A Novel Mechanism Driving Poor-Prognosis Prostate Cancer: Overexpression of the DNA Repair Gene, Ribonucleotide Reductase Small Subunit M2 (RRM2)

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.

Targeting the Cell Cycle, RRM2 and NF-κB for the Treatment of Breast Cancers

A hallmark of cancer is the dysregulation of the cell cycle. The CDK4/6 inhibitor palbociclib is approved for treating advanced estrogen-receptor-positive breast cancer, but its success is limited by the development of acquired resistance owing to long-term therapy despite promising clinical outcomes. This situation necessitates the development of potential combination strategies. Here, we report that didox, an inhibitor of ribonucleotide reductase in combination with palbociclib, can overcome palbociclib resistance in ER-positive and ER-negative breast cancers. This study shows didox downregulates an element of the cell cycle checkpoint, cyclin D1, accompanied by a reduction in NF-κB activity in vitro and tumor growth inhibition of palbociclib-resistant ER positive breast cancer tumor growth in vivo. Furthermore, didox induces cell cycle arrest at G1 as well as reduces ROS generated by on-target effects of palbociclib on the cell cycle. Our current study also reports that the CCND1 and RRM2 upregulation associated with palbociclib-resistant breast cancers decreases upon ribonucleotide reductase inhibition. Our data present a novel and promising biomarker-driven combination therapeutic approach for the treatment of ER-positive and ER-negative breast cancers that involves the inhibition of the CDK4/6-cyclinD1/pRb cell cycle axis that merits further clinical investigation in human models.

ORAOV1, CCND1, and MIR548K Are the Driver Oncogenes of the 11q13 Amplicon in Squamous Cell Carcinoma

11q13 amplification is a frequent event in human cancer and in particular in squamous cell carcinomas (SCC). Despite almost invariably spanning 10 genes, it is unclear which genetic components of the amplicon are the key driver events in SCC. A combination of computational, in vitro, ex vivo, and in vivo models leveraging efficient primary human keratinocyte genome editing by Cas9-RNP electroporation, identified ORAOV1, CCND1, and MIR548K as the critical drivers of the amplicon in head and neck SCC. CCND1 amplification drives the cell cycle in a CDK4/6/RB1-independent fashion and may confer a novel dependency on RRM2. MIR548K contributes to epithelial-mesenchymal transition. Finally, we identify ORAOV1 as an oncogene that acts likely via its ability to modulate reactive oxygen species. Thus, the 11q13 amplicon drives SCC through at least three independent genetic elements and suggests therapeutic targets for this morbid and lethal disease.

IMPLICATIONS

This work demonstrates novel mechanisms and ways to target these mechanisms underlying the most common amplification in squamous cell carcinoma, one of the most prevalent and deadly forms of human cancer.

Ribonucleotide reductase M2 (RRM2): Regulation, function and targeting strategy in human cancer

Ribonucleotide reductase M2 (RRM2) is a small subunit in ribonucleotide reductases, which participate in nucleotide metabolism and catalyze the conversion of nucleotides to deoxynucleotides, maintaining the dNTP pools for DNA biosynthesis, repair, and replication. RRM2 performs a critical role in the malignant biological behaviors of cancers. The structure, regulation, and function of RRM2 and its inhibitors were discussed. RRM2 gene can produce two transcripts encoding the same ORF. RRM2 expression is regulated at multiple levels during the processes from transcription to translation. Moreover, this gene is associated with resistance, regulated cell death, and tumor immunity. In order to develop and design inhibitors of RRM2, appropriate strategies can be adopted based on different mechanisms. Thus, a greater appreciation of the characteristics of RRM2 is a benefit for understanding tumorigenesis, resistance in cancer, and tumor microenvironment. Moreover, RRM2-targeted therapy will be more attention in future therapeutic approaches for enhancement of treatment effects and amelioration of the dismal prognosis.

Oncogenic role of FOXM1 in human prostate cancer (Review)

Prostate cancer is the leading cause of cancer‑related mortality among men worldwide. In particular, castration‑resistant prostate cancer presents a formidable clinical challenge and emphasizes the need to develop novel therapeutic strategies. Forkhead box M1 (FOXM1) is a multifaceted transcription factor that is implicated in the acquisition of the multiple cancer hallmark capabilities in prostate cancer cells, including sustaining proliferative signaling, resisting cell death and the activation of invasion and metastasis. Elevated FOXM1 expression is frequently observed in prostate cancer, and in particular, FOXM1 overexpression is closely associated with poor clinical outcomes in patients with prostate cancer. In the present review, recent advances in the understanding of the oncogenic role of deregulated FOXM1 expression in prostate cancer were highlighted. In addition, the molecular mechanisms by which FOXM1 regulates prostate cancer development and progression were described, thereby providing knowledge and a conceptual framework for FOXM1. The present review also provided valuable insight into the inherent challenges associated with translating biomedical knowledge into effective therapeutic strategies for prostate cancer.

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.

Identifying genes associated with resistance to KRAS G12C inhibitors via machine learning methods

BACKGROUND

Targeted therapy has revolutionized cancer treatment, greatly improving patient outcomes and quality of life. Lung cancer, specifically non-small cell lung cancer, is frequently driven by the G12C mutation at the KRAS locus. The development of KRAS inhibitors has been a breakthrough in the field of cancer research, given the crucial role of KRAS mutations in driving tumor growth and progression. However, over half of patients with cancer bypass inhibition show limited response to treatment. The mechanisms underlying tumor cell resistance to this treatment remain poorly understood.

METHODS

To address above gap in knowledge, we conducted a study aimed to elucidate the differences between tumor cells that respond positively to KRAS (G12C) inhibitor therapy and those that do not. Specifically, we analyzed single-cell gene expression profiles from KRAS G12C-mutant tumor cell models (H358, H2122, and SW1573) treated with KRAS G12C (ARS-1620) inhibitor, which contained 4297 cells that continued to proliferate under treatment and 3315 cells that became quiescent. Each cell was represented by the expression levels on 8687 genes. We then designed an innovative machine learning based framework, incorporating seven feature ranking algorithms and four classification algorithms to identify essential genes and establish quantitative rules.

RESULTS

Our analysis identified some top-ranked genes, including H2AFZ, CKS1B, TUBA1B, RRM2, and BIRC5, that are known to be associated with the progression of multiple cancers.

CONCLUSION

Above genes were relevant to tumor cell resistance to targeted therapy. This study provides important insights into the molecular mechanisms underlying tumor cell resistance to KRAS inhibitor treatment.

The key cellular senescence related molecule RRM2 regulates prostate cancer progression and resistance to docetaxel treatment

BACKGROUND

Prostate cancer is a leading cause of cancer-related deaths among men worldwide. Docetaxel chemotherapy has proven effective in improving overall survival in patients with castration-resistant prostate cancer (CRPC), but drug resistance remains a considerable clinical challenge.

METHODS

We explored the role of Ribonucleotide reductase subunit M2 (RRM2), a gene associated with senescence, in the sensitivity of prostate cancer to docetaxel. We evaluated the RRM2 expression, docetaxel resistance, and ANXA1 expression in prostate cancer cell lines and tumour xenografts models. In addition, We assessed the impact of RRM2 knockdown, ANXA1 over-expression, and PI3K/AKT pathway inhibition on the sensitivity of prostate cancer cells to docetaxel. Furthermore, we assessed the sensitivity of prostate cancer cells to the combination treatment of COH29 and docetaxel.

RESULTS

Our results demonstrated a positive association between RRM2 expression and docetaxel resistance in prostate cancer cell lines and tumor xenograft models. Knockdown of RRM2 increased the sensitivity of prostate cancer cells to docetaxel, suggesting its role in mediating resistance. Furthermore, we observed that RRM2 stabilizes the expression of ANXA1, which in turn activates the PI3K/AKT pathway and contributes to docetaxel resistance. Importantly, we found that the combination treatment of COH29 and docetaxel resulted in a synergistic effect, further augmenting the sensitivity of prostate cancer cells to docetaxel.

CONCLUSION

Our findings suggest that RRM2 regulates docetaxel resistance in prostate cancer by stabilizing ANXA1-mediated activation of the PI3K/AKT pathway. Targeting RRM2 or ANXA1 may offer a promising therapeutic strategy to overcome docetaxel resistance in prostate cancer.

