MiR-490-5p inhibits the stemness of hepatocellular carcinoma cells by targeting ECT2

To explore the targeting relationship between miR-490-5p and ECT2 in hepatocellular carcinoma (HCC) and the influences of miR-490-5p and ECT2 on the stemness of HCC cells. The expressions of miR-490-5p and ECT2 in HCC tissues and adjacent tissues were identified by quantitative real-time polymerase chain reaction (qRT-PCR). The relationships between the expression levels of miR-490-5p/ ECT2 and the overall/disease-free survival (OS/DFS) of patients with HCC were evaluated using correlative curves. In addition, the targeting relationship between miR-490-5p and ECT2 was predicted by TargetScan and verified by dual-luciferase reporter assay. Plasmid transfection was used for overexpression of ECT2 in HepG2 cells, and transfection efficiency was verified by qRT-PCR. Cell Counting Kit-8 assay and cell sphere-formation assay were conducted to detect the proliferation and sphere-formation ability of HCC cells, respectively. Cell populations with different cell transfections were sorted using flow cytometry. The expression levels of proteins in the stem cell signaling pathway were determined using Western blot analysis. MiR-490-5p was remarkably downregulated, yet ECT2 was upregulated in HCC tissues compared with adjacent tissues. MiR-490-5p expression was positively correlated with OS and DFS of patients with HCC, which were otherwise negatively correlated with ECT2 expression. ECT2 was validated to be the downstream target of miR-490-5p. Overexpression of miR-490-5p restrained the sphere formation ability, stemness, and proliferation of HCC cells. MiR-490-5p repressed the stemness of HCC cells through inhibiting the expression of ECT2. MiR-490-5p may be an underlying therapeutic target in HCC treatment.     

Preoperative albumin-to-globulin ratio predicts survival in patients with non-small-cell lung cancer after surgery

The prognostic value of the preoperative albumin-to-globulin ratio (AGR) has not been investigated in non-small-cell lung cancer (NSCLC). Therefore, we aimed to assess the clinical applicability of the preoperative AGR to predict the prognosis in patients with NSCLC. We retrospectively enrolled 545 patients with stage I/II/III NSCLC who underwent surgery at our institution. The cutoff value for preoperative AGR was calculated by using a receiver operating characteristic curve analysis. A low AGR was associated with several clinicopathological variables related to tumor progression. In the multivariate analyses, the preoperative AGR was identified as an independent prognostic factor for disease-free survival (DFS; P = 0.003) and overall survival (OS; P = 0.005). For patients with stage II and III with a preoperative AGR ≤ 1.43, the surgery plus chemotherapy group had a significantly longer DFS and OS than the surgery alone group (P = 0.002 and P = 0.001, respectively); however, a significant difference in DFS and OS between these two groups was not observed in patients with stage II and III with an AGR > 1.43 (P = 0.808 and P = 0.842, respectively). The preoperative AGR is an independent, significant predictor of DFS and OS in patients with NSCLC. Our results also demonstrate that the preoperative AGR might be a predictive marker of the therapeutic effect of postoperative chemotherapy in patients with stage II and III NSCLC.     

Identification and validation of key genes associated with non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the main causes of death induced by cancer globally. However, the molecular aberrations in NSCLC patients remain unclearly. In the present study, four messenger RNA microarray datasets (GSE18842, GSE40275, GSE43458, and GSE102287) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NSCLC tissues and adjacent lung tissues were obtained from GEO2R and the overlapping DEGs were identified. Moreover, functional and pathway enrichment were performed by Funrich, while the protein–protein interaction (PPI) network construction were obtained from STRING and hub genes were visualized and identified by Cytoscape software. Furthermore, validation, overall survival (OS) and tumor staging analysis of selected hub genes were performed by GEPIA. A total of 367 DEGs (95 upregulated and 272 downregulated) were obtained through gene integration analysis. The PPI network consisted of 94 nodes and 1036 edges in the upregulated DEGs and 272 nodes and 464 edges in the downregulated DEGs, respectively. The PPI network identified 46 upregulated and 27 downregulated hub genes among the DEGs, and six (such as CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M) of that have not been identified to be associated with NSCLC so far. Moreover, the expression differences of the mentioned hub genes were consistent with that in lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. Further analysis showed that all the six hub genes were associated with tumor staging except MYH11, while only the upregulated DEG CENPE was associated with the worse OS of patients with NSCLC. In conclusion, the current study showed that CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M might be the key genes contributed to tumorigenesis or tumor progression in NSCLC, further functional study is needed to explore the involved mechanisms.     

