Hypermethylated and downregulated MEIS2 are involved in stemness properties and oxaliplatin-based chemotherapy resistance of colorectal cancer

The resistance against oxaliplatin (L-OHP) based regimens remains a major obstacle for its efficient usage in treating metastatic colorectal cancer (mCRC). In this study, we performed weighted gene coexpression network analysis (WGCNA) to systematically screen the relevant hub genes for L-OHP resistance using the raw microarray data of 30 consecutive mCRC samples from our earlier study (GSE69657). The results were further confirmed through datasets from Gene Expression Omnibus (GEO). From L-OHP resistance module, nine genes in both the coexpression and protein–protein interaction networks were chosen as hub genes. Among these genes, Meis Homeobox 2 (MEIS2) had the highest correlation with L-OHP resistance (r = −0.443) and was deregulated in L-OHP resistant tissues compared with L-OHP sensitive tissues in both our own dataset and GSE104645 testing dataset. The receiver operating characteristic curve validated that MEIS2 had a good ability in predicting L-OHP response in both our own dataset (area under the curve [AUC] = 0.802) and GSE104645 dataset (AUC = 0.746). Then, the down expression of MEIS2 was observed in CRC tissue compared with normal tissue in 12 GEO-sourced datasets and The Cancer Genome Atlas (TCGA) and was correlated with poor event-free survival. Furthermore, analyzing methylation data from TCGA showed that MEIS2 had increased promoter hypermethylation. In addition, MEIS2 expression was significantly decreased in CRC stem cells compared with nonstem cells in two GEO datasets (GSE14773 and GSE24747). Further methylation analysis from GSE104271 demonstrated that CRC stem cells had higher MEIS2 promoter methylation levels in cg00366722 and cg00610348 sites. Gene set enrichment analysis showed that MEIS2 might be involved in the Wnt/β-catenin pathway. In the overall view, MEIS2 had increased promoter hypermethylation and was downregulated in poor L-OHP response mCRC tissues. MEIS2 might be involved in the Wnt/β-catenin pathway to maintain CRC stemness, which leads to L-OHP resistance.     

Construction and analysis of dysregulated lncRNA-associated ceRNA network in colorectal cancer

Colorectal cancer (CRC) is one of the most frequently diagnosed digestive system cancer. The aim of the present study was to investigate the interactions among messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs) in CRC to reveal the mechanisms of CRC. Differentially expressed genes (DEGs) were identified from public gene expression data sets. One thousand eighty-one common dysregulated mRNAs in two data sets were identified. Gene function analysis and protein-protein interaction network analysis indicated that these DEGs might play important roles in CRC. LINC00365 was selected through coding- noncoding network analysis and its expression was validated upregulated in 22 paired clinical samples and four CRC cell lines. A competing endogenous RNA network composed of 70 miRNAs, nine mRNAs, and LINC00365 was constructed. Eight of nine mRNAs were validated upregulated in The Cancer Genome Atlas data set. Our results suggested that LINC00365 was an oncogene in CRC and it could regulate the expression of several mRNAs through sponging miRNAs.     

Prognostic genes of hepatocellular carcinoma based on gene coexpression network analysis

Hepatocellular carcinoma (HCC) is the most common subtype in liver cancer whose prognosis is affected by malignant progression associated with complex gene interactions. However, there is currently no available biomarkers associated with HCC progression in clinical application. In our study, RNA sequencing expression data of 50 normal samples and 374 tumor samples was analyzed and 9225 differentially expressed genes were screened. Weighted gene coexpression network analysis was then conducted and the blue module we were interested was identified by calculating the correlations between 17 gene modules and clinical features. In the blue module, the calculation of topological overlap was applied to select the top 30 genes and these 30 genes were divided into the green group (11 genes) and the yellow group (19 genes) through searching whether these genes were validated by in vitro or in vivo experiments. The genes in the green group which had never been validated by any experiments were recognized as hub genes. These hub genes were subsequently validated by a new data set GSE76427 and KM Plotter Online Tool, and the results indicated that 10 genes (FBXO43, ARHGEF39, MXD3, VIPR1, DNASE1L3, PHLDA1, CSRNP1, ADR2B, C1RL, and CDC37L1) could act as prognosis and progression biomarkers of HCC. In summary, 10 genes who have never been mentioned in HCC were identified to be associated with malignant progression and prognosis of patients. These findings may contribute to the improvement of the therapeutic decision, risk stratification, and prognosis prediction for HCC patients.     

Identification and functional analysis of spermatogenesis-associated gene modules in azoospermia by weighted gene coexpression network analysis

Nonobstructive azoospermia (NOA) or testicular failure is the most severe form of male infertility. A variety of conditions, both acquired and congenital, can cause azoospermia. However, in a large number of azoospermia patients who are classified as idiopathic cases, the etiology remains poorly understand mainly due to the lack of knowledge of all the genetic causes and molecular mechanisms responsible for spermatogenesis failure. Identification of the key gene modules and pathways-related spermatogenesis failure might help to reveal the mechanisms of idiopathic azoospermia. Therefore, the expression patterns of spermatogenesis-associated genes in NOA were analyzed by weighted gene coexpression network analysis (WGCNA) based on two public microarray data sets (GSE45885 and GSE45887), which included 51 samples and 32,321 genes. We identified a module (turquoise) that was significantly related to the Johnsen score of the testicular samples. In addition, the results of function and pathway enrichment analyses based on the online bioinformatics database Metascape revealed that genes in the turquoise module were mainly related to the process of spermatogenesis and spermatid development. To further identify spermatogenesis-associated genes, a microarray data set (GSE926) of murine testis at different developmental time points was analyzed by WGCNA. The blue module in GSE926 was significantly related to the time of murine testis development. The overlap study and k-core analysis based on protein–protein interaction network revealed that spermatogenesis- and spermatid development–associated genes, including glyceraldehyde-3-phosphate dehydrogenase, ADAM metallopeptidase domain 2, transition protein 1, testis-specific serine kinase 2, transition protein 2, and germ cell-associated 1 (GSG1), were further identified in the selected modules. The expression profile of GSG1 in human testis was chosen for further study using immunochemistry staining. Taken together, these screened gene modules and pathways provided a more detailed genetic and molecular mechanism underlying spermatogenesis failure occurrence and holds promise as potential diagnosis biomarkers and therapeutic targets.     

利用加权基因共表达网络分析方法挖掘香菇发育不同阶段的关键基因

香菇是世界产量第二大食用菌,栽培历史悠久.在木屑袋料栽培模式下,香菇发育可以分为菌丝生长期(G)、菌丝褐化期(B)、原基形成期(P)以及出菇期(FB)4个阶段.褐化期和原基形成期是香菇从营养生长期到生殖生长两个关键发育阶段,对香菇子实体产量和质量至关重要.本研究以3种不同栽培材料为重复,对香菇发育的前3个阶段进行了转录...     

Systematic prediction of key genes for ovarian cancer by co-expression network analysis

Ovarian cancer (OC) is the most lethal gynaecological malignancy, characterized by high recurrence and mortality. However, the mechanisms of its pathogenesis remain largely unknown, hindering the investigation of the functional roles. This study sought to identify key hub genes that may serve as biomarkers correlated with prognosis. Here, we conduct an integrated analysis using the weighted gene co-expression network analysis (WGCNA) to explore the clinically significant gene sets and identify candidate hub genes associated with OC clinical phenotypes. The gene expression profiles were obtained from the MERAV database. Validations of candidate hub genes were performed with RNASeqV2 data and the corresponding clinical information available from The Cancer Genome Atlas (TCGA) database. In addition, we examined the candidate genes in ovarian cancer cells. Totally, 19 modules were identified and 26 hub genes were extracted from the most significant module (R² = .53) in clinical stages. Through the validation of TCGA data, we found that five hub genes (COL1A1, DCN, LUM, POSTN and THBS2) predicted poor prognosis. Receiver operating characteristic (ROC) curves demonstrated that these five genes exhibited diagnostic efficiency for early-stage and advanced-stage cancer. The protein expression of these five genes in tumour tissues was significantly higher than that in normal tissues. Besides, the expression of COL1A1 was associated with the TAX resistance of tumours and could be affected by the autophagy level in OC cell line. In conclusion, our findings identified five genes could serve as biomarkers related to the prognosis of OC and may be helpful for revealing pathogenic mechanism and developing further research.     

