Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis

Exploring the potential mechanisms of sorafenib resistance in hepatocellular carcinoma cell lines based on RNA sequencing

BACKGROUND

Exploring the mechanisms underlying sorafenib resistance that arises in hepatocellular carcinoma (HCC) may provide new treatment perspectives.

METHODS

Drug-resistant and drug-sensitive HCC cell lines were constructed from existing HepG2 and Huh7 cell lines, and gene expression profiles were determined. Genes differentially expressed between the resistant and sensitive lines were identified and organized into modules based on weighted gene co-expression network analysis. Pathways and biological processes involving the module genes were explored and validated using gene set enrichment analysis. By analyzing the expression differences of Long non-coding ribonucleic acid (RNAs), microRNAs (miR), circular RNAs, and messenger RNAs between drug-resistant and sensitive cell lines, a gene regulatory network was constructed to reveal the mechanism of sorafenib resistance. In addition, we also analyzed the correlation between the candidate sorafenib resistance gene and the survival of patients with liver cancer.

RESULTS

Our analyses suggested that sorafenib resistance could arise when the circular RNA circ_SPECC1 regulated the microRNA hsa-let-7c-5p, which in turn regulated the cell cycle proteins cyclin-dependent kinase 1 and polo-like kinase 1, as well as interleukin 13 receptor, alpha 1 in the Janus kinase-signal transducer (JAK-STAT) and activator of transcription signaling pathway. Patient survival was associated with miR-18a-z and mitogen-activated protein kinase kinase 4 levels.

CONCLUSIONS

Sorafenib resistance in HCC may involve the circ_SPECC1, hsa-let-7c-5p, cell cycle, and JAK-STAT signaling pathways. These insights may guide future efforts to mitigate or prevent such resistance.

LINC317.5 as a novel biomarker for hypertriglyceridemia in normal glucose metabolism

The global rise in prediabetes and diabetes, with type 2 diabetes (T2DM) being predominant, highlights the association between T2DM and hypertriglyceridemia (HTG). Patients with both abnormal glucose levels and HTG require increased attention due to higher risks of complications and mortality. Therefore, this study aimed to find the key long non-coding RNA (lncRNA) of HTG in the abnormal glucose metabolism patients. We collected blood samples for RNA sequencing experiments and blood samples for validation in population. We have conducted RNA sequencing, weighted gene co-expression network analysis (WGCNA), quantitative real-time polymerase chain reaction (qRT-PCR) in a 82-vs-82-sample-size population and insulin induced HepG2, RNA- Fluorescence in situ hybridization (FISH) and Cell Counting Kit-8 (CCK-8). We also explored lipid metabolism related transcription factor and the related protein expression and processed key lncRNA by both interference expression and overexpression, and the related consequences were rescued by its target mRNA. ENST00000540317.5 (LINC317.5) was lower in HTG with abnormal glucose metabolism and was found in both cytoplasm and nucleus in HepG2, inversely regulating the accumulation of TG and its target mRNA TKFC. Relative expression of peroxisome proliferator-activated receptor alpha (PPARα) and peroxisome proliferator-activated receptor gamma (PPARγ) were decreasing, and SREBP-1c (sterol regulatory element-binding protein-1c) was increasing of the interference expression of LINC317.5. Interference expression of LINC317.5 significantly decreased the protein expression of ACADM and CPT1A, whereas increased the protein expression of FAS and ACC1. TKFC partly reduced the triglyceride (TG) accumulation of LINC317.5. In conclusion, we suggested LINC317.5-TKFC as a key for TG accumulation in the HepG2-insulin resistant (IR). These might provide information of non-invasive biomarkers for the HTG with abnormal glucose.

Analysis of disulfidptosis- and cuproptosis-related LncRNAs in modulating the immune microenvironment and chemosensitivity in colon adenocarcinoma

The main objective was to establish a prognostic model utilising long non-coding RNAs associated with disulfidptosis and cuproptosis. The data for RNA-Sequence and clinicopathological information of Colon adenocarcinoma (COAD) were acquired from The Cancer Genome Atlas. A prognostic model was constructed using Cox regression and the Least Absolute Shrinkage and Selection Operator method. The model's predictive ability was assessed through principal component analysis, Kaplan-Meier analysis, nomogram etc. The ability of identifying the rates of overall survival, infiltration of immune cells, and chemosensitivity was also explored. In vitro experiments were conducted for the validation of differential expression and function of lncRNAs. A disulfidptosis and cuproptosis-related lncRNA prognostic model was constructed. The prognostic model exhibits excellent independent predictive capability for patient outcomes. Based on the authors' model, the high-risk group exhibited higher tumour mutation burdened worse survival. Besides, differences in immune cell infiltration and responsiveness to chemotherapeutic medications exist among patients with different risk scores. Furthermore, aberrant expressions in certain lncRNAs have been validated in HCT116 cells. In particular, FENDRR and SNHG7 could affect the proliferation and migration of colorectal cancer cells. Our study developed a novel prognostic signature, providing valuable insights into prognosis, immune infiltration, and chemosensitivity in COAD patients.

Holistic exploration of CHGA and hsa-miR-137 in colorectal cancer via multi-omic data Integration

Colorectal cancer (CRC) ranks among the most widespread malignancies globally, with early detection significantly influencing prognosis. Employing a systems biology approach, we aimed to unravel the intricate mRNA-miRNA network linked to CRC pathogenesis, potentially yielding diagnostic biomarkers. Through an integrative analysis of microarray, Bulk RNA-seq, and single-cell RNA-seq data, we explored CRC-related transcriptomes comprehensively. Differential gene expression analysis uncovered crucial genes, while Weighted Gene Co-expression Network Analysis (WGCNA) identified key modules closely linked to CRC. Remarkably, CRC manifested its strongest correlation with the turquoise module, signifying its pivotal role. From the cohort of genes showing high Gene Significance (GS) and Module Membership (MM), and Differential Expression Genes (DEGs), we highlighted the downregulated Chromogranin A (CHGA) as a notable hub gene in CRC. This finding was corroborated by the Human Protein Atlas database, which illustrated decreased CHGA expression in CRC tissues. Additionally, CHGA displayed elevated expression in primary versus metastatic cell lines, as evidenced by the CCLE database. Subsequent RT-qPCR validation substantiated the marked downregulation of CHGA in CRC tissues, reinforcing the significance of our differential expression analysis. Analyzing the Space-Time Gut Cell Atlas dataset underscored specific CHGA expression in epithelial cell subclusters, a trend persisting across developmental stages. Furthermore, our scrutiny of colon and small intestine Enteroendocrine cells uncovered distinct CHGA expression patterns, accentuating its role in CRC pathogenesis. Utilizing the WGCNA algorithm and TargetScan database, we validated the downregulation of hsa-miR-137 in CRC, and integrated assessment highlighted its interplay with CHGA. Our findings advocate hsa-miR-137 and CHGA as promising CRC biomarkers, offering valuable insights into diagnosis and prognosis. Despite proteomic analysis yielding no direct correlation, our multifaceted approach contributes comprehensive understanding of CRC's intricate regulatory mechanisms. In conclusion, this study advances hsa-miR-137 and CHGA as promising CRC biomarkers through an integrated analysis of diverse datasets and network interactions.

The Role of Transcription Factors in the Loss of Inter-Chromosomal Co-Expression for Breast Cancer Subtypes

Breast cancer encompasses a diverse array of subtypes, each exhibiting distinct clinical characteristics and treatment responses. Unraveling the underlying regulatory mechanisms that govern gene expression patterns in these subtypes is essential for advancing our understanding of breast cancer biology. Gene co-expression networks (GCNs) help us identify groups of genes that work in coordination. Previous research has revealed a marked reduction in the interaction of genes located on different chromosomes within GCNs for breast cancer, as well as for lung, kidney, and hematopoietic cancers. However, the reasons behind why genes on the same chromosome often co-express remain unclear. In this study, we investigate the role of transcription factors in shaping gene co-expression networks within the four main breast cancer subtypes: Luminal A, Luminal B, HER2+, and Basal, along with normal breast tissue. We identify communities within each GCN and calculate the transcription factors that may regulate these communities, comparing the results across different phenotypes. Our findings indicate that, in general, regulatory behavior is to a large extent similar among breast cancer molecular subtypes and even in healthy networks. This suggests that transcription factor motif usage does not fully determine long-range co-expression patterns. Specific transcription factor motifs, such as CCGGAAG, appear frequently across all phenotypes, even involving multiple highly connected transcription factors. Additionally, certain transcription factors exhibit unique actions in specific subtypes but with limited influence. Our research demonstrates that the loss of inter-chromosomal co-expression is not solely attributable to transcription factor regulation. Although the exact mechanism responsible for this phenomenon remains elusive, this work contributes to a better understanding of gene expression regulatory programs in breast cancer.

Tumor cell-derived exosomes mediating hsa_circ_0001739/lncRNA AC159540.1 facilitate liver metastasis in colorectal cancer

BACKGROUND

The current study probed into how tumor cell-derived exosomes (Exos) mediated hsa_circ_0001739/lncRNA AC159540.1 to manipulate microRNA (miR)-218-5p/FTO-N6-methyladenosine (m6A)/MYC signal axis in liver metastasis in colorectal cancer (CRC).

