scholarly journals Different Gene Expression Patterns in Invasive Lobular and Ductal Carcinomas of the Breast

2004 ◽  
Vol 15 (6) ◽  
pp. 2523-2536 ◽  
Author(s):  
Hongjuan Zhao ◽  
Anita Langerød ◽  
Youngran Ji ◽  
Kent W. Nowels ◽  
Jahn M. Nesland ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Expression Patterns ◽  
The United States ◽  
Immune Defense ◽  
Differentially Expressed ◽  
Fatty Acid Transport ◽  
Lipid Fatty Acid

Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two major histological types of breast cancer worldwide. Whereas IDC incidence has remained stable, ILC is the most rapidly increasing breast cancer phenotype in the United States and Western Europe. It is not clear whether IDC and ILC represent molecularly distinct entities and what genes might be involved in the development of these two phenotypes. We conducted comprehensive gene expression profiling studies to address these questions. Total RNA from 21 ILCs, 38 IDCs, two lymph node metastases, and three normal tissues were amplified and hybridized to ∼42,000 clone cDNA microarrays. Data were analyzed using hierarchical clustering algorithms and statistical analyses that identify differentially expressed genes (significance analysis of microarrays) and minimal subsets of genes (prediction analysis for microarrays) that succinctly distinguish ILCs and IDCs. Eleven of 21 (52%) of the ILCs (“typical” ILCs) clustered together and displayed different gene expression profiles from IDCs, whereas the other ILCs (“ductal-like” ILCs) were distributed between different IDC subtypes. Many of the differentially expressed genes between ILCs and IDCs code for proteins involved in cell adhesion/motility, lipid/fatty acid transport and metabolism, immune/defense response, and electron transport. Many genes that distinguish typical and ductal-like ILCs are involved in regulation of cell growth and immune response. Our data strongly suggest that over half the ILCs differ from IDCs not only in histological and clinical features but also in global transcription programs. The remaining ILCs closely resemble IDCs in their transcription patterns. Further studies are needed to explore the differences between ILC molecular subtypes and to determine whether they require different therapeutic strategies.

scholarly journals Tamoxifen treatment for breast cancer enforces a distinct gene-expression profile on the human endometrium: an exploratory study

2005 ◽  
Vol 12 (4) ◽  
pp. 1037-1049 ◽  
Author(s):  
S C J P Gielen ◽  
L C M Kühne ◽  
P C Ewing ◽  
L J Blok ◽  
C W Burger
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Exploratory Study ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Tamoxifen Treatment ◽  
Endometrial Polyps ◽  
Pathological Classification

Tamoxifen treatment for breast cancer increases proliferation of the endometrium, resulting in an enhanced prevalence of endometrial pathologies, including endometrial cancer. An exploratory study was performed to begin to understand the molecular mechanism of tamoxifen action in the endometrium. Gene-expression profiles were generated of endometrial samples of tamoxifen users and compared with matched controls. The pathological classification of samples from both groups included atrophic/inactive endometrium and endometrial polyps. Unsupervised clustering revealed that samples of tamoxifen users were, irrespective of pathological classification, fairly similar and consequently form a subgroup distinct from the matched controls. Using SAM analysis (a statistical method to select genes differentially expressed between groups), 256 differentially expressed genes were selected between the tamoxifen and control groups. Upon comparing these genes with oestrogen-regulated genes, identified under similar circumstances, 95% of the differentially expressed genes turned out to be tamoxifen-specific. Finally, construction of a gene-expression network of the differentially expressed genes revealed that 69 genes centred around five well-known genes: TP53, RELA, MYC, epidermal growth factor receptor and β-catenin. This could indicate that these well-known genes, and the pathways in which they function, are important for tamoxifen-controlled proliferation of the endometrium.

scholarly journals Gene expression profiling of skeletal muscles

2021 ◽  
Author(s):  
Sarah I. Alto ◽  
Chih-Ning Chang ◽  
Kevin Brown ◽  
Chrissa Kioussi ◽  
Theresa M. Filtz
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Differentially Expressed Genes ◽  
Tibialis Anterior ◽  
Skeletal Muscles ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Analysis Tool

