Researchers & Clinicians

The Cancer Bioinformatics Shared Resource (CBSR) supports Cancer Center members by providing a variety of bioinformatics services and resources. The major goal of CBSR is to facilitate the development of strong interdisciplinary cancer programs by providing necessary bioinformatics resources to Cancer Center members. In particular, the CBSR strives to bridge the gap between clinicians and basic researchers for collaborations on translational cancer research.

Mark Maienschein-Cline, PhD, Resource Director, has many years of experience in providing bioinformatics services to UIC researchers. His group has close collaboration with the UIC Genome Research Core, providing all necessary bioinformatics support for the analysis of high-throughput omics data.

Our Services

The CBSR employs a fee-for-service model for standard bioinformatics requests from Cancer Center members. This is a cost-effective strategy to handle user requests in an efficient way using standard bioinformatics pipelines. On the other hand, for complex or non-standard bioinformatics requests, we employ a collaborator/co-investigator model to better serve the members.

Consultation Services

The CBSR offers free consultation meetings with all Cancer Center members regarding various bioinformatics needs related to cancer research. The major goal of these meetings is to help Cancer Center researchers identify bioinformatics requirements for designing research projects and developing data analysis plans. These consultation services are an important first step to engage Cancer Center members and subsequently provide appropriate bioinformatics support tailored for individual research projects.

Bioinformatics Data Analysis Services

The CBSR provides a wide array of data analysis services to Cancer Center members. Common tasks include the analysis of high-throughput omics data generated by Cancer Center members. The CBSR provides comprehensive solutions to process various types of data, most commonly involving transcriptomics (e.g., bulk, single-cell, spatial sequencing), genomics (e.g., ChIP-seq, ATAC-seq), epigenomics, metabolomics, and proteomics. Besides helping on the analysis of user-generated data, the CBSR also provides data mining services based on public genomic data repositories such as The Cancer Genome Atlas.

Infrastructural Support for Bioinformatics Research

In collaboration with the Cancer Center Data Integration Shared Resource (DISR), the CBSR recently established cloud computing capacity based on the Amazon Azure platform. This Azure cluster is readily accessible to all Cancer Center members who need extensive computing power to perform their own bioinformatics analysis. In addition, the CBSR has five Linux workstations that are accessible to Cancer Center members for less-intensive bioinformatics analysis jobs.

The Biostatistics Shared Resource (BSR) Core is composed of a group of experienced faculty and dedicated staff whose mission is to provide outstanding statistical and analytic support to Cancer Center research projects across its three research programs—Cancer Biology, Translational Oncology, and Cancer Prevention and Control. BSR provides Cancer Center members with comprehensive biostatistical services and fosters collaborations in a way that maximizes research impact.

To request services, email Program Director Zhengjia Nelson Chen, PhD, at znchen@uic.edu

Who We Are

The BSR plays a pivotal role in the success of research at the Cancer Center by providing state-of-the-art biostatistics services. 

We work with all Cancer Center members and participate in research across our three research programs — Cancer Biology, Translational Oncology, and Cancer Prevention & Control. Working together as partners, the BSR collaborates and consults with investigators in design, conduct, and analysis of cancer-related clinical, preclinical, epidemiological, and community-based research. These collaborations lead to the development and application of innovative statistical methodology and the summarization of results to address cancer research. They also allow us to facilitate the translation of research findings into clinical trials and to disseminate new knowledge that supports the planning of new collaborative research projects.

By providing biostatistics services within one shared resource, the BSR offers University of Illinois Cancer Center investigators a single point of collaboration during all stages of their research.

Education and Training

An important component of the BSR is supporting the University of Illinois Cancer Center’s education mission. 

We provide journal clubs, training workshops, and statistical consultation and collaboration for trainees and early Cancer Center members.

For graduate students, oncology residents, fellows, and Cancer Center members, we provide a monthly seminar on state-of-the-art approaches for cancer research.

Biostatistics Support

The BSR’s services focus on statistical and collaborative support for the design, conduct, analysis, and interpretation of all research activities at the University of Illinois Cancer Center. 

