Next-gen computing for terabase transfer

The single biggest challenge presently facing humanity is the new era of ICT (information and communication technology) required to advance the progress of science and technology. This constitutes more of a grand challenge than do disease, poverty, climate change, etc. because solutions are not immediately clear, and are likely to be more technical than political in nature. The raw capacity in information processing and transfer is required and also the software to drive these processes at higher levels of abstraction to make the information useable and meaningful. The computing and communications industries have been focused on incremental Moore’s Law extensions rather than new paradigms and do not appear to be cognizant of the current needs of science, and particularly the magnitude.

Computational era of science
One trigger for a new ICT era is the shift in the way that science is conducted. The old trial and error lab experimentation has been supplemented with informatics and computational science for characterizing, modeling, simulating, predicting and designing. Life sciences is the most prominent area of science requiring ICT advances, for a variety of purposes including biological process characterization and simulation. Genomics is possibly the field with the most ICT urgency; genomic data is growing at 10x/year vs. Moore’s Law at 1.5x/year for example, however nearly every field of science has progressed to large data sets and computational models.

Status of cancer detection

The Canary Foundation’s annual symposium held May 4-6, 2009 indicated progress in two dimensions of a systemic approach to cancer detection: blood biomarker identification and molecular imaging analysis.

Systems approach to cancer detection
A systems approach is required for effective cancer detection as assays show that many proteins, miRNAs, gene variants and other biomarkers found in cancer are also present in healthy organisms. The two current methods are one, looking comprehensively at the full suite of genes and proteins, checking for over-expression, under-expression, mutation, quantity, proximity and other factors in a tapestry of biological interactions and two, seeking to identify biomarkers that are truly unique to cancer, for example resulting from post-translational modifications like glycosylation and phosphorylation. Establishing mathematical simulation models has also been an important step in identifying baseline normal variation, treatment windows and cost trade-offs.

Blood biomarker analysis
There are several innovative approaches to blood biomarker analysis including blood-based protein-assays (identifying and quantifying novel proteins related to cancer), methylation analysis (looking at abnormal methylation as a cancer biomarker) and miRNA biomarker studies (distinguishing miRNAs which originated from tumors). Creating antibodies and assays for better discovery is also advancing particularly protein detection approaches using zero, one and two antibodies.

Molecular Imaging
The techniques for imaging have been improving to molecular level resolution. It is becoming possible to dial-in to any set of 3D coordinates in the body with high-frequency, increase the temperature and destroy only that area of tissue. Three molecular imaging technologies appear especially promising: targeted microbubble ultrasound imaging (where targeted proteins attach to cancer cells and microbubbles are attached to the proteins which make the cancerous cells visible via ultrasound; a 10-20x cheaper technology than the CT scan alternative), Raman spectroscopy (adding light-based imaging to endoscopes) and a new imaging strategy using photoacoustics (light in/sound out).

Tools: Cancer Genome Atlas and nextgen sequencing
As with other high-growth science and technology areas, tools and research findings evolve in lockstep. The next generation of tools for cancer detection includes a vast cataloging of baseline and abnormal data and a more detailed level of assaying and sequencing. In the U.S., the NIH’s Cancer Genome Atlas is completing a pilot phase and being expanded to include 50 tumor types (vs. the pilot phase’s three types: glioblastoma, ovarian and lung) and abnormalities in 25,000 tumors. The project performs a whole genomic scan of cancer tumors, analyzing mutations, methylation, coordination, pathways, copy number, miRNAs and expression. A key tool is sequencing technology itself which is starting to broaden out from basic genomic scanning to targeted sequencing, whole RNA sequencing, methylome sequencing, histone modification sequencing, DNA methylation by arrays and RNA analysis by arrays. The next level would be including another layer of detail, areas such as acetylation and phosphorylation.

Future paradigm shifts: prevention, omnisequencing, nanoscience and synthetic biology
Only small percentages of annual cancer research budgets are spent on detection vs. treatment, but it is possible that the focus will be further upstreamed to prevention and health maintenance as more is understood about the disease mechanisms of cancer. Life sciences technology is not just moving at Moore’s Law paces but there are probably also some paradigm shifts coming.

The three most suggestive areas for coming life science discontinuities are genomic sequencing, nanoscience and synthetic biology.

Genomic sequencing contemplates the routine scanning of each individual and tumor at multiple levels: genomic, proteomic, methylomic, etc. Nanoscience is the ability to design, construct and render mobile a large variety of molecular [biological] devices. Synthetic biology is designing new or modifying existing biological pathways in order to produce systems with superior or different properties, exercised by both traditional practitioners (recent conferences: Advances in Synthetic Biology, Synthetic Biology 4.0) and diybio’ers.