Dataset Information

Dynamic re-wiring of apoptotic signaling networks enhances tumor cell killing by DNA damage

ABSTRACT: Crosstalk and complexity within signaling pathways has limited our ability to devise rational strategies for using network biology to treat human disease. This is particularly problematic in cancer where oncogenes that drive or maintain the tumorigenic state alter the normal flow of molecular information within signaling networks that control growth, survival and death. Understanding the architecture of oncogenic signaling pathways, and how these networks are re-wired by ligands or drugs, could provide opportunities for the specific targeting of oncogene-driven tumors. Here we use a systems biology-based approach to explore synergistic therapeutic strategies to optimize the killing of triple negative breast cancer cells, an incompletely understood tumor type with a poor treatment outcome. Using targeted inhibition of oncogenic signaling pathways combined with DNA damaging chemotherapy, we report the surprising finding that time-staggered EGFR inhibition, but not simultaneous co-administration, can dramatically sensitize the apoptotic response of a subset of triple-negative cells to conventional DNA damaging agents. A systematic analysis of the order and timing of inhibitor/genotoxin presentation—using a combination of high-density time-dependent activity measurements of signaling networks, gene expression profiles, cell phenotypic responses, and mathematical modeling—revealed an approach for altering the intrinsic oncogenic state of the cell through dynamic re-wiring of oncogenic signaling pathways. This process converts these cells to a less tumorigenic state that is more susceptible to DNA damage-induced cell death, through re-activation of an extrinsic apoptotic pathway whose function is suppressed in the oncogene-addicted state. Three or 4 replicates of 3 different cell lines at time points 0minutes, 30minutes, 6 hours and 1 day after EGFR inhibition with erlotinib

ORGANISM(S): Homo sapiens

SUBMITTER: Lee MJ

PROVIDER: S-ECPF-GEOD-30516 | biostudies-other | 2012 May

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Background: Epithelial-stromal crosstalk plays a critical role in invasive breast cancer (IBC) pathogenesis; however, little is known on a systems level about how epithelial-stromal interactions evolve during carcinogenesis. Results: We develop a framework for building genome-wide epithelial-stromal co-expression networks composed of pairwise co-expression relationships between mRNA levels of genes expressed in the epithelium and stroma across a population of patients. We apply this method to laser capture micro-dissection expression profiling datasets in the setting of breast carcinogenesis. Our analysis shows that epithelial-stromal co-expression networks undergo extensive re-wiring during carcinogenesis, with the emergence of distinct network hubs in normal breast, ER-positive IBC, and ER-negative IBC, and the emergence of distinct patterns of functional network enrichment. In contrast to normal breast, the strongest epithelial-stromal co-expression relationships in IBC mostly represent self-loops, in which the same gene is co-expressed in epithelial and stromal regions. We validate this observation using an independent laser capture micro-dissection dataset and confirm that self-loop interactions are significantly increased in cancer by performing computational image analysis of epithelial and stromal protein expression using images from the Human Protein Atlas. Conclusions: Epithelial-stromal co-expression network analysis represents a new approach for systems-level analyses of spatially-localized transcriptomic data. The analysis provides new biological insights into the re-wiring of epithelial-stromal co-expression networks and the emergence of epithelial-stromal co-expression self-loops in breast cancer. The approach may facilitate the development of new diagnostics and therapeutics targeting epithelial-stromal interactions in cancer. 36 flash-frozen human primary breast cancer samples were subjected to laser capture microdissection to separately isolate matched tumor epithelial and tumor-associated stromal components. RNA was isolated, subjected to 2 rounds of amplification, and hybridized on Agilent 4x44K microarrays along with a common reference (single round-amplified commercially obtained Universal Human Reference RNA) in a dyeswap design. For two samples of tumor-associated stroma, a second technical replicate was performed. Samples were labelled as ER-positive based on ESR1 gene expression levels in the tumor epithelium, using univariate Gaussian mixture model-based clustering via the mclust package in R.

Dataset Information

Dynamic re-wiring of apoptotic signaling networks enhances tumor cell killing by DNA damage

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets