scholarly journals Identification of Differentially Expressed Genes and Prognostic Biomarkers of Breast Cancer Based on RNA-Seq and KEGG Pathway Network

2016 ◽  
Author(s):  
S.M. Zhang ◽  
Y. Gu ◽  
S.Y. Wu ◽  
Y. Kang ◽  
S. Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Differentially Expressed Genes ◽  
Kegg Pathway ◽  
Differentially Expressed ◽  
Prognostic Biomarkers ◽  
Rna Seq ◽  
Pathway Network

Evaluation of gene expression by RNA-seq after single dose of trastuzumab (T) reveals predictors of pathologic complete response (pCR) in HER2-positive early breast cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10558-10558 ◽  
Author(s):  
Natalie Galanina ◽  
Emmet Sprecher ◽  
Veerle Bossuyt ◽  
Sudipa Sarkar ◽  
Ian E. Krop ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Single Dose ◽  
Differentially Expressed Genes ◽  
Early Breast Cancer ◽  
Single Agent ◽  
Pathologic Complete Response ◽  
Differentially Expressed ◽  
Illumina Genome Analyzer ◽  
Rna Seq

10558 Background: The use of a ‘brief exposure’ to single agent T allows the measurement of dynamic changes in the transcriptome that may predict response to T-based combinations. We have shown that most gene expression changes in HER2+ tumors treated with T occur in tumors that ultimately achieve a pCR. Our further analysis suggests several patterns of transcriptional change in pCR tumors suggesting different mechanisms of action of T. RNA-seq analysis provides more in-depth annotation of these mechanisms. Methods: Fresh tumor core biopsies were taken at a 2 week time point after a single dose of T (8mg/m2) from 80 HER2+ early breast cancer patients enrolled on a clinical trial of T>T+C. Nucleic acids were extracted using Qiagen AllPrep and were analyzed with Illumina HT12v3 Beadchip and Illumina 610 QUAD V1 SNP arrays. RNA was also processed for sequencing using the Ovation RNA-Seq System and paired-end sequenced using an Illumina Genome Analyzer IIxRNA-seq data was analyzed with Tophat/Cufflinks. Network analysis was performed with Metacore. Results: Among pCR tumors, distinct patterns of differential expression pre/post T were observed, in both microarray and RNA-seq data. ERBB2 down-regulation was characteristic of pCR in one subgroup by microarray. In this group, differentially expressed genes belonged to interaction networks involved in apoptosis and cell cycle regulation. In contrast, tumors with no change in ErbB2 showed differentially expressed genes that belonged to networks related to chromatin assembly and regulation of immune pathways. NOLC1, RPL41, ZCHHC17, and B2M had altered alternative splicing product distributions in both groups. In the ERBB2 down-regulated group, genes with changed expression were enriched for targets of STAT3 and YY1. Conclusions: RNA-seq and microarray reveal distinct responses in tumors that achieve pCR to T-containing regimens. These methods provide predictive markers for validation in subsequent clinical trials.

scholarly journals Transcriptomic Profiling Identifies Differentially Expressed Genes in Palbociclib-Resistant ER+ MCF7 Breast Cancer Cells

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 467 ◽  
Author(s):  
Lilibeth Lanceta ◽  
Conor O'Neill ◽  
Nadiia Lypova ◽  
Xiahong Li ◽  
Eric Rouchka ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Differentially Expressed Genes ◽  
Pathway Analysis ◽  
Metabolic Pathways ◽  
Acquired Resistance ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Kegg Database ◽  
Cyclin Dependent Kinases ◽  
Estrogen Receptor Positive

Acquired resistance to cyclin-dependent kinases 4 and 6 (CDK4/6) inhibition in estrogen receptor-positive (ER+) breast cancer remains a significant clinical challenge. Efforts to uncover the mechanisms underlying resistance are needed to establish clinically actionable targets effective against resistant tumors. In this study, we sought to identify differentially expressed genes (DEGs) associated with acquired resistance to palbociclib in ER+ breast cancer. We performed next-generation transcriptomic RNA sequencing (RNA-seq) and pathway analysis in ER+ MCF7 palbociclib-sensitive (MCF7/pS) and MCF7 palbociclib-resistant (MCF7/pR) cells. We identified 2183 up-regulated and 1548 down-regulated transcripts in MCF7/pR compared to MCF7/pS cells. Functional analysis of the DEGs using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database identified several pathways associated with breast cancer, including ‘cell cycle’, ‘DNA replication’, ‘DNA repair’ and ‘autophagy’. Additionally, Ingenuity Pathway Analysis (IPA) revealed that resistance to palbociclib is closely associated with deregulation of several key canonical and metabolic pathways. Further studies are needed to determine the utility of these DEGs and pathways as therapeutics targets against ER+ palbociclib-resistant breast cancer.

scholarly journals Transcriptome Analysis of a Cotton Cultivar Provides Insights into the Differentially Expressed Genes Underlying Heightened Resistance to the Devastating Verticillium Wilt