Our services include:

• Provide consultation and collaboration regarding all types of study design (e.g., validity of design, feasibility of meeting objectives, sample size, projection of study duration).
• Design clinical trials with an adaptive and sequential design
• Clinical trial and study protocol development
• Statistical monitoring and assessing the progress of studies
• Data analysis, assistance in manuscripts and presentations
• Develop novel biostatistics and bioinformatics methods
• Review proposals for clinical cancer-related studies within the context of the clinical trials review committee

Data Management

The BSR statistical data management operations are responsible for the support of research databases, including OnCore and eCRFs forms. We also incorporate REDCap in support of studies such as population-based observational studies and hospital chart review data. Statistical data managers routinely perform data extractions, ensure quality control, and create analysis datasets.

Scientific Review for Cancer Center

By evaluating the statistical feasibility of each proposed project — particularly on sample size, power, and study design — the BSR members are an integral part of Clinical Protocol and Data Management (CPDM), Protocol Review and Committee (PRC), the Data and Safety Monitoring Committee (DSMC), and service based programs.

For Cancer Center Members

The BSRC is dedicated to Cancer Center members.

Priority for the BSR services is given to the cancer investigators with peer-reviewed funding, extramural grant submissions, and pending manuscript or abstract submissions. Please fill in the request form to schedule a consultation.

We do not implement a charge-back system for cancer center members. Assistance with preliminary data analysis for grant applications, grant statistical support, investigator-initiated clinical trial design, protocol preparation, and project planning services are all provided at no cost to our members.

Providing a no-cost service for conceptualization of grant design and methods encourages members to consider applying for extramural grant funding and expedites the statistical planning of cancer-focused research.

BSR members on funded grants or contracts are covered by appropriate levels of percent effort on collaborative work. It is a common criteria to cover a faculty biostatistician at least 5% effort on a R01, and 3% at R21, R03, ACS, DOD, etc. It is also required to budget 3% effort for Biostatistician in a Sponsor or contract supported clinical trial with more than 20 patients, or 5% in one with more than 100 patients, respectively.

Publication Acknowledgement Policy

The National Cancer Institute requires that publications acknowledge the University of Illinois Cancer Center BSR and it is tracking compliance. If BSR provided data, designed the study, performed analyses, provided results used in your publication, and/or provided any systems or services that were used for the work that resulted in your publication, please include the following statement in the acknowledgment section of your publication(s):

“Research reported in this publication was supported in part by the University of Illinois Cancer Center Biostatistics Shared Resource Core (BSR).”

Meet Our Team

Zhengjia (Nelson) Chen, PhD, is Director of the BSR and Professor in the Division of Epidemiology and Biostatistics at the UIC School of Public Health. He has extensive experience in epidemiological, genetic, molecular, clinical, and surgical research on lung, head and neck, ovarian, leukemia, lymphoma, breast, melanoma, brain and other cancers.

Li Liu, PhD, is an Associate Professor of Biostatistics in the Division of Epidemiology and Biostatistics in the School of Public Health. She serves as Senior Biostatistician, participating in the design, data collection, analysis, and result dissemination of clinical, efficacy trials, and biological and clinical studies in cancer research.

Jiehuan Sun, PhD, MS, has primary research interests focused on developing efficient and novel statistical methods to deal with high-dimensional (big) biomedical data, including electronic health record data and genomics data. Specifically, his research areas include biomarker discovery, disease subtype identification, dynamic risk prediction and network modeling.

Meida Wang, PhD, is Clinical Assistant Professor of Biostatistics in the Division of Epidemiology and Biostatistics and a faculty Biostatistician at the BSR. She specializes in statistical genetics, with expertise in genome-wide association studies, joint analysis of multiple phenotypes, and detecting associations between ordinal traits and rare variants.

Michael Berbaum, PhD, is a Senior Biostatistician.

Weiwei Ma, MS, is a Biostatistician.

The Cancer Genomics Shared Resource (CGSR) provides state-of-the-art services for investigators to conduct genomic research on cancer complexity through effective utilization of equipment, scientific knowledge, and technical guidance. We offer technologies, help to design experiments, and interpret data for multidimensional genomic and epigenomic analyses. We provide advice on using other cores at the University of Illinois and other institutions to match the investigator’s needs.

Our Services

Consultation

We offer free consultations to members regarding:

• Developing testable hypotheses based on whole-genome data
• Study design
• Troubleshooting methodological difficulties
• Grant and manuscript support (letters of support, text for grants and manuscripts, etc.)

Education and Training

The faculty associated with CGSR gives presentations on cancer genomics at Cancer Center Program meetings, Working Groups meetings, and at the Center for Bioinformatics and Quantitative Biology. The staff also organizes seminars with various vendors offering. 

