Minichromosome maintenance deficient 6 as a core biomarker for the identification of gynecological pan-carcinoma

Cervical, endometrial, and breast cancers are common diseases studied in the field of gynecology. We conducted a series of bioinformatics analyses on these different gynecological cancers. After downloading mRNA microarray data on these gynecological cancers from the TCGA database, we applied a differential analysis. We combined the differential genes obtained from each disease sample and obtained 2,353 public differential genes (P <0.01). Through a weighted gene co-expression network analysis, we obtained five functional disorder modules, and found the essential genes to be LHFP, DNAJC27, GIMAP4, MCM6, and AIM1L. The analysis results showed that dysfunctional genes are associated with ameoidal-type cell migration and DNA replication. We predicted the regulator using cpRNA and a pivot analysis of the transcription factors. Studies have shown that miR-21-5p and miR-300 regulate three modules, MSC regulates m3 and m5, and YBX1 regulates m4 and m5. All are involved in the regulation of m5, and the co-regulated core gene of m5 is MCM6. We believe that MCM6 has a central regulatory role in a disease network and that MCM6 can be considered as a core biomarker for gynecological pan-cancer.

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MiRNA-4665-3p Regulates Expression of PLD5 in Thyroid Cancer Patients and Predicts Death

Journal of Biomaterials and Tissue Engineering ◽

10.1166/jbt.2019.2068 ◽

2019 ◽

Vol 9 (7) ◽

pp. 871-880

Author(s):

Yifan Han ◽

Lei Zhou

Keyword(s):

Survival Analysis ◽

Thyroid Cancer ◽

Cancer Patients ◽

Microarray Data ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Core Gene ◽

Differential Analysis ◽

The Core ◽

Differential Genes

Thyroid cancer has become an increasingly common malignant tumor around the world, and its incidence is increasing year by year. In this study, mRNA microarray data of thyroid cancer patients from four periods were collected from the TCGA database. We performed a series of bioinformatics analyses on these mRNA expression profiles, including differential analysis, co-expression analysis, enrichment analysis, regulator prediction, and survival analysis. There were 13126, 10914, 13585, and 13241 differential genes in the four periods; 4822 differential genes were obtained by union and deduplication (p < 0.01). Weighted gene co-expression network analysis indicated a total of 21 functional disorder modules. In each module, PLD5, CHD4, ADGRA3, ITGA3, etc. were the key genes. Enrichment analysis showed that the dysfunctional module genes were mainly related to pre-replicative complex assembly, Cytokine–cytokine receptor interaction, and MAPK signaling pathway. We downloaded thyroid cancer-associated miRNA microarray data from the GEO database for differential analysis. Then, we crossed the predicted ncRNA with the differential miRNA to obtain thyroid cancer-associated regulatory factors. Finally, we found that miRNA-4665-3p regulates the core gene PLD5, and six regulators such as miRNA-3140-3p and miRNA-324-3p regulate the core gene CHD4. Survival analysis showed that both up-regulation of PLD5 expression and down-regulation of CHD4 expression accelerated patient death. According to the above analysis, we believe miRNA-4665-3p regulates the expression of PLD5 and affects the development of thyroid cancer. Its up-regulation promotes the death of patients.

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Insights into the Mechanism of Bovine Spermiogenesis Based on Comparative Transcriptomic Studies

Animals ◽

10.3390/ani11010080 ◽

2021 ◽

Vol 11 (1) ◽

pp. 80

Author(s):

Xin Li ◽

Chenying Duan ◽

Ruyi Li ◽

Dong Wang

Keyword(s):

Gene Expression ◽

Semen Quality ◽

Regulation Of Gene Expression ◽

Physiological Mechanism ◽

Interaction Network ◽

Seminiferous Tubules ◽

Differential Analysis ◽

Epididymal Sperm ◽

Bioinformatics Analyses ◽

Acrosome Formation

To reduce subfertility caused by low semen quality and provide theoretical guidance for the eradication of human male infertility, we sequenced the bovine transcriptomes of round, elongated spermatids and epididymal sperms. The differential analysis was carried out with the reference of the mouse transcriptome, and the homology trends of gene expression to the mouse were also analysed. First, to explore the physiological mechanism of spermiogenesis that profoundly affects semen quality, homological trends of differential genes were compared during spermiogenesis in dairy cattle and mice. Next, Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment, protein–protein interaction network (PPI network), and bioinformatics analyses were performed to uncover the regulation network of acrosome formation during the transition from round to elongated spermatids. In addition, processes that regulate gene expression during spermiogenesis from elongated spermatid to epididymal sperm, such as ubiquitination, acetylation, deacetylation, and glycosylation, and the functional ART3 gene may play important roles during spermiogenesis. Therefore, its localisation in the seminiferous tubules and epididymal sperm were investigated using immunofluorescent analysis, and its structure and function were also predicted. Our findings provide a deeper understanding of the process of spermiogenesis, which involves acrosome formation, histone replacement, and the fine regulation of gene expression.

