Michael J. Becich, MD, PhD
• Translational Bioinformatics
• Pathology Informatics
• Oncology Informatics
• Tissue Banking Informatics
• Research Resource Development
• Personalized Medicine
Appointments and Positions
Current Research Projects and Collaborations
Advanced Development of TIES-Enhancing Access to Tissue for Cancer Research
Archived human tissues are an essential resource for translational research. Formalin-fixed, paraffin-embedded (FFPE) tissues from cancer patients are used in a wide range of assays, including RT-PCR, SNP profiling, multiplex biomarkers, imaging biomarkers, targeted exome, whole exome, and whole genome sequencing. Remainder FFPE tissues generated during patient care are ‘retrospective’; use of these tissues under specific conditions does not require consent. For personalized medicine researchers, these specimens are vital resources enabling biomarker validation, detailed molecular analysis, and systems modeling before application is made to individual patients. But access to these human tissues is often a rate limiting factor in cancer research. We propose advanced development of the TIES software to (1) increase institutional capacity for using FFPE to support molecular characterization of human tumors, (2) increase access to tissues within cancer centers, and (3) improve the ability to share tissues and associated phenotype data among cancer centers. 9/25/2013 - 7/31/2018
A P2aTH towards a Learning Health System in the Mid-Atlantic Region
The P2aTH Clinical Data Research Network brings together four Mid-Atlantic Health Systems: University of Pittsburgh/UPMC, Penn State College of Medicine/Hershey Medical Center, Temple University School of Medicine/Temple Health, and Johns Hopkins University/ Johns Hopkins Health System/ Johns Hopkins Health Care. In P2aTH, we will combine resources to follow a longitudinal cohort of at least 1 million diverse individuals across a variety of health care settings to maximize our power to conduct meaningful patient-centered outcomes research. Our vision is to develop a learning health system that is jointly led by patients and providers. While P2aTH is a new network, we have worked throughout the planning for this project to bring key stakeholders together to ensure success in this endeavor. The strengths of P2aTH include our experience caring for vulnerable patients, extensive electronic capture of longitudinal clinical data; collaboration with health insurers, clinician and patient partners, and health system leadership; success in embedding research into clinical care; expertise in collecting patient-reported outcomes within standard clinical workflow; experience collecting and sharing biospecimens; and strong information technology integration strategy that will facilitate future collaborations among institutions with disparate electronic medical records.
1/1/2014 - 6/30/2015
Sarcoidosis and A1AT Genomics & Informatics Coordinating Center (SAGIC) Alpha-1 antitrypsin deficiency (A1AT), an autosomal recessive genetic disease that is associated with a variable risk of COPD, and Sarcoidosis, a systemic disease characterized by the formation of granulomatous lesions especially in the lungs, liver, skin, and lymph nodes that leads to a dramatically heterogeneous set of clinical manifestations, differ in etiology and clinical presentation but share a variable and unpredictable course. To improve disease classification, facilitate biomarker discovery and accelerate advent of novel therapy an integrative approach that combines the results of clinical studies with molecular phenotyping results is required. SAGIC will facilitate this process by addressing the following objectives for the NHLBI Genomic Research in A1AT and Sarcoidosis (GRADS) program: 1) Coordination of Clinical Centers activities that include patient recruitment and phenotyping and biospecimen collection. 2) Performance of transcriptome and microbiome analyses of the samples obtained by the Clinical Centers, 3) Data analysis and integration, 4) Dataset preparation for deposit in the NHLBI BioLINCC repository. The objectives will be addressed through two research projects. Project 1: A1AT microbiome - will address the hypothesis that shifts in the lung microbiome determine the extent of lung involvement in A1AT and that they are reflected in mRNA and microRNA changes in surrogate tissues, and Project 2: Novel molecular phenotypes in Sarcoidosis - will address the hypothesis that systemic inflammation as reflected in gene expression changes in PBMC is indicative of disease extent, microbiome shifts and granuloma molecular networks. 4/1/2012-3/31/16
SPORE in Skin Cancer: Translational research such as that proposed in the Melanoma and Skin SPORE (MSCP) has a spectrum of needs that benefit from software solutions, including data warehousing, analysis tools and clinical information management. It is critical that this resource be supported and integrated into NCI’s research mission. The Informatics Core (Core D) of the MSCP is composed of the following integrated services:
1) Clinical Trials Management Application (CTMA) – collects, manages, and aggregates all data to support the clinical trials of the MSCP and UPCI with integration to the Cancer Registry, Tissue Banking Information Systems and our Research Data Warehouse (RDW).
2) Registry Information and Honest Broker Services (RIS/HBS) – collects and manages all clinical and outcomes annotation of patients who contribute their cancer tissues to our MSCP translational research efforts. HBS provides a de-identification service which is critical for HIPAA compliant research information data sharing and analysis.
3) Research Data Warehouse (RDW) – translate our clinical data collection from our oncology EMR, laboratory and radiology information systems, cancer registry, tissue bank and immunophenotyping core into an i2b2 database instance.
