Combinatorial Development of Biomaterials for Clonal Growth of Human Pluripotent Stem Cells

July 3, 2012Both human embryonic stem cells and induced pluripotent stem cells can self-renew indefinitely in culture; however, present methods to clonally grow them are inefficient and poorly defined for genetic manipulation and therapeutic purposes. Here we develop the first chemically defined, xeno-free, feeder-free synthetic substrates to support robust self-renewal of fully dissociated human embryonic stem and induced pluripotent stem cells. Material properties including wettability, surface topography, surface chemistry and indentation elastic modulus of all polymeric substrates were quantified using high-throughput methods to develop structure–function relationships between material properties and biological performance. These analyses show that optimal human embryonic stem cell substrates are generated from monomers with high acrylate content, have a moderate wettability and employ integrin α[subscript v]β[subscript 3] and α[subscript v]β[subscript 5] engagement with adsorbed vitronectin to promote colony formation. The structure–function methodology employed herein provides a general framework for the combinatorial development of synthetic substrates for stem cell culture.National Institutes of Health (U.S.) (Grant R37-CA084198)National Institutes of Health (U.S.) (Grant RO1-CA087869)National Institutes of Health (U.S.) (Grant RO1-HD045022)National Institutes of Health (U.S.) (Grant DE016516)Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies (Contract W911NF-07-D-0004

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases