Cancer arises in normal cells by means of genetic and epigenetic alterations. Our research focuses on understanding the molecular mechanisms regulating tumor homeostasis and response to anti-cancer therapy.

In other words, we want to understand how tumor tissues balance self-growth and interactions with the host. Both processes can ensure cancer survival and govern critical cell decisions such as to whether self-renew, differentiate or die (i.e. homeostasis). Ultimately, tumor homeostasis can be viewed as the dark side of the normal tissue self-regulation. 

We also want to know how do cancer cells deal with the therapy-induced stress.

Learning about these mechanisms will enable us to identify cancer-specific vulnerabilities, which in turn may pave the way to identifying more effective treatments.



One of the approaches we take is to model human cancers in laboratory animals using genetic alterations described in patients (see example in figure below). In turn, these models are used to study:

  • genotype-to-molecular phenotype connections (Fig.1b)
  • molecular mechanisms of tumor growth and response to therapy (Fig.1c)
  • target discovery and validation (Fig.1d)

In the long run, we aim to exploit animal models as “surrogate” or “targeted” patients to ultimately identify novel anti-cancer treatments and biomarkers for response.

Mechanistically, we focus on genetic and epigenetic control of gene expression in cancer cells. We make use of a combination of experimental and computational approaches among which: adult stem cells genetic engineering, in vivo tumor modeling, in vivo genetic screens and genome-wide binding, occupancy & expression profiling by high throughput sequencing. As we thrive to achieve a conceivably rapid translation of our experimental efforts into clinical oncology, we leverage our results against large publicly available repositories containing patients’ molecular and clinical information.


Focus on solid tumors

Currently, we focus our work on solid tumors such as brain and lung cancers. In particular, the lab established a long-term research program dealing with the Glioblastoma Multiforme (GBM). The GBM is the most common primary brain tumor, and is currently incurable. It is urgent to devise treatments best fitting individual patients (precision medicine) and be able to predict the patients’ response to the chosen therapy. Both tumor heterogeneity and resistance to available treatments significantly affect GBM clinical management. As mentioned above, we approach these problems by creating and characterizing “humanized” animal models of GBM accurately reflecting patients at molecular level and exploiting these models in state-of-the-art genetic screens in vivo. In this setting, we aim to identify molecular biomarkers for response to standard-of-care for GBM patients as well as to uncover mechanisms of intrinsic and acquired resistance.

For lung cancer, we are interested in those tumor subtypes driven by the Kras oncogene, for which effective treatments are currently lacking.