Genome‑scale analysis to identify potential prognostic microRNA biomarkers for predicting overall survival in patients with colon adenocarcinoma

The high expression of ADRM1 in hepatocellular carcinoma is closely related to tumor immune infiltration and is regulated by miR-891a-5p

Liver cancer is one of the most common malignant tumors worldwide. Although some progress has been made in the diagnosis and treatment of Hepatocellular carcinoma (HCC), the diagnosis and treatment of HCC is still facing great challenges because of the high mortality rate and poor prognosis of HCC. The purpose of this study was to explore the relationship between adhesion-regulating molecule1 (ADRM1), and liver cancer, and the relationship between prognoses. ADRM1 is highly expressed in tumors and is closely associated with the prognosis of patients with liver cancer. In our previous study, we found that ADRM1 was highly expressed in HCC and was closely related to tumor immune and immune checkpoint levels in HCC. We validated the immune expression of ADRM1 in liver cancer cells using flow cytometry. In hepatocellular carcinoma tissues, miR-891a-5p regulates ADRM1. Upregulation of miR-891a-5p upregulates ADRM1, and downregulation of miR-891a-5p downregulates ADRM1. It is suggested that ADRM1 plays a key role in the occurrence and development of hepatocellular carcinoma. This study is expected to provide new ideas for the research and development of anti-HCC drugs targeting miR-891a-5p/ADRM1. However, further trials are needed to confirm these results and explore the actual results in patients with HCC.

Identification and diagnostic potential of hsa_circ_101303 in colorectal cancer: unraveling a regulatory network

BACKGROUND

The role of novel circular RNAs (circRNAs) in colorectal cancer (CRC) remains to be determined. This study aimed to identify a novel circRNA involved in CRC pathogenesis, assess its diagnostic value, and construct a regulatory network.

METHODS

Differential expression analysis was conducted using circRNA datasets to screen for differentially expressed circRNAs. The expression of selected circRNAs was validated in external datasets and clinical samples. Diagnostic value of plasma circRNA levels in CRC was assessed. A competing endogenous RNA (ceRNA) network was constructed for the circRNA using TCGA dataset.

RESULTS

Analysis of datasets revealed that hsa_circ_101303 was significantly overexpressed in CRC tissues compared to normal tissues. The upregulation of hsa_circ_101303 in CRC tissues was further confirmed through the GSE138589 dataset and clinical samples. High expression of hsa_circ_101303 was associated with advanced N stage, M stage, and tumor stage in CRC. Plasma levels of hsa_circ_101303 were markedly elevated in CRC patients and exhibited moderate diagnostic ability for CRC (AUC = 0.738). The host gene of hsa_circ_101303 was also found to be related to the TNM stage of CRC. Nine miRNAs were identified as target miRNAs for hsa_circ_101303, and 27 genes were identified as targets of these miRNAs. Subsequently, a ceRNA network for hsa_circ_101303 was constructed to illustrate the interactions between the nine miRNAs and 27 genes.

CONCLUSIONS

The study identifies hsa_circ_101303 as a highly expressed circRNA in CRC, which is associated with the progression of the disease. Plasma levels of hsa_circ_101303 show promising diagnostic potential for CRC. The ceRNA network for hsa_circ_101303 provides valuable insights into the regulatory mechanisms underlying CRC.

Regularized survival learning and cross-database analysis enabled identification of colorectal cancer prognosis-related immune genes

Colon adenocarcinoma is the most common type of colorectal cancer. The prognosis of advanced colorectal cancer patients who received treatment is still very poor. Therefore, identifying new biomarkers for prognosis prediction has important significance for improving treatment strategies. However, the power of biomarker analyses was limited by the used sample size of individual database. In this study, we combined Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to expand the number of healthy tissue samples. We screened differentially expressed genes between the GTEx healthy samples and TCGA tumor samples. Subsequently, we applied least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to identify nine prognosis-related immune genes: ANGPTL4, IDO1, NOX1, CXCL3, LTB4R, IL1RL2, CD72, NOS2, and NUDT6. We computed the risk scores of samples based on the expression levels of these genes and divided patients into high- and low-risk groups according to this risk score. Survival analysis results showed a significant difference in survival rate between the two risk groups. The high-risk group had a significantly lower overall survival rate and poorer prognosis. We found the receiver operating characteristic based on the risk score was showed to accurately predict patients' prognosis. These prognosis-related immune genes may be potential biomarkers for colorectal cancer diagnosis and treatment. Our open-source code is freely available from GitHub at https://github.com/gutmicrobes/Prognosis-model.git.

