Monotherapy with anti-PD-1 is indicated as first-line therapy in patients with advanced non-small-cell lung cancer (NSCLC) that carry non-targetable driver mutations and higher than 50% PDL1 expression. Still, many patients do not respond or become resistant after they exhibit an initial response. Identifying patients who will benefit from anti-PD-1 monotherapy or that require a more aggressive combination therapy is an unmet need.

Three-dimensