Recurrent ubiquitin B silencing in gynecological cancers establishes dependence on ubiquitin C

Histone Lactylation Antagonizes Senescence and Skeletal Muscle Aging by Modulating Aging-Related Pathways

Epigenetic alterations are among the prominent drivers of cellular senescence and/or aging, intricately orchestrating gene expression programs during these processes. This study shows that histone lactylation, plays a pivotal role in counteracting senescence and mitigating dysfunctions of skeletal muscle in aged mice. Mechanistically, histone lactylation and lactyl-CoA levels markedly decrease during cellular senescence but are restored under hypoxic conditions primarily due to elevated glycolytic activity. The enrichment of histone lactylation at promoters is essential for sustaining the expression of genes involved in the cell cycle and DNA repair pathways. Furthermore, the modulation of enzymes crucial for histone lactylation, leads to reduced histone lactylation and accelerated cellular senescence. Consistently, the suppression of glycolysis and the depletion of histone lactylation are also observed during skeletal muscle aging. Modulating the enzymes can also lead to the loss of histone lactylation in skeletal muscle, downregulating DNA repair and proteostasis pathways and accelerating muscle aging. Running exercise increases histone lactylation, which in turn upregulate key genes in the DNA repair and proteostasis pathways. This study highlights the significant roles of histone lactylation in modulating cellular senescence as well as muscle aging, providing a promising avenue for antiaging intervention via metabolic manipulation.

New insights into the role of mitophagy related gene affecting the metastasis of osteosarcoma through scRNA-seq and CRISPR-Cas9 genome editing

BACKGROUND

Osteosarcoma (OSA), the most common primary bone malignancy, poses significant challenges due to its aggressive nature and propensity for metastasis, especially in adolescents. Mitophagy analysis can help identify new therapeutic targets and combined treatment strategies.

METHODS

This study integrates single-cell sequencing (scRNA-seq) data and bulk-seq to identify mitophagy-related genes (MRGs) associated with the progression of OSA metastasis and analyze their clinical significance. scRNA-seq data elucidates the relationship between mitophagy and OSA metastasis, employing "CellChat" R package to explore intercellular communications and report on hundreds of ligand-receptor interactions. Subsequently, the combination of bulk-seq and CRISPR-Cas9 gene editing identifies mitophagy-related biomarker associated with metastatic prognosis. Finally, validation of the relationship between mitophagy and OSA metastasis is achieved through cellular biology experiments and animal studies.

RESULTS

The distinct mitophagy activity of various mitochondria manifests in diverse spatial localization, cellular developmental trajectories, and intercellular interactions. OSA tissue exhibits notable heterogeneity in mitophagy within osteoblastic OSA cells. However, high mitophagy activity correlates consistently with high metastatic potential. Subsequently, we identified three critical genes associated with mitophagy in OSA, namely RPS27A, TOMM20 and UBB. According to the aforementioned queue of genes, we have constructed a mitophagy_score (MIP_score). We observed that it consistently predicts patient prognosis in both internal and external datasets, demonstrating strong robustness and stability. Furthermore, we have found that MIP_score can also guide chemotherapy, with varying sensitivities to chemotherapeutic agents based on different MIP_score. It is noteworthy that, through the integration of CRISPR-Cas9 genome-wide screening and validation via cellular and animal experiments, we have identified RPS27A as a potential novel biomarker for OSA.

CONCLUSIONS

Our comprehensive analysis elucidated the profile of mitophagy throughout the OSA metastasis process, forming the basis for a mitophagy-related prognostic model that addresses clinical outcomes and drug sensitivity following OSA metastasis. Additionally, an online interactive platform was established to assist clinicians in decision-making ( https://mip-score.shinyapps.io/labtan/ ). These findings lay the groundwork for developing targeted therapies aimed at improving the prognosis of OSA patients.

Identification of biomarkers related to angiogenesis in myocardial ischemia-reperfusion injury and prediction of potential drugs

Myocardial ischemia-reperfusion injury (MIRI) refers to the secondary damage to myocardial tissue that occurs when blood perfusion is rapidly restored following myocardial ischemia. This process often exacerbates the injury to myocardial fiber structure and function. The activation mechanism of angiogenesis is closely related to MIRI and plays a significant role in the occurrence and progression of ischemic injury. In this study, we utilized sequencing data from the GEO database and employed WGCNA, Mfuzz cluster analysis, and protein interaction network to identify Stat3, Rela, and Ubb as hub genes involved in MIRI-angiogenesis. Additionally, the GO and KEGG analysis of differentially expressed genes highlighted their broad participation in inflammatory responses and associated signaling pathways. Moreover, the analysis of sequencing data and hub genes revealed a notable increase in the infiltration ratio of monocytes and activated mast cells. By establishing key cell ROC curves, using independent datasets, and validating the expression of hub genes, we demonstrated their high diagnostic value. Moreover, by scrutinizing single-cell sequencing data alongside trajectory analysis, it has come to light that Stat3 and Rela exhibit predominant expression within Dendritic cells. In contrast, Ubb demonstrates expression across multiple cell types, with all three genes being expressed at distinct stages of cellular development. Lastly, leveraging the CMap database, we predicted potential small molecule compounds for the identified hub genes and validated their binding activity through molecular docking. Ultimately, our research provides valuable evidence and references for the early diagnosis and treatment of MIRI from the perspective of angiogenesis.

Network Analysis of Osteoarthritis Progression Using a Steiner Minimal Tree Algorithm

Purpose

To provide a comprehensive analysis of associated genes with osteoarthritis (OA). Here, we reported a network analysis of OA progression by using a Steiner minimal tree algorithm.

Methods

We collected the OA-related genes through screening the publications in MEDLINE. We performed functional analysis to analyze the associated biochemical pathways of the OA-related genes. Pathway crosstalk analysis was constructed to explore interactions of the enriched pathways. Steiner minimal tree algorithm was used to analyze molecular pathway networks. The average clustering coefficient was compared with the corresponding values of the Osteoarthritis-specific network. The new finding RNA was compared with former single-cell RNA-seq analysis results.

Results

A gene set with 177 members reported to be significantly associated with Osteoarthritis was collected from 187 studies. Functional enrichment analysis revealed a specific related-OA gene including skeletal system development, cytokine-mediated signaling pathway, inflammatory response, cartilage development, and extracellular matrix organization. We performed a pathway crosstalk analysis among the 72 significantly enriched pathways. A total of 151 of the 177 genes in the Osteoarthritis gene set were included in the human interactome network. There were 31 genes in the former single-cell RNA-seq analysis results. The CLU, ENO1, SRRM1, UBC, HMGB1, NR3C1, NOTCH2NL, and CBX5 have significantly increased expression in seven molecularly defined populations of OA cartilage.

Conclusion

The Steiner tree-based approach finds new biological molecules associated with OA genes.

Downregulation of UBB potentiates SP1/VEGFA-dependent angiogenesis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) presents a unique profile characterized by high levels of angiogenesis and robust vascularization. Understanding the underlying mechanisms driving this heterogeneity is essential for developing effective therapeutic strategies. This study revealed that ubiquitin B (UBB) is downregulated in ccRCC, which adversely affects the survival of ccRCC patients. UBB exerts regulatory control over vascular endothelial growth factor A (VEGFA) by directly interacting with specificity protein 1 (SP1), consequently exerting significant influence on angiogenic processes. Subsequently, we validated that DNA methyltransferase 3 alpha (DNMT3A) is located in the promoter of UBB to epigenetically inhibit UBB transcription. Additionally, we found that an unharmonious UBB/VEGFA ratio mediates pazopanib resistance in ccRCC. These findings underscore the critical involvement of UBB in antiangiogenic therapy and unveil a novel therapeutic strategy for ccRCC.

Quantitative transcriptomic and proteomic analysis reveals corosolic acid inhibiting bladder cancer via suppressing cell cycle and inducing mitophagy in vitro and in vivo

Corosolic acid (CA) is a plant-derived terpenoid compound with many health benefits. However, the anti-tumor effects of CA in bladder cancer remain unexplored. Here, we found that CA inhibited bladder tumor both in vitro and in vivo, and had no significant toxicity in mice. With the aid of transcriptomics and proteomics, we elucidated the regulatory network mechanism of CA inhibiting bladder cancer. Through cell viability detection, cell fluorescence staining and flow cytometry, we discovered that CA inhibited bladder cancer mainly through blocking cell cycle. Interestingly, CA played anticancer roles by distinct mechanisms at different concentrations: low concentrations (<7.0 μg/ml) of CA mainly inhibited DNA synthesis by downregulating TOP2A and LIG1, and diminished mitosis by downregulating CCNA2, CCNB1, CDC20, and RRM2; high concentrations (≥7.0 μg/ml) of CA induced cell death through triggering mitophagy via upregulating NBR1, TAXBP1, SQSTM1/P62, and UBB. CA, as a natural molecule of homology of medicine and food, is of great significance for the prevention and treatment of cancer patients following clarifying its anti-cancer mechanism. This study provides a comprehensive understanding of the pharmacological mechanism of CA inhibition in bladder cancer, which is helpful for the development of new anti-tumor drugs based on CA.

Paralog-based synthetic lethality: rationales and applications

Tumor cells can result from gene mutations and over-expression. Synthetic lethality (SL) offers a desirable setting where cancer cells bearing one mutated gene of an SL gene pair can be specifically targeted by disrupting the function of the other genes, while leaving wide-type normal cells unharmed. Paralogs, a set of homologous genes that have diverged from each other as a consequence of gene duplication, make the concept of SL feasible as the loss of one gene does not affect the cell's survival. Furthermore, homozygous loss of paralogs in tumor cells is more frequent than singletons, making them ideal SL targets. Although high-throughput CRISPR-Cas9 screenings have uncovered numerous paralog-based SL pairs, the unclear mechanisms of targeting these gene pairs and the difficulty in finding specific inhibitors that exclusively target a single but not both paralogs hinder further clinical development. Here, we review the potential mechanisms of paralog-based SL given their function and genetic combination, and discuss the challenge and application prospects of paralog-based SL in cancer therapeutic discovery.

Development and Validation of a Prognostic Risk Model Based on Nature Killer Cells for Serous Ovarian Cancer

Nature killer (NK) cells are increasingly considered important in tumor microenvironment, but their role in predicting the prognosis of ovarian cancer has not been revealed. This study aimed to develop a prognostic risk model for ovarian cancer based on NK cells. Firstly, differentially expressed genes (DEGs) of NK cells were found by single-cell RNA-sequencing dataset analysis. Based on six NK-cell DEGs identified by univariable, Lasso and multivariable Cox regression analyses, a prognostic risk model for serous ovarian cancer was developed in the TCGA cohort. This model was then validated in three external cohorts, and evaluated as an independent prognostic factor by multivariable Cox regression analysis together with clinical characteristics. With the investigation of the underlying mechanism, a relation between a higher risk score of this model and more immune activities in tumor microenvironment was revealed. Furthermore, a detailed inspection of infiltrated immunocytes indicated that not only quantity, but also the functional state of these immunocytes might affect prognostic risk. Additionally, the potential of this model to predict immunotherapeutic response was exhibited by evaluating the functional state of cytotoxic T lymphocytes. To conclude, this study introduced a novel prognostic risk model based on NK-cell DEGs, which might provide assistance for the personalized management of serous ovarian cancer patients.

The inhibitory role of si-UBB delivered by degradable dendrimers-based lipid nanoparticles in ovarian cancer

Objective

RNA interference holds tremendous potential in the treatment of malignant tumors. However, efficient and biocompatible delivery methods are needed for systemic delivery of small interfering RNA (siRNA). In this study, we explored the delivery efficiency and therapy effect of si-UBB-5A2SC8 in ovarian cancer.

Methods and materials

Si-UBB-5A2SC8 nanoparticles were successfully prepared according to the established procedure and the characteristic of nanoparticles was determined by digital laser scanning. Flow cytometry and confocal analysis demonstrated si-UBB was efficiently transfected to cell by the delivery of 5A2SC8 complexes. The in vitro gene knockdown efficiency of ubiquitin B was demonstrated by RT-qPCR and Western blot analysis, which was further verified by the inhibition of proliferation and migration of ovarian cancer cells. Accumulative efficiency of si-UBB-5A2SC8 nanoparticles was investigated in BALB/c mice bearing SKOV3-GFP tumor xenograft. In vivo imaging was adopted to test the accurate location of the nanoparticle in the tumor. The feature of the tumor and pivotal organ was determined. TUNEL and caspase-3 expression was used to analyze the underling mechanism of the inhibition effect.

Results

The average size and the zeta potential of the si-UBB-5A2SC8 was (150 ± 11) nm and − (20 ± 4) mV, respectively. Transmission electronic microscopy showed the nanoparticle was near-spherical with the mean size of (100 ± 15) nm. Flow cytometry and confocal microscopic images demonstrated 5A2SC8 complex could successfully deliver Cy5.5-siRNA to the cytoplasm of ovarian cancer cells. qRT-PCR and western blot demonstrated the mRNA and protein expression of ubiquitin B was decreased to 62.5% and 36.5% of the control group, which was accompanied with the decreased proliferation and migration ability in si-UBB-5A2SC8-transfected cells. Ex vivo fluorescence imaging demonstrated 5A2SC8 complex could successfully carry siRNA to the tumor lesion and exert the inhibition effect, which was verified by the decreased tumor weight and increased apoptosis and caspase-3 expression in mice treated with si-UBB-5A2SC8.

Conclusions

5A2SC8 complex was a safe and efficient gene delivery vehicle and ubiquitin B was a potential target for the ovarian cancer targeted therapy.

Tools for Decoding Ubiquitin Signaling in DNA Repair

The maintenance of genome stability requires dedicated DNA repair processes and pathways that are essential for the faithful duplication and propagation of chromosomes. These DNA repair mechanisms counteract the potentially deleterious impact of the frequent genotoxic challenges faced by cells from both exogenous and endogenous agents. Intrinsic to these mechanisms, cells have an arsenal of protein factors that can be utilised to promote repair processes in response to DNA lesions. Orchestration of the protein factors within the various cellular DNA repair pathways is performed, in part, by post-translational modifications, such as phosphorylation, ubiquitin, SUMO and other ubiquitin-like modifiers (UBLs). In this review, we firstly explore recent advances in the tools for identifying factors involved in both DNA repair and ubiquitin signaling pathways. We then expand on this by evaluating the growing repertoire of proteomic, biochemical and structural techniques available to further understand the mechanistic basis by which these complex modifications regulate DNA repair. Together, we provide a snapshot of the range of methods now available to investigate and decode how ubiquitin signaling can promote DNA repair and maintain genome stability in mammalian cells.

Construction and validation of a novel aging-related gene signature and prognostic nomogram for predicting the overall survival in ovarian cancer

BACKGROUND

Ovarian cancer (OC) is the most lethal gynecological malignancy. The objective of this study was to establish and validate an individual aging-related gene signature and a clinical nomogram that can powerfully predict independently the overall survival rate of patients with ovarian cancer.

METHODS

Data on transcriptomic profile and relevant clinical information were retrieved from The Cancer Genome Atlas (TCGA) database as a training group, and the same data from three public Gene Expression Omnibus (GEO) databases as validation groups. Univariate Cox regression analysis, lasso regression analysis, and multiple multivariate Cox analysis were analyzed sequentially to select the genes to be included in the aging-associated signature. A risk scoring model was established and verified, the predictive value of the model was evaluated, and a clinical nomogram was established.

RESULTS

We found eight genes that were most relevant to prognosis and constructed an eight-mRNA signature. Based on the model, each OC patient's risk score was able to be calculated and patients were split into groups of low and high risks with a distinct outcome. Survival analysis confirmed that the outcome of patients in the high-risk group was dramatically shorter than that of those in the low-risk group, and the eight-mRNA signature can be considered as a powerful and independent predictor that could predict the outcome of OC patient. Additionally, the risk score and age can be used to construct a clinical nomogram as a simpler tool for predicting prognosis. We also explored the association between the risk score and immunity and drug sensitivity.

CONCLUSION

This study suggested that the aging-related gene signature could be used as an intervention point and latent prognostic predictor in OC, which may provide new perceptions for postoperative treatment strategies.

GraphSynergy: a network-inspired deep learning model for anticancer drug combination prediction

OBJECTIVE

To develop an end-to-end deep learning framework based on a protein-protein interaction (PPI) network to make synergistic anticancer drug combination predictions.

MATERIALS AND METHODS

We propose a deep learning framework named Graph Convolutional Network for Drug Synergy (GraphSynergy). GraphSynergy adapts a spatial-based Graph Convolutional Network component to encode the high-order topological relationships in the PPI network of protein modules targeted by a pair of drugs, as well as the protein modules associated with a specific cancer cell line. The pharmacological effects of drug combinations are explicitly evaluated by their therapy and toxicity scores. An attention component is also introduced in GraphSynergy, which aims to capture the pivotal proteins that play a part in both PPI network and biomolecular interactions between drug combinations and cancer cell lines.

RESULTS

GraphSynergy outperforms the classic and state-of-the-art models in predicting synergistic drug combinations on the 2 latest drug combination datasets. Specifically, GraphSynergy achieves accuracy values of 0.7553 (11.94% improvement compared to DeepSynergy, the latest published drug combination prediction algorithm) and 0.7557 (10.95% improvement compared to DeepSynergy) on DrugCombDB and Oncology-Screen datasets, respectively. Furthermore, the proteins allocated with high contribution weights during the training of GraphSynergy are proved to play a role in view of molecular functions and biological processes, such as transcription and transcription regulation.

CONCLUSION

The introduction of topological relations between drug combination and cell line within the PPI network can significantly improve the capability of synergistic drug combination identification.

Integrated miRNA and mRNA omics reveal the anti-cancerous mechanism of Licochalcone B on Human Hepatoma Cell HepG2

To unravel the potential of Licochalcone B as an anti-tumour phytochemical agent and evaluate its underlying mechanisms, we analyzed the mRNAs and miRNAs expression profiles of HepG2 cells in response to Licochalcone B (120 μM). mRNA and miRNA expression libraries were conducted and functional analysis for differential expression mRNAs was carried out utilizing Clue GO. We found 763 Licochalcone B -responsive differently expressed genes, among them, 572 mRNAs were up-regulated and 191 mRNAs were down-regulated, many of which were related to the MAPK signaling pathway. A protein-protein interaction network was constructed to discover the hub genes, and IL6, FOS, JUN, NOTCH1, UBC, UBB, CXCL8, CDKN1A, IL1B, ATF3, and GATA3 genes were screened out. Additionally, miRNAs engaged in Licochalcone B -mediated regulation on HepG2 cells were also studied. 85 differential expression miRNAs were identified, including 39 up-regulated miRNAs and 46 down-regulated miRNAs. Co-expression of miRNA-mRNA network was created and two key miRNAs (hsa-miR-29b-3p and hsa-miR-96-5p) were identified. These recognized key genes, miRNA, and the miRNA-mRNA regulatory network may provide clues to understand the molecular mechanism of Licochalcone B as an apoptotic inducer which may offer hint for its application as a functional food component.

Recent Advances in Integrative Multi-Omics Research in Breast and Ovarian Cancer

The underlying molecular heterogeneity of cancer is responsible for the dynamic clinical landscape of this disease. The combination of genomic and proteomic alterations, including both inherited and acquired mutations, promotes tumor diversity and accounts for variable disease progression, therapeutic response, and clinical outcome. Recent advances in high-throughput proteogenomic profiling of tumor samples have resulted in the identification of novel oncogenic drivers, tumor suppressors, and signaling networks; biomarkers for the prediction of drug sensitivity and disease progression; and have contributed to the development of novel and more effective treatment strategies. In this review, we will focus on the impact of historical and recent advances in single platform and integrative proteogenomic studies in breast and ovarian cancer, which constitute two of the most lethal forms of cancer for women, and discuss the molecular similarities of these diseases, the impact of these findings on our understanding of tumor biology as well as the clinical applicability of these discoveries.

Tumor-intrinsic and -extrinsic (immune) gene signatures robustly predict overall survival and treatment response in high grade serous ovarian cancer patients

In the present study, we developed a transcriptomic signature capable of predicting prognosis and response to primary therapy in high grade serous ovarian cancer (HGSOC). Proportional hazard analysis was performed on individual genes in the TCGA RNAseq data set containing 229 HGSOC patients. Ridge regression analysis was performed to select genes and develop multigenic models. Survival analysis identified 120 genes whose expression levels were associated with overall survival (OS) (HR = 1.49-2.46 or HR = 0.48-0.63). Ridge regression modeling selected 38 of the 120 genes for development of the final Ridge regression models. The consensus model based on plurality voting by 68 individual Ridge regression models classified 102 (45%) as low, 23 (10%) as moderate and 104 patients (45%) as high risk. The median OS was 31 months (HR = 7.63, 95% CI = 4.85-12.0, P < 1.0-10) and 77 months (HR = ref) in the high and low risk groups, respectively. The gene signature had two components: intrinsic (proliferation, metastasis, autophagy) and extrinsic (immune evasion). Moderate/high risk patients had more partial and non-responses to primary therapy than low risk patients (odds ratio = 4.54, P < 0.001). We concluded that the overall survival and response to primary therapy in ovarian cancer is best assessed using a combination of gene signatures. A combination of genes which combines both tumor intrinsic and extrinsic functions has the best prediction. Validation studies are warranted in the future.