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Role of DNA polymerases family members in cancer: The pan-cancer perspective.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.3_suppl.475 ◽

2021 ◽

Vol 39 (3_suppl) ◽

pp. 475-475

Author(s):

Zhiwen Luo ◽

Xinyu Bi ◽

Xingang Bi

Keyword(s):

Expression Pattern ◽

Drug Target ◽

Dna Polymerases ◽

Family Members ◽

Prognostic Biomarkers ◽

Cancer Type ◽

Sequencing Data ◽

Clinical Value ◽

Bioinformatics Analyses ◽

Pan Cancer

475 Background: DNA polymerases family (DNA pols) has a lengthy reported significant influence on the initiation, development, and progress of cancer. However, the pan-cancer value of whole family members was poorly done. Our study intends to demonstrate the expression pattern and clinical cancer value of DNA pols members as prognostic biomarkers and a therapeutic target of pan-cancer. Methods: Comprehensive bioinformatics analyses were done using data from TCGA and CCLE. MultiCox regression was done to select tumor prognosis-related members. Nomogram was constructed to predict the overall survival (OS) across cancer patients. Transcription factor, GO, IPA, and GSEA enrichments were done to explore regulatory mechanisms and functions. Results: A total of 22 DNA pols were identified to have a potential to diagnostic value, and 10 DNA pols have a pan-cancer prognostic value under various stages, and cancer type, among which overexpression of 6 DNA-pols (POLA2, POLD1, POLD2, POLE2, POLE4, and POLQ) was found to be significantly related to worse outcomes regarding OS, while 4 DNA-pols (POLH, POLL, POLN, and REV1) significantly related to better outcomes. A 5-DNA pols based risk score (POLQ, POLD2, POLL, POLH, and REV1) was generated by MultiCox regression with a nomogram validated an accurate predictive efficacy. MYB Proto-Oncogene Like 2 (MYBL2) was identified as transcription factors of prognostic DNA pols in pan-cancer, and IPA mimic experiment reveals inhibiting MYBL2 could be a drug target to recover and balance the dysregulated expression pattern of DNA pols in pan-cancer. GO, IPA, and GSEA enrichments revealed functions and pathways altered by DNA pols in cancer, and the results were supported by pan-cancer cell sequencing data. Conclusions: DNA pols have a pan-cancer clinical value and can work as potential prognostic biomarkers. Furthermore, MYBL2 could be a drug target for pan-cancer.

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Comprehensive Analysis of Differential Immunocyte Infiltration and Potential ceRNA Networks Involved in the Development of Atrial Fibrillation

BioMed Research International ◽

10.1155/2020/8021208 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Jiafeng Wu ◽

Huiming Deng ◽

Qianghua Chen ◽

Qiang Wu ◽

Xiaolong Li ◽

...

Keyword(s):

Atrial Fibrillation ◽

Dna Methylation ◽

Left Atrial ◽

Molecular Mechanisms ◽

Linear Models ◽

Core Gene ◽

Differential Analysis ◽

Methylation Analysis ◽

Protein Protein Interaction ◽

Dna Methylation Analysis

This study is aimed at identifying potential molecular mechanisms and candidate biomarkers in the left atrial regions for the diagnosis and treatment of valvular atrial fibrillation (VAF). Multibioinformatics methods, including linear models for microarray analysis (LIMMA), an SVA algorithm, CIBERSORT immune infiltration, and DNA methylation analysis, were employed. In addition, the protein-protein interaction (PPI) network, Gene Ontology (GO), and molecular pathways of differentially expressed genes (DEGs) or differential methylation regions were constructed. In all, compared with the normal rhythm group, 243 different mRNAs (29 downregulated and 214 upregulated) and 26 different lncRNAs (3 downregulated and 23 upregulated) were detected in the left atrium (LA) of atrial fibrillation (AF) patients, and the neutrophil and CD8+ T cell were infiltrated. Additionally, 199 different methylation sites (107 downregulated and 92 upregulated) were also identified based on DNA methylation analysis. After integration, ELOVL2, CCR2, and WEE1 were detected for differentially methylated and differentially transcribed genes. Among them, WEE1 was also a core gene identified by the competing endogenous RNA (ceRNA) network that included WEE1-KRBOX1-AS1-hsa-miR-17-5p, in VAF left atrial tissue. We combined the DNA methylation and transcriptional expression differential analysis and found that WEE1 (cg13365543) may well be a candidate gene regulated by DNA methylation modification. Moreover, KRBOX1-AS1 and WEE1 can compete endogenously and may mediate myocardial tissue infiltration into CD8+ T cells and participate in the AF process.

