Rutgers Cancer Institute of New Jersey
195 Little Albany Street
New Brunswick, NJ 08903-2681
Biomedical Informatics Support for Genome Scale Analyses: Next Generation Sequencing (NGS) promises to revolutionize biomedical research. Through technological advances based on massive parallelization, NGS provides an enormous number of reads and permits sequencing of entire genomes (and their transcriptome). The Biomedical Informatics Shared Resource made considerable investment in computational hardware and Biomedical Informatics software development to manage the very large data sets generated and to extract biomedical insights from the data collected. We have pipelines to analyze data collected in RNA-Seq, Chip-Seq, whole genome sequencing, etc. using in-house shared memory computational platforms as well as deployed massively parallel sequence alignment/assembly codes on our University’s Newton MPP supercomputer. Biomedical Informatics deployed, and is using, sequence assembly, alignment codes (SOAP, Bowtie, Abyss) and data visualization tools (Galaxy, IGV from the Broad Institute) on shared memory and massively parallel supercomputers to analyze and visualize the vast data set generation from the Illumina and ABI/Solid Next Generation sequencers.
Microarray Database and Analysis: The Biomedical Informatics Shared Resource supports experimental design and analysis of microarray data, often generated by the Functional Genomics Shared Resource, including pathway analysis and molecular modeling. We expect this effort to lead to co-authorships in publications in the near future and requests for Biomedical Informatics support in future grant applications. In addition, we have deployed and manage data backup/storage (via a dedicated server and disk/tape devices) to ensure that the data collected in a PI laboratory is automatically copied to dedicated server storage at the Rutgers Cancer Institute's Data Center every night. The data is migrated monthly to an encrypted tape facility and shipped to a remote site.
CINJ Warehouse Services/Integrative Cancer Biology and Data Mining: Biomedical research has yet to fully harness the transformative power of information technology to enhance research productivity and efficiency, which accelerates research discoveries that transform clinical practice. Effective aggregation and management of knowledge along with data resources is critical to advancing clinical and translational science. It is a priority of the Biomedical Informatics Shared Resource to organize and implement informatics initiatives and their associated cyber-infrastructure and support capabilities to meet these needs. As in most medical centers, the information management needs of the combined clinical and translational research community at Rutgers Cancer Institute have historically been met by resources available within individual research programs that were too diffuse and/or lacked focus. In the past two years, Rutgers Cancer Institute leadership and individual investigators have been strong advocates and supporters of the Biomedical Informatics Shared Resource in its efforts to develop and deploy a model of information integration and data sharing to catalyze the translation of research discoveries and to advance research into quantifiable outcomes across traditional institutional and geographic boundaries. The Biomedical Informatics Shared Resource is working with Rutgers Cancer Institute investigators to facilitate mining of existing data based on each research project’s scientific priorities. Therefore, a significant component of the resource includes detailed outreach activities that are designed to maximize the power of the Biomedical Informatics Shared Resource’s expertise and resources to advance research. A major component of the efforts in support of integrative cancer biology is focused on developing, deploying and supporting data repositories using commercial and/or open source software that meet the specific requirements of Rutgers Cancer Institute members. The Biomedical informatics team has purchased and is rolling out an enterprise-wide clinical data warehouse based the web-accessible clinical & translational research management software system, LabMatrix offered from BioFortis, Columbia, MD. The data repositories will provide federated access to clinical data, archive research datasets from completed studies, link research data sources for multidisciplinary collaboration, and serve as a platform for translational research. Targeted clinical data sources for phase I of the project include the ARIA-EMR containing encounter, laboratory, other EMR data, computerized physician order entry and data originating from radiology reports, pathology reports, surgical notes, clinical history, nursing notes, genomic sequencing studies, and information resident in Oncore which supports ongoing clinical trials. Examples of research data sources that will be integrated into the data warehouse in phase II of the project include radiology PACS, digitized pathology repositories, and epidemiologic data from Rutgers Cancer Institute Shared Resources, NJ State Cancer Registry/SEER and data bases linking Rutgers Cancer Institute’s Network of Hospitals, etc. As part of data repository development, wherever possible, the Biomedical Informatics Shared Resource is implementing a standard format to which data from heterogeneous sources will be transformed for further use. Standardization will facilitate data sharing both within and outside Rutgers Cancer Institute. The data structures within repositories are searchable and graphically browsable with data elements, volume and date range of the source, as well as standard and lexical reference to the data element (such as DICOM, HL7 v2.x, SNOMED, UMLS, caDSR, ICD10) where applicable.