AbstractSoleus and tibialis anterior are two well-characterized skeletal muscles commonly utilized in skeletal muscle-related studies. Next-generation sequencing provides an opportunity for an in-depth biocomputational analysis to identify the gene expression patterns between soleus and tibialis anterior and analyze those genes’ functions based on past literature. This study acquired the gene expression profiles from soleus and tibialis anterior murine skeletal muscle biopsies via RNA-sequencing. Read counts were processed through edgeR’s differential gene expression analysis. Differentially expressed genes were filtered down using a false discovery rate less than 0.05c, a fold-change value larger than twenty, and an association with overrepresented pathways based on the Reactome pathway over-representation analysis tool. Most of the differentially expressed genes associated with soleus encoded for components of lipid metabolism and unique contractile elements. Differentially expressed genes associated with tibialis anterior encoded mostly for glucose and glycogen metabolic pathways’ regulatory enzymes and calcium-sensitive contractile components. These gene expression distinctions partly explain the genetic basis for muscle specialization and may help to explain skeletal muscle susceptibility to disease and drugs and refine tissue engineering approaches.

Gene Expression Profiles of CD34+ Cells in Myelodysplastic Syndrome

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 5078-5078
Author(s):  
Monika Belickova ◽  
Alzbeta Vasikova ◽  
Eva Budinska ◽  
Jaroslav Cermak
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Statistical Testing ◽  
Differentially Expressed ◽  
Control Group ◽  
Regulation Of Transcription ◽  
Cd34 Cells

Abstract Myelodysplatic syndrome (MDS) represents a heterogeneous group of clonal disorders with ineffective hematopoiesis that is characterized by dysplasia and peripheral cytopenia of one or more cell lineages. We studied gene expression profiles in CD34+ cells of 42 MDS patients and 6 healthy controls using Illumina cDNA microarray technology. Nine patients had RA, 7 patients had RCMD, 17 patients had RAEB and 9 had RAEB-T. CD34+ cells were isolated from bone marrow samples using MACS magnetic columns. The quality of total extracted RNA was confirmed with the Agilent Bioanalyzer 2100. 200ng of total RNA was amplified using Illumina RNA amplification kit. cRNA targets were hybridized on the Sentrix HumanRef-8 BeadChips (> 24 000 probes), which were scanned on the Illumina BeadStation 500. The data were pre-processed and normalized by lumi R package designed to preprocess the Illumina microarray data. Normalized data were filtered by detection p-value <0.01, resulting in total number of 10 091 genes. This gene set was tested for differential expression between clinical groups and control group. For this purpose, statistical testing by ANOVA with correction for multiple testing problem by Bayesian thresholding was performed. Additionally, analysis by random-forests (RAFT) was performed. Significant genes from both analyses were merged resulting in 332 differentially expressed genes detected. Out of these, 79 genes showed ≥2.5 fold changes in gene expression between controls and all MDS groups (22 up-regulated and 57 down-regulated). Our findings were confirmed by real-time quantitative PCR for several genes (TaqMan Gene Expression Assays). We used DAVID database to annotate 79 selected genes: 8 of 22 up-regulated genes in MDS patients were recognized to play a role in regulation of transcription (LEO1, E2F6 and several zing finger proteins). A half of these over-expressed genes could not be annotated due to still unknown biological function. Within the set of the down-regulated genes in MDS patients those biological processes were predominantly detected: cell differentiation (KLF4, FOSL2, STK17B, BCL3, SNF1LK, ID2 etc.), response to stress (CXCL12, SMAD7, CYGB, etc.) and cell proliferation (MXD1, OSM, FTH1, KLF10 etc.). In the set of 31 genes with 5 fold decreased expression, we identified 8 genes involved in B-cell development. (VPREB1, VPREB3, CD79A, EBI2, LEF1, CXCL12, CTGF, GALNAC4S-6ST). RAFT analysis was performed also in the set of 332 statistically differentially expressed genes in order to evaluate accuracy of grouping the patients according their diagnosis. We detected strong heterogeneity in gene expression patterns within the MDS patients, especially in the RAEB group reflecting clinical diversity of MDS. Clustering analysis (Spearman correlation) showed that most of the RAEB-2 patients (7 out of 9) were clustered together with REAB-T whereas RAEB-1 clustered with RCMD or RA. These results underline the need of distinguishing RAEB-1 and RAEB-2 diagnosis according to WHO classification system, since their expression profiles are significantly different.

