Mackenzie Wehner
University of Texas MD Anderson Cancer Center, TX·Medicine & Clinical Research·Early-career
Actinic keratoses are rough, scaly patches caused by years of sun exposure. They affect tens of millions of people in the United States each year.
- Fields
Medicine & Clinical Research
Public Health & Epidemiology
- Topics
actinic keratosis
cutaneous squamous cell carcinoma
cSCC
- Grants
- 2 known grants, through May 2031
What they work on
- Test whether a 4-day course of 5-fluorouracil plus calcipotriene, a vitamin D analog, is non-inferior to 2–4 weeks of 5-fluorouracil alone, in a two-site randomized trial of patients with multiple actinic keratoses.
- Compare patient satisfaction, side effects, adherence and new squamous cell carcinomas between the short combination and standard 5-fluorouracil treatment of actinic keratoses.
- Compare in-person actinic keratosis counts with counts from standardized digital photographs. Explore whether an AI image segmentation algorithm can automate the counting.
- Assess whether vision-language models, AI that interprets images alongside text, can reliably grade the severity of precancerous skin conditions for telemonitoring.
- Measure the absolute risks of melanoma, basal cell carcinoma and squamous cell carcinoma over time in patients with actinic keratoses, using large administrative datasets.
- Characterize current skin cancer follow-up care for patients with actinic keratoses and develop the first skin cancer risk prediction model for this group.
More about the research
Some turn into cutaneous squamous cell carcinoma, the second most common cancer in the country. Treating them well, and knowing which patients face the highest cancer risk, could prevent many skin cancers. This work tackles both questions. One project is a clinical trial of a shorter, gentler cream treatment. The other uses large health datasets to measure and predict skin cancer risk in people with these lesions.
Why it matters
People with actinic keratoses are a large, high-risk group, yet there are no specific guidelines for their skin cancer screening. Risk estimates and a prediction model could form the basis for such recommendations. A shorter, more tolerable treatment could lead more patients to accept preventive therapy and so prevent squamous cell carcinomas. Photo-based, AI-assisted lesion counting could support remote follow-up and make skin trials more efficient.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Steven Frank
University of Texas MD Anderson Cancer Center, TX·Medicine & Clinical Research
Characterize late radiation-associated dysphagia (L-RAD) and identify its subtypes by extending follow-up of a 440-patient randomized trial of proton therapy (IMPT) versus X-ray therapy (IMRT) to 10 years.
Joann Elmore
University of California-Los Angeles, CA·Medicine & Clinical Research
Run a two-year pragmatic randomized trial of more than 154,000 3D screening mammograms assigned to interpretation with or without an FDA-cleared AI tool, measuring cancer detection and recall rates across 16 breast imaging facilities.
Kang Wang
University of California-San Francisco, CA·Medicine & Clinical Research
Build a large standardized database of abdominal CT images and radiology reports, using large language models to automatically extract findings from reports and select data for AI training.
The school
University of Texas MD Anderson Cancer Center: 23 labs on PI Pages, $1.4B a year on research.
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