RRM2‑mediated Wnt/β‑catenin signaling pathway activation in lung adenocarcinoma: A potential prognostic biomarker

The present study aimed to investigate the role and mechanism of action of ribonucleotide reductase M2 (RRM2) in lung adenocarcinoma and its potential as a therapeutic target. Data of patients with lung adenocarcinoma from The Cancer Genome Atlas database were collected and analyzed to evaluate the potential of RRM2 as a biomarker. The expression of RRM2 was evaluated in the A549 cell line and its cisplatin-resistant A549/DDP cell line derivative by western blot and reverse transcription-quantitative PCR. The study also investigated cell proliferation and the mechanism by which RRM2 controls cellular cisplatin resistance using CCK-8 and colony-formation assays. In addition, cell migration was assessed using Transwell assays, and the cell cycle and apoptosis were examined using flow cytometry. RRM2 was highly expressed in lung adenocarcinoma and was associated with the clinical TMN stage. Functional enrichment analysis showed that RRM2 was enriched in the cell cycle. Immune cell infiltration analysis identified 12 types of immune cell that exhibited differences between patients expressing different levels of RRM2. Cellular assays revealed higher levels of RRM2 expression in A549/DDP cells than A549 cells, and its expression was induced by cisplatin. RRM2 knockdown decreased cell proliferation and migration, accelerated apoptosis and caused cell cycle arrest in the S-phase, increasing the sensitivity of A549 and A549/DDP cells to cisplatin through the Wnt/β-catenin signaling pathway. Overexpression of β-catenin reduced the effects of RRM2 knockdown on A549 cells. Lung adenocarcinoma growth may be influenced by RRM2 through the Wnt/β-catenin signaling pathway, suggesting a potential pathway for cancer progression.

RRM2 as a novel prognostic and therapeutic target of NF1-associated MPNST

BACKGROUND

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas that typically develop in the setting of neurofibromatosis type 1 (NF1) and cause significant morbidity. Conventional therapies are often ineffective for MPNSTs. Ribonucleotide reductase subunit M2 (RRM2) is involved in DNA synthesis and repair, and is overexpressed in multiple cancers. However, its role in NF1-associated MPNSTs remains unknown. Our objective was to determine the therapeutic and prognostic potential of RRM2 in NF1-associated MPNSTs.

METHODS

Identification of hub genes was performed by using NF1-associated MPNST microarray datasets. We detected RRM2 expression by immunochemical staining in an MPNST tissue microarray, and assessed the clinical and prognostic significance of RRM2 in an MPNST cohort. RRM2 knockdown and the RRM2 inhibitor Triapine were used to assess cell proliferation and apoptosis in NF1-associated MPNST cells in vitro and in vivo. The underlying mechanism of RRM2 in NF1-associated MPNST was revealed by transcriptome analysis.

RESULTS

RRM2 is a key hub gene and its expression is significantly elevated in NF1-associated MPNST. We revealed that high RRM2 expression accounted for a larger proportion of NF1-associated MPNSTs and confirmed the correlation of high RRM2 expression with poor overall survival. Knockdown of RRM2 inhibited NF1-associated MPNST cell proliferation and promoted apoptosis and S-phase arrest. The RRM2 inhibitor Triapine displayed dose-dependent inhibitory effects in vitro and induced significant tumor growth reduction in vivo in NF1-associated MPNST. Analysis of transcriptomic changes induced by RRM2 knockdown revealed suppression of the AKT-mTOR signaling pathway. Overexpression of RRM2 activates the AKT pathway to promote NF1-associated MPNST cell proliferation.

CONCLUSIONS

RRM2 expression is significantly elevated in NF1-associated MPNST and that high RRM2 expression correlates with poorer outcomes. RRM2 acts as an integral part in the promotion of NF1-associated MPNST cell proliferation via the AKT-mTOR signaling pathway. Inhibition of RRM2 may be a promising therapeutic strategy for NF1-associated MPNST.

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.

Inhibition of RRM2 radiosensitizes glioblastoma and uncovers synthetic lethality in combination with targeting CHK1

Glioblastoma (GBM) is an aggressive malignant primary brain tumor. Radioresistance largely contributes to poor clinical outcomes in GBM patients. We targeted ribonucleotide reductase subunit 2 (RRM2) with triapine to radiosensitize GBM. We found RRM2 is associated with increasing tumor grade, is overexpressed in GBM over lower grade gliomas and normal tissue, and is associated with worse survival. We found silencing or inhibition of RRM2 by siRNA or triapine sensitized GBM cells to ionizing radiation (IR) and delayed resolution of IR-induced γ-H2AX nuclear foci. In vivo, triapine and IR reduced tumor growth and increased mouse survival. Intriguingly, triapine led to RRM2 upregulation and CHK1 activation, suggesting a CHK1-dependent RRM2 upregulation following RRM2 inhibition. Consistently, silencing or inhibition of CHK1 with rabusertib abolished the triapine-induced RRM2 upregulation. Accordingly, combining rabusertib and triapine resulted in synthetic lethality in GBM cells. Collectively, our results suggest RRM2 is a promising therapeutic target for GBM, and targeting RRM2 with triapine sensitizes GBM cells to radiation and independently induces synthetic lethality of GBM cells with CHK1 inhibition. Our findings suggest combining triapine with radiation or rabusertib may improve therapeutic outcomes in GBM.

LncRNA SNHG4 promotes prostate cancer cell survival and resistance to enzalutamide through a let-7a/RREB1 positive feedback loop and a ceRNA network

BACKGROUND

Prostate cancer threatens the health of men over sixty years old, and its incidence ranks first among all urinary tumors among men. Enzalutamide remains the first-line drug for castration-resistant prostate cancer, however, tumors inevitably become resistant to enzalutamide. Hence, it is of great importance to investigate the mechanisms that induce enzalutamide resistance in prostate cancer cells.

METHODS

Bioinformatic analyzing approaches were used to identified the over-expressed genes in prostate cancer tumor tissues from three GEO datasets. qRT-PCR, western blotting and immunochemistry/In situ hybridization staining assays were performed to assess the expression of SNHG4, RRM2, TK1, AURKA, EZH2 and RREB1. Cell cycle was measured by flow cytometry. CCK-8, plate colony formation and EdU assays were performed to assess the cell proliferation. Senescence-associated β-Gal assay was used to detect the cell senescence level. γ-H2AX staining assay was performed to assess the DNA damages of PCa cells. Luciferase reporter assay and RNA immunoprecipitation assay were performed to verify the RNA-RNA interactions. Chromatin immunoprecipitation assay was performed to assess the bindings between protein and genomic DNA.

RESULTS

We found that RRM2 and NUSAP1 are highly expressed in PCa tumors and significantly correlated with poor clinical outcomes in PCa patients. Bioinformatic analysis as well as experimental validation suggested that SNHG4 regulates RRM2 expression via a let-7 miRNA-mediated ceRNA network. In addition, SNHG4 or RRM2 knockdown significantly induced cell cycle arrest and cell senescence, and inhibited DNA damage repair and cell proliferation, and the effects can be partially reversed by let-7a knockdown or RRM2 reoverexpression. In vitro and in vivo experiments showed that SNHG4 overexpression markedly enhanced cell resistance to enzalutamide. RREB1 was demonstrated to transcriptionally regulate SNHG4, and RREB1 was also validated to be a target of let-7a and thereby regulated by the SNHG4/let-7a feedback loop.

CONCLUSION

Our study uncovered a novel molecular mechanism of lncRNA SNHG4 in driving prostate cancer progression and enzalutamide resistance, revealing the critical roles and therapeutic potential of RREB1, SNHG4, RRM2 and let-7 miRNAs in anticancer therapy.

Unveiling the prognostic significance of SOX5 in esophageal squamous cell carcinoma: a comprehensive bioinformatic and experimental analysis

BACKGROUND

This study aimed to investigate the expression and prognostic significance of SOX5 in esophageal squamous cell carcinoma (ESCC).

METHODS

Gene Expression Omnibus (GEO) data were analyzed to assess SOX5 expression in ESCC and normal tissues. Survival analysis was performed to evaluate its prognostic significance. Pathway enrichment analysis was conducted to identify pathways associated with low SOX5 expression. Methylation status of CpG sites in ESCC cases was examined, and SOX5 expression was evaluated. Differential expression and ChIP-seq data analyses were used to identify genes significantly correlated with SOX5 and to obtain target genes. A protein-protein interaction (PPI) network was constructed using hub genes, and their association with immune cell infiltration was determined. In vitro ESCC cell experiments validated the findings.

RESULTS

SOX5 was significantly downregulated in ESCC samples compared to normal samples. Its downregulation was associated with shorter survival in ESCC patients. Pathway enrichment analysis revealed enrichment in regulated necrosis, NLRP3 inflammasome, formation of the cornified envelope, and PD-1 signaling. Methylation status of two CpG sites negatively correlated with SOX5 expression. Differential expression analysis identified 122 genes significantly correlated with SOX5, and 28 target genes were obtained from ChIP-seq analysis. Target genes were enriched in DNA replication, cell cycle, spindle, and ATPase activity. Five hub genes were identified, and the PPI network showed significant associations with immune cell infiltration. In vitro experiments confirmed SOX5 downregulation, upregulation of hub genes, and their functional effects on ESCC cell apoptosis and proliferation.

CONCLUSIONS

These findings enhance understanding of SOX5 in ESCC and potential therapeutic strategies.