Weighted gene correlation network analysis identifies RSAD2, HERC5, and CCL8 as prognostic candidates for breast cancer

As the most commonly diagnosed malignant tumor in female population, the prognosis of breast cancer is affected by complex gene interaction networks. In this research weighted gene co-expression network analysis (WGCNA) would be utilized to build a gene co-expression network to identify potential biomarkers for prediction the prognosis of patients with breast cancer. We downloaded GSE25065 from Gene Expression Omnibus database as the test set. GSE25055 and GSE42568 were utilized to validate findings in the research. Seven modules were established in the GSE25065 by utilizing average link hierarchical clustering. Three hub genes, RSAD2, HERC5, and CCL8 were screened out from the significant module (R ² = 0.44), which were considerably interrelated to worse prognosis. Within test dataset GSE25065, RSAD2, and CCL8 were correlated with tumor stage, grade, and lymph node metastases, whereas HERC5 was correlated with lymph node metastases and tumor grade. In the validation dataset GSE25055 and RSAD2 expression was correlated with tumor grade, stage, and size, whereas HERC5 was related to tumor stage and tumor grade, and CCL8 was associated with tumor size and tumor grade. Multivariable survival analysis demonstrated that RSAD2, HERC5, and CCL8 were independent risk factors. In conclusion, the WGCNA analysis conducted in this study screened out novel prognostic biomarkers of breast cancer. Meanwhile, further in vivo and in vitro studies are required to make the clear molecular mechanisms.     

The role of microRNAs in 5-FU resistance of colorectal cancer: Possible mechanisms

Colorectal cancer (CRC) is one of the most common cancers globally. Despite recent advances in therapeutic approaches, this cancer continues to have a poor prognosis, particularly when diagnosed late. 5-Fluorouracil (5-FU) has been commonly prescribed for patients with CRC, but resistance to 5-FU is one of the main reasons for failure in the treatment of this condition. Recently, microRNAs (miRNAs) have been established as a means of modifying the signaling pathways involved in initiation and progression of CRC and their role as oncogene or tumor suppressor have been investigated in various studies. Moreover, miRNAs through various mechanisms play an important role in inducing tumor resistance or sensitivity to anticancer drugs. Detecting and targeting these mechanisms may be a new therapeutic approach. This review summarizes the current knowledge about the potential roles of miRNAs in 5-FU resistance, with particular emphasis on molecular mechanism involved.     

Identification of gene expression profiles and key genes in subchondral bone of osteoarthritis using weighted gene coexpression network analysis

Osteoarthritis (OA) significantly influences the quality life of people around the world. It is urgent to find an effective way to understand the genetic etiology of OA. We used weighted gene coexpression network analysis (WGCNA) to explore the key genes involved in the subchondral bone pathological process of OA. Fifty gene expression profiles of GSE51588 were downloaded from the Gene Expression Omnibus database. The OA‐associated genes and gene ontologies were acquired from JuniorDoc. Weighted gene coexpression network analysis was used to find disease‐related networks based on 21756 gene expression correlation coefficients, hub‐genes with the highest connectivity in each module were selected, and the correlation between module eigengene and clinical traits was calculated. The genes in the traits‐related gene coexpression modules were subject to functional annotation and pathway enrichment analysis using ClusterProfiler. A total of 73 gene modules were identified, of which, 12 modules were found with high connectivity with clinical traits. Five modules were found with enriched OA‐associated genes. Moreover, 310 OA‐associated genes were found, and 34 of them were among hub‐genes in each module. Consequently, enrichment results indicated some key metabolic pathways, such as extracellular matrix (ECM)‐receptor interaction (hsa04512), focal adhesion (hsa04510), the phosphatidylinositol 3'‐kinase (PI3K)‐Akt signaling pathway (PI3K‐AKT) (hsa04151), transforming growth factor beta pathway, and Wnt pathway. We intended to identify some core genes, collagen (COL)6A3, COL6A1, ITGA11, BAMBI, and HCK, which could influence downstream signaling pathways once they were activated. In this study, we identified important genes within key coexpression modules, which associate with a pathological process of subchondral bone in OA. Functional analysis results could provide important information to understand the mechanism of OA.     