DNA Methylation Profiles of Ovarian Granular Cells from Fluorosis Female Patients Suffering Reproductive Dysfunctions

Fluorosis often causes female reproductive dysfunction. A rapid turnover of DNA methylation is a pathological change in many human diseases, including female reproductive dysfunction. The role of DNA methylation in fluorosis was unknown and investigated in this experiment. Fifty fluorosis women patients were selected as High F group and forty-six healthy women were recruited as Control group were enrolled. In addition, ovarian granulosa cells were obtained from five women in High F group and five women in Control group. All ten women went through in vitro fertilization (IVF) process with DNA methylation sequencing. KGN cells (human granulosa cell line) were cultured with different concentrations of sodium fluoride (0-8 mM NaF) for 24 h for the in vitro study. The level of DNA methylation in blood samples was significantly higher in High F group than that in Control group. The level of serum estradiol (E₂) was significantly lower in women from High F group, while the levels of serum luteinizing hormone (LH) and follicle-stimulating hormone (FSH) in High F group were significantly higher than that in Control group. The methylation sequences of KGN cells relating to autophagy were significantly changed by NaF treatment dose-dependently. Based on these results, it is concluded that DNA methylation and autophagy may play a significant role in the pathophysiology of reproductive dysfunction caused by fluorosis.

Multi-Omics Reveal the Immunological Role and the Theragnostic Value of miR-216a/GDF15 Axis in Human Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is the most common type of gastrointestinal cancer and is still the third leading cause of cancer-related mortality worldwide. Accurate screening tools for early diagnosis and prediction of prognosis and precision treatment strategies are urgently required to accommodate the unmet medical needs of COAD management. We herein aimed to explore the significance of the microRNA (miR)-216a/growth differentiation factor 15 (GDF15) axis in terms of clinical value, tumor immunity, and potential mechanisms in COAD by using multi-omic analysis. The gene expression levels of miR-216a and GDF15 showed an increase in the COAD group compared to those of the normal group. The expression of miR-216a presented a negative correlation with GDF15 in COAD tumor tissue. The use of an in vitro luciferase reporter assay and bioinformatic prediction revealed that miR-216a-3p acted toward translational inhibition on GDF15 by targeting its 3′untranslated region (UTR) site. High miR-216a expression was associated with decreased overall survival (OS), while the high expression of GDF15 was associated with increased OS. Enriched type 1 T-helper (Th1), enriched regulatory T (Treg), enriched eosinophils, and decreased nature killer T-cells (NKTs) in COAD tumor tissue may play counteracting factors on the tumor-regulatory effects of miR-216a and GDF15. In addition, high GDF15 expression had associations with suppressed immunoinhibitory genes and negative correlations with the infiltration of macrophages and endothelial cells. The enrichment analysis revealed that GDF15 and its co-expression network may be implicated in mitochondrial organization, apoptosis signaling, and endoplasmic reticulum (ER) stress response. The Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) analysis identified that Gemcitabine acted as a precision treatment for COAD when GDF15 expression was low. This study supports the miR-216a/GDF15 axis as a diagnostic/prognostic panel for COAD, identifies Th1, Treg, eosinophils, and NKTs as counteracting factors, indicates potential relationships underlying immunomodulation, mitochondrial organization, apoptotic signaling, and ER stress and unveil Gemcitabine as a potential drug for the development of treatment strategy when combined with targeting GDF15.

miR-940 is a new biomarker with tumor diagnostic and prognostic value

miR-940 is a microRNA located on chromosome 16p13.3, which has varying degrees of expression imbalance in many diseases. It binds to the 3′ untranslated region (UTR) and affects the transcription or post-transcriptional regulation of target protein-coding genes. For a diversity of cellular processes, including cell proliferation, migration, invasion, apoptosis, epithelial-to-mesenchymal transition (EMT), cell cycle, and osteogenic differentiation, miR-940 can affect them not only by regulating protein-coding genes but also long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in pathways. Intriguingly, miR-940 participates in four pathways that affect cancer development, including the Wnt/β-catenin pathway, mitogen-activated protein kinase (MAPK) pathway, PD-1 pathway, and phosphatidylinositol 3-kinase (PI3K)-Akt pathway. Importantly, the expression of miR-940 is intimately correlated with the diagnosis and prognosis of tumor patients, as well as to the efficacy of tumor chemotherapy drugs. In conclusion, our main purpose is to outline the expression of miR-940 in various diseases and the molecular biological and cytological functions of target genes in order to reveal its potential diagnostic and prognostic value as well as its predictive value of drug efficacy.

