scholarly journals Transcriptomic and Mutational Analysis Discovering Distinct Molecular Characteristics Among Chinese Thymic Epithelial Tumor Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Naixin Liang ◽  
Lei Liu ◽  
Cheng Huang ◽  
Hongsheng Liu ◽  
Chao Guo ◽  
...  
Keyword(s):  
Mutational Analysis ◽  
Developmental Process ◽  
Expression Profiles ◽  
Molecular Data ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Molecular Characteristics ◽  
Epithelial Tumor ◽  
Thymic Epithelial Tumors ◽  
Underlying Mechanisms

IntroductionThymic epithelial tumors (TETs) are malignancies arising from the epithelium of the thymic gland, rare but with relatively favorable prognosis. TETs have different pathological subtypes: thymomas and thymic carcinoma, and they show different clinical characteristics regarding prognosis, pathology, and molecular profiles, etc. Although some studies have investigated the pathogenesis of TETs, more molecular data is still needed to further understand the underlying mechanisms among different TETs subtypes and populations.MethodsIn this study, we performed targeted gene panel sequencing and whole transcriptome sequencing on the tumor tissues from 27 Chinese TET patients, including 24 thymomas (A, AB, and B subtypes) and 3 thymic squamous cell carcinomas. We analyzed the genetic variations and differentially expressed genes among multiple TET subtypes. Moreover, we compared our data with the published The Cancer Genome Atlas (TCGA) TET data on both the genetic and transcriptomic levels.ResultsCompared with the TCGA TET genomic data, we found that NF1 and ATM were the most frequently mutated genes (each with a frequency of 11%, 3/27). These mutations were not mutually exclusive, since one B1 thymoma showed mutations of both genes. The GTF2I mutation was mainly enriched in subtype A and AB thymomas, consistent with the previous reports. RNA-seq results unveiled that the genes related to thymus development (FGF7, FGF10 and CLDN4) were highly expressed in certain TET subtypes, implicating that the developmental process of thymus might be linked to the tumorigenesis of these subtypes. We found high expression of CD274 (PD-L1) in B2 and B3 thymoma samples, and validated its expression using immunohistochemistry (IHC). Based on the expression profiles, we further established a machine learning model to predict the myasthenia gravis status of TET patients and achieved 90% sensitivity and 70.6% specificity in the testing cohort.ConclusionThis study provides the first genomic and transcriptomic analysis of a Chinese TET cohort. The high expression of genes involved in thymus developmental processes suggests the potential association between tumorigenesis of TETs and dysregulation of developmental pathways. The high expression of PD-L1 in B2 and B3 thymomas support the potential application of immunotherapy on certain thymoma subtypes.

scholarly journals The Cancer Genome Atlas expression profiles of low-grade gliomas

2014 ◽  
Vol 36 (4) ◽  
pp. E23 ◽  
Author(s):  
David D. Gonda ◽  
Vincent J. Cheung ◽  
Karra A. Muller ◽  
Amit Goyal ◽  
Bob S. Carter ◽  
...  
Keyword(s):  
Cpg Island ◽  
Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Low Grade ◽  
Cpg Island Methylator Phenotype ◽  
Low Grade Gliomas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Differentiating between low-grade gliomas (LGGs) of astrocytic and oligodendroglial origin remains a major challenge in neurooncology. Here the authors analyzed The Cancer Genome Atlas (TCGA) profiles of LGGs with the goal of identifying distinct molecular characteristics that would afford accurate and reliable discrimination of astrocytic and oligodendroglial tumors. They found that 1) oligodendrogliomas are more likely to exhibit the glioma-CpG island methylator phenotype (G-CIMP), relative to low-grade astrocytomas; 2) relative to oligodendrogliomas, low-grade astrocytomas exhibit a higher expression of genes related to mitosis, replication, and inflammation; and 3) low-grade astrocytic tumors harbor microRNA profiles similar to those previously described for glioblastoma tumors. Orthogonal intersection of these molecular characteristics with existing molecular markers, such as IDH1 mutation, TP53 mutation, and 1p19q status, should facilitate accurate and reliable pathological diagnosis of LGGs.

