Kim Blenman, PhD, MS, University of Florida College of Medicine

Kim Blenman's picture
Assistant Professor of Medicine (Medical Oncology) and of Computer Science
300 George Street, New Haven, CT 06511

Research Projects:


Project 1:

Title: Protecting me from myself: Autoantibodies

Short Description: An antibody is a protein that is produced in response to a substance that causes the body to make a specific immune response called an antigen. The antigen is usually a threat such as a pathogen or toxin. The purpose of the binding is to help destroy the antigen. An autoantibody is an antibody made against substances formed by a person’s own body. Autoantibodies can directly destroy cells that have the antigens on them or can make it easier for other white blood cells to destroy them. Some autoimmune diseases are caused by autoantibodies. We are developing an autoantibody matrix platform that contains ≥ 20,000 potential human antigen targets. We are developing tools for visualization and statistical assessment to (1) Identify autoantibodies, (2) Identify biological pathways for autoantibodies, (3) Identify autoantibodies that can be used for assay normalization and QA/QC assessment, (4) Quantitate autoantibody (based on GST-tag expression), and (5) Identify and remove non-specific background staining or autofluorescence. Multiple projects are available.


Project 2:

Title: Clones R Us: Deep dive into immunarch for immune repertoire profiling

Short Description: The immune system attacks and destroys threats (e.g., toxins, pathogens, cancer) through pattern recognition of antigens (e.g., proteins) that comprise the threat. B cells and T cells respond to that pattern recognition by making clones of themselves that are specific for recognition of the antigen. When we treat patients with various therapies, those clones are either eliminated, expanded, or have no response to the treatments. Developing visual tools that can identify clones before treatment and after treatment with a display of the kinetics of their behavior will shed light on what treatments are doing to these immune populations when treatments work and when they do not work. Immunarch package in R could be a helpful tool for visualization and statistical assessment of the kinetics of the behaviors. Multiple projects are available.


Project 3:

Title: Essence of Ground Truth: Real-world scenarios

Short Description: Histology, the study of microscopic structures in patient tissue, is a pathologist’s and clinician’s first step to diagnosing and monitoring many diseases. Patient tissues are stained with vibrant dyes, such as hematoxylin and eosin (H&E), that highlight components of the tissue such as cells, vessels, and architectural features. AI tools are being developed to identify and quantitate components and features in scanned images of H&E stained tissue. However, comparative ground truth data that are required to produce effective recognition of real-world scenarios are lacking. Using a custom-built microscopy platform, we are developing ground truth datasets, imaging software (acquisition, visualization, assessment), statistical packages, and educational training tools for H&E stained tissue assessment in collaboration with the U.S. Food and Drug Administration (FDA). Multiple projects are available.


Project 4:

Title: Location, location!!!!: Spatial Dynamics of TIME

Short Description: The right tumor immune microenvironment (TIME) is critical for elimination of cancer cells. Immunohistochemistry and immunofluorescence staining of histology tissue are used to assess multiple cellular (e.g., immune cells) and structural (e.g., extracellular matrix) targets. We have developed several staining methods and software tools to evaluate >25 targets (e.g., cell proteins) simultaneously in a single tissue section using different color chromogens and fluorochromes. The distribution of each target is assessed in the tissue through creation of unique spectral wavelength profiles for each chromogen or fluorochrome associated with the target of interest. These unique spectral wavelength profiles allow for linear unmixing of the targets of interest into separate channels which enables the quantitation of the targets on each cell and assessment of spatial relationships within a scanned image of the stained tissue. We are developing methods to visualize the changes in spatial relationships over distances from key components within TIME. Multiple projects are available.


Project 5:

Title: Best of many worlds: Proteogenomic profiling

Short Description: TP53 is the gene that encodes p53, a protein that regulates cell division by keeping cells from growing and dividing too fast or uncontrollably. TP53 mutations are high in human papilloma virus (HPV) negative head and neck small cell carcinomas (HNSCCs). These mutations may be associated with specific changes in the tumor immune microenvironment. Phosphoproteomics, proteomics, transcriptomics, DNA methylation, somatic copy number alterations, and mutational analysis have been performed in a large HPV HNSCC cohort to address this question. Integration of data from multiple -omic platforms may help to provide insights that can lead to more precise approaches to treatment. We will create visualization tools that shed light on common biomarkers and biological pathways. Multiple projects are available.