Direct Services

• scRNA-seq (from fresh tissue or FFPE tissue)
• CITE-seq
• scATAC-seq
• We work closely with DNA Services Core at University of Illinois at Urbana-Champaign for sequencing on Novaseq 6000 flowcell
• Sanger sequencing
• Shotgun DNA sequencing
• Subcloning in a virus vector (adenoviral, lentiviral or retroviral) for gene knockdown, knockout, overexpression, tagging, etc.; preparation of viral supernatants; virus titaration
• Cell line authentication via short tandem repeat analysis
• Mycoplasma testing by PCR to detect contamination in cell cultures
• Transcriptional profiling by RNA-seq (from total RNA, with options including whole transcript total RNA sequencing with ribosomal depletion, mRNA sequencing, miRNA sequencing)
• Gene expression analysis by RT-qPCR
• Library preparation for ChIP-seq, methylation (MeDIP), CRISPR
• Preparing investigators’ raw samples for NGS-based analyses
• “Ready-to-load” service includes quality control and preparation for NGS submission
• Targeted genotyping, cancer mutation panel sequencing and copy number analysis (custom multiplex panes, multiplexed targeted NGS amplicon sequencing-, HT array-based for custom SNP-type assays)
• DNA/RNA extractions from multiple sample types, including FFPE tissue, flash-frozen tissue, RNA-later stored tissue, cell cultures and cell pellets
• DNA/RNA quality control (QC), quality analysis and quantification.

Equipment and Platforms

• Single-cell sequencing

1. Chromium X (10xGenomics)

• Sanger (daily) sequencing

1. Life Technologies 3730xl Analyzer

• Sample homogenizing

1. Bullet Blender
2. MP FastPrep-24 5G

• Nucleic acid extraction devices

1. Promega Maxwell 16
2. Promega Maxwell RSC
3. Qiagen QIAcube Nucleic Acid Extraction Robot
4. Nucleic acid quality analysis and quantification
5. Life Technologies Qubit
6. Fluidigm BioMark HD & JUNO
7. Agena Bio MassArray System

• NGS devices

1. Agilent TapeStation 4200 automated RNA and DNA size selection
2. Sage Scientific Blue PippinPrep automated DNA size selection

• Sequencers

1. Illumina MiniSeq
2. Illumina MiSeq

• NanoDrop One – Thermo Scientific™ Microvolume UV-Vis Spectrophotometer
• Covaris S2 acoustic shearing device
• Life Technologies 7500Fast
• Life Technologies Viia7 – (96-well standard, 96-well fast, and 384-well interchangeable blocks)

Protocols

Cell sorting before scRNA-seq

Lung tissue cell preparation for single-cell sequencing

Publications

Principe DR, Aissa AF, Kumar S, Pham TND, Underwood PW, Nair R, Ke R, Rana B, Trevino JG, Munshi HG, Benevolenskaya EV*, Rana A*. Calcium channel blockers potentiate gemcitabine chemotherapy in pancreatic cancer. Proc. Natl. Acad. Sci. USA 2022 119(18): e2200143119. doi: 10.1073/pnas.2200143119. PMCID: PMC9170157. *Co-corresponding authors.

Kopanja D, Chand V, O’Brien E, Mukhopadhyay NK, Zappia MP, Islam ABMMK, Frolov, MV, Merrill BJ, Raychaudhuri P. Transcriptional repression by FoxM1 suppresses tumor differentiation and promotes metastasis of breast cancer. Cancer Res 2022 82(13):2458-2471. doi: 10.1158/0008-5472.CAN-22-0410. PMCID: PMC9258028

Blaha CS, Ramakrishnana G, Jean SM, Nogueira V, Rho H, Kang S, Bhaskar P, Terry AR, Aissa AF, Frolov MV, Patra KC, Robey RB, Hay N. A non-catalytic scaffolding activity of hexokinase 2 contributes to EMT and metastasis. Nat Commun. 2022 Feb 16;13(1):899. doi: 10.1038/s41467-022-28440-3.PMID: 35173161

Aissa AF, Islam ABMMK, Ariss MM, Go CC, Rader AE, Conrardy RD, Gajda AM, Rubio-Perez C, Valyi-Nagy K, Pasquinelli M, Feldman LE, Green SJ, Lopez-Bigas N, Frolov MV, Benevolenskaya EV.   Single-cell transcriptional changes associated with drug tolerance and response to combination therapies in cancer. Nat Commun. 2021 Mar 12;12(1):1628. doi: 10.1038/s41467-021-21884-z.PMID: 33712615  