Commonality and differences in leukocyte gene expression patterns among three models of inflammation and injury

2006 ◽  
Vol 24 (3) ◽  
pp. 298-309 ◽  
Author(s):  
Bernard H. Brownstein ◽  
Tanya Logvinenko ◽  
James A. Lederer ◽  
J. Perren Cobb ◽  
William J. Hubbard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Animal Models ◽  
Differentially Expressed Genes ◽  
Burn Injury ◽  
Expression Profiles ◽  
Expression Patterns ◽  
White Blood Cells ◽  
Differentially Expressed ◽  
Leukocyte Populations ◽  
Time Point

The aim of this study was to compare gene expression profiles of leukocytes from blood (white blood cells; WBCs) and spleen harvested at an early time point after injury or sham injury in mice subjected to trauma/hemorrhage, burn injury, or lipopolysaccharide (LPS) infusion at three experimental sites. Groups of injured or LPS-infused animals and sham controls were killed at 2 h after injury and resuscitation, blood and spleen were harvested, and leukocyte populations were recovered after erythrocyte lysis. RNA was extracted from postlysis leukocyte populations. Complementary RNA was synthesized from each RNA sample and hybridized to microarrays. A large number (500–1,400) of genes were differentially expressed at the 2-h time point in injured or LPS-infused vs. sham animals. Thirteen of the differentially expressed genes in blood, and 46 in the spleen, were upregulated or downregulated in common among all three animal models and may represent a common, early transcriptional response to systemic inflammation from a variety of causes. The majority of these genes could be assigned to pathways involved in the immune response and cell death. The up- or downregulation of a cohort of 23 of these genes was validated by RT-PCR. This large-scale microarray analysis shows that, at the 2-h time point, there is marked alteration in leukocyte gene expression in three animal models of injury and inflammation. Although there is some commonality among the models, the majority of the differentially expressed genes appear to be uniquely associated with the type of injury and/or the inflammatory stimulus.

scholarly journals Global blood gene expression profiles following a breast cancer diagnosis—Clinical follow-up in the NOWAC post-genome cohort

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246650
Author(s):  
Karina Standahl Olsen ◽  
Marit Holden ◽  
Jean-Christophe Thalabard ◽  
Lill-Tove Rasmussen Busund ◽  
Eiliv Lund ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Cancer Diagnosis ◽  
Expression Profiles ◽  
Metastatic Cancer ◽  
Breast Cancer Diagnosis ◽  
Differentially Expressed ◽  
Blood Gene Expression

Objective This explorative study aimed to assess if there are any time-dependent blood gene expression changes during the first one to eight years after breast cancer diagnosis, which can be linked to the clinical outcome of the disease. Material and methods A random distribution of follow-up time from breast cancer diagnosis till blood sampling was obtained by a nested, matched case-control design in the Norwegian Women and Cancer Post-genome Cohort. From 2002–5, women were invited to donate blood samples, regardless of any cancer diagnosis. At end of the study period in 2015, any cancer diagnoses in the 50 000 participants were obtained via linkage to the Norwegian Cancer Registry. For each breast cancer patient (n = 415), an age- and storage time-matched control was drawn. The design gave a uniform, random length of follow-up time, independent of cancer stage. Differences in blood gene expression between breast cancer cases and controls were identified using the Bioconductor R-package limma, using a moving window in time, to handle the varying time elapsed from diagnosis to blood sample. Results The number of differentially expressed genes between cases and controls were close to 2,000 in the first year after diagnosis, but fell sharply the second year. During the next years, a transient second increase was observed, but only in women with metastatic disease who later died, both compared to invasive cases that survived (p<0,001) and to metastatic cases that survived (p = 0.024). Among the differentially expressed genes there was an overrepresentation of heme metabolism and T cell-related processes. Conclusion This explorative analysis identified changing trajectories in the years after diagnosis, depending on clinical stage. Hypothetically, this could represent the escape of the metastatic cancer from the immune system.

