Pan-cancer analysis of LRRC59 with a focus on prognostic and immunological roles in hepatocellular carcinoma.

BACKGROUND: LRRC59 is a leucine-rich repeats-containing protein located in the endoplasmic reticulum (ER), it serves as a prognostic marker in several cancers. However, there has been no systematic analysis of its role in the tumor immune microenvironment, nor its predictive value of prognosis and immunotherapy response in different cancers. METHODS: A comprehensive pan-cancer analysis of LRRC59 was conducted from various databases to elucidate the associations between its expression and the prognosis of cancer, genetic alterations, tumor metabolism, and tumor immunity. Additionally, further functional assays were performed in hepatocellular carcinoma (HCC) to study its biological role in regulating cell proliferation, migration, apoptosis, cell cycle arrest, and sensitivity to immunotherapy. RESULTS: The pan-cancer analysis reveals a significant upregulation of LRRC59 in pan-cancer, and its overexpression is correlated with unfavorable prognosis in cancer patients. LRRC59 is negatively correlated with immune cell infiltration, tumor purity estimation, and immune checkpoint genes. Finally, the validation in HCC demonstrates LRRC59 is significantly overexpressed in cancer tissue and cell lines, and its knockdown inhibits cell proliferation and migration, promotes cell apoptosis, induces cell cycle arrest, and enhances the sensitivity to immunotherapy in HCC cells. CONCLUSIONS: LRRC59 emerges as a novel potential prognostic biomarker across malignancies, offering promise for anti-cancer drugs and immunotherapy.

Single-cell RNA-seq reveals T cell exhaustion and immune response landscape in osteosarcoma.

Background: T cell exhaustion in the tumor microenvironment has been demonstrated as a substantial contributor to tumor immunosuppression and progression. However, the correlation between T cell exhaustion and osteosarcoma (OS) remains unclear. Methods: In our present study, single-cell RNA-seq data for OS from the GEO database was analysed to identify CD8+ T cells and discern CD8+ T cell subsets objectively. Subgroup differentiation trajectory was then used to pinpoint genes altered in response to T cell exhaustion. Subsequently, six machine learning algorithms were applied to develop a prognostic model linked with T cell exhaustion. This model was subsequently validated in the TARGETs and Meta cohorts. Finally, we examined disparities in immune cell infiltration, immune checkpoints, immune-related pathways, and the efficacy of immunotherapy between high and low TEX score groups. Results: The findings unveiled differential exhaustion in CD8+ T cells within the OS microenvironment. Three genes related to T cell exhaustion (RAD23A, SAC3D1, PSIP1) were identified and employed to formulate a T cell exhaustion model. This model exhibited robust predictive capabilities for OS prognosis, with patients in the low TEX score group demonstrating a more favorable prognosis, increased immune cell infiltration, and heightened responsiveness to treatment compared to those in the high TEX score group. Conclusion: In summary, our research elucidates the role of T cell exhaustion in the immunotherapy and progression of OS, the prognostic model constructed based on T cell exhaustion-related genes holds promise as a potential method for prognostication in the management and treatment of OS patients.

Identification of hub genes and potential therapeutic mechanisms related to HPV positive head and neck squamous carcinoma based on full transcriptomic detection and ceRNA network construction.

Infection with human papillomavirus (HPV) is a major risk factor for head and neck squamous cell carcinoma (HNSCC). The objective of this study is to investigate the gene expression profiles and signaling pathways that are specific to HPV-positive HNSCC (HPV+ HNSCC). Moreover, a competing endogenous RNA (ceRNA) network analysis was utilized to identify the core gene of HPV+ HNSCC and potential targeted therapeutic drugs. Transcriptome sequencing analysis identified 3,253 coding RNAs and 3,903 non-coding RNAs (ncRNAs) that exhibited preferentially expressed in HPV+ HNSCC. Four key signaling pathways were selected through pathway enrichment analysis. By combining ceRNA network and protein-protein interaction (PPI) network topology analysis, RNA Polymerase II Associated Protein 2 (RPAP2), which also exhibited high expression in HPV+ HNSCC based on the TCGA database, was identified as the hub gene. Gene set enrichment analysis (GSEA) results revealed RPAP2's involvement in various signaling pathways, encompassing basal transcription factors, ubiquitin-mediated proteolysis, adherens junction, other glycan degradation, ATP-binding cassette (ABC) transporters, and oglycan biosynthesis. Five potential small molecule targeted drugs (enzastaurin, brequinar, talinolol, phenylbutazone, and afuresertib) were identified using the cMAP database, with enzastaurin showing the highest affinity for RPAP2. Cellular functional experiments confirmed the inhibitory effect of enzastaurin on cell viability of HPV+ HNSCC and RPAP2 expression levels. Additionally, enzastaurin treatment suppressed the expression levels of the top-ranked long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) in the ceRNA network. This study based on the ceRNA network provides valuable insights into the molecular mechanisms and potential therapeutic strategies for HPV+ HNSCC, and provide theoretical basis for the exploration of HPV+ HNSCC biomarkers and the development of targeted drugs.