Chen X, Ariss MM, Ramakrishnan G, Nogueira V, Blaha C, Putzbach W, Islam ABMMK, Frolov MV, Hay N. Cell-Autonomous versus Systemic Akt Isoform Deletions Uncovered New Roles for Akt1 and Akt2 in Breast Cancer Mol Cell. 2020 Oct 1;80(1):87-101.e5. doi: 10.1016/j.molcel.2020.08.017. Epub 2020 Sep 14.PMID: 32931746

Zappia MP, de Castro L, Ariss MM, Jefferson H, Islam AB, Frolov MV. A cell atlas of adult muscle precursors uncovers early events in fibre-type divergence in Drosophila. EMBO Rep. 2020 Oct 5;21(10):e49555. doi: 10.15252/embr.201949555. Epub 2020 Aug 19.PMID: 32815271 

The Data Integration Shared Resource (DISR) fosters innovation at the intersection of individual and population-level data, clinical and public health research, and data analytics. The goal of the DISR is to support cancer researchers at the University of Illinois Chicago in leveraging data to conduct studies across the cancer control continuum that address the needs of our communities.

Please use the link below to create a request in iLab for the DISR team. Two hours of free consultation are provided for every project. No additional charges will accrue to your account unless approved.

Request Resources from DISR

Our Services

With the support of DISR, researchers can:

• Determine the types of data needed to answer research questions of interest
• Obtain, aggregate, visualize, and securely store data
• Ensure research questions address one or more catchment area cancer-relevant priorities (and if not, how to ensure alignment)

Services and resources support cancer researchers by providing multidimensional data and geospatial analysis to address the needs of the catchment area.

These services include:

• Identification, curation, and linkage of multidimensional data to support the investigation of hypotheses related to cancer biology, prevention, treatment, and survivorship (including social epigenomics)
• Secure storage in the Cancer Data Shelter (IRB# 2018-0577) for data obtained from patients screened for or diagnosed/treated for cancer 
• Visualization of cancer-relevant data through maps, charts, plots, and infographics 
• Consultation regarding disease-specific cohort identification and feasibility analyses
• High-Performance Computing (HPC) solutions for high throughput computing and running omics pipelines

Technologies and Equipment

• The Cancer Center CADS data repository, which houses:

1. Clinical data from UI Health cancer patients (14 years of EHR and tumor registry data)
2. Clinical trial information
3. Research and treatment outcomes data
4. Biomarker data (including “omics”: epigenomics and metabolomics)
5. Biospecimen information (blood, urine, tissues from the UI Health biorepository)

• Population-level data dashboards, powered by Metopio – web-based platforms for Cancer Center members and community leaders that provide population-level spatial data at multiple geographic levels. Data are available for hundreds of indicators in the following domains: demography, social and economic factors, physical environment, health behaviors, clinical care, morbidity, and mortality
• TEMPUS LENS – a platform that offers access to de-identified tumor genomic sequencing data collected from thousands of UI Health cancer patients
• Epic tools, including Epic Cosmos and Slicer Dicer, which DISR co-leaders have training and approval to use. Epic Cosmos integrates billions of clinical data points from 193 million patients across the US. For cancer patients, it includes information about detailed oncology visits, cancer staging, advanced lab results, hospitalizations, and standard outpatient visits. Slicer Dicer is a data exploration and analytics tool that allows users to find, refine, and visualize patient data.
• Disease Specific Cohort (DSC) tool is a self-service discovery software developed by the Cancer Center that allows users to conduct real-time patient cohort discovery. The DSC quickly filters data from the Tumor Registry to stratify data based on disease site, race/ethnicity, vital status, and stage in order to return a cohort that researchers can use to plan protocols or grants.

Meet Our Co-Leaders

Sandeep Kataria, MBA, Director of Oncology Informatics, is charged with creating an integrated data architecture and environment that allows researchers to interact visually with their data. Having planned and implemented large-scale, multiple-source data integrations, he brings more than 22 years of knowledge and experience in cancer data management.

Margaret Wright, PhD, Senior Research Scientist, is a cancer epidemiologist with more than 20 years of experience in the conceptualization, design, and execution of all phases of clinical, epidemiological, and practice-based research. Her expertise include catchment-focused cancer research, leveraging population-based data from local, state, and national sources, and data visualization and mapping.

