Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Computational Process Zeroes in on Top Genetic Cancer Suspects

03.09.2009
Johns Hopkins engineers have devised innovative computer software that can sift through hundreds of genetic mutations and highlight the DNA changes that are most likely to promote cancer.

The goal is to provide critical help to researchers who are poring over numerous newly discovered gene mutations, many of which are harmless or have no connection to cancer. According to its inventors, the new software will enable these scientists to focus more of their attention on the mutations most likely to trigger tumors.

A description of the method and details of a test using it on brain cancer DNA were published in the August 15 issue of the journal Cancer Research.

The new process focuses on missense mutations, meaning protein sequences that each possess a single tiny variation from the normal pattern. A small percentage of these genetic errors can reduce the activity of proteins that usually suppress tumors or hyperactivate proteins that make it easier for tumors to grow, thereby allowing cancer to develop and spread. But finding these genetic offenders can be difficult.

“It’s very expensive and time-consuming to test a huge number of gene mutations, trying to find the few that have a solid link to cancer,” said Rachel Karchin, an assistant professor of biomedical engineering who supervised the development of the computational sorting approach. “Our new screening system should dramatically speed up efforts to identify genetic cancer risk factors and help find new targets for cancer-fighting medications.”

The new computational method is called CHASM, short for Cancer-specific High-throughput Annotation of Somatic Mutations.

Developing this system required a partnership of researchers from diverse disciplines. Karchin and doctoral student Hannah Carter drew on their skills as members of the university's Institute for Computational Medicine, which uses powerful information management and computing technologies to address important health problems, and collaborated with leading Johns Hopkins cancer and biostatistics experts from the university’s School of Medicine, its Bloomberg School of Public Health and the Johns Hopkins Kimmel Cancer Center.

The team first narrowed the field of about 600 potential brain cancer culprits using a computational method that would sort these mutations into “drivers” and “passengers.” Driver mutations are those that initiate or promote the growth of tumors. Passenger mutations are those that are present when a tumor forms but appear to play no role in its formation or growth. In other words, the passenger mutations are only along for the ride.

To prepare for the sorting, the researchers used a machine-learning technique in which about 50 characteristics or properties associated with cancer-causing mutations were given numerical values and programmed into the system. Karchin and Carter then employed a math technique called a Random Forest classifier to help separate and rank the drivers and the passengers. In this step, 500 computational “decision trees” considered each mutation to decide whether it possessed the key characteristics associated with promoting cancer. Eventually, each “tree” cast a vote: Was the gene a driver or a passenger?

“It’s a little like the children’s game of ‘Guess Who,’ where you ask a series of yes or no questions to eliminate certain people until you narrow it down to a few remaining suspects,” said Carter, who earned her undergraduate and master’s degrees at the University of Louisville and served as lead author of the Cancer Research paper. “In this case, the decision trees asked questions to figure out which mutations were most likely to be implicated in cancer.”

The election results—such as how many driver votes a mutation received—were used to produce a ranking. The genetic errors that collected the most driver votes wound up at the top of the list. The ones with the most passenger votes were placed near the bottom. With a list like this in hand, the software developers said, cancer researchers can direct more of their time and energy to the mutations at the top of the rankings.

Karchin and Carter plan to post their system on the Web and will allow researchers worldwide to use it freely to prioritize their studies. Because different genetic characteristics are associated with different types of cancers, they said the method can easily be adapted to rank the mutations that may be linked to different forms of the disease, such as breast cancer or lung cancer.

In addition to Karchin and Carter, the Johns Hopkins co-authors of the Cancer Research paper were Sining Chen, Leyla Isik, Svitlana Tyekucheva, Victor E. Velculescu, Kenneth W. Kinzler and Bert Vogelstein.

Funding for the research was provided by the National Cancer Institute, the Susan G. Komen Foundation, the Virginia and D. K. Ludwig Fund for Cancer Research and the National Institutes of Health.

Color images of the researchers available; Contact Phil Sneiderman.

Related links:
Rachel Karchin’s Lab Page: http://karchinlab.org/
Department of Biomedical Engineering: http://www.bme.jhu.edu/
Johns Hopkins Institute for Computational Medicine: http://www.icm.jhu.edu/
Johns Hopkins Kimmel Cancer Center: http://www.hopkinskimmelcancercenter.org/

Phil Sneiderman | Newswise Science News
Further information:
http://www.jhu.edu

More articles from Information Technology:

nachricht Controlling robots with brainwaves and hand gestures
20.06.2018 | Massachusetts Institute of Technology, CSAIL

nachricht Innovative autonomous system for identifying schools of fish
20.06.2018 | IMDEA Networks Institute

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Temperature-controlled fiber-optic light source with liquid core

In a recent publication in the renowned journal Optica, scientists of Leibniz-Institute of Photonic Technology (Leibniz IPHT) in Jena showed that they can accurately control the optical properties of liquid-core fiber lasers and therefore their spectral band width by temperature and pressure tuning.

Already last year, the researchers provided experimental proof of a new dynamic of hybrid solitons– temporally and spectrally stationary light waves resulting...

Im Focus: Overdosing on Calcium

Nano crystals impact stem cell fate during bone formation

Scientists from the University of Freiburg and the University of Basel identified a master regulator for bone regeneration. Prasad Shastri, Professor of...

Im Focus: AchemAsia 2019 will take place in Shanghai

Moving into its fourth decade, AchemAsia is setting out for new horizons: The International Expo and Innovation Forum for Sustainable Chemical Production will take place from 21-23 May 2019 in Shanghai, China. With an updated event profile, the eleventh edition focusses on topics that are especially relevant for the Chinese process industry, putting a strong emphasis on sustainability and innovation.

Founded in 1989 as a spin-off of ACHEMA to cater to the needs of China’s then developing industry, AchemAsia has since grown into a platform where the latest...

Im Focus: First real-time test of Li-Fi utilization for the industrial Internet of Things

The BMBF-funded OWICELLS project was successfully completed with a final presentation at the BMW plant in Munich. The presentation demonstrated a Li-Fi communication with a mobile robot, while the robot carried out usual production processes (welding, moving and testing parts) in a 5x5m² production cell. The robust, optical wireless transmission is based on spatial diversity; in other words, data is sent and received simultaneously by several LEDs and several photodiodes. The system can transmit data at more than 100 Mbit/s and five milliseconds latency.

Modern production technologies in the automobile industry must become more flexible in order to fulfil individual customer requirements.

Im Focus: Sharp images with flexible fibers

An international team of scientists has discovered a new way to transfer image information through multimodal fibers with almost no distortion - even if the fiber is bent. The results of the study, to which scientist from the Leibniz-Institute of Photonic Technology Jena (Leibniz IPHT) contributed, were published on 6thJune in the highly-cited journal Physical Review Letters.

Endoscopes allow doctors to see into a patient’s body like through a keyhole. Typically, the images are transmitted via a bundle of several hundreds of optical...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

Munich conference on asteroid detection, tracking and defense

13.06.2018 | Event News

2nd International Baltic Earth Conference in Denmark: “The Baltic Sea region in Transition”

08.06.2018 | Event News

ISEKI_Food 2018: Conference with Holistic View of Food Production

05.06.2018 | Event News

 
Latest News

Graphene assembled film shows higher thermal conductivity than graphite film

22.06.2018 | Materials Sciences

Fast rising bedrock below West Antarctica reveals an extremely fluid Earth mantle

22.06.2018 | Earth Sciences

Zebrafish's near 360 degree UV-vision knocks stripes off Google Street View

22.06.2018 | Life Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>