Genetic network analysis of human CD34+ hematopoietic stem/precursor cells

Enhancing biological relevance of a weighted gene co-expression network for functional module identification

Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structural information to represent the gene co-expression network. The entire backbone network is decoupled into a number of coherent sub-networks, and then the functional modules are reconstructed from these sub-networks to ensure minimum redundancy. The method was tested with a simulated gene expression dataset and case-control expression datasets of autism spectrum disorder and colorectal cancer studies. The results indicate that the proposed method can accurately identify clusters in the simulated dataset, and the functional modules of the backbone network are more biologically relevant than those obtained from the original approach.

Rare cell proteomic reactor applied to stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomics study of human embryonic stem cell differentiation

The molecular basis governing the differentiation of human embryonic stem cells (hESCs) remains largely unknown. Systems-level analysis by proteomics provides a unique approach to tackle this question. However, the requirement of a large number of cells for proteomics analysis (i.e. 10(6)-10(7) cells) makes this assay challenging, especially for the study of rare events during hESCs lineage specification. Here, a fully integrated proteomics sample processing and analysis platform, termed rare cell proteomic reactor (RCPR), was developed for large scale quantitative proteomics analysis of hESCs with ∼50,000 cells. hESCs were completely extracted by a defined lysis buffer, and all of the proteomics sample processing procedures, including protein preconcentration, reduction, alkylation, and digestion, were integrated into one single capillary column with a strong cation exchange monolith matrix. Furthermore, on-line two-dimensional LC-MS/MS analysis was performed directly using RCPR as the first dimension strong cation exchange column. 2,281 unique proteins were identified on this system using only 50,000 hESCs. For stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative study, a ready-to-use and chemically defined medium and an in situ differentiation procedure were developed for complete SILAC labeling of hESCs with well characterized self-renewal and differentiation properties. Mesoderm-enriched differentiation was studied by RCPR using 50,000 hESCs, and 1,086 proteins were quantified with a minimum of two peptides per protein. Of these, 56 proteins exhibited significant changes during mesoderm-enriched differentiation, and eight proteins were demonstrated for the first time to be overexpressed during early mesoderm development. This work provides a new platform for the study of rare cells and in particular for further elucidating proteins that govern the mesoderm lineage specification of human pluripotent stem cells.

Unique biological properties and application potentials of CD34+ CD38- stem cells from various sources

OBJECTIVE

Somatic CD34+ CD38- stem cells can differentiate into cells of hematopoietic and endothelial lineages and have been clinically used to treat diseases. These stem cells can be obtained from cord blood (CB), bone marrow or granulocyte-macrophage colony-stimulating factor-mobilized peripheral blood. Unmasking genes differentially expressed in hematopoietic stem cells (HSCs) from different anatomic locations can improve our understanding of their basic biological features and help in clinical decision making when applying different HSCs.

MATERIALS AND METHODS

We performed microarray analysis on human CD34+ CD38- HSCs isolated from CB, bone marrow and peripheral blood. Systems biology and advanced bioinformatics tools were used to better understand the biological modules and genetic networks accompanying each HSC subtype.

RESULTS

We identified HSC genes differentially expressed in various HSCs and found them to be involved in critical biological processes such as cell cycle regulation, cell motility, and endogenous antigen presentation. Among these three HSC types, HSCs from CB expressed the fewest rejection and immune response-associated genes, thereby showing the best potential as a transplantation source. Analysis of HSC-enriched genes using systems biology tools revealed a complex genetic network functioning in different CD34+ CD38- cells, in which several genes act as hubs, such as MYC in CB HSCs and hepatic growth factor in bone marrow HSCs, to maintain the stability or connectivity of the whole network.

CONCLUSION

This study provides the foundation for a more detailed understanding of CD34+ CD38- HSCs from different sources, and reveals the potentials of different HSCs for different clinical applications.

Increased epithelial stem cell traits in advanced endometrial endometrioid carcinoma

Background

It has been recognized cancer cells acquire characters reminiscent of those of normal stem cells, and the degree of stem cell gene expression correlates with patient prognosis. Lgr5(+) or CD133(+) epithelial stem cells (EpiSCs) have recently been identified and these cells are susceptible to neoplastic transformation. It is unclear, however, whether genes enriched in EpiSCs also contribute in tumor malignancy. Endometrial endometrioid carcinoma (EEC) is a dominant type of the endometrial cancers and is still among the most common female cancers. Clinically endometrial carcinoma is classified into 4 FIGO stages by the degree of tumor invasion and metastasis, and the survival rate is low in patients with higher stages of tumors. Identifying genes shared between advanced tumors and stem cells will not only unmask the mechanisms of tumor malignancy but also provide novel therapeutic targets.

Results

To identify EpiSC genes in late (stages III-IV) EECs, a molecular signature distinguishing early (stages I-II) and late EECs was first identified to delineate late EECs at the genomics level. ERBB2 and CCR1 were genes activated in late EECs, while APBA2 (MINT2) and CDK inhibitor p16 tumor suppressors in early EECs. MAPK pathway was significantly up in late EECs, indicating drugs targeting this canonical pathway might be useful for treating advanced EECs. A six-gene mini-signature was further identified to differentiate early from advanced EECs in both the training and testing datasets. Advanced, invasive EECs possessed a clear EpiSC gene expression pattern, explaining partly why these tumors are more malignant.

Conclusions

Our work provides new insights into the pathogenesis of EECs and reveals a previously unknown link between adult stem cells and the histopathological traits of EECs. Shared EpiSC genes in late EECs may contribute to the stem cell-like phenotypes shown by advanced tumors and hold the potential of being candidate therapeutic targets and novel prognosis biomarkers.