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Large-scale RNA-Seq Transcriptome Analysis of 4043 Cancers and 548 Normal Tissue Controls across 12 TCGA Cancer Types.

Peng L, Bian XW, Li DK, Xu C, Wang GM, Xia QY, Xiong Q - Sci Rep (2015)

Bottom Line: A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively.A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively.These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400715, China.

ABSTRACT
The Cancer Genome Atlas (TCGA) has accrued RNA-Seq-based transcriptome data for more than 4000 cancer tissue samples across 12 cancer types, translating these data into biological insights remains a major challenge. We analyzed and compared the transcriptomes of 4043 cancer and 548 normal tissue samples from 21 TCGA cancer types, and created a comprehensive catalog of gene expression alterations for each cancer type. By clustering genes into co-regulated gene sets, we identified seven cross-cancer gene signatures altered across a diverse panel of primary human cancer samples. A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively. A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively. These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer.

No MeSH data available.


Related in: MedlinePlus

The normalized expression levels of SFTPA1 and SFTPA2 across 12 types of cancer and normal samples.
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f4: The normalized expression levels of SFTPA1 and SFTPA2 across 12 types of cancer and normal samples.

Mentions: CLUSTER1520 contains 39 genes. Some genes in this cluster have been reported to be associated with lung cancer or other lung diseases (see Table 3 for details). Among them, two genes, SFTPA1 and SFTPA2, encode surfactant protein A (SP-A) that plays a vital role in maintaining normal lung function100 and have been implicated in various lung diseases101102103104105106107108109. The expression levels of SFTPA1 and SFTPA2 were much higher in lung tissue samples than in any other tissue samples, moreover, these two genes were strikingly down-regulated in lung tumor tissues as compared to the adjacent nontumor tissues (Fig. 4). We thus speculate that the expression changes in these two genes might be an important indicator for lung function abnormalities, and those 39 genes in CLUSTER1520 might form a network underlying the initiation and/or development of lung cancers. It could be valuable to elucidate the possible roles of these genes in lung cancer in an experimental setting.


Large-scale RNA-Seq Transcriptome Analysis of 4043 Cancers and 548 Normal Tissue Controls across 12 TCGA Cancer Types.

Peng L, Bian XW, Li DK, Xu C, Wang GM, Xia QY, Xiong Q - Sci Rep (2015)

The normalized expression levels of SFTPA1 and SFTPA2 across 12 types of cancer and normal samples.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4544034&req=5

f4: The normalized expression levels of SFTPA1 and SFTPA2 across 12 types of cancer and normal samples.
Mentions: CLUSTER1520 contains 39 genes. Some genes in this cluster have been reported to be associated with lung cancer or other lung diseases (see Table 3 for details). Among them, two genes, SFTPA1 and SFTPA2, encode surfactant protein A (SP-A) that plays a vital role in maintaining normal lung function100 and have been implicated in various lung diseases101102103104105106107108109. The expression levels of SFTPA1 and SFTPA2 were much higher in lung tissue samples than in any other tissue samples, moreover, these two genes were strikingly down-regulated in lung tumor tissues as compared to the adjacent nontumor tissues (Fig. 4). We thus speculate that the expression changes in these two genes might be an important indicator for lung function abnormalities, and those 39 genes in CLUSTER1520 might form a network underlying the initiation and/or development of lung cancers. It could be valuable to elucidate the possible roles of these genes in lung cancer in an experimental setting.

Bottom Line: A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively.A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively.These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400715, China.

ABSTRACT
The Cancer Genome Atlas (TCGA) has accrued RNA-Seq-based transcriptome data for more than 4000 cancer tissue samples across 12 cancer types, translating these data into biological insights remains a major challenge. We analyzed and compared the transcriptomes of 4043 cancer and 548 normal tissue samples from 21 TCGA cancer types, and created a comprehensive catalog of gene expression alterations for each cancer type. By clustering genes into co-regulated gene sets, we identified seven cross-cancer gene signatures altered across a diverse panel of primary human cancer samples. A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively. A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively. These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer.

No MeSH data available.


Related in: MedlinePlus