The early detection of non-small cell lung cancer (NSCLC) is an unmet challenge in the field with significant direct impact on effectiveness of treatments and survival rate of affected patients. The emergence of neoadjuvant therapies and the challenges associated with detecting minimal residual disease (MRD) in NSCLC patients necessitates the development of new diagnostic tests that can help physicians tailor appropriate therapeutic regimens to the individual patient and detect MRD early to improve patient outcomes. Previously, Exai Bio has discovered a new class of small RNAs that are mainly expressed in the tumor tissues, denoted as orphan noncoding RNAs (oncRNAs). Moreover, Exai Bio has shown that oncRNAs are promising biomarkers for early cancer detection, using blood as part of a novel liquid biopsy technique. We have recently developed a novel assay and an artificial intelligence (AI) model for early detection of lung cancer and predicting the subtypes using oncRNA profiles. We have shown in a small, retrospective cohort that this new assay has a higher sensitivity than state-of-the-art approaches available or published. As part of this project we will work closely with outside collaborators to gather samples and test the performance of this new assay for detection of MRD in NSCLC patients and to identify its subtypes.

Lung cancer is the leading cause of cancer death in the US (1 in 5 of all cancer deaths). Early detection of lung cancer minimal residual disease (MRD) after treatment improves the effectiveness of therapies and patient survival rates. The goal of this program is to develop a highly sensitive, tumor-naive, blood-based laboratory developed test (LDT) for detecting MRD in stage IB–IIIA non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant therapy.