Identifying different types of lung cancer using advanced data analysis
Official title: Leveraging Heterogenous Common Fund Data Sets and Beyond for Identifying Lung Cancer Subtypes
Funded at University of Nebraska Medical Center · NIH-10990280 · Data updated 2026-11-12
This study is looking to make it easier to identify different types of lung cancer by using advanced technology to analyze a lot of biological information, which could help doctors provide more personalized treatment options for patients.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Nebraska Medical Center NIH-funded |
| Lab location | 1 site (Omaha, United States) |
| Project start | September 5, 2024 |
| Project end | September 4, 2025 |
| Funding year | 2024 |
| Award (this year) | $307,000 |
| NIH project number | 1R03OD038391-01 |
| Project ID | NIH-10990280 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with lung cancer, particularly those with non-small cell lung cancer or small cell lung cancer.
✕Less likely to help
Patients with lung cancer who do not have identifiable subtypes or those with other unrelated cancers may not benefit from this research.
What this research studies
This research aims to improve the identification of lung cancer subtypes by integrating various types of biological data, including genomic and epigenetic information. By utilizing advanced machine learning techniques, the project seeks to analyze large datasets generated from multiple sources, which can lead to more accurate and efficient subtype classification. This approach aims to overcome the limitations of traditional methods that are often costly and time-consuming. Patients may benefit from more personalized treatment options based on their specific lung cancer subtype.
Why it matters
Potential benefit: If successful, this research could lead to more precise and tailored treatment strategies for lung cancer patients.
How similar studies have gone: Previous research has shown promise in using integrated data approaches for cancer subtype identification, indicating potential success for this novel methodology.
Where this research is happening
-
University of Nebraska Medical Center
Omaha, United States Active
Researchers
- Principal investigator: Wan, Shibiao — University of Nebraska Medical Center
- Study coordinator: Wan, Shibiao
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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.