Colon cancer-specific diagnostic and prognostic biomarkers based on genome-wide abnormal DNA methylation

Abnormal DNA methylation is a major early contributor to colon cancer (COAD) development. We conducted a cohort-based systematic investigation of genome-wide DNA methylation using 299 COAD and 38 normal tissue samples from TCGA. Through conditional screening and machine learning with a training cohort, we identified one hypomethylated and nine hypermethylated differentially methylated CpG sites as potential diagnostic biomarkers, and used them to construct a COAD-specific diagnostic model. Unlike previous models, our model precisely distinguished COAD from nine other cancer types (e.g., breast cancer and liver cancer; error rate ≤ 0.05) and from normal tissues in the training cohort (AUC = 1). The diagnostic model was verified using a validation cohort from The Cancer Genome Atlas (AUC = 1) and five independent cohorts from the Gene Expression Omnibus (AUC ≥ 0.951). Using Cox regression analyses, we established a prognostic model based on six CpG sites in the training cohort, and verified the model in the validation cohort. The prognostic model sensitively predicted patients’ survival (p ≤ 0.00011, AUC ≥ 0.792) independently of important clinicopathological characteristics of COAD (e.g., gender and age). Thus, our DNA methylation analysis provided precise biomarkers and models for the early diagnosis and prognostic evaluation of COAD.

Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis

Background

Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD.

Methods

The gene expression profiles and clinical information of patients with colon adenocarcinoma were obtained from the TCGA and GEO databases and were divided into training and validation cohorts. Immune genes were selected that showed a significant association with prognosis.

Results

Among 1647 immune genes, a model with 17 IRGPs was built that was significantly associated with OS in the training cohort. In the training and validation datasets, the IRGP model divided patients into the high-risk group and low-risk group, and the prognosis of the high-risk group was significantly worse (P<0.001). Univariate and multivariate Cox proportional hazard analyses confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways were upregulated in the high-risk groups. Regulatory T cells and macrophages M0 were significantly highly expressed in the high-risk group.

Conclusion

We successfully constructed an IRGP model that can predict the prognosis of COAD, providing new insights into the treatment strategy of COAD.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s12885-020-07532-7.

Prognostic lncRNA, miRNA, and mRNA Signatures in Papillary Thyroid Carcinoma

The current focus in the treatment of papillary thyroid carcinoma (PTC) is tumor progression. The aim of this study was to build RNA-based classifiers and develop a comprehensive model to provide progression-free interval (PFI) risk prediction for PTC. The RNAseq data, miRNAseq data, and clinical information of PTC were downloaded from The Cancer Genome Atlas database. Based on the differently expressed RNAs, the least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to build the RNA-based classifiers for PFI of the patients with PTC. A 6-messenger RNA (mRNA)-based classifier, a 5-long non-coding RNA (lncRNA)-based classifier, and a 4-microRNA (miRNA)-based classifier were constructed to predict the PFI. Patients with high risk based on the constructed RNA-based classifiers had worse prognosis in Kaplan–Meier curve analysis with log-rank test. The areas under the curves of the first, third, and fifth years in the training and testing set were 0.83, 0.82, and 0.82 and 0.67, 0.72, and 0.73 for the 6-mRNA-based classifier, respectively; 0.75, 0.84, and 0.85 and 0.71, 0.67, and 0.71 for the 5-lncRNA-based classifier, respectively; and 0.70, 0.77, and 0.79 and 0.74, 0.67, and 0.66 for the 4-miRNA-based classifier, respectively. The prediction capability of the three RNA-based classifiers was superior to the TNM stage system. Furthermore, a nomogram based on the verified independent prognostic factors was established for the prognostic prediction. The C-index and calibration plots indicated good predictive accuracy of the nomogram. In summary, the 6-mRNA-based classifier and 5-lncRNA-based classifier constructed in this study were independent prognostic factors for PTC.