Deciphering the Biology of Circulating Tumor Cells through Single-Cell RNA Sequencing: Implications for Precision Medicine in Cancer

Circulating tumor cells (CTCs) hold unique biological characteristics that directly involve them in hematogenous dissemination. Studying CTCs systematically is technically challenging due to their extreme rarity and heterogeneity and the lack of specific markers to specify metastasis-initiating CTCs. With cutting-edge technology, single-cell RNA sequencing (scRNA-seq) provides insights into the biology of metastatic processes driven by CTCs. Transcriptomics analysis of single CTCs can decipher tumor heterogeneity and phenotypic plasticity for exploring promising novel therapeutic targets. The integrated approach provides a perspective on the mechanisms underlying tumor development and interrogates CTCs interactions with other blood cell types, particularly those of the immune system. This review aims to comprehensively describe the current study on CTC transcriptomic analysis through scRNA-seq technology. We emphasize the workflow for scRNA-seq analysis of CTCs, including enrichment, single cell isolation, and bioinformatic tools applied for this purpose. Furthermore, we elucidated the translational knowledge from the transcriptomic profile of individual CTCs and the biology of cancer metastasis for developing effective therapeutics through targeting key pathways in CTCs.

Diosmetin suppresses the progression of ESCC by CDK2/Rb/E2F2/RRM2 pathway and synergies with cisplatin

Cisplatin (CDDP) is the first-line drug in the clinical treatment of esophageal squamous cell carcinoma (ESCC), which has severe nephrotoxicity. Diosmetin (DIOS) can protect kidney from oxidative damage, however, its function in ESCC is unknown. This study aims to explore the effect and mechanism of DIOS on ESCC and its combined effect with CDDP. Herein, we found that DIOS significantly inhibited the progression of ESCC in vitro and in vivo. Furthermore, the anti-tumor effect of DIOS was not statistically different from that of CDDP. Mechanically, transcriptomics revealed that DIOS inhibited the E2F2/RRM2 signaling pathway. The transcriptional regulation of RRM2 by E2F2 was verified by luciferase assay. Moreover, docking model, CETSA, pull-down assay and CDK2 inhibitor assay confirmed that DIOS directly targeted CDK2, leading to significant suppression of ESCC. Additionally, the patient-derived xenografts (PDX) model showed that the combination of DIOS and CDDP significantly inhibited the growth of ESCC. Importantly, the combined treatment with DIOS and CDDP significantly reduced the mRNA expression levels of kidney injury biomarkers KIM-1 and NGAL in renal tissue, as well as the levels of blood urea nitrogen, serum creatinine and blood uric acid compared to the single treatment with CDDP. In conclusion, DIOS could be an effective drug and a potential chemotherapeutic adjuvant for ESCC treatment. Furthermore, DIOS could reduce the nephrotoxicity of CDDP to some extent.

C11orf54 promotes DNA repair via blocking CMA-mediated degradation of HIF1A

C11orf54 is an ester hydrolase highly conserved across different species. C11orf54 has been identified as a biomarker protein of renal cancers, but its exact function remains poorly understood. Here we demonstrate that C11orf54 knockdown decreases cell proliferation and enhances cisplatin-induced DNA damage and apoptosis. On the one hand, loss of C11orf54 reduces Rad51 expression and nuclear accumulation, which results in suppression of homologous recombination repair. On the other hand, C11orf54 and HIF1A competitively interact with HSC70, knockdown of C11orf54 promotes HSC70 binding to HIF1A to target it for degradation via chaperone-mediated autophagy (CMA). C11orf54 knockdown-mediated HIF1A degradation reduces the transcription of ribonucleotide reductase regulatory subunit M2 (RRM2), which is a rate-limiting RNR enzyme for DNA synthesis and DNA repair by producing dNTPs. Supplement of dNTPs can partially rescue C11orf54 knockdown-mediated DNA damage and cell death. Furthermore, we find that Bafilomycin A1, an inhibitor of both macroautophagy and chaperone-mediated autophagy, shows similar rescue effects as dNTP treatment. In summary, we uncover a role of C11orf54 in regulating DNA damage and repair through CMA-mediated decreasing of HIF1A/RRM2 axis.

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.

Over-expression of RRM2 predicts adverse prognosis correlated with immune infiltrates: A potential biomarker for hepatocellular carcinoma

Background

Ribonucleotide reductase regulatory subunit M2 (RRM2) has been reported to be an oncogene in some malignant tumors, such as lung adenocarcinoma, oral squamous cell carcinoma, glioblastoma, and breast cancer. However, the clinical significance of RRM2 in hepatocellular carcinoma has been less studied. The aim of this study was to assess the importance of RRM2 in hepatocellular carcinoma (HCC) based on the Cancer Genome Atlas (TCGA) database.

Methods

The RRM2 expression levels and clinical features were downloaded from the TCGA database. Immunohistochemistry results between tumor tissues and normal tissues were downloaded from the Proteinatlas database. Meanwhile, the expression levels of RRM2 in tumor and paraneoplastic tissues were further verified by qRT-PCR and Western Blotting. Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein-interactions (PPI) network were constructed to analyze RRM2-related downstream molecules. In addition, RRM2 expression-related pathways performed by gene set enrichment analysis (GSEA). Association analysis of RRM2 gene expression and immune infiltration was performed by single-sample GSEA (ssGSEA).

Results

The RRM2 expression level in tumor tissues was higher than normal tissues (P <0.001). The elevated expression of RRM2 in HCC was significantly correlated with T stage (P <0.05), pathologic stage (P <0.05), tumor status (P <0.05), histologic grade (P<0.001), and AFP (P <0.001). HCC with higher RRM2 expression was positively associated with worse OS (overall survival), PFS (progression-free survival), and DSS (disease-specific survival). In the univariate analysis, the expression of RRM2, T stage, M stage, pathologic stage, and tumor status were negatively correlated with OS (P <0.05). Further analysis using multivariate Cox regression showed that tumor status (P<0.01) and RRM2 expression (P<0.05) were independent prognostic factors of OS in HCC. GO/KEGG analysis showed that the critical biological process (chromosome condensation and p53 signaling pathway) might be the possible function mechanism in promoting HCC. Moreover, GSEA showed that several pathways were enriched in RRM2 high-expression samples, including PD-1 signaling, cell cycle, P27 pathway, and T cell receptor signaling pathway. RRM2 was significantly correlated with the infiltration level of CD8 T cells, Cytotoxic cells, DCs, Neutrophils, NK cells, and T helper cells (P <0.05).

Conclusion

Over-expression of RRM2 predict adverse prognosis and is correlated with immune infiltrates in HCC. RRM2 may be a significant molecular biomarker for HCC diagnosis and prognosis.

OGT and FLAD1 Genes Had Significant Prognostic Roles in Progressive Pathogenesis in Prostate Cancer

PURPOSE

This study aimed to identify metabolic genes associated with non-metastatic prostate cancer progression using The Cancer Genome Atlas (TCGA) datasets and validate their prognostic role by assessing patients' immunohistochemical prostatectomy specimens.

MATERIALS AND METHODS

Several metabolic candidate genes analyzed were highly correlated with cancer progression to biochemical recurrence (BCR) and deaths in 335 patients' genetic information from TCGA datasets. Those candidate genes and their expressions in tissue specimens were validated retrospectively by immunohistochemical analysis of radical prostatectomy specimens collected from 514 consecutive patients with non-metastatic prostate cancer between 2000 and 2015. The Cox proportional-hazards model was used to predict the prognostic role of each candidate gene expression in BCR and survival prognoses with a statistical significance of p-value <0.05. Twenty metabolic genes were identified by own developed software (Targa; https://github.com/cgab-ncc/TarGA), whose median expression levels consistently increased with cancer progression to the BCR and deaths.

RESULTS

Five metabolic genes (MAT2A, FLAD1, UGDH, OGT, and RRM2) were found to be significantly involved in the overall survival in the TCGA dataset. The immunohistochemical validation and clinicopathological data showed that OGT (hazard ratio [HR], 1.002; 95% confidence interval [CI], 1.001-1.003) and FLAD1 (HR, 1.010; 95% CI, 1.003-1.017) remained significant factors for BCR and cancer-specific survival, respectively, in the multivariate analysis even after adjusting for confounding clinicopathological parameters (p<0.05).

CONCLUSIONS

OGT and FLAD1 showed significant prognostic factors of disease progression, even after adjustment for confounding clinicopathological parameters in non-metastatic prostate cancer.

