Sunday, June 14, 2015

How Indirect Reciprocity is An Evolutionary Force for Cooperation

A co-authored paper and a fascinating look at how indirect reciprocity is an evolutionary force for cooperation --by Martin Nowak in the Proceedings of National Academy of Sciences.
 

Abstract

Indirect reciprocity is a mechanism for the evolution of cooperation that is relevant for pro-social behavior among humans. Indirect reciprocity means that my behavior towards you also depends on what you have done to others. Indirect reciprocity is associated with the evolution of social intelligence and human language. Most approaches to indirect reciprocity assume obligatory interactions, but here we explore optional interactions. In any one round a game between two players is offered. A cooperator accepts a game unless the reputation of the other player indicates a defector. For a game to take place, both players must accept. In a game between a cooperator and a defector, the reputation of the defector is revealed to all players with probability Q  . After a sufficiently large number of rounds the identity of all defectors is known and cooperators are no longer exploited. The crucial condition for evolution of cooperation can be written as hQB>1, where h   is the average number of rounds per person and B=(b/c)−1 specifies the benefit-to-cost ratio. We analyze both stochastic and deterministic evolutionary game dynamics. We study two extensions that deal with uncertainty: hesitation and malicious gossip.

SOURCE: www.pnas.org

Only three driver gene mutations are required for the development of lung and colorectal cancers

A recent collaborative study published by the Proceedings of the National Academy of Sciences--by.. C. Tomasetti, L. Marchionni, M. Nowak, G. Parmigiani and B. Vogelstein shows how only three genetic mutations can drive both lung and colorectal cancers.
 

Abstract

Cancer arises through the sequential accumulation of mutations in oncogenes and tumor suppressor genes. However, how many such mutations are required for a normal human cell to progress to an advanced cancer? The best estimates for this number have been provided by mathematical models based on the relation between age and incidence. For example, the classic studies of Nordling [Nordling CO (1953) Br J Cancer 7(1):68–72] and Armitage and Doll [Armitage P, Doll R (1954) Br J Cancer 8(1):1–12] suggest that six or seven sequential mutations are required. Here, we describe a different approach to derive this estimate that combines conventional epidemiologic studies with genome-wide sequencing data: incidence data for different groups of patients with the same cancer type were compared with respect to their somatic mutation rates. In two well-documented cancer types (lung and colon adenocarcinomas), we find that only three sequential mutations are required to develop cancer. This conclusion deepens our understanding of the process of carcinogenesis and has important implications for the design of future cancer genome-sequencing efforts.

SOURCE: www.pnas.org

Complexity and stability in growing cancer cell populations

A recent collaborative paper in the Proceedings of the National Academy of Sciences by the Program for Evolutionary Dynamics, the Dana-Farber Institute, Chalmers University of Technology and the University of Gothenburg, looks at the complex growth and patterns of cancer cell populations:
 
Abstract of the Article:
 
Evolutionary game theory (EGT) describes dynamics in populations in which individual fitness can change because of the interactions with others, called frequency-dependent selection (1). Interactions are driven by differences in phenotype. EGT has been proposed as a framework for evolutionary dynamics of tumors (2). An underlying assumption is that different cancer cell types within a tumor engage in different heritable behavior; thus, frequency-dependent selection acts. Until now there has been little direct empirical evidence for this.
                          
The study by Archetti et al. (3) demonstrates frequency-dependent growth rates of two phenotypically distinct cancer subclones. One clone produced the insulin-like growth factor (IGF)-II, the other did not. In a mix of producers and nonproducers, the growth rates of both clones varied with the frequency of producers. Because a similar effect was shown when varying the concentration of serum, the production of IGF-II could be viewed as a public goods game.
 

How the Micro-Environment of Tumors Can Impair Targeted Therapies for Cancer


Recent collaborative research at the Program for Evolutionary Dynamics looks at how the microenvironment of a tumor can impair the efficacies of targeted treatment. Their findings were published in Science Daily.
Cancer Therapy 'tumor sanctuaries' and the Breeding Ground of Resistance
Science Daily