4) Cohort Discovery and Disease Modeling – utilize the clinical and demographic data from RDW into our analytical tool, Megascope, to allow for deep cohort identification and information modeling of disease biomarkers and outcomes to enable translational clinical research.
5) Bioinformatics Analysis – biomarker data derived from the MSCP projects and those from the Career Development Program (CDP) and Research Development Program (RDP) will require sophisticated bioinformatics analysis.
MSCP will be increasingly reliant on developing robust research information services to more effectively support the translation of innovation from the laboratory to the bedside and to utilize critical clinical and outcomes data in the clinic to guide discovery at the bench. Ms. Saul and Dr. Becich will co-direct this core. Both are also involved in the Biomedical Informatics Core of the Clinical and Translational Science Institute at the University of Pittsburgh as well as the Cancer Informatics Core of the Cancer Center Support Grant (CCSG). This additional level of integration with NIH Roadmap Initiatives and the NCI CCSG program is a key strength of the Informatics Core of the MSCP at UPCI. University of Pittsburgh and the University of Pittsburgh Cancer Institute (UPCI) 2008-2013
Cancer Bioinformatics Services: The Cancer Bioinformatics Services (CBS) provides equipment and expertise to researchers to assist with their translational research efforts. The CBS at UPCI is composed of the following tightly integrated services:
Bioinformatics Services: Providing comprehensive bioinformatics support, from experimental design to data analysis, for high-throughput genomics studies
Tissue Banking and Data Warehouse: Establish integration points between disparate clinical and research applications (CoPath/CaRegistry/Tissue Banks) to provide sources for “automated annotation”
Enterprise Analytics Data Warehouse (EDW) and Personalized Medicine Support: Build an integrated view of clinical, consumer, and financial data in a central repository. Develop a translational research center to collect, store, and analyze disparate clinical and molecular data including -omics data
Cancer Center Support (CCSG) P30 CA47904-24 (Davidson) 2010-2015
CIS Website- http://www.upci.upmc.edu/cis/index.cfm
CDC Expansion of the National Mesothelioma Virtual Registry and Tissue Bank: The purpose of the National Mesothelioma Virtual Bank (NMVB) for Translational Research is to maximize the effectiveness of data and biospecimen collection and sharing for mesothelioma research nationally. The NMVB will continue to serve as a resource that will allow researchers real time access to clinical data associated with blood, DNA and tissue specimens from the registry, thus expanding scientific discovery and effective treatments to benefit the Mesothelioma clinical and translational research and patient communities. Our specific aims are: 1) To expand the NMVB to Mt. Sinai School of Medicine. We will continue to collect patients’ clinical data and enroll them in the biospecimen bank at the original NMVB partners: New York University (NYU), the University of Pennsylvania (Penn), the University of Pittsburgh (Pitt). At all sites we will collect biological samples including (but not limited to) biopsy material (fixed or frozen), blood, serum and white blood cells (for DNA). This will include continuing to accrue prospective cases, retrospective cases and case controls. 2) To expand the NMVB collection sites to the University of Hawaii Cancer Center and the University of California San Francisco through the “SPIRiT of Collaboration” and to facilitate translational research from funded investigators by the Meso Foundation and proposed Mesothelioma SPORE. 3) We will document and continually evaluate the usefulness of the NMVB to the scientific community and measure its impact in studies that address the etiology, mechanisms, diagnosis and treatment of malignant mesothelioma. The advantages of this approach which we call “The SPIRiT of Collaboration” is that it will begin to couple funding sources from the CDC NIOSH to the NCI (through the Meso SPORE) and NCRR (through the CTSA program). This effort will serve as a model for multi-agency funding of synergistic efforts. The NIH Roadmap stresses the importance of collaborative networks of researchers and the sharing of biospecimen resources and the National Mesothelioma Virtual Bank program of NIOSH/CDC clearly aims to facilitate that vision. University of Pennsylvania and New York University 2008-2016
Clinical and Translational Science Award (CTSA) Biomedical Informatics Core for the Clinical and Translational Science Institute (CTSI) at Pittsburgh: Codirector of CTSI, Member of CTSA Steering Committee and Operations Committee, 38 funded CTSA sites 2006-2016
CTSI's Biomedical Informatics Core seeks to integrate informatics in all phases of the research lifecycle by offering assistance in obtaining data, consulting about software solutions, and deploying novel tools that address the needs of those conducting clinical and translational studies.
The Biomedical Informatics Core offers researchers at Pitt the following software and services:
The Text Information Extraction System (TIES)
The Text Information Extraction System (TIES) is the name given to the Cancer Text Information Extraction System (caTIES) production system at the University of Pittsburgh. It is a slightly customized version of caTIES that is freely available for download from the caTIES website.
The TIES system provides researchers with an intuitive user interface for finding patient cases and clinical data in a repository of more than 1.6 million UPMC de-identified pathology reports and to order the associated tissue for IRB-approved studies. A powerful charts builder allows researchers to create bar and pie charts categorized by age, gender, collection year or concepts like diagnosis or organ. Researchers can save the charts as image files to use later in publications or grants. Similar to tagging on sites like Flickr, researchers can now tag a set of reports with a descriptive name and then restrict searches within a particular set of tagged reports. TIES supports case sets, order management, and honest broker features to help manage tissue and data requests.
For more information about TIES, including information on how to request a TIES account, or to view the TIES User Manual or TIES Software Demos, visit the TIES website.
Digital Vita is web-based social networking software that helps users identify potential research collaborators by using information about faculty members' research interests and publications. Users create an online profile in Digital Vita, and the system manages all of the data in each faculty member’s Curriculum Vitae (CV), providing an easy user interface for creating a paper or electronic CV and NIH biosketch. For more information on Digital Vita, visit the Find Colleagues/Digital Vita Page, or log into the network at the Digital Vita Website.
Center for Assistance in Research using eRecord (CARe)
The Center for Assistance in Research using eRecord (CARe) provides centralized assistance for researchers to access and extract data from UPMC electronic health records, for research purposes. CARe facilitates the safe, secure, and compliant transfer of data from the multiple electronic medical record systems that comprise UPMC eRecord.
The staff of the Biomedical Informatics Core is available to help investigators identify the appropriate software for storing research data or the appropriate methodology for design or evaluation of software to be developed for a grant. While we do not develop software for individual research projects, we can often direct researchers to other resources on campus. To request a consulting session, email Girish Chavan at firstname.lastname@example.org.
The Biomedical Informatics Core provides support for Digital Vita, TIES, and various software applications used by the Clinical & Translational Resource Centers that comprise the Clinical Resources and Research Facilities and Networks.
Amin W, Srinivasan M, Song SY, Parwani AV, Becich MJ. Use of automated image analysis in evaluation of mesothelioma Tissue Microarray (TMA) from National Mesothelioma Virtual Bank. Pathology Research and Practice 2014 Feb. 210(2) 79-82. doi: 10.1016/j.prp.2013.09.002 Epub 2013 Nov 14.
Risinger JI, Allard J, Chandran U, Day R, Chandramouli GV, Miller C, Zahn C, Oliver J, Litzi T, Marcus C, Dubil E, Byrd K, Cassablanca Y, Becich M, Berchuck A, Darcy KM, Hamilton CA, Conrads TP, Maxwell GL. Gene expression analysis of early stage endometrial cancers reveals unique transcripts associated with grade and histology but not depth of invasion. Front Oncol. 2013 Jun 17;3:139. doi: 10.3389/fonc.2013.00139. Print 2013. PMID: 23785665
Park S, Parwani AV, Aller RD, Banach L, Becich MJ, Borkenfeld S, Carter AB, Friedman BA, Rojo MG, Georgiou A, Kayser G, Kayser K, Legg M, Naugler C, Sawai T, Weiner H, Winsten D, Pantanowitz L. The history of pathology informatics: A global perspective. J Pathol Inform. 2013 May 30;4:7. doi: 10.4103/2153-3539.112689
Amin W, Parwani A, Melamed J, Flores R, Pennathur A, Valdivieso F, Whelan N, Landreneau R, Luketich J, Feldman M, Pass H, and Becich MJ. National Mesothelioma Virtual Bank: A Platform for Collaborative Research and Mesothelioma Biobanking Resource to Support Translational Research. Lung Cancer International, Volume 2013, Article ID 765748.
Lee RE, McClintock DS, Balis UJ, Baron JM, Becich MJ, Beckwith BA, Brodsky VB, Carter AB, Dighe AS, Haghighi M, Hipp JD, Henricks WH, Kim JY, Klepseis VE, Kuo FC, Lane WJ, Levy BP, Onozato ML, Park SL, Sinard JH, Tuthill MJ, Gilbertson JR. Pathology informatics fellowship retreats: The use of interactive scenarios and case studies as pathology informatics teaching tools. J Pathol Inform. 2012;3:41. doi: 10.4103/2153-3539.103995. Epub 2012 Nov 28. PMID: 23248762
Gullapalli RR, Desai KV, Santana-Santos L, Kant JA, Becich MJ. Next generation sequencing in clinical medicine: Challenges and lessons for pathology and biomedical informatics. J Pathol Inform. 2012;3:40. doi: 10.4103/2153-3539.103013. Epub 2012 Oct 31. PMID: 23248761
Gullapalli RR, Lyons-Weiler M, Petrosko P, Dhir R, Becich MJ, LaFramboise WA. Clinical integration of next-generation sequencing technology. Clin Lab Med. 2012 Dec;32(4):585-99. doi: 10.1016/j.cll.2012.07.005. Review. PMID: 23078661
Jiang X, Barmada MM, Becich MJ. Evaluating de novo locus-disease discoveries in GWAS using the signal-to-noise ratio. AMIA Annu Symp Proc. 2011;2011:617-24. Epub 2011 Oct 22. PMID: 22195117
Jiang X, Barmada MM, Cooper GF, Becich MJ. A bayesian method for evaluating and discovering disease loci associations. PLoS One. 2011;6(8):e22075. doi: 10.1371/journal.pone.0022075. Epub 2011 Aug 10.
Most Impactful Publications