Gene expression patterns in melanocytic cells: candidate markers for early stage and malignant transformation

AbstractBone displays suppressed osteogenesis in inflammatory diseases such as sepsis and rheumatoid arthritis. However, the underlying mechanisms have not yet been clearly explained. To identify the gene expression patterns in the bone, we performed Affymetrix Mouse Genome 430 2.0 Array with RNA isolated from mouse femurs 4 h after lipopolysaccharide (LPS) administration. The gene expressions were confirmed with real-time PCR. The serum concentration of the N-terminal propeptide of type I collagen (PINP), a bone-formation marker, was determined using ELISA. A total of 1003 transcripts were upregulated and 159 transcripts were downregulated (more than twofold upregulation or downregulation). Increased expression levels of the inflammation-related genes interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis factor α (TNF-α) were confirmed from in the period 4 h to 72 h after LPS administration using real-time PCR. Gene ontogene analysis found four bone-related categories involved in four biological processes: system development, osteoclast differentiation, ossification and bone development. These processes involved 25 upregulated genes. In the KEGG database, we further analyzed the transforming growth factor β (TGF-β) pathway, which is strongly related to osteogenesis. The upregulated bone morphogenetic protein 2 (BMP2) and downregulated inhibitor of DNA binding 4 (Id4) expressions were further confirmed by real-time PCR after LPS stimulation. The osteoblast function was determined through examination of the expression levels of core binding factor 1 (Cbfa1) and osteocalcin (OC) in bone tissues and serum PINP from 4 h to 72 h after LPS administration. The expressions of OC and Cbfa1 decreased 6 h after administration (p < 0.05). Significantly suppressed PINP levels were observed in the later stage (from 8 h to 72 h, p < 0.05) but not in the early stage (4 h or 6 h, p > 0.05) of LPS stimulation. The results of this study suggest that LPS induces elevated expressions of skeletal system development- and osteoclast differentiation-related genes and inflammation genes at an early stage in the bone. The perturbed functions of these two groups of genes may lead to a faint change in osteogenesis at an early stage of LPS stimulation. Suppressed bone formation was found at later stages in response to LPS stimulation.

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Gene Expression Patterns as Potential Molecular Biomarkers for Malignant Transformation in Human Keratinocytes Treated with MNNG, Arsenic, or a Metal Mixture

Toxicological Sciences ◽

10.1093/toxsci/kfg124 ◽

2003 ◽

Vol 74 (1) ◽

pp. 32-42 ◽

Cited By ~ 15

Author(s):

D.-S. Bae

Keyword(s):

Gene Expression ◽

Malignant Transformation ◽

Expression Patterns ◽

Human Keratinocytes ◽

Molecular Biomarkers ◽

Gene Expression Patterns ◽

Metal Mixture

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BEST: A Novel Computational Approach for Comparing Gene Expression Patterns From Early Stages of Drosophila melanogaster Development

Genetics ◽

10.1093/genetics/162.4.2037 ◽

2002 ◽

Vol 162 (4) ◽

pp. 2037-2047

Author(s):

Sudhir Kumar ◽

Karthik Jayaraman ◽

Sethuraman Panchanathan ◽

Rajalakshmi Gurunathan ◽

Ana Marti-Subirana ◽

...

Keyword(s):

Gene Expression ◽

Developmental Biology ◽

Drosophila Melanogaster ◽

Expression Pattern ◽

Early Stage ◽

Expression Patterns ◽

Gene Expression Pattern ◽

Computational Approach ◽

Gene Expression Patterns ◽

Early Stages

Abstract Embryonic gene expression patterns are an indispensable part of modern developmental biology. Currently, investigators must visually inspect numerous images containing embryonic expression patterns to identify spatially similar patterns for inferring potential genetic interactions. The lack of a computational approach to identify pattern similarities is an impediment to advancement in developmental biology research because of the rapidly increasing amount of available embryonic gene expression data. Therefore, we have developed computational approaches to automate the comparison of gene expression patterns contained in images of early stage Drosophila melanogaster embryos (prior to the beginning of germ-band elongation); similarities and differences in gene expression patterns in these early stages have extensive developmental effects. Here we describe a basic expression search tool (BEST) to retrieve best matching expression patterns for a given query expression pattern and a computational device for gene interaction inference using gene expression pattern images and information on the associated genotypes and probes. Analysis of a prototype collection of Drosophila gene expression pattern images is presented to demonstrate the utility of these methods in identifying biologically meaningful matches and inferring gene interactions by direct image content analysis. In particular, the use of BEST searches for gene expression patterns is akin to that of BLAST searches for finding similar sequences. These computational developmental biology methodologies are likely to make the great wealth of embryonic gene expression pattern data easily accessible and to accelerate the discovery of developmental networks.

