Abstract
Identification of conserved co-expression networks is a useful tool for clustering groups of genes enriched for common molecular or cellular functions [1]. The relative importance of genes within networks can frequently be inferred by the degree of connectivity, with those displaying high connectivity being significantly more likely to be associated with specific molecular functions [2]. Previously we utilized cross-species network analysis to identify two network modules that were significantly associated with distant metastasis free survival in breast cancer. Here, we validate one of the highly connected genes as a metastasis associated gene. Tpx2, the most highly connected gene within a proliferation network specifically prognostic for estrogen receptor positive (ER+) breast cancers, enhances metastatic disease, but in a tumor autonomous, proliferation-independent manner. Histologic analysis suggests instead that variation of TPX2 levels within disseminated tumor cells may influence the transition between dormant to actively proliferating cells in the secondary site. These results support the co-expression network approach for identification of new metastasis-associated genes to provide new information regarding the etiology of breast cancer progression and metastatic disease.
Highlights
Advances in sequencing and computational technologies have enabled biologists to examine the complex inter-relationships between genes in an unprecedented scale
To determine whether TPX2 contributed to the distant metastasis free survival (DMFS) discriminatory capacity of this network short-hairpin RNA (shRNA) knockdown of Tpx2 was performed in a highly metastatic mouse mammary cell line, 6DT1 [13] originally derived from an MMTV-myc transgenic animal, which gene expression analysis suggests most closely resembles human luminal breast cancer [17] which form ER+ tumors after orthotopic implantation [18]
Tpx2 was partially depleted in 6DT1 cells by lentiviral transduction with two independent, nonoverlapping short-hairpin RNA interference constructs and stable, polyclonal pools were used in all subsequent experiments
Summary
Advances in sequencing and computational technologies have enabled biologists to examine the complex inter-relationships between genes in an unprecedented scale. High throughput technologies such as gene chip or RNA-sequence analysis permit investigators to determine how perturbations affect the transcriptional program of entire genomes, rather than select pathways. Network analysis can implicate novel or poorly annotated genes with particular biological functions or phenotypes based on statistically significant transcriptional correlations. We have utilized gene network analysis to investigate the transcriptional programs associated with breast cancer metastasis [3]. Metastasis, the colonization and growth of secondary tumors at sites distant from the primary lesion, remains a significant problem for the management of human neoplastic disease. Better understanding of the etiology of tumor progression and metastasis is important in the development of improved metastasis prevention strategies and anti-metastasis therapies
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