METHODS

hsa_circ_0001739 and lncRNA AC159540.1 were identified as the upstream regulator of miR-218-5p using ENCORI and LncBase databases. Expression patterns of miR-218-5p, hsa_circ_0001739, lncRNA AC159540.1, FTO, and MYC were detected, accompanied by loss-and-gain-of function assays to examine their effects on CRC cell biological functions. SW480 cells-derived Exos were purified, followed by in vitro studies to uncover the effect of hsa_circ_0001739/lncRNA AC159540.

RESULTS

miR-218-5p was downregulated while hsa_circ_0001739/lncRNA AC159540.1 was upregulated in CRC tissues and cells. Silencing of hsa_circ_0001739/lncRNA AC159540.1 restrained the malignant phenotypes of CRC cells. Exos-mediated hsa_circ_0001739/lncRNA AC159540.1 competitively inhibited miR-218-5p to elevate FTO and MYC. The inducing role of Exos-mediated hsa_circ_0001739/lncRNA AC159540.1 in CRC was also validated in vivo.

CONCLUSION

Conclusively, Exos-mediated circ_0001739/lncRNA AC159540.1 regulatory network is critical for CRC, offering a theoretical basis for CRC treatment.

Identification of genes associated with abiotic stress tolerance in sweetpotato using weighted gene co-expression network analysis

Sweetpotato, Ipomoea batatas (L.), a key food security crop, is negatively impacted by heat, drought, and salinity stress. The orange-fleshed sweetpotato cultivar "Beauregard" was exposed to heat, salt, and drought treatments for 24 and 48 h to identify genes responding to each stress condition in leaves. Analysis revealed both common (35 up regulated, 259 down regulated genes in the three stress conditions) and unique sets of up regulated (1337 genes by drought, 516 genes by heat, and 97 genes by salt stress) and down regulated (2445 genes by drought, 678 genes by heat, and 204 genes by salt stress) differentially expressed genes (DEGs) suggesting common, yet stress-specific transcriptional responses to these three abiotic stressors. Gene Ontology analysis of down regulated DEGs common to both heat and salt stress revealed enrichment of terms associated with "cell population proliferation" suggestive of an impact on the cell cycle by the two stress conditions. To identify shared and unique gene co-expression networks under multiple abiotic stress conditions, weighted gene co-expression network analysis was performed using gene expression profiles from heat, salt, and drought stress treated 'Beauregard' leaves yielding 18 co-expression modules. One module was enriched for "response to water deprivation," "response to abscisic acid," and "nitrate transport" indicating synergetic crosstalk between nitrogen, water, and phytohormones with genes encoding osmotin, cell expansion, and cell wall modification proteins present as key hub genes in this drought-associated module. This research lays the groundwork for exploring to a further degree, mechanisms for abiotic stress tolerance in sweetpotato.

A WGCNA-based cancer-associated fibroblast risk signature in colorectal cancer for prognosis and immunotherapy response

Background

Cancer-associated fibroblasts (CAFs) are notably involved in colorectal cancer (CRC) tumorigenesis, progression, and treatment failure. In this article, we report the in silico development of a CAF-related prognostic signature for CRC.

Methods

We separately downloaded CRC transcription data from The Cancer Genome Atlas and the Gene Expression Omnibus database. Deconvolution algorithms, including Estimating the Proportions of Immune and Cancer Cells and the Microenvironment Cell Population-counter, were used to calculate CAF abundance, while the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression algorithm was used to calculate the stromal score. Weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator algorithm were used to identify CAF-related genes and prognostic signatures.

Results

We identified a three-gene, prognostic, CAF-related signature and defined risk groups based on the Riskscores. Multidimensional validations were applied to evaluate the robustness of the signature and its correlation with clinical parameters. We utilized Tumor Immune Dysfunction and Exclusion (TIDE) and oncoPredict algorithms to predict therapy responses and found that patients in low-risk groups are more sensitive to immunotherapy and chemotherapy drugs such as 5-fluorouracil and oxaliplatin. Finally, we used the Cancer Cell Line Encyclopedia and Human Protein Atlas databases to evaluate the mRNA and protein levels encoded by the signature genes.

Conclusions

This novel CAF-related three-gene signature is expected to become a potential prognostic biomarker in CRC and predict chemotherapy and immunotherapy responses. It may be of considerable value for studying the tumor microenvironment in CRC.

Novel insights on perils and promises of miRNA in understanding colon cancer metastasis and progression

Colorectal cancer (CRC) is the third highest frequent malignancy and ultimate critical source of cancer-associated mortality around the world. Regardless of latest advances in molecular and surgical targeted medicines that have increased remedial effects in CRC patients, the 5-year mortality rate for CRC patients remains dismally low. Evidence suggests that microRNAs (miRNAs) execute an essential part in the development and spread of CRC. The miRNAs are a type of short non-coding RNA that exhibited to control the appearance of tumor suppressor genes and oncogenes. miRNA expression profiling is already being utilized in clinical practice as analytical and prognostic biomarkers to evaluate cancer patients' tumor genesis, advancement, and counteraction to drugs. By modulating their target genes, dysregulated miRNAs are linked to malignant characteristics (e.g., improved proliferative and invasive capabilities, cell cycle aberration, evasion of apoptosis, and promotion of angiogenesis). This review presents an updated summary of circulatory miRNAs, tumor-suppressive and oncogenic miRNAs, and the potential reasons for dysregulated miRNAs in CRC. Further we will explore the critical role of miRNAs in CRC drug resistance.

The role of miRNA in colorectal cancer diagnosis: A pilot study

Despite recent advances in diagnosis and treatment, colorectal cancer (CRC) remains the third most common cancer worldwide, and has both a poor prognosis and a high recurrence rate, thus indicating the need for new, sensitive and specific biomarkers. MicroRNAs (miRNAs/miRs) are important regulators of gene expression, which are involved in numerous biological processes implicated in tumorigenesis. The objective of the present study was to investigate the expression of miRNAs in plasma and tissue samples from patients with CRC, and to examine their potential as CRC biomarkers. Using reverse transcription-quantitative PCR, it was revealed that miR-29a, miR-101, miR-125b, miR-146a and miR-155 were dysregulated in the formalin-fixed paraffin-embedded tissues of patients with CRC, compared with the surrounding healthy tissue, and these miRNAs were associated with several pathological features of the tumor. Bioinformatics analysis of overlapping target genes identified AGE-RAGE signaling as a putative joint regulatory pathway. miR-146a was also upregulated in the plasma of patients with CRC, compared with the healthy control group, and had a fair discriminatory power (area under the curve, 0.7006), with 66.7% sensitivity and 77.8% specificity. To the best of our knowledge, this distinct five-miRNA deregulation pattern in tumor tissue, and upregulation of plasma miR-146a, were shown for the first time in patients with CRC; however, studies on larger patient cohorts are warranted to confirm their potential to be used as CRC diagnostic biomarkers.

Prognostic Value and Immunological Role of P4HA3 in Colon Adenocarcinoma

Purpose

Prolyl 4-hydroxylase subunit alpha 3 (P4HA3) has been proven to participate in the occurrence and development of multiple cancers. However, the functional role of P4HA3 in the tumor immune microenvironment (TIME) of colon adenocarcinoma (COAD) and the prognosis of COAD patients has not been clarified. This study aimed to elucidate the immunological role and prognostic value of P4HA3 in COAD.

Methods

P4HA3 expression in COAD tissues was analyzed via experiments and a bioinformatics algorithm. Based on the COAD patients in The Cancer Genome Atlas database, we comprehensively evaluated whether the expression levels of P4HA3 affected clinical prognosis, TIME, and immunotherapy of COAD using the R platforms and several public databases, including GEPIA, TIMER, TISIDB, and TCIA.

Results

The results of the pan-cancer analysis indicated that P4HA3 expression was significantly different in most tumor tissues compared with normal tissues. P4HA3 was overexpressed in COAD tissues, and overexpression of P4HA3 was associated with a worse overall survival and a shorted progression-free interval in COAD patients. The expression of P4HA3 was positively correlated with pathological stage, T stage, N stage, perineural infiltration, and lymphatic infiltration. There were significant correlations of P4HA3 expression levels with immune cell infiltration and their makers, as well as immunomodulators, chemokines, and microsatellite status. Moreover, overexpression of P4HA3 was associated with a lower response rate to immunotherapy in the IMvigor210 cohort.

Conclusion

Overexpression of P4HA3 is closely related to the poor prognosis of COAD patients, and P4HA3 is a potential target for immunotherapy in COAD patients.

Optimisation Models for Pathway Activity Inference in Cancer

BACKGROUND

With advances in high-throughput technologies, there has been an enormous increase in data related to profiling the activity of molecules in disease. While such data provide more comprehensive information on cellular actions, their large volume and complexity pose difficulty in accurate classification of disease phenotypes. Therefore, novel modelling methods that can improve accuracy while offering interpretable means of analysis are required. Biological pathways can be used to incorporate a priori knowledge of biological interactions to decrease data dimensionality and increase the biological interpretability of machine learning models.

METHODOLOGY

A mathematical optimisation model is proposed for pathway activity inference towards precise disease phenotype prediction and is applied to RNA-Seq datasets. The model is based on mixed-integer linear programming (MILP) mathematical optimisation principles and infers pathway activity as the linear combination of pathway member gene expression, multiplying expression values with model-determined gene weights that are optimised to maximise discrimination of phenotype classes and minimise incorrect sample allocation.

RESULTS

The model is evaluated on the transcriptome of breast and colorectal cancer, and exhibits solution results of good optimality as well as good prediction performance on related cancer subtypes. Two baseline pathway activity inference methods and three advanced methods are used for comparison. Sample prediction accuracy, robustness against noise expression data, and survival analysis suggest competitive prediction performance of our model while providing interpretability and insight on key pathways and genes. Overall, our work demonstrates that the flexible nature of mathematical programming lends itself well to developing efficient computational strategies for pathway activity inference and disease subtype prediction.

Identification of Key Modules and Candidate Genes for Powdery Mildew Resistance of Wheat-Agropyron cristatum Translocation Line WAT-2020-17-6 by WGCNA

As one of the serious diseases of wheat, powdery mildew (Blumeria graminis f. sp. tritici) is a long-term threat to wheat production. Therefore, it is of great significance to explore new powdery mildew-resistant genes for breeding. The wild relative species of wheat provide gene resources for resistance to powdery mildew breeding. Agropyron cristatum (2n = 4x = 28, genomes PPPP) is an important wild relative of wheat, carrying excellent genes for high yield, disease resistance, and stress resistance, which can be used for wheat improvement. To understand the molecular mechanism of powdery mildew resistance in the wheat-A. cristatum translocation line WAT2020-17-6, transcriptome sequencing was performed, and the resistance genes were analyzed by weighted gene co-expression network analysis (WGCNA). In the results, 42,845 differentially expressed genes were identified and divided into 18 modules, of which six modules were highly correlated with powdery mildew resistance. Gene ontology (GO) enrichment analysis showed that the six interested modules related to powdery mildew resistance were significantly enriched in N-methyltransferase activity, autophagy, mRNA splicing via spliceosome, chloroplast envelope, and AMP binding. The candidate hub genes of the interested modules were further identified, and their regulatory relationships were analyzed based on co-expression data. The temporal expression pattern of the 12 hub genes was verified within 96 h after powdery mildew inoculation by RT-PCR assay. In this study, we preliminarily explained the resistance mechanism of the wheat-A. cristatum translocation lines and obtained the hub candidate genes, which laid a foundation in the exploration of resistance genes in A. cristatum for powdery mildew-resistant breeding in wheat.

Weighted Gene Co-Expression Network Analysis of Oxymatrine in Psoriasis Treatment

Purpose

Psoriasis is a common, chronic, inflammatory, recurrent, immune-mediated skin disease. Oxymatrine is effective for treating moderate and severe psoriasis. Here, transcriptional changes in skin lesions before and after oxymatrine treatment of patients with psoriasis were identified using full-length transcriptome analysis and then compared with those of normal skin tissues.

Patients and Methods

Co-expression modules were constructed by combining the psoriasis area and severity index (PASI) score with weighted gene co-expression network analysis to explore the action mechanism of oxymatrine in improving clinical PASI. The expression of selected genes was verified using immunohistochemistry, quantitative real-time PCR, and Western blotting.

Results

Kyoto Encyclopedia of Gene and Genome pathway analysis revealed that oxymatrine treatment reversed the abnormal pathways, with an improvement in lesions and a reduction in PASI scores. Gene Ontology (GO) analysis revealed that oxymatrine treatment led to altered GO terms being regulated with a decrease in the PASI score in patients. Therefore, oxymatrine treatment may improve the skin barrier, differentiation of keratinocytes, and alleviate abnormality of organelles such as desmosomes. Protein-protein interaction network interaction analysis revealed that the top five hub genes among many interrelated genes were CNFN, S100A8, SPRR2A, SPRR2D, and SPRR2E, associated with the epidermal differentiation complex (EDC). EDC regulates keratinocyte differentiation. This result indicates that oxymatrine treatment can restore keratinocyte differentiation by regulating the expression of EDC-related genes.

Conclusion

Oxymatrine can improve erythema, scales, and other clinical symptoms of patients with psoriasis by regulating EDC-related genes and multiple pathways, thereby promoting the repair of epithelial tissue and maintaining the dynamic balance of skin keratosis.

Correlation Analysis of Gene and Radiomic Features in Colorectal Cancer Liver Metastases

Colorectal cancer liver metastasis (CRLM) was one of the cancers with high mortality. Clinically, the target point was determined by invasive detection, which increased the suffering of patients and the cost of treatment. If the target point was found through the relationship between early radiomic information and genetic information, it was expected to assist doctors in diagnosing disease, formulating treatment plans, and reducing the pain and burden of patients. In this study, gene coexpression analysis and hub gene mining were first performed on the gene data; secondly, quantitative radiomic features were extracted from CT-enhanced radiomic data to obtain features highly correlated with CRLM; and finally, we analyzed the relationship between gene features and radiomic feature correlations by establishing a link between early radiomic features and gene sequencing and finding highly correlated expressions. This experiment demonstrated that radiomic features could be used to mine gene attributes. Based on the four previously identified genes (NRAS, KRAS, BRAF, and PIK3CA), we identified two novel genes, MAPK1 and STAT1, highly associated with CRLM. There were specific correlations between these 6 genes and radiomic features (shape_elongation, glcm, glszm, firstorder_10percentile, gradient, exponent_firstorder_Range, and gradient_glszm_SmallAreaLowGrayLevel). Therefore, this paper established the correlation between radiomic features and genes, and through radiomic features, we could find the genes associated with them, which was expected to achieve noninvasive prediction of liver metastasis.

Development of a 7-miRNA prognostic signature for patients with bladder cancer

BACKGROUND

Bladder carcinoma (BC) represents one of the most prevalent malignant cancers, while predicting its clinical outcomes using traditional indicators is difficult. This study aimed to develop a miRNA signature for the prognostic prediction of patients with BC.

MATERIALS AND METHODS

MiRNAs that expressed differentially were identified between 413 BC and 19 non-tumor patients, whose prognostic values were evaluated using univariate and multivariate Cox regression analyses. The independent prognostic factors were screened out and were used to establish a signature. The risk score of the signature was calculated. Receiver operating characteristic (ROC) curves and Kaplan-Meier curves were used to verify the predictive performance of the miRNA signature and the risk score. A nomogram was constructed which integrated with the miRNA signature and clinical parameters. Experiments were performed.

RESULTS

7 prognosis related miRNAs were selected as independent risk factors, and a 7-miRNA signature was constructed, with an area under ROC (AUC) of 0.721. The 7-miRNA-signature based risk score acts as an independent prognostic factor, with satisfactory predictive performance (AUC = 0.744). Increased miR-337-3p expressions were detected in tumor samples and BC cell lines than in non-tumorigenic tissues and cell lines. Experiments suggested that miR-337-3p induces the proliferation, migration, and invasion of BC cells.

CONCLUSION

The constructed 7-miRNA signature is a promising biomarker for predicting the prognosis of patients with BC, and miR-337-3p may act as a candidate therapeutic target in BC treatments.

Identification of Four Hub Genes as Promising Biomarkers for the Evaluation of Ovarian Cancer Prognosis

Ovarian malignant growth is perhaps the most lethal disease in females. There are no exact biomarkers for the early determination of ovarian disease. We obtained a total of 12 gene clusters through WGCNA and studied the azure gene modules related to the lymphatic infiltration of ovarian cancer further. What’s more, endurance investigation was utilized to decide three qualities connected with the by and large and infection-free endurance in ovarian disease patients, including GOGA8B [Hazard Ratio (HR)=1.53, p=0.037, 95% CI: 1.05–2.24], LRRC26 (HR=0.7, p =0.045, 95% CI: 0.48–1.01), and CCDC114 (HR = 0.72, p = 0.042, 95% CI: 0.53–0.98). A prognostic risk score model was built to anticipate the endurance pace of patients at 1, 3, and 5 years, individually. The area under the receiver operating characteristic (ROC) curve (AUC) of the training set was 0.749, 0.764, and 0.784, respectively; the test AUC was 0.601, 0.623, and 0.709. Our review gives a point of view on significant possible biomarkers for the determination, anticipation, and therapy of ovarian malignant growth.

A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective

Molecular and sequencing technologies have been successfully used in decoding biological mechanisms of various diseases. As revealed by many novel discoveries, the role of non-coding RNAs (ncRNAs) in understanding disease mechanisms is becoming increasingly important. Since ncRNAs primarily act as regulators of transcription, associating ncRNAs with diseases involves multiple inference steps. Leveraging the fast-accumulating high-throughput screening results, a number of computational models predicting ncRNA-disease associations have been developed. These tools suggest novel disease-related biomarkers or therapeutic targetable ncRNAs, contributing to the realization of precision medicine. In this survey, we first introduce the biological roles of different ncRNAs and summarize the databases containing ncRNA-disease associations. Then, we suggest a new trend in recent computational prediction of ncRNA-disease association, which is the mode of action (MoA) network perspective. This perspective includes integrating ncRNAs with mRNA, pathway and phenotype information. In the next section, we describe computational methodologies widely used in this research domain. Existing computational studies are then summarized in terms of their coverage of the MoA network. Lastly, we discuss the potential applications and future roles of the MoA network in terms of integrating biological mechanisms for ncRNA-disease associations.

Construction of CeRNA regulatory network based on WGCNA reveals diagnosis biomarkers for colorectal cancer

Background

Colorectal cancer is the third most common cause of death among cancers in the world. Although improvements in various treatments have greatly improved the survival time of colorectal cancer patients, since colorectal cancer is often at an advanced stage when diagnosed, the prognosis of patients is still very poor. Since the ceRNA regulatory network was proposed in 2011, it has greatly promoted the study of the molecular mechanism of colorectal cancer occurrence and development.

