RRM2 is a potential prognostic biomarker with functional significance in glioma

Decoding the immune microenvironment: unveiling CD8 + T cell-related biomarkers and developing a prognostic signature for personalized glioma treatment

BACKGROUND

Gliomas are aggressive brain tumors with poor prognosis. Understanding the tumor immune microenvironment (TIME) in gliomas is essential for developing effective immunotherapies. This study aimed to identify TIME-related biomarkers in glioma using bioinformatic analysis of RNA-seq data.

METHODS

In this study, we employed weighted gene co-expression network analysis (WGCNA) on bulk RNA-seq data to identify TIME-related genes. To identify prognostic genes, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Based on these genes, we constructed a prognostic signature and delineated risk groups. To validate the prognostic signature, external validation was conducted.

RESULTS

CD8 + T cell infiltration was strongly correlated with glioma patient prognosis. We identified 115 CD8 + T cell-related genes through integrative analysis of bulk-seq data. CDCA5, KIF11, and KIF4A were found to be significant immune-related genes (IRGs) associated with overall survival in glioma patients and served as independent prognostic factors. We developed a prognostic nomogram that incorporated these genes, age, gender, and grade, providing a reliable tool for clinicians to predict patient survival probabilities. The nomogram's predictions were supported by calibration plots, further validating its accuracy.

CONCLUSION

In conclusion, our study identifies CD8 + T cell infiltration as a strong predictor of glioma patient outcomes and highlights the prognostic value of genes. The developed prognostic nomogram, incorporating these genes along with clinical factors, provides a reliable tool for predicting patient survival probabilities and has important implications for personalized treatment decisions in glioma.

Identification of the ferroptosis-related gene signature and the associated regulation axis in lung cancer and rheumatoid arthritis

Patients with Rheumatoid arthritis (RA) have an elevated risk of lung cancer compared to the healthy population. However, there are few studies on the relationship between RA and lung adenocarcinoma (LUAD), especially the mechanisms at the genetic level. In this study, we investigated the link between RA and LUAD regarding Ferroptosis-Related Genes. The RNA-seq data of RA (GSE77298 and GSE 82107) and LUAD(GSE75037) in the Gene Expression Omnibus (GEO) database were obtained. 259 ferroptosis-related genes were obtained from the website ( http://www.zhounan.org/ferrdb/ ).The differential genes obtained from the RA and LUAD datasets were intersected with ferroptosis-related genes to obtain the ferroptosis-related differentially expressed genes (FRDEGs). Next, the mRNA-miRNA network was constructed, then Gene Set Enrichment Analysis (GSEA) for target genes were performed. The CIBERSORT algorithm was used to analyze the immune infiltration. Finally, the results were validated using external datasets (GSE89408 and GSE48780) and The Cancer Genome Atlas (TCGA) dataset. We obtained FRDEGs common to LUAD and RA: FANCD2, HELLS, RRM2, G6PD, VLDLR. These five genes play important roles in the progression of RA and LUAD. They also hold great diagnostic value for both diseases. Also, we found that LUAD and RA share common signaling pathways and similar immune mechanisms.

A comprehensive analysis of ribonucleotide reductase subunit M2 for carcinogenesis in pan-cancer

BACKGROUND

Although there is evidence that ribonucleotide reductase subunit M2 (RRM2) is associated with numerous cancers, pan-cancer analysis has seldom been conducted. This study aimed to explore the potential carcinogenesis of RRM2 in pan-cancer using datasets from The Cancer Genome Atlas (TCGA).

METHODS

Data from the UCSC Xena database were analyzed to investigate the differential expression of RRM2 across multiple cancer types. Clinical data such as age, race, sex, tumor stage, and status were acquired to analyze the influence of RRM2 on the clinical characteristics of the patients. The role of RRM2 in the onset and progression of multiple cancers has been examined in terms of genetic changes at the molecular level, including tumor mutational burden (TMB), microsatellite instability (MSI), biological pathway changes, and the immune microenvironment.

RESULTS

RRM2 was highly expressed in most cancers, and there was an obvious correlation between RRM2 expression and patient prognosis. RRM2 expression is associated with the infiltration of diverse immune and endothelial cells, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI). Moreover, the cell cycle is involved in the functional mechanisms of RRM2.

CONCLUSIONS

Our pan-cancer study provides a comprehensive understanding of the carcinogenesis of RRM2 in various tumors.

RRM2 promotes the proliferation of chicken myoblasts, inhibits their differentiation and muscle regeneration

During myogenesis and regeneration, the proliferation and differentiation of myoblasts play key regulatory roles and may be regulated by many genes. In this study, we analyzed the transcriptomic data of chicken primary myoblasts at different periods of proliferation and differentiation with protein‒protein interaction network, and the results indicated that there was an interaction between cyclin-dependent kinase 1 (CDK1) and ribonucleotide reductase regulatory subunit M2 (RRM2). Previous studies in mammals have a role for RRM2 in skeletal muscle development as well as cell growth, but the role of RRM2 in chicken is unclear. In this study, we investigated the effects of RRM2 on skeletal muscle development and regeneration in chickens in vitro and in vivo. The interaction between RRM2 and CDK1 was initially identified by co-immunoprecipitation and mass spectrometry. Through a dual luciferase reporter assay and quantitative real-time PCR, we identified the core promoter region of RRM2, which is regulated by the SP1 transcription factor. In this study, through cell counting kit-8 assays, 5-ethynyl-2'-deoxyuridine incorporation assays, flow cytometry, immunofluorescence staining, and Western blot analysis, we demonstrated that RRM2 promoted the proliferation and inhibited the differentiation of myoblasts. In vivo studies showed that RRM2 reduced the diameter of muscle fibers and slowed skeletal muscle regeneration. In conclusion, these data provide preliminary insights into the biological functions of RRM2 in chicken muscle development and skeletal muscle regeneration.

Targeting of RRM2 suppresses DNA damage response and activates apoptosis in atypical teratoid rhabdoid tumor

BACKGROUND

Atypical teratoid rhabdoid tumors (ATRT) is a rare but aggressive malignancy in the central nervous system, predominantly occurring in early childhood. Despite aggressive treatment, the prognosis of ATRT patients remains poor. RRM2, a subunit of ribonucleotide reductase, has been reported as a biomarker for aggressiveness and poor prognostic conditions in several cancers. However, little is known about the role of RRM2 in ATRT. Uncovering the role of RRM2 in ATRT will further promote the development of feasible strategies and effective drugs to treat ATRT.

METHODS

Expression of RRM2 was evaluated by molecular profiling analysis and was confirmed by IHC in both ATRT patients and PDX tissues. Follow-up in vitro studies used shRNA knockdown RRM2 in three different ATRT cells to elucidate the oncogenic role of RRM2. The efficacy of COH29, an RRM2 inhibitor, was assessed in vitro and in vivo. Western blot and RNA-sequencing were used to determine the mechanisms of RRM2 transcriptional activation in ATRT.

RESULTS

RRM2 was found to be significantly overexpressed in multiple independent ATRT clinical cohorts through comprehensive bioinformatics and clinical data analysis in this study. The expression level of RRM2 was strongly correlated with poor survival rates in patients. In addition, we employed shRNAs to silence RRM2, which led to significantly decrease in ATRT colony formation, cell proliferation, and migration. In vitro experiments showed that treatment with COH29 resulted in similar but more pronounced inhibitory effect. Therefore, ATRT orthotopic mouse model was utilized to validate this finding, and COH29 treatment showed significant tumor growth suppression and prolong overall survival. Moreover, we provide evidence that COH29 treatment led to genomic instability, suppressed homologous recombinant DNA damage repair, and subsequently induced ATRT cell death through apoptosis in ATRT cells.

