Cancer Systems Biology
Group leader: Zoltan Szallasi
Members: Andrea Marion Marquard, Aron Charles Eklund, Francesco Favero, Marcin Krzystanek, Nicolai Juul Birkbak, Russell Hanson, Tejal Joshi
Guest member: Agnieszka Sierakowska Juncker
Catalog of previous student projects.
About the group
Our group specializes in methods for the analysis and interpretation of high-throughput measurements with the goal to understand mechanisms of tumor development and drug resistance
Predictive biomarkers of agent-specific drug response in cancer patients
For the most common cancers of the breast, lung, or colon, an individual patient has a 20-40% chance of responding to a particular chemotherapeutic agent. Thus, to maximize the chances of curing the patient, a typical treatment regimen may involve several drugs, most of which are not effective against the cancer and cause only side effects. We use causative learning approaches such as RNAi screens to discover candidate predictive biomarkers of drug response, which we then evaluate in tumor molecular (RNA, DNA) profiles from clinical trials. These predictive biomarkers will enable personalized patient treatment and reduce unnecessary suffering caused by ineffective therapy.
Novel methods for molecular characterization of tumors
A typical gene expression or CGH microarray measurement yields 104 ~ 106 values per array. We are developing methods to reduce this data to a small number of robust, biologically- or clinically-relevant parameters. These parameters will allow us to probe the underlying status of a given tumor, which may prove to be prognostic or predictive of drug response.
Selected recent publications
Full list of CBS publications
Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets.
Swanton C, Larkin JM, Gerlinger M, Eklund AC, Howell M, Stamp G, Downward J, Gore M, Futreal PA, Escudier B, Andre F, Albiges L, Beuselinck B, Oudard S, Hoffmann J, Gyorffy B, Torrance CJ, Boehme KA, Volkmer H, Toschi L, Nicke B, Beck M, Szallasi Z.
Genome Med. 2010 Aug 11;2(8):53.
Assessment of an RNA interference screen-derived mitotic and ceramide pathway metagene as a predictor of response to neoadjuvant paclitaxel for primary triple-negative breast cancer: a retrospective analysis of five clinical trials.
Juul N, Szallasi Z, Eklund AC, Li Q, Burrell RA, Gerlinger M, Valero V, Andreopoulou E, Esteva FJ, Symmans WF, Desmedt C, Haibe-Kains B, Sotiriou C, Pusztai L, Swanton C.
Lancet Oncol. 2010 Apr;11(4):358-65.
Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer.
Li Y, Zou L, Li Q, Haibe-Kains B, Tian R, Li Y, Desmedt C, Sotiriou C, Szallasi Z, Iglehart JD, Richardson AL, Wang ZC.
Nat Med. 2010 Feb;16(2):214-8.
Optimization of the BLASTN substitution matrix for prediction of non-specific DNA microarray hybridization.
Eklund AC, Friis P, Wernersson R, Szallasi Z.
Nucleic Acids Res. 2010 Mar;38(4):e27.