Association between the gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study.

Numerous studies have revealed a correlation between the risk of developing diabetic nephropathy (DN) and the gut microbiota (GM) composition. However, it remains uncertain whether the GM composition causes DN. We aimed to explore any potential causal links between the GM composition and the risk of developing DN. A meta-analysis conducted by the MiBioGen consortium of the largest genome-wide association study (GWAS) provided aggregated data on the GM. DN data were obtained from the IEU database. The inverse-variance weighting (IVW) method was employed as the primary analytical approach. The IVW analysis indicated that genus Dialister (OR = 0.51, 95% CI: 0.34-0.77, p = 0.00118) was protective against DN. In addition, class Gammaproteobacteria (OR = 0.47, 95% CI: 0.27-0.83, p = 0.0096), class Lentisphaeria (OR =0.76, 95% CI: 0.68-0.99, p = 0.04), order Victivallales (OR = 0.76, 95% CI: 0.58-0.99, p = 0.04), and phylum Proteobacteria (OR = 0.53, 95% CI: 0.33-0.85, p = 0.00872) were negatively associated with the risk of developing DN. Genus LachnospiraceaeUCG008 (OR =1.45, 95% CI: 1.08-1.95, p = 0.01), order Bacteroidales (OR = 1.59, 95% CI: 1.02-2.49, p = 0.04), and genus Terrisporobacter (OR = 1.98, 95% CI: 1.14-3.45, p = 0.015) were positively associated with the risk of developing DN. In this study, we established a causal relationship between the genus Dialister and the risk of developing DN. Further trials are required to confirm the protective effects of probiotics on DN and to elucidate the precise protective mechanisms involving genus Dialister and DN.

Pan-cancer analysis of NLRP3 inflammasome with potential implications in prognosis and immunotherapy in human cancer.

NLRP3 inflammasome was introduced as a double-edged sword in tumorigenesis and influenced immunotherapy response by modulating host immunity. However, a systematic assessment of the NLRP3-inflammasome-related genes across human cancers is lacking, and the predictive role of NLRP3 inflammasome in cancer immunotherapy (CIT) response remains unexplored. Thus, in this study, we performed a pan-cancer analysis of NLRP3-inflammasome-related genes across 24 human cancers. Out of these 24 cancers, 15 cancers had significantly different expression of NLRP3-inflammasome-related genes between normal and tumor samples. Meanwhile, Cox regression analysis showed that the NLRP3 inflammasome score could be served as an independent prognostic factor in skin cutaneous melanoma. Further analysis indicated that NLRP3 inflammasome may influence tumor immunity mainly by mediating tumor-infiltrating lymphocytes and macrophages, and the effect of NLRP3 inflammasome on immunity is diverse across tumor types in tumor microenvironment. We also found that the NLRP3 inflammasome score could be a stronger predictor for immune signatures compared with tumor mutation burden (TMB) and glycolytic activity, which have been reported as immune predictors. Furthermore, analysis of the association between NLRP3 inflammasome and CIT response using six CIT response datasets revealed the predictive value of NLRP3 inflammasome for immunotherapy response of patients in diverse cancers. Our study illustrates the characterization of NLRP3 inflammasome in multiple cancer types and highlights its potential value as a predictive biomarker of CIT response, which can pave the way for further investigation of the prognostic and therapeutic potentials of NLRP3 inflammasome.

LncRNA SPRY4-IT1 regulates breast cancer cell stemness through competitively binding miR-6882-3p with TCF7L2.