Bioinformatics Analysis of Prognostic miRNA Signature and Potential Critical Genes in Colon Cancer

This study aims to lay a foundation for studying the regulation of microRNAs (miRNAs) in colon cancer by applying bioinformatics methods to identify miRNAs and their potential critical target genes associated with colon cancer and prognosis. Data of differentially expressed miRNAs (DEMs) and genes (DEGs) downloaded from two independent databases (TCGA and GEO) and analyzed by R software resulted in 472 DEMs and 565 DEGs in colon cancers, respectively. Next, we developed an 8-miRNA (hsa-mir-6854, hsa-mir-4437, hsa-mir-216a, hsa-mir-3677, hsa-mir-887, hsa-mir-4999, hsa-mir-34b, and hsa-mir-3189) prognostic signature for patients with colon cancer by Cox proportional hazards regression analysis. To predict the target genes of these miRNAs, we used TargetScan and miRDB. The intersection of DEGs with the target genes predicted for these eight miRNAs retrieved 112 consensus genes. GO and KEGG pathway enrichment analyses showed these 112 genes were mainly involved in protein binding, one-carbon metabolic process, nitrogen metabolism, proteoglycans in cancer, and chemokine signaling pathways. The protein-protein interaction network of the consensus genes, constructed using the STRING database and imported into Cytoscape, identified 14 critical genes in the pathogenesis of colon cancer (CEP55, DTL, FANCI, HMMR, KIF15, MCM6, MKI67, NCAPG2, NEK2, RACGAP1, RRM2, TOP2A, UBE2C, and ZWILCH). Finally, we verified the critical genes by weighted gene co-expression network analysis (WGCNA) of the GEO data, and further mined the core genes involved in colon cancer. In summary, this study identified an 8-miRNA model that can effectively predict the prognosis of colon cancer patients and 14 critical genes with vital roles in colon cancer carcinogenesis. Our findings contribute new ideas for elucidating the molecular mechanisms of colon cancer carcinogenesis and provide new therapeutic targets and biomarkers for future treatment and prognosis.

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

MicroRNAs (miRNAs) are a kind of non-coding RNA (ncRNA) that regulate the expression of target genes and play a role in the occurrence and development of cancers. Colon cancer (COAD) is the second most common cause of cancer-related mortality. However, the prognostic value of miRNAs in COAD is still confusing. In this study, we obtain miRNAs and messenger RNAs (mRNAs) expression profiles of COAD from the Cancer Genome Atlas (TCGA) database. After preliminary data screening and preprocessing, we acquire the expression data of 894 miRNAs and 17,019 mRNAs. Then, compared with the normal samples, 39 upregulated miRNAs and 54 downregulated miRNAs are identified by differential expression analysis. Furthermore, we obtain 1,487 upregulated mRNAs and 2,847 downregulated mRNAs. We confirm nine key miRNAs related to the survival rate of COAD patients. Moreover, by using bioinformatics methods, we get 461 common genes from both the target genes of these nine key miRNAs and differentially expressed mRNAs. Through analyzing the protein-protein interaction (PPI) network of these 461 common genes and survival analysis, we confirm five hub genes as promising biomarkers for COAD prognosis. It is worth mentioning that no previous reports have found that PGR and KCNB1 are related to COAD. We expect these key miRNAs and hub genes will provide a new way for the study of COAD.

A Five-microRNA Signature as Prognostic Biomarker in Colorectal Cancer by Bioinformatics Analysis

Mounting evidence has demonstrated that a lot of miRNAs are overexpressed or downregulated in colorectal cancer (CRC) tissues and play a crucial role in tumorigenesis, invasion, and migration. The aim of our study was to screen new biomarkers related to CRC prognosis by bioinformatics analysis. By using the R language edgeR package for the differential analysis and standardization of miRNA expression profiles from The Cancer Genome Atlas (TCGA), 502 differentially expressed miRNAs (343 up-regulated, 159 down-regulated) were screened based on the cut-off criteria of p < 0.05 and |log2FC|>1, then all the patients (421) with differentially expressed miRNAs and complete survival time, status were then randomly divided into train group (212) and the test group (209). Eight miRNAs with p < 0.005 were revealed in univariate cox regression analysis of train group, then stepwise multivariate cox regression was applied for constituting a five-miRNA (hsa-miR-5091, hsa-miR-10b-3p, hsa-miR-9-5p, hsa-miR-187-3p, hsa-miR-32-5p) signature prognostic biomarkers with obviously different overall survival. Test group and entire group shown the same results utilizing the same prescient miRNA signature. The area under curve (AUC) of receiver operating characteristic (ROC) curve for predicting 5 years survival in train group, test group, and whole cohort were 0.79, 0.679, and 0.744, respectively, which demonstrated better predictive power of prognostic model. Furthermore, Univariate cox regression and multivariate cox regression considering other clinical factors displayed that the five-miRNA signature could serve as an independent prognostic factor. In order to predict the potential biological functions of five-miRNA signature, target genes of these five miRNAs were analyzed by Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway and Gene Ontology (GO) enrichment analysis. The top 10 hub genes (ESR1, ADCY9, MEF2C, NRXN1, ADCY5, FGF2, KITLG, GATA1, GRIA1, KAT2B) of target genes in protein protein interaction (PPI) network were screened by string database and Cytoscape 3.6.1 (plug-in cytoHubba). In addition, 19 of target genes were associated with survival prognosis. Taken together, the current study showed the model of five-miRNA signature could efficiently function as a novel and independent prognosis biomarker and therapeutic target for CRC patients.