Tumors acquiring resistance is one of the major barriers to successful cancer therapy. Feng Fu, Sebastian Bonhoeffer (ETH Zurich) and their collaborator Martin Nowak (Harvard) use mathematical models to characterize how important aspects of tumor microenvironment can impair the efficacy of targeted cancer therapies.
Failure of cancer therapy is commonly attributed to pre-existing resistant mutants already present prior to treatment. However, the research publishing this week in PLOS Computational Biology highlights the important role of tumor sanctuaries in the rapid acquisition of resistance.
The authors offer an in silico model for predicting treatment outcomes that depend on the tumor microenvironment within a solid tumor or across metastases. The results show that resistance in non-sanctuary sites is likely originated from sanctuaries with little drug exposure.
There is increasing evidence that the tumor microenvironment influences cell sensitivity to drugs mediating the evolution of drug resistance. The results provide new insights into understanding why cancers tend to quickly become resistant, and that cell migration and the presence of sanctuary sites with little drug exposure are essential to this end. The researchers say: "In order to improve our ability to fight against cancer, not only we should search for more effective therapies that sufficiently target tumor genetic heterogeneity, but also such efforts will have to be paralleled with finding novel delivery approaches aimed at eliminating potential tumor sanctuaries."

Wednesday, May 6, 2015

Three driver gene mutations are required for development of lung and colorectal cancers

A recent revealing article from the Proceedings of the National Academy of Science of the United States of America. Martin Nowak from the Program for Evolutionary Dynamics, co-authors. 

 

Abstract

Cancer arises through the sequential accumulation of mutations in oncogenes and tumor suppressor genes. However, how many such mutations are required for a normal human cell to progress to an advanced cancer? The best estimates for this number have been provided by mathematical models based on the relation between age and incidence. For example, the classic studies of Nordling [Nordling CO (1953) Br J Cancer 7(1):68–72] and Armitage and Doll [Armitage P, Doll R (1954) Br J Cancer 8(1):1–12] suggest that six or seven sequential mutations are required. Here, we describe a different approach to derive this estimate that combines conventional epidemiologic studies with genome-wide sequencing data: incidence data for different groups of patients with the same cancer type were compared with respect to their somatic mutation rates. In two well-documented cancer types (lung and colon adenocarcinomas), we find that only three sequential mutations are required to develop cancer. This conclusion deepens our understanding of the process of carcinogenesis and has important implications for the design of future cancer genome-sequencing efforts.

Read Full Article

NEURO.tv 16 - Memories, false memories and consciousness.




The Jeffrey Epstein VI Foundation is proud to support NeuroTV, a monthly online conversation between neuroscientists, psychologists and philosophers about the brain, cognition and mind. Every month, NeuroTV airs a videotaped discussion and/or interview with detailed graphics and drawings to help a general audience understand the most cutting edge research about how the brain controls our psychology and behaviors.

NeuroTV's Episode 16 - Memories, false memories and consciousness In this episode, Felipe de Brigard, Assistant Professor at Duke University, discusses memory, false memories and consciousness.

Friday, April 3, 2015

The Jeffrey Epstein VI Foundation Funds Study that Identifies How Tumors Grow

 
 
NEW YORK, / Mathematic studies at the Program for Evolutionary Dynamics (PED) at Harvard University, and funded by the Jeffrey Epstein VI Foundation, have shown that the most aggressive cells within tumors can be visually identified for elimination. These aggressive cells are the driver mutations that drive the tumor's growth. The study, which shows a topological map of what to look for when examining tumors, comes at a needed time in cancer research, for while tumor cells can be extracted from biopsy, it's very difficult to know which cells are actually causing the growth. And for inhibitor drugs to work, they have to target the most genetically aggressive cancer cells, amongst others.

The Program, or PED, studies the evolution of living systems with the use of mathematics. Much of their work focuses on the evolution of cancer and has significantly impacted treatment at universities across the country. Funding their work is an inscrutable New York private fund manager, called Jeffrey Epstein. Epstein established the PED in 2003 with a $30 million dollar gift to the university and his science foundation is one of the largest donors to individual scientists around the world including a list of luminaries such as Stephen Hawking and Nobel laureates, Gerard 't Hooft, David Gross and Frank Wilczek.

One of the great challenges of cancer is that tumors are genetically diverse, making it extremely difficult to tackle them with tailored inhibitor drugs. In 2010, the PED showed that even small solid tumors contain at least 40 to 100 genetic mutations within its structure, and that only 5 to 15 of those actually drive tumor growth. The findings highlighted the urgency for better genetic profiling of tumor masses beyond random excision, and the need to pinpoint the minority of tumor cell aggressors.

The PED's spatial modeling of how tumors grow however, now offers the first mathematically proven map of how to visually target the key aggressors within a tumor.

"Mathematics in medical research reveals patterns that are otherwise hidden and it's exhilarating when a mathematician can determine cellular behavior with the precision of an engineer," Jeffrey Epstein asserted.