Molecular predictors of drug response in breast cancer: Abstract 4963
Researchers at Lawrence Berkeley National Laboratory have identified gene expression signatures that could serve as biomarkers to predict how individuals will respond to the breast cancer drugs lapatinib and CI-1040. Their findings could help in individualizing treatments for women, and their methodologies could aid in identifying similar biomarkers for responses to other drugs and for other types of cancer.
"Individuals respond differently to different therapeutics because there are substantial differences in the spectrum of genetic, biological and epigenetic characteristics between breast cancers, although some recurrent abnormality patterns are emerging that define breast cancer subtypes" said Joe W. Gray, Ph.D., staff scientist and director of the Life Sciences Division at Lawrence Berkeley National Laboratory. "We need better ways to identify how we can best tailor existing therapies to individuals and how to target experimental agents."
Gray and his colleagues have developed a system to evaluate drug response comprised of a panel of 50 breast cancer cell lines. Each of these cell lines represents a single variant among the different genomic abnormalities found among breast cancers. They measured molecular profiles of each cell line and used these to identify subsets of cell lines that represent the subtypes observed in analyses of primary tumors.
By correlating the responses of these cells to targeted therapeutic drugs, the researchers were able to identify the molecular characteristics of cells that were most sensitive to the drugs. They tested their approach by analyzing responses of the cell line panel to lapatinib, a duel inhibitor of EGFR and ErbB2 and CI-1040, a MEK enzyme inhibitor. These studies defined molecular signatures that predicted individual responses among the cell lines to the drugs. For Lapatinib, the strongest correlate of response was amplification and over expression of ErBB2, consistent with clinical experience. For CI-1040, changes in the MEK pathway were most strongly associated with response. Predictors based on combinations of molecular correlates of response were able to quantitatively predict individual cell line responses.
"The concordance of our markers of response to lapatinib with those observed clinically suggests that the molecular markers identified in the cell line collection can be used to guide the use and testing of other approved and experimental drugs," Gray said. "This is important since it is logistically and financially impossible to test all of the experimental medicines in each cancer subtype. This ‘systems?approach suggests a way to prioritize drugs for use in patients and for initial clinical tests."
According to Gray, a large of number of emerging therapeutic agents should be prioritized for testing in the subtypes of breast cancer along with other cancers and their subtypes. When therapies are ineffective, they may produce harmful side effects and decrease a patient’s quality of life.
KRAS mutation in colorectal cancer is a predictive factor of response and progression free survival in patients treated with Cetuximab: Abstract 5671
Mutations in the KRAS oncogene could predict a lack of response to the drug cetuximab in patie nts with colorectal tumors. For those with the mutations, the drug is likely to be inefficient and possibly harmful, according to researchers at France’s Institut National de la Sante et de la Recherche Medicale (INSERM).
"Because a variety of different effective agents may now be available for any given type of cancer, deciding which treatment regimen is likely to be the most effective and the least toxic is more complicated than ever," said Pierre Laurent-Puig, M.D., PhD, a professor of Oncology at University of Paris-Decartes. "Characterizing the factors that are predictive of toxicity and efficacy could lead to significant improvement in both the quality of treatment and outcomes."
Cetuximab, an antibody that attacks the ability of cells to respond to the epidermal growth factor, has been previously shown to be effective in treating metastatic colorectal cancer.
Dr. Laurent-Puig and his colleagues studied 114 patients who had been given cetuximab in combination with another drug, irinotecan.
According to the researchers, approximately 30 percent of patients may have a poor response to the drug. Almost none of the patients who responded to the drug had an activating KRAS mutation, as compared to 35 percent of the patients with stable disease or 55 percent of the patients with progressive disease.
According to Dr. Laurent-Puig, this might be due to the cascade of molecular interactions that occur after epidermal growth factor meets its receptor, EGFR. The KRAS enzyme is a key component to these molecular actions, but mutations in the KRAS gene could allow the enzyme to function whether or not it receives the commanding signal from EGFR. Therefore, the inhibition of EGF receptor by cetuximab will not block the molecular signals that are activated farther down the cascade.
