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Revolutionary T-Cell Analysis Unveiled for Early Cancer Detection at AACR | Reports Serum Detect

Editor: What To Know

  • At the University of Texas Southwestern and the University of Pennsylvania, the Li lab has developed a suite of computational methods designed to identify cancer-related signals within the TCR repertoire.
  • Serum Detect has shown that these TCR repertoire functional units (or RFUs) can be associated with the presence of cancer and is developing diagnostics to detect RFUs linked to a cancer-specific immune response.
  • Serum Detect, a cancer diagnostics company, is debuting a novel and promising approach for cancer early detection at the upcoming American Association for Cancer Research (AACR) conference.

Serum Detect

Serum Detect, a cancer diagnostics company, is debuting a novel and promising approach for cancer early detection at the upcoming American Association for Cancer Research (AACR) conference. The company is developing diagnostic tests, using standard liquid biopsy samples, that complement and enhance existing screening techniques for early detection of cancer.

Detection

“Detecting cancer early, before it has spread throughout the body, remains the primary way to achieve cancer cures. Too often the diagnosis is late, limiting treatment options and increasing mortality. The development of novel, practical, and cost-effective technologies to save lives by detecting cancer early is a critical priority in biomedical research and Serum’s goal,” said Roman Yelensky, PhD, Serum Detect’s founder and CEO.

Liquid Biopsy

Liquid biopsy, or the assessment of cancer through standard blood draws, is an important potential tool for cancer early detection. Existing approaches for liquid biopsy primarily detect tumor shed analytes such as circulating tumor DNA. These methods have achieved breakthroughs in finding recurring cancer and later stage disease, but often fail to detect earlier stage disease, when the concentration of target analytes is low. In pursuit of broader detection capabilities, researchers have explored if the immune response against cancer may offer a complementary and more abundant molecular target for screening. However, this research has not yet been developed into practical assays that are compatible with and can improve existing clinical liquid biopsy tools.

Serum Detect was founded to address this challenge. The company’s technology is based on novel computational techniques pioneered by co-founder Bo Li, Ph.D. at the University of Texas Southwestern. By advancing scalable algorithms for T-cell receptor (TCR) clustering and statistical association testing in large TCR repertoire databases, Li demonstrated the potential to identify groups of similar TCRs that recognize the same antigens as part of related immune responses. Serum Detect has shown that these TCR repertoire functional units (or RFUs) can be associated with the presence of cancer and is developing diagnostics to detect RFUs linked to a cancer-specific immune response. These TCR RFUs aggregate signal across T-cells with similar TCR sequences, which may make them a more sensitive indicator of disease earlier in its progression.

Further, TCR repertoire functional units can be analyzed using the buffy coat, which is a residual fraction of a standard liquid biopsy blood draw. The use of existing, remaining liquid biopsy materials make Serum Detect’s technology a compelling complementary and orthogonal method to current approaches, potentially enhancing detection capabilities for early-stage cancer. The company is currently pursuing partnering opportunities to complement existing ctDNA tests, as well as planning development of diagnostic test products in-house.

Serum Detect’s founding team has deep sector expertise. CEO Roman Yelensky, Ph.D. was an early member of the leadership teams at both Foundation Medicine and Gritstone bio, bringing a wealth of experience in developing cancer genomics technologies and diagnostics. Co-founder Bo Li, Ph.D. is currently an Associate Professor at the Perelman School of Medicine, University of Pennsylvania. At the University of Texas Southwestern and the University of Pennsylvania, the Li lab has developed a suite of computational methods designed to identify cancer-related signals within the TCR repertoire.

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