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Deep Learning Based Tumor Type Classification Using Gene Expression Data

10.1101/364323 ◽

2018 ◽

Cited By ~ 4

Author(s):

Boyu Lyu ◽

Anamul Haque

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Tumor Type ◽

Differential Analysis ◽

Rna Seq ◽

Heat Map ◽

Standard Practices ◽

Tumor Types ◽

Pan Cancer

ABSTRACTDifferential analysis occupies the most significant portion of the standard practices of RNA-Seq analysis. However, the conventional method is matching the tumor samples to the normal samples, which are both from the same tumor type. The output using such method would fail in differentiating tumor types because it lacks the knowledge from other tumor types. Pan-Cancer Atlas provides us with abundant information on 33 prevalent tumor types which could be used as prior knowledge to generate tumor-specific biomarkers. In this paper, we embedded the high dimensional RNA-Seq data into 2-D images and used a convolutional neural network to make classification of the 33 tumor types. The final accuracy we got was 95.59%, higher than another paper applying GA/KNN method on the same dataset. Based on the idea of Guided Grad Cam, as to each class, we generated significance heat-map for all the genes. By doing functional analysis on the genes with high intensities in the heat-maps, we validated that these top genes are related to tumor-specific pathways, and some of them have already been used as biomarkers, which proved the effectiveness of our method. As far as we know, we are the first to apply convolutional neural network on Pan-Cancer Atlas for classification, and we are also the first to match the significance of classification with the importance of genes. Our experiment results show that our method has a good performance and could also apply in other genomics data.

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Genomic events shaping epithelial-to-mesenchymal trajectories in cancer

10.21203/rs.3.rs-754194/v1 ◽

2021 ◽

Author(s):

Guidantonio Tagliazucchi ◽

Maria Secrier

Keyword(s):

Cancer Progression ◽

Epithelial To Mesenchymal Transition ◽

Evolutionary Constraints ◽

Breast Cancers ◽

Driver Genes ◽

Mesenchymal Transition ◽

Therapeutic Value ◽

Intermediate States ◽

Mesenchymal Transformation ◽

Pan Cancer

Abstract The epithelial to mesenchymal transition (EMT) is a key cellular process underlying cancer progression, with multiple intermediate states whose molecular hallmarks remain poorly characterized. To fill this gap, we explored EMT trajectories in 8,778 tumours of epithelial origin and identified three macro-states with prognostic and therapeutic value, attributable to epithelial, hybrid E/M (hEMT) and mesenchymal phenotypes. We show that the hEMT state is remarkably stable and linked with increased aneuploidy, APOBEC mutagenesis and hypoxia. Additionally, we provide an extensive catalogue of genomic events underlying distinct evolutionary constraints on EMT transformation, including novel pan-cancer dependencies of hEMT on driver genes PRRX1, BCOR and CNOT3, as well as links between full mesenchymal transformation and REG3A and SHISA4 mutations in lung and breast cancers, respectively. This study sheds light on the aetiology of the lesser characterised hybrid E/M state in cancer progression and the broader genomic hallmarks shaping the mesenchymal transformation of primary tumours.

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Abstract 3303: A comprehensive TCGA Pan-Cancer molecular study of gynecologic and breast cancers

10.1158/1538-7445.am2018-3303 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ashton Berger ◽

Anil Korkut ◽

Rupa S. Kanchi ◽

TCGA Pan-Gynecologic Group and Rese Network ◽

Gordon B. Mills ◽

...

Keyword(s):

Molecular Study ◽

Breast Cancers ◽

Pan Cancer

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A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers

Cancer Cell ◽

10.1016/j.ccell.2018.03.014 ◽

2018 ◽

Vol 33 (4) ◽

pp. 690-705.e9 ◽

Cited By ~ 152

Author(s):

Ashton C. Berger ◽

Anil Korkut ◽

Rupa S. Kanchi ◽

Apurva M. Hegde ◽

Walter Lenoir ◽

...

