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Integrated analysis of long noncoding RNA and coding RNA expression in esophageal squamous cell carcinoma.

Cao W, Wu W, Shi F, Chen X, Wu L, Yang K, Tian F, Zhu M, Chen G, Wang W, Biddle FG, Gu J - Int J Genomics (2013)

Bottom Line: We identified differentially expressed lncRNAs and coding RNAs in ESCC relative to their matched normal tissue counterparts and validated the result using polymerase chain reaction analysis.Furthermore, we identified differentially expressed lncRNAs that are co-located and co-expressed with differentially expressed coding RNAs in ESCC and the results point to a potential interaction between lncRNAs and neighboring coding genes that affect ether lipid metabolism, and the interaction may contribute to the development of ESCC.These data provide compelling evidence for a potential novel genomic biomarker of esophageal squamous cell cancer.

View Article: PubMed Central - PubMed

Affiliation: Clinical Research Center, People's Hospital of Zhengzhou, 33 Yellow River Road, Zhengzhou, Henan 45003, China.

ABSTRACT
Tumorigenesis is a complex dynamic biological process that includes multiple steps of genetic and epigenetic alterations, aberrant expression of noncoding RNA, and changes in the expression profiles of coding genes. We call the collection of those perturbations in genome space the "cancer initiatome." Long noncoding RNAs (lncRNAs) are pervasively transcribed in the genome and they have key regulatory functions in chromatin remodeling and gene expression. Spatiotemporal variation in the expression of lncRNAs has been observed in development and disease states, including cancer. A few dysregulated lncRNAs have been studied in cancers, but the role of lncRNAs in the cancer initiatome remains largely unknown, especially in esophageal squamous cell carcinoma (ESCC). We conducted a genome-wide screen of the expression of lncRNAs and coding RNAs from ESCC and matched adjacent nonneoplastic normal tissues. We identified differentially expressed lncRNAs and coding RNAs in ESCC relative to their matched normal tissue counterparts and validated the result using polymerase chain reaction analysis. Furthermore, we identified differentially expressed lncRNAs that are co-located and co-expressed with differentially expressed coding RNAs in ESCC and the results point to a potential interaction between lncRNAs and neighboring coding genes that affect ether lipid metabolism, and the interaction may contribute to the development of ESCC. These data provide compelling evidence for a potential novel genomic biomarker of esophageal squamous cell cancer.

No MeSH data available.


Related in: MedlinePlus

Transcriptomic landscape of esophageal squamous cell cancer (ESCC). (a) Whole transcriptome of tumor (T) and adjacent normal tissue (N) of four patients with ESCC were detected using a microarray with 7,419 long noncoding RNAs (lncRNAs) and 27,958 coding RNAs. Two main clusters (Ts and Ns) were generated using unsupervised clustering methods. Then, a self-organizing map (SOM) of either whole transcriptome (both lncRNAs and mRNAs) or lncRNAs or mRNA was produced from each sample (see legend in up-left corner of this figure, and the arrows are meant to indicate the potential interaction), using gene expression dynamic inspector (GEDI). Mosaic patterns are pseudocolored SOMs to show integrated biological entity in each sample. Red through blue color indicates high to low expression level. (b) and (c) Differentially expressed lncRNAs (DE-lncRNAs) and coding RNAs (DE-mRNAs) in ESCC. Hierarchical clustering analysis of 410 DE-lncRNAs (b) and 1219 DE-mRNAs (c) between ESCC tissue and adjacent normal tissue (fold change > or < 2-fold and P < 0.05). Red and green colors indicate high and low expression, respectively. In the heatmap, columns represent samples, and rows represent each gene. The scale of expression level is shown on the horizontal bar. (d) KEGG functional analysis of DE-mRNA networks in ESCC. The DE-mRNA genes are involved in cancer-related signaling functions, and a detailed list of significant GO terms is shown in Figure S1 and its associated legend in Supplementary Information.
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fig1: Transcriptomic landscape of esophageal squamous cell cancer (ESCC). (a) Whole transcriptome of tumor (T) and adjacent normal tissue (N) of four patients with ESCC were detected using a microarray with 7,419 long noncoding RNAs (lncRNAs) and 27,958 coding RNAs. Two main clusters (Ts and Ns) were generated using unsupervised clustering methods. Then, a self-organizing map (SOM) of either whole transcriptome (both lncRNAs and mRNAs) or lncRNAs or mRNA was produced from each sample (see legend in up-left corner of this figure, and the arrows are meant to indicate the potential interaction), using gene expression dynamic inspector (GEDI). Mosaic patterns are pseudocolored SOMs to show integrated biological entity in each sample. Red through blue color indicates high to low expression level. (b) and (c) Differentially expressed lncRNAs (DE-lncRNAs) and coding RNAs (DE-mRNAs) in ESCC. Hierarchical clustering analysis of 410 DE-lncRNAs (b) and 1219 DE-mRNAs (c) between ESCC tissue and adjacent normal tissue (fold change > or < 2-fold and P < 0.05). Red and green colors indicate high and low expression, respectively. In the heatmap, columns represent samples, and rows represent each gene. The scale of expression level is shown on the horizontal bar. (d) KEGG functional analysis of DE-mRNA networks in ESCC. The DE-mRNA genes are involved in cancer-related signaling functions, and a detailed list of significant GO terms is shown in Figure S1 and its associated legend in Supplementary Information.