A machine learning framework develops a DNA replication stress model for predicting clinical outcomes and therapeutic vulnerability in primary prostate cancer

Recent studies have identified DNA replication stress as an important feature of advanced prostate cancer (PCa). The identification of biomarkers for DNA replication stress could therefore facilitate risk stratification and help inform treatment options for PCa. Here, we designed a robust machine learning-based framework to comprehensively explore the impact of DNA replication stress on prognosis and treatment in 5 PCa bulk transcriptomic cohorts with a total of 905 patients. Bootstrap resampling-based univariate Cox regression and Boruta algorithm were applied to select a subset of DNA replication stress genes that were more clinically relevant. Next, we benchmarked 7 survival-related machine-learning algorithms for PCa recurrence using nested cross-validation. Multi-omic and drug sensitivity data were also utilized to characterize PCa with various DNA replication stress. We found that the hyperparameter-tuned eXtreme Gradient Boosting model outperformed other tuned models and was therefore used to establish a robust replication stress signature (RSS). RSS demonstrated superior performance over most clinical features and other PCa signatures in predicting PCa recurrence across cohorts. Lower RSS was characterized by enriched metabolism pathways, high androgen activity, and a favorable prognosis. In contrast, higher RSS was significantly associated with TP53, RB1, and PTEN deletion, exhibited increased proliferation and DNA replication stress, and was more immune-suppressive with a higher chance of immunotherapy response. In silico screening identified 13 potential targets (e.g. TOP2A, CDK9, and RRM2) from 2249 druggable targets, and 2 therapeutic agents (irinotecan and topotecan) for RSS-high patients. Additionally, RSS-high patients were more responsive to taxane-based chemotherapy and Poly (ADP-ribose) polymerase inhibitors, whereas RSS-low patients were more sensitive to androgen deprivation therapy. In conclusion, a robust machine-learning framework was used to reveal the great potential of RSS for personalized risk stratification and therapeutic implications in PCa.

MicroRNA-1 attenuates the growth and metastasis of small cell lung cancer through CXCR4/FOXM1/RRM2 axis

BACKGROUND

Small cell lung cancer (SCLC) is an aggressive lung cancer subtype that is associated with high recurrence and poor prognosis. Due to lack of potential drug targets, SCLC patients have few therapeutic options. MicroRNAs (miRNAs) provide an interesting repertoire of therapeutic molecules; however, the identification of miRNAs regulating SCLC growth and metastasis and their precise regulatory mechanisms are not well understood.

METHODS

To identify novel miRNAs regulating SCLC, we performed miRNA-sequencing from donor/patient serum samples and analyzed the bulk RNA-sequencing data from the tumors of SCLC patients. Further, we developed a nanotechnology-based, highly sensitive method to detect microRNA-1 (miR-1, identified miRNA) in patient serum samples and SCLC cell lines. To assess the therapeutic potential of miR-1, we developed various in vitro models, including miR-1 sponge (miR-1Zip) and DOX-On-miR-1 (Tet-ON) inducible stable overexpression systems. Mouse models derived from intracardiac injection of SCLC cells (miR-1Zip and DOX-On-miR-1) were established to delineate the role of miR-1 in SCLC metastasis. In situ hybridization and immunohistochemistry were used to analyze the expression of miR-1 and target proteins (mouse and human tumor specimens), respectively. Dual-luciferase assay was used to validate the target of miR-1, and chromatin immunoprecipitation assay was used to investigate the protein-gene interactions.

RESULTS

A consistent downregulation of miR-1 was observed in tumor tissues and serum samples of SCLC patients compared to their matched normal controls, and these results were recapitulated in SCLC cell lines. Gain of function studies of miR-1 in SCLC cell lines showed decreased cell growth and oncogenic signaling, whereas loss of function studies of miR-1 rescued this effect. Intracardiac injection of gain of function of miR-1 SCLC cell lines in the mouse models showed a decrease in distant organ metastasis, whereas loss of function of miR-1 potentiated growth and metastasis. Mechanistic studies revealed that CXCR4 is a direct target of miR-1 in SCLC. Using unbiased transcriptomic analysis, we identified CXCR4/FOXM1/RRM2 as a unique axis that regulates SCLC growth and metastasis. Our results further showed that FOXM1 directly binds to the RRM2 promoter and regulates its activity in SCLC.

CONCLUSIONS

Our findings revealed that miR-1 is a critical regulator for decreasing SCLC growth and metastasis. It targets the CXCR4/FOXM1/RRM2 axis and has a high potential for the development of novel SCLC therapies. MicroRNA-1 (miR-1) downregulation in the tumor tissues and serum samples of SCLC patients is an important hallmark of tumor growth and metastasis. The introduction of miR-1 in SCLC cell lines decreases cell growth and metastasis. Mechanistically, miR-1 directly targets CXCR4, which further prevents FOXM1 binding to the RRM2 promoter and decreases SCLC growth and metastasis.

Identification and validation of an E2F-related gene signature for predicting recurrence-free survival in human prostate cancer

BACKGROUND

It is well-established that biochemical recurrence is detrimental to prostate cancer (PCa). In the present study, we explored the mechanisms underlying PCa progression.

METHODS

Five cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases were used to perform gene set variation analysis (GSVA) between nonrecurrent and recurrent PCa patients. We obtained the intersection of pathway enrichment results and extracted the corresponding gene list. LASSO Cox regression analysis was used to identify recurrence-free survival (RFS)-related significant genes and establish an RFS prediction gene signature and nomogram. MTT and colony formation assays were conducted to validate our findings.

RESULTS

The E2F signaling pathway was activated in recurrent PCa patients compared to nonrecurrent patients. We established an E2F-related gene signature for RFS prediction based on the four identified E2F-related genes (CDKN2C, CDKN3, RACGAP1, and RRM2) using LASSO Cox regression in the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. The risk score of each patient in MSKCC was calculated based on the expression levels of CDKN2C, CDKN3, RACGAP1, and RRM2. PCa patients with low-risk scores exhibited higher RFS than those with high-risk scores. Receiver operating characteristic (ROC) curve analysis validated the good performance and prognostic accuracy of the E2F-related gene signature, which was validated in the TCGA-prostate adenocarcinoma (TCGA-PRAD) cohort. Compared to patients with low Gleason scores and early T stages, PCa patients with high Gleason scores and advanced T stages had high-risk scores. Moreover, the E2F-related gene signature-based nomogram yielded good performance in RFS prediction. Functional experiments further confirmed these results.

CONCLUSIONS

The E2F signaling pathway is associated with biochemical recurrence in PCa. Our established E2F-related gene signature and nomogram yielded good accuracy in predicting the biochemical recurrence in PCa.

ERK Inhibitor Ulixertinib Inhibits High-Risk Neuroblastoma Growth In Vitro and In Vivo

Neuroblastoma (NB) is a pediatric tumor of the peripheral nervous system. Approximately 80% of relapsed NB show RAS-MAPK pathway mutations that activate ERK, resulting in the promotion of cell proliferation and drug resistance. Ulixertinib, a first-in-class ERK-specific inhibitor, has shown promising antitumor activity in phase 1 clinical trials for advanced solid tumors. Here, we show that ulixertinib significantly and dose-dependently inhibits cell proliferation and colony formation in different NB cell lines, including PDX cells. Transcriptomic analysis revealed that ulixertinib extensively inhibits different oncogenic and neuronal developmental pathways, including EGFR, VEGF, WNT, MAPK, NGF, and NTRK1. The proteomic analysis further revealed that ulixertinib inhibits the cell cycle and promotes apoptosis in NB cells. Additionally, ulixertinib treatment significantly sensitized NB cells to the conventional chemotherapeutic agent doxorubicin. Furthermore, ulixertinib potently inhibited NB tumor growth and prolonged the overall survival of the treated mice in two different NB mice models. Our preclinical study demonstrates that ulixertinib, either as a single agent or in combination with current therapies, is a novel and practical therapeutic approach for NB.

Identification of the effect and mechanism of Yiyi Fuzi Baijiang powder against colorectal cancer using network pharmacology and experimental validation

Background: Yiyi Fuzi Baijiang powder (YFBP) is a traditional Chinese medicine used to treat colorectal cancer, although its bioactivity and mechanisms of action have not been studied in depth yet. The study intended to identify the potential targets and signaling pathways affected by YFBP during the treatment of colorectal cancer through pharmacological network analysis and to further analyze its chemical compositions and molecular mechanisms of action. Methods: The Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicine Integrated Database (TCMID), HitPredict (HIT), and Search Tool for Interactions of Chemicals (STITCH) databases were used to screen the bioactive components and promising targets of YFBP. Targets related to colorectal cancer were retrieved from the GeneCards and Gene Ontology databases. Cytoscape software was used to construct the "herb-active ingredient-target" network. The STRING database was used to construct and analyze protein-protein interactions (PPIs). Afterward, the R packages clusterProfiler and Cytoscape Hub plug-in were used to perform Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of target genes. The results of the network pharmacological analysis were also experimentally validated. Results: In total, 33 active components and 128 target genes were screened. Among them, 46 target genes were considered potential therapeutic targets that crossed the CRC target genes. The network pharmacology analysis showed that the active components of YFBP were correlated positively with CRC inflammatory target genes such as TLR4, TNF, and IL-6. The inflammation-related signaling pathways affected by the active components included the TNF-α, interleukin-17, and toll-like receptor signaling pathways. The active ingredients of YFBP, such as luteolin, β-sitosterol, myristic acid, and vanillin, may exert anti-tumor effects by downregulating SMOX expression via anti-inflammatory signaling and regulation of the TLR4/NF-κB signaling pathway. Conclusion: In the present study, the potential active components, potential targets, and key biological pathways involved in the YFBP treatment of CRC were determined, providing a theoretical foundation for further anti-tumor research.

