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A live tumor fragment (LTF) platform with real-time imaging for immune response assays

Immuno-Oncology (IO) therapies provide remarkable clinical benefits. However, too few patients respond, and there are no diagnostic tools that predict IO response with high accuracy. Moreover, as more IO drugs and combinations are approved, selecting the best IO-based regimen for each patient will become more complex. To facilitate this selection, we are developing an ex vivo live tumor fragment (LTF) screening platform that retains representation...

AACR  | 2022
Tumor/normal and live/dead classification in live tumor fragments using label-free multiphoton microscopy

We have developed a live tumor fragment (LTF) platform for predicting clinical response to cancer drugs. The success of this approach depends on screening tissue fragments derived from biopsies and excisions before drug treatment to select those that have acceptable levels of viability and tumor content. To enable this screening, we are developing label-free methods for integrated assessment of LTF histology, viability, and metabolic status ...

AACR  | 2022
Dynamic imaging of T cell surveillance in live tumor fragments using camelid nanobodies

Immunotherapies (ITx) have revolutionized the oncology landscape. However, predicting patient responses to ITx is difficult based solely on static correlates such as TIL localization and molecular signatures. Anti-tumor immune response depends on motile surveillance by tumor infiltrating lymphocytes (TIL) which recognize antigenic determinants and engage target cells in serial stop-and-go interactions ...

AACR  | 2022
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