SPRY4-intronic transcript 1 has been found in several kinds of cancers, but the role of SPRY4-IT1 in breast cancer stem cells has not been studied. We investigated whether SPRY4-IT1 is involved in the promotion of breast cancer stem cells (BCSCs). We used qRT-PCR to detect the expression of SPRY4-IT1 in MCF-7 cells and MCF-7 cancer stem cells (MCF-7 CSCs). The effects of SPRY4-IT1 on the proliferation and renewal ability of breast cancer cells were investigated by in vitro and in vivo assays (ie in situ hybridization, colony formation assay, sphere formation assay, flow cytometry assay, western blotting, xenograft model and immunohistochemistry). The mechanism of SPPRY4-IT1 as a ceRNA was studied by a dual-luciferase reporter assay and bioinformatic analysis. In our study, SPRY4-IT1 was up-regulated in MCF-7 CSCs compared with MCF-7 cells, and high SPRY4-IT1 expression was related to reduced breast cancer patient survival. Furthermore, SPRY4-IT1 overexpression promoted breast cancer cell proliferation and stemness in vitro and in vivo. In addition, SPRY4-IT1 knockdown suppressed BCSC renewal ability and stemness maintenance in vivo and in vitro. The dual-luciferase reporter assays indicated that SPRY4-IT1 as a sponge for miR-6882-3p repressed transcription factor 7-like 2 (TCF7L2) expression. Taken together, these findings demonstrated that SPRY4-IT1 promotes proliferation and stemness of breast cancer cells as well as renewal ability and stemness maintenance of BCSCs by increasing the expression of TCF7L2 through targeting miR-6882-3p.

A five-mRNA signature associated with post-translational modifications can better predict recurrence and survival in cervical cancer.

High mortality of patients with cervical cancer (CC) stresses the imperative of prognostic biomarkers for CC patients. Additionally, the vital status of post-translational modifications (PTMs) in the progression of cancers has been reported by numerous researches. Therefore, the purpose of this research was to dig a prognostic signature correlated with PTMs for CC. We built a five-mRNA (GALNTL6, ARSE, DPAGT1, GANAB and FURIN) prognostic signature associated with PTMs to predict both disease-free survival (DFS) (hazard ratio [HR] = 3.967, 95% CI = 1.985-7.927; P < .001) and overall survival (HR = 2.092, 95% CI = 1.138-3.847; P = .018) for CC using data from The Cancer Genome Atlas database. Then, the robustness of the signature was validated using GSE44001 and the Human Protein Atlas (HPA) database. CIBERSORT algorithm analysis displayed that activated CD4 memory T cell was also an independent indicator for DFS (HR = 0.426, 95% CI = 0.186-0.978; P = .044) which could add additional prognostic value to the signature. Collectively, the PTM-related signature and activated CD4 memory T cell can provide new avenues for the prognostic predication of CC. These findings give further insights into effective treatment strategies for CC, providing opportunities for further experimental and clinical validations.

Expression signature of six-snoRNA serves as novel non-invasive biomarker for diagnosis and prognosis prediction of renal clear cell carcinoma.

Increasing evidence has verified that small nucleolar RNAs (snoRNAs) play significant roles in tumorigenesis and exhibit prognostic value in clinical practice. In the study, we analysed the expression profile and clinical relevance of snoRNAs from TCGA database including 530 ccRCC (clear cell renal cell carcinoma) and 72 control cases. By using univariate and multivariate Cox analysis, we established a six-snoRNA signature and divided patients into high-risk or low-risk groups. We found patients in high-risk group had significantly shorter overall survival and recurrence-free survival than those in low-risk group in test series, validation series and entire series by Kaplan-Meier analysis. We also confirmed this signature had a great accuracy and specificity in 64 clinical tissue cases and 50 serum samples. Then, depending on receiver operating characteristic curve analysis we found the six-snoRNA signature was an superior indicator better than conventional clinical factors (AUC = 0.732). Furthermore, combining the signature with TNM stage or Fuhrman grade were the optimal indicators (AUC = 0.792; AUC = 0.800) and processed the clinical applied value for ccRCC. Finally, we found the SNORA70B and its hose gene USP34 might directly regulate Wnt signalling pathway to promote tumorigenesis in ccRCC. In general, our study established a six-snoRNA signature as an independent and superior diagnosis and prognosis indicator for ccRCC.

Identification of a panel of mitotic spindle-related genes as a signature predicting survival in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most malignant tumor types worldwide. Our objective was to identify a genetic signature that could predict the prognosis of patients with LUAD. We extracted gene data sets from The Cancer Genome Atlas and obtained differentially expressed genes that were highly expressed at every stage. These genes were analyzed using gene set enrichment analysis to obtain four biological processes associated with LUAD. Subsequently, Cox univariate and multivariate analyses were performed to generate four optimized models (G2M checkpoint, E2F targets, mitotic spindle, and glycolysis). We identified a mitotic spindle-related signature (KIF15, BUB1, CCNB2, CDK1, KIF4A, DLGAP5, ECT2, and ANLN), which could be an independent prognostic indicator, to predict the prognosis of patients with LUAD. This new discovery should offer opportunities to explore the pathogenesis of LUAD and prove clinically useful in predicting LUAD patient prognosis.