scholarly journals Differential gene expression profiles in foetal skin of Rex rabbits with different wool density

2016 ◽  
Vol 24 (3) ◽  
pp. 223
Author(s):  
L. Liu ◽  
B. Li ◽  
Y.L. Zhu ◽  
C.Y. Wang ◽  
F.C. Li
Keyword(s):  
Gene Expression ◽  
Hair Follicle ◽  
Differentially Expressed Genes ◽  
Transforming Growth Factor Beta ◽  
Transforming Growth Factor ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Signalling Pathways ◽  
Rex Rabbit

<p>This study investigated the mechanisms controlling hair follicle development in the Rex rabbit. The Agilent rabbit gene expression microarray was used to determine differentially expressed genes in Rex rabbit foetuses with different wool densities. The expression patterns of selected differentially-expressed genes were further investigated by quantitative real-time PCR. Compared to low wool density rabbits, 1342 differentially expressed probes were identified in high wool density rabbits, including 950 upregulated probes and 392 downregulated probes. Gene ontology analysis revealed that the most upregulated differentially expressed probes belonged to receptors and the most downregulated differentially expressed probes belonged to DNA binding molecules. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the differentially expressed probes were mainly involved in the sonic hedgehog (Shh) and Eph signalling pathways. The results also suggest that transforming growth factor-beta 1, growth hormone receptor, and the keratin-associated protein 6.1 genes, as well as the Shh and Eph signalling pathways, may be involved in the regulation of hair follicle developmental in Rex rabbits.</p>

scholarly journals Comprehensive Comparison of Amnion Stromal Cells and Chorion Stromal Cells by RNA-Seq

2021 ◽  
Vol 22 (4) ◽  
pp. 1901
Author(s):  
Brielle Jones ◽  
Chaoyang Li ◽  
Min Sung Park ◽  
Anne Lerch ◽  
Vimal Jacob ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stromal Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Principal Component ◽  
Differentially Expressed ◽  
Inflammatory Factor ◽  
Next Generation Sequencing Technology ◽  
Angiogenic Potential ◽  
Anti Inflammatory

Mesenchymal stromal cells derived from the fetal placenta, composed of an amnion membrane, chorion membrane, and umbilical cord, have emerged as promising sources for regenerative medicine. Here, we used next-generation sequencing technology to comprehensively compare amniotic stromal cells (ASCs) with chorionic stromal cells (CSCs) at the molecular and signaling levels. Principal component analysis showed a clear dichotomy of gene expression profiles between ASCs and CSCs. Unsupervised hierarchical clustering confirmed that the biological repeats of ASCs and CSCs were able to respectively group together. Supervised analysis identified differentially expressed genes, such as LMO3, HOXA11, and HOXA13, and differentially expressed isoforms, such as CXCL6 and HGF. Gene Ontology (GO) analysis showed that the GO terms of the extracellular matrix, angiogenesis, and cell adhesion were significantly enriched in CSCs. We further explored the factors associated with inflammation and angiogenesis using a multiplex assay. In comparison with ASCs, CSCs secreted higher levels of angiogenic factors, including angiogenin, VEGFA, HGF, and bFGF. The results of a tube formation assay proved that CSCs exhibited a strong angiogenic function. However, ASCs secreted two-fold more of an anti-inflammatory factor, TSG-6, than CSCs. In conclusion, our study demonstrated the differential gene expression patterns between ASCs and CSCs. CSCs have superior angiogenic potential, whereas ASCs exhibit increased anti-inflammatory properties.