METTL16 promotes osteosarcoma progression by downregulating VPS33B in an m6 A-dependent manner.

N6-methyladenosine (m6 A) is one of the main epitranscriptomic modifications that accelerates the progression of malignant tumors by modifying RNA. Methyltransferase-like 16 (METTL16) is a newly identified methyltransferase that has been found to play an important oncogenic role in a few malignancies; however, its function in osteosarcoma (OS) remains unclear. In this study, METTL16 was found to be upregulated in OS tissues, and associated with poor prognosis in OS patients. Functionally, METTL16 substantially promoted OS cell proliferation, migration, and invasion in vitro and OS growth in vivo. Mechanistically, vacuolar protein sorting protein 33b (VPS33B) was identified as the downstream target of METTL16, which induced m6 A modification of VPS33B and impaired the stability of the VPS33B transcript, thereby degrading VPS33B. In addition, VPS33B was found to be downregulated in OS tissues, VPS33B knockdown markedly attenuated shMETTL16-mediated inhibition on OS progression. Finally, METTL16/VPS33B might facilitate OS progression through PI3K/AKT pathway. In summary, this study revealed an important role for the METTL16-mediated m6 A modification in OS progression, implying it as a promising target for OS treatment.

Ectopic and visceral fat deposition in aging, obesity, and idiopathic pulmonary fibrosis: an interconnected role.

Idiopathic pulmonary fibrosis (IPF) is considered an age-related disease. Age-related changes, along with other factors such as obesity, hormonal imbalances, and various metabolic disorders, lead to ectopic fat deposition (EFD). This accumulation of fat outside of its normal storage sites is associated with detrimental effects such as lipotoxicity, oxidative stress, inflammation, and insulin resistance. This narrative review provides an overview of the connection between ectopic and visceral fat deposition in aging, obesity, and IPF. It also elucidates the mechanism by which ectopic fat deposition in the airways and lungs, pericardium, skeletal muscles, and pancreas contributes to lung injury and fibrosis in patients with IPF, directly or indirectly. Moreover, the review discusses the impact of EFD on the severity of the disease, quality of life, presence of comorbidities, and overall prognosis in IPF patients. The review provides detailed information on recent research regarding representative lipid-lowering drugs, hypoglycemic drugs, and lipid-targeting drugs in animal experiments and clinical studies. This may offer new therapeutic directions for patients with IPF.