Development of a novel gene signature in patients without Helicobacter pylori infection gastric cancer.

Gastric cancer (GC) is one of the most fatal common cancers in worldwide. Helicobacter pylori (H. pylori) infection is closely related to the development of GC, although the mechanism is still unclear. In our study, we aim to develop a robust messenger RNA (mRNA) signature associated with H. pylori (-) GC that can sensitively and efficiently predict the prognostic. The RNA-seq expression profile and corresponding clinical data of 598 gastric cancer samples and 63 normal samples obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database. Using gene set enrichment analysis H. pylori (+) GC and H. pylori (-) GC patients and normal samples to select certain genes for further analysis. Using univariate and multivariate Cox regression model to establish a gene signature for predicting the overall survival (OS). Finally, we identified G2/M related seven-mRNA signature (TGFB1, EGF, MKI67, ILF3, INCENP, TNPO2, and CHAF1A) closely related to the prognosis of patients with H. pylori (-) GC. The seven-mRNA signature was identified to act as an independent prognostic biomarker by stratified analysis and multivariate Cox regression analysis. It was also validated on two test groups from TCGA and GSE15460 and shown that patients with high-risk scores based on the expression of the seven mRNAs had significantly shorter survival times compared to patients with low-risk scores (P < .0001). In this study, we developed a seven-mRNA signature related to G2/M checkpoint from H. pylori (-) GCs that as an independent biomarker potentially with a good performance in predicting OS and might be valuable for the clinical management for patients with GC.

Identification of a novel cell cycle-related gene signature predicting survival in patients with gastric cancer.

Gastric cancer (GC) is one of the most fatal cancers in the world. Thousands of biomarkers have been explored that might be related to survival and prognosis via database mining. However, the prediction effect of single gene biomarkers is not specific enough. Increasing evidence suggests that gene signatures are emerging as a possible better alternative. We aimed to develop a novel gene signature to improve the prognosis prediction of GC. Using the messenger RNA (mRNA)-mining approach, we performed mRNA expression profiling in a large GC cohort (n = 375) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and we recovered genes related to the G2/M checkpoint, which we identified with a Cox proportional regression model. We identified a set of five genes (MARCKS, CCNF, MAPK14, INCENP, and CHAF1A), which were significantly associated with overall survival (OS) in the test series. Based on this five-gene signature, the test series patients could be classified into high-risk or low-risk subgroups. Multivariate Cox regression analysis indicated that the prognostic power of this five-gene signature was independent of clinical features. In conclusion, we developed a five-gene signature related to the cell cycle that can predict survival for GC. Our findings provide novel insight that is useful for understanding cell cycle mechanisms and for identifying patients with GC with poor prognoses.

Prognostic relevance of miR-137 and its liver microenvironment regulatory target gene AFM in hepatocellular carcinoma.

MiR-137 has been identified as potential hepatocellular carcinoma (HCC) prognostic biomarkers. Highly relevant HCC prognostic biomarkers may be derived from combinations of miR-137 with its target genes involved in the regulation of liver microenvironment. This study aimed at the discovery of such a combination with improved HCC prognosis performance than miR-137 or its target gene alone in a significantly higher number of HCC patients than previous studies. Analysis of the differentially expressed micro RNAs (miRNAs) between cancer and noncancer tissues reconfirmed miR-137 to be among the most relevant prognostic miRNAs and the data of 375 HCC patients and 50 normal cases were from the Cancer Genome Atlas (TCGA) data sets. Target genes were identified by the established search methods and Kaplan-Meier survival analysis of HCC patients was used to evaluate the overall survival (OS) and recurrence-free survival (RFS). Cox proportional hazards regression indicated that the miR-137 and its target gene AFM combination is an independent prognostic factor for the OS and RFS in HCC. In vitro experiments validated that miR-137 could bind to 3'-untranslated region of the AFM and promote the invasion and metastasis of HCC cell lines. The expressions of miR-137 and its liver microenvironment regulatory target gene AFM in combination significantly correlated with HCC progression in a higher number of patients than in previous studies, which suggested their potential as prognostic biomarkers for HCC.

SNORD89 promotes stemness phenotype of ovarian cancer cells by regulating Notch1-c-Myc pathway.

BACKGROUND: Ovarian cancer is the leading cause of death in gynecological cancer. Cancer stem cells (CSCs) contribute to the occurrence, progression and resistance. Small nucleolar RNAs (SnoRNAs), a class of small molecule non-coding RNA, involve in the cancer cell stemness and tumorigenesis. METHODS: In this study, we screened out SNORNAs related to ovarian patient's prognosis by analyzing the data of 379 cases of ovarian cancer patients in the TCGA database, and analyzed the difference of SNORNAs expression between OVCAR-3 (OV) sphere-forming (OS) cells and OV cells. After overexpression or knockdown SNORD89, the expression of Nanog, CD44, and CD133 was measured by qRT-PCR or flow cytometry analysis in OV, CAOV-3 (CA) and OS cells, respectively. CCK-8 assays, plate clone formation assay and soft agar colony formation assay were carried out to evaluate the changes of cell proliferation and self-renewal ability. Scratch migration assay and trans-well invasion analysis were used for assessing the changes of migration and invasion ability. RESULTS: High expression of SNORD89 indicates the poor prognosis of ovarian cancer patients and was associated with patients' age, therapy outcome. SNORD89 highly expressed in ovarian cancer stem cells. The overexpression of SNORD89 resulted in the increased stemness markers, S phase cell cycle, cell proliferation, invasion and migration ability in OV and CA cells. Conversely, these phenomena were reversed after SNORD89 silencing in OS cells. Further, we found that SNORD89 could upregulate c-Myc and Notch1 expression in mRNA and protein levels. SNORD89 deteriorates the prognosis of ovarian cancer patients by regulating Notch1-c-Myc pathway to promote cell stemness and acts as an oncogene in ovarian tumorigenesis. Consequently, SNORD89 can be a novel prognostic biomarker and therapeutic target for ovarian cancer.

Identification of potential key genes and pathways predicting pathogenesis and prognosis for triple-negative breast cancer.

BACKGROUND: Triple negative breast cancer (TNBC) is a specific subtype of breast cancer with a poor prognosis due to its aggressive biological behaviour and lack of therapeutic targets. We aimed to explore some novel genes and pathways related to TNBC prognosis through bioinformatics methods as well as potential initiation and progression mechanisms. METHODS: Breast cancer mRNA data were obtained from The Cancer Genome Atlas database (TCGA). Differential expression analysis of cancer and adjacent cancer, as well as, triple negative breast cancer and non-triple negative breast cancer were performed using R software. The key genes related to the pathogenesis were identified by functional and pathway enrichment analysis and protein-protein interaction network analysis. Based on univariate and multivariate Cox proportional hazards model analyses, a gene signature was established to predict overall survival. Receiver operating characteristic curve was used to evaluate the prognostic performance of our model. RESULTS: Based on mRNA expression profiling of breast cancer patients from the TCGA database, 755 differentially expressed overlapping mRNAs were detected between TNBC/non-TNBC samples and normal tissue. We found eight hub genes associated with the cell cycle pathway highly expressed in TNBC. Additionally, a novel six-gene (TMEM252, PRB2, SMCO1, IVL, SMR3B and COL9A3) signature from the 755 differentially expressed mRNAs was constructed and significantly associated with prognosis as an independent prognostic signature. TNBC patients with high-risk scores based on the expression of the 6-mRNAs had significantly shorter survival times compared to patients with low-risk scores (P < 0.0001). CONCLUSIONS: The eight hub genes we identified might be tightly correlated with TNBC pathogenesis. The 6-mRNA signature established might act as an independent biomarker with a potentially good performance in predicting overall survival.

MicroRNA-100 suppresses the migration and invasion of breast cancer cells by targeting FZD-8 and inhibiting Wnt/ß-catenin signaling pathway.

Wnt/ß-catenin signaling pathway plays a major role in the cancer metastasis. Several microRNAs (miRNAs) are contributed to the inhibition of breast cancer metastasis. Here, we attempted to find novel targets and mechanisms of microRNA-100 (miR-100) in regulating the migration and invasion of breast cancer cells. In this study, we found that miR-100 expression was downregulated in human breast cancer tissues and cell lines. The overexpression of miR-100 inhibited the migration and invasion of MDA-MB-231 breast cancer cells. Inversely, the downregulation of miR-100 increased the migration and invasion of MCF-7 breast cancer cells. Furthermore, FZD-8, a receptor of Wnt/ß-catenin signaling pathway, was demonstrated a direct target of miR-100. The overexpression of miR-100 decreased the expression levels not only FZD-8 but also the key components of Wnt/ß-catenin pathway, including ß-catenin, metalloproteniase-7 (MMP-7), T-cell factor-4 (TCF-4), and lymphoid enhancing factor-1 (LEF-1), and increased the protein expression levels of GSK-3ß and p-GSK-3ß in MDA-MB-231 cells, and the transfection of miR-100 inhibitor in MCF-7 cells showed the opposite effects. In addition, the expression of miR-100 was negatively correlated with the FZD-8 expression in human breast cancer tissues. Overall, these findings suggest that miR-100 suppresses the migration and invasion of breast cancer cells by targeting FZD-8 and inhibiting Wnt/ß-catenin signaling pathway and manipulation of miR-100 may provide a promoting therapeutic strategy for cancer breast treatment.

miR-302a/b/c/d cooperatively inhibit BCRP expression to increase drug sensitivity in breast cancer cells.

OBJECTIVE: BCRP is overexpressed in many tumors and mediates multidrug resistance in breast cancer. In this study, we determined the involvement of miR-302S in the development of drug resistance in breast cancer. METHODS: The differential miRNA expression profiling in parental MCF-7 cells and its derivative mitoxantrone (MX)-resistant MCF-7 (MCF-7/MX) cells was determined by the microarray analysis. The levels of miR-302S family and BCRP mRNA expression were determined by using Quantitative Real-Time PCR. The targeting effect between the individuals of miR-302S and BCRP mRNA-3'UTR were detected by dual-luciferase reporter assay. Proteins of BCRP are represented by Western blot assay. Cell viability was assessed by MTS assay. Efflux capacity was evaluated using flow cytometry. RESULTS: The miR-302S family including miR-302a, miR-302b, miR-302c, and miR-302d was significantly down-regulated in BCRP-overexpressing MCF-7/MX cells. Luciferase activity assay showed that miR-302 inhibited BCRP expression by targeting the 3'-untranslated region (UTR) of the BCRP mRNA. Overexpression of miR-302 increased intracellular accumulation of MX and sensitized breast cancer cells to MX. Furthermore, intratumoral injection of miR-302 potentiated the inhibitory effect of MX on tumor growth in mice transplanted with MCF-7/MX cells. Most importantly, miR-302S produced stronger effects than each individual member alone. CONCLUSIONS: These findings suggest that miR-302 inhibits BCRP expression via targeting the 3'-UTR of BCRP mRNA. miR-302 members may cooperatively downregulate BCRP expression to increase chemosensitivity of breast cancer cells. miR-302 gene cluster may be a potential target for reversing BCRP-mediated chemoresistance in breast cancer.

Association between CD24-P226-C/T polymorphism and multiple sclerosis: a meta-analysis.

BACKGROUND: Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system (CNS), the etiology of which is still uncertain. Several case-control studies investigated the association between CD24-P226-C/T polymorphism and MS risk, and these studies have shown inconsistent results. OBJECTIVE: To address the association of CD24-P226-C/T polymorphism with MS risk by meta-analysis. METHODS: A comprehensive search was conducted to identify all eligible studies of CD24-P226-C/T polymorphism and MS risk up to July 2013. The odds ratios (ORs) of CD24 allele distributions in MS were analyzed against controls. RESULTS: In total, seven case-control studies with 949 cases of MS and 1177 controls were included in this meta-analysis. The overall results showed a significant association between CD24-P226-C/T polymorphism and MS susceptibility under homozygote comparison model (OR = 2.496, 95% CI = 1.813-3.435, p < 0.0005), dominant model (OR = 1.367, 95% CI = 1.147-1.629, p < 0.0005), recessive model (OR = 2.305, 95% CI = 1.700-3.126, p < 0.0005) and allelic model (OR = 1.422, 95% CI = 1.244-1.625, p < 0.0005). However, no significant association was observed under heterozygous comparison model (OR = 1.182, 95% CI = 0.982-1.423, p = 0.078). CONCLUSIONS: This meta-analysis indicates that CD24 P266-C/T polymorphism is more associated with the risk of MS than healthy controls. However, due to the small sample size in most of the included studies, additional large-scale and well-designed case-control studies were required for the validation of this association.

Mendelian randomization supports causality between COVID-19 and glaucoma.

To determine whether there is a causal relationship between Corona Virus Disease 2019 (COVID-19) and glaucoma, a 2-sample Mendelian Randomization (MR) design was applied with the main analysis method of inverse-variance-weighted. The reliability of the results was checked using the heterogeneity test, pleiotropy test, and leave-one-out method. Four sets of instrumental variables (IVs) were used to investigate the causality between COVID-19 and glaucoma risk according to data from the IEU Genome Wide Association Study (GWAS). The results showed that 2 sets of COVID-19(RELEASE) were significantly associated with the risk of glaucoma [ID: ebi-a-GCST011071, OR (95% CI) = 1.227 (1.076-1.400), P = .002259; ID: ebi-a-GCST011073: OR (95% CI) = 1.164 (1.022-1.327), P = .022450; 2 sets of COVID-19 hospitalizations were significantly associated with the risk of glaucoma (ID: ebi-a-GCST011081, OR (95% CI) = 1.156 (1.033-1.292), P = .011342; ID: ebi-a-GCST011082: OR (95% CI) = 1.097 (1.007-1.196), P = .034908)]. The sensitivity of the results was acceptable (P > .05) for the 3 test methods. In conclusion, this MR analysis provides preliminary evidence of a potential causal relationship between COVID-19 and glaucoma.

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.

[Corrigendum] MicroRNA-148a inhibits breast cancer migration and invasion by directly targeting WNT-1.

Subsequently to the publication of the above article, an interested reader drew to the authors' attention that the data panel for the MDA­MB­231/migration/NC experiment in Fig. 2B on p. 1428 was strikingly similar to the data shown for the MDA­MB­231/invasion/Blank experiment in Fig. 2C, such that these data appeared to have been derived from the same original source. The authors have referred back to their original data, and realize that the data panel was selected incorrectly for Fig. 2B. The corrected version of Fig. 2, showing the correct data for the MDA­MB­231/migration/NC experiment in Fig. 2B, is shown on the next page. The authors regret the error that was made during the preparation of this figure, and can confirm that the error in the assembly of this figure did not adversely affect the conclusions reported in the study. The authors are grateful to the Editor of Oncology Reports for allowing them the opportunity to publish a Corrigendum, and all the authors agree to this Corrigendum. Furthermore, they apologize to the readership for any inconvenience caused. [the original article was published in Oncology Reports 35: 1425­1432, 2016; DOI: 10.3892/or.2015.4502].

N6-Methyladenosine-Related RNA Signature Predicting the Prognosis of Ovarian Cancer.

BACKGROUND: N6-Methyladenosine (m6A) RNA methylation is the most universal mRNA modification in eukaryotic cells. M6A mRNA modification affects almost every phases of RNA processing, including splicing, decay, export, translation and expression. Several patents have reported the application of m6A mRNA modification in cancer diagnosis and treatment. Ovarian cancer is the leading cause of death among all gynecological cancers. It is urgent to identify new biomarkers for early diagnosis and prognosis of ovarian cancer. OBJECTIVE: In the current study, we aimed to evaluate the m6A RNA methylation regulators and m6A related genes and establish a new gene signature panel for the prognosis of ovarian cancer. METHODS: We downloaded the mutations data, FPKM data and corresponding clinical information of 373 patients with Ovarian Cancer (OC) from the TCGA database. We performed LASSO regression analysis and multivariate cox regression analysis to develop a risk-identifying gene signature panel. RESULTS: A total of 317 candidate m6A RNA methylation related genes were obtained. Finally, 12 - genes (WTAP, LGR6, ZC2HC1A, SLC4A8, AP2A1, NRAS, CUX1, HDAC1, CD79A, ACE2, FLG2 and LRFN1) were selected to establish the signature panel. We analyzed the genetic alterations of the selected 12 -genes in OC using cBioPortal database. Among the 373 patients, 368 patients have mutations. The results showed that all queried genes were altered in 137 of 368 cases (37.23%). The 12-gene signature panel was confirmed as an independent prognostic indicator (P =2.29E-18, HR = 1.699, 95% CI = 1.508-1.913). CONCLUSION: We established an effective m6A-related gene signature panel consisted of 12 -genes, which can predict the outcome of patients with OC. The high risk score indicates unfavorable survival. Our study provided novel insights into the relationship between m6A and OC. This gene signature panel will be helpful in identifying poor prognostic patients with OC and could be a promising prognostic indicator in clinical practice.