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Segmenting Gene Expression Patterns of Early-stage Drosophila Embryos

Mathematics and Visualization - Visualization in Medicine and Life Sciences ◽

10.1007/978-3-540-72630-2_18 ◽

2008 ◽

pp. 313-327 ◽

Cited By ~ 1

Author(s):

Min-Yu Huang ◽

Oliver Rübel ◽

Gunther H. Weber ◽

Cris L. Luengo Hendriks ◽

Mark D. Biggin ◽

...

Keyword(s):

Gene Expression ◽

Early Stage ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Drosophila Embryos

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Digital Gene Expression Tag Profiling Analysis of the Gene Expression Patterns Regulating the Early Stage of Mouse Spermatogenesis

PLoS ONE ◽

10.1371/journal.pone.0058680 ◽

2013 ◽

Vol 8 (3) ◽

pp. e58680 ◽

Cited By ~ 14

Author(s):

Xiujun Zhang ◽

Lili Hao ◽

Lijun Meng ◽

Meiling Liu ◽

Lina Zhao ◽

...

Keyword(s):

Gene Expression ◽

Early Stage ◽

Expression Patterns ◽

Digital Gene Expression ◽

Gene Expression Patterns ◽

Profiling Analysis

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A transcriptomic landscape of cancer and TME in early-stage lungadenocarcinomaby single-cell sequencing.

Journal of Global Oncology ◽

10.1200/jgo.2019.5.suppl.33 ◽

2019 ◽

Vol 5 (suppl) ◽

pp. 33-33

Author(s):

Siwei Wang ◽

Yiqi Zhou ◽

Jue Fan ◽

Rong Yin

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Single Cell ◽

Cancer Cells ◽

Rational Design ◽

Early Stage ◽

Expression Patterns ◽

Marker Gene ◽

Gene Expression Patterns ◽

Mutation Status

33 Background: Immuno-checkpoint inhibition therapies has been revolutionizing cancer treatment. Yet only a fraction of patients show durable responses , whereas the majority of treated patients show relatively low clinical response. This difference is likely to be caused by the heterogeneity of both cancer cells and cells involved in the tumor microenvironment (TME). However, the extent of this heterogeneity, how it is shaped by other factors in the tumor and vice versa, remains poorly understood. Methods: To explore the heterogeneity of lung adenocarcinoma, we obtained tumor tissuesand peripheral blood froma cohort of 30 treatment-naive patients. For each sample, single-cell RNA sequencingand whole exome sequencing(WES) wereperformed. A graph-based unsupervised clusteringmethod was usedand cell types were assignedto clusters based on marker gene expression. The sub-types of both cancer cells and TME cells along with their gene expression patterns were comparedbetween different cancer stages and mutation status. Results: we presented a landscape of cancer and TME transcriptome in human lung adenocarcinoma at single-cell resolution. We found the expression of cancer cells exhibits distinct characteristics with different TNM stages. For instance, the tumor cells of a patient classified as T1aN2M0 highly express genes enriched in the cell migration pathway. By comparing TME cells among patients with different mutation status, we identified changes in various T cell subtypes and tumor-infiltrating myeloid cells. Conclusions: This study provided a detailed cell atlas of lung adenocarcinoma and identified gene expression patterns that are unique to specific TNM stages. Moreover, single-cell analyses offer valuable knowledgeof immune changes for each patient subgroup, providing ausefultool for the rational design of immunetherapies.