Keyword(s):

Molecular Study ◽

Breast Cancers ◽

Pan Cancer

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Multi-omics analysis reveals prognostic value of tumor mutation burden in hepatocellular carcinoma

Cancer Cell International ◽

10.1186/s12935-021-02049-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Qianhui Xu ◽

Hao Xu ◽

Rongshan Deng ◽

Zijie Wang ◽

Nanjun Li ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Risk Score ◽

Enrichment Analysis ◽

R Package ◽

Immune Checkpoint Blockade ◽

Differential Analysis ◽

Bioinformatics Analyses ◽

Tumor Mutation Burden ◽

Mutation Burden

Abstract Background Hepatocellular carcinoma (HCC) was the sixth common malignancies characteristic with highly aggressive in the world. It was well established that tumor mutation burden (TMB) act as indicator of immunotherapeutic responsiveness in various tumors. However, the role of TMB in tumor immune microenvironment (TIME) is still obscure. Method The mutation data was analyzed by employing “maftools” package. Weighted gene co-expression network analysis (WGCNA) was implemented to determine candidate module and significant genes correlated with TMB value. Differential analysis was performed between different level of TMB subgroups employing R package “limma”. Gene ontology (GO) enrichment analysis was implemented with “clusterProfiler”, “enrichplot” and “ggplot2” packages. Then risk score signature was developed by systematical bioinformatics analyses. K-M survival curves and receiver operating characteristic (ROC) plot were further analyzed for prognostic validity. To depict comprehensive context of TIME, XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT, and CIBERSORT-ABS algorithm were employed. Additionally, the potential role of risk score on immune checkpoint blockade (ICB) immunotherapy was further explored. The quantitative real-time polymerase chain reaction was performed to detect expression of HTRA3. Results TMB value was positively correlated with older age, male gender and early T status. A total of 75 intersection genes between TMB-related genes and differentially expressed genes (DEGs) were screened and enriched in extracellular matrix-relevant pathways. Risk score based on three hub genes significantly affected overall survival (OS) time, infiltration of immune cells, and ICB-related hub targets. The prognostic performance of risks score was validated in the external testing group. Risk-clinical nomogram was constructed for clinical application. HTRA3 was demonstrated to be a prognostic factor in HCC in further exploration. Finally, mutation of TP53 was correlated with risk score and do not interfere with risk score-based prognostic prediction. Conclusion Collectively, a comprehensive analysis of TMB might provide novel insights into mutation-driven mechanism of tumorigenesis further contribute to tailored immunotherapy and prognosis prediction of HCC.

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Comprehensive Pan-Cancer Analysis and the Regulatory Mechanism of ASF1B, a Gene Associated With Thyroid Cancer Prognosis in the Tumor Micro-Environment

Frontiers in Oncology ◽

10.3389/fonc.2021.711756 ◽

2021 ◽

Vol 11 ◽

Author(s):

Jing Ma ◽

Wei Han ◽

Kai Lu

Keyword(s):

Gene Expression ◽

Survival Analysis ◽

Thyroid Cancer ◽

Prognostic Marker ◽

Enrichment Analysis ◽

Differential Analysis ◽

Expression Levels ◽

Multiple Cancers ◽

Mtorc1 Signaling ◽

Pan Cancer

BackgroundThe incidence of thyroid cancer, whose local recurrence and metastasis lead to death, has always been high and the pathogenesis of papillary thyroid carcinoma (PTC) has not been clearly elucidated. Therefore, the research for more accurate prognosis-related predictive biomarkers is imminent, and a key gene can often be a prognostic marker for multiple tumors.MethodsGene expression profiles of various cancers in the TCGA and GTEx databases were downloaded, and genes significantly associated with the prognosis of THCA were identified by combining differential analysis with survival analysis. Then, a series of bioinformatics tools and methods were used to analyze the expression of the gene in each cancer and the correlation of each expression with prognosis, tumor immune microenvironment, immune neoantigens, immune checkpoints, DNA repair genes, and methyltransferases respectively. The possible biological mechanisms were also investigated by GSEA enrichment analysis.Results656 differentially expressed genes were identified from two datasets and 960 DEGs that were associated with disease-free survival in THCA patients were screened via survival analysis. The former and the latter were crossed to obtain 7 key genes, and the gene with the highest risk factor, ASF1B, was selected for this study. Differential analysis of multiple databases showed that ASF1B was commonly and highly expressed in pan-cancer. Survival analysis showed that high ASF1B expression was significantly associated with poor patient prognosis in multiple cancers. In addition, ASF1B expression levels were found to be associated with tumor immune infiltration in THCA, KIRC, LGG, and LIHC, and with tumor microenvironment in BRCA, LUSC, STAD, UCEC, and KIRC. Further analysis of the relationship between ASF1B expression and immune checker gene expression suggested that ASF1B may regulate tumor immune patterns in most tumors by regulating the expression levels of specific immune checker genes. Finally, GSEA enrichment analysis showed that ASF1B high expression was mainly enriched in cell cycle, MTORC1 signaling system, E2F targets, and G2M checkpoints pathways.ConclusionsASF1B may be an independent prognostic marker for predicting the prognosis of THCA patients. The pan-cancer analysis suggested that ASF1B may play an important role in the tumor micro-environment and tumor immunity and it has the potential of serving as a predictive biomarker for multiple cancers.

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