Objective

Exploring the new molecular mechanism of colorectal cancer occurrence and development and providing new targets for the diagnosis and treatment of colorectal cancer.

Method

We analyzed the RNA-seq data of CRC from TCGA, such as differential expression analysis, weighted gene co-expression network analysis (WGCNA) and construction of ceRNA regulatory network.

Results

We constructed a ceRNA network using RNA-seq data of CRC from TCGA. In the ceRNA regulatory network, 19 hub molecules with significant prognostic effects were ultimately identified, including 8 lncRNAs, 2 mRNAs and 9 miRNAs. These hub molecules constitute the lncRNA-miRNA, miRNA-mRNA or lncRNA-miRNA-mRNA axis.

Conclusion

In this article, some new ceRNA regulatory axes have been discovered, which may potentially disclose new molecular mechanisms for the occurrence and development of colorectal cancer, thereby providing an important blueprint for the treatment and prognosis assessment of CRC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10054-z.

Application of miRNA Biomarkers in Predicting Overall Survival Outcomes for Lung Adenocarcinoma

BACKGROUND

With the development of research, the importance of microRNAs (miRNAs) in the occurrence, metastasis, and prognosis of lung adenocarcinoma (LUAD) has attracted extensive attention. This study is aimed at predicting overall survival (OS) results through bioinformatics to identify novel miRNA biomarkers and hub genes.

MATERIALS AND METHODS

The data of LUAD-related miRNA and mRNA samples was downloaded from The Cancer Genome Atlas (TCGA) database. Upon screening and pretreatment of initial data, TCGA data were analyzed using R platform and a series of analytical tools to identify biomarkers with high specificity and sensitivity.

RESULTS

7 miRNAs and 13 hub genes that had strong relation to the overall surviving status were identified in patients with LUAD. The expression of seven miRNAs (hsa-miR-19a-3p, hsa-miR-126-5p, hsa-miR-556-3p, hsa-miR-671-5p, hsa-miR-937-3p, hsa-miR-4664-3p, and hsa-miR-4746-5p) could apparently improve the OS rate of patient with LUAD. The 13 hub genes, namely, CCT6A, CDK5R1, CEP55, DNAJB4, EGLN3, HDGF, HOXC8, LIMD1, MKI67, PCP4L1, PPIL1, SCAI, and STK32A, showed a correlation with the OS status.

CONCLUSION

7 miRNAs were identified as novel biomarkers for the prognosis of patients with LUAD. This study offered a deeper comprehension of LUAD treatment and prognosis from the molecular level and helped enhance the understanding of the pathogenesis and potential molecular events of LUAD.

Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis

Background

Thyroid eye disease (TED) is the most common orbital pathology that occurs in up to 50% of patients with Graves’ disease. Herein, we aimed at discovering the possible hub genes and pathways involved in TED based on bioinformatical approaches.

Results

The GSE105149 and GSE58331 datasets were downloaded from the Gene Expression Omnibus (GEO) database and merged for identifying TED-associated modules by weighted gene coexpression network analysis (WGCNA) and local maximal quasi-clique merger (lmQCM) analysis. EdgeR was run to screen differentially expressed genes (DEGs). Transcription factor (TF), microRNA (miR) and drug prediction analyses were performed using ToppGene suite. Function enrichment analysis was used to investigate the biological function of genes. Protein–protein interaction (PPI) analysis was performed based on the intersection between the list of genes obtained by WGCNA, lmQCM and DEGs, and hub genes were identified using the MCODE plugin. Based on the overlap of 497 genes retrieved from the different approaches, a robust TED coexpression network was constructed and 11 genes (ATP6V1A, PTGES3, PSMD12, PSMA4, METAP2, DNAJA1, PSMA1, UBQLN1, CCT2, VBP1 and NAA50) were identified as hub genes. Key TFs regulating genes in the TED-associated coexpression network, including NFRKB, ZNF711, ZNF407 and MORC2, and miRs including hsa-miR-144, hsa-miR-3662, hsa-miR-12136 and hsa-miR-3646, were identified. Genes in the coexpression network were enriched in the biological processes including proteasomal protein catabolic process and proteasome-mediated ubiquitin-dependent protein catabolic process and the pathways of endocytosis and ubiquitin-mediated proteolysis. Drugs perturbing genes in the coexpression network were also predicted and included enzyme inhibitors, chlorodiphenyl and finasteride.

Conclusions

For the first time, TED-associated coexpression network was constructed and key genes and their functions, as well as TFs, miRs and drugs, were predicted. The results of the present work may be relevant in the treatment and diagnosis of TED and may boost molecular studies regarding TED.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-022-00412-0.

THUMPD3-AS1 facilitates cell growth and aggressiveness by the miR-218-5p/SKAP1 axis in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a malignant cancer with a high mortality. Accumulating studies have revealed that mRNAs involved in ceRNA (competing endogenous RNA) network are implicated in the tumorigenesis and development of CRC. Here, we aimed to elucidate the ceRNA network involving Src kinase associated phosphoprotein 1 (SKAP1) in the biological characteristics of CRC.

METHODS

Expression levels of genes in colon adenocarcinoma (COAD) samples and prognosis of COAD patients were predicted using publicly available online tool. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), clony formation and Transwell assays were conducted to test the biological functions of SKAP1 and THUMPD3 antisense RNA 1 (THUMPD3-AS1) in CRC cells. Western blot was used to measure the protein levels of SKAP1. Gene expression in CRC cells was detected by reverse transcription quantitative polymerase chain reaction (RT-qPCR). The interaction between miR-218-5p and THUMPD3-AS1 (or SKAP1) was verified by RNA pulldown and luciferase reporter assays.

RESULTS

SKAP1 was upregulated in COAD tissues and CRC cells and it reflected a poor prognosis in patients with COAD. SKAP1 knockdown inhibited CRC (HT-29 and HCT-116) cell proliferation, migration and invasion. Mechanistically, THUMPD3-AS1 acted as a ceRNA to sponge miR-218-5p and subsequently upregulated SKAP1 expression in CRC cells. SKAP1 overexpression reversed the suppressive effect of THUMPD3-AS1 knockdown on proliferation, migration and invision of CRC cells.

CONCLUSIONS

THUMPD3-AS1 promotes CRC cell growth and aggressiveness by regulating the miR-218-5p/SKAP1 axis.

Screening and Biological Function Analysis of miRNA and mRNA Related to Lung Adenocarcinoma Based on Bioinformatics Technology

Objective. To screen the differentially expressed miRNAs (DEMs) and the differentially expressed gene mRNAs (DEGs) in lung adenocarcinoma (LUAD) from the TCGA database and to explore the relationship between miRNAs and the prognosis of lung adenocarcinoma and their biological functions. Methods. The RNA-seq and miRNA-seq data of lung adenocarcinoma samples were downloaded from the TCGA database for analysis, and the R program was used to screen for differentially expressed miRNAs and mRNAs. Then, the molecular functions, biological processes, cellular components, and signaling pathways involved in the occurrence and development of LUAD were analyzed using the functional accumulation analysis software of GSEA. The relationship between the integrated differentially expressed RNAs was analyzed by miRcode, TargetScan, and miRTarbase databases, and the miRNA-mRNA network was constructed. Result. A total of 516 differentially expressed miRNAs and 5464 differentially expressed mRNAs were identified in LUAD. The GSEA enrichment analysis showed that miRNAs and mRNAs were mainly enriched in extracellular structure organization, external encapsulating structure organization, extracellular matrix organization, and gated channel activity. They were mainly involved in neuroactive ligand-receptor interaction signaling pathway. Some miRNAs and mRNAs in clustering modules were found to be associated with the prognosis of LUAD. Four targeting networks consisting of 22 miRNAs and 531 mRNAs were constructed. Conclusion. The miRNA and mRNA related to the prognosis of LUAD were screened out, which provided a valuable preliminary basis for the follow-upin-depth clinical research and basic experimental research of LUAD.

Identification of Differentially Expressed Genes and Prediction of Expression Regulation Networks in Dysfunctional Endothelium

The detection of early coronary atherosclerosis (ECA) is still a challenge and the mechanism of endothelial dysfunction remains unclear. In the present study, we aimed to identify differentially expressed genes (DEGs) and the regulatory network of miRNAs as well as TFs in dysfunctional endothelium to elucidate the possible pathogenesis of ECA and find new potential markers. The GSE132651 data set of the GEO database was used for the bioinformatic analysis. Principal component analysis (PCA), the identification of DEGs, correlation analysis between significant DEGs, the prediction of regulatory networks of miRNA and transcription factors (TFs), the validation of the selected significant DEGs, and the receiver operating characteristic (ROC) curve analysis as well as area under the curve (AUC) values were performed. We identified ten genes with significantly upregulated signatures and thirteen genes with significantly downregulated signals. Following this, we found twenty-two miRNAs regulating two or more DEGs based on the miRNA–target gene regulatory network. TFs with targets ≥ 10 were E2F1, RBPJ, SSX3, MMS19, POU3F3, HOXB5, and KLF4. Finally, three significant DEGs (TOX, RasGRP3, TSPAN13) were selected to perform validation experiments. Our study identified TOX, RasGRP3, and TSPAN13 in dysfunctional endothelium and provided potential biomarkers as well as new insights into the possible molecular mechanisms of ECA.