scholarly journals Prognostic Implications of Alcohol Dehydrogenases Inhepatocellular Carcinoma

2020 ◽  
Author(s):  
Xiangye Liu ◽  
Delong Kong ◽  
Tingting Li ◽  
Hongjuan You ◽  
Fanyun Kong ◽  
...  
Keyword(s):  
Cox Regression ◽  
Expression Profiles ◽  
Normal Liver ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Good Survival ◽  
Oncogenic Signaling ◽  
Alcohol Dehydrogenases ◽  
Incidence And Mortality ◽  
Prognostic Implications

Abstract Background Hepatocellular carcinoma (HCC) is a malignancy with high incidence and mortality rates worldwide. Alcohol dehydrogenases (ADHs) are huge family of dehydrogenase enzymes and associated with the prognosis of various cancers. However, comprehensive analysis of prognostic implications related to ADHs in HCC is still lacking and largely unknown. Results In our study, the expression profiles and corresponding clinical information of HCC from The Cancer Genome Atlas (TCGA) were used to evaluate the association between ADHs and outcomes of the patients. We found that the expression of ADH1A, ADH1B, ADH1C, ADH4, and ADH6 was significantly downregulated in HCC samples compared to normal liver samples. Our univariate and multivariate Cox regression analyses results showed that high expression of ADH1A, ADH1B, ADH1C, ADH4, and ADH6 was considered as an independent factor with an improved prognosis for the survival of HCC patients. Moreover, our Kaplan-Meier analysis results also revealed that high expression of AHD1A, ADH1B, ADH1C, ADH4, and ADH6 was significantly associated with good survival rate in HCC patients. In addition, GO, KEGG, and GSEA analyses unveiled several oncogenic signaling pathways were negatively associated high expression of ADHs in HCC. Conclusion Overall, our results provide the potential prognostic biomarkers or molecular targets for the patients with HCC.

scholarly journals Comprehensive Analysis of Differentially Expressed Profiles of lncRNAs/mRNAs and miRNAs with Associated ceRNA Networks in Triple-Negative Breast Cancer

2018 ◽  
Vol 50 (2) ◽  
pp. 473-488 ◽  
Author(s):  
Rui Yang ◽  
Lei Xing ◽  
Min Wang ◽  
Hong Chi ◽  
Luyu Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Large Scale ◽  
Triple Negative ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Malignant Breast ◽  
Underlying Mechanisms

Background/Aims: Triple-negative breast cancer (TNBC) is a subtype of highly malignant breast cancer with poor prognosis. Growing evidence indicates that Long noncoding RNAs (lncRNAs) play important regulatory roles in the development and progression of a variety of cancers including breast cancer. However, the underlying mechanisms remain largely unknown. Methods: Here, we compared the expression profiles of mRNAs, lncRNAs and miRNAs between 111 TNBC tissues and 104 non-cancerous tissues utilizing RNA-Seq Data from The Cancer Genome Atlas (TCGA). Gene Ontology and KEGG pathway enrichment analyses were executed to investigate the principal functions of the significantly dysregulated mRNAs. Moreover, Kaplan-Meier survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs on overall survival. Subsequently, we constructed a competing endogenous RNA (ceRNA) network, which included 66 dysregulated lncRNAs, 24 miRNAs and 55 mRNAs. The four dysregulated lncRNAs, three aberrantly expressed miRNAs and four mRNAs were confirmed in the ceRNA network by qRT-PCR in 30 pairs of samples, respectively. Results: A total of 1441 lncRNAs, 114 miRNA and 2501 mRNAs were found to be differentially expressed in TNBC tissues compared with controls. 109 lncRNAs and 124 mRNAs might serve as prognostic signature for patients with TNBC according to the survival analysis. Functional analysis revealed that 19 mRNAs in the ceRNA network were enriched in 17 cancer-related pathways. Conclusion: Taken together, we identified novel lncRNAs/miRNAs which may serve as potential biomarkers to predict the survival and therapeutic targets for TNBC patients based on a large-scale sample. More importantly, we constructed the ceRNA network of TNBC, which provides valuable information to further explore the molecular mechanism underlying tumorigenesis and development of TNBC.