The researchers also determined that KRAS mutations are independent of another predictive marker of cetuximab response, skin toxic ity, which appears through a variety of forms including rashes, eczema and fissures. Skin toxicity also indicates a poor response to cetuximab. The study indicated that median survival is 15.6 months for patients with skin toxicity and without a KRAS mutation; whereas the survival is only 5.6 months for patients with the mutation, but no skin toxicity.
Dr. Laurent-Puig and colleagues are continuing to investigate the molecular biomarkers associated with cetuximab, including in tumors without the KRAS mutation that do not respond to the drug.
Recombinant peptides as biomarkers for cancer response to tyrosine kinase inhibitors combined with radiation: Abstract 4657
A new method for determining biomarkers could allow physicians to personalize lung or brain cancer therapy and lower the risk of unnecessary radiation treatments. Researchers at Vanderbilt University are using a biomarker library of peptides to determine whether or not tyrosine kinase inhibitor therapy, combined with radiation therapy, is indeed effective against lung or brain cancer.
"It is difficult to assess the response of cancer in the brain or lung to treatment, since those neoplasms are difficult to access safely," said Roberto Diaz, M.D., Ph.D., a resident in Radiation Oncology at the Vanderbilt-Ingram Cancer Center. "With the proper biomarkers physicians may be able to tell if a patient is not responding to the therapy and alter their treatment strategy accordingly."
The researchers screened lung and brain tumors to determine which peptides ?or protein fragments ?were active in the tissue environment surrounding the tumors. This phage displayed library ?called so after the bacteriophage viruses used to capture protein fragments ?was then isolated and tested.
With the library, Dr. Diaz and his colleagues could select peptides that bind to tumors that are affected by a combination of radiation and tyrosine kinase inhibitor the rapy, but not to tumors that do not respond to therapy. Ultimately, they uncovered 44 peptides that serve as biomarkers for response to therapy. According to Dr. Diaz, the physiological role of the 44 peptides might also point toward new cancer therapies.
"This study provides us with a starting point for understanding how tumors physiologically respond to therapy and a non-invasive technique for monitoring that response," Dr. Diaz said.
Cellular pharmacogenomic to discover genetic determinants of Tykerb response: Abstract 5684
A new high-throughput genetic analysis technique can reveal gene markers ?by the dozens ?that determine how a patient might respond to certain cancer drugs, according to scientists at the Translational Genomics Research Institute (TGen). The TGen researchers have found 164 genes that are involved in regulating the sensitivity of squamous cell head and neck cancer cells to lapatinib, a cancer drug that was recently approved for use in metastatic breast cancer under the name Tykerb.
The study, a collaboration with GlaxoSmithKline, evaluated 7,000 genetic targets in human head and neck cancer cells to discover specific genes that might shade an individual’s response to Tykerb.
"Our goal is to apply advanced cellular genomic strategies to assist clinical drug development by finding gene states that predict a patient’s response to a specific drug, and which combination of drugs produce the most favorable response." said Spyro Mousses, Ph.D., director of the Pharmaceutical Genomics Division at TGen. "In this study, we were able to discover new candidate gene states that may be useful in determining a patient’s sensitivity or resistance to Tykerb, and the results have revealed several sensitizing drug targets that reveal a set of candidate combination drugs that are predicted to be synergistic with Tykerb."
Tykerb is an enzyme inhibitor that effectively blocks two cell receptors , ERBB2 and EGFR, from receiving molecular signals. By blocking these signals, Tykerb could effectively shut down the growth of solid tumors, such as those found in breast, lung and head and neck cancer. However, molecular mechanisms within the cell, largely determined by genetics, could determine how effective cancer drugs are for a particular recipient, Mousses said.
To search for target genes that regulate Tykerb response, Mousses and his colleagues performed a genome-scale scan of two cancer cell lines using high-throughput RNAi, "interfering" RNA strands that bind to and knock out one gene individually, across the genome. It is a systematic and highly efficient technique that uses high-speed mechanization to quickly evaluate how specific genes might affect the cell’s sensitivity to an agent, Tykerb in this case.
The TGen researchers are currently in the process of refining their genetic "hits" and learning more about how cancer specific variations in these sensitizing genes might further affect Tykerb response. While their findings are still at a preliminary stage, Mousses and his colleagues believe their studies will provide important insights into how to predict oncology drug response and much needed genomic intelligence to support commercial drug development.
Source:American Association for Cancer Research
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