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2961
Author(s):  
He Zhu ◽  
Jian Song ◽  
Nikhilesh Dhar ◽  
Ying Shan ◽  
Xi-Yue Ma ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Verticillium Wilt ◽  
Kegg Pathway ◽  
Fiber Quality ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Go Enrichment ◽  
Serious Disease ◽  
Insight Into ◽  
Cotton Cultivar

Cotton is an important economic crop worldwide. Verticillium wilt (VW) caused by Verticillium dahliae (V. dahliae) is a serious disease in cotton, resulting in massive yield losses and decline of fiber quality. Breeding resistant cotton cultivars is an efficient but elaborate method to improve the resistance of cotton against V. dahliae infection. However, the functional mechanism of several excellent VW resistant cotton cultivars is poorly understood at present. In our current study, we carried out RNA-seq to discover the differentially expressed genes (DEGs) in the roots of susceptible cotton Gossypium hirsutum cultivar Junmian 1 (J1) and resistant cotton G.hirsutum cultivar Liaomian 38 (L38) upon Vd991 inoculation at two time points compared with the mock inoculated control plants. The potential function of DEGs uniquely expressed in J1 and L38 was also analyzed by GO enrichment and KEGG pathway associations. Most DEGs were assigned to resistance-related functions. In addition, resistance gene analogues (RGAs) were identified and analyzed for their role in the heightened resistance of the L38 cultivar against the devastating Vd991. In summary, we analyzed the regulatory network of genes in the resistant cotton cultivar L38 during V. dahliae infection, providing a novel and comprehensive insight into VW resistance in cotton.

scholarly journals Aligning the Aligners: Comparison of RNA Sequencing Data Alignment and Gene Expression Quantification Tools for Clinical Breast Cancer Research

2019 ◽  
Vol 9 (2) ◽  
pp. 18 ◽  
Author(s):  
Isaac D. Raplee ◽  
Alexei V. Evsikov ◽  
Caralina Marín de Evsikova
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Research ◽  
Rna Sequencing ◽  
Differentially Expressed Genes ◽  
Ductal Carcinoma ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Bioinformatics Tools ◽  
Ffpe Samples

The rapid expansion of transcriptomics and affordability of next-generation sequencing (NGS) technologies generate rocketing amounts of gene expression data across biology and medicine, including cancer research. Concomitantly, many bioinformatics tools were developed to streamline gene expression and quantification. We tested the concordance of NGS RNA sequencing (RNA-seq) analysis outcomes between two predominant programs for read alignment, HISAT2, and STAR, and two most popular programs for quantifying gene expression in NGS experiments, edgeR and DESeq2, using RNA-seq data from breast cancer progression series, which include histologically confirmed normal, early neoplasia, ductal carcinoma in situ and infiltrating ductal carcinoma samples microdissected from formalin fixed, paraffin embedded (FFPE) breast tissue blocks. We identified significant differences in aligners’ performance: HISAT2 was prone to misalign reads to retrogene genomic loci, STAR generated more precise alignments, especially for early neoplasia samples. edgeR and DESeq2 produced similar lists of differentially expressed genes, with edgeR producing more conservative, though shorter, lists of genes. Gene Ontology (GO) enrichment analysis revealed no skewness in significant GO terms identified among differentially expressed genes by edgeR versus DESeq2. As transcriptomics of FFPE samples becomes a vanguard of precision medicine, choice of bioinformatics tools becomes critical for clinical research. Our results indicate that STAR and edgeR are well-suited tools for differential gene expression analysis from FFPE samples.

scholarly journals Screening of prognostic biomarkers for endometrial carcinoma based on a ceRNA network

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e6091 ◽  
Author(s):  
Ming-Jun Zheng ◽  
Rui Gou ◽  
Wen-Chao Zhang ◽  
Xin Nie ◽  
Jing Wang ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Prognostic Biomarkers ◽  
Rna Seq ◽  
Cerna Network ◽  
Topological Network ◽  
Regulation Network ◽  
Underlying Mechanisms

Objective This study aims to reveal the regulation network of lncRNAs-miRNAs-mRNA in endometrial carcinoma (EC), to investigate the underlying mechanisms of EC occurrence and progression, to screen prognostic biomarkers. Methods RNA-seq and miRNA-seq data of endometrial carcinoma were downloaded from the TCGA database. Edge.R package was used to screen differentially expressed genes. A database was searched to determine differentially expressed lncRNA-miRNA and miRNA-mRNA pairs, to construct the topological network of ceRNA, and to elucidate the key RNAs that are for a prognosis of survival. Results We screened out 2632 mRNAs, 1178 lncRNAs and 189 miRNAs that were differentially expressed. The constructed ceRNA network included 97 lncRNAs, 20 miRNAs and 73 mRNAs. Analyzing network genes for associations with prognosies revealed 169 prognosis-associated RNAs, including 92 lncRNAs, 16miRNAs and 61 mRNAs. Conclusion Our results reveal new potential mechanisms underlying the carcinogenesis and progression of endometrial carcinoma.