Establishment and application of the BRP prognosis model for idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is the most common idiopathic interstitial lung disease. Clinical models to accurately evaluate the prognosis of IPF are currently lacking. This study aimed to construct an easy-to-use and robust prediction model for transplant-free survival (TFS) of IPF based on clinical and radiological information. METHODS: A multicenter prognostic study was conducted involving 166 IPF patients who were followed up for 3 years. The end point of follow-up was death or lung transplantation. Clinical information, lung function tests, and chest computed tomography (CT) scans were collected. Body composition quantification on CT was performed using 3D Slicer software. Risk factors in blood routine examination-radiology-pulmonary function (BRP) were identified by Cox regression and utilized to construct the "BRP Prognosis Model". The performance of the BRP model and the gender-age-physiology variables (GAP) model was compared using time-ROC curves, calibration curves, and decision curve analysis (DCA). Furthermore, histopathology fibrosis scores in clinical specimens were compared between the different risk stratifications identified by the BRP model. The correlations among body composition, lung function, serum inflammatory factors, and profibrotic factors were analyzed. RESULTS: Neutrophil percentage > 68.3%, pericardial adipose tissue (PAT) > 94.91 cm3, pectoralis muscle radiodensity (PMD) ≤ 36.24 HU, diffusing capacity of the lung for carbon monoxide/alveolar ventilation (DLCO/VA) ≤ 56.03%, and maximum vital capacity (VCmax) < 90.5% were identified as independent risk factors for poor TFS among patients with IPF. We constructed a BRP model, which showed superior accuracy, discrimination, and clinical practicability to the GAP model. Median TFS differed significantly among patients at different risk levels identified by the BRP model (low risk: TFS > 3 years; intermediate risk: TFS = 2-3 years; high risk: TFS ≈ 1 year). Patients with a high-risk stratification according to the BRP model had a higher fibrosis score on histopathology. Additionally, serum proinflammatory markers were positively correlated with visceral fat volume and infiltration. CONCLUSIONS: In this study, the BRP prognostic model of IPF was successfully constructed and validated. Compared with the commonly used GAP model, the BRP model had better performance and generalization with easily obtainable indicators. The BRP model is suitable for clinical promotion.

Quercetin: A promising drug candidate against the potential SARS-CoV-2-Spike mutants with high viral infectivity.

The emergence of SARS-CoV-2-Spike mutants not only enhances viral infectivity but also lead to treatment failure. Gaining a comprehensive understanding of the molecular binding mode between the mutant SARS-CoV-2-Spike and human ACE2 receptor is crucial for therapeutic development against this virus. Building upon our previous predictions and verifications regarding heightened viral infectivity of six potential SARS-CoV-2-Spike mutants, this study aims to further investigate the potential disruption of the interaction between these mutants and ACE2 by quercetin, a Chinese herbal compound. Molecular docking and dynamics simulations results reveal that the binding sites of quercetin particularly enriched around a specific "cavity" at the interface of Spike/ACE2 complex, indicating a favorable region for quercetin to interfere with Spike/ACE2 interaction. Virus infection assay confirms that quercetin not only attenuates wild-type virus infectivity but also suppresses the infectivity of all six tested SARS-CoV-2-Spike mutants. Therefore, quercetin represents a promising therapeutic candidate against both wild-type and potential future variants of SARS-CoV-2 exhibiting high viral infectivity.

SYVN1-mediated ubiquitylation directs localization of MCT4 in the plasma membrane to promote the progression of lung adenocarcinoma.

Tumour cells mainly generate energy from glycolysis, which is commonly coupled with lactate production even under normoxic conditions. As a critical lactate transporter, monocarboxylate transporter 4 (MCT4) is highly expressed in glycolytic tissues, such as muscles and tumours. Overexpression of MCT4 is associated with poor prognosis for patients with various tumours. However, how MCT4 function is post-translationally regulated remains largely unknown. Taking advantage of human lung adenocarcinoma (LUAD) cells, this study revealed that MCT4 can be polyubiquitylated in a nonproteolytic manner by SYVN1 E3 ubiquitin ligase. The polyubiquitylation facilitates the localization of MCT4 into the plasma membrane, which improves lactate export by MCT4; in accordance, metabolism characterized by reduced glycolysis and lactate production is effectively reprogrammed by SYVN1 knockdown, which can be reversed by MCT4 overexpression. Biologically, SYVN1 knockdown successfully compromises cell proliferation and tumour xenograft growth in mouse models that can be partially rescued by overexpression of MCT4. Clinicopathologically, overexpression of SYVN1 is associated with poor prognosis in patients with LUAD, highlighting the importance of the SYVN1-MCT4 axis, which performs metabolic reprogramming during the progression of LUAD.

A Novel lncRNA FUAT1/TNS4 Axis Confers Chemoresistance by Suppressing Reactive Oxygen Species-Mediated Apoptosis in Gastric Cancer.

Aims: Reactive oxygen species (ROS) play a vital role in conveying the cytotoxicity and resistance of most chemotherapy drugs. Therefore, gaining a comprehensive understanding of the intricate activities against oxidative stress in cancer cells may provide valuable insights into the discovery of common mechanisms underlying chemoresistance. Results: We identified a novel long noncoding RNA (lncRNA), designated fluorouracil-associated transcript-1 (FUAT1), as a key nongenetic player involved in ROS-mediated intrinsic chemoresistance by employing a unique screening strategy based on transcriptome sequencing (RNA-Seq) technology. To investigate the precise role of the FUAT1 regulatory axis in chemoresistance, we conducted a series of in vitro and in vivo assays including gain/loss-of-function and rescue experiments. Mechanistically, our findings revealed that FUAT1 upregulates Tensin 4 (TNS4) by sponging miR-140-5p, which allows gastric cancer cells to survive chemotherapy by inhibiting ROS-mediated apoptosis. Clinically, we observed that the FUAT1/TNS4 regulatory axis is negatively associated with overall survival and progression-free survival among gastric and colon cancer patients treated with 5-fluorouracil adjuvant chemotherapy. Innovation: We devised a novel screening strategy distinct from conventional approaches using drug-resistant strains. Through this approach, we identified the previously unrecognized lncRNA FUAT1/TNS4 axis that plays a critical role in ROS-mediated intrinsic chemoresistance. Conclusions: Our findings shed light on fundamental adaptive mechanisms employed by cancer cells to respond to chemotherapy and provide new insights into developing strategies aiming at overcoming chemoresistance.

Pan-cancer analysis shows that IBSP is a potential prognostic and immunotherapeutic biomarker for multiple cancer types including osteosarcoma.

Background: IBSP is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family that plays a vital role in bone formation, renewal and repair. Emerging evidence revealed that IBSP participated in the tumorigenesis and progression in some cancers. However, its significance in tumour prognosis and immunotherapy is still unknown. Methods: In the current study, we studied the role of IBSP in tumorigenesis, tumor diagnosis, genomic heterogeneity, methylation modifications, immune infiltration, and therapy response in pan-cancer. In addition, we constructed a risk score model to assessed the prognostic classification efficiency of IBSP using the co-expression genes of IBSP in osteosarcoma (OS), and analyzed the expression and role of IBSP in OS through a series of assays in vitro. Results: IBSP was upregulated in various cancers compared to the paired normal tissues, and it was strongly correlated with the prognosis, pathological stage, diagnostic accuracy, genomic heterogeneity, methylation modification, immune infiltration, immune and checkpoint. Moreover, the predictive model we established in combination with the clinical characteristics of OS patients showed high survival predictive power in these individuals. The assays in vitro showed that IBSP promoted the proliferation, migration and invasion of OS cells, which further confirmed IBSP's role in cancers. Conclusions: Our research revealed the multifunctionality of IBSP in the tumorigenesis, progression and therapy in various cancers, which demonstrated that IBSP may serve as a potential prognostic biomarker and a novel immunotherapy target in pan-cancer.

Integrated network pharmacology and serum metabolomics approach deciphers the anti-colon cancer mechanisms of Huangqi Guizhi Wuwu Decoction.

Huangqi Guizhi Wuwu Decoction (HGWD), as a classic Chinese herbal decoction, has been widely used in treating various diseases for hundreds of years. However, systematically elucidating its mechanisms of action remains a great challenge to the field. In this study, taking advantage of the network pharmacology approach, we discovered a potential new use of HGWD for patients with colon cancer (CC). Our in vivo result showed that orally administered HGWD markedly inhibited the growth of CC xenografts in mice. The subsequent enrichment analyses for the core therapeutic targets revealed that HGWD could affect multiple biological processes involving CC growth, such as metabolic reprogramming, apoptosis and immune regulation, through inhibiting multiple cell survival-related signalings, including MAPK and PI3K-AKT pathways. Notably, these in silico analysis results were most experimentally verified by a series of in vitro assays. Furthermore, our results based on serum metabolomics showed that the lipid metabolic pathways, including fatty acid biosynthesis and cholesterol metabolism, play key roles in delivery of the anti-CC effect of HGWD on tumor-bearing mice, and that cytochrome P450 family 2 subfamily E member 1 (CYP2E1) is a potential therapeutic target. Together, our integrated approach reveals a therapeutic effect of HGWD on CC, providing a valuable insight into developing strategies to predict and interpret the mechanisms of action for Chinese herbal decoctions.

