pubmed.ncbi.nlm.nih.gov

A developmental model of sarcomagenesis defines a differentiation-based classification for liposarcomas - PubMed

A developmental model of sarcomagenesis defines a differentiation-based classification for liposarcomas

Igor Matushansky et al. Am J Pathol. 2008 Apr.

Abstract

The importance of adult stem cells in the development of neoplastic diseases is becoming increasingly well appreciated. We hypothesized that sarcomas of soft tissue could be categorized by their developmental/differentiation status from stem cell to mature tissue, similar to the hematological malignancies. We conducted gene expression analyses during in vitro differentiation of human mesenchymal stem cells into adipose tissue, as a representative mature connective tissue, and identified genes whose expression changed significantly during adipogenesis. Gene clustering and distance correlation analysis allowed the assignment of a unique time point during adipogenesis that strongly correlates to each of the four major liposarcoma subtypes. Using a novel gene expression strategy, in which liposarcomas are compared to their corresponding adipocytic maturing cells, we identified a group of genes overexpressed in liposarcomas that indicate the stage of differentiation arrest, ie, sharing a similar expression profile to adipocytic cells at a corresponding stage of differentiation, and a distinct set of genes overexpressed in liposarcomas that are not found in the corresponding stage of differentiation. We propose that the latter set is enriched for candidate transformation-associated genes. Our results indicate that a degree of developmental maturity can be quantitatively assigned to solid tumors, supporting the notion that transformation of a solid tumor stem cell can occur at distinct stages of maturation.

PubMed Disclaimer

Figures

Figure 1
Figure 1

A: hMSCs were plated at 2 × 104 and cultured in the presence of AM for 21 days as described in the Materials and Methods. At the indicated time points 100 μl of cells in culture were removed and counted via a Coulter counter. B: Separate T25 flasks of hMSCs undergoing adipogenesis were stained with Oil-Red-O at the indicated time points. Bottom panel shows day 0 hMSCs whereas top panel shows hMSCs after 21 days in AM. C: Similarity function (Find Similar Sample) of the GeneSpring package was used to compare each differentiation time point to the hMSCs (day 0). Two replicates were used for each analysis and the average shown.

Figure 2
Figure 2

Hierarchical clustering of hMSCs differentiating along the adipocytic lineage in relation to human liposarcomas using the full U133a gene set (A) and using the 69 adipocytic-maturation-specific genes (B). Each hMSC differentiating time point is represented by two replicates and compared to five samples of each of five liposarcoma subtypes as well as to five specimens of normal human fat, visually presented using GeneSpring. C: Distance mapping analysis comparing each liposarcoma subtype and normal fat as a control to adipogenesis time points using the 69 adipocytic-maturation-specific genes as the gene set.

Figure 3
Figure 3

A: Immunoblot analysis of the indicated proteins at the indicated times of adipogenesis. B: Immunohistochemical analysis of a sarcoma tissue microarray examining for expression of the indicated proteins on the indicated representative liposarcoma subtypes. Percentages represent number of liposarcoma subtypes staining positive compared to number present on the tissue microarray.

Figure 4
Figure 4

A: Schematic representation of the differential gene expression approach used to eliminate maturation-related genes from potential tumor genes. See text for details. B: Schematic representation of gene lists. Each Venn diagram is a composite of genes either overexpressed (left) or underexpressed (right) in the tumor versus normal fat (red circles) or corresponding differentiating cells versus differentiated cells (yellow circle). The overlapping genes are indicated in orange. C: Percentage of overlapping differentiation genes in the subsets of genes differentially expressed as a function of genes overexpressed (blue), under (red), and total (green) in tumors versus normal fat in tumor versus DD (dedifferentiated), Pl (pleomorphic), M (myxoid), R (round cell) liposarcoma.

Figure 5
Figure 5

A: Schematic representation of the correlation of adipogenesis to liposarcoma transformation. B: Schematic representation of the similarity of hematopoietic differentiation to neoplastic formation modified from DeVita, VT, Hellman S, Rosenberg SA: Cancer: Principles and Practice of Oncology, Ed 7, Philadelphia, Lippincott Williams and Wilkins, 2005.

Similar articles

Cited by

References

    1. Sieber OM, Tomlinson SR, Tomlinson IP. Tissue, cell and stage specificity of (epi)mutations in cancers. Nat Rev Cancer. 2005;5:649–655. - PubMed
    1. Orfao A, Schmitz G, Brando B, Ruiz-Arguelles A, Basso G, Braylan R, Rothe G, Lacombe F, Lanza F, Papa S, Lucio P, San Miguel JF. Clinically useful information provided by the flow cytometric immunophenotyping of hematological malignancies: current status and future directions. Clin Chem. 1999;45:1708–1717. - PubMed
    1. Fenske TS, Pengue G, Mathews V, Hanson PT, Hamm SE, Riaz N, Graubert TA. Stem cell expression of the AML1/ETO fusion protein induces a myeloproliferative disorder in mice. Proc Natl Acad Sci USA. 2004;101:15184–15189. - PMC - PubMed
    1. Yuan Y, Zhou L, Miyamoto T, Iwasaki H, Harakawa N, Hetherington CJ, Burel SA, Lagasse E, Weissman IL, Akashi K, Zhang DE. AML1-ETO expression is directly involved in the development of acute myeloid leukemia in the presence of additional mutations. Proc Natl Acad Sci USA. 2001;98:10398–10403. - PMC - PubMed
    1. Segal NH, Pavlidis P, Antonescu CR, Maki RG, Noble WS, DeSantis D, Woodruff JM, Lewis JJ, Brennan MF, Houghton AN, Cordon-Cardo C. Classification and subtype prediction of adult soft tissue sarcoma by functional genomics. Am J Pathol. 2003;163:691–700. - PMC - PubMed

Publication types

MeSH terms

Substances