The Ubiquitin Gene Expression Pattern and Sensitivity to UBB and UBC Knockdown Differentiate Primary 23132/87 and Metastatic MKN45 Gastric Cancer Cells

Gastric cancer (GC) is one of the most common and lethal cancers. Alterations in the ubiquitin (Ub) system play key roles in the carcinogenetic process and in metastasis development. Overexpression of transcription factors YY1, HSF1 and SP1, known to regulate Ub gene expression, is a predictor of poor prognosis and shorter survival in several cancers. In this study, we compared a primary (23132/87) and a metastatic (MKN45) GC cell line. We found a statistically significant higher expression of three out of four Ub coding genes, UBC, UBB and RPS27A, in MKN45 compared to 23132/87. However, while the total Ub protein content and the distribution of Ub between the conjugated and free pools were similar in these two GC cell lines, the proteasome activity was higher in MKN45. Ub gene expression was not affected upon YY1, HSF1 or SP1 small interfering RNA (siRNA) transfection, in both 23132/87 and MKN45 cell lines. Interestingly, the simultaneous knockdown of UBB and UBC mRNAs reduced the Ub content in both cell lines, but was more critical in the primary GC cell line 23132/87, causing a reduction in cell viability due to apoptosis induction and a decrease in the oncoprotein and metastatization marker β-catenin levels. Our results identify UBB and UBC as pro-survival genes in primary gastric adenocarcinoma 23132/87 cells.

Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma

In this study, we identified prognostic biomarkers in ovarian carcinoma by integrating multi-omics DNA copy number variation (CNV) and methylation variation (MET) data. CNV, MET, and messenger RNA (mRNA) expression were examined in 351 ovarian carcinoma patients. Genes for which expression was correlated with DNA copy-number or DNA methylation were identified; three ovarian carcinoma gene subtypes were defined based on these correlations. Overall survival and B cell scores were lower, while the macrophage cell score was higher, in the DNA imprinting centre 1 (iC1) subtype than in the iC2 and iC3 subtypes. Comparison of CNV, MET, and mRNA expression among the subtypes identified two genes, ubiquitin B (UBB) and interleukin 18 binding protein (IL18BP), that were associated with prognosis. Mutation spectrum results based on subtype indicated that UBB and IL18BP expression may be influenced by mutation loci. Mutation levels were higher in iC1 samples than in iC2 or iC3 samples, indicating that the iC1 subtype is associated with disease progression. This integrated multi-omics analysis of genomics, epigenomics, and transcriptomics provides new insight into the molecular mechanisms of ovarian carcinoma and may help identify biomolecular markers for early disease diagnosis.

USP22 promotes development of lung adenocarcinoma through ubiquitination and immunosuppression

Ubiquitin-specific protease 22 (USP22) expresses highly in lung adenocarcinoma (LUAD), which are associated with poor overall survival (OS). Microarray processing was performed to determine gene expression profiling, in which it was found that knocking down USP22 resulted in abnormal expression of a large number of genes. Differentially expressed genes (DEGs)-based protein-protein interaction (PPI) network was organized into 9 functional modules. These functional modules participated significantly in protein modification-related biological process and were involved in cancer-related pathways. The network was constructed to describe the global regulation of USP22-TF/pivot-module-pathway. It suggested that knocking down USP22 may up-regulate the expression of UBC to promote the pathways of cell cycle and ubiquitin-mediated proteolysis in the development of LUAD. More than that, knocking down USP22 can up-regulate STAT1 to activate JAK1-STAT1-caspase pathway, and promote apoptosis of tumor cell. Receiver operating characteristic (ROC) curve analysis suggested that E2F3, H2AFX, TFAP2A, PITX1, IRF7, and FOXM1 may be the potential diagnosis biomarkers for LUAD. On the other hand, BRCA1, FOXM1 and TFAP2A may be prognostic biomarkers of LUAD. In conclusion, we constructed a global regulation network to show that USP22 may promote the development of LUAD through ubiquitination and immunosuppression.

