Mapping lung cancer tumors to better treatment models using protein analysis
Official title: Proteomics-driven precision molecular mapping of patient tumors to preclinical models in lung cancer
Funded at University of Tx Md Anderson Can Ctr · NIH-11112630 · Data updated 2026-11-12
This study is looking for better ways to treat lung cancer by matching your tumor's unique protein patterns to new treatment models, so we can find the most effective therapies for you.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Tx Md Anderson Can Ctr NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project start | March 11, 2025 |
| Project end | February 28, 2027 |
| Funding year | 2025 |
| Award (this year) | $244,228 |
| NIH project number | 1R21CA288901-01A1 |
| Project ID | NIH-11112630 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are lung cancer patients who have not responded well to existing treatments or are at risk of developing drug resistance.
✕Less likely to help
Patients with early-stage lung cancer or those who have not yet begun treatment may not benefit from this research.
What this research studies
This research focuses on improving treatment options for lung cancer patients by developing new strategies that match their tumors to preclinical models based on protein data. The study utilizes reverse-phase protein arrays (RPPAs) to analyze proteins in tumor samples, which may provide more accurate information than traditional genomic methods. By identifying key biomarkers and therapeutic targets through this proteomic approach, the research aims to enhance the effectiveness of cancer therapies and reduce drug resistance. Patients' tumor samples will be analyzed to find the best preclinical models for their specific cancer characteristics.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective treatment options for lung cancer patients.
How similar studies have gone: Previous research has shown promise in using proteomic approaches for cancer treatment matching, indicating potential success for this novel method.
Where this research is happening
-
University of Tx Md Anderson Can Ctr
Houston, United States Active
Researchers
- Principal investigator: Li, Jun — University of Tx Md Anderson Can Ctr
- Study coordinator: Li, Jun
Related research
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Integrative Analysis of Lung Cancer Risk and Causes
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Digital health strategies to expand lung cancer screening in safety-net clinics
A funded project aims to help low-resource clinics increase the use of lung cancer screening for patients who smoke or are at risk.
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Proteomics-guided matching of lung cancer tumors to preclinical models
This grant aims to improve how we match a patient’s lung cancer tumor to the right preclinical models using protein data.
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Optimizing lung cancer care with smart tools for prevention, early detection, treatment, and survivorship
A U01 grant using AI and biomarkers to improve lung cancer prevention, screening, treatment, and survivorship care for people at risk or living with lung cancer.
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.