159P - Precision medicine-based platform to guide the treatment of EML4-ALK fusion lung cancers and other NSCLC

Background

Lung cancer (LC) remains the top cause of cancer-associated mortality worldwide, with a 10-year overall survival rate of only 5%. While most LCs are smoking related, 25% of non-small cell LC (NSCLC) are diagnosed in patients with little or no smoking history. Fusions involving ALK are the oncogenic driver in ∼3–7% of NSCLC. While inhibitors targeting the kinase domain of ALK (TKI) have proven extremely effective, inevitably, resistance develops with limited effective treatment options.

Methods

We developed a precision medicine-based platform (PMP) to screen patient-derived material (PDM) directly from the operating room with curated panels of drugs. PDM collected during clinically indicated procedures is plated in culture to generate patient-derived organoids (PDOs) and screened with drugs curated to each tumor type. PDOs are screened at therapeutically relevant doses, drawing from pharmacokinetic data for each drug, when available. We have optimized an assay to rapidly screen for EML4-ALK fusions and can perform NGS in real time (∼7 days) to integrate with drug screening results.

Results

To date, we have screened 51 NSCLC cases, including 7 ALK-positive NSCLC. Screening of EML4-ALK tumors which have progressed to second or higher line TKI, demonstrates sensitivity to earlier generation ALK TKIs, a known phenomenon in the literature. Our results recapitulate known resistance in samples previously exposed to therapy, demonstrating a strong negative predictive value. Longitudinal assessment will be required to robustly assess positive predictive value (PPV). In one EML4-ALK NSCLC we were able to collect PDM from two distinct regions (pleural effusion and paracentesis) and screen with the same panel of drugs, highlighting the reproducibility and consistency of our assay.

Conclusions

Our PMP captures robust and reproducible results that are consistent with known clinical pathogenesis. Moving forward, we are collecting longitudinal data from enrolled patients in parallel with clinical trials to demonstrate PPV of our PMP. We additionally strive to demonstrate reproducibility to obtain Clinical Laboratory Improvement Amendments (CLIA) approval and to deliver results to patients and physicians to help guide clinical care.

Editorial acknowledgement

Clinical trial identification

Legal entity responsible for the study

The authors.

Funding

Judy Tam Research Initiative.

Disclosure

All authors have declared no conflicts of interest.