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Overview | Research Directions | Group members | Grants | Selected Publications


The main focus of the laboratory is the development of novel approaches to understand the biological mechanisms that underlie cancer genesis, cancer evolution and cancer treatment resistance. We design and combine bioinformatics approaches, computational strategies and algorithms for the analysis of next generation sequencing and high-density array data, and systems biology methods. We are particularly interested in exploiting our analyses to identify prognostic and predictive cancer biomarkers.

Research Directions

Determinants of cancers: Regulatory regions mediate a variety of cellular processes at the transcriptional, post-transcriptional, and post-translational levels. Inherited polymorphisms and somatic aberrations within regulatory elements can affect regulatory mechanisms impacting gene expression and were shown to increase cancer susceptibility and to drive progression. We design and implement novel computational strategies to understand the intricate links between inherited polymorphisms and somatic events.

Liquid biopsies: Plasma DNA contains circulating tumor DNA (ctDNA) released from widespread tumor cells, that potentially uncovers full cancer heterogeneity. We develop advanced ad-hoc computational methods to analyze next generation sequencing data obtained from plasma DNA.

Allele-specific expression in cancer: Allele-specific expression (ASE) is a common phenomenon observed in human cells where transcription originates predominantly from one allele. Although many studies showed that ASE is essential for cellular programming a development as well as for the diversity of cellular phenotypes, limited studies have explored the role and impact of ASE in cancer genesis and progression. We analyze genomes of thousands of patients’ cancer cells to deeply investigate ASE phenomena in cancer and identify cancer specific ASE genes and cancer specific ASE patterns.

Group members

  • Alessandro Romanel
  • Francesco Gandolfi, Post-doctoral fellow
  • Samuel Valentini, PhD student 
  • Chiara Lattanzi, Master student QCB
  • Stefania Pirrotta, Master student QCB
  • Lara Pozza, Bachelor student BST
  • Ermano Buikis, Bachelor student BST
  • Mattia Carolo, Bachelor student DISI


2018-2022, AIRC MFAG

Selected publications

A. Romanel*, S. Garritano*, B. Stringa, M. Blattner, D. Dalfovo, D. Chakravarty, D. Soong, K.A. Cotter, G. Petris, P. Dhingra, P. Gasperini, A. Cereseto, O. Elemento, A. Sboner, E. Khurana, A. Inga, M.A. Rubin, F. Demichelis. Inherited determinants of early recurrent somatic mutations in prostate cancer. Nature Communications, 8:48, 2017.

A. Romanel, T. Zhang, O. Elemento, F. Demichelis. EthSEQ: ethnicity annotation from whole exome sequencing data. Bioinformatics 33(15):2402-2404, 2017.

A. Romanel*, D. Gasi Tandefelt*, V. Conteduca, A. Jayaram, N. Casiraghi, D. Wetterskog, S. Salvi, D. Amadori, Z. Zafeiriou, P. Rescigno, D. Bianchini, G. Gurioli, V. Casadio, S. Carreira, J. Goodall, A. Wingate, R. Ferraldeschi, N. Tunariu, P. Flohr, U. De Giorgi, J.S. de Bono, F. Demichelis*, G. Attard*. Plasma AR and abiraterone-resistant prostate cancer. Science Translational Medicine 7 312re10, 2015.

A. Romanel, S. Lago, D. Prandi, A. Sboner, F. Demichelis. ASEQ: fast allele-specific studies from next-generation sequencing data. BMC Medical Genomics 8(1):9, 2015.

S. Garritano*, A. Romanel*, Y. Ciribilli*, A. Bisio, A. Gavoci, A. Inga, F. Demichelis. In-silico identification and functional validation of allele-dependent AR enhancers. Oncotarget 6(7):4816-4828, 2015.

S. Carreira*, A. Romanel*, J. Goodall*, E. Grist, R. Ferraldeschi, S. Miranda, D. Prandi, D. Lorente, J-S. Frenel,C. Pezaro, A. Omlin, D.N. Rodrigues, P. Flohr, N. Tunariu, J.S. de Bono, F. Demichelis*, G. Attard*. Tumor clone dynamics in lethal prostate cancer. Science Translational Medicine 6 254ra125, 2014.