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Cappable-Seq Reveals Specific Patterns of Metabolism and Virulence for Salmonella Typhimurium Intracellular Survival within Acanthamoeba castellanii

International Journal of Molecular Sciences ◽

10.3390/ijms22169077 ◽

2021 ◽

Vol 22 (16) ◽

pp. 9077

Author(s):

Alexander S. Balkin ◽

Andrey O. Plotnikov ◽

Natalia E. Gogoleva ◽

Yuri V. Gogolev ◽

Kirill N. Demchenko ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Early Stage ◽

Glyoxylate Cycle ◽

Expression Patterns ◽

Bacterial Pathogen ◽

Acanthamoeba Castellanii ◽

Flagellar Apparatus ◽

Gene Expression Patterns ◽

Broad Host Range

The bacterial pathogen Salmonella enterica, which causes enteritis, has a broad host range and extensive environmental longevity. In water and soil, Salmonella interacts with protozoa and multiplies inside their phagosomes. Although this relationship resembles that between Salmonella and mammalian phagocytes, the interaction mechanisms and bacterial genes involved are unclear. Here, we characterized global gene expression patterns of S. enterica serovar Typhimurium within Acanthamoeba castellanii at the early stage of infection by Cappable-Seq. Gene expression features of S. Typhimurium within A. castellanii were presented with downregulation of glycolysis-related, and upregulation of glyoxylate cycle-related genes. Expression of Salmonella Pathogenicity Island-1 (SPI-1), chemotaxis system, and flagellar apparatus genes was upregulated. Furthermore, expression of genes mediating oxidative stress response and iron uptake was upregulated within A. castellanii as well as within mammalian phagocytes. Hence, global S. Typhimurium gene expression patterns within A. castellanii help better understand the molecular mechanisms of Salmonella adaptation to an amoeba cell and intracellular persistence in protozoa inhabiting water and soil ecosystems.

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Barrett’s Epithelium to Esophageal Adenocarcinoma: Is There a “Point of No Return”?

Frontiers in Genetics ◽

10.3389/fgene.2021.706706 ◽

2021 ◽

Vol 12 ◽

Author(s):

Anshuman Panda ◽

Mi ryung Shin ◽

Christina Cheng ◽

Manisha Bajpai

Keyword(s):

Gene Expression ◽

Malignant Transformation ◽

Esophageal Adenocarcinoma ◽

Clinical Management ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Time Points ◽

Window Period ◽

Barrett’S Epithelium ◽

Point Of No Return

Background: Esophageal adenocarcinoma (EA) arises from Barrett’s epithelium (BE), and chronic gastroesophageal reflux disease is considered the strongest risk factor for disease progression. All BE patients undergo acid suppressive therapy, surveillance, and BE removal by surgery or endoscopic ablation, yet the incidence of EAC continues to increase. Despite the known side effects and mortality, the one-size-fits-all approach is the standard clinical management as there are no reliable methods for risk stratification.Methods: Paired-end Illumina NextSeq500 RNA sequencing was performed on total RNA extracted from 20-week intervals (0, 20, 40, and 60 W) of an in vitro BE carcinogenesis (BEC) model to construct time series global gene expression patterns (GEPs). The cells from two strategic time points (20 and 40 W) based on the GEPs were grown for another 20 weeks, with and without further acid and bile salt (ABS) stimulation, and the recurrent neoplastic cell phenotypes were evaluated.Results: Hierarchical clustering of 866 genes with ≥ twofold change in transcript levels across the four time points revealed maximum variation between the BEC20W and BEC40W cells. Enrichment analysis confirmed that the genes altered ≥ twofold during this window period associated with carcinogenesis and malignancy. Intriguingly, the BEC20W cells required further ABS exposure to gain neoplastic changes, but the BEC40W cells progressed to malignant transformation after 20 weeks even in the absence of additional ABS.Discussion: The transcriptomic gene expression patterns in the BEC model demonstrate evidence of a clear threshold in the progression of BE to malignancy. Catastrophic transcriptomic changes during a window period culminate in the commitment of the BE cells to a “point of no return,” and removal of ABS is not effective in preventing their malignant transformation. Discerning this “point of no return” during BE surveillance by tracking the GEPs has the potential to evaluate risk of BE progression and enable personalized clinical management.

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