scholarly journals Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Jin-Cheng Guo ◽  
Qing-Shuang Wei ◽  
Lei Dong ◽  
Shuang-Sang Fang ◽  
Feng Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Lower Grade ◽  
Cox Regression Analysis ◽  
Tcga Dataset ◽  
Genome Atlas

Background: Molecular characteristics can be good indicators of tumor prognosis and have been introduced into the classification of gliomas. The prognosis of patients with newly classified lower-grade gliomas (LGGs, including grade 2 and grade 3 gliomas) is highly heterogeneous, and new molecular markers are urgently needed.Methods: Autophagy related genes (ATGs) were obtained from Human Autophagy Database (HADb). From the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), gene expression profiles including ATG expression information and patient clinical data were downloaded. Cox regression analysis, receiver operating characteristic (ROC) analysis, Kaplan–Meier analysis, random survival forest algorithm (RSFVH) and stratification analysis were performed.Results: Through univariate Cox regression analysis, we found a total of 127 ATGs associated with the prognosis of LGG patients from TCGA dataset and a total of 131 survival-related ATGs from CGGA dataset. Using TCGA dataset as the training group (n = 524), we constructed a five-ATG signature (including BAG1, BID, MAP1LC3C, NRG3, PTK6), which could divide LGG patients into two risk groups with significantly different overall survival (Log Rank P < 0.001). Then we confirmed in the independent CGGA dataset that the five-ATG signature had the ability to predict prognosis (n = 431, Log Rank P < 0.001). We further discovered that the predictive ability of the five-ATG signature was better than the existing clinical indicators and IDH mutation status. In addition, the five-ATG signature could further classify patients after receiving radiotherapy or chemotherapy into groups with different prognosis.Conclusions: We identified a five-ATG signature that could be a reliable prognostic marker and might be therapeutic targets for autophagy therapy for LGG patients.

scholarly journals Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7436 ◽  
Author(s):  
Ze-Kun Liu ◽  
Ren-Yu Zhang ◽  
Yu-Le Yong ◽  
Zhi-Yun Zhang ◽  
Can Li ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Molecular Mechanisms ◽  
Rho Gtpase ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
High Expression ◽  
Pcr Analysis ◽  
Chronic Hepatitis B Virus

Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant cancers with no effective targets and treatments. However, the molecular pathogenesis of HCC remains largely uncertain. The aims of our study were to find crucial genes involved in HCC through multidimensional methods and revealed potential molecular mechanisms. Here, we reported the gene expression profile GSE121248 findings from 70 HCC and 37 adjacent normal tissues, all of which had chronic hepatitis B virus (HBV) infection, we were seeking to identify the dysregulated pathways, crucial genes and therapeutic targets implicated in HBV-associated HCC. We found 164 differentially expressed genes (DEGs) (92 downregulated genes and 72 upregulated genes). Gene ontology (GO) analysis of DEGs revealed significant functional enrichment of mitotic nuclear division, cell division, and the epoxygenase P450 pathway. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the DEGs were mainly enriched in metabolism, cell cycle regulation and the p53 signaling pathway. The Mcode plugin was calculated to construct a module complex of DEGs, and the module was mainly enriched in cell cycle checkpoints, RHO GTPase effectors and cytochrome P450. Considering a weak contribution of each gene, gene set enrichment analysis (GSEA) was performed, revealing results consistent with those described above. Six crucial proteins were selected based on the degree of centrality, including NDC80, ESR1, ZWINT, NCAPG, ENO3 and CENPF. Real-time quantitative PCR analysis validated the six crucial genes had the same expression trend as predicted. Furthermore, the methylation data of The Cancer Genome Atlas (TCGA) with HCC showed that mRNA expression of crucial genes was negatively correlated with methylation levels of their promoter region. The overall survival reflected that high expression of NDC80, CENPF, ZWINT, and NCAPG significantly predicted poor prognosis, whereas ESR1 high expression exhibited a favorable prognosis. The identification of the crucial genes and pathways would contribute to the development of novel molecular targets and biomarker-driven treatments for HCC.

