Characterizing the ecological and evolutionary dynamics of cancer.

Tumor initiation and progression are somatic evolutionary processes driven by the accumulation of genetic alterations, some of which confer selective fitness advantages to the host cell. This gene-centric model has shaped the field of cancer biology and advanced understanding of cancer pathophysiology. Importantly, however, each genotype encodes diverse phenotypic traits that permit acclimation to varied microenvironmental conditions.

A community computational challenge to predict the activity of pairs of compounds.

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing.

Systems biology: confronting the complexity of cancer.

The AACR-NCI Conference "Systems Biology: Confronting the Complexity of Cancer" took place from February 27 to March 2, 2011, in San Diego, CA. Several themes resonated during the meeting, notably (i) the need for better methods to distill insights from large-scale networks, (ii) the importance of integrating multiple data types in constructing more realistic models, (iii) challenges in translating insights about tumorigenic mechanisms into therapeutic interventions, and (iv) the role of the tumor microenvironment, at the physical, cellular, and molecular levels. The meeting highlighted concrete applications of systems biology to cancer, and the value of collaboration between interdisciplinary researchers in attacking formidable problems.

Systems biologists seek fuller integration of systems biology approaches in new cancer research programs.

Systems biology takes an interdisciplinary approach to the systematic study of complex interactions in biological systems. This approach seeks to decipher the emergent behaviors of complex systems rather than focusing only on their constituent properties. As an increasing number of examples illustrate the value of systems biology approaches to understand the initiation, progression, and treatment of cancer, systems biologists from across Europe and the United States hope for changes in the way their field is currently perceived among cancer researchers.

Report on EU-USA workshop: how systems biology can advance cancer research (27 October 2008).

The main conclusion is that systems biology approaches can indeed advance cancer research, having already proved successful in a very wide variety of cancer-related areas, and are likely to prove superior to many current research strategies. Major points include: Systems biology and computational approaches can make important contributions to research and development in key clinical aspects of cancer and of cancer treatment, and should be developed for understanding and application to diagnosis, biomarkers, cancer progression, drug development and treatment strategies. Development of new measurement technologies is central to successful systems approaches, and should be strongly encouraged.

Digital biology: an emerging and promising discipline.

This article examines the role of computation and quantitative methods in modern biomedical research to identify emerging scientific, technical, policy and organizational trends. It identifies common concerns and practices in the emerging community of computationally-oriented bio-scientists by reviewing a national symposium, Digital Biology: the Emerging Paradigm, held at the National Institutes of Health in Bethesda, Maryland, November 6th and 7th 2003. This meeting showed how biomedical computing promises scientific breakthroughs that will yield significant health benefits.