Analysis of methylation-driven genes for predicting the prognosis of patients with head and neck squamous cell carcinoma

To help provide evidence for prognosis prediction and personalized targeted therapy for patients with head and neck squamous cell carcinoma (HNSCC), we investigated prognosis-specific methylation-driven genes in HNSCC. Survival time data, RNA sequencing data, and methylation data for HNSCC patients were downloaded from The Cancer Genome Atlas. The MethylMix R package based on the β mixture model was utilized to screen genes with different methylation statuses in tumor tissues and adjacent normal tissues, and a total of 182 HNSCC-related methylation-driven genes were then identified. A survival prediction scoring model based on multivariate Cox analysis was developed to screen the genes related to the prognosis of HNSCC, and a linear risk model of the methylation status of six genes (INA, LINC01354, TSPYL4, MAGEB2, EPHX3, and ZNF134) was constructed. The prognostic values of the six genes were further independently explored by survival analysis combined with methylation and gene expression analyses. The 5-year survival rate in the high-risk group of patients in the test set was 30.4% (95% CI: 22.7%-40.8%) and that in the low-risk group of patients was 65.5% (95% CI: 56.1%-76.5%). The area under the receiver operating characteristic curve for the model was 0.723, which further verified the specificity and sensitivity of the model. In addition, subsequent combined survival analysis revealed that all six genes could be used as independent prognostic markers and thus might be potential drug targets. The innovative method provides new insight into the molecular mechanism and prognosis of HNSCC.     

Pre-treatment systemic immune-inflammation index is a useful prognostic indicator in patients with breast cancer undergoing neoadjuvant chemotherapy

The systemic immune-inflammation index (SII = N × P/L) based on neutrophil (N), platelet (P) and lymphocyte (L) counts is used to predict the survival of patients with malignant tumours and can fully reflect the balance between host inflammatory and immune status. This study is conducted to explore the potential prognostic significance of SII in patients with breast cancer undergoing neoadjuvant chemotherapy (NACT). A total of 262 patients with breast cancer received NACT were enrolled in this study. According to the receiver operating characteristic curve, the optimal cut-off value of SII was divided into two groups: low SII group (<602 × 10⁹/L) and high SII group (≥602 × 10⁹/L). The associations between breast cancer and clinicopathological variables by SII were determined by chi-squared test or Fisher's exact test. The Kaplan-Meier plots and log-rank test were used to determine clinical outcomes of disease-free survival (DFS) and overall survival (OS). The prognostic value of SII was analysed by univariate and multivariate Cox proportional hazards regression models. The toxicity of NACT was accessed by National Cancer Institute Common Toxicity Criteria (NCICTC). According to univariate and multivariate Cox regression survival analyses, the results showed that the value of SII had prognostic significance for DFS and OS. The patients with low SII value had longer DFS and OS than those with high SII value (31.11 vs 40.76 months, HR: 1.075, 95% CI: 0.718-1.610, P = .006; 44.47 vs 53.68 months, HR: 1.051, 95% CI: 0.707-1.564, P = .005, respectively). The incidence of DFS and OS in breast cancer patients with low SII value was higher than that in those patients with high SII value in 3-, 5- and 10-year rates. The common toxicities after NACT were haematological and gastrointestinal reaction, and there were no differences by SII for the assessment of side effects of neoadjuvant chemotherapy. Meanwhile, the results also proved that breast cancer patients with low SII value and high Miller and Payne grade (MPG) survived longer than those breast cancer with high SII value and low MPG grade. In patients without lymph vessel invasion, these breast cancer patients with low SII value had better prognosis and lower recurrence rates than those with high SII value. Pre-treatment SII with the advantage of reproducible, convenient and non-invasive was a useful prognostic indicator for breast cancer patients undergoing neoadjuvant chemotherapy and is a promising biomarker for breast cancer on treatment strategy decisions.     

Retracted: Role of CXCL12–CXCR4 axis in ovarian cancer metastasis and CXCL12–CXCR4 blockade with AMD3100 suppresses tumor cell migration and invasion in vitro

Ovarian cancer (OC) is a lethal gynecologic tumor, which brings its mortality to the head. CXCL12 and its receptor chemokine receptor 4 ( CXCR4) have been found to be highly expressed in OC and contribute to the disease progression by affecting tumor cell proliferation and invasion. Here, in this study, we aim to explore whether the blockade of CXCL12–CXCR4 axis with AMD3100 (a selective CXCR4 antagonist) has effects on the progression of OC. On the basis of the gene expression omnibus database of OC gene expression chips, the OC differentially expressed genes were screened by microarray analysis. OC (nonmetastatic and metastatic) and normal ovarian tissues were collected to determine the expressions of CXCL12 and CXCR4. A series of AMD3100, shRNA against CXCR4, and pCNS-CXCR4 were introduced to treat CAOV3 cells with the highest CXCR4 was assessed. Cell viability, apoptosis, migration, and invasion were all evaluated. The microarray analysis screened out the differential expression of CXCL12–CXCR4 in OC. CXCL12 and CXCR4 expressions were increased in OC tissues, particularly in the metastatic OC tissues. Downregulation of CXCR4 by AMD3100 or shRNA was observed to have a critical role in inhibiting cell proliferation, migration, and invasion of the CAOV3 OC cell line while promoting cell apoptosis. Overexpressed CXCR4 brought significantly promoting effects on the proliferation and invasiveness of OC cells. These results reinforce that the blockade of CXCL12–CXCR4 axis with AMD3100 inhibits the growth of OC cells. The antitumor role of the inhibition of CXCL12–CXCR4 axis offers a preclinical validation of CXCL12–CXCR4 axis as a therapeutic target in OC.     

Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer

To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS ≥7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (n=70) vs. those without (n=86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3+4 cases and GS 4+3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (n=30) than in the no-recurrence (n=52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.     

The microRNA-29 plays a central role in osteosarcoma pathogenesis and progression

Osteosarcoma is the most common type of bone cancer, with a peak incidence in the early childhood. The relationship between microRNAs (miRNAs) and cancer development attracted more and more attention over the last few years. Members of the miRNA-29 family, including miRNA-29a, miRNA-29b, and miRNA-29c were shown to participate in the development of rhabdomyosarcoma and hepatocarcinogenesis. Here, it has been demonstrated miRNA-29a and miRNA-29b expression levels to be downregulated in most of the osteosarcoma tissues (23 from 30). Besides, miRNA-29a displayed ability to induce apoptosis in both U2OS and SAOS-2 osteoblastic cells. While miRNA-29 members induced apoptosis through p53 gene activation, the effect of miRNA-29a on osteoblastic cells was independent on p53 expression level. Moreover, Bcl-2 and Mcl-1 were earlier demonstrated to be the direct targets of miRNA-29 in many types of cancer tissues and cancers. In both U2OS and SAOS-2 osteoblastic cell types, overexpression of miRNA-29a also downregulated Bcl-2 and Mcl-1, while silencing of miRNA-29a increased their expression. In addition, enhanced expression of miRNA-29a increased the expression of two tumor suppressor genes, E2F1 and E2F3. In summary, data obtained highlight the role of miRNA-29a in the regulation of osteoblastic cell apoptosis by silencing Bcl-2 and Mcl-1 and inducing E2F1 and E2F3 expression.     

12 Survival-related differentially expressed genes based on the TARGET-osteosarcoma database

The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) project aims to determine molecular changes that drive childhood cancers, including osteosarcoma. The main purpose of the program is to use the open-source database to develop novel, effective, and less toxic therapies. We downloaded TARGET-OS RNA-Sequencing data through R studio and merged the mRNA expression of genes with clinical information (vital status, survival time and gender). Further, we analyzed differential gene expressions between dead and alive patients based on TARGET-OS project. By this study, we found 5758 differentially expressed genes between deceased and alive patients with a false discovery rate below 0.05; 4469 genes were upregulated in deceased patients compared to alive, whereas 1289 genes were downregulated. The survival-related genes were obtained using Kaplan–Meier survival analysis and Cox univariate regression (KM < 0.05 and Cox P-value < 0.05). Out of 5758 differentially expressed genes, only 217 have been associated with overall survival. Eight survival-related downregulated genes (ERCC4, CLUAP1, CTNNBIP1, GCA, RAB40C, SIRPA, USP11, and TCN2) and four survival-related upregulated genes (MUC1, COL13A1, JAG2 and KAZALD1) were selected for further analysis as potential independent prognostic candidate genes. This study may help to discover novel prognostic markers and potential therapeutic targets for osteosarcoma.     