Comprehensive bioinformatics analysis of ribonucleoside diphosphate reductase subunit M2(RRM2) gene correlates with prognosis and tumor immunotherapy in pan-cancer

Ribonucleotide reductase (RNR) small subunit M2 (RRM2) levels are known to regulate the activity of RNR, a rate-limiting enzyme in the synthesis of deoxyribonucleotide triphosphates (dNTPs) and essential for both DNA replication and repair. The high expression of RRM2 enhances the proliferation of cancer cells, thereby implicating its role as an anti-cancer agent. However, little research has been performed on its role in the prognosis of different types of cancers. This pan-cancer study aimed to evaluate the effect of high expression of RRM2 the tumor prognosis based on clinical information collected from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We found RRM2 gene was highly expressed in 30 types of cancers. And we performed a pan-cancer analysis of the genetic alteration status and methylation of RRM2. Results indicated that RRM2 existed hypermethylation, associated with m6A, m1A, and m5C related genes. Subsequently, we explored the microRNAs (miRNA), long non-coding RNAs (lncRNA), and the transcription factors responsible for the high expression of RRM2 in cancer cells. Results indicated that has-miR-125b-5p and has-miR-30a-5p regulated the expression of RRM2 along with transcription factors, such as CBFB, E2F1, and FOXM. Besides, we established the competing endogenous RNA (ceRNA) diagram of lncRNAs-miRNAs-circular RNAs (circRNA) involved in the regulation of RRM2 expression. Meanwhile, our study demonstrated that high-RRM2 levels correlated with patients' worse prognosis survival and immunotherapy effects through the consensus clustering and risk scores analysis. Finally, we found RRM2 regulated the resistance of immune checkpoint inhibitors through the PI3K-AKT single pathways. Collectively, our findings elucidated that high expression of RRM2 correlates with prognosis and tumor immunotherapy in pan-cancer. Moreover, these findings may provide insights for further investigation of the RRM2 gene as a biomarker in predicting immunotherapy's response and therapeutic target.

Targeting the USP7/RRM2 axis drives senescence and sensitizes melanoma cells to HDAC/LSD1 inhibitors

Deubiquitinating enzymes are key regulators of the ubiquitin-proteasome system and cell cycle, and their dysfunction leads to tumorigenesis. Our in vivo drop-out screens in patient-derived xenograft models identify USP7 as a regulator of melanoma. We show that USP7 downregulation induces cellular senescence, arresting melanoma growth in vivo and proliferation in vitro in BRAF- and NRAS-mutant melanoma. We provide a comprehensive understanding of targets and networks affected by USP7 depletion by performing a global transcriptomic and proteomics analysis. We show that RRM2 is a USP7 target and is regulated by USP7 during S phase of the cell cycle. Ectopic expression of RRM2 in USP7-depleted cells rescues the senescent phenotype. Pharmacological inhibition of USP7 by P5091 phenocopies the shUSP7-induced senescent phenotype. We show that the bifunctional histone deacetylase (HDAC)/LSD1 inhibitor domatinostat has an additive antitumor effect, eliminating P5091-induced senescent cells, paving the way to a therapeutic combination for individuals with melanoma.

Identifying potential prognosis markers in hepatocellular carcinoma via integrated bioinformatics analysis and biological experiments

Background: Hepatocellular carcinoma is one kind of clinical common malignant tumor with a poor prognosis, and its pathogenesis remains to be clarified urgently. This study was performed to elucidate key genes involving HCC by bioinformatics analysis and experimental evaluation.

Methods: We identified common differentially expressed genes (DEGs) based on gene expression profile data of GSE60502 and GSE84402 from the Gene Expression Omnibus (GEO) database. Gene Ontology enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, REACTOME pathway enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used to analyze functions of these genes. The protein-protein interaction (PPI) network was constructed using Cytoscape software based on the STRING database, and Molecular Complex Detection (MCODE) was used to pick out two significant modules. Hub genes, screened by the CytoHubba plug-in, were validated by Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (HPA) database. Then, the correlation between hub genes expression and immune cell infiltration was evaluated by Tumor IMmune Estimation Resource (TIMER) database, and the prognostic values were analyzed by Kaplan-Meier plotter. Finally, biological experiments were performed to illustrate the functions of RRM2.

Results: Through integrated bioinformatics analysis, we found that the upregulated DEGs were related to cell cycle and cell division, while the downregulated DEGs were associated with various metabolic processes and complement cascade. RRM2, MAD2L1, MELK, NCAPG, and ASPM, selected as hub genes, were all correlated with poor overall prognosis in HCC. The novel RRM2 inhibitor osalmid had anti-tumor activity, including inhibiting proliferation and migration, promoting cell apoptosis, blocking cell cycle, and inducing DNA damage of HCC cells.

Conclusion: The critical pathways and hub genes in HCC progression were screened out, and targeting RRM2 contributed to developing new therapeutic strategies for HCC.

RRM2 enhances MYCN-driven neuroblastoma formation and acts as a synergistic target with CHK1 inhibition

High-risk neuroblastoma, a pediatric tumor originating from the sympathetic nervous system, has a low mutation load but highly recurrent somatic DNA copy number variants. Previously, segmental gains and/or amplifications allowed identification of drivers for neuroblastoma development. Using this approach, combined with gene dosage impact on expression and survival, we identified ribonucleotide reductase subunit M2 (RRM2) as a candidate dependency factor further supported by growth inhibition upon in vitro knockdown and accelerated tumor formation in a neuroblastoma zebrafish model coexpressing human RRM2 with MYCN. Forced RRM2 induction alleviates excessive replicative stress induced by CHK1 inhibition, while high RRM2 expression in human neuroblastomas correlates with high CHK1 activity. MYCN-driven zebrafish tumors with RRM2 co-overexpression exhibit differentially expressed DNA repair genes in keeping with enhanced ATR-CHK1 signaling activity. In vitro, RRM2 inhibition enhances intrinsic replication stress checkpoint addiction. Last, combinatorial RRM2-CHK1 inhibition acts synergistic in high-risk neuroblastoma cell lines and patient-derived xenograft models, illustrating the therapeutic potential.

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.

A supervised machine learning approach identifies gene-regulating factor-mediated competing endogenous RNA networks in hormone-dependent cancers

Competing endogenous RNAs (ceRNAs) have become an emerging topic in cancer research due to their role in gene regulatory networks. To date, traditional ceRNA bioinformatic studies have investigated microRNAs as the only factor regulating gene expression. Growing evidence suggests that genomic (e.g., copy number alteration [CNA]), transcriptomic (e.g., transcription factors [TFs]), and epigenomic (e.g., DNA methylation [DM]) factors can influence ceRNA regulatory networks. Herein, we used the Least absolute shrinkage and selection operator regression, a machine learning approach, to integrate DM, CNA, and TFs data with RNA expression to infer ceRNA networks in cancer risk. The gene‐regulating factors‐mediated ceRNA networks were identified in four hormone‐dependent (HD) cancer types: prostate, breast, colorectal, and endometrial. The shared ceRNAs across HD cancer types were further investigated using survival analysis, functional enrichment analysis, and protein–protein interaction network analysis. We found two (BUB1 and EXO1) and one (RRM2) survival‐significant ceRNA(s) shared across breast‐colorectal‐endometrial and prostate–colorectal–endometrial combinations, respectively. Both BUB1 and BUB1B genes were identified as shared ceRNAs across more than two HD cancers of interest. These genes play a critical role in cell division, spindle‐assembly checkpoint signalling, and correct chromosome alignment. Furthermore, shared ceRNAs across multiple HD cancers have been involved in essential cancer pathways such as cell cycle, p53 signalling, and chromosome segregation. Identifying ceRNAs' roles across multiple related cancers will improve our understanding of their shared disease biology. Moreover, it contributes to the knowledge of RNA‐mediated cancer pathogenesis.

Computational Recognition of a Regulatory T-cell-specific Signature With Potential Implications in Prognosis, Immunotherapy, and Therapeutic Resistance of Prostate Cancer

Prostate cancer, recognized as a "cold" tumor, has an immunosuppressive microenvironment in which regulatory T cells (Tregs) usually play a major role. Therefore, identifying a prognostic signature of Tregs has promising benefits of improving survival of prostate cancer patients. However, the traditional methods of Treg quantification usually suffer from bias and variability. Transcriptional characteristics have recently been found to have a predictive power for the infiltration of Tregs. Thus, a novel machine learning-based computational framework has been presented using Tregs and 19 other immune cell types using 42 purified immune cell datasets from GEO to identify Treg-specific mRNAs, and a prognostic signature of Tregs (named "TILTregSig") consisting of five mRNAs (SOCS2, EGR1, RRM2, TPP1, and C11orf54) was developed and validated to monitor the prognosis of prostate cancer using the TCGA and ICGC datasets. The TILTregSig showed a stronger predictive power for tumor immunity compared with tumor mutation burden and glycolytic activity, which have been reported as immune predictors. Further analyses indicate that the TILTregSig might influence tumor immunity mainly by mediating tumor-infiltrating Tregs and could be a powerful predictor for Tregs in prostate cancer. Moreover, the TILTregSig showed a promising potential for predicting cancer immunotherapy (CIT) response in five CIT response datasets and therapeutic resistance in the GSCALite dataset in multiple cancers. Our TILTregSig derived from PBMCs makes it possible to achieve a straightforward, noninvasive, and inexpensive detection assay for prostate cancer compared with the current histopathological examination that requires invasive tissue puncture, which lays the foundation for the future development of a panel of different molecules in peripheral blood comprising a biomarker of prostate cancer.

Identification of novel biomarkers in prostate cancer diagnosis and prognosis

Prostate cancer (PCa) is a common urinary malignancy. The lack of specific and sensitive biomarkers for the early diagnosis and prognosis of PCa makes it important to seek alternatives. R software was used to analyze the PCa expression profile from data sets in Gene Expression Omnibus. Core differential genes were identified by String and Cytoscape and further validated by Gene Expression Profiling Interactive Analysis (GEPIA) and The Human Protein Atlas (HPA). Gene Ontology analysis was done in the DIVID database and visualization analysis was conducted by Hiplot. Pathway enrichment was analyzed by IPA. To identify potential competitive endogenous RNAs (ceRNA) networks, the experimentally validated microRNA-target interactions database (miRTarBase), The Encyclopedia of RNA Interactomes (StarBase), lncBase, and GEPIA were used. The lncLocator was utilized to perform subcellular localization of long noncoding RNAs (lncRNAs). Both miRTarBase and StarBase were used to find the binding site of mRNAs-miRNAs and miRNAs-lncRNAs. Visualization of the ceRNA network was performed with Cytoscape. Nine genes closely related to the diagnosis and prognosis of PCa were obtained, including four identified biomarkers by HPA, CENPF, TPX2, TK1, and CCNB1, and five novel PCa biomarkers, RRM2, UBE2C, TOP2A, BIRC5, and ZWINT. Pathway analysis indicated that PCa carcinogenesis was highly correlated with liver fibrosis pathways, ILK signaling, and NRF2-mediated oxidative stress response. Two sets of ceRNA networks, BIRC5/hsa-miR-218-5p/NEAT1 and UBE2C/hsa-miR-483-3p/NEAT1 were found to be novel biomarkers for the identification of PCa. The quantitative real-time polymerase chain reaction results verified that UBE2C, BIRC5, and NEAT1 were upregulated and hsa-miR-218-5p and hsa-miR-483-3p were downregulated in human PCa cells compared with normal prostate epithelial cells. The novel identified biomarkers in this study would be valuable for the diagnosis and prognosis of PCa.

Wilms tumor reveals DNA repair gene hyperexpression is linked to lack of tumor immune infiltration

Background

A T cell-rich tumor microenvironment has been associated with improved clinical outcome and response to immune checkpoint blockade therapies in several adult cancers. Understanding the mechanisms for lack of immune cell infiltration in tumors is critical for expanding immunotherapy efficacy. To gain new insights into the mechanisms of poor tumor immunogenicity, we turned to pediatric cancers, which are generally unresponsive to checkpoint blockade.

Methods

RNA sequencing and clinical data were obtained for Wilms tumor, rhabdoid tumor, osteosarcoma, and neuroblastoma from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, and adult cancers from The Cancer Genome Atlas (TCGA). Using an 18-gene tumor inflammation signature (TIS) representing activated CD8⁺ T cells, we identified genes inversely correlated with the signature. Based on these results, adult tumors were also analyzed, and immunofluorescence was performed on metastatic melanoma samples to assess the MSH2 relationship to anti-programmed cell death protein-1 (PD-1) efficacy.

Results

Among the four pediatric cancers, we observed the lowest TIS scores in Wilms tumor. TIS scores were lower in Wilms tumors compared with matched normal kidney tissues, arguing for loss of endogenous T cell infiltration. Pathway analysis of genes upregulated in Wilms tumor and anti-correlated with TIS revealed activated pathways involved DNA repair. The majority of adult tumors in TCGA also showed high DNA repair scores associated with low TIS. Melanoma samples from an independent cohort revealed an inverse correlation between MSH2⁺ tumor cells and CD8⁺ T cells. Additionally, melanomas with high MSH2⁺ tumor cell numbers were largely non-responders to anti-PD-1 therapy.

Conclusions

Increased tumor expression of DNA repair genes is associated with a less robust immune response in Wilms tumor and the majority of TCGA tumor types. Surprisingly, the negative relationship between DNA repair score and TIS remained strong across TCGA when correcting for mutation count, indicating a potential role for DNA repair genes outside of preventing the accumulation of mutations. While loss of DNA repair machinery has been associated with carcinogenesis and mutational antigen generation, our results suggest that hyperexpression of DNA repair genes might be prohibitive for antitumor immunity, arguing for pharmacologic targeting of DNA repair as a potential therapeutic strategy.

Preclinical validation and phase I trial of 4-hydroxysalicylanilide, targeting ribonucleotide reductase mediated dNTP synthesis in multiple myeloma

Background

Aberrant DNA repair pathways contribute to malignant transformation or disease progression and the acquisition of drug resistance in multiple myeloma (MM); therefore, these pathways could be therapeutically exploited. Ribonucleotide reductase (RNR) is the rate-limiting enzyme for the biosynthesis of deoxyribonucleotides (dNTPs), which are essential for DNA replication and DNA damage repair. In this study, we explored the efficacy of the novel RNR inhibitor, 4-hydroxysalicylanilide (HDS), in myeloma cells and xenograft model. In addition, we assessed the clinical activity and safety of HDS in patients with MM.

Methods

We applied bioinformatic, genetic, and pharmacological approaches to demonstrate that HDS was an RNR inhibitor that directly bound to RNR subunit M2 (RRM2). The activity of HDS alone or in synergy with standard treatments was evaluated in vitro and in vivo. We also initiated a phase I clinical trial of single-agent HDS in MM patients (ClinicalTrials.gov: NCT03670173) to assess safety and efficacy.

Results

HDS inhibited the activity of RNR by directly targeting RRM2. HDS decreased the RNR-mediated dNTP synthesis and concomitantly inhibited DNA damage repair, resulting in the accumulation of endogenous unrepaired DNA double-strand breaks (DSBs), thus inhibiting MM cell proliferation and inducing apoptosis. Moreover, HDS overcame the protective effects of IL-6, IGF-1 and bone marrow stromal cells (BMSCs) on MM cells. HDS prolonged survival in a MM xenograft model and induced synergistic anti-myeloma activity in combination with melphalan and bortezomib. HDS also showed a favorable safety profile and demonstrated clinical activity against MM.

Conclusions

Our study provides a rationale for the clinical evaluation of HDS as an anti-myeloma agent, either alone or in combination with standard treatments for MM.

Trial registration: ClinicalTrials.gov, NCT03670173, Registered 12 September 2018.

Supplementary information

The online version contains supplementary material available at 10.1186/s12929-022-00813-2.

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 (HPV^neg) 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 HPV^neg HNSCC. Thus, innovative agents to augment the efficacy of palbociclib in HPV^neg 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 HPV^neg 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 HPV^neg HNSCC cell lines and patient-derived xenograft models.

RESULTS

Palbociclib displayed limited efficacy in HPV^neg 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 HPV^neg 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 HPV^neg HNSCC with PIK3CA alterations.

Ribonucleotide reductase holoenzyme inhibitor COH29 interacts with deubiquitinase ubiquitin-specific protease 2 and downregulates its substrate protein cyclin D1

USP2 contributes to the quality control of multiple oncogenic proteins including cyclin D1, Mdm2, Aurora-A, etc., and it is a potential target for anti-cancer drug development. However, currently only a few inhibitors with moderate inhibition activities against USP2 have been discovered. USP2-targeted active compounds with either new scaffolds or enhanced activities are in need. Here in this study, Ub-AMC hydrolysis assay-based screening against ~4000 commercially available drugs and drug candidates was performed to identify USP2-targeted inhibitors. COH29, which was originally developed as an anti-cancer agent by blocking the function of human ribonucleotide reductase (RNR, IC₅₀  = 16 µM), was found to exhibit an inhibition activity against USP2 with the IC₅₀ value at 2.02 ± 0.16 µM. The following conducted biophysical and biochemical experiments demonstrated that COH29 could specifically interact with USP2 and inhibit its enzymatic activity in a noncompetitive inhibition mode (K_i  = 1.73 ± 0.14 µM). Since COH29 shows similar inhibitory potencies against RNR (RRM2) and USP2, USP2 inhibition-dependent cellular consequences of COH29 are expected. The results of cellular assays confirmed that the application of COH29 could downregulate the level of cyclin D1 by enhancing its degradation via ubiquitin-proteasome system (UPS), and the modulation effect of COH29 on cyclin D1 is independent of RRM2. Since cyclin D1 acts as an oncogenic driver in human cancer, our findings suggest that USP2 might be a promising therapeutic target for cyclin D1-addicted cancers, and COH29 could serve as a starting compound for high selectivity inhibitor development against USP2.