CONCLUSIONS

Collectively, our study uncovers the oncogenic functions of RRM2 in ATRT cell lines, and highlights the therapeutic potential of targeting RRM2 in ATRT. The promising effect of COH29 on ATRT suggests its potential suitability for clinical trials as a novel therapeutic approach for ATRT.

USP12 promotes nonsmall cell lung cancer progression through deubiquitinating and stabilizing RRM2

RRM2 is the catalytic subunit of ribonucleotide reductase (RNR), which catalyzes de novo synthesis of deoxyribonucleotide triphosphates (dNTPs) and plays critical roles in cancer cell proliferation. RRM2 protein level is controlled by ubiquitination mediated protein degradation system; however, its deubiquitinase has not been identified yet. Here we showed that ubiquitin-specific peptidase 12 (USP12) directly interacts with and deubiquitinates RRM2 in non-small cell lung cancer (NSCLC) cells. Knockdown of USP12 causes DNA replication stress and retards tumor growth in vivo and in vitro. Meanwhile, USP12 protein levels were positively correlated to RRM2 protein levels in human NSCLC tissues. In addition, high expression of USP12 was associated with poor prognosis in NSCLC patients. Therefore, our study reveals that USP12 is a RRM2 regulator and targeting USP12 could be considered as a potential therapeutical strategy for NSCLC treatment.

Delineating the glioblastoma stemness by genes involved in cytoskeletal rearrangements and metabolic alterations

Literature data on glioblastoma ongoingly underline the link between metabolism and cancer stemness, the latter is one responsible for potentiating the resistance to treatment, inter alia due to increased invasiveness. In recent years, glioblastoma stemness research has bashfully introduced a key aspect of cytoskeletal rearrangements, whereas the impact of the cytoskeleton on invasiveness is well known. Although non-stem glioblastoma cells are less invasive than glioblastoma stem cells (GSCs), these cells also acquire stemness with greater ease if characterized as invasive cells and not tumor core cells. This suggests that glioblastoma stemness should be further investigated for any phenomena related to the cytoskeleton and metabolism, as they may provide new invasion-related insights. Previously, we proved that interplay between metabolism and cytoskeleton existed in glioblastoma. Despite searching for cytoskeleton-related processes in which the investigated genes might have been involved, not only did we stumble across the relation to metabolism but also reported genes that were found to be implicated in stemness. Thus, dedicated research on these genes in GSCs seems justifiable and might reveal novel directions and/or biomarkers that could be utilized in the future. Herein, we review the previously identified cytoskeleton/metabolism-related genes through the prism of glioblastoma stemness.

Non-thermal plasma-treated melatonin inhibits the biological activity of HCC cells by increasing intracellular ROS levels and reducing RRM2 expression

Non-thermal plasma (NTP) is thought to have a cytotoxic effect on tumor cells. Although its application in cancer therapy has shown considerable promise, the current understanding of its mechanism of action and cellular responses remains incomplete. Furthermore, the use of melatonin (MEL) as an adjuvant anticancer drug remains unexplored. In this study, we found that NTP assists MEL in promoting apoptosis, delaying cell cycle progression, and inhibiting cell invasion and migration in hepatocellular carcinoma (HCC) cells. This mechanism may be associated with the regulation of intracellular reactive oxygen species levels and ribonucleotide reductase regulatory subunit M2 expression. Our findings confirm the pharmacological role of MEL and the adjuvant value of NTP, emphasizing their potential in combination therapy for HCC. Our study may have important implications for the development of new approaches for HCC treatment.

Ribonucleotide reductase subunit switching in hepatoblastoma drug response and relapse

Prognosis of children with high-risk hepatoblastoma (HB), the most common pediatric liver cancer, remains poor. In this study, we found ribonucleotide reductase (RNR) subunit M2 (RRM2) was one of the key genes supporting cell proliferation in high-risk HB. While standard chemotherapies could effectively suppress RRM2 in HB cells, they induced a significant upregulation of the other RNR M2 subunit, RRM2B. Computational analysis revealed distinct signaling networks RRM2 and RRM2B were involved in HB patient tumors, with RRM2 supporting cell proliferation and RRM2B participating heavily in stress response pathways. Indeed, RRM2B upregulation in chemotherapy-treated HB cells promoted cell survival and subsequent relapse, during which RRM2B was gradually replaced back by RRM2. Combining an RRM2 inhibitor with chemotherapy showed an effective delaying of HB tumor relapse in vivo. Overall, our study revealed the distinct roles of the two RNR M2 subunits and their dynamic switching during HB cell proliferation and stress response.

A 9-gene prognostic signature for kidney renal clear cell carcinoma overall survival based on co-expression and regression analyses

This research attempted to screen potential signatures associated with KIRC progression and overall survival by weighted gene co-expression network analysis (WGCNA) and Cox regression. The KIRC-associated mRNA expression and clinical data were accessed from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened by differential analysis. A co-expression network was constructed by "WGCNA". Based on WGCNA module, GO and KEGG analyses were performed. Protein-protein interaction (PPI) network was constructed. Prognostic signatures were screened by Lasso-Cox regression. Prognostic model was evaluated by Receiver Operating Characteristic (ROC) and Kaplan-Meier (K-M) curves. Multivariate Cox and nomogram were introduced to examine whether risk score could be an independent marker. qRT-PCR was introduced to determine expression of 9 hub genes in KIRC clinical tumor tissues and adjacent tissues, respectively. Genes in the green module were highly associated with clinical status, and green module genes were significantly enriched in mitotic nuclear division, cell cycle, and p53 signaling pathway. Twenty-six candidates were subsequently screened out from the green module. Next, a 9-gene prognostic model (DLGAP5, NUF2, TOP2A, RRM2, HJURP, PLK1, AURKB, KIF18A, CCNB2) was constructed. The predicting ability of the model was optimal. Some cancer-related signaling pathways were differently activated between two risk score groups. Additionally, under-expression of some signature genes (AURKB, CCNB2, PLK1, RRM2, TOP2A) was associated with better survival rate for KIRC patients. Meanwhile, all 9 hub genes were substantially overexpressed in KIRC patients. A KIRC prognostic signature was screened in this study, contributing valuable findings to KIRC biomarker development.

Multi-Omics Integration Analysis of TK1 in Glioma: A Potential Biomarker for Predictive, Preventive, and Personalized Medical Approaches

Multi-omics expression datasets obtained from multiple public databases were used to elucidate the biological function of TK1 and its effects on clinical outcomes. The Kaplan-Meier curve, a predictive nomogram mode, and the time-dependent receiver operating characteristic (ROC) curve were established to assess the role of TK1 expression in glioma prognosis. TK1 was overexpressed in glioma compared with normal samples, and patients with elevated expression of TK1 had poor overall survival. The ROC curves indicated a high diagnostic value of TK1 expression in patients of glioma; the areas under the ROC curve (AUC) were 0.682, 0.735, and 0.758 for 1 year, 3 years, and 5 years of glioma survival, respectively. For a model based on TK1 expression and other clinical characteristics, the values of AUC were 0.864, 0.896, and 0.898 for 1 year, 3 years, and 5 years, respectively. Additionally, the calibration curve indicated that the predicted and observed areas at 1 year, 3 years, and 5 years of survival were in excellent agreement. Three types of TK1 alterations-missense mutations, splice mutations, and amplifications-were identified in 25 of 2706 glioma samples. The TK1-altered group had better overall survival than the unaltered group. Single-cell function analysis showed that TK1 was positively associated with proliferation, the cell cycle, DNA repair, DNA damage, and epithelial-mesenchymal transition in glioma. Immunoinfiltration analysis indicated that TK1 expression might play different roles in low-grade glioma and glioblastoma multiforme tumor microenvironments, but TK1 expression was positively associated with activated CD4 and Th2, regardless of tumor grade. In summary, our findings identified TK1 as a novel marker for predicting clinical outcomes and a potential target for glioma.

