Leonard Alfredo Harris, PhD

Research Program: Cancer Biology Faculty Rank: Assistant Professor Campus: University of Arkansas (Fayetteville) College: College of Engineering Department: Biomedical Engineering

Cancer Research Interest

• Disease Site Focus: Cutaneous/Melanoma, Thoracic/ Lung, No Specific Disease Site
• Research Focus Area: Treatment, Informatics
• Type of Research: Basic
• Research Keywords: Systems biology, Computational modeling, Signal transduction pathways, Cell-cell interactions
• Research Interest Statement: My expertise is in computational modeling of intracellular signaling pathways and cell-cell interactions in tumors. Before joining the Department of Biomedical Engineering at UA-Fayetteville, I worked as a postdoctoral researcher in the Center for Cancer Systems Biology at Vanderbilt University School of Medicine. I maintain an active role in the Center and work closely with experimentalists to build computational models that can provide insight and aid in the interpretation of experimental data at both the single-cell and cell population levels in a variety of cancer types. Examples include live-cell fluorescence imaging, bulk and single-cell RNA sequencing, and whole-exome sequencing in small cell lung cancer, EGFR-mutant non-small cell lung cancer, and BRAF-mutant melanoma cell lines. Our goal is to understand the roles of genetic heterogeneity and phenotypic plasticity in anticancer drug response and treatment evasion. I also continue to work closely with collaborators in the Vanderbilt Center for Bone Biology to build biochemical and cell-cell interaction models of tumor-induced bone disease. My research goals here at UA-Fayetteville include building detailed mechanistic models of whole cancer cells and whole tumors that can be used as in silico platforms for identifying new therapeutic targets and developing personalized treatments for patients. This work is highly interdisciplinary and I hope to forge new collaborations with researchers at UAMS to address important questions relevant to the residents of Arkansas.

Contact Information

• Email Address: harrisl@uark.edu

Recent Publications

• Beik SP, Harris LA, Kochen MA, [et al.]. Unified tumor growth mechanisms from multimodel inference and dataset integration. PLoS computational biology. 2023 19(7):e1011215. PMID: 37406008. PMCID: PMC10351715.
• Groves SM, Panchy N, Tyson DR, [et al., including Harris LA]. Involvement of Epithelial-Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity. Cancers. 2023 15(5). PMID: 36900269. PMCID: PMC10001072.
• Ildefonso GV, Metzig MO, Hoffmann A, [et al., including Harris LA]. A biochemical necroptosis model explains cell-type-specific responses to cell death cues. Biophysical journal. 2023. PMID: 36710493. PMCID: PMC10027451.
• Velleuer E, Domínguez-Hüttinger E, Rodríguez A, [et al., including Harris LA]. Concepts of multi-level dynamical modelling: understanding mechanisms of squamous cell carcinoma development in Fanconi anemia. Frontiers in genetics. 2023 14:1254966. PMID: 38028610. PMCID: PMC10652399.
• Wandishin CM, Robbins CJ, Tyson DR, [et al., including Harris LA]. Real-time luminescence enables continuous drug-response analysis in adherent and suspension cell lines. Cancer biology & therapy. 2022 23(1):358-368. PMID: 35443861. PMCID: PMC9037430.
• Pino JC, Lubbock ALR, Harris LA, [et al.]. Processes in DNA damage response from a whole-cell multi-omics perspective. iScience. 2022 25(11):105341. PMID: 36339253. PMCID: PMC9633746.
• Hayford CE, Tyson DR, Robbins CJ 3rd, [et al., including Harris LA]. An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability. PLoS biology. 2021 19(6):e3000797. PMID: 34061819. PMCID: PMC8195356.
• Prugger M, Einkemmer L, Beik SP, [et al., including Harris LA]. Unsupervised logic-based mechanism inference for network-driven biological processes. PLoS computational biology. 2021 17(6):e1009035. PMID: 34077417. PMCID: PMC8202945.
• Lubbock ALR, Harris LA, Quaranta V, [et al.]. Thunor: visualization and analysis of high-throughput dose-response datasets. Nucleic acids research. 2021. PMID: 34038546. PMCID: PMC8265171.
• Keating SM, Harris L, Waltemath D, [et al.]. SBML Level 3: an extensible format for the exchange and reuse of biological models. Molecular systems biology. 2020 16(8):e9110. PMID: 32845085. PMCID: PMC8411907.
• Zhang F, Smith LP, Blinov ML, [et al., including Harris LA]. Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2. Journal of integrative bioinformatics. 2020 17(2-3). PMID: 32628633. PMCID: PMC7756619.