Competitive Endogenous RNA (ceRNA) Regulation Network of lncRNA-miRNA-mRNA in Colorectal Carcinogenesis

BACKGROUND

Competitive endogenous RNA (ceRNA) regulation suggested complex network of all transcript RNAs including long noncoding RNAs (lncRNAs), which can act as natural miRNA sponges to inhibit miRNA functions and modulate mRNA expression. Until now, the specific ceRNA regulatory mechanism of lncRNA-miRNA-mRNA in colorectal cancer (CRC) still remains unclear.

MATERIALS AND METHODS

RNA sequencing data of 478 colon adenocarcinoma cases and 41 controls as well as 166 rectum adenocarcinoma cases and 10 controls were obtained from The Cancer Genome Atlas (TCGA) to investigate the significant changes of lncRNAs, miRNAs and mRNAs in colorectal carcinogenesis. The target lncRNAs and mRNAs of miRNAs were predicted by miRWalk. Functional and enrichment analyses were conducted by DAVID database. The lncRNA-miRNA-mRNA interaction network was constructed using Cytoscape.

RESULTS

We constructed ceRNA regulatory networks including 22 up-regulated lncRNAs, 12 down-regulated miRNAs and 122 up-regulated mRNAs, as well as 8 down-regulated lncRNAs, 43 up-regulated miRNAs and 139 down-regulated mRNAs. The GO enrichment showed that up-regulated genes mainly enriched in biological process including organic anion transport, collagen catabolic process, wound healing, Wnt receptor signalling and in pathways of tyrosine metabolism, taurine and hypotaurine metabolism, melanogenesis and phenylalanine metabolism. For down-regulated genes, significant enrichment was found in biological process of metal ion homeostasis, transmission of nerve impulse, cell-cell signalling, transmembrane transport and in pathways of ABC transporters, neuroactive ligand-receptor interaction, retinol metabolism, nitrogen metabolism and steroid hormone biosynthesis.

CONCLUSION

We identified significantly altered lncRNAs, miRNAs and mRNAs in colorectal carcinogenesis, which might serve as potential biomarkers for tumorigenesis of CRC. In addition, the ceRNA regulatory network of lncRNA-miRNA-mRNA was constructed, which would elucidate novel molecular mechanisms involved in initiation and progression of CRC, thus providing promising clues for clinical diagnosis and therapy.

Genome-scale integrated analysis to identify prospective molecular mechanisms and therapeutic targets in isocitrate dehydrogenase 2 R140Q-mutated acute myeloid leukemia

The aim of the present study was to identify potential molecular mechanisms and therapeutic targets in regards to isocitrate dehydrogenase 2 (IDH2) R140Q-mutated acute myeloid leukemia (AML). An RNA sequencing dataset of IDH2 wild-type and R140Q-mutated adult de novo AML bone marrow samples was obtained from The Cancer Genome Atlas (TCGA) database. The edgeR package was used to screen for the differentially expressed genes (DEGs), and the potential molecular mechanisms and therapeutic targets were identified using Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.8, Biological Networks Gene Ontology tool, Connectivity Map (CMap), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and GeneMANIA. A total of 230 DEGs were identified between the bone marrow tissues of IDH2 R140Q-mutated and wild-type AML patients, of which 31 were significantly associated with overall survival (OS). Functional assessment of DEGs showed significant enrichment in multiple biological processes, including angiogenesis and cell differentiation. STRING and GeneMANIA were used to identify the hub genes of these DEGs. CMap analysis identified 13 potential small-molecule drugs against IDH2 R140Q-mutated adult de novo AML. Genome-wide co-expression network analysis identified several IDH2 R140Q co-expressed genes, of which 56 were significantly associated with AML OS. The difference in IDH2 mRNA expression levels and OS between the IDH2 R140Q-mutated and wild-type AML were not statistically significant in our cohort. In conclusion, we identified several co-expressing genes and potential molecular mechanisms that are instrumental in IDH2 R140Q-mutated adult de novo AML, along with 13 candidate targeted therapeutic drugs.