Expression Profile of Genes Associated with the Proteins Degradation Pathways in Colorectal adenocarcinoma

Background:

Changes in expression of genes associated with proteins or organelles degradation system in the cell may be a cause or signal to carcinogenesis. Thus, the aim of this study was to assess the profile of gene expression linked to the degradation systems of proteins or organelles in histo-pathologically confirmed colorectal adenocarcinoma in relation to normal colon tissue.

Methods:

Using oligonucleotide microarrays and GeneSpring 13.0, and PANTHER 13.1 software’s we characterized 1095 mRNAs linked to the degradation system of proteins and organelles in sections of colorectal cancer from patients at various clinical stages of disease. Subsequent analyses with restrictive assumptions narrowed down the number of genes differentiating cancer, assuming a P-value of less than 0.05.

Results:

We found that most of the significant genes were silenced in the development of colorectal cancer. The FOXO1 had the lowest fold change value in the first clinical stage (CSI) comparing to the control. The HSPA8 was up-regulated in the two early clinical stages (CSI and CSII), and UBB only in the CSI. Only little-known PTPN22 showed increasing expression at all stages.

Conclusion:

In summary, the examined colorectal adenocarcinoma samples were characterized by almost complete silencing of the significant genes associated with the degradation of proteins and mitochondria in transcriptomic level. The FOXO1, HSPA8 and UBB genes may become potential diagnostic and/or therapeutic targets in the early stage of this cancer.

High-affinity free ubiquitin sensors for quantifying ubiquitin homeostasis and deubiquitination

Ubiquitin (Ub) conjugation is an essential post-translational modification that affects nearly all proteins in eukaryotes. The functions and mechanisms of ubiquitination are areas of extensive study, and yet the dynamics and regulation of even free (i.e., unconjugated) Ub are poorly understood. A major impediment has been the lack of simple and robust techniques to quantify Ub levels in cells and to monitor Ub release from conjugates. Here we describe avidity-based fluorescent sensors that address this need. The sensors bind specifically to free Ub, have K_d values down to 60 pM, and, in concert with a newly developed workflow, allow us to distinguish and quantify the pools of free, protein-conjugated, and thioesterified forms of Ub from cell lysates. Alternatively, free Ub in fixed cells can be visualized microscopically by staining with a sensor. Real-time assays using the sensors afford unprecedented flexibility and precision to measure deubiquitination of virtually any (poly)Ub conjugate.

Integrated analysis identified core signal pathways and hypoxic characteristics of human glioblastoma

As a hallmark for glioblastoma (GBM), high heterogeneity causes a variety of phenotypes and therapeutic responses among GBM patients, and it contributes to treatment failure. Moreover, hypoxia is a predominant feature of GBM and contributes greatly to its phenotype. To analyse the landscape of gene expression and hypoxic characteristics of GBM cells and their clinical significance in GBM patients, we performed transcriptome analysis of the GBM cell line U87‐MG and the normal glial cell line HEB under normoxia and hypoxia conditions, with the results of which were analysed using established gene ontology databases as well as The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia. We revealed core signal pathways, including inflammation, angiogenesis and migration, and for the first time mapped the components of the toll‐like receptor 6 pathway in GBM cells. Moreover, by investigating the signal pathways involved in homoeostasis, proliferation and adenosine triphosphate metabolism, the critical response of GBM to hypoxia was clarified. Experiments with cell lines, patient serum and tissue identified IL1B, CSF3 and TIMP1 as potential plasma markers and VIM, STC1, TGFB1 and HMOX1 as potential biopsy markers for GBM. In conclusion, our study provided a comprehensive understanding for signal pathways and hypoxic characteristics of GBM and identified new biomarkers for GBM patients.

Ubiquitin levels: the next target against gynecological cancers?

Ubiquitylation is a tightly regulated process that is essential for appropriate cell survival and function, and the ubiquitin pathway has shown promise as a therapeutic target for several forms of cancer. In this issue of the JCI, Kedves and colleagues report the identification of a subset of gynecological cancers with repressed expression of the polyubiquitin gene UBB, which renders these cancer cells sensitive to further decreases in ubiquitin production by inhibition of the polyubiquitin gene UBC. Moreover, inducible depletion of UBC in mice harboring tumors with low UBB levels dramatically decreased tumor burden and prolonged survival. Together, the results of this study indicate that there is a synthetic lethal relationship between UBB and UBC that has potential to be exploited as a therapeutic strategy to fight these devastating cancers.