inflammation, fibrosis and hyperplasia in CIA. Based on KOG function class analysis, the proteins involved in the events of the central dogma was explored. They might be hyperplasia related proteins for most of them are related to the proliferation of cancer. ETD significantly attenuated synovial inflammation, fibrosis and hyperplasia in CIA rats by downregulating these proteins. Several proteins have not been observed in RA so far, such as Tmsb4x, Pura, Nfic, Ruvbl1, Snrpd3, U2af2, Srrm2, Srsf7, Elavl1, Hnrnph1, Wars, Yars, Bzw2, Mcts1, Eif4b, Ctsh, Lamp1, Dpp7, Ptges3, Cdc37 and Septin9, they might be potentials targets for RA. Blood biochemistry tests showed the safety of 7 months use of ETD on rats. In conclusion, present study displayed a comprehensive mechanism of synovial hyperplasia in CIA rats, on this basis, the clinical value of ETD in the treatment of RA was well confirmed.

Identification of survival-related genes and a novel gene-based prognostic signature involving the tumor microenvironment of uveal melanoma

Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults and almost fifty percent of patients subsequently develop systemic metastases usually involving the liver. The tumor microenvironment (TME) is crucial to the initiation and progression of tumors. In the present study, we comprehensively evaluated the TME of primary UM samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database by using several bioinformatic algorithms. The prognostic value of immune score and infiltrating immune cells in the TME were evaluated. Differentially expressed genes between the low- and high-immune score groups were also identified. The majority of tumor-infiltrating lymphocytes in UM have been determined to be activated CD8 + T cells. Therefore, weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression modules and genes significantly associated with the level of infiltrating CD8 + T cells in UM. Survival-related genes involved in the TME were identified by univariate Cox regression analysis. Furthermore, an eight-gene-based prognostic signature was established in the training dataset TCGA-UM via Lasso-penalized and multivariate Cox regression analyses. The predictive value of this signature was validated in two testing datasets. Besides, a nomogram was established to serve clinical practice. Moreover, hub genes involved in the infiltrating CD8 + T cells were identified and a potential targeted therapy for preventing metastasis of UM was proposed based on the results. In summary, our results provided a robust gene-based prognostic signature for predicting prognosis of UM patients and proposed a potential targeted therapy for preventing UM metastasis.

Tryptophanyl-tRNA Synthetase as a Potential Therapeutic Target

Tryptophanyl-tRNA synthetase (WRS) is an essential enzyme that catalyzes the ligation of tryptophan (Trp) to its cognate tRNA^trp during translation via aminoacylation. Interestingly, WRS also plays physiopathological roles in diseases including sepsis, cancer, and autoimmune and brain diseases and has potential as a pharmacological target and therapeutic. However, WRS is still generally regarded simply as an enzyme that produces Trp in polypeptides; therefore, studies of the pharmacological effects, therapeutic targets, and mechanisms of action of WRS are still at an emerging stage. This review summarizes the involvement of WRS in human diseases. We hope that this will encourage further investigation into WRS as a potential target for drug development in various pathological states including infection, tumorigenesis, and autoimmune and brain diseases.

Expression of apolipoprotein C1 in clear cell renal cell carcinoma: An oncogenic gene and a prognostic marker

This study aimed to explore whether APOC1 expression has a function in the biological behavior of clear cell renal cell carcinoma (ccRCC) cells and its possible mechanism. Bioinformatics analysis of data TCGA and OnComine was conducted to explore the expression pattern and prognostic value of APOC1, as well as the relationship between APOC1 expression and clinical indicators. Loss- and gain- of APOC1 function assays were carried out to assess the biological functions of APOC1. Western blotting was applied to detect protein expression. We revealed that APOC1 was upregulated in ccRCC tissues. APOC1 expression was related to gender, grade, pathologic-T, pathologic-stage, and pathologic-M in patients with ccRCC. Meanwhile, Kaplan-Meier analysis evidenced that the high APOC1 expression indicated unfavorable outcomes of ccRCC. Functional experiments in vitro revealed that upregulation of APOC1 in UT33A cells promoted cell proliferation, invasion, and migration, while downregulation of APOC1 in 786-O cells had the opposite effect. Furthermore, epithelial mesenchymal transition (EMT) was activated in cells with upregulated APOC1 but inhibited in cells with down-regulated APOC1. Collectively, our data suggested that APOC1 was overexpressed in ccRCC cells and promoted the malignant biological behaviors and EMT of ccRCC cells.