Ribonucleotide Reductase Subunit Switching in Hepatoblastoma Drug Response and Relapse

Prognosis of children with high-risk hepatoblastoma (HB), the most common pediatric liver cancer, remains poor. In this study, we found ribonucleotide reductase (RNR) subunit M2 ( RRM2 ) was one of the key genes supporting cell proliferation in high-risk HB. While standard chemotherapies could effectively suppress RRM2 in HB cells, they induced a significant upregulation of the other RNR M2 subunit, RRM2B . Computational analysis revealed distinct signaling networks RRM2 and RRM2B were involved in HB patient tumors, with RRM2 supporting cell proliferation and RRM2B participating heavily in stress response pathways. Indeed, RRM2B upregulation in chemotherapy-treated HB cells promoted cell survival and subsequent relapse, during which RRM2B was gradually replaced back by RRM2. Combining an RRM2 inhibitor with chemotherapy showed an effective delaying of HB tumor relapse in vivo. Overall, our study revealed the distinct roles of the two RNR M2 subunits and their dynamic switching during HB cell proliferation and stress response.

Circ_0006646 Accelerates the Growth and Metastasis of Cervical Cancer by Elevating RRM2 Through miR-758-3p

Cervical cancer (CC) is the fourth most common cancer in women, and circular RNAs (circRNAs) have been shown to regulate CC development. However, the role of circ_0006646 in CC progression is still unclear. The levels of circ_0006646, miR-758-3p, and ribonucleotide reductase regulatory subunit M2 (RRM2) were evaluated by quantitative real-time PCR. Cell proliferation was tested by cell counting kit 8 and 5-ethynyl-2'-deoxyuridine assays. Flow cytometry was used to test cell apoptosis. Migration and invasion were estimated by transwell assay. Western blot assay was performed to examine protein expression. Dual-luciferase reporter assay, RIP assay, and RNA pull down assay were used to analyze the connection between miR-758-3p and circ_0006646 or RRM2. Tumor growth was detected by in vivo experiments. Exosomes were isolated form CC patients and healthy controls. Circ_0006646 expression was elevated in CC cells, and its knockdown suppressed CC cell growth, migration, and invasion. MiR-758-3p was sponged by circ_0006646, and RRM2 was targeted by miR-758-3p. In addition, the effects of circ_0006646 depletion on CC cell progression were overturned by miR-758-3p inhibitor, and either RRM2 overexpression reversed those effects of miR-758-3p overexpression on CC cell progression. Circ_0006646 was highly expressed in the exosomes of CC patients. Circ_0006646 expedited CC cell growth and metastasis by regulating miR-758-3p/RRM2 axis, and exosomal circ_0006646 might be a potential diagnostic indicator of CC.

SLC1A5 enhances malignant phenotypes through modulating ferroptosis status and immune microenvironment in glioma

Glioma is the most common type of primary malignant tumor in the central nervous system with limited treatment satisfaction. Finding new therapeutic targets has remained a major challenge. Ferroptosis is a novel and distinct type of programmed cell death, playing a regulatory role in the progression of tumors. However, the role of ferroptosis or ferroptosis-related genes (FRGs) in glioma progression has not been extensively studied. In our study, a novel ferroptosis-related prognostic model, including 7 genes, was established, in which patients classified into the high-risk group had more immuno-suppressive status and worse prognosis. Among these 7 genes, we screened solute carrier family 1 member 5 (SLC1A5), an FRG, as a possible new target for glioma treatment. Our results showed that the expression of SLC1A5 was significantly upregulated in glioblastoma tissues compared with the low-grade gliomas. In addition, SLC1A5 knockdown could significantly inhibit glioma cell proliferation and invasion, and reduce the sensitivity of ferroptosis via the GPX4-dependent pathway. Furthermore, SLC1A5 was found to be related to immune response and SLC1A5 knockdown decreased the infiltration and M2 polarization of tumor-associated macrophages. Pharmacological inhibition of SLC1A5 by V9302 was confirmed to promote the efficacy of anti-PD-1 therapy. Overall, we developed a novel prognostic model for glioma based on the seven-FRGs signature, which could apply to glioma prognostic and immune status prediction. Besides, SLC1A5 in the model could regulate the proliferation, invasion, ferroptosis and immune state in glioma, and be applied as a prognostic biomarker and potential therapeutic target for glioma.

Purine metabolism-related gene expression signature predicts survival outcome and indicates immune microenvironment profile of gliomas

Glioma is the most common malignant tumor in the central nervous system. The impact of metabolism on cancer development and the immune microenvironment landscape has recently gained broad attention. Purines are involved in multiple metabolic pathways. It has been proved that purine metabolism could regulate malignant biological behaviors and response to immune checkpoint inhibitors in multiple cancers. However, the relationship of purine metabolism with clinicopathological features and the immune landscape of glioma remains unclear. In this study, we explored the relationships between the expression of purine metabolism-related genes (PuMGs) and tumor features, including prognosis and microenvironment of glioma, based on analyses of 1,523 tumors from 4 public databases and our cohort. Consensus clustering based on 136 PuMGs classified the glioma patients into two clusters with significantly distinguished prognosis and immune microenvironment landscapes. Increased immune infiltration was associated with more aggressive gliomas. The prognostic Purine Metabolism-Related Genes Risk Signature (PuMRS), based on 11 critical PuMGs, stratified the patients into PuMRS low- and high-risk groups in the training set and was validated by validation sets from multiple cohorts. The high-risk group presented with significantly shorter overall survival, and further survival analysis demonstrated that the PuMRS was an independent prognostic factor in glioma. The nomogram combining PuMRS and other clinicopathological factors showed satisfactory accuracy in predicting glioma patients' prognosis. Furthermore, analyses of the tumor immune microenvironment suggested that higher PuMRS was correlated with increased immune cell infiltration and gene expression signatures of "hotˮ tumors. Gliomas in the PuMRS high-risk group presented a higher expression level of multiple immune checkpoints, including PD-1 and PD-L1, and a better-predicted therapy response to immune checkpoint inhibitors. In conclusion, our study elucidated the relationship between the expression level of PuMGs and the aggressiveness of gliomas. Our study also endorsed the application of PuMRS to construct a new robust model for the prognosis evaluation of glioma patients. The correlations between the profiles of PuMGs expression and tumor immune microenvironment potentially provided guidance for immunotherapy in glioma.

High expression of RRM2 mediated by non-coding RNAs correlates with poor prognosis and tumor immune infiltration of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is known to have a poor prognosis. Accumulating evidence indicates that RRM2 plays a critical role in the occurrence and progression of multiple human cancers. However, the knowledge about RRM2 in HCC is still insufficient, and further research is needed. Here, we first analyzed the expression and prognosis of RRM2 using TCGA and GTEx data, and found that RRM2 may play a potential carcinogenic role in HCC. Then, through a series of comprehensive analysis, including expression analysis, correlation analysis or survival analysis, non-coding RNAs (ncRNAs) that regulate RRM2 overexpression were identified. Finally, MIR4435-2HG/CYTOR were observed to be the most promising upstream lncRNAs for the miR-125b-5p/RRM2 axis in HCC. In addition, RRM2 expression was significantly positively related to immune cell infiltration, immune cell biomarker or immune checkpoint expression in HCC. Altogether, the upregulation of RRM2 mediated by ncRNAs correlates with poor prognosis and tumor immune infiltration of HCC.

Comprehensive Landscape of RRM2 with Immune Infiltration in Pan-Cancer

Simple Summary

RRM2 is a crucial subunit of ribonucleotide reductase. In this article, we provided a comprehensive analysis of RRM2 with immune infiltration in pan-cancer. We focused on the hotspots of ferroptosis-related gene RRM2 and immunotherapy. Via bioinformatics analysis, multiple indicators suggested that RRM2 high expression may enhance immunotherapy sensitivity. For the first time, we systematically analyzed the role of RRM2 in pan-cancer. We provided the prospect of RRM2 and immunotherapy for pan-cancer. Additionally, we proved the expression pattern, clinical value, prognostic value and potential pathways of RRM2 with different platforms. In particular, we confirmed RRM2 expression and function in bladder cancer in our clinical samples and cell lines. Collectively, we found that RRM2 is a novel prognostic biomarker, and these findings may aid in an improved understanding of the role of RRM2 and its clinical application in human cancers.

Abstract

As a crucial subunit of ribonucleotide reductase, RRM2 plays a significant part in DNA synthesis. This study aimed to elucidate the comprehensive landscape of RRM2 in human cancers. With different bioinformatics platforms, we investigated the expression pattern, prognostic significance, mutational landscapes, gene interaction network, signaling pathways and immune infiltration of RRM2 in tumors. We found that RRM2 expression was predominantly up-expressed in tumor tissues in most tumors. Concurrently, RRM2 expression was significantly associated with worse prognosis and tumor stage across TCGA cancers. Moreover, RRM2 high levels were critically associated with the infiltration of natural killer T cells and immune scores. RRM2 was positively related to immune checkpoints, tumor mutation burden, microsatellite instability, neoantigen, and cytotoxic T lymphocyte in several cancers, predicting effective response to immunotherapy. Meanwhile, a strong co-expression of RRM2 with immune-related genes was observed. Additionally, multiple Cox regression analysis showed that RRM2 was an independent prognostic factor in bladder cancer (BLCA). Eventually, we verified that RRM2 was overexpressed in BLCA clinical samples and cell lines. Blocking RRM2 could suppress BLCA cells’ growth and proliferation while enhancing sensitivity to cisplatin. This study provided a new perspective for understanding RRM2 in cancers and new strategies for tumor immunotherapy.

RRM2 Mediates the Anti-Tumor Effect of the Natural Product Pectolinarigenin on Glioblastoma Through Promoting CDK1 Protein Degradation by Increasing Autophagic Flux

The natural product pectolinarigenin exerts anti-inflammatory activity and anti-tumor effects, and exhibits different biological functions, particularly in autophagy and cell cycle regulation. However, the antineoplastic effect of pectolinarigenin on glioblastoma (GBM) remains unclear. In the present study, we found that pectolinarigenin inhibits glioblastoma proliferation, increases autophagic flux, and induces cell cycle arrest by inhibiting ribonucleotide reductase subunit M2 (RRM2), which can be reversed by RRM2 overexpression plasmid. Additionally, pectolinarigenin promoted RRM2 protein degradation via autolysosome-dependent pathway by increasing autophagic flow. RRM2 knockdown promoted the degradation of CDK1 protein through autolysosome-dependent pathway by increasing autophagic flow, thereby inhibiting the proliferation of glioblastoma by inducing G2/M phase cell cycle arrest. Clinical data analysis revealed that RRM2 expression in glioma patients was inversely correlated with the overall survival. Collectively, pectolinarigenin promoted the degradation of CDK1 protein dependent on autolysosomal pathway through increasing autophagic flux by inhibiting RRM2, thereby inhibiting the proliferation of glioblastoma cells by inducing G2/M phase cell cycle arrest, and RRM2 may be a potential therapeutic target and a prognosis and predictive biomarker in GBM patients.

Identification of hub genes and biological pathways in glioma via integrated bioinformatics analysis

OBJECTIVE

Glioma is the most common intracranial primary malignancy, but its pathogenesis remains unclear.

METHODS

We integrated four eligible glioma microarray datasets from the gene expression omnibus database using the robust rank aggregation method to identify a group of significantly differently expressed genes (DEGs) between glioma and normal samples. We used these DEGs to explore key genes closely associated with glioma survival through weighted gene co-expression network analysis. We then constructed validations of prognosis and survival analyses for the key genes via multiple databases. We also explored their potential biological functions using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA).

RESULTS

We selected DLGAP5, CDCA8, NCAPH, and CCNB2, as four genes that were abnormally up-regulated in glioma samples, for verification. They showed high levels of isocitrate dehydrogenase gene mutation and tumor grades, as well as good prognostic and diagnostic value for glioma. Their methylation levels were generally lower in glioma samples. GSEA and GSVA analyses suggested the genes were closely involved with glioma proliferation.

CONCLUSION

These findings provide new insights into the pathogenesis of glioma. The hub genes have the potential to be used as diagnostic and therapeutic markers.

Palbociclib-based high-throughput combination drug screening identifies synergistic therapeutic options in HPV-negative head and neck squamous cell carcinoma

BACKGROUND

Deregulation of cell-cycle pathway is ubiquitously observed in human papillomavirus negative (HPVneg) head and neck squamous cell carcinoma (HNSCC). Despite being an attractive target, CDK4/6 inhibition using palbociclib showed modest or conflicting results as monotherapy or in combination with platinum-based chemotherapy or cetuximab in HPVneg HNSCC. Thus, innovative agents to augment the efficacy of palbociclib in HPVneg HNSCC would be welcomed.

METHODS

A collection of 162 FDA-approved and investigational agents was screened in combinatorial matrix format, and top combinations were validated in a broader panel of HPVneg HNSCC cell lines. Transcriptional profiling was conducted to explore the molecular mechanisms of drug synergy. Finally, the most potent palbociclib-based drug combination was evaluated and compared with palbociclib plus cetuximab or cisplatin in a panel of genetically diverse HPVneg HNSCC cell lines and patient-derived xenograft models.

RESULTS

Palbociclib displayed limited efficacy in HPVneg HNSCC as monotherapy. The high-throughput combination drug screening provided a comprehensive palbociclib-based drug-drug interaction dataset, whereas significant synergistic effects were observed when palbociclib was combined with multiple agents, including inhibitors of the PI3K, EGFR, and MEK pathways. PI3K pathway inhibitors significantly reduced cell proliferation and induced cell-cycle arrest in HPVneg HNSCC cell lines when combined with palbociclib, and alpelisib (a PI3Kα inhibitor) was demonstrated to show the most potent synergy with particularly higher efficacy in HNSCCs bearing PIK3CA alterations. Notably, when compared with cisplatin and cetuximab, alpelisib exerted stronger synergism in a broader panel of cell lines. Mechanistically, RRM2-dependent epithelial mesenchymal transition (EMT) induced by palbociclib, was attenuated by alpelisib and cetuximab rather than cisplatin. Subsequently, PDX models with distinct genetic background further validated that palbociclib plus alpelisib had significant synergistic effects in models harboring PIK3CA amplification.

CONCLUSIONS

This study provides insights into the systematic combinatory effect associated with CDK4/6 inhibition and supports further initiation of clinical trials using the palbociclib plus alpelisib combination in HPVneg HNSCC with PIK3CA alterations.

Ribonucleotide reductase subunit M2 is a potential prognostic marker and therapeutic target for soft tissue sarcoma

Soft tissue sarcomas (STSs) are highly aggressive malignant tumors that exhibit poor therapeutic outcomes. Hence, we aimed to track down a potential gene that can be used as a prognostic marker and therapeutic target for this malignancy. We integrated omics analysis of clinical data and in vitro studies and identified Ribonucleotide reductase subunit M2 (RRM2) as a potential oncogene associated with STS prognosis. We found RRM2 is highly expressed in STS cell lines and tissues. STS patients with increased RRM2 levels showed worse overall survival, disease-free survival, progression-free survival, and disease-specific survival. Further, overexpression of RRM2 in HT1080 cells induces proliferation, migration, invasion, and colony formation, whereas its silencing arrest the cell cycle at G0/G1 phase and induces apoptosis. Taken together, we established RRM2 to be positively associated with oncogenesis and prognosis of STS and therefore could be a promising prognostic marker and therapeutic target.

