Posts Tagged ‘network analysis’

Author and Reporter: Anamika Sarkar, Ph.D.

Targeted therapies are proven approaches in Cancer and other complicated diseases. Degrees of activation of measured EGFR and ERB2/HER2 in cancer cells are thought of one of the ways to identify the scale of aggressiveness of cancer in tissues.  There are drugs, mostly for breast cancer, which targets inhibition of these receptors. Lapatinib (Tykerb, GSK – see Source for other targeted drugs) is the first drug which inhibits both EGFR and ERB2/HER2 gave hope to cancer patients, especially advanced ERB2-postive or metastatic breast cancer patients. Despite of proven high efficacy, Lapatinib didn’t show promising results in clinical responses due to acquired resistance.

Komurov et. al. (Mol. Systems.Biol., 2012) used network analysis along with experimental findings on cultured human breast cancer cell lines (SKBR3) and showed that a large part of acquired resistance to Lapatinib is due to  increased levels of activated states of glucose deprivation signaling network. The authors cultured ERB2-positive SKBR3 cells with increasing doses of Lapatinib, to make the control cell lines for analyzing their experimental results in comparison with (SKBR3- R),SKBR3-Resistant cells. Their Western Blot analysis showed that Lapatinib was successful to inhibit down signaling pathways to ERB2 and EGFR in both control and resistant cells however fails to induce apoptotic pathways in resistant cells when compared with the controlled cells.

To identify other factors which can influence the differential effects of Lapatinib on controlled and resistant cell lines, Komurov et. al. used a data biased random walk network analysis method called Netwalk (Komurov et. al. PLOS Comp Biol., 2010). Their method is data driven and based on comparative network analysis of gene expressions at different conditions rather than network analysis at one gene level. Their network analysis identified presence of high levels of genes which act as compensatory mechanisms for glucose deprivation (as shown in Figure 2 of the paper Komurov et. al. (2012) Figure 2). They showed validation of their network analysis findings using Western Blot analysis (as shown in Figure 3 of the paper Komurov et.al. (2012) Figure 3).


The authors’ results not only show a nice elegant way of finding new information using network analysis and experimental techniques together, but also points out an important concept which can be future of cancer therapy. Their results show that along with targeting mutated Oncogenes eg., EGFR and ERB2/HER2 as in case of Lapatinib, additional way of controlling the pathway of deprivation of glucose, can achieve better clinical responses for cancer patients with aggressive levels of cancer. Targeting glucose or pathways of glucose can be tricky, because of its ubiquitous links to many physiological functions, including metabolism. However, the levels at which these pathways need to be targeted to achieve certain positive responses at in-vitro, supported by systems biology methods, and then in-vivo studies can be informative.  Moreover, targeting many parts in the network in smaller amounts, along with targeted cancer drugs, may produce interesting results.


Komurov et.al. (2012) : http://www.ncbi.nlm.nih.gov/pubmed/22864381

A News and Views on Lapatinib (2005) : http://www.emilywaltz.com/Herceptin.pdf

Komurov et.al. (2010) – Article published on methods of Netwalk : http://www.ncbi.nlm.nih.gov/pubmed/20808879

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