Finding rare cancer cells in blood and biopsy samples

RarecyteFinder: A Bench-to-Bits Toolkit for Label-Free, Whole-Spectrum Analysis of Rare Disseminated Tumor Cells in Liquid and Tissue Biopsies

NIH-funded research Institute for Systems Biology · NIH-11252521

This project builds a label-free toolkit to find and analyze extremely rare tumor cells in blood and tissue samples from people with cancer.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionInstitute for Systems Biology NIH-funded
Lab location1 site (Seattle, United States)
Project IDNIH-11252521 on NIH RePORTER

What this research studies

The team is developing a 'bench-to-bits' approach that combines label-free wide-spectrum imaging with advanced computer algorithms to detect rare disseminated tumor cells in blood, peritumoral tissue, and lymph nodes. The system avoids relying on specific molecular tags and instead uses imaging patterns and machine learning to pick out tumor cells from many normal cells. Researchers will test the toolkit on clinical blood and biopsy specimens from solid tumor patients and refine methods to retrieve identified cells for deeper molecular profiling. This work aims to reduce missed detections and false positives to make detection of metastatic precursor cells more reliable for staging and monitoring.

Who could benefit from this research

Good fit: Ideal participants would be people with solid tumors who can provide blood samples or tissue/lymph node biopsy specimens for analysis.

Not a fit: Healthy individuals and people who cannot provide suitable blood or tissue samples, or whose cancers do not shed detectable tumor cells, are unlikely to benefit directly.

Why it matters

Potential benefit: If successful, this could enable earlier and more accurate detection of metastatic tumor cells to help guide staging and treatment decisions.

How similar studies have performed: Existing liquid biopsy methods like ctDNA and some CTC assays have shown promise but often miss very rare cells, and this label-free imaging-plus-AI approach is relatively novel and less clinically proven.

Where this research is happening

Seattle, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.