Ryan Nguyen, DO, is the Faculty Liaison.

DISR is additionally staffed by:

• Prajwal Khot, MS, Expertise with Genomic data visualization
• Ekas Abrol, MS, Expertise in GIS, data visualization, and data science
• Abdul Wahab, MS, Web applications developer
• Nikita Thakur, MSCS, Expertise in data mining and NLP/AI
• Sushma Suda, MSBA (Class of 2024), Expertise in data mining and visualization
• Saransh Singh, MS Data Science, Expertise in data analysis and machine Learning

Citing DISR

Please acknowledge the Cancer Center’s DISR Shared Resource in your written products (grants, publications, etc…) and presentations as follows: 

“We acknowledge the support of the University of Illinois Cancer Center Data Integration Shared Resource (DISR) for their data and dashboard services.”

The Flow Cytometry Shared Resource (FCSR) supports basic and translational research of University of Illinois Cancer Center members by providing a wide array of analytical spectral and traditional flow cytometry, single-cell mass cytometry, high-speed cell sorting services, and imaging flow cytometry. The FCSR also provides instrumentation for the detection of sub-cellular particles such as exosomes and extracellular vesicles, and live cell metabolic flux studies. In addition, biomarker assay development for the detection of soluble proteins such as cytokines, chemokines, and phospho-proteins from biological samples via multiplex assays or ELISA is available. Services extend beyond basic techniques to include the development of new antibody panels for mass cytometry and customized methods for cell sorting.

Request Services from FCSR

Our Services

The FCSR offers multiple services, including flow cytometry analysis on bench-top flow cytometers, cutting-edge mass and imaging cytometers, high-speed cell sorting, experimental design, and data analysis. 

Consultations and Collaborations

FCSR has an open-door policy and provides free consultations for designing experiments, reagents, and protocol optimization as well as support with experimental design and data analysis. Grant writing support as consultants or collaborations, contributions to manuscripts, and letters of support are also provided to Cancer Center members.

Education and Training

The FCSR has hosted lectures on immunological methods with a focus on flow cytometry theory and hands-on instrument use. Lecture hours are devoted to immunological reagents and the theory behind flow cytometry and related techniques, followed by sample preparation, data acquisition and data analysis. Dissemination of information by the FCSR also occurs through regular seminars and workshops. For unassisted use, one-on-one training on all instruments with the exception of the mass cytometer and the cell sorters is provided.

Direct and Pipeline Services

Direct Services: Assisted acquisition and data analysis are provided to Cancer Center users who desire expert acquisition and analysis of samples, particularly for complex, multi-parametric assays. This includes quality control setting up of voltages and gains by the FCSR staff, as well as data analysis using high-capability software platforms such as Cytobank and Kaluza.

Pipeline Services Performed in Collaboration with Other Shared Resources:To study the role of single cells in cancer, a pipeline for cell sorting, single cell transcriptomics/genomics, single cell data analysis, data interpretation, and bioinformatics is set up between the FCSR, CGSR, and CBSR.

Equipment

• Traditional flow cytometers
• LSR Fortessa (4 lasers, 13-color)
• CytoFLEX S (4 lasers, 13-color)
• Gallios (3 lasers, 10-color)
• Spectral flow cytometers
• Aurora (5 lasers, up to 40-colors)
• Mass Cytometer
• Fluidigm Mass cytometer (CyTOF 2, upgraded to Helios)
• Cell sorters
• MoFlo Astrios- (5 lasers, 18-color and six-way sorting)
• MoFlo Astrios EQ- (4 lasers, 14-color and six-way sorting)
• Extracellular Vesicle/small Particle Research
• Nanosight NS300- 488nm (detection of particles between 20-2000nm)
• Zeta sizer Nano series
• Biomarker Analysis
• MagPix (for measuring cytokines, phosphoproteins from serum, supernatant, BAL, etc.)
• SpectraMax M2 microplate/cuvette reader for spectrophotometry
• Metabolic studies
• SeaHorse XFe96
• Data Analysis Platforms
• Kaluza (site license), Cytobank, Modfit, CytExpert

Meet Our Team

Balaji Ganesh, PhD, FCSR Director, is an immunologist and flow cytometrist with more than 17 years of experience in the field in high-parameter data design, acquisition, and analysis. He is responsible for facility oversight and overall administrative and scientific direction of the Shared Resource.