scholarly journals Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ping Yan ◽  
Zuotian Huang ◽  
Tong Mou ◽  
Yunhai Luo ◽  
Yanyao Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Clinical Information ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Competing Endogenous Rna ◽  
Tissue Samples ◽  
Potential Biomarkers

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

scholarly journals Iron-Bound Lipocalin-2 from Tumor-Associated Macrophages Drives Breast Cancer Progression Independent of Ferroportin

Metabolites ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 180
Author(s):  
Christina Mertens ◽  
Matthias Schnetz ◽  
Claudia Rehwald ◽  
Stephan Grein ◽  
Eiman Elwakeel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Progression ◽  
Tumor Cells ◽  
Cancer Progression ◽  
Lung Metastases ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Lipocalin 2 ◽  
Tumor Associated Macrophages

Macrophages supply iron to the breast tumor microenvironment by enforced secretion of lipocalin-2 (Lcn-2)-bound iron as well as the increased expression of the iron exporter ferroportin (FPN). We aimed at identifying the contribution of each pathway in supplying iron for the growing tumor, thereby fostering tumor progression. Analyzing the expression profiles of Lcn-2 and FPN using the spontaneous polyoma-middle-T oncogene (PyMT) breast cancer model as well as mining publicly available TCGA (The Cancer Genome Atlas) and GEO Series(GSE) datasets from the Gene Expression Omnibus database (GEO), we found no association between tumor parameters and Lcn-2 or FPN. However, stromal/macrophage-expression of Lcn-2 correlated with tumor onset, lung metastases, and recurrence, whereas FPN did not. While the total iron amount in wildtype and Lcn-2−/− PyMT tumors showed no difference, we observed that tumor-associated macrophages from Lcn-2−/− compared to wildtype tumors stored more iron. In contrast, Lcn-2−/− tumor cells accumulated less iron than their wildtype counterparts, translating into a low migratory and proliferative capacity of Lcn-2−/− tumor cells in a 3D tumor spheroid model in vitro. Our data suggest a pivotal role of Lcn-2 in tumor iron-management, affecting tumor growth. This study underscores the role of iron for tumor progression and the need for a better understanding of iron-targeted therapy approaches.

Redescription and synonymization of Oscheius citri Tabassum, Shahina, Nasira and Erum, 2016 (Rhabditida, Rhabditidae) from India and its taxonomical consequences

2021 ◽  
Vol 95 ◽  
Author(s):  
A. Rana ◽  
A.H. Bhat ◽  
A.K. Chaubey ◽  
V. Půža ◽  
J. Abolafia
Keyword(s):  
Indian Population ◽  
Uttar Pradesh ◽  
Nematode Species ◽  
Molecular Data ◽  
Molecular Characteristics ◽  
Morphometric Characteristics ◽  
High Similarity ◽  
Rdna Sequences ◽  
Indian Strain ◽  
28S Rdna Sequences

Abstract A population of a nematode species belonging to the genus Oscheius was isolated in western Uttar Pradesh, India. Morphological and morphometrical studies on this species showed its high similarity with six species described previously from Pakistan (Oscheius citri, O. cobbi, O. cynodonti, O. esculentus, O. punctatus and O. sacchari). The molecular analysis of the ITS1-5.8S-ITS2 rDNA sequences of the Indian population and the six species described from Pakistan showed that all the sequences are almost identical. Thus, based on morphological and molecular characteristics, all of the six above-mentioned Pakistani species and Indian strain do not differ from each other, hence can be considered synonyms. The correct name for this taxon is the first described species O. citri. Additionally, the phylogenetic analysis of the 18S rDNA and the 28S rDNA sequences showed that Oscheius citri is sister to the clade formed by O. chongmingensis and O. rugaoensis from China. The high similarity of morphological and morphometric characteristics of O. citri and other species, O. maqbooli, O. nadarajani, O. niazii, O. shamimi and O. siddiqii, suggest their conspecificity; however, lack of molecular data for these species does not allow this hypothesis to be tested.

scholarly journals Comprehensive analysis of IgA nephropathy expression profiles: identification of potential biomarkers and therapeutic agents

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Alieh Gholaminejad ◽  
Yousof Gheisari ◽  
Sedigheh Jalali ◽  
Amir Roointan
Keyword(s):  
Iga Nephropathy ◽  
Regulatory Network ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
Integrative Approach ◽  
Potential Factors ◽  
Ngf Signaling ◽  
Underlying Mechanisms

Abstract Background IgA nephropathy (IgAN) is a kidney disease recognized by the presence of IgA antibody depositions in kidneys. The underlying mechanisms of this complicated disease are remained to be explored and still, there is an urgent need for the discovery of noninvasive biomarkers for its diagnosis. In this investigation, an integrative approach was applied to mRNA and miRNA expression profiles in PBMCs to discover a gene signature and novel potential targets/biomarkers in IgAN. Methods Datasets were selected from gene expression omnibus database. After quality control checking, two datasets were analyzed by Limma to identify differentially expressed genes/miRNAs (DEGs and DEmiRs). Following identification of DEmiR-target genes and data integration, intersecting mRNAs were subjected to different bioinformatic analyses. The intersecting mRNAs, DEmiRs, related transcription factors (from TRRUST database), and long-non coding RNAs (from LncTarD database) were used for the construction of a multilayer regulatory network via Cytoscape. Result “GSE25590” (miRNA) and “GSE73953” (mRNA) datasets were analyzed and after integration, 628 intersecting mRNAs were identified. The mRNAs were mainly associated with “Innate immune system”, “Apoptosis”, as well as “NGF signaling” pathways. A multilayer regulatory network was constructed and several hub-DEGs (Tp53, STAT3, Jun, etc.), DEmiRs (miR-124, let-7b, etc.), TFs (NF-kB, etc.), and lncRNAs (HOTAIR, etc.) were introduced as potential factors in the pathogenesis of IgAN. Conclusion Integration of two different expression datasets and construction of a multilayer regulatory network not only provided a deeper insight into the pathogenesis of IgAN, but also introduced several key molecules as potential therapeutic target/non-invasive biomarkers.

scholarly journals Screening of gene markers related to the prognosis of metastatic skin cutaneous melanoma based on Logit regression and survival analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Guoliang Jia ◽  
Zheyu Song ◽  
Zhonghang Xu ◽  
Youmao Tao ◽  
Yuanyu Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cutaneous Melanoma ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Validation Dataset ◽  
Survival Prognosis ◽  
Gene Markers ◽  
Clinical Prognosis ◽  
Logit Regression

Abstract Background Bioinformatics was used to analyze the skin cutaneous melanoma (SKCM) gene expression profile to provide a theoretical basis for further studying the mechanism underlying metastatic SKCM and the clinical prognosis. Methods We downloaded the gene expression profiles of 358 metastatic and 102 primary (nonmetastatic) CM samples from The Cancer Genome Atlas (TCGA) database as a training dataset and the GSE65904 dataset from the National Center for Biotechnology Information database as a validation dataset. Differentially expressed genes (DEGs) were screened using the limma package of R3.4.1, and prognosis-related feature DEGs were screened using Logit regression (LR) and survival analyses. We also used the STRING online database, Cytoscape software, and Database for Annotation, Visualization and Integrated Discovery software for protein–protein interaction network, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses based on the screened DEGs. Results Of the 876 DEGs selected, 11 (ZNF750, NLRP6, TGM3, KRTDAP, CAMSAP3, KRT6C, CALML5, SPRR2E, CD3G, RTP5, and FAM83C) were screened using LR analysis. The survival prognosis of nonmetastatic group was better compared to the metastatic group between the TCGA training and validation datasets. The 11 DEGs were involved in 9 KEGG signaling pathways, and of these 11 DEGs, CALML5 was a feature DEG involved in the melanogenesis pathway, 12 targets of which were collected. Conclusion The feature DEGs screened, such as CALML5, are related to the prognosis of metastatic CM according to LR. Our results provide new ideas for exploring the molecular mechanism underlying CM metastasis and finding new diagnostic prognostic markers.

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