Cinnamomi Ramulus inhibits the growth of colon cancer cells via Akt/ERK signaling pathways.

BACKGROUND: Colon cancer (CC) ranks the second highest mortality rate among malignant tumors worldwide, and the current mainstream treatment regimens are not very effective. The unique efficacy of Chinese herb medicine (CHM) for cancer has recently attracted increasing attention. Cinnamomi Ramulus (CR), as a classic CHM, has been widely used in the treatment of a variety of diseases for hundreds of years in China, but its specific pharmacological mechanism against CC needs to be fully evaluated. METHODS: TCMSP and China National Knowledge Infrastructure database were utilized to predict the candidate ingredients of CR, and TCMSP and SwissTargetPrediction database were also employed to predict the drug targets of the candidate ingredients from CR. We subsequently evaluated the therapeutic effect of CR by orally administrating it on CC-bearing mice. Next, we further identified the potential CC-related targets by using Gene Expression Omnibus (GEO) database. Based on these obtained targets, the drug/disease-target PPI networks were constructed using Bisogenet plugin of Cytoscape. The potential core therapeutic targets were then identified through topological analysis using CytoNCA plugin. GO and KEGG enrichment analyses were performed to predict the underlying mechanism of CR against CC. Furthermore, these in silico analysis results were validated by a series of cellular functional and molecular biological assays. UPLC-MS/MS method and molecular docking analysis were employed to identify the potential key components from CR. RESULTS: In this study, we firstly found that CR has potential therapeutic effect on cancer. Then, oral administration of CR could inhibit the growth of CC cells in C57BL/6 mice, while inhibiting the viability and motility of CC cells in vitro. We obtained 111 putative core therapeutic targets of CR. Subsequent enrichment analysis on these targets showed that CR could induce apoptosis and cell cycle arrest in CC cells by blocking Akt/ERK signaling pathways, which was further experimentally verified. We identified 5 key components from the crude extract of CR, among which taxifolin was found most likely to be the key active component against CC. CONCLUSIONS: Our results show that CR as well as its active component taxifolin holds great potential in treatment of CC.

Polygonum cuspidatum inhibits the growth of osteosarcoma cells via impeding Akt/ERK/EGFR signaling pathways.

ABBREVIATIONS: CC: Closeness centrality; OS: Osteosarcoma; TCM: Traditional Chinese medicine; NSCLC: Non-small cell lung cancer; DC: Degree centrality; CHM: Chinese herb medicine; BC: Betweenness centrality.

Potential Prospective Biomarkers for Non-small Cell Lung Cancer: Mini-Chromosome Maintenance Proteins.

Minichromosome maintenance proteins (MCMs) are considered to be essential factors coupling DNA replication to both cell cycle progression and checkpoint regulation. Previous studies have shown that dysregulation of MCMs are implicated in tumorigenesis of lung cancer. However, the distinct expression/mutation patterns and prognostic values of MCMs in lung cancer have yet to be systematically elucidated. In the present study, we analyzed the transcriptional levels, mutations, and prognostic value of MCM1-10 in non-small cell lung cancer (NSCLC) patients using multiple bioinformatics tools, including ONCOMINE, GEPIA, Kaplan-Meier Plotter, cBioPortal, and GESA. The analysis results from GEPIA dataset showed that MCM2/4/10 was significantly high expressed in both lung adenocarcinoma (LUAD) and squamous cell lung carcinomas (LUSCs). Meanwhile, the expression levels of MCM2/4/6/7/8 were associated with advanced tumor stages. Subsequent survival analysis using the Kaplan-Meier Plotter indicated that high expression levels of MCM1/2/3/4/5/6/7/8/10 were associated with worse overall survival (OS), while high expression level of MCM9 predicted better OS in these patients. Furthermore, we experimentally validated overexpression of MCM2 and MCM4 in NSCLC, thus the results from this study support a view that they may serve as potential prospective biomarkers to identify high-risk subgroups of NSCLC patients.

Chinese herbal compounds against SARS-CoV-2: Puerarin and quercetin impair the binding of viral S-protein to ACE2 receptor.