Zainab Alshawabkeh, BS, Research Specialist, is experienced in flow cytometry and maintains and operates the instruments, and provides staff-assisted acquisition services for analytical flow cytometry and cell sorting.

Wei Feng, MS, Research Specialist, has a background in basic biology, helps to develop cutting-edge flow cytometric techniques and provides day-to-day management of the cell sorters, as well as provides staff-assisted runs on the mass cytometer. 

Recent Publications

Serikbaeva A, Li Y, Ganesh B, Zelkha R, Kazlauskas A. Hyperglycemia Promotes Mitophagy and Thereby Mitigates Hyperglycemia-Induced Damage. Am J Pathol. 2022 Dec;192(12):1779-1794. doi: 10.1016/j.ajpath.2022.08.004. Epub 2022 Sep 3. PubMed PMID: 36063899

Kumar S, Das S, Sun J, Huang Y, Singh SK, Srivastava P, Sondarva G, Nair RS, Viswakarma N, Ganesh BB, Duan L, Maki CG, Hoskins K, Danciu O, Rana B, Li S, Rana A. Mixed lineage kinase 3 and CD70 cooperation sensitize trastuzumab-resistant HER2+ breast cancer by ceramide-loaded nanoparticles. Proc Natl Acad Sci U S A. 2022 Sep 20;119(38):e2205454119. doi: 10.1073/pnas.2205454119. Epub 2022 Sep 12. PubMed PMID: 36095190; 

Bachmaier K, Stuart A, Singh A, Mukhopadhyay A, Chakraborty S, Hong Z, Wang L, Tsukasaki Y, Maienschein-Cline M, Ganesh BB, Kanteti P, Rehman J, Malik AB. Albumin Nanoparticle Endocytosing Subset of Neutrophils for Precision Therapeutic Targeting of Inflammatory Tissue Injury. ACS Nano. 2022 Mar 22;16(3):4084-4101. doi: 10.1021/acsnano.1c09762. Epub 2022 Mar 1. PubMed PMID: 35230826

Chen T, Sun MR, Zhou Q, Guzman AM, Ramchandran R, Chen J, Ganesh B, Raj JU. Extracellular vesicles derived from endothelial cells in hypoxia contribute to pulmonary artery smooth muscle cell proliferation in-vitro and pulmonary hypertension in mice. Pulm Circ. 2022 Jan;12(1):e12014. doi: 10.1002/pul2.12014. eCollection 2022 Jan. PubMed PMID: 35506070

Kumar P, Arbieva ZH, Maienschein-Cline M, Ganesh BB, Ramasamy S, Prabhakar BS. Induction of Antigen-Independent Proliferation of Regulatory T-Cells by TNF Superfamily Ligands OX40L and GITRL. Methods Mol Biol. 2021;2248:63-71. doi: 10.1007/978-1-0716-1130-2_4. PubMed PMID: 33185867.

Zhou B, Magana L, Hong Z, Huang LS, Chakraborty S, Tsukasaki Y, Huang C, Wang L, Di A, Ganesh B, Gao X, Rehman J, Malik AB. The angiocrine Rspondin3 instructs interstitial macrophage transition via metabolic-epigenetic reprogramming and resolves inflammatory injury. Nat Immunol. 2020 Nov;21(11):1430-1443. doi: 10.1038/s41590-020-0764-8. Epub 2020 Aug 24. PubMed PMID: 32839607

Qin S, Predescu DN, Patel M, Drazkowski P, Ganesh B, Predescu SA. Sex differences in the proliferation of pulmonary artery endothelial cells: implications for plexiform arteriopathy. J Cell Sci. 2020 May 14;133(9). doi: 10.1242/jcs.237776. PubMed PMID: 32409569

The Translational Pathology Shared Resource (TPSR) was established in 2011. It provides University of Illinois Cancer Center members with access to a comprehensive range of services involving the analysis of animal model and human tissue samples. These services include basic and advanced histological techniques, chemical staining and immunohistochemistry, digital slide scanning, image analysis, tissue microarray design and construction, and laser capture microdissection. In addition, it provides consultation for projects from pathologists with both clinical and laboratory animal expertise.

Request Services from TPSR

Our Services

The TPSR supports its users through consultation, direct services, and relevant training and education.

Consultation

The TPSR staff is available to Cancer Center members for consultation regarding:

• Human and laboratory animal pathology
• Histology
• Digital imaging
• Laser capture
• Tissue microarrays (TMAs)
• Patient-derived organoid / xenograft (PDO/PDX) development

Complex projects begin with a free 1-hour consultation that results in a plan and related cost estimate.

