8P - Precision medicine drug testing platform to guide the treatment of EML4-ALK fusion lung cancers

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 persons with little or no smoking history. Fusions involving anaplastic lymphoma kinase (ALK) are the oncogenic driver in ∼3–7% of NSCLC. While inhibitors targeting the kinase domain of ALK (TKIs) have proven effective, inevitably, resistance develops with limited effective treatment options. Choosing the next treatment is a major challenge.

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 3D-culture to generate patient-derived organoids (PDOs). PDOs are screened at therapeutically relevant doses, drawing from pharmacokinetic data for each drug. We have optimized an assay to rapidly screen for EML4-ALK fusions and can perform next-generation sequencing in ∼7 days to integrate with drug screening results.

Results

To date, we have screened 105 NSCLC tissue/fluid collections, including 15 distinct cases of EML4-ALK NSCLC. We have demonstrated an ability to produce high quality data from low input samples (biopsies). In one EML4-ALK NSCLC we were able to collect PDM from two distinct anatomic spaces (pleural effusion and peritoneal fluid) and screen with the same panel of drugs, with nearly identical results, highlighting the consistency of our assay. Our results recapitulate known resistance/progression in samples previously exposed to therapy, demonstrating a strong negative predictive value. The output of our PMP is a ranked list of plausibly active drugs for each tumor.

Conclusions

Our PMP produces robust results that are consistent with known clinical pathogenesis. Ongoing longitudinal data from enrolled patients in parallel with clinical trials aims to demonstrate the positive predictive value of our PMP. We additionally strive to prove reproducibility to obtain Clinical Laboratory Improvement Amendments approval. Integration with multiomics is performed in each sample to maximally inform the patient's clinical team.

Editorial acknowledgement

Clinical trial identification

Legal entity responsible for the study

University of Michigan, Ann Arbor, MI, USA.

Funding

Judith Tam ALK Lung Cancer Research Initiative.

Disclosure

A. Qin: Non-Financial Interests, Personal, Research Grant: Genentech, AstraZeneca, Janssen, Merck; Financial Interests, Personal, Advisory Role: Summit Therapeutics, Regeneron, Strata; Non-Financial Interests, Personal, Sponsor/Funding: Astellas. V. Navani: Financial Interests, Personal, Advisory Board: AstraZeneca, Sanofi, Ipsen, Pfizer, Janssen, EMD Serono, Novotech; Other, Personal, Other, Travel: Sanofi, EMD Serono. M.S. Ali: Financial Interests, Personal, Advisory Role: Inyuiyive Surgical. A. Smith: Financial Interests, Personal, Stocks/Shares: Xilis; Financial Interests, Personal, Proprietary Information: Xilis. All other authors have declared no conflicts of interest.