High-intensity aerobic interval training and resistance training are feasible in rectal cancer patients undergoing chemoradiotherapy: a feasibility randomized controlled study

BackgroundThere has been growing evidence of the benefits of high-intensity aerobic interval training (HIIT) and resistance training (RES) for populations with cancer. However, these two modalities have not yet been performed alone in rectal cancer patients undergoing neoadjuvant chemoradiotherapy (NACR T). Therefore, this study aimed to determine the feasibility of HIIT and RES in rectal cancer patients undergoing NACR T.Materials and methodsRectal cancer patients set to undergo NACRT were randomly assigned to HIIT intervention, RES intervention, or the usual care. Feasibility of HIIT and RES was assessed by measuring recruitment rate, adherence (retention rate, attendance rate, and exercise sessions duration and intensity), and adverse events. Endpoints (changes in fatigue, health-related quality of life, depression, daytime sleepiness, insomnia, sleep quality, functional exercise capacity, and executive function) were assessed at baseline and at week 5.ResultsAmong the 20 eligible patients, 18 subjects were enrolled and completed the study, yielding a 90% recruitment rate and 100% retention rate. Attendance at exercise sessions was excellent, with 92% in HIIT and 88% in RES. No exercise-related adverse events occurred.ConclusionThis study demonstrated that HIIT and RES are feasible in rectal cancer patients undergoing NACR T.Trial registrationwww.clinicaltrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT03252821","term_id":"NCT03252821"}}NCT03252821 (date of registration: March 30, 2017)     

Identification of hub genes in colorectal cancer based on weighted gene co-expression network analysis and clinical data from The Cancer Genome Atlas

Colorectal cancer (CRC) is one of the most common tumors worldwide and is associated with high mortality. Here we performed bioinformatics analysis, which we validated using immunohistochemistry in order to search for hub genes that might serve as biomarkers or therapeutic targets in CRC. Based on data from The Cancer Genome Atlas (TCGA), we identified 4832 genes differentially expressed between CRC and normal samples (1562 up-regulated and 3270 down-regulated in CRC). Gene ontology (GO) analysis showed that up-regulated genes were enriched mainly in organelle fission, cell cycle regulation, and DNA replication; down-regulated genes were enriched primarily in the regulation of ion transmembrane transport and ion homeostasis. Weighted gene co-expression network analysis (WGCNA) identified eight gene modules that were associated with clinical characteristics of CRC patients, including brown and blue modules that were associated with cancer onset. Analysis of the latter two hub modules revealed the following six hub genes: adhesion G protein-coupled receptor B3 (BAI3, also known as ADGRB3), cyclin F (CCNF), cytoskeleton-associated protein 2 like (CKAP2L), diaphanous-related formin 3 (DIAPH3), oxysterol binding protein-like 3 (OSBPL3), and RERG-like protein (RERGL). Expression levels of these hub genes were associated with prognosis, based on Kaplan–Meier survival analysis of data from the Gene Expression Profiling Interactive Analysis database. Immunohistochemistry of CRC tumor tissues confirmed that OSBPL3 is up-regulated in CRC. Our findings suggest that CCNF, DIAPH3, OSBPL3, and RERGL may be useful as therapeutic targets against CRC. BAI3 and CKAP2L may be novel biomarkers of the disease.     