Identification of Pathologic and Prognostic Genes in Prostate Cancer Based on Database Mining

Background: Prostate cancer (PCa) is an epithelial malignant tumor that occurs in the urinary system with high incidence and is the second most common cancer among men in the world. Thus, it is important to screen out potential key biomarkers for the pathogenesis and prognosis of PCa. The present study aimed to identify potential biomarkers to reveal the underlying molecular mechanisms.

Methods: Differentially expressed genes (DEGs) between PCa tissues and matched normal tissues from The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset were screened out by R software. Weighted gene co-expression network analysis was performed primarily to identify statistically significant genes for clinical manifestations. Protein–protein interaction (PPI) network analysis and network screening were performed based on the STRING database in conjunction with Cytoscape software. Hub genes were then screened out by Cytoscape in conjunction with stepwise algorithm and multivariate Cox regression analysis to construct a risk model. Gene expression in different clinical manifestations and survival analysis correlated with the expression of hub genes were performed. Moreover, the protein expression of hub genes was validated by the Human Protein Atlas database.

Results: A total of 1,621 DEGs (870 downregulated genes and 751 upregulated genes) were identified from the TCGA-PRAD dataset. Eight prognostic genes [BUB1, KIF2C, CCNA2, CDC20, CCNB2, PBK, RRM2, and CDC45] and four hub genes (BUB1, KIF2C, CDC20, and PBK) potentially correlated with the pathogenesis of PCa were identified. A prognostic model with good predictive power for survival was constructed and was validated by the dataset in GSE21032. The survival analysis demonstrated that the expression of RRM2 was statistically significant to the prognosis of PCa, indicating that RRM2 may potentially play an important role in the PCa progression.

Conclusion: The present study implied that RRM2 was associated with prognosis and could be used as a potential therapeutic target for PCa clinical treatment.

RRM2 Alleviates Doxorubicin-Induced Cardiotoxicity through the AKT/mTOR Signaling Pathway

Doxorubicin (DOX) is an effective chemotherapeutic agent that plays an unparalleled role in cancer treatment. However, its serious dose-dependent cardiotoxicity, which eventually contributes to irreversible heart failure, has greatly limited the widespread clinical application of DOX. A previous study has demonstrated that the ribonucleotide reductase M2 subunit (RRM2) exerts salutary effects on promoting proliferation and inhibiting apoptosis and autophagy. However, the specific function of RRM2 in DOX-induced cardiotoxicity is yet to be determined. This study aimed to elucidate the role and potential mechanism of RRM2 on DOX-induced cardiotoxicity by investigating neonatal primary cardiomyocytes and mice treated with DOX. Subsequently, the results indicated that RRM2 expression was significantly reduced in mice hearts and primary cardiomyocytes. Apoptosis and autophagy-related proteins, such as cleaved-Caspase3 (C-Caspase3), LC3B, and beclin1, were distinctly upregulated. Additionally, RRM2 deficiency led to increased autophagy and apoptosis in cells. RRM2 overexpression, on the contrary, alleviated DOX-induced cardiotoxicity in vivo and in vitro. Consistently, DIDOX, an inhibitor of RRM2, attenuated the protective effect of RRM2. Mechanistically, we found that AKT/mTOR inhibitors could reverse the function of RRM2 overexpression on DOX-induced autophagy and apoptosis, which means that RRM2 could have regulated DOX-induced cardiotoxicity through the AKT/mTOR signaling pathway. In conclusion, our experiment established that RRM2 could be a potential treatment in reversing DOX-induced cardiac dysfunction.

Prognostic and therapeutic significance of COP9 signalosome subunit CSN5 in prostate cancer

Chromosome 8q gain is associated with poor clinical outcomes in prostate cancer, but the underlying biological mechanisms remain to be clarified. CSN5, a putative androgen receptor (AR) partner that is located on chromosome 8q, is the key subunit of the COP9 signalosome, which deactivates ubiquitin ligases. Deregulation of CSN5 could affect diverse cellular functions that contribute to tumor development, but there has been no comprehensive study of its function in prostate cancer. The clinical significance of CSN5 amplification/overexpression was evaluated in 16 prostate cancer clinical cohorts. Its oncogenic activity was assessed by genetic and pharmacologic perturbations of CSN5 activity in prostate cancer cell lines. The molecular mechanisms of CSN5 function were assessed, as was the efficacy of the CSN5 inhibitor CSN5i-3 in vitro and in vivo. Finally, the transcription cofactor activity of CSN5 in prostate cancer cells was determined. The prognostic significance of CSN5 amplification and overexpression in prostate cancer was independent of MYC amplification. Inhibition of CSN5 inhibited its oncogenic function by targeting AR signaling, DNA repair, multiple oncogenic pathways, and spliceosome regulation. Furthermore, inhibition of CSN5 repressed metabolic pathways, including oxidative phosphorylation and glycolysis in AR-negative prostate cancer cells. Targeting CSN5 with CSN5i-3 showed potent antitumor activity in vitro and in vivo. Importantly, CSN5i-3 synergizes with PARP inhibitors to inhibit prostate cancer cell growth. CSN5 functions as a transcription cofactor to cooperate with multiple transcription factors in prostate cancer. Inhibiting CSN5 strongly attenuates prostate cancer progression and could enhance PARP inhibition efficacy in the treatment of prostate cancer.

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.

From DNA Copy Number Gains and Tumor Dependencies to Novel Therapeutic Targets for High-Risk Neuroblastoma

Neuroblastoma is a pediatric tumor arising from the sympatho-adrenal lineage and a worldwide leading cause of childhood cancer-related deaths. About half of high-risk patients die from the disease while survivors suffer from multiple therapy-related side-effects. While neuroblastomas present with a low mutational burden, focal and large segmental DNA copy number aberrations are highly recurrent and associated with poor survival. It can be assumed that the affected chromosomal regions contain critical genes implicated in neuroblastoma biology and behavior. More specifically, evidence has emerged that several of these genes are implicated in tumor dependencies thus potentially providing novel therapeutic entry points. In this review, we briefly review the current status of recurrent DNA copy number aberrations in neuroblastoma and provide an overview of the genes affected by these genomic variants for which a direct role in neuroblastoma has been established. Several of these genes are implicated in networks that positively regulate MYCN expression or stability as well as cell cycle control and apoptosis. Finally, we summarize alternative approaches to identify and prioritize candidate copy-number driven dependency genes for neuroblastoma offering novel therapeutic opportunities.

Inhibition of GATA2 in prostate cancer by a clinically available small molecule

Castration-resistant prostate cancer (CRPC) remains highly lethal and in need of novel, actionable therapeutic targets. The pioneer factor GATA2 is a significant prostate cancer (PC) driver and is linked to poor prognosis. GATA2 directly promotes androgen receptor (AR) gene expression (both full-length and splice-variant) and facilitates AR binding to chromatin, recruitment of coregulators, and target gene transcription. Unfortunately, there is no clinically applicable GATA2 inhibitor available at the moment. Using a bioinformatics algorithm, we screened in silico 2650 clinically relevant drugs for a potential GATA2 inhibitor. Validation studies used cytotoxicity and proliferation assays, global gene expression analysis, RT-qPCR, reporter assay, reverse phase protein array analysis (RPPA), and immunoblotting. We examined target engagement via cellular thermal shift assay (CETSA), ChIP-qPCR, and GATA2 DNA-binding assay. We identified the vasodilator dilazep as a potential GATA2 inhibitor and confirmed on-target activity via CETSA. Dilazep exerted anticancer activity across a broad panel of GATA2-dependent PC cell lines in vitro and in a PDX model in vivo. Dilazep inhibited GATA2 recruitment to chromatin and suppressed the cell-cycle program, transcriptional programs driven by GATA2, AR, and c-MYC, and the expression of several oncogenic drivers, including AR, c-MYC, FOXM1, CENPF, EZH2, UBE2C, and RRM2, as well as of several mediators of metastasis, DNA damage repair, and stemness. In conclusion, we provide, via an extensive compendium of methodologies, proof-of-principle that a small molecule can inhibit GATA2 function and suppress its downstream AR, c-MYC, and other PC-driving effectors. We propose GATA2 as a therapeutic target in CRPC.

piR-39980 mediates doxorubicin resistance in fibrosarcoma by regulating drug accumulation and DNA repair

Resistance to doxorubicin (DOX) is an obstacle to successful sarcoma treatment and a cause of tumor relapse, with the underlying molecular mechanism still unknown. PIWI-interacting RNAs (piRNAs) have been shown to enhance patient outcomes in cancers. However, there are few or no reports on piRNAs affecting chemotherapy in cancers, including fibrosarcoma. The current study aims to investigate the relationship between piR-39980 and DOX resistance and the underlying mechanisms. We reveal that piR-39980 is less expressed in DOX-resistant HT1080 (HT1080/DOX) fibrosarcoma cells. Our results show that inhibition of piR-39980 in parental HT1080 cells induces DOX resistance by attenuating intracellular DOX accumulation, DOX-induced apoptosis, and anti-proliferative effects. Its overexpression in HT1080/DOX cells, on the other hand, increases DOX sensitivity by promoting intracellular DOX accumulation, DNA damage, and apoptosis. The dual-luciferase reporter assay indicates that piR-39980 negatively regulates RRM2 and CYP1A2 via direct binding to their 3'UTRs. Furthermore, overexpressing RRM2 induces DOX resistance of HT1080 cells by rescuing DOX-induced DNA damage by promoting DNA repair, whereas CYP1A2 confers resistance by decreasing intracellular DOX accumulation, which piR-39980 restores. This study reveals that piR-39980 could reduce fibrosarcoma resistance to DOX by modulating RRM2 and CYP1A2, implying that piRNA can be used in combination with DOX.