For grant proposals, the TPSR provides budget details, text regarding methodology, and information regarding facilities. The TPSR also connects investigators with pathology faculty who have specialized knowledge related to their research.

Direct Services

Histology

Through its Research Histology Core (RHC), TPSR offers a full range of basic histology services, including:

• Specimen processing
• Embedding
• Sectioning
• RNA/DNA extraction
• Direct chemical staining
• Immunohistochemistry

We also provide antibody validation and optimization of immunochemistry protocols.

Advanced histology methods, such as multiplex staining using chromagen or fluorescence labeling, and CISH/FISH are also available.

Imaging

The Research Tissue Imaging Core (RTIC) provides whole-slide digital scanning, allowing users to view, annotate, and share histology images with free Web-based software (Aperio ImageScope®).

Projects requiring image analysis begin with a consultation involving both histology and imaging specialists in order to ensure that staining is optimal.

A suite of image analysis modules from Indicalabs (HALO®) serves as the main platform for most brightfield (and selected fluorescence) analyses. These modules include machine learning capability and algorithms for a wide range of digital pathology tasks, including:

• Quantification of signals in various cell compartments
• Area quantification (e.g., inflammatory foci)
• Tumor vascularization analysis
• Spatial analysis
• ISH
• TMA analysis
• Serial section registration

Images obtained on the multispectral Vectra system are typically analyzed using inForm® and Phenoptics® software (Akoya Biosciences), whose capabilities include spatial analysis of multiple molecular or cellular targets in an image. A Nanostring nCounter® instrument is available for image-based quantification of multiplexed, bar-coded RNA transcripts from tissue or cell specimens.

TMA Services

To receive TMA services, Cancer Center members meet with a research pathologist to design the TMA. Once IRB approval is obtained and a design is final, archival tissue blocks are accessioned, usually through the UI Biorepository. Whole-slide scans of H&E-stained sections are used to select areas for core punching using either an automated or manual array device.

Patient-Derived Models

Investigators interested in PDX/PDO models either receive training in how to develop and maintain models in their own labs or direct services involving the entire process, from harvesting of primary cells to initial culturing and propagation/expansion of specimens in either xenografts or 3D culture.

Training and Education

The TPSR provides education and training on:

• Preparation of tissue samples for histological analysis, including microtome/cryostat use
• Laser capture microdissection
• Basic image analysis
• Developing and maintaining PDX and PDO specimens

Meet Our Team

Andre Kajdacsy Balla, MD, PhD, TPSR Leader is Professor of Pathology, and a board-certified clinical and surgical pathologist. He has provided surgical pathology support to TPSR and Cancer Center members since 2003 as Director of the Division of Transdisciplinary Pathology in the Department of Pathology. He has participated as a Principal Investigator or as a collaborator in multiple grants on cancer biology and novel imaging methods such as FT-IR spectroscopy and Spatial Light Interference Microscopy.

Eileen Brister, PhD, Research Tissue Imaging Core, is a Research Assistant Professor in the Department of Pathology with expertise in imaging and image processing. They manage the day-to-day operations of the Research Tissue Imaging Core and develop digital pathology methods for reproducible, automated analysis of tissue morphology and biomarkers in human and animal tissues. They are available for consultations regarding tissue imaging and digital analysis approaches.

Subhasis Das, MSc, PhD, Patient-Derived Models Laboratory, is a Research Assistant Professor in the Department of Surgery with broad expertise in developing preclinical cancer models, including PDXs, PDOs, and metastatic models. He has established the patient-derived models’ core lab and plays a leadership role in creating and performing experiments using patient-derived models. He provides direct service and consultation to investigators studying potential drug responses.

Maria Sverdlov, PhD, MS, Research Histology, is a Research Assistant Professor in Pathology. She oversees the day-to-day operations of the research histology core and develops and validates novel and complex immunohistochemical and molecular (RNAscope) assays on human and animal tissue. She is available for consultations on sample preparation and experimental assay design.

Virgilia Macias, MD, TMA/LCM, is a research surgical pathologist with training in oncologic surgical pathology, electron microscopy, and immunohistochemistry. She is a Research Assistant Professor in the Division of Transdisciplinary Pathology at UIC. She has been conducting translational research for 20+ years. In addition to LCM and TMA services, she performs central histology reviews of pathological entities.