HT-29 colorectal cancer cells undergoing apoptosis overexpress COX-2 to delay ursolic acid-induced cell death

Colorectal cancer is one of the most common cancer types and the third leading cause of cancer-related death in the western world. Generally, colorectal cancers are resistant to anticancer drugs. Several lines of evidence support a critical role for cyclooxygenase-2 (COX-2) during colorectal tumorigenesis and its role in chemoresistance. In this study, we focused our interest on the role played by COX-2 in apoptosis induced in HT-29 human colorectal cancer cells by ursolic acid (UA), a triterpenoid found in a large variety of plants. We showed that UA-induced apoptosis and that COX-2 was overexpressed only in apoptotic cells. We demonstrated that this overexpression was mediated by the p38 MAP kinase pathway as inhibiting its activation using a p38-specific inhibitor, SB 203580, abrogated COX-2 expression. Inhibiting COX-2 expression either by using a p38-specific inhibitor or COX-2-specific siRNA increased apoptosis. These results demonstrated that COX-2 was involved in a resistance mechanism to UA-induced apoptosis in HT-29 cells. Cells undergoing apoptosis were able to trigger a resistance mechanism by overexpressing a protein such as COX-2 to delay their death. Furthermore, we demonstrated that this resistance mechanism was independent of PGE₂ production as the addition of the specific COX-2 activity inhibitor, NS-398, did not affect apoptosis in UA-treated cells.     

Annexin A3 depletion overcomes resistance to oxaliplatin in colorectal cancer via the MAPK signaling pathway

Colorectal cancer (CRC) is a common disease with high mortality and morbidity. Annexin A3 (ANXA3) belongs to the structurally homologous family of Ca²⁺ and phospholipid-binding proteins. This study aimed to investigate the effects and potential mechanisms of ANXA3 on oxaliplatin (Ox) resistance in CRC. We generated two human CRC cell lines (HCT116/Ox and SW480/Ox) with acquired Ox resistance and determined their resistance properties. ANXA3 expression and cell apoptosis, migration and invasion also were evaluated. We found that cell viability of HCT116/Ox and SW480/Ox was higher than that in parental cells in the presence of Ox. ANXA3 was highly expressed in HCT116/Ox and SW480/Ox cells. ANXA3 downregulation diminished cell survival, migration and invasion, while increased the apoptosis of HCT116 and SW480 with or without Ox. Moreover, depletion of ANXA3 reduced cell viability and BrdU incorporation, increased cell apoptosis and c-caspase 3 expression in HCT116/Ox with or without Ox. A transwell assay determined that knockdown of ANXA3 impeded the migration and invasion of HCT116/Ox and SW480/Ox cells. Additionally, phosphorylation of extracellular signal–regulated kinase (ERK) and c-Jun N-terminal kinase (JNK) decreased upon ANXA3 depletion in HCT116/Ox cells, and ANXA3 silencing suppressed Ox-induced activation of ERK and JNK signaling pathway. ANXA3 downregulation reduced Ox resistance in CRC, and treatment with the ERK inhibitor PD098059 or JNK inhibitor SP600125 contributed to this process. These results indicate that silencing ANXA3 could overcome Ox resistance in CRC via the mitogen-activated protein kinase signaling pathway.     

Integrative analysis from multi‐centre studies identifies a function‐derived personalized multi‐gene signature of outcome in colorectal cancer

Colorectal cancer (CRC) is highly heterogeneous leading to variable prognosis and treatment responses. Therefore, it is necessary to explore novel personalized and reproducible prognostic signatures to aid clinical decision‐making. The present study combined large‐scale gene expression profiles and clinical data of 1828 patients with CRC from multi‐centre studies and identified a personalized gene prognostic signature consisting of 46 unique genes (called function‐derived personalized gene signature [FunPGS]) from an integrated statistics and function‐derived perspective. In the meta‐training and multiple independent validation cohorts, the FunPGS effectively discriminated patients with CRC with significantly different prognosis at the individual level and remained as an independent factor upon adjusting for clinical covariates in multivariate analysis. Furthermore, the FunPGS demonstrated superior performance for risk stratification with respect to other recently reported signatures and clinical factors. The complementary value of the molecular signature and clinical factors was further explored, and it was observed that the composite signature called IMCPS greatly improved the predictive performance of survival estimation relative to molecular signatures or clinical factors alone. With further prospective validation in clinical trials, the FunPGS may become a promising and powerful personalized prognostic tool for stratifying patients with CRC in order to achieve an optimal systemic therapy.