Alexander T Pearson, MD PhD

  • Associate Professor of Medicine
    Committee on Cancer Biology
    Committee on Clinical Pharmacology and Pharmacogenomics
    Committee on Genetics, Genomics and Systems Biology
  • Clinical Interests: Clinical Trials, Immunotherapy, Medical education, Salivary gland cancers, Squamous Cell Carcinoma Tumors
  • Research and Scholarly Interests: Education, Graduate Medical, Head and Neck Cancer, Mathematical Model, Models, Biologic, Neural Network Models, Salivary Gland Cancers, Statistical Models, Therapies, Combined Modality, Tumor Cell Lines, Tumor Immune Escape
  • Websites: Research Network Profile
  • Contact: apearson5@uchicago.edu
  • Graduate Programs: Cancer Biology, Genetics, Genomics & Systems Biology, UChicago Biosciences

The Pearson Lab integrates clinical expertise, mathematical modeling, high dimensional statistics, and basic tumor biology methods to investigate and propose new treatments for head and neck cancer.

University of Michigan
Ann Arbor, MI
Fellowship - Hematology/Oncology
2016

University of Michigan
Ann Arbor, MI
Postdoctoral Fellowship - Nor Lab (2013-2017)
2016

University of Michigan
Ann Arbor, MI
Residency - Internal Medicine
2012

University of Rochester
Rochester, NY
MD - Medicine
2010

University of Rochester
Rochester, NY
PhD - Statistics
2009

Cornell University
Ithaca, NY
BS - Biometry and Statistics
2002

Dysregulated FGFR3 signaling alters the immune landscape in bladder cancer and presents therapeutic possibilities in an agent-based model.
Dysregulated FGFR3 signaling alters the immune landscape in bladder cancer and presents therapeutic possibilities in an agent-based model. Front Immunol. 2024; 15:1358019.
PMID: 38515743

Evolutionary dynamics of tipifarnib in HRAS mutated head and neck squamous cell carcinoma.
Evolutionary dynamics of tipifarnib in HRAS mutated head and neck squamous cell carcinoma. Oral Oncol. 2024 Feb; 149:106688.
PMID: 38219706

Validation of the RSClin risk calculator in the National Cancer Data Base.
Validation of the RSClin risk calculator in the National Cancer Data Base. Cancer. 2024 Apr 15; 130(8):1210-1220.
PMID: 38146744

Mathematical model predicts tumor control patterns induced by fast and slow cytotoxic T lymphocyte killing mechanisms.
Mathematical model predicts tumor control patterns induced by fast and slow cytotoxic T lymphocyte killing mechanisms. Sci Rep. 2023 12 18; 13(1):22541.
PMID: 38110479

Olaparib and Ceralasertib (AZD6738) in Patients with Triple-Negative Advanced Breast Cancer: Results from Cohort E of the plasmaMATCH Trial (CRUK/15/010).
Olaparib and Ceralasertib (AZD6738) in Patients with Triple-Negative Advanced Breast Cancer: Results from Cohort E of the plasmaMATCH Trial (CRUK/15/010). Clin Cancer Res. 2023 12 01; 29(23):4751-4759.
PMID: 37773077

The use of deep learning state-of-the-art architectures for oral epithelial dysplasia grading: A comparative appraisal.
The use of deep learning state-of-the-art architectures for oral epithelial dysplasia grading: A comparative appraisal. J Oral Pathol Med. 2023 Nov; 52(10):980-987.
PMID: 37712321

Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary.
Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary. Haematologica. 2023 08 01; 108(8):1993-2010.
PMID: 36700396

External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population.
External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population. Radiol Artif Intell. 2023 Nov; 5(6):e220299.
PMID: 38074785

Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study.
Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study. Gastric Cancer. 2023 09; 26(5):708-720.
PMID: 37269416

Deep learning generates synthetic cancer histology for explainability and education.
Deep learning generates synthetic cancer histology for explainability and education. NPJ Precis Oncol. 2023 May 29; 7(1):49.
PMID: 37248379

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Mark Roth Award
University of Michigan
2015

Chief Fellow in Hematology/Oncology
University of Michigan
2014 - 2015