Still no Rest for the Reductases: Ribonucleotide Reductase (RNR) Structure and Function: An Update

Herein we present a multidisciplinary discussion of ribonucleotide reductase (RNR), the essential enzyme uniquely responsible for conversion of ribonucleotides to deoxyribonucleotides. This chapter primarily presents an overview of this multifaceted and complex enzyme, covering RNR's role in enzymology, biochemistry, medicinal chemistry, and cell biology. It further focuses on RNR from mammals, whose interesting and often conflicting roles in health and disease are coming more into focus. We present pitfalls that we think have not always been dealt with by researchers in each area and further seek to unite some of the field-specific observations surrounding this enzyme. Our work is thus not intended to cover any one topic in extreme detail, but rather give what we consider to be the necessary broad grounding to understand this critical enzyme holistically. Although this is an approach we have advocated in many different areas of scientific research, there is arguably no other single enzyme that embodies the need for such broad study than RNR. Thus, we submit that RNR itself is a paradigm of interdisciplinary research that is of interest from the perspective of the generalist and the specialist alike. We hope that the discussions herein will thus be helpful to not only those wanting to tackle RNR-specific problems, but also those working on similar interdisciplinary projects centering around other enzymes.

Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma

Lower-grade glioma (LGG) is characterized by genetic and transcriptional heterogeneity, and a dismal prognosis. Iron metabolism is considered central for glioma tumorigenesis, tumor progression and tumor microenvironment, although key iron metabolism-related genes are unclear. Here we developed and validated an iron metabolism-related gene signature LGG prognosis. RNA-sequence and clinicopathological data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were downloaded. Prognostic iron metabolism-related genes were screened and used to construct a risk-score model via differential gene expression analysis, univariate Cox analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO)-regression algorithm. All LGG patients were stratified into high- and low-risk groups, based on the risk score. The prognostic significance of the risk-score model in the TCGA and CGGA cohorts was evaluated with Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analysis. Risk- score distributions in subgroups were stratified by age, gender, the World Health Organization (WHO) grade, isocitrate dehydrogenase 1 (IDH1) mutation status, the O6-methylguanine-DNA methyl-transferase (MGMT) promoter-methylation status, and the 1p/19q co-deletion status. Furthermore, a nomogram model with a risk score was developed, and its predictive performance was validated with the TCGA and CGGA cohorts. Additionally, the gene set enrichment analysis (GSEA) identified signaling pathways and pathological processes enriched in the high-risk group. Finally, immune infiltration and immune checkpoint analysis were utilized to investigate the tumor microenvironment characteristics related to the risk score. We identified a prognostic 15-gene iron metabolism-related signature and constructed a risk-score model. High risk scores were associated with an age of > 40, wild-type IDH1, a WHO grade of III, an unmethylated MGMT promoter, and 1p/19q non-codeletion. ROC analysis indicated that the risk-score model accurately predicted 1-, 3-, and 5-year overall survival rates of LGG patients in the both TCGA and CGGA cohorts. KM analysis showed that the high-risk group had a much lower overall survival than the low-risk group (P < 0.0001). The nomogram model showed a strong ability to predict the overall survival of LGG patients in the TCGA and CGGA cohorts. GSEA analysis indicated that inflammatory responses, tumor-associated pathways, and pathological processes were enriched in high-risk group. Moreover, a high risk score correlated with the infiltration immune cells (dendritic cells, macrophages, CD4+ T cells, and B cells) and expression of immune checkpoint (PD1, PDL1, TIM3, and CD48). Our prognostic model was based on iron metabolism-related genes in LGG, can potentially aid in LGG prognosis, and provides potential targets against gliomas.

Large-scale and high-resolution mass spectrometry-based proteomics profiling defines molecular subtypes of esophageal cancer for therapeutic targeting

Esophageal cancer (EC) is a type of aggressive cancer without clinically relevant molecular subtypes, hindering the development of effective strategies for treatment. To define molecular subtypes of EC, we perform mass spectrometry-based proteomic and phosphoproteomics profiling of EC tumors and adjacent non-tumor tissues, revealing a catalog of proteins and phosphosites that are dysregulated in ECs. The EC cohort is stratified into two molecular subtypes-S1 and S2-based on proteomic analysis, with the S2 subtype characterized by the upregulation of spliceosomal and ribosomal proteins, and being more aggressive. Moreover, we identify a subtype signature composed of ELOA and SCAF4, and construct a subtype diagnostic and prognostic model. Potential drugs are predicted for treating patients of S2 subtype, and three candidate drugs are validated to inhibit EC. Taken together, our proteomic analysis define molecular subtypes of EC, thus providing a potential therapeutic outlook for improving disease outcomes in patients with EC.

PLEK2, RRM2, GCSH: A Novel WWOX-Dependent Biomarker Triad of Glioblastoma at the Crossroads of Cytoskeleton Reorganization and Metabolism Alterations

Glioblastoma is one of the deadliest human cancers. Its malignancy depends on cytoskeleton reorganization, which is related to, e.g., epithelial-to-mesenchymal transition and metastasis. The malignant phenotype of glioblastoma is also affected by the WWOX gene, which is lost in nearly a quarter of gliomas. Although the role of WWOX in the cytoskeleton rearrangement has been found in neural progenitor cells, its function as a modulator of cytoskeleton in gliomas was not investigated. Therefore, this study aimed to investigate the role of WWOX and its collaborators in cytoskeleton dynamics of glioblastoma. Methodology on RNA-seq data integrated the use of databases, bioinformatics tools, web-based platforms, and machine learning algorithm, and the obtained results were validated through microarray data. PLEK2, RRM2, and GCSH were the most relevant WWOX-dependent genes that could serve as novel biomarkers. Other genes important in the context of cytoskeleton (BMP4, CCL11, CUX2, DUSP7, FAM92B, GRIN2B, HOXA1, HOXA10, KIF20A, NF2, SPOCK1, TTR, UHRF1, and WT1), metabolism (MTHFD2), or correlation with WWOX (COL3A1, KIF20A, RNF141, and RXRG) were also discovered. For the first time, we propose that changes in WWOX expression dictate a myriad of alterations that affect both glioblastoma cytoskeleton and metabolism, rendering new therapeutic possibilities.

Proteomic Level Changes on Treatment in MCF-7/DDP Breast Cancer Drug- Resistant Cells

Background

LCL161, a SMAC’S small molecule mimetic, can bind to a variety of IAPs and activate Caspases. We found that on its own, LCL161induces apoptosis of drug-resistant breast cancer cells by binding to a variety of IAPs and activating Caspases. However, when LCL161 is used in combination with Caspase Inhibitors (CI), its capacity to induce apoptosis of breast cancer cells is enhanced.

Objective

To carry out proteomic and bioinformatics analysis of LCL161 in combination with CI. We aim to identify the key proteins and mechanisms of breast cancer drug-resistant apoptosis, thereby aiding in the breast cancer drug resistance treatment and identification of drug targeting markers.

Methods

Cell culture experiments were carried out to explore the effect of LCL161 combined with CI on the proliferation of breast cancer drug-resistant cells. Proteomic analysis was carried out to determine the protein expression differences between breast cancer drug-resistant cells and LCL161 combined with CI treated cells. Bioinformatics analysis was carried out to determine its mechanism of action. Validation of proteomics results was done using Parallel Reaction Monitoring (PRM).