Mentions: Our genome-wide gene expression profiling of both lncRNAs and coding genes from ESCC and adjacent nonneoplastic tissue was conducted to detect possible associations of lncRNAs with ESCC. We first asked whether these transcripts of 7,419 noncoding and 27,958 coding RNAs could distinguish ESCC from normal tissues. Figure 1(a) shows that the four ESCC samples are clustered together in one group and clearly separated from the samples of normal tissue. Next, we examined the whole transcriptomic pattern (lncRNAs + coding RNAs) from each sample and the landscapes of the whole transcriptome (represented by heatmaps in Figure 1(a)) of normal tissues differ from those of ESCC that exhibit more heterogeneous alterations. The overall changes from a respective normal to cancer state were also seen separately as a difference in expression profile of either the lncRNA or the coding RNA. These observations suggest that a potential dynamic interaction between lncRNAs and coding RNAs may be reshaping the landscape of the whole transcriptome during ESCC development.


Integrated analysis of long noncoding RNA and coding RNA expression in esophageal squamous cell carcinoma.

Cao W, Wu W, Shi F, Chen X, Wu L, Yang K, Tian F, Zhu M, Chen G, Wang W, Biddle FG, Gu J - Int J Genomics (2013)

Transcriptomic landscape of esophageal squamous cell cancer (ESCC). (a) Whole transcriptome of tumor (T) and adjacent normal tissue (N) of four patients with ESCC were detected using a microarray with 7,419 long noncoding RNAs (lncRNAs) and 27,958 coding RNAs. Two main clusters (Ts and Ns) were generated using unsupervised clustering methods. Then, a self-organizing map (SOM) of either whole transcriptome (both lncRNAs and mRNAs) or lncRNAs or mRNA was produced from each sample (see legend in up-left corner of this figure, and the arrows are meant to indicate the potential interaction), using gene expression dynamic inspector (GEDI). Mosaic patterns are pseudocolored SOMs to show integrated biological entity in each sample. Red through blue color indicates high to low expression level. (b) and (c) Differentially expressed lncRNAs (DE-lncRNAs) and coding RNAs (DE-mRNAs) in ESCC. Hierarchical clustering analysis of 410 DE-lncRNAs (b) and 1219 DE-mRNAs (c) between ESCC tissue and adjacent normal tissue (fold change > or < 2-fold and P < 0.05). Red and green colors indicate high and low expression, respectively. In the heatmap, columns represent samples, and rows represent each gene. The scale of expression level is shown on the horizontal bar. (d) KEGG functional analysis of DE-mRNA networks in ESCC. The DE-mRNA genes are involved in cancer-related signaling functions, and a detailed list of significant GO terms is shown in Figure S1 and its associated legend in Supplementary Information.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3814080&req=5