Transcriptional identification of differentially expressed genes during the prepupal–pupal transition in the oriental armyworm, Mythimna separata (Walker) (Lepidoptera: Noctuidae)

2021 ◽  
pp. 1-14
Author(s):  
Peirong Li ◽  
Xinru Li ◽  
Wei Wang ◽  
Xiaoling Tan ◽  
Xiaoqi Wang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Metabolic Pathways ◽  
Developmental Stages ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Mythimna Separata ◽  
Kegg Pathway Analysis ◽  
Oriental Armyworm ◽  
Lepidoptera Noctuidae

Abstract The oriental armyworm, Mythimna separata (Walker) is a serious pest of agriculture that does particular damage to Gramineae crops in Asia, Europe, and Oceania. Metamorphosis is a key developmental stage in insects, although the genes underlying the metamorphic transition in M. separata remain largely unknown. Here, we sequenced the transcriptomes of five stages; mature larvae (ML), wandering (W), and pupation (1, 5, and 10 days after pupation, designated P1, P5, and P10) to identify transition-associated genes. Four libraries were generated, with 22,884, 23,534, 26,643, and 33,238 differentially expressed genes (DEGs) for the ML-vs-W, W-vs-P1, P1-vs-P5, and P5-vs-P10, respectively. Gene ontology enrichment analysis of DEGs showed that genes regulating the biosynthesis of the membrane and integral components of the membrane, which includes the cuticular protein (CP), 20-hydroxyecdysone (20E), and juvenile hormone (JH) biosynthesis, were enriched. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that DEGs were enriched in the metabolic pathways. Of these DEGs, thirty CP, seventeen 20E, and seven JH genes were differentially expressed across the developmental stages. For transcriptome validation, ten CP, 20E, and JH-related genes were selected and verified by real-time PCR quantitative. Collectively, our results provided a basis for further studies of the molecular mechanism of metamorphosis in M. separata.

scholarly journals Key Genes and Prognostic Analysis in HER2+ Breast Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382098329
Author(s):  
Yujie Weng ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Zhongxian Li ◽  
Rong Jia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Differentially Expressed ◽  
Protein Kinase Activity ◽  
Protein Protein Interaction ◽  
Risk Of Death ◽  
Her2 Breast Cancer ◽  
Key Genes

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes ( CCNA2, CDK1, CDC20, CCNB1, DLGAP5, AURKA, BUB1B, RRM2, TPX2, and MAD2L1), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20, CCNA2, DLGAP5, RRM2, and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2, DLGAP5, and TPX2 was positively associated with the risk of death. TPX2, which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

scholarly journals The role of ferroptosis in breast cancer patients: a comprehensive analysis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Hong Yu ◽  
Hua-Dong Li
Keyword(s):  
Breast Cancer ◽  
T Cell ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Function Analysis ◽  
Cancer Prognosis ◽  
Differentially Expressed ◽  
Immune Checkpoints ◽  
Cell Functions

AbstractBreast cancer (BC) affects the breast tissue and is the second most common cause of mortalities among women. Ferroptosis is an iron-dependent cell death mode that is characterized by intracellular accumulation of reactive oxygen species (ROS). We constructed a prognostic multigene signature based on ferroptosis-associated differentially expressed genes (DEGs). Moreover, we comprehensively analyzed the role of ferroptosis-associated miRNAs, lncRNAs, and immune responses. A total of 259 ferroptosis-related genes were extracted. KEGG function analysis of these genes revealed that they were mainly enriched in the HIF-1 signaling pathway, NOD-like receptor signaling pathway, central carbon metabolism in cancer, and PPAR signaling pathway. Fifteen differentially expressed genes (ALOX15, ALOX15B, ANO6, BRD4, CISD1, DRD5, FLT3, G6PD, IFNG, NGB, NOS2, PROM2, SLC1A4, SLC38A1, and TP63) were selected as independent prognostic factors for BC patients. Moreover, T cell functions, including the CCR score, immune checkpoint, cytolytic activity, HLA, inflammation promotion, para-inflammation, T cell co-stimulation, T cell co-inhibition, and type II INF responses were significantly different between the low-risk and high-risk groups of the TCGA cohort. Immune checkpoints between the two groups revealed that the expressions of PDCD-1 (PD-1), CTLA4, LAG3, TNFSF4/14, TNFRSF4/8/9/14/18/25, and IDO1/2 among others were significantly different. A total of 1185 ferroptosis-related lncRNAs and 219 ferroptosis-related miRNAs were also included in this study. From the online database, we identified novel ferroptosis-related biomarkers for breast cancer prognosis. The findings of this study provide new insights into the development of new reliable and accurate cancer treatment options.

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