Results

Cell culture experiments showed that LCL161 in combination with CI can significantly promote the apoptosis of breast cancer drug-resistant cells. Up-regulation of 92 proteins and down-regulation of 114 proteins protein were noted, of which 4 were selected for further validation.

Conclusion

Our results show that LCL161 combined with CI can promote the apoptosis of drug-resistant breast cancer cells by down-regulation of RRM2, CDK4, and ITGB1 expression through Cancer pathways, p53 or PI3K-AKT signaling pathway. In addition, the expression of CDK4, RRM2, and CDC20 can be down-regulated by the nuclear receptor pathway to affect DNA transcription and replication, thereby promoting apoptosis of breast cancer drug-resistant cells.

Systematic identification of clinically relevant miRNAs for potential miRNA-based therapy in lung adenocarcinoma

Lung adenocarcinoma (LUAD), the most common histological type of non-small cell lung cancer, is one of the most malignant and deadly diseases. Current treatments for advanced LUAD patients are far from ideal and require further improvements. Here, we utilized a systematic integrative analysis of LUAD microRNA sequencing (miRNA-seq) and RNA-seq data from The Cancer Genome Atlas (TCGA) to identify clinically relevant tumor suppressor miRNAs. Three miRNA candidates (miR-195-5p, miR-101-3p, and miR-338-5p) were identified based on their differential expressions, survival significance levels, correlations with targets, and an additive effect on survival among them. We further evaluated mimics of the three miRNAs to determine their therapeutic potential in inhibiting cancer progression. The results showed not only that each of the miRNA mimics alone but also the three miRNA mimics in combination were efficient at inhibiting tumor growth and progression with equal final concentrations, meaning that the three miRNA mimics in combination were more effective than the single miRNA mimics. Moreover, the combined miRNA mimics provided significant therapeutic effects in terms of reduced tumor volume and metastasis nodules in lung tumor animal models. Hence, our findings show the potential of using the three miRNAs in combination to treat LUAD patients with poor survival outcomes.

MicroRNA-520a Suppresses Pathogenesis and Progression of Non-Small-Cell Lung Cancer through Targeting the RRM2/Wnt Axis

MicroRNAs (miRNAs) regulate multiple cellular behaviors, and their aberrant expression is frequently associated with disease progression. This research focused on the effects of miR-520a on the development of non-small-cell lung cancer (NSCLC) and the molecules involved. Tumor and normal tissues from 24 patients with NSCLC were collected. Differentially expressed miRNAs between tumor tissues and normal tissues were screened using microarrays, and miR-520a was screened to be significantly poorly expressed in tumor samples. Artificial upregulation of miR-520a reduced proliferation, migration and invasion, and resistance to death of NSCLC A549 and H460 cells according to the MTT, EdU labeling, transwell, and flow cytometry assays, respectively. miR-520a upregulation suppressed growth and metastasis of xenograft tumors in vivo. The integrated bioinformatic analysis and dual luciferase assays suggested that miR-520a targeted ribonucleotide reductase subunit 2 (RRM2) mRNA and inactivated the Wnt/β-catenin signaling pathway in NSCLC cells. Upregulation of RRM2 enhanced the malignant behaviors of NSCLCs, but the oncogenic effects of RRM2 were blocked upon miR-520a overexpression. To conclude, this study evidenced that miR-520a inhibits NSCLC progression through suppressing RRM2 and the Wnt signaling pathway. This paper may offer novel insights into NSCLC treatment.

Identification and validation of a two-gene metabolic signature for survival prediction in patients with kidney renal clear cell carcinoma

Metabolic reprogramming contributes to the high mortality of advanced stage kidney renal clear cell carcinoma (KIRC), the most common renal cancer subtype. This study aimed to identify a metabolism-related gene (MRG) signature to improve survival prediction in KIRC patients. We downloaded RNA sequencing data and corresponding clinical information for KIRC and control samples from The Cancer Genome Atlas database and identified, based on an MRG dataset in the Molecular Signatures Database, 123 MRGs with differential expression in KIRC. Following Cox regression analysis and least absolute shrinkage and selection operator selection, RRM2 and ALDH6A1 were identified as prognosis-related genes and used to construct a prognostic signature with independent prognostic significance. After risk score-based patient separation, stratified survival analysis indicated that high-risk patients showed poorer overall survival than low-risk patients. We then constructed a clinical nomogram that showed a concordance index of 0.774 and good performance based upon calibration curves. Gene set enrichment analysis revealed several metabolic pathways significantly enriched in the target genes. The two-gene metabolic signature identified herein may represent a highly valuable tool for KIRC prognosis prediction, and might also help identify new metabolism-related biomarkers and therapeutic targets for KIRC.

Cyclin F Downregulation Affects Epithelial-Mesenchymal Transition Increasing Proliferation and Migration of the A-375 Melanoma Cell Line

Background

Cyclins are well-known cell cycle regulators. The activation of cyclin-dependent kinases by cyclins allows orchestration of the complicated cell cycle machinery and drives the cell from the G1 phase to the end of the mitotic phase. In recent years, it has become evident that cyclins are involved in processes beyond the cell cycle. Cyclin F does not activate CDKs but forms part of the Skp1-Cul1-F-box (SCF) complex where it is responsible for protein target recognition and subsequent degradation in a proteasome-dependent manner.

Results

Here, we report that the downregulation of cyclin F in the A-375 melanoma cell line increases cell viability and colony formation in a cell cycle independent manner. Lower levels of cyclin F do not appear to affect the cell cycle, based on flow cytometry measuring BrdU incorporation and propidium iodide staining. By means of immunofluorescence staining and Western blot analysis, we observed changes in cell morphology-related markers which suggested ongoing epithelial-mesenchymal transition (EMT) in response to cyclin F downregulation. Increases in vimentin and N-cadherin protein levels, decreases in levels of epithelial markers such as ZO-1, along with changes in morphology to a spindle-like shape with the appearance of actin stress fibers, are all hallmarks of EMT. These changes are associated with increased invasive and migratory potential, based on 2D migration assays. Moreover, we observe an increase in RhoABC, talin and paxillin levels, the proteins involved in controlling cell signaling and motility. Lastly, upon knocking down cyclin F expression, we observed a decrease in thrombospondin-1 expression, suggesting a role of cyclin F in angiogenesis.

Conclusion

Cyclin F depletion induces proliferation and EMT processes in the A-375 melanoma model.

High expression of RRM2 as an independent predictive factor of poor prognosis in patients with lung adenocarcinoma

Ribonucleotide reductase subunit M2 may play a role as a potential prognostic biomarker in several cancers. In this study, we evaluated whether RRM2 gene expression is associated with the prognosis of patients with lung adenocarcinoma (LUAD) using publicly available data from The Cancer Genome Atlas (TCGA). Wilcoxon signed-rank test and logistic regression were performed to evaluate the association between RRM2 expression and clinical features in patients with LUAD. Kaplan-Meier and Cox regression methods were used to examine the effect of RRM2 expression level in the overall survival, and a nomogram was performed to illustrate the correlation between the RRM2 gene expression and the risk of LUAD. TCGA data set was used for gene set enrichment analysis (GSEA). We also performed a further experiment in vitro to assess the effect of RRM2 expression on the proliferation and invasive abilities of LUAD cells and its key signaling pathway proteins. Our results revealed that the expression level of RRM2 in patients with LUAD was much higher than that in normal tissues (p = 3.99e-32). High expression of RRM2 was significantly associated with tumor stage (IV vs. I: OR = 3.02, p = 0.012) and TNM classification (T2 vs. T1: OR = 1.88, p = 0.001; N2 vs. N0: OR = 2.69, p < 0.001). Kaplan-Meier survival analysis showed that high expression of RRM2 was associated with a worse prognosis of LUAD compared low expression of RRM2 (p = 7.86e-04). Multivariate analysis showed that high RRM2 expression was an independent factor affecting overall survival (HR = 1.29, p < 0.001). The association between RRM2 gene expression and the risk of LUAD was presented in a nomogram. GSEA revealed that the cell cycle, p53 signaling pathway, DNA replication, small cell lung cancer, apoptosis, and pathways in cancer were differentially enriched in patients with high expression of RRM2. RRM2 over-expression promoted the proliferation and invasive abilities of LUAD cells. RRM2 over-expression increased the activation of Bcl-2 and E-cadherin signaling pathways, and reduced the activation of p53 signaling pathway. In summary, high RRM2 expression is an independent predictive factor of poor prognosis in patients with lung adenocarcinoma.

Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types

Studies describing the expression patterns and biomarkers for the tumoral process increase in number every year. The availability of new datasets, although essential, also creates a confusing landscape where common or critical mechanisms are obscured amidst the divergent and heterogeneous nature of such results. In this work, we manually curated the Gene Expression Omnibus using rigorous filtering criteria to select the most homogeneous and highest quality microarray and RNA-seq datasets from multiple types of cancer. By applying systems biology approaches, combined with machine learning analysis, we investigated possible frequently deregulated molecular mechanisms underlying the tumoral process. Our multi-approach analysis of 99 curated datasets, composed of 5,406 samples, revealed 47 differentially expressed genes in all analyzed cancer types, which were all in agreement with the validation using TCGA data. Results suggest that the tumoral process is more related to the overexpression of core deregulated machinery than the underexpression of a given gene set. Additionally, we identified gene expression similarities between different cancer types not described before and performed an overall survival analysis using 20 cancer types. Finally, we were able to suggest a core regulatory mechanism that could be frequently deregulated.

Independent prognostic implications of RRM2 in lung adenocarcinoma

Background: Ribonucleoside-diphosphate reductase subunit M2 (RRM2) is the catalytic subunit of ribonucleotide reductase and modulates the enzymatic activity, which is essential for DNA replication and repair. However, the role of RRM2 in lung adenocarcinoma (LUAD) remains unclear.

Methods: In this study, we explored the expression pattern and prognostic value of RRM2 in LUAD across TCGA, GEO, Oncomine, UALCAN, PrognoScan, and Kaplan-Meier Plotter, and confirmed its independent prognostic value via Cox analyses. LinkedOmics and GEPIA2 were applied to investigate co-expression and functional networks associated with RRM2. Besides, we used TIMER to assess the correlation between RRM2 and the main six types of tumor-infiltrating immune cells. Lastly, the correlations between immune signatures of immunomodulators, chemokines, and 28 tumor-infiltrating lymphocytes (TILs) and RRM2 were examined by tumor purity-corrected partial Spearman's rank correlation coefficient through TIMER portal.

Results:RRM2 was found upregulated in tumor tissues in TCGA-LUAD, and validated in multiple independent cohorts. Moreover, whether in TCGA or other cohorts, high RRM2 expression was found to be associated with poor survival. Cox analyses showed that high RRM2 expression was an independent risk factor for overall survival, disease-specific survival, and progression-free survival of LUAD. Functional network analysis suggested that RRM2 regulates RNA transport, oocyte meiosis, spliceosome, ribosome biogenesis in eukaryotes, and cellular senescence signaling through pathways involving multiple cancer-related kinases and E2F family. Also, RRM2 expression correlated with infiltrating levels of B cells, CD4+ T cells, and neutrophils. Subsequent analysis found that B cells and dendritic cells could predict the outcome of LUAD. B cells were identified as an independent risk factor among six types of immune cells through Cox analyses. At last, the correlation analysis showed RRM2 correlated with 67.68% (624/922) of the immune signatures we performed.

Conclusion: Our research showed that RRM2 could independently predict the prognosis of LUAD and was associated with immune infiltration. In particular, the tight relationship between RRM2 and B cell marker genes are the potential epicenter of the immune response and one of the critical factors affecting the prognosis. Our findings laid the foundation for further research on the immunomodulatory role of RRM2 in LUAD.

Identification of the potential biomarkers in patients with glioma: a weighted gene co-expression network analysis

Glioma is the most common brain tumor with high mortality. However, there are still challenges for the timely and accurate diagnosis and effective treatment of the tumor. One hundred and twenty-one samples with grades II, III and IV from the Gene Expression Omnibus database were used to construct gene co-expression networks to identify hub modules closely related to glioma grade, and performed pathway enrichment analysis on genes from significant modules. In gene co-expression network constructed by 2345 differentially expressed genes from 121 gene expression profiles for glioma, we identified the black and blue modules that associated with grading. The module preservation analysis based on 118 samples indicates that the two modules were replicable. Enrichment analysis showed that the extracellular matrix genes were enriched for blue module, while cell division genes were enriched for black module. According to survival analysis, 21 hub genes were significantly up-regulated and one gene was significantly down-regulated. What’s more, IKBIP, SEC24D, and FAM46A are the genes with little attention among the 22 hub genes. In this study, IKBIP, SEC24D, and FAM46A related to glioma were mentioned for the first time to the current knowledge, which might provide a new idea for us to study the disease in the future. IKBIP, SEC24D and FAM46A among the 22 hub genes identified that are related to the malignancy degree of glioma might be used as new biomarkers to improve the diagnosis, treatment and prognosis of glioma.

A novel hypoxic tumor microenvironment signature for predicting the survival, progression, immune responsiveness and chemoresistance of glioblastoma: a multi-omic study

The hypoxic tumor microenvironment (TME) was reported to promote the aggressive phenotype, progression, recurrence, and chemoresistance of glioblastoma (GBM). We developed and validated a hypoxia gene signature for individualized prognostic prediction in GBM patients. In total, 259 GBM-specific hypoxia-related genes (HRGs) were obtained in hypoxic cultured GBM cells compared with normoxic cells. By applying the k-means algorithm, TCGA GBM patients were divided into two subgroups, and the patients in Cluster 1 exhibited high HRG expression patterns, older age, and poor prognosis, which was validated in the CGGA cohort. Cox regression analyses were performed to generate an HRG-based risk score model consisting of five HRGs, which could reliably discriminate the overall survival (OS) and progression-free survival (PFS) of high- and low-risk patients in both the TCGA training and CGGA validation cohorts. Then, nomograms with the hypoxia signature for OS and PFS prediction were constructed for individualized survival prediction, better treatment decision-making, and follow-up scheduling. Finally, functional enrichment, immune infiltration, immunotherapy response prediction and chemotherapy resistance analyses demonstrated the vital roles of the hypoxic TME in the development, progression, multitherpy resistance of GBM. The hypoxia gene signature could serve as a promising prognostic predictor and potential therapeutic target to combat chemoresistant GBM.

Large-Scale Differential Gene Expression Transcriptomic Analysis Identifies a Metabolic Signature Shared by All Cancer Cells

Cancer-dependent metabolic rewiring is often manifested by selective expression of enzymes essential for the transformed cells’ viability. However, the metabolic variations between normal and transformed cells are not fully characterized, and therefore, a systematic analysis will result in the identification of unknown cellular mechanisms crucial for tumorigenesis. Here, we applied differential gene expression transcriptome analysis to examine the changes in metabolic gene profiles between a wide range of normal tissues and cancer samples. We found that, in contrast to normal tissues which exhibit a tissue-specific expression profile, cancer samples are more homogenous despite their diverse origins. This similarity is due to a “proliferation metabolic signature” (PMS), composed of 158 genes (87 upregulated and 71 downregulated gene sets), where 143 are common to all proliferative cells but 15 are cancer specific. Intriguingly, the PMS gene set is enriched for genes encoding rate-limiting enzymes, and its upregulated set with genes associated with poor patient outcome and essential genes. Among these essential genes is ribulose-5-phosphate-3-epimerase (RPE), which encodes a pentose phosphate pathway enzyme and whose role in cancer is still unclear. Collectively, we identified a set of metabolic genes that can serve as novel cancer biomarkers and potential targets for drug development.