fig1: Transcriptomic landscape of esophageal squamous cell cancer (ESCC). (a) Whole transcriptome of tumor (T) and adjacent normal tissue (N) of four patients with ESCC were detected using a microarray with 7,419 long noncoding RNAs (lncRNAs) and 27,958 coding RNAs. Two main clusters (Ts and Ns) were generated using unsupervised clustering methods. Then, a self-organizing map (SOM) of either whole transcriptome (both lncRNAs and mRNAs) or lncRNAs or mRNA was produced from each sample (see legend in up-left corner of this figure, and the arrows are meant to indicate the potential interaction), using gene expression dynamic inspector (GEDI). Mosaic patterns are pseudocolored SOMs to show integrated biological entity in each sample. Red through blue color indicates high to low expression level. (b) and (c) Differentially expressed lncRNAs (DE-lncRNAs) and coding RNAs (DE-mRNAs) in ESCC. Hierarchical clustering analysis of 410 DE-lncRNAs (b) and 1219 DE-mRNAs (c) between ESCC tissue and adjacent normal tissue (fold change > or < 2-fold and P < 0.05). Red and green colors indicate high and low expression, respectively. In the heatmap, columns represent samples, and rows represent each gene. The scale of expression level is shown on the horizontal bar. (d) KEGG functional analysis of DE-mRNA networks in ESCC. The DE-mRNA genes are involved in cancer-related signaling functions, and a detailed list of significant GO terms is shown in Figure S1 and its associated legend in Supplementary Information.
Mentions: Our genome-wide gene expression profiling of both lncRNAs and coding genes from ESCC and adjacent nonneoplastic tissue was conducted to detect possible associations of lncRNAs with ESCC. We first asked whether these transcripts of 7,419 noncoding and 27,958 coding RNAs could distinguish ESCC from normal tissues. Figure 1(a) shows that the four ESCC samples are clustered together in one group and clearly separated from the samples of normal tissue. Next, we examined the whole transcriptomic pattern (lncRNAs + coding RNAs) from each sample and the landscapes of the whole transcriptome (represented by heatmaps in Figure 1(a)) of normal tissues differ from those of ESCC that exhibit more heterogeneous alterations. The overall changes from a respective normal to cancer state were also seen separately as a difference in expression profile of either the lncRNA or the coding RNA. These observations suggest that a potential dynamic interaction between lncRNAs and coding RNAs may be reshaping the landscape of the whole transcriptome during ESCC development.

Bottom Line: We identified differentially expressed lncRNAs and coding RNAs in ESCC relative to their matched normal tissue counterparts and validated the result using polymerase chain reaction analysis.Furthermore, we identified differentially expressed lncRNAs that are co-located and co-expressed with differentially expressed coding RNAs in ESCC and the results point to a potential interaction between lncRNAs and neighboring coding genes that affect ether lipid metabolism, and the interaction may contribute to the development of ESCC.These data provide compelling evidence for a potential novel genomic biomarker of esophageal squamous cell cancer.

View Article: PubMed Central - PubMed

Affiliation: Clinical Research Center, People's Hospital of Zhengzhou, 33 Yellow River Road, Zhengzhou, Henan 45003, China.

ABSTRACT
Tumorigenesis is a complex dynamic biological process that includes multiple steps of genetic and epigenetic alterations, aberrant expression of noncoding RNA, and changes in the expression profiles of coding genes. We call the collection of those perturbations in genome space the "cancer initiatome." Long noncoding RNAs (lncRNAs) are pervasively transcribed in the genome and they have key regulatory functions in chromatin remodeling and gene expression. Spatiotemporal variation in the expression of lncRNAs has been observed in development and disease states, including cancer. A few dysregulated lncRNAs have been studied in cancers, but the role of lncRNAs in the cancer initiatome remains largely unknown, especially in esophageal squamous cell carcinoma (ESCC). We conducted a genome-wide screen of the expression of lncRNAs and coding RNAs from ESCC and matched adjacent nonneoplastic normal tissues. We identified differentially expressed lncRNAs and coding RNAs in ESCC relative to their matched normal tissue counterparts and validated the result using polymerase chain reaction analysis. Furthermore, we identified differentially expressed lncRNAs that are co-located and co-expressed with differentially expressed coding RNAs in ESCC and the results point to a potential interaction between lncRNAs and neighboring coding genes that affect ether lipid metabolism, and the interaction may contribute to the development of ESCC. These data provide compelling evidence for a potential novel genomic biomarker of esophageal squamous cell cancer.

No MeSH data available.


Related in: MedlinePlus