The outbreak of COVID-19 raises an urgent need for the therapeutics to contain the emerging pandemic. However, no effective treatment has been found for SARS-CoV-2 infection to date. Here, we identified puerarin (PubChem CID: 5281807), quercetin (PubChem CID: 5280343) and kaempferol (PubChem CID: 5280863) as potential compounds with binding activity to ACE2 by using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Molecular docking analysis showed that puerarin and quercetin exhibit good binding affinity to ACE2, which was validated by surface plasmon resonance (SPR) assay. Furthermore, SPR-based competition assay revealed that puerarin and quercetin could significantly affect the binding of viral S-protein to ACE2 receptor. Notably, quercetin could also bind to the RBD domain of S-protein, suggesting not only a receptor blocking, but also a virus neutralizing effect of quercetin on SARS-CoV-2. The results from network pharmacology and bioinformatics analysis support a view that quercetin is involved in host immunomodulation, which further renders it a promising candidate against COVID-19. Moreover, given that puerarin is already an existing drug, results from this study not only provide insight into its action mechanism, but also propose a prompt application of it on COVID-19 patients for assessing its clinical feasibility.

A Mechanism of Action Study on Danggui Sini Decoction to Discover Its Therapeutic Effect on Gastric Cancer.

Danggui Sini Decoction (DSD), a classic Chinese herb medicine (CHM) formula, has been used to treat various diseases in China for centuries. However, it remains challenging to reveal its mechanism of action through conventional pharmacological methods. Here, we first explored the mechanism of action of DSD with the assistance of network pharmacology and bioinformatic analysis tools, and found a potential therapeutic effect of DSD on cancer. Indeed, our in vivo experiment demonstrated that oral administration of DSD could significantly inhibit the growth of xenografted gastric cancer (GC) on mice. The subsequent enrichment analyses for 123 candidate core targets evacuated from the drug/disease-target protein-protein interaction network showed that DSD could affect the key biological processes involving the survival and growth of GC cells, such as apoptosis and cell cycle, and the disturbance of these biological processes is likely attributed to the simultaneous inhibition of multiple signaling pathways, including PI3K/Akt, MAPK, and p53 pathways. Notably, these in silico results were further validated by a series of cellular functional and molecular biological assays in vitro. Moreover, molecular docking analysis suggested an important role of MCM2 in delivering the pharmacological activity of DSD against GC. Together, these results indicate that our network pharmacology and bioinformatics-guided approach is feasible and useful in exploring not only the mechanism of action, but also the "new use" of the old CHM formula.

Unraveling the action mechanism of polygonum cuspidatum by a network pharmacology approach.

As a popular Chinese herbal medicine (CHM), polygonum cuspidatum is widely used to treat various diseases in China. However, its biological function and action mechanism have yet to be systematically explored. In the present study, we first identified 14 potential active ingredients of polygonum cuspidatum using the TCMSP server and then conducted an in silico target prediction for these ingredients using PharmMapper. The subsequent KEGG pathway enrichment analysis of the 57 identified potential targets revealed that they were closely associated with cancer and gynecological disorders. Furthermore, a protein-protein interaction network of these targets was constructed using STRING and Cytoscape, through which 11 core targets were excavated according to degree, a key topological parameter. Meanwhile, we developed a novel formula, in which the "R value" is determined by average shortest path length and closeness centrality, two other key topological parameters, to evaluate the reliability of these predicted core targets. Intriguingly, among the top 10 core targets excavated using this new formula, 7 overlapped with the former 11 core targets, showing a good consistency in these core targets between the different prediction algorithms. Next, 7 ingredients were identified/validated from the crude extract of polygonum cuspidatum using UPLC-MS/MS. Noteworthy, 6 potential targets predicted for these 7 ingredients overlapped with the 7 core targets excavated from the previous in silico analyses. Further molecular docking and druggability analyses suggested that polydatin may play a pivotal role in manifesting the therapeutic effects of polygonum cuspidatum. Finally, we carried out a series of cell functional assays, which validated the anti-proliferative effects of polygonum cuspidatum on gynecological cancer cells, thus demonstrating our network pharmacology approach is reliable and powerful enough to guide the CHM mechanism study.

Integrated bioinformatics analysis revealing independent prognostic long non-coding RNAs DNAH17-AS1 and RP11-400N13.2 and their potential oncogenic roles in colorectal cancer.