Dynamic expression of SNAI2 in prostate cancer predicts tumor progression and drug sensitivity

Prostate cancer is a highly heterogeneous disease, understanding the crosstalk between complex genomic and epigenomic alterations will aid in developing targeted therapeutics. We demonstrate that, even though snail family transcriptional repressor 2 (SNAI2) is frequently amplified in prostate cancer, it is epigenetically silenced in this disease, with dynamic changes in SNAI2 levels showing distinct clinical relevance. Integrative clinical data from 18 prostate cancer cohorts and experimental evidence showed that gene fusion between transmembrane serine protease 2 (TMPRSS2) and ETS transcription factor ERG (ERG) (TMPRSS2–ERG fusion) is involved in the silencing of SNAI2. We created a silencer score to evaluate epigenetic repression of SNAI2, which can be reversed by treatment with DNA methyltransferase inhibitors and histone deacetylase inhibitors. Silencing of SNAI2 facilitated tumor cell proliferation and luminal differentiation. Furthermore, SNAI2 has a major influence on the tumor microenvironment by reactivating tumor stroma and creating an immunosuppressive microenvironment in prostate cancer. Importantly, SNAI2 expression levels in part determine sensitivity to the cancer drugs dasatinib and panobinostat. For the first time, we defined the distinct clinical relevance of SNAI2 expression at different disease stages. We elucidated how epigenetic silencing of SNAI2 controls the dynamic changes of SNAI2 expression that are essential for tumor initiation and progression and discovered that restoring SNAI2 expression by treatment with panobinostat enhances dasatinib sensitivity, indicating a new therapeutic strategy for prostate cancer.

Prognostic Value of Metabolism-Related Genes and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers. Thus, it is warranted to detect the status of metabolism-related genes (MRGs) and infiltrating immune cells in ccRCC progression for the prognosis of ccRCC. This research was designed to establish and verify the prognostic signature of ccRCC using MRGs. In addition, we investigated the potential link between the relative proportion of tumor infiltrated immune cells (TIICs) and ccRCC prognosis.

Methods

Sequencing data of metabolism-related gene sets in ccRCC cases were obtained from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus Database (GEO). The R Programming Language software packages were applied for differential analysis of MRGs. First, a univariate Cox regression model was applied to determine the MRGs linked with overall survival (OS). Then, the multivariate Cox regression model was applied to establish the prognostic signature. Finally, the CIBERSORT algorithm was used to determine the proportion of TIICs.

Results

Overall, 286 differentially expressed MRGs were identified in the TCGA dataset. Univariate and multivariate Cox regression models were applied to develop a prognostic signature with six MRGs. The predictive capability of the prognostic signature was further verified by TCGA and GEO database. In addition, RS positively correlated with memory B cells, plasma cells, activated memory CD4+ T cells, follicular helper T cells, regulatory T cells, CD8+ T cells, and M0 macrophages, and were negatively associated with resting memory CD4+ T cells, resting dendritic cells, activated dendritic cells, M2 macrophages, monocytes, resting mast cells, and eosinophils.

Conclusion

Herein, a prognostic signature was developed using MRGs for ccRCC prognosis. The proportion of 22 TIICs in ccRCC and the association between TIICs and clinical outcomes were also determined. The identified genes and cells could guide future targeted therapy and immunotherapy.

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Breast cancer is the most common cancer and the leading cause of cancer-related deaths in women. Increasing molecular targets have been discovered for breast cancer prognosis and therapy. However, there is still an urgent need to identify new biomarkers. Therefore, we evaluated biomarkers that may aid the diagnosis and treatment of breast cancer. We searched three mRNA microarray datasets (GSE134359, GSE31448 and GSE42568) and identified differentially expressed genes (DEGs) by comparing tumor and non-tumor tissues using GEO2R. Functional and pathway enrichment analyses of the DEGs were performed using the DAVID database. The protein-protein interaction (PPI) network was plotted with STRING and visualized using Cytoscape. Module analysis of the PPI network was done using MCODE. The associations between the identified genes and overall survival (OS) were analyzed using an online Kaplan-Meier tool. The redundancy analysis was conducted by DepMap. Finally, we verified the screened HUB gene at the protein level. A total of 268 DEGs were identified, which were mostly enriched in cell division, cell proliferation, and signal transduction. The PPI network comprised 236 nodes and 2132 edges. Two significant modules were identified in the PPI network. Elevated expression of the genes Discs large-associated protein 5 (DLGAP5), aurora kinase A (AURKA), ubiquitin-conjugating enzyme E2 C (UBE2C), ribonucleotide reductase regulatory subunit M2(RRM2), kinesin family member 23(KIF23), kinesin family member 11(KIF11), non-structural maintenance of chromosome condensin 1 complex subunit G (NCAPG), ZW10 interactor (ZWINT), and denticleless E3 ubiquitin protein ligase homolog(DTL) are associated with poor OS of breast cancer patients. The enriched functions and pathways included cell cycle, oocyte meiosis and the p53 signaling pathway. The DEGs in breast cancer have the potential to become useful targets for the diagnosis and treatment of breast cancer.

Identification of potential biomarkers associated with immune infiltration in papillary renal cell carcinoma

Background

Immunotherapeutic approaches have recently emerged as effective treatment regimens against various types of cancer. However, the immune‐mediated mechanisms surrounding papillary renal cell carcinoma (pRCC) remain unclear. This study aimed to investigate the tumor microenvironment (TME) and identify the potential immune‐related biomarkers for pRCC.

Methods

The CIBERSORT algorithm was used to calculate the abundance ratio of immune cells in each pRCC samples. Univariate Cox analysis was used to select the prognostic‐related tumor‐infiltrating immune cells (TIICs). Multivariate Cox regression analysis was performed to develop a signature based on the selected prognostic‐related TIICs. Then, these pRCC samples were divided into low‐ and high‐risk groups according to the obtained signature. Analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to investigate the biological function of the DEGs (differentially expressed genes) between the high‐ and low‐risk groups. The hub genes were identified using a weighted gene co‐expression network analysis (WGCNA) and a protein‐protein interaction (PPI) analysis. The hub genes were subsequently validated by multiple clinical traits and databases.

Results

According to our analyses, nine immune cells play a vital role in the TME of pRCC. Our analyses also obtained nine potential immune‐related biomarkers for pRCC, including TOP2A, BUB1B, BUB1, TPX2, PBK, CEP55, ASPM, RRM2, and CENPF.

Conclusion

In this study, our data revealed the crucial TIICs and potential immune‐related biomarkers for pRCC and provided compelling insights into the pathogenesis and potential therapeutic targets for pRCC.

The High Expression of RRM2 Can Predict the Malignant Transformation of Endometriosis

INTRODUCTION

A large number of epidemiological studies have revealed that women with endometriosis (EMS) have a higher risk of developing endometriosis-associated ovarian cancer (EAOC). At present, there are few studies on predicting the malignant transformation of ovarian endometriosis (OE). The purpose of this study is to identify and verify the molecules that may be able to predict the malignant transformation of OE.

METHODS

The gene expression profiles of ovarian cancer and OE were downloaded from Gene Expression Omnibus (GEO), and a common hub gene ribonucleotide reductase M2 (RRM2) was identified. A total of 44 patients with EAOC and 44 with OE were enrolled in this study. Immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction (RT-qPCR) were used to detect the expression of RRM2, while the relationship between RRM2 and Ki-67 was analyzed by IHC co-localization.

RESULTS

Bioinformatics analysis showed that the expression of RRM2 was low in EMS and high in ovarian cancer. RRM2 was obviously positively expressed in eutopic endometrium (EU), ectopic endometrium (EC), and cancer tissues of EAOC patients. The IHC signal and mRNA levels of RRM2 were higher in the EC of EAOC patients compared with OE patients (P < 0.01). In addition, there was a correlation between the expression of RRM2 and Ki-67 in EC of EAOC patients (P < 0.01).

CONCLUSION

The upregulated expression of RRM2 in the EC of OE patients may indicate malignant transformation. High expression of RRM2 promotes abnormal proliferation of histiocytes. RRM2 can be used as a potential marker of malignant transformation of OE.

Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments

Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.