The Role of DACT Family Members in Tumorigenesis and Tumor Progression

Disheveled-associated antagonist of β-catenin (DACT), which ubiquitously expressed in human tissue, is critical for regulating cell proliferation and several developmental processes in different cellular contexts. In addition, DACT is essential for some other cellular processes, such as cell apoptosis, migration and differentiation. Given the importance of DACT in these cellular processes, many scientists are gradually interested in studying the role of DACT in tumorigenesis and cancer progression. This review article focuses on the latest research regarding the essential functions and potential DACT mechanisms in the occurrence and progression of tumors. Our study indicates that DACT may act as a tumor biomarker for cancer diagnosis and prognosis, as well as a promising therapeutic target in cancers.

A Novel Pyroptosis-Related Gene Signature for Predicting the Prognosis and the Associated Immune Infiltration in Colon Adenocarcinoma

Background

Pyroptosis has been demonstrated to be an inflammatory form of programmed cell death recently. However, the expression of pyroptosis-related genes (PRGs) in colon adenocarcinoma (COAD) and their correlations with prognosis remain unclear.

Methods

Data of COAD patients were obtained from The Cancer Genome Atlas (TCGA) database to screen differentially expressed genes (DEGs). Univariate Cox regression analysis and the LASSO Cox regression analysis were applied to construct a gene signature. All COAD patients in TCGA cohort were separated into low-risk subgroup or high-risk subgroup via the risk score. Kaplan–Meier survival analysis and receiver operator characteristic (ROC) curves were adopted to assess its prognostic efficiency. COAD data from the GSE17537 datasets was used for validation. A prognostic nomogram was established to predict individual survival. The correlation between PRGs and immune cell infiltration in COAD was verified based on TIMER database. CIBERSORT analysis was utilized on risk subgroup as defined by model. The protein and mRNA expression level of PRGs were verified by HPA database and qPCR.

Results

A total of 51 differentially expressed PRGs were identified in TCGA cohort. Through univariate Cox regression analysis and LASSO Cox regression analysis, a prognostic model containing 7 PRGs was constructed. Kaplan–Meier survival analysis indicated that patients in the low-risk subgroup exhibited better prognosis compared to those in the high-risk subgroup. Additionally, the area under the curve (AUC) of ROC is 0.60, 0.63, and 0.73 for 1-, 3-, and 5-year survival in TCGA cohort and 0.63, 0.65, and 0.64 in validation set. TIMER database showed a strong correlation between 7 PRGs and tumor microenvironment in COAD. Moreover, CIBERSORT showed significant differences in the infiltration of plasma cells, M0 macrophages, resting dendritic cells, and eosinophils between low-risk subgroup and high-risk subgroup. HPA database showed that protein expression level of SDHB, GZMA, BTK, EEF2K, and NR1H2 was higher in normal tissues. And the transcriptional level of CASP5, BTK, SDHB, GZMA, and RIPK3 was high in normal tissues.

Conclusions

Our study identified a novel PRGs signature that could be used to predict the prognosis of COAD patients, which might provide a new therapeutic target for the treatment of COAD patients.

Identification of Immune-Related Hub Genes in Thymoma: Defects in CD247 and Characteristics of Paraneoplastic Syndrome

Background: Thymomas (Ts) and thymic carcinomas (TCs) are rare primary tumors of the mediastinum. Paraneoplastic syndrome (PNS) is an important feature of thymoma, which presents great challenges to clinicians.

Methods: The present study uses the weighted gene co-expression network analysis (WGCNA) to identify possible immunologic mechanisms of thymoma. RNA sequencing data from thymoma samples were downloaded from the TCGA. Core genes were taken from the module that is closely related to the WHO’s stage of classification. Enhanced analysis using the online database “Metascape” and an overall survival (OS) analysis were carried out via the Kaplan–Meier method. The hub genes were obtained from the protein–protein interaction (PPI) network. In addition, we jointly analyzed multiple sets of PNS data related to thymomas from other sources to verify the correlation between thymomas and PNS. The impact of hub genes on the prognosis of PNS was evaluated via the ROC curve, with simultaneous analysis of immune infiltration by CIBERSORT.

Findings: The 14 immune hub genes closely related to thymomas were found to be jointly involved in the T-cell receptor signaling pathway. Compared to the normal thymus and type B1/B2 thymoma, there is a lower number of T-cells in type A/B3 thymoma and thymic carcinoma. The expression of genes related to the T-cell receptor signaling pathway appeared defective. The low expression of CD247 and the decrease in the number of mature T-cells are common features among thymomas, specific pulmonary fibrosis, rheumatoid arthritis, and systemic lupus erythematosus.

DNMBP-AS1 Regulates NHLRC3 Expression by Sponging miR-93-5p/17-5p to Inhibit Colon Cancer Progression

Long non-coding RNAs (LncRNAs) act as competing endogenous RNAs (ceRNAs) in colon cancer (CC) progression, via binding microRNAs (miRNAs) to regulate the expression of corresponding messenger RNAs (mRNAs). This article aims to explore the detailed molecular mechanism of ceRNA in CC. Top mad 5000 lncRNAs and top mad 5000 mRNAs were used to perform weighted gene co-expression network analysis (WGCNA), and key modules were selected. We used 405 lncRNAs in the red module and 145 mRNAs in the purple module to build the original ceRNA network by online databases. The original ceRNA network included 50 target lncRNAs, 41 target miRNAs, and 34 target mRNAs. Fifty target lncRNAs were used to establish a prognostic risk model by univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. LncRNAs in the risk model were used to build the secondary ceRNA network, which contained 9 lncRNAs in the risk model, 35 miRNAs, and 29 mRNAs. Survival analyses of 29 mRNAs in the secondary ceRNA network have shown HOXA10 and NHLRC3 were identified as crucial prognostic factors. Finally, we constructed the last ceRNA network including 5 lncRNAs in the risk model, 8 miRNAs, and 2 mRNAs related to prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR) results revealed that DNMBP-AS1 and FAM87A were down-regulated in CC cells and tissues. Function assays showed that over-expression of DNMBP-AS1 and FAM87A inhibited CC cells proliferation and migration. Mechanism study showed that DNMBP-AS1 served as miR-93-5p/17-5p sponges and relieved the suppression effect of miR-93-5p/17-5p on their target NHLRC3. Our study suggested that DNMBP-AS1 inhibited the progression of colon cancer through the miR-93-5p/17-5p/NHLRC3 axis, which could be potential therapeutic targets for CC.

Regulatory mechanism of miR-20a-5p expression in Cancer

MicroRNAs(miRNAs) are non-coding single-stranded RNA molecules encoded by endogenous genes with a length of about 22 nucleotides. The dysregulation of miRNAs has been proven to be one of the vital causes of cancer, which makes them a biomarker for cancer diagnosis and prognosis. Compared with surgery and chemotherapy, nucleic acid therapy targeting specific miRNAs is a promising candidate for cancer treatment. miR-20a-5p plays an anticancer role in high-incidence human cancers such as cervical cancer, breast cancer and leukemia, which is of great importance in the diagnosis of cancers. The up-regulation and down-regulation of miR-20a-5p offers a possible breakthrough for the treatment of cancers. In this paper, we aim to investigate the functional significance of miR-20a-5p in different cancers, reviewing the expression differences of miR-20a-5p in cancer, while systematically summarizing the changes of circRNA-miR-20a-5p networks, and probe how it promotes messenger RNA (mRNA) degradation or inhibits mRNA translation to regulate downstream gene expression. We've also summarized the biogenesis mechanism of miRNAs, and emphasized its role in cell proliferation, cell apoptosis and cell migration. On this basis, we believe that miR-20a-5p is a promising and effective marker for cancer diagnosis, prognosis and treatment.

Artificial intelligence in cancer target identification and drug discovery

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover drugs. First, we describe the scope of artificial intelligence biology analysis for novel anticancer target investigations. Second, we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence algorithms. Finally, we showcase the applications of artificial intelligence approaches in cancer target identification and drug discovery. Taken together, the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer, thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.

Identified lncRNAs functional modules and genes in prediabetes with hypertriglyceridemia by weighted gene co-expression network analysis

Background

Hypertriglyceridemia (HTG) is one of the most important comorbidities in abnormal glucose patients. The aim of this study was to identify lncRNAs functional modules and hub genes related to triglyceride (TG) in prediabetes.

Methods

The study included 12 prediabetic patients: 6 participants with HTG and 6 participants with normal triglyceride (NTG). Whole peripheral blood RNA sequencing was performed for these samples to establish a lncRNA library. WGCNA, KEGG pathways analysis and the PPI network were used to construct co‐expression network, to obtain modules related to blood glucose, and to detect key lncRNAs. Meanwhile, GEO database and qRT-PCR were used to validate above key lncRNAs.

Results

We found out that the TCONS_00334653 and PVT1, whose target mRNA are MYC and HIST1H2BM, were downregulating in the prediabetes with HTG. Moreover, both of TCONS_00334653 and PVT1 were validated in the GEO database and qRT-PCR.

Conclusions

Therefore, the TCONS_00334653 and PVT1 were detected the key lncRNAs for the prediabetes with HTG, which might be a potential therapeutic or diagnostic target for the treatment of prediabetes with HTG according to the results of validation in the GEO database, qRT-PCR and ROC curves.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12986-022-00665-5.

