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2022 James Coulter – PCF Young Investigator Award

Single-Center Retrospective Clinical Study of Artificial Intelligence (AI)-Based Protein Assessment of Three Tumor Suppressor Genes (“Triple-TSG”) for Improved Risk Stratification and Treatment Management of Advanced Prostate Cancer

Tamara Jamaspishvili, MD, PhD
State University of New York (SUNY) Upstate Medical University

Mentors: Jeremy Squire, PhD, Alina Basnet, MD

Description:

  • Hormonal therapy or androgen deprivation therapy (ADT), with or without radiation, is a mainstay of treatment for advanced prostate cancer. Unfortunately, treatment failure and development of hormone-insensitive or castrate-resistant prostate cancer (CRPC) is very common and alternative treatment options are limited or less effective. Therefore, it is crucial to timely and accurately stratify the patients who will likely respond to ADT and progress to lethal metastatic (mCRPC) or non-metastatic (nmCRPC) castrate-resistant prostate cancer.
  • Dr Jamaspishvili’s research focuses on developing artificial intelligence (AI)-based tissue biomarker assessment to better risk stratify the diseases and identify patients at risk of disease progression, metastasis or treatment resistance.
  • Improvement in biomarker research is urgently needed to advance precision medicine. Developing bias-free, objective, quantitative approaches in pathology practices is a prerequisite for precision medicine and biomarker-guided clinical trials.
  • In this project, Tamara Jamaspishvili aims to clinically validate PTEN (tumor suppressor gene) loss assessment AI-based workflow that she and her colleagues at NCI have developed to predict prostate cancer recurrence and metastasis.
  • Along with PTEN loss assessment, Dr Jamaspishvili and her multi-disciplinary team will assess two crucial tumor suppressor genes, p53 and Rb1, which are known to identify patients with more aggressive diseases and who are unlikely to respond to hormonal therapy. They will examine immunohistochemically stained scanned prostate cancer tissue images to unravel complex cellular and molecular relationships predicting disease progression, duration and response to hormonal treatment, and the development of hormone-resistant prostate cancer.
  • Improving prostate cancer risk stratification and management will positively impact the quality of life of cancer patients by timely avoiding unnecessary side effects and finding effective treatment options early in the disease process.
  • Dr Jamaspishvili and her team believe their cost-efficient, bias-free AI-based biomarker approach will be an excellent alternative to expensive genomic testing in low-to-middle income countries.
  • If successful, this project will develop a new cost-efficient tissue test using prostate cancer tissue images to identify patients at risk for aggressive disease and poor outcomes and guide treatment management in such patients.

What this means to patients: In this project, Dr. Jamaspishvili and team will create an AI-based “triple-tumor suppressor gene” protein status assessment that uses pathology slides to improve risk stratification and help guide physicians in the treatment management of patients with high-risk, advanced prostate cancer. This could also serve as a cost-efficient screening method in low-to-middle income countries where genomic testing is still expensive and challenging.