scholarly journals Transcriptome Analysis of Differentially Expressed mRNA Related to Pigeon Muscle Development

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2311
Author(s):  
Hao Ding ◽  
Yueyue Lin ◽  
Tao Zhang ◽  
Lan Chen ◽  
Genxi Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Differentially Expressed Genes ◽  
Growth And Development ◽  
Muscle Development ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Growth Stages ◽  
Gene Expression And Regulation

The mechanisms behind the gene expression and regulation that modulate the development and growth of pigeon skeletal muscle remain largely unknown. In this study, we performed gene expression analysis on skeletal muscle samples at different developmental and growth stages using RNA sequencing (RNA−Seq). The differentially expressed genes (DEGs) were identified using edgeR software. Weighted gene co−expression network analysis (WGCNA) was used to identify the gene modules related to the growth and development of pigeon skeletal muscle based on DEGs. A total of 11,311 DEGs were identified. WGCNA aggregated 11,311 DEGs into 12 modules. Black and brown modules were significantly correlated with the 1st and 10th day of skeletal muscle growth, while turquoise and cyan modules were significantly correlated with the 8th and 13th days of skeletal muscle embryonic development. Four mRNA−mRNA regulatory networks corresponding to the four significant modules were constructed and visualised using Cytoscape software. Twenty candidate mRNAs were identified based on their connectivity degrees in the networks, including Abca8b, TCONS−00004461, VWF, OGDH, TGIF1, DKK3, Gfpt1 and RFC5, etc. A KEGG pathway enrichment analysis showed that many pathways were related to the growth and development of pigeon skeletal muscle, including PI3K/AKT/mTOR, AMPK, FAK, and thyroid hormone pathways. Five differentially expressed genes (LAST2, MYPN, DKK3, B4GALT6 and OGDH) in the network were selected, and their expression patterns were quantified by qRT−PCR. The results were consistent with our sequencing results. These findings could enhance our understanding of the gene expression and regulation in the development and growth of pigeon muscle.

scholarly journals Analysis of Transcriptional Changes in Different Brassica napus Synthetic Allopolyploids

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 82
Author(s):  
Yunxiao Wei ◽  
Guoliang Li ◽  
Shujiang Zhang ◽  
Shifan Zhang ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Napus ◽  
Differentially Expressed Genes ◽  
Expression Patterns ◽  
Female Parent ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Transcriptional Changes ◽  
Aa Genome ◽  
High Degree

Allopolyploidy is an evolutionary and mechanistically intriguing process involving the reconciliation of two or more sets of diverged genomes and regulatory interactions, resulting in new phenotypes. In this study, we explored the gene expression patterns of eight F2 synthetic Brassica napus using RNA sequencing. We found that B. napus allopolyploid formation was accompanied by extensive changes in gene expression. A comparison between F2 and the parent shows a certain proportion of differentially expressed genes (DEG) and activation\silent gene, and the two genomes (female parent (AA)\male parent (CC) genomes) showed significant differences in response to whole-genome duplication (WGD); non-additively expressed genes represented a small portion, while Gene Ontology (GO) enrichment analysis showed that it played an important role in responding to WGD. Besides, genome-wide expression level dominance (ELD) was biased toward the AA genome, and the parental expression pattern of most genes showed a high degree of conservation. Moreover, gene expression showed differences among eight individuals and was consistent with the results of a cluster analysis of traits. Furthermore, the differential expression of waxy synthetic pathways and flowering pathway genes could explain the performance of traits. Collectively, gene expression of the newly formed allopolyploid changed dramatically, and this was different among the selfing offspring, which could be a prominent cause of the trait separation. Our data provide novel insights into the relationship between the expression of differentially expressed genes and trait segregation and provide clues into the evolution of allopolyploids.

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.

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