The aberrant expression of long non-coding RNAs (lncRNAs) has been associated with a variety of malignancies, including colorectal cancer (CRC); however, the key lncRNAs associated with patient prognosis and their biological roles in CRC are yet to be determined. The aim of the present study was to determine the key lncRNAs associated with patient prognosis as well as their biological roles in CRC. Therefore, a dataset from The Cancer Genome Atlas containing the lncRNA expression data of 521 CRC and normal colorectal mucosal tissues, as well as the corresponding clinical data, were screened. A total of 1,180 significantly differentially expressed lncRNAs were associated with CRC as determined by t-tests in edgeR. Kaplan-Meier analysis revealed that 56 of the 1,180 lncRNAs were associated with overall survival (OS); 7 of the 56 lncRNAs were identified as key lncRNAs associated with the Tumor-Node-Metastasis stage of CRC by Kruskal-Wallis test. Subsequent univariate and multivariate Cox regression analyses of the 7 lncRNAs revealed 2 lncRNAs, DNAH17-AS1 and RP11-400N13.2, as potential independent prognostic factors for the OS of patients with CRC. Furthermore, the expression levelsof these 2 lncRNAs were significantly upregulated in CRC compared with those in normal tissues, which suggested that they may serve an oncogenic role in CRC. In addition, networks comprising the 2 lncRNAs and their respective co-expressed protein-coding genes (PCGs) were constructed using cor.test in R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of these PCGs were conducted; DNAH17-AS1- and RP11-400N13.2-associated PCGs were reported to be involved in G-protein coupling-related functions. Thus, these independent prognostic lncRNAs and their associated functions identified in the present study may provide novel insight into potential prognostic biomarkers and therapeutic targets for the treatment of CRC.

UBE2C overexpression in melanoma and its essential role in G2/M transition.

Ubiquitin­conjugating enzyme E2C (UBE2C) is a key regulator of cell cycle progression, and its aberrant expression has been implicated in various malignancies. However, its clinical and biological roles in malignant melanoma is still unclear. In this study, we found a significant high expression level of UBE2C in melanoma by an in silico analysis of The Cancer Genome Atlas (TCGA) database, which was further validated using fresh melanoma samples. The KM plotter showed that UBE2C level was statistically related to the overall survival (OS) of melanoma patients (p<0.01). RNA interference of UBE2C inhibited the growth of melanoma cells via deactivating ERK/Akt signaling pathways, and blocked the G2/M transition through downregulation of both the level and the activity of mitosis promoting factor (MPF), triggering the apoptosis of melanoma cells. Further, silencing of UBE2C significantly inhibited the xenografted tumor growth on nude mice, indicating an important role of UBE2C in melanoma growth in vivo. Together, our results show that UBE2C may serve as a novel prognostic biomarker as well as a potential therapeutic target for melanoma.

Add-On therapy with Chinese herb medicine Bo-Er-Ning capsule (BENC) improves outcomes of gastric cancer patients: a randomized clinical trial followed with bioinformatics-assisted mechanism study.

As a Chinese herb medicine (CHM), Bo-Er-Ning capsule (BENC) has been approved in China for adjuvant treatment of cancer, but the particular therapeutic effect of BENC on gastric cancer (GC) has yet to be evaluated. In this study, we implemented an efficacy-driven approach by directly starting the study with a randomized clinical trial to assess the add-on therapeutic effect of BENC on advanced GC patients. Our results showed that the addition of BENC to chemotherapy resulted in higher Karnofsky performance scores and better 3-year overall survival, compared to those treated with the conventional chemotherapy regimen. Subsequently, we explored the mechanism of BENC action on GC cells in the assistance of BATMAN-TCM, the first online bioinformatics analysis tool designed especially for the mechanism study of CHM, by which we identified 263 candidate protein targets of BENC involved in GC treatment. The further enrichment analysis suggested that BENC treatment affected a diversity of biological processes of GC cells, such as cell proliferation, cell cycle and apoptosis, which were further validated in the following in vitro and in vivo assays, indicating such a bioinformatics-assisted approach was feasible and powerful to CHM mechanism study. Thus, as exemplified by BENC, we provided an efficacy-driven and bioinformatics-assisted strategy for CHM research, which may help promote the discovery and application of novel CHM drugs on patients with refractory diseases.