Microfluidic and AI-based Profiling of Cancer Cells in Blood
Official title: Microfluidic Isolation and Deep Learning-based Profiling of Subtypes of Circulating Tumor Cells during Epithelial Mesenchymal Transition
Funded at Texas Tech University · NIH-11361375 · Data updated 2026-11-12
A scientist team will use microfluidics and deep learning to identify and study subtypes of circulating tumor cells in blood, aiming to understand which subtypes drive cancer spread.
Quick facts
| Grant type | R15 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Texas Tech University NIH-funded |
| Lab location | 1 site (Lubbock, United States) |
| Project start | June 1, 2026 |
| Project end | May 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $607,488 |
| NIH project number | 1R15CA313429-01 |
| Project ID | NIH-11361375 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with cancer whose blood contains circulating tumor cells and whose disease could be studied using CTC isolation and EMT profiling.
✕Less likely to help
Patients without detectable circulating tumor cells or with cancer types not studied in this project may not experience direct benefits.
What this research studies
This project combines a specialized microfluidic device with advanced AI to isolate circulating tumor cells from blood and categorize them by epithelial and mesenchymal features. By profiling these subtypes, the team hopes to uncover markers linked to metastatic potential. The work is designed to be translatable to pre-clinical and eventually patient settings, with a focus on robust data analysis and imaging-based profiling. Results could guide future tests or treatments aimed at preventing metastasis.
Why it matters
Potential benefit: If successful, patients could benefit from better understanding of metastatic processes and the development of targeted diagnostics or therapies.
How similar studies have gone: Previous studies show that profiling CTC subtypes can provide insights into metastasis, but this project emphasizes EMT-focused subtyping with microfluidics and deep learning, which is still being established.
Where this research is happening
-
Texas Tech University
Lubbock, United States Active
Researchers
- Principal investigator: Li, Wei — Texas Tech University
- Study coordinator: Li, Wei
Related research
Other NIH-funded projects on the same topics.
-
Integrative histo-genomic analysis to guide cancer risk and targeted therapies with interpretable AI
Researchers are developing an advanced AI-powered approach to map genetic and cellular patterns across breast and cervical cancers to help tailor treatments.
-
Predicting how antimalarial drug resistance spreads with AI
A powerful AI model will be built to forecast how resistance to antimalarial drugs might spread in Africa and beyond, helping clinicians and public health teams stay ahead of outbreaks.
-
Self-supervised deep learning for biological sequences
A deep learning project uses self-supervised methods to better understand biological sequences and related data, with the goal of advancing biology and medicine.
-
Mobile phone imaging and AI to screen oral cancers in low-resource settings
A low-cost mobile phone device with artificial intelligence is being developed to help frontline health workers screen for oral cancer early in low-resource areas.
-
Linking Genetic Variants to Real-Life Health Effects with Smart AI
A new AI-powered approach will predict how genetic differences affect health across multiple levels to help doctors understand diseases and tailor care.
-
Integrative AI tools to map protein sequences to structures and functions
A scientist team will develop advanced AI methods to better connect protein sequences, their 3D shapes, and how they work, using large biological data from sequencing and structures.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.