Identification of a Novel Epithelial-Mesenchymal Transition Gene Signature Predicting Survival in Patients With HNSCC.

Head and neck squamous cell cancer (HNSCC) is one of the most common types of cancer worldwide. There have been many reports suggesting that biomarkers explored via database mining plays a critical role in predicting HNSCC prognosis. However, a single biomarker for prognostic analysis is not adequate. Additionally, there is growing evidence indicating that gene signature could be a better choice for HNSCC prognosis. We performed a comprehensive analysis of mRNA expression profiles using clinical information of HNSCC patients from The Cancer Genome Atlas (TCGA). Gene Set Enrichment Analysis (GSEA) was performed, and we found that a set of genes involved in epithelial mesenchymal transition (EMT) contributed to HNSCC. Cox proportional regression model was used to identify a four-gene (WIPF1, PPIB, BASP1, PLOD2) signature that were significantly associated with overall survival (OS), and all the four genes were significantly upregulated in tumor tissues. We successfully classified the patients with HNSCC into high-risk and low-risk groups, where in high-risk indicated poorer patient prognosis, indicating that this gene signature might be a novel potential biomarker for the prognosis of HNSCC. The prognostic ability of the gene signature was further validated in an independent cohort from the Gene Expression Omnibus (GEO) database. In conclusion, we identified a four-EMT-based gene signature which provides the potentiality to serve as novel independent biomarkers for predicting survival in HNSCC patients, as well as a new possibility for individualized treatment of HNSCC.

LncRNA CBR3-AS1 regulates of breast cancer drug sensitivity as a competing endogenous RNA through the JNK1/MEK4-mediated MAPK signal pathway.

BACKGROUND: Adriamycin (ADR) resistance is one of the main obstacles to improving the clinical prognosis of breast cancer patients. Long noncoding RNAs (lncRNAs) can regulate cell behavior, but the role of these RNAs in the anti-ADR activity of breast cancer remains unclear. Here, we aim to investigate the imbalance of a particular long noncoding RNA, lncRNA CBR3 antisense RNA 1 (CBR3-AS1), and its role in ADR resistance. METHODS: Microarray analysis of ADR-resistant breast cancer cells was performed to identify CBR3-AS1. CCK-8 and colony formation assays were used to detect the sensitivity of breast cancer cells to ADR. Dual-luciferase reporter, RNA pulldown, IHC and western blot analyses were used to verify the relationship between the expression of CBR3-AS1, miRNA and target genes. For in vivo experiments, the effect of CBR3-AS1 on breast cancer resistance was observed in a xenograft tumor model. The role of CBR3-AS1 in influencing ADR sensitivity was verified by clinical breast cancer specimens from the TCGA, CCLE, and GDSC databases. RESULTS: We found that CBR3-AS1 expression was significantly increased in breast cancer tissues and was closely correlated with poor prognosis. CBR3-AS1 overexpression promoted ADR resistance in breast cancer cells in vitro and in vivo. Mechanistically, we identified that CBR3-AS1 functioned as a competitive endogenous RNA by sponging miR-25-3p. MEK4 and JNK1 of the MAPK pathway were determined to be direct downstream proteins of the CBR3-AS1/miR-25-3p axis in breast cancer cells. CONCLUSIONS: In summary, our findings demonstrate that CBR3-AS1 plays a critical role in the chemotherapy resistance of breast cancer by mediating the miR-25-3p and MEK4/JNK1 regulatory axes. The potential of CBR3-AS1 as a targetable oncogene and therapeutic biomarker of breast cancer was identified.