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A Balanced Tissue Composition Reveals New Metabolic and Gene Expression Markers in Prostate Cancer.

ABSTRACT: Molecular analysis of patient tissue samples is essential to characterize the in vivo variability in human cancers which are not accessible in cell-lines or animal models. This applies particularly to studies of tumor metabolism. The challenge is, however, the complex mixture of various tissue types within each sample, such as benign epithelium, stroma and cancer tissue, which can introduce systematic biases when cancers are compared to normal samples. In this study we apply a simple strategy to remove such biases using sample selections where the average content of stroma tissue is balanced between the sample groups. The strategy is applied to a prostate cancer patient cohort where data from MR spectroscopy and gene expression have been collected from and integrated on the exact same tissue samples. We reveal in vivo changes in cancer-relevant metabolic pathways which are otherwise hidden in the data due to tissue confounding. In particular, lowered levels of putrescine are connected to increased expression of SRM, reduced levels of citrate are attributed to upregulation of genes promoting fatty acid synthesis, and increased succinate levels coincide with reduced expression of SUCLA2 and SDHD. In addition, the strategy also highlights important metabolic differences between the stroma, epithelium and prostate cancer. These results show that important in vivo metabolic features of cancer can be revealed from patient data only if the heterogeneous tissue composition is properly accounted for in the analysis.

SUBMITTER: Tessem MB

PROVIDER: S-EPMC4839647 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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A Balanced Tissue Composition Reveals New Metabolic and Gene Expression Markers in Prostate Cancer.

Tessem May-Britt MB Bertilsson Helena H Angelsen Anders A Bathen Tone F TF Drabløs Finn F Rye Morten Beck MB

PloS one 20160421 4

Molecular analysis of patient tissue samples is essential to characterize the in vivo variability in human cancers which are not accessible in cell-lines or animal models. This applies particularly to studies of tumor metabolism. The challenge is, however, the complex mixture of various tissue types within each sample, such as benign epithelium, stroma and cancer tissue, which can introduce systematic biases when cancers are compared to normal samples. In this study we apply a simple strategy to ...[more]

PMID: 27100877

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Project description:Information on over- and underexpressed genes in prostate cancer in comparison to adjacent normal tissue was sought by DNA microarray analysis. Approximately 12,600 mRNA sequences were analyzed from a total of 26 tissue samples (17 untreated prostate cancers, 9 normal adjacent to prostate cancer tissues) obtained by prostatectomy. Hierarchical clustering was performed. Expression levels of 63 genes were found significantly (at least 2.5-fold) increased, whereas expression of 153 genes was decreased (at least 2.5-fold) in prostate cancer versus adjacent normal tissue. In addition to previously described genes such as hepsin, overexpression of several genes was found that has not drawn attention before, such as the genes encoding the specific granule protein (SGP28), alpha-methyl-acyl-CoA racemase, low density lipoprotein (LDL)-phospholipase A2, and the anti-apoptotic gene PYCR1. The radiosensitivity gene ATDC and the genes encoding the DNA-binding protein inhibitor ID1 and the phospholipase inhibitor uteroglobin were significantly down-regulated in the cancer samples. DNA microarray data for eight genes were confirmed quantitatively in five normal and five cancer tissues by real-time reverse transcriptase-polymerase chain reaction with a high correlation between the two methods. Laser capture microdissection of epithelial and stromal compartments from cancer and histological normal specimens followed by an amplification protocol for low levels of RNA (<0.1 microg) allowed us to distinguish between gene expression profiles characteristic of epithelial cells and those typical of stroma. Most of the genes identified in the nonmicrodissected tumor material as up-regulated were indeed overexpressed in cancerous epithelium rather than in the stromal compartment. We conclude that development of prostate cancer is associated with down-regulation as well as up-regulation of genes that show complex differential regulation in epithelia and stroma. Some of the gene expression alterations identified in this study may prove useful in the development of novel diagnostic and therapeutic strategies.

Dataset Information

A Balanced Tissue Composition Reveals New Metabolic and Gene Expression Markers in Prostate Cancer.

Publications

A Balanced Tissue Composition Reveals New Metabolic and Gene Expression Markers in Prostate Cancer.

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