Comprehensive Analysis of miRNA-Mediated Regulatory Network and Identification of Prognosis Biomarkers in Rectal Cancer

Rectal cancer is a malignant tumor with poor prognosis. Identification of prognostic biomarkers is needed to improve overall survival of rectal cancer patients. Here, we firstly identified miR-20a-5p significantly classifying high-risk group and low-risk group of rectal cancer patients. We also found that several known miRNAs miR-142-5p, miR-486-5p, miR-490-3p and miR-133a-3p played important roles in rectal cancer. Secondly, we constructed and analyzed a rectal cancer-related miRNA-mRNA network. A rectal cancer-related functional module was identified from the miRNA-mRNA network. Survival analysis demonstrated great prognosis capacity of the module to distinguish rectal cancer patients. Thirdly, a rectal cancer-related miRNA-lncRNA network was constructed, which followed power law distribution. Hub miRNAs and lncRNAs of the network were suggested to show significant prognosis ability and be enriched in cancer-related pathways. Fourthly, we constructed a rectal cancer-related ceRNA network and detected several typical lncRNA-miRNA-mRNA crosstalk, such as HAND2-AS1, HAND2 and miR-20a-5p crosstalk and MBNL1-AS1, miR-429 and LONRF2 crosstalk, which were validated to function in improving overall survival of rectal cancer patients. Finally, we identified the regulatory feedback that was constituted by transcriptional factors and lncRNAs, including MEIS1, MEIS2 and multiple lncRNAs. We also demonstrated that these lncRNAs were high related to immune cell infiltration. All these results can help us to uncover the molecular mechanism and provide new light on miRNA-mediated gene crosstalks in rectal cancer.

Long Non-coding RNA HOXA11-AS Facilitates Proliferation of Lung Adenocarcinoma Cells via Targeting the Let-7c-5p/IGF2BP1 Axis

Objective: This study investigates the relationship between the HOXA11-AS/let-7c-5p/IGF2BP1 regulatory axis and lung adenocarcinoma.

Methods: The expression levels of HOXA11-AS, let-7c-5p, and IGF2BP1 were evaluated in LUAD tissue and cell lines. Subcellular fractionation detection assay was adopted to verify the HOXA11-AS distribution in LUAD cells. The interaction relationship between let-7c-5p and HOXA11-AS or IGF2BP1 was validated by dual-luciferase reporter detection. In RNA binding protein immunoprecipitation assay, the binding relationship between HOXA11-AS and let-7c-5p was identified. The cell viability of transfected cells was tested by the Cell Counting Kit-8 assay. The mouse xenograft model was used to identify the effect of HOXA11-AS on tumor growth in vivo.

Results: Upregulation of lncRNA HOXA11-AS was found in LUAD, and suppression of HOXA11-AS could suppress the proliferative ability of LUAD cells. The let-7c-5p was expressed to be downregulated, which played an inhibitory role in LUAD cell proliferation. Let-7c-5p was negatively regulated by HOXA11-AS. HOXA11-AS promoted LUAD cell proliferation, while let-7c-5p had an inverse effect. Besides, IGF2BP1, regulated by let-7c-5p, had a positive relation with HOXA11-AS, while overexpression of IGF2BP1 could suppress the inhibition of silencing HOXA11-AS on LUAD cell proliferation. Experiments on mice confirmed that HOXA11-AS facilitated LUAD cell growth in vivo through regulating the let-7c-5p/IGF2BP1 axis.

Conclusion: HOXA11-AS promoted LUAD cell proliferation by targeting let-7c-5p/IGF2BP1, which could be potential molecular targets for LUAD.

Weighted correlation network analysis revealed novel long non-coding RNAs for colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide, which after breast, lung and, prostate cancers, is the fourth prevalent cancer in the United States. Long non-coding RNAs (lncRNAs) have an essential role in the pathogenesis of CRC. Therefore, bioinformatics studies on lncRNAs and their target genes have potential importance as novel biomarkers. In the current study, publicly available microarray gene expression data of colorectal cancer (GSE106582) was analyzed with the Limma, Geoquery, Biobase package. Afterward, identified differentially expressed lncRNAs and their target genes were inserted into Weighted correlation network analysis (WGCNA) to obtain modules and hub genes. A total of nine differentially expressed lncRNAs (LINC01018, ITCH-IT, ITPK1-AS1, FOXP1-IT1, FAM238B, PAXIP1-AS1, ATP2B1-AS1, MIR29B2CHG, and SNHG32) were identified using microarray data analysis. The WGCNA has identified several hub genes for black (LMOD3, CDKN2AIPNL, EXO5, ZNF69, BMS1P5, METTL21A, IL17RD, MIGA1, CEP19, FKBP14), blue (CLCA1, GUCA2A, UGT2B17, DSC2, CA1, AQP8, ITLN1, BEST4, KLF4, IQCF6) and turquoise (PAFAH1B1, LMNB1, CACYBP, GLO1, PUM3, POC1A, ASF1B, SDCCAG3, ASNS, PDCD2L) modules. The findings of the current study will help to improve our understanding of CRC. Moreover, the hub genes that we have identified could be considered as possible prognostic/diagnostic biomarkers. This study led to the determination of nine lncRNAs with no previous association with CRC development.

Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease

Background: Coronary artery disease (CAD) exerts a global challenge to public health. Genetic heritability is one of the most vital contributing factors in the pathophysiology of CAD. Co-expression network analysis is an applicable and robust method for the interpretation of biological interaction from microarray data. Previous CAD studies have focused on peripheral blood samples since the processes of CAD may vary from tissue to blood. It is therefore necessary to find biomarkers for CAD in heart tissues; their association also requires further illustration.

Materials and Methods: To filter for causal genes, an analysis of microarray expression profiles, GSE12504 and GSE22253, was performed with weighted gene co-expression network analysis (WGCNA). Co-expression modules were constructed after batch effect removal and data normalization. The results showed that 7 co-expression modules with 8,525 genes and 1,210 differentially expressed genes (DEGs) were identified. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Four major pathways in CAD tissue and hub genes were addressed in the Hybrid Mouse Diversity Panel (HMDP) and Human Protein Atlas (HPA), and isoproterenol (ISO)/doxycycline (DOX)-induced heart toxicity models were used to validate the hub genes. Lastly, the hub genes and risk variants were verified in the CAD cohort and in genome-wide association studies (GWAS).

Results: The results showed that RNF181 and eight other hub genes are perturbed during CAD in heart tissues. Additionally, the expression of RNF181 was validated using RT-PCR and immunohistochemistry (IHC) staining in two cardiotoxicity mouse models. The association was further verified in the CAD patient cohort and in GWAS.

Conclusion: Our findings illustrated for the first time that the E3 ubiquitination ligase protein RNF181 may serve as a potential biomarker in CAD, but further in vivo validation is warranted.

TRIP13, identified as a hub gene of tumor progression, is the target of microRNA-4693-5p and a potential therapeutic target for colorectal cancer

Colorectal cancer (CRC) is one of the digestive tract malignancies whose early symptoms are not obvious. This study aimed to identify novel targets for CRC therapy, especially early-stage CRC, by reanalyzing the publicly available GEO and TCGA databases. Thyroid hormone receptor interactor 13 (TRIP13) correlated with tumor progression and prognosis of patients after several rounds of analysis, including weighted gene correlation network analysis (WGCNA), and further chosen for experimental validation in cancer cell lines and patient samples. We identified that mRNA and protein levels of TRIP13 increased in CRC cells and tumor tissues with tumor progression. miR-4693-5p was significantly downregulated in CRC tumor tissues and bound to the 3′ untranslated region (3′UTR) of TRIP13, downregulating TRIP13 expression. DCZ0415, a small molecule inhibitor targeting TRIP13, induced anti-tumor activity in vitro and in vivo. DCZ0415 markedly suppressed CRC cell proliferation, migration, and tumor growth, promoted cell apoptosis, and resulted in the arrest of the cell cycle. Our research suggests that TRIP13 might play a crucial role in CRC progression and could be a potential target for CRC therapy.

Identification of Survival-Associated Hub Genes in Pancreatic Adenocarcinoma Based on WGCNA

Pancreatic adenocarcinoma is one of the leading causes of cancer-related death worldwide. Since little clinical symptoms were shown in the early period of pancreatic adenocarcinoma, most patients were found to carry metastases when diagnosis. The lack of effective diagnosis biomarkers and therapeutic targets makes pancreatic adenocarcinoma difficult to screen and cure. The fundamental problem is we know very little about the regulatory mechanisms during carcinogenesis. Here, we employed weighted gene co-expression network analysis (WGCNA) to build gene interaction network using expression profile of pancreatic adenocarcinoma from The Cancer Genome Atlas (TCGA). STRING was used for the construction and visualization of biological networks. A total of 22 modules were detected in the network, among which yellow and pink modules showed the most significant associations with pancreatic adenocarcinoma. Dozens of new genes including PKMYT1, WDHD1, ASF1B, and RAD18 were identified. Further survival analysis yielded their valuable effects on the diagnosis and treatment of pancreatic adenocarcinoma. Our study pioneered network-based algorithm in the application of tumor etiology and discovered several promising regulators for pancreatic adenocarcinoma detection and therapy.

