Hua Li
Washington University in St Louis, MO·Biomedical Engineering
Cancer patients given the same standard treatment respond very differently, and many tumors come back. Knowing early which patients are likely to respond would let doctors personalize care.
- Fields
Biomedical Engineering
Medicine & Clinical Research
Computer Science
- Topics
cervical cancer
head and neck squamous cell carcinoma
head and neck cancer
- Grants
- 2 known grants, through May 2029
What they work on
- Develop a learning-based prognostic model that predicts cervical cancer treatment response and outcome by integrating RNA biomarkers, radiologic and histologic images, and clinicopathologic data from about 600 patients at two institutions.
- Discover correlations among RNA, imaging and clinical data in cervical cancer to enable dynamic patient stratification that could support adaptive treatment strategies.
- Build a computational model for early prediction of treatment failure and recurrence in head and neck squamous cell carcinoma (HNSCC), using about 1,200 patient cases from two institutions.
- Combine human and HPV RNA biomarkers with PET, CT and MR imaging, histology images and clinicopathologic data to derive a multimodal biomarker signature for HNSCC recurrence.
More about the research
Each available data source, including tumor RNA, medical scans, tissue slides and clinical records, offers only part of the picture. This work combines all of them in machine learning models that predict how patients with two cancers will fare: cervical cancer and head and neck cancer.
Why it matters
Patients with cervical cancer or head and neck squamous cell carcinoma could benefit if doctors could predict early who will respond to treatment or relapse. Such predictions could let care teams intensify or adapt therapy for high-risk patients and spare others unneeded treatment. The work could provide prognostic tools to support personalized and adaptive cancer care.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Dohun Pyeon
Michigan State University, MI·Microbiology & Immunology
Define how the chemokine CXCL14 increases MHC-I antigen presentation, which lets immune cells recognize tumor cells, to suppress HPV-positive head and neck squamous cell carcinoma.
Jeanne Shen
Stanford University, CA·Medicine & Clinical Research
Build a publicly available, expert-annotated multimodal colorectal cancer dataset. It will combine pathology whole-slide images, preoperative CT and MRI scans, and structured electronic medical record data.
Riyue Bao
University of Pittsburgh, PA·Medicine & Clinical Research
Establish whether tumor-cell p38 MAPK signaling causes non-T cell-inflamed tumors and resistance to checkpoint inhibitors in HPV-negative head and neck squamous cell carcinoma, using patient cohorts and four syngeneic mouse models.
The school
Washington University in St Louis: 97 labs on PI Pages, $1.2B a year on research, 365 research doctorates a year.
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