Long noncoding RNA ATB promotes ovarian cancer tumorigenesis by mediating histone H3 lysine 27 trimethylation through binding to EZH2

Ovarian cancer (OC) remains one of the most lethal gynecological malignancies. The unfavourable prognosis is mainly due to the lack of early-stage diagnosis, drug resistance and recurrence. Therefore, it needs to investigate the mechanism of OC tumorigenesis and identify effective biomarkers for the clinical diagnosis. It is reported that long noncoding RNAs (lncRNAs) play important roles during the tumorigenesis of OC. Therefore, the present study aimed to study the role and clinical significance of LncRNAs ATB (lnc-ATB) in the development and progression of OC. In our research, lnc-ATB expression in OC tissues was elevated compared with adjacent normal tissues and high expression of lnc-ATB was associated with poor outcomes of OC patients. The silencing of lnc-ATB blocked cell proliferation, invasion and migration in SKOV3 and A2780 cells. RNA immunoprecipitation and RNA pull-down results showed that lnc-ATB positively regulated the expression of EZH2 via directly interacting with EZH2. Besides, the overexpression of EZH2 partly rescued lnc-ATB silencing-inducing inhibition of cell proliferation, invasion and migration. Chromatin immunoprecipitation assay results demonstrated that the silencing of lnc-ATB reduced the occupancy of caudal-related homeobox protein 1, Forkhead box C1, Large tumour suppressor kinase 2, cadherin-1 and disabled homolog 2 interacting protein promoters on EZH2 and H3K27me3. These data revealed the oncogenic of lnc-ATB and provided a novel biomarker for OC diagnosis. Furthermore, these findings indicated the mechanism of lnc-ATB functioning in the progression of OC, which provided a new target for OC therapy.     

Clinical prognostic evaluation of immunocytes in different molecular subtypes of breast cancer

To retrospectively analyze the relationship between preoperative blood parameters and postoperative clinical outcomes in patients with different molecular subtypes of breast cancer (BC), a cohort of 601 patients with BC in the Third Affiliated Hospital, Sun Yat-sen University, was retrospectively reviewed. They were categorized into four subtypes according to the expression of ER, PR, HER-2, and KI-67%. White blood cell, neutrophil, lymphocyte, monocyte, eosinophil, basophil, and platelet counts, the neutrophil-to-lymphocyte ratio (NLR), the neutrophil-to-monocyte ratio (NMR), the lymphocyte-to-monocyte ratio (LMR), and the platelet-to-lymphocyte ratio (PLR) were recorded. Univariate and multivariate analyses were performed to identify the relationship between parameters and ratios and disease-free survival (DFS) and overall survival (OS). Luminal subtypes of BC had smaller tumor volume, better differentiation degree of invasive ductal carcinoma, less lymph node metastasis, and better clinical outcome than the HER-2 overexpression and triple-negative BC (TNBC) subtypes. In multivariate analysis, age and LMR were the independent prognostic factors of DFS in patients with luminal A (age, p = 0.005; LMR, P = 0.026); PLR in patients with luminal B (DFS; p = 0.032; OS, p= 0.012); LMR in patients with HER-2 overexpression (DFS; p = 0.008; OS, p = 0.017); and NLR for DFS (p = 0.014); and WBC for OS (p = 0.008) in patients with TNBC. LMR was the benign predictor of luminal A and HER-2 overexpression. PLR was the adverse predictor of luminal B. WBC and NLR were the adverse predictors of TNBC. Therefore, these peripheral blood parameters can play an important role in the diagnosis and treatment of patients with different molecular subtypes of BC.