Survival stratification for colorectal cancer via multi-omics integration using an autoencoder-based model

Prognosis stratification in colorectal cancer helps to address cancer heterogeneity and contributes to the improvement of tailored treatments for colorectal cancer patients. In this study, an autoencoder-based model was implemented to predict the prognosis of colorectal cancer via the integration of multi-omics data. DNA methylation, RNA-seq, and miRNA-seq data from The Cancer Genome Atlas (TCGA) database were integrated as input for the autoencoder, and 175 transformed features were produced. The survival-related features were used to cluster the samples using k-means clustering. The autoencoder-based strategy was compared to the principal component analysis (PCA)-, t-distributed random neighbor embedded (t-SNE)-, non-negative matrix factorization (NMF)-, or individual Cox proportional hazards (Cox-PH)-based strategies. Using the 175 transformed features, tumor samples were clustered into two groups (G1 and G2) with significantly different survival rates. The autoencoder-based strategy performed better at identifying survival-related features than the other transformation strategies. Further, the two survival groups were robustly validated using "hold-out" validation and five validation cohorts. Gene expression profiles, miRNA profiles, DNA methylation, and signaling pathway profiles varied from the poor prognosis group (G2) to the good prognosis group (G1). miRNA-mRNA networks were constructed using six differentially expressed miRNAs (let-7c, mir-34c, mir-133b, let-7e, mir-144, and mir-106a) and 19 predicted target genes. The autoencoder-based computational framework could distinguish good prognosis samples from bad prognosis samples and facilitate a better understanding of the molecular biology of colorectal cancer.

Exploring the mechanism of Yixinyin for myocardial infarction by weighted co-expression network and molecular docking

Yixinyin, the traditional Chinese medicine, has the effects of replenishing righteous qi, and promoting blood circulation to eliminate blood stagnation. It is often used to treat patients with acute myocardial infarction (MI). The purpose of our study is to explore the key components and targets of Yixinyin in the treatment of MI. In this study, we analyzed gene expression data and clinical information from 248 samples of MI patients with the GSE34198, GSE29111 and GSE66360 data sets. By constructing a weighted gene co-expression network, gene modules related to myocardial infarction are obtained. These modules can be mapped in Yixinyin PPI network. By integrating differential genes of healthy/MI and unstable angina/MI, key targets of Yixinyin for the treatment of myocardial infarction were screened. We validated the key objectives with external data sets. GSEA analysis is used to identify the biological processes involved in key targets. Through molecular docking screening, active components that can combine with key targets in Yixinyin were obtained. In the treatment of myocardial infarction, we have obtained key targets of Yixinyin, which are ALDH2, C5AR1, FOS, IL1B, TLR2, TXNRD1. External data sets prove that they behave differently in the healthy and MI (P < 0.05). GSEA enrichment analysis revealed that they are mainly involved in pathways associated with myocardial infarction, such as viral myocarditis, VEGF signaling pathway and type I diabetes mellitus. The docking results showed that the components that can be combined with key targets in YixinYin are Supraene, Prostaglandin B1, isomucronulatol-7,2'-di-O-glucosiole, angusifolin B, Linolenic acid ethyl ester, and Mandenol. For that matter, they may be active ingredients of Yixinyin in treating MI. These findings provide a basis for the preliminary research of myocardial infarction therapy in traditional Chinese medicine and provide ideas for the design of related drugs.

miR-125b Promotes Colorectal Cancer Migration and Invasion by Dual-Targeting CFTR and CGN

Simple Summary

Colorectal cancer (CRC) is the third leading cause for cancer related death, in which metastasis exerts a pivotal role. Therefore, we aim to find out the possible mechanism underlying CRC metastasis. We found that the level of miR-125b was elevated in normal, primary CRC, and distant metastasis tissues stepwise, and high level miR-125b was positively correlated with lymph node metastasis and tumor differentiation. In vitro and in vivo assays showed miR-125b significantly promoted CRC migration and invasion. To elucidate the potential mechanism, cystic fibrosis transmembrane conductance regulator (CFTR) and cingulin (CGN) were defined as two target genes of miR-125b. On the one hand, miR-125b promoted epithelial-mesenchymal transition (EMT) and the production and secretion of urokinase plasminogen activator (uPA) by inhibiting CFTR; on the other hand, miR-125b activated Ras Homolog Family Member A (RhoA)/Rho Kinase (ROCK) signaling by repressing CGN. Therefore, we provided a potential biomarker for CRC prevention and treatment in the future.

Abstract

Metastasis contributes to the poor prognosis of colorectal cancer, the causative factor of which is not fully understood. Previously, we found that miR-125b (Accession number: MIMAT0000423) contributed to cetuximab resistance in colorectal cancer (CRC). In this study, we identified a novel mechanism by which miR-125b enhances metastasis by targeting cystic fibrosis transmembrane conductance regulator (CFTR) and the tight junction-associated adaptor cingulin (CGN) in CRC. We found that miR-125b expression was upregulated in primary CRC tumors and metastatic sites compared with adjacent normal tissues. Overexpression of miR-125b in CRC cells enhanced migration capacity, while knockdown of miR-125b decreased migration and invasion. RNA-sequencing (RNA-seq) and dual-luciferase reporter assays identified CFTR and CGN as the target genes of miR-125b, and the inhibitory impact of CFTR and CGN on metastasis was further verified both in vitro and in vivo. Moreover, we found that miR-125b facilitated the epithelial-mesenchymal transition (EMT) process and the expression and secretion of urokinase plasminogen activator (uPA) by targeting CFTR and enhanced the Ras Homolog Family Member A (RhoA)/Rho Kinase (ROCK) pathway activity by targeting CGN. Together, these findings suggest miR-125b as a key functional molecule in CRC and a promising biomarker for the diagnosis and treatment of CRC.

Hub microRNAs and genes in the development of atrial fibrillation identified by weighted gene co-expression network analysis

Co-expression network may contribute to better understanding molecular interaction patterns underlying cellular processes. To explore microRNAs (miRNAs) expression patterns correlated with AF, we performed weighted gene co-expression network analysis (WGCNA) based on the dataset GSE28954. Thereafter, we predicted target genes using experimentally verified databases (ENOCRI, miRTarBase, and Tarbase), and overlapped genes with differentially expressed genes (DEGs) from GSE79768 were identified as key genes. Integrated analysis of association between hub miRNAs and key genes was conducted to screen hub genes. In general, we identified 3 differentially expressed miRNAs (DEMs) and 320 DEGs, predominantly enriched in inflammation-related functional items. Two significant modules (red and blue) and hub miRNAs (hsa-miR-146b-5p and hsa-miR-378a-5p), which highly correlated with AF-related phenotype, were detected by WGCNA. By overlapping the DEGs and predicted target genes, 38 genes were screened out. Finally, 9 genes (i.e. ATP13A3, BMP2, CXCL1, GABPA, LIF, MAP3K8, NPY1R, S100A12, SLC16A2) located at the core region in the miRNA-gene interaction network were identified as hub genes. In conclusion, our study identified 2 hub miRNAs and 9 hub genes, which may improve the understanding of molecular mechanisms and help to reveal potential therapeutic targets against AF.

Bone marrow-derived mesenchymal stem cells promote Helicobacter pylori-associated gastric cancer progression by secreting thrombospondin-2

OBJECTIVES

Bone marrow-derived cells (BMDCs), especially mesenchymal stem cells (MSCs), may be involved in the development of Helicobacter pylori-associated gastric cancer (GC) in mice, but the specific mechanism remains unclear, and evidence from human studies is lacking.

MATERIALS AND METHODS

To verify the role of BM-MSCs in H pylori-associated GC, green fluorescent protein (GFP)-labelled BM-MSCs were transplanted into the subserosal layers of the stomach in a mouse model of chronic H pylori infection. Three months post-transplantation, the mice were sacrificed, and the gastric tissues were subjected to histopathological and immunofluorescence analyses. In addition, we performed fluorescence in situ hybridization (FISH) and immunofluorescence analyses of gastric tissue from a female patient with H pylori infection and a history of acute myeloid leukaemia who received a BM transplant from a male donor.

RESULTS

In mice with chronic H pylori infection, GFP-labelled BM-MSCs migrated from the serous layer to the mucosal layer and promoted GC progression. The BM-MSCs differentiated into pan-cytokeratin-positive epithelial cells and α-smooth muscle actin-positive cancer-associated fibroblasts (CAFs) by secreting the protein thrombospondin-2. FISH analysis of gastric tissue from the female patient revealed Y-chromosome-positive cells. Immunofluorescence analyses further confirmed that Y-chromosome-positive cells showed positive BM-MSCs marker. These results suggested that allogeneic BMDCs, including BM-MSCs, can migrate to the stomach under chronic H pylori infection.

CONCLUSIONS

Taken together, these findings imply that BM-MSCs participate in the development of chronic H pylori-associated GC by differentiating into both gastric epithelial cells and CAFs.

4-Methylumbelliferone treatment and hyaluronan inhibition as a therapeutic strategy for chronic prostatitis

BACKGROUND

Hyaluronan (HA), an extracellular matrix component, accumulates in most chronic inflammatory tissues. Here, we studied the impact of HA on the pathogenesis of chronic prostatitis.