Knockdown of lncRNA KCNQ1OT1 inhibits glioma progression by regulating miR-338-3p/RRM2

The dysregulated lncRNA play essential roles in glioma development. This study aimed to investigate the role and mechanism of lncRNA potassium voltage-gated channel subfamily Q member 1 opposite strand/ antisense transcript 1 (KCNQ1OT1) in glioma progression. Tumor tissues and adjacent normal samples were collected from 30 glioma patients. The expression levels of lncRNA KCNQ1OT1, microRNA (miR)-338-3p and ribonucleotide reductase M2 (RRM2) were detected by quantitative real-time polymerase chain reaction or western blot analyses. Levels of cell viability, apoptosis, cell migration and invasion in glioma cell lines were determined using cell counting kit-8, flow cytometry with annexin V-FITC and trans-well assays, respectively. The role of KCNQ1OT1 in glioma development in vivo was investigated using a xenograft model. The target association between miR-338-3p and KCNQ1OT1 or RRM2 was validated by luciferase reporter assay. The results found that expression of KCNQ1OT1 was enhanced in glioma tissues and cells, and KCNQ1OT1 knockdown inhibited cell viability, migration and invasion, and xenograft tumor growth, but promoted apoptosis. miR-338-3p was targeted via KCNQ1OT1 and could reverse the effect of KCNQ1OT1 on glioma progression. RRM2 was targeted via miR-338-3p and attenuated the suppressive effect of miR-338-3p on glioma cell viability, migration and invasion. Besides, KCNQ1OT1 overexpression increased RRM2 expression, and this event was weakened via miR-338-3p up-regulation. In conclusion, the present finding suggest that silencing of KCNQ1OT1 can suppress the development and progression of glioma by up-regulating miR-338-3p and down-regulating RRM2.

Systematically Dissecting the Function of RNA-Binding Proteins During Glioma Progression

RNA-binding proteins (RBPs) play important roles in regulating gene expression and dysregulation of RBPs have been observed in various types of cancer. However, the role of RBPs during glioma progression, and particular in Chinese patients, is only starting to be unveiled. Here, we systematically analyzed the somatic mutation, gene expression patterns of 2949 RBPs during glioma progression. Our comprehensive study reveals several of highly mutated genes (such as ATRX, TTN and SETD2) and differentially expressed genes (such as KIF4A, TTK and CEP55). Integration of the expression of RBPs and genes, we constructed a regulatory network in glioma and revealed the functional links between RBPs and cancer-related genes. Moreover, we identified the prognosis spectrum of RBPs during glioma progression. The expression of a number of RBPs, such as SNRPN and IGF2BP3, are significantly associated with overall survival of patients in all grades. Taken together, our analyses provided a valuable RBP resource during glioma progression, and revealed several candidates that potentially contribute to development of therapeutic targets for glioma.

Potential mechanism of RRM2 for promoting Cervical Cancer based on weighted gene co-expression network analysis

Cervical cancer is the most common gynecologic malignant tumor, with a high incidence in 50-55-year-olds. This study aims to investigate the potential molecular mechanism of RRM2 for promoting the development of cervical cancer based on The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). RRM2 was found to be significant upregulated in cervical tissue (P<0.05) by extracting the expression of RRM2 from TCGA, GSE63514, GSE7410, GSE7803 and GSE9750. Survival analysis indicated that the overall survival was significantly worse in the patients with high-expression of RRM2 (P<0.05). The top 1000 positively/negatively correlated genes with RRM2 by Pearson Correlation test were extracted. The gene co-expression network by Weighted Gene Co-Expression Network Analysis (WGCNA) with these genes and the clinical characteristics (lymphocyte infiltration, monocyte infiltration, necrosis, neutrophil infiltration, the number of normal/stromal/tumor cells and the number of tumor nuclei) was constructed. By screening the hub nodes from the co-expression network, results suggested that RRM2 may co-express with relevant genes to regulate the number of stromal/tumor cells and the process of lymphocyte infiltration to promote the progression of cervical cancer. RRM2 is likely to become a novel potential diagnostic and prognostic biomarker of cervical cancer and provide evidence to support the study of mechanisms for cervical cancer.

Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a widespread, common type of cancer in Asian countries, and the need for biomarker-matched molecularly targeted therapy for HCC has been increasingly recognized. However, the effective treatment for HCC is unclear. Therefore, identifying additional hub genes and pathways as novel prognostic biomarkers for HCC is necessary. In this study, the expression profiles of GSE121248, GSE45267 and GSE84402 were obtained from the Gene Expression Omnibus (GEO), including 132 HCC and 90 noncancerous liver tissues. Differentially expressed genes (DEGs) between HCC and noncancerous samples were identified by GEO2 R and Venn diagrams. In total, 109 DEGs were identified in these datasets, including 24 upregulated genes and 85 downregulated genes. Subsequently, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) preliminary analyses of the DEGs were performed using DAVID. The protein-protein interaction (PPI) network of the DEGs was constructed with the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized in Cytoscape. Module analysis of the PPI network was performed using MCODE to get hub genes. Moreover, the influence of the hub genes on overall survival was determined with Kaplan-Meier plotter. All hub genes were analyzed by Gene Expression Profiling Interactive Analysis (GEPIA) and KEGG. Overall, the hub genes DTL, CDK1, CCNB1, RACGAP1, ECT2, NEK2, BUB1B, PBK, TOP2A, ASPM, HMMR, RRM2, CDKN3, PRC1, and ANLN were upregulated in HCC, and the survival rate was lower for HCC with increased expression of these hub genes. CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway, and CCNB1, CDK1, and BUB1B were enriched in the cell cycle. In brief, we screened 15 hub genes and pathways to identify potential prognostic markers for HCC treatment. However, the specific occurrence and development of HCC with expression of the hub genes should be verified in vivo and in vitro.

Knockdown of ribonucleotide reductase regulatory subunit M2 increases the drug sensitivity of chronic myeloid leukemia to imatinib‑based therapy

Imatinib-based targeted treatment is the standard therapy for chronic myeloid leukemia (CML); however, drug resistance is an inevitable issue for imatinib-based CML treatment. Imatinib resistance can be ascribed to Bcr-Abl-dependent and independent resistance. In the present study, peripheral blood samples were collected from imatinib-sensitive (IS) and imatinib-resistant (IR) CML patients and transcriptome sequencing was carried out. From the RNA-seq data, a significantly altered IR-related gene (IRG), ribonucleotide reductase regulatory subunit M2 (RRM2) was identified. Using real-time quantitative fluorescence PCR (qF-PCR), we found that RRM2 was elevated in both IR CML patients and an IR cell line. Using reverse-transcription PCR (RT-PCR) and western blot analysis, we indicated that imatinib can increase RRM2 level in a dose-dependent manner in IR cells. We also demonstrated that RRM2 is involved in the Bcl-2/caspase cell apoptotic pathway and in the Akt cell signaling pathway, and therefore affects the cell survival following imatinib therapy. The present study, for the first time, indicates that RRM2 is responsible for drug resistance in imatinib-based therapy. Therefore, RRM2 gene can be considered as a potential therapeutic target in the clinical treatment of CML.