Skip to main page content
U.S. flag
See More

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2004 Jan 13;101(2):615-20.
doi: 10.1073/pnas.2536479100.

In silico dissection of cell-type-associated patterns of gene expression in prostate cancer

Robert O Stuart  1 , William Wachsman, Charles C Berry, Jessica Wang-Rodriguez, Linda Wasserman, Igor Klacansky, Dan Masys, Karen Arden, Steven Goodison, Michael McClelland, Yipeng Wang, Anne Sawyers, Iveta Kalcheva, David Tarin, Dan Mercola
Affiliations

In silico dissection of cell-type-associated patterns of gene expression in prostate cancer

Robert O Stuart et al. Proc Natl Acad Sci U S A. .

Abstract

Prostate tumors are complex entities composed of malignant cells mixed and interacting with nonmalignant cells. However, molecular analyses by standard gene expression profiling are limited because spatial information and nontumor cell types are lost in sample preparation. We scored 88 prostate specimens for relative content of tumor, benign hyperplastic epithelium, stroma, and dilated cystic glands. The proportions of these cell types were then linked in silico to gene expression levels determined by microarray analysis, revealing unique cell-specific profiles. Gene expression differences for malignant and nonmalignant epithelial cells (tumor versus benign hyperplastic epithelium) could be identified without being confounded by contributions from stroma that dominate many samples or sacrificing possible paracrine influences. Cell-specific expression of selected genes was validated by immunohistochemistry and quantitative PCR. The results provide patterns of gene expression for these three lineages with relevance to pathogenetic, diagnostic, and therapeutic considerations.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Ternary graph of sample characteristics. Eighty-eight prostatectomy samples from 41 individuals comprising 50 nontumor and 38 tumor-containing specimens were scored for proportional content of tumor, BPH, stroma, and dilated cystic glands. Vertices represent pure tissue types. Epithelia of dilated cystic glands, nerves, and vessels are small components. Note the wide range of proportions of tumor and stromal cells. Estimated tumor percentages ranged from 0.3% through 100%. The proportions were used in the linear models (xkj in Eq. 1) for cell-associated gene expression.
Fig. 2.
Fig. 2.
Statistical modeling. (A) Regression on cell type. The expected cell type expression levels are the coefficients β in models of gene expression as a linear function of fractional cell type (Eq. 1) and were calculated by using the lsfit function in r. Modified t statistics were calculated as t = β/(0.0029 + βse), where βse is the standard error of the coefficient. “Volcano plot” representations of the data reveal genes associated with the tumor cell type with high confidence in the upper right portion of the graph. Similar plots for the BPH and stroma cell types are omitted (see supporting information). (B) Multiple regression on percentage stroma, BPH, and tumor allows direct identification of tumor–BPH differences beyond the effect of stroma. Posterior probabilities akin to those in Efron et al. (9) used an estimating equations approach (gee library for r) (10). BPH-specific gene expression is in the upper left (note CK15), and tumor-specific gene expression is in the upper right (tubulin-β) of the graph. (C) Tumor–stroma interaction model. Inclusion of cross-product terms in the linear model identifies genes in which the contribution of a cell may be more or less than in another tissue environment; i.e., the contributions of individual cell types to the overall profile depend on the proportions of other types present. Data show tumor-stroma cross-product t statistics versus probabilities (y axis), which were calculated as in B by comparing actual with permuted t statistics. The upper left portion of graph represents a large number of stroma-associated genes with a high likelihood deviation from a strictly linear model. The right portion of the graph reveals a number of tumor-associated genes that appear to deviate from linearity, albeit with considerably less confidence. Among these is TCRγ, which is among the most discriminant tumor/no tumor genes even at low proportions of tumor; i.e., the expression of TCRγ is greater than that predicted by proportion of tumor cells alone. The stromal gene with the greatest deviation was TGF-β2, a candidate paracrine signaling molecule in prostate cancer.
Fig. 3.
Fig. 3.
Global view of cell-type-associated gene expression. The t statistics calculated from two-cell-type linear models embody the direction and magnitude as well as goodness of fit of the coefficients. t statistics were filtered to include genes with >4-fold predicted changes in between pure and 0% specific cell type sample composition and an absolute correlation coefficient of >0.25. By these criteria, 3,387 transcripts displayed cell-type-associated gene expression (see supporting information), and the t statistics are visualized here by hierarchical clustering. Red corresponds to a positive correlation, and green corresponds to a negative correlation between cell type (B, BPH; S, stroma; T, tumor) and gene expression. Representative genes from each group are at right. Previously available tumor/no tumor distinction is represented by middle labels. The analysis provides for further classification of “no tumor” markers into stromal (the vast majority) and BPH-associated genes. Likewise, “tumor” markers can be subdivided. Markers of the tumor–stroma difference may reflect epithelial mesenchymal differences in gene expression. Genes that differ according to the tumor–BPH distinction may reflect changes between malignant and nonmalignant states of prostate epithelium.
Fig. 4.
Fig. 4.
Validation by immunohistochemistry. The cell-type-specific expression of representative proteins was examined by immunohistochemistry. (a) β-tubulin. (b) Prostaglandin-D2 synthase (PD2S). (c) Prostate-specific membrane antigen (PSMA). (d) Desmin. (e) CK15. (f) PSA. Single and double arrows indicate sites of differential expression (see text). T and N indicate tumor-infiltrated and normal stroma, respectively.
See this image and copyright information in PMC

References

    1. Howe, H. L., Wingo, P. A., Thun, M. J., Ries, L. A. G., Rosenberg, H. M., Feigal, E. G. & Edwards, B. K. (2001) J. Natl. Cancer Inst. 93, 824–842. - PubMed
    1. DeVita, V. T., Jr., & Bleickardt, E. W. (2001) Cancer J. 7, Supp. 1, S2–S13. - PubMed
    1. Dhanasekaran, S. M., Barrette, T. R., Ghosh, D., Shah, R., Varambally, S., Kurachi, K., Pienta, K. J., Rubin, M. A. & Chinnaiyan, A. M. (2001) Nature 412, 822–826. - PubMed
    1. Ho, S. M. & Lau, K. M. (2002) Curr. Urol. Rep. 3, 53–60. - PubMed
    1. Rhodes, D. R., Barrette, T. R., Rubin, M. A., Ghosh, D. & Chinnaiyan, A. M. (2002) Cancer Res. 62, 4427–4433. - PubMed

Publication types