Wei Huang

About

Wei Huang is a Professor (CHS) in the Department of Pathology and Laboratory Medicine at the University of Wisconsin School of Medicine and Public Health. His research involves the development and validation of artificial intelligence-powered platforms for prostate cancer grading, quantification, and prediction of early recurrence post-prostatectomy. His work also includes studying the expression of spermidine/spermine N-acetyl transferase (SSAT) in human prostate tissues in relation to cancer progression and metastasis, as well as advancing quantitative pathology techniques such as chromogenic multiplexed immunohistochemistry. Dr. Huang has contributed to the field through publications in prominent journals, focusing on innovative methods for cancer diagnosis and prognosis.

Research topics

• Internal medicine
• Medicine
• Radiology
• Biology
• Genetics
• Cell biology
• Cancer research
• Medical physics
• Urology
• Pathology

Selected publications

• Development and Validation of an Artificial Intelligence–Powered Platform for Prostate Cancer Grading and Quantification

  JAMA Network Open · 2021 · 66 citations

  1st authorCorresponding

  Importance: The Gleason grading system has been the most reliable tool for the prognosis of prostate cancer since its development. However, its clinical application remains limited by interobserver variability in grading and quantification, which has negative consequences for risk assessment and clinical management of prostate cancer. Objective: To examine the impact of an artificial intelligence (AI)-assisted approach to prostate cancer grading and quantification. Design, Setting, and Participa…

  DOI

• A phase II randomized placebo‐controlled trial of pomegranate fruit extract in men with localized prostate cancer undergoing active surveillance

  The Prostate · 2020 · 34 citations

  INTRODUCTION OR OBJECTIVE: Men with favorable-risk prostate cancer (PCa) on active surveillance may benefit from intervention strategies to slow or prevent disease progression and the need for definitive treatment. Pomegranate and its extracts have shown antiproliferative and proapoptotic effects in cell lines and animal models, but its effect on human prostate cancer as a target tissue remain unclear. Objectives of this trial include pomegranate's ability to alter serum and prostate tissue biom…

  DOI

• PLK1 and NOTCH Positively Correlate in Melanoma and Their Combined Inhibition Results in Synergistic Modulations of Key Melanoma Pathways

  Molecular Cancer Therapeutics · 2020 · 33 citations

  , which have not been well studied in melanoma. In conclusion, our study demonstrated a synergistic antiproliferative response of concomitant targeting of PLK1 and NOTCH in melanoma, unraveling a potential novel therapeutic approach for detailed preclinical/clinical evaluation.

  DOI

• PLK4 is upregulated in prostate cancer and its inhibition reduces centrosome amplification and causes senescence

  The Prostate · 2022 · 27 citations

  BACKGROUND: Identification of novel molecular target(s) is important for designing newer mechanistically driven approaches for the treatment of prostate cancer (PCa), which is one of the main causes of morbidity and mortality in men. In this study, we determined the role of polo-like kinase 4 (PLK4), which regulates centriole duplication and centrosome amplification (CA), in PCa. MATERIALS AND METHODS: Employing human PCa tissue microarrays, we assessed the prevalence of CA, correlated with Glea…

  DOI

• Artificial Intelligence–Based Digital Histologic Classifier for Prostate Cancer Risk Stratification: Independent Blinded Validation in Patients Treated With Radical Prostatectomy

  JCO Clinical Cancer Informatics · 2025-06-01 · 5 citations

  articleOpen access

  PURPOSE Artificial intelligence (AI) tools that identify pathologic features from digitized whole-slide images (WSIs) of prostate cancer (CaP) generate data to predict outcomes. The objective of this study was to evaluate the clinical validity of an AI-enabled prognostic test, PATHOMIQ_PRAD, using a clinical cohort from the Cleveland Clinic. METHODS We conducted a retrospective analysis of PATHOMIQ_PRAD using CaP WSIs from patients who underwent radical prostatectomy (RP) between 2009 and 2022 a…

  PublisherDOI

Recent grants

• Multicenter Quantitative MRI Assessment of Breast Cancer Therapy Response

  NIH · $2.8M · 2020–2026

• NIH Grant U01CA154602

  NIH · $2.9M · 2017

• NIH Grant R01CA120861

  NIH · $928k · 2012

Frequent coauthors

• David F. Jarrard

  82 shared

• Charles S. Springer

  70 shared

• Luminita A. Tudorica

  66 shared

• William D. Rooney

  51 shared

• Xin Li

  University of Maryland, Baltimore

  44 shared

• Alina Tudorica

  44 shared

• Ian Tagge

  Biogen (United States)

  42 shared

• Aneela Afzal

  40 shared

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