MATERIALS AND METHODS

First, we sorted demographic characteristics and peripheral blood serum samples from patients with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) to assess the relationship between the levels of HA in peripheral blood serum and the severity of inflammation in patients. Second, we induced an experimental autoimmune prostatitis (EAP) mouse model and treated the mice with 4-methylumbelliferone (4-MU) (200 mg/kg/day). After the mice were sacrificed, RNA from Th1 cells of the mouse spleens was extracted for RNA sequencing. We used weighted gene co-expression network analysis (WGCNA) to identify co-expressed gene modules and hub-gene related to the pathogenesis of EAP. The expression of critical genes associated with the identified pathway was confirmed by using western blot analysis.

RESULTS

HA was significantly more highly expressed in CP/CPPS patients than in healthy volunteers and positively correlated with the severity of pain, urination symptoms, and quality of life. Besides, the protein expression of HA was significantly higher in prostate tissues derived from EAP models than in those derived from controls. 4-MU, an oral inhibitor of HA synthesis, relieved immunocyte infiltration to the prostate and significantly reduced the proportion of Th1 cells. Based on the WGCNA, we identified 18 co-expression modules and identified that the Grey60 and brown modules were positively associated with the EAP and negatively associated with the Control and 4-MU-treated groups. Pathway enrichment analyses and western blot assays proved that HA potentially activated the cell cycle pathway, increasing the proportion of Th1 cells promoting chronic prostatitis pathogenesis, while these processes were reversed by 4-MU treatment.

CONCLUSIONS

Our results suggest that HA is elevated in patients with CP/CPPS compared with healthy controls and that targeting HA through 4-MU suppresses the activity of the cell cycle-related pathway, potentially by decreasing the proportion of Th1 cells and relieving chronic prostatitis. Our findings might inspire the clinical treatment of chronic prostatitis.

Identification of Key Modules and Hub Genes Involved in Esophageal Squamous Cell Carcinoma Tumorigenesis Using WCGNA

Introduction:

The mechanistic basis for the development of esophageal squamous cell carcinoma (ESCC) remains poorly understood. The goal of the present study was thus to characterize mRNA and long noncoding RNA (lncRNA) expression profiles associated with ESCC in order to identify key hub genes associated with the pathogenesis of this cancer.

Materials and Methods:

The GSE26866 and GSE45670 datasets from the Gene Expression Omnibus (GEO) database were used to conduct a weighted gene co-expression network analysis (WGCNA), after which Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Cytoscape was additionally used to construct lncRNA-mRNA networks, after which hub genes were identified and validated through the assessment of TCGA datasets and clinical samples.

Results:

Two gene modules were found to be closely linked to ESCC tumorigenesis. These genes were enriched in cell cycle, MAPK signaling, JAK-STAT signaling, pyrimidine metabolism, arachidonic acid metabolism, and P53 signaling pathway activity, all of which are directly linked with the development of cancer. In total, we identified and validated 9 hub genes associated with ESCC (DDX18, DNMT1, NCAPG, WDHD1, PRR11, VOPP1, ZKSCAN5, LC35C2, and PHACTR2).

Conclusion:

In summary, we identified key gene modules and hub genes associated with ESCC development, and we constructed a lncRNA-mRNA network pertaining to this cancer type. These results provide a foundation for future research regarding the mechanistic basis of ESCC.

Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis

Colon adenocarcinoma is a prevalent malignancy with significant mortality. Hence, the identification of molecular biomarkers with prognostic significance is important for improved treatment and patient outcomes. Clinical traits and RNA-Seq of 551 patient samples in the UCSC Toil Recompute Compendium of The Cancer Genome Atlas TARGET and Genotype Tissue Expression project datasets (primary_site = colon) were used for weighted gene co-expression network analysis to reveal the association between gene networks and cancer cell invasion. One module, containing 151 genes, was significantly correlated with lymphatic invasion, a histopathological feature of higher risk colon cancer. DAPK3 (death-associated protein kinase 3) was identified as the pseudohub of the module. Gene ontology identified gene enrichment related to cytoskeletal organization and apoptotic signaling processes, suggesting modular involvement in tumor cell survival, migration, and epithelial-mesenchymal transformation. Although DAPK3 expression was reduced in patients with colon cancer, high expression of DAPK3 was significantly correlated with greater lymphatic invasion and poor overall survival.

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WCGNA reveals a gene module linked to lymphatic invasion in colon adenocarcinoma

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DAPK3 is a pseudohub gene with differential expression in colon cancer

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Gene ontology identified relationships to cytoskeletal organization and apoptosis

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DAPK3 was correlated with lymphatic invasion and poor overall survival

Epithelial-Mesenchymal Transition Gene Signature Related to Prognostic in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) remains an important cause of cancer-related mortality worldwide. Epithelial–mesenchymal transition (EMT) is a key mechanism, promoting not only the invasive or metastatic phenotype but also resistance to therapy. Using bioinformatics approaches, we studied the alteration on EMT related genes and its implication on COAD prognostic based on public datasets. For the EMT mechanisms, two overexpressed genes were identified (NOX4 and IGF2BP3), as well as five downregulated genes (BMP5, DACT3, EEF1A2, GCNT2 and SFRP1) that were related to prognosis in COAD. A qRT-PCR validation step was conducted in a COAD patient cohort comprising of 29 tumor tissues and 29 normal adjacent tissues, endorsing the expression level for BMP5, as well as for two of the miRNAs targeting key EMT related genes, revealing upregulation of miR-27a-5p and miR-146a-5p. The EMT signature can be used to develop a panel of biomarkers for recurrence prediction in COAD patients, which may contribute to the improvement of risk stratification for the patients.

Predictive Efficacy of MiR-125b-5p, MiR-17-5p, and MiR-185-5p in Liver Metastasis and Chemotherapy Response Among Advanced Stage Colorectal Cancer Patients

MicroRNAs (miRNAs), a class of small non-coding RNAs represent potential biomarkers for colorectal cancer (CRC). The study hypothesized that miRNAs associated with liver metastases may also contribute to assessing treatment response when associated to plasma exosomes. In this study, we used two sets of biological samples, a collection of tumor tissues harvested from patients with CRC with and without liver metastases, and a collection of plasma from CRC patients with and without response to FOLFOX4/FOLFIRI regimens. We investigated 10 target miRNAs in the tissue of 28 CRC patients and identified miR-125b-5p, miR-17-5p, and miR-185-5p to be associated with liver metastasis. Further, we investigated the three miRNAs at the exosomal level in a plasma collection to test their association with chemotherapy response. Our data suggest that the elevated plasma levels of miR-17-5p and miR-185-5p could be predictive of treatment response. Overexpression of miR-17-5p and underexpression of miR-125b-5p and miR-185-5p in CRC tissue seem to be associated with metastatic potential. On the other hand, an increased expression of miR-125b-5p in plasma exosomes was potentially correlated with a more aggressive CRC phenotype.

Effect of c-fos gene silence on PM2.5-induced miRNA alteration in human bronchial epithelial cells

Human bronchial epithelial (HBE) cells and c-fos-silenced HBE cells were first exposed to fine particulate matter (PM_2.5) and the resulting miRNA sequenced. Thereafter, a weighted gene co-expression network analysis was performed using Cytoscape software to visualize the interactions between identified hub miRNAs and their target genes. Nine differentially expressed miRNAs in hub miRNAs were identified in the different treatment groups, of which miR-25-3p, miR-215-5p, and miR-145-5p were selected for further study. Following qPCR validation, both miR-25-3p and miR-215-5p were found to be significantly up-regulated whilst, miR-145-5p was significantly down-regulated (p < 0.05) in the PM_2.5 group. Furthermore, miR-25-3p and miR-145-5p were also significantly down-regulated in the untreated group of c-fos silenced HBE cells. However, miR-215-5p was significantly down-regulated in both the untreated and PM_2.5-treated groups of c-fos silenced HBE cells. Subsequent analysis of their target genes also illustrated differential gene expression when comparing the treatment groups of the two cell types. The present data indicated that the c-fos gene has an important effect on the miRNA expression profiles and the related signaling pathways in PM_2.5-treated HBE cells. Therefore, each of miR-25-3p, miR-145-5p, and miR-215-5p may potentially provide future research information for additional exploration of a PM_2.5-induced carcinogenesis mechanism.

miR-1253, a novel tumor suppressor gene in colon cancer, is associated with poor patients prognosis

MiR-1253 has been reported to play vital roles in a variety of cancers. However, its function in the progression and prognosis of colon cancer remains unclear. Here, the clinical significance and biological function of miR-1253 in the development of colon cancer was investigated. The expression of miR-1253 was identified in colon cancer tissues and cell lines by qRT-PCR. The prognostic value of miR-1253 was evaluated by Kaplan-Meier and Cox regression analysis. The roles of miR-1253 in regulating cell proliferation, migration, and invasion of colon cancer were evaluated in vitro by CCK8 and Transwell assay. It was found that miR-1253 was significantly downregulated in colon cancer tissues and cell lines (P < 0.001). The downregulation of miR-1253 was associated with the TNM stage (P = 0.007) and lymph node metastasis (P = 0.037) of patients. MiR-1253 (HR factor = 2.564, 95% CI = 1.077-6.107, P = 0.033) and TNM stage (HR factor = 2.899, 95% CI = 1.024-8.205, P = 0.045) were identified as independent factors that can predict the prognosis of patients. Functionally, miR-1253 acts as a tumor suppressor that inhibited cell proliferation, migration, and invasion of colon cancer through targeting EZH2. MiR-1253 was identified as a prognostic biomarker and a tumor suppressor of colon cancer.