Clinical Data Repository and Services: There is a need for a data repository for the population sciences, epidemiologists and clinicians in the various disease specific groups at Rutgers Cancer Institute to view populations and disease trends of patients. To support phase I studies and NCI-investigator driven clinical trials at Rutgers Cancer Institute, the Biomedical Informatics Shared Resource works with Rutgers Cancer Institute’s Office of Human Research Services shared resource in providing hardware, software and disaster recovery support for their OnCore Clinical Trial Data Management System. They are working with the commercial vendor to expand on the capabilities for real-time electronic data capture from our Aria-EMR as well as expanding on the OnCore Biospecimen Module that will facilitate integration with the data capture efforts in our Biospecimen Repository Service Shared Resource. The Biomedical Informatics Shared Resource ensures that the right data in the right format flows into appropriate data repositories in an efficient and secure manner. They have supported the Rutgers Cancer Institute membership using CAISIS (see http://www.caisis.org), which is an open source, web-based, cancer data management system that integrates research with patient care. CAISIS was developed by Memorial Sloan-Kettering Cancer Center and is now utilized by many of the Comprehensive Cancer Centers for their own research as well as for the exchange of data to create larger populations and cohorts for study.
Histopathology Imaging and Computational Image Analysis: Digital pathology technology enables biomedical researchers to digitize de-identified patient specimens and experimental specimens for easy storage, duplication, sharing and analysis. With the newly acquired high-throughput Olympus VS120 whole slide scanner, the Imaging Shared Resource can help users capture their experimental results in high-quality images for publication and analysis. The four-color fluorescent imaging capability allows fluorescent immunohistochemistry specimens to be digitized in their entirety, avoiding common fluorescent study pitfalls such as sampling error and photo-bleaching. State-of-art multispectral imaging not only captures entire emission spectrum of specimens in small wavelength intervals but also supports further fluorescent multiplexing by providing a means to separate emission signals originating from each fluorophors. The Imaging Shared Resource also provides consultation and help to projects related to imaging and image analysis to users. Researchers with specific analytical needs can receive custom analysis and software development service by working with staff at the service.
Chemical Informatics Analysis: Informaticians use small molecule/peptide databases for 'in silico' screening studies of key enzymes and receptors to identify lead targets for design and development of novel therapeutics. Molecular dynamics techniques are applied to develop a broader understanding of the biophysical significance of mutation and in the estimation of drug-receptor complex binding free energies. Software packages used for docking (in silico screening) include Autodock, UCSF DOCK, Gold and Vina. Software used for molecular dynamics projects includes Amber, Gromacs and NAMD. Quantum mechanics programs like Gaussian and Spartan are used to study physical properties of small molecule drugs, small peptides and unusual nucleic acids. The resource uses the Modeller program for homology modeling and the Rosetta package to model small proteins via ab initio protein folding techniques. This service is a key component of the translational science efforts at Rutgers Cancer Institute.
Support of Other Rutgers Cancer Institute of New Jersey Shared Resources: The Biomedical Informatics Shared Resource develops the web portals for access to the services of most Rutgers Cancer Institute of New Jersey Shared Resources. In addition, more specific Biomedical Informatics needs of various Shared Resources are met, as follows:
Web-based Application Development: It is difficult for many projects to separate web development (web site) from medical/clinical informatics and database design/installation since all these applications are through a web portal requiring a “website/interface” with underlying database design, programming and linkage to informatics. While a majority of the web portals are used to support ongoing outreach and educational initiatives, a significant number are targeted to the collection and integration of data in support of research in population science and translational research where integration of data from the lab, clinic and population based studies will advance our research agenda in cancer prevention, control and survivorship. At a practical level, the resources and manpower devoted to developing and deploying web portals benefits our research agenda at Rutgers Cancer Institute as it helps to increase recruitment for clinical trials carried out at the center by making patients and clinicians aware of the ongoing trials. Examples of projects implemented and maintained by the Bioinformatics Shared Resource include the following: