The study was conducted by Iuliana Ionita, a PhD student in computer science, Raoul-Sam Daruwala, a former research scientist from Courant Bioinformatics group and currently at Google, and Courant Professor Bud Mishra. Mishra is a professor of computer science and mathematics at the Courant Institute and also has an appointment in the Department of Cell Biology at NYU’s School of Medicine.
Previous research has found that certain gene-chips--a technology that allows the genome-wide screening for mutations in genes or changes in gene expressions all at once--shed light on genes and mechanisms involved in the onset and spread of cancer. Specifically, chromosomal segments, when deleted in a single or both copies of genomes of a group of cancer patients, point to locations of tumor suppressor genes implicated in the cancer. The NYU study focused on automatic methods for reliable detection of such genes, their locations, and their boundaries. For this purpose, the NYU scientists sought to devise an efficient and novel statistical algorithm to map tumor suppressor genes using a multi-point statistical score function. Their algorithm is unique in that it exploits the high resolution of gene-chips and prior biological models through Bayesian statistics in order to optimally pinpoint the genes involved in the cancer, even when these genomes may have many other unrelated deletions, which happen as "collateral damage" to the genomes as the cancer progresses to an advanced stage.
The NYU algorithm estimates the location of tumor suppressor genes by analyzing segmental deletions in the genomes from cancer patients and the spatial relation of the deleted segments to any specific genomic interval. Since the gene-chip consists of many "probes"--each one characterizing an almost unique word and its location in the already-sequenced human genome--by combining these probe-measurements, one can estimate if an important genomic segment is missing. By analogy, this process is akin to guessing if a new edition of a book is missing an important paragraph by checking if some of the important key words in that paragraph are missing from the index of the new edition. The new algorithm computes a multipoint score for all intervals of consecutive probes, and the score reflects how well the deletion of that genomic interval may explain the cancer in these patients. In other words, the computed score measures how likely it is for a particular genomic interval to be a tumor suppressor gene implicated in the disease. In order to validate their algorithm, the authors produced a high fidelity in silico model of cancer, and checked how well they can detect the right genes, as they modified various parameters of the model in an adversarial manner. Encouraged by the success of their in silico study, they applied the algorithm to currently available patient data, and discovered that they were able to detect many genes that were already known in the literature, but also, several others that are statistically equally significant, but not found by the earlier studies.
The findings also showed that the algorithm may be applied to a wider class of problems--including the detection of oncogenes, which promote the growth of cancer when they are mutated or overexpressed. As the technology and the statistical algorithms of this nature keep improving in cost and accuracy, it will prove useful in finding good biomarkers, drug discovery, disease diagnosis, and choosing correct therapeutic intervention. The members of the NYU group (the authors, Dr. Salvatore Paxia and Dr. Thomas Anantharaman) are in the process of creating a simpler user interface for their software, providing interoperability across many different chip technologies, and finally, making it publicly available in order to facilitate its free and wide-spread usage.
James Devitt | EurekAlert!
North and South Cooperation to Combat Tuberculosis
22.03.2018 | Universität Zürich
Researchers Discover New Anti-Cancer Protein
22.03.2018 | Universität Basel
An international team of researchers has discovered a new anti-cancer protein. The protein, called LHPP, prevents the uncontrolled proliferation of cancer cells in the liver. The researchers led by Prof. Michael N. Hall from the Biozentrum, University of Basel, report in “Nature” that LHPP can also serve as a biomarker for the diagnosis and prognosis of liver cancer.
The incidence of liver cancer, also known as hepatocellular carcinoma, is steadily increasing. In the last twenty years, the number of cases has almost doubled...
In just a few weeks from now, the Chinese space station Tiangong-1 will re-enter the Earth's atmosphere where it will to a large extent burn up. It is possible that some debris will reach the Earth's surface. Tiangong-1 is orbiting the Earth uncontrolled at a speed of approx. 29,000 km/h.Currently the prognosis relating to the time of impact currently lies within a window of several days. The scientists at Fraunhofer FHR have already been monitoring Tiangong-1 for a number of weeks with their TIRA system, one of the most powerful space observation radars in the world, with a view to supporting the German Space Situational Awareness Center and the ESA with their re-entry forecasts.
Following the loss of radio contact with Tiangong-1 in 2016 and due to the low orbital height, it is now inevitable that the Chinese space station will...
Fraunhofer Institute for Organic Electronics, Electron Beam and Plasma Technology FEP, provider of research and development services for OLED lighting solutions, announces the founding of the “OLED Licht Forum” and presents latest OLED design and lighting solutions during light+building, from March 18th – 23rd, 2018 in Frankfurt a.M./Germany, at booth no. F91 in Hall 4.0.
They are united in their passion for OLED (organic light emitting diodes) lighting with all of its unique facets and application possibilities. Thus experts in...
A new scenario seeking to explain how Mars' putative oceans came and went over the last 4 billion years implies that the oceans formed several hundred million...
For the first time, an interdisciplinary team from the University of Basel has succeeded in integrating artificial organelles into the cells of live zebrafish embryos. This innovative approach using artificial organelles as cellular implants offers new potential in treating a range of diseases, as the authors report in an article published in Nature Communications.
In the cells of higher organisms, organelles such as the nucleus or mitochondria perform a range of complex functions necessary for life. In the networks of...
19.03.2018 | Event News
16.03.2018 | Event News
13.03.2018 | Event News
22.03.2018 | Trade Fair News
22.03.2018 | Earth Sciences
22.03.2018 | Earth Sciences