Roles of Aminoacyl-tRNA Synthetases in Cancer

Aminoacyl-tRNA synthetases (ARSs) catalyze the ligation of amino acids to their cognate transfer RNAs (tRNAs), thus playing an important role in protein synthesis. In eukaryotic cells, these enzymes exist in free form or in the form of multi-tRNA synthetase complex (MSC). The latter contains nine cytoplasmic ARSs and three ARS-interacting multifunctional proteins (AIMPs). Normally, ARSs and AIMPs are regarded as housekeeping molecules without additional functions. However, a growing number of studies indicate that ARSs are involved in a variety of physiological and pathological processes, especially tumorigenesis. Here, we introduce the roles of ARSs and AIMPs in certain cancers, such as colon cancer, lung cancer, breast cancer, gastric cancer and pancreatic cancer. Furthermore, we particularly focus on their potential clinical applications in cancer, aiming at providing new insights into the pathogenesis and treatment of cancer.

Multi-Omics Database Analysis of Aminoacyl-tRNA Synthetases in Cancer

Aminoacyl-tRNA synthetases (aaRSs) are key enzymes in the mRNA translation machinery, yet they possess numerous non-canonical functions developed during the evolution of complex organisms. The aaRSs and aaRS-interacting multi-functional proteins (AIMPs) are continually being implicated in tumorigenesis, but these connections are often limited in scope, focusing on specific aaRSs in distinct cancer subtypes. Here, we analyze publicly available genomic and transcriptomic data on human cytoplasmic and mitochondrial aaRSs across many cancer types. As high-throughput technologies have improved exponentially, large-scale projects have systematically quantified genetic alteration and expression from thousands of cancer patient samples. One such project is the Cancer Genome Atlas (TCGA), which processed over 20,000 primary cancer and matched normal samples from 33 cancer types. The wealth of knowledge provided from this undertaking has streamlined the identification of cancer drivers and suppressors. We examined aaRS expression data produced by the TCGA project and combined this with patient survival data to recognize trends in aaRSs' impact on cancer both molecularly and prognostically. We further compared these trends to an established tumor suppressor and a proto-oncogene. We observed apparent upregulation of many tRNA synthetase genes with aggressive cancer types, yet, at the individual gene level, some aaRSs resemble a tumor suppressor while others show similarities to an oncogene. This study provides an unbiased, overarching perspective on the relationship of aaRSs with cancers and identifies certain aaRS family members as promising therapeutic targets or potential leads for developing biological therapy for cancer.

Identification of prognostic genes in uveal melanoma microenvironment

Background

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Many previous studies have demonstrated that the infiltrating of immune and stromal cells in the tumor microenvironment contributes significantly to prognosis.

Methods

Dataset TCGA-UVM, download from TCGA portal, was taken as the training cohort, and GSE22138, obtained from GEO database, was set as the validation cohort. ESTIMATE algorithm was applied to find intersection differentially expressed genes (DEGs) among tumor microenvironment. Kaplan-Meier analysis and univariate Cox regression model were performed on intersection DEGs to initial screen for potential prognostic genes. Then these genes entered into the validation cohort for validation using the same methods as that in the training cohort. Moreover, we conducted correlation analyses between the genes obtained in the validation cohort and the status of chromosome 3, chromosome 8q, and tumor metastasis to get prognosis genes. At last, the immune infiltration analysis was performed between the prognostic genes and 6 main kinds of tumor-infiltrating immune cells (TICs) for understanding the role of the genes in the tumor microenvironment.

Results

959 intersection DEGs were found in the UM microenvironment. Kaplan-Meier and Cox analysis was then performed in the training and validation cohorts on these DEGs, and 52 genes were identified with potential prognostic value. After comparing the 52 genes to chromosome 3, chromosome 8q, and metastasis, we obtained 21 genes as the prognostic genes. The immune infiltration analysis showed that Neutrophil had the potential prognostic ability, and almost every prognostic gene we had identified was correlated with abundances of Neutrophil and CD8+ T Cell.

Conclusions

Identifying 21 prognosis genes (SERPINB9, EDNRB, RAPGEF3, HFE, RNF43, ZNF415, IL12RB2, MTUS1, NEDD9, ZNF667, AZGP1, WARS, GEM, RAB31, CALHM2, CA12, MYEOV, CELF2, SLCO5A1, ISM1, and PAPSS2) could accurately identify patients' prognosis and had close interactions with Neutrophil in the tumor environment, which may provide UM patients with personalized prognosis prediction and new treatment insights.

Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma

Metabolic reprogramming is closely related to melanoma. However, the prognostic role of metabolism-related genes (MRGs) remains to be elucidated. We aimed to establish a nomogram by combining MRGs signature and clinicopathological factors to predict melanoma prognosis. Eighteen prognostic MRGs between melanoma and normal samples were identified using The Cancer Genome Atlas (TCGA) and GSE15605. WARS (HR = 0.881, 95% CI = 0.788–0.984, P = 0.025) and MGST1 (HR = 1.124, 95% CI = 1.007–1.255, P = 0.037) were ultimately identified as independent prognostic MRGs with LASSO regression and multivariate Cox regression. The MRGs signature was established according to these two genes and externally validated in the Gene Expression Omnibus (GEO) dataset. Kaplan-Meier survival analysis indicated that patients in the high-risk group had significantly poorer overall survival (OS) than those in the low-risk group. Furthermore, the MRGs signature was identified as an independent prognostic factor for melanoma survival. An MRGs nomogram based on the MRGs signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Calibration plots showed good consistency between the prediction of nomogram and actual observation. The receiver operating characteristic curve and decision curve analysis indicated that MRGs nomogram had better OS prediction and clinical net benefit than the stage system. To our knowledge, we are the first to develop a prognostic nomogram based on MRGs signature with better predictive power than the current staging system, which could assist individualized prognosis prediction and improve treatment.

Chromatin modified protein 4C (CHMP4C) facilitates the malignant development of cervical cancer cells

Despite improvements in prevention and treatment, cervical cancer (CC) still poses a serious threat to women’s health. CHMP4C (chromatin modified protein 4C) is a subunit of the endosomal sorting complex required for transport, which is expressed in both nucleus and cytoplasm. Here, we examined the effect of CHMP4C on the biological behavior of CC cells and the underlying mechanisms. We report that CHMP4C expression is higher in CC tissues, and high CHMP4C expression is associated with lower survival. Up‐regulation of CHMP4C in C‐33A cells accelerates cell proliferation, migration and invasion, whereas down‐regulation of CHMP4C in Ca Ski cells had the opposite effect. Moreover, overexpression of CHMP4C induced activation of the epithelial–mesenchymal transition pathway, whereas depletion of CHMP4C inhibited activation. Our results suggest that CHMP4C contributes to the viability and motility of CC cells by modulating epithelial–mesenchymal transition and may facilitate the identification of novel biomarkers for CC therapy.

SP1-mediated long noncoding RNA POU3F3 accelerates the cervical cancer through miR-127-5p/FOXD1

Emerging evidence supports the critical roles of long noncoding RNA (lncRNA) in cervical cancer. However, the pathological roles of lncRNA POU3 F3 in the cervical cancer tumorigenesis are still elusive. POU3 F3 was validated to be up-regulated in the cervical cancer tissue specimens and cells comparing with normal controls. Moreover, the ectopic overexpression of POU3 F3 was closely correlated with poor prognosis. In vitro, POU3 F3 promoted the proliferation, invasion of cervical cancer cells. In vivo, POU3 F3 knockdown repressed the tumor growth of cervical cancer cells. The transcriptional expression of POU3 F3 was activated by the transcription factor SP1. Mechanically, POU3 F3 acted as the sponge to target miR-127-5p, while miR-127-5p bind with the 3'-UTR of FOXD1 gene. In conclusion, our data verifies that lncRNA POU3 F3, induced by transcription factor SP1, acts as an oncogene in the cervical cancer tumorigenesis via regulating miR-127-5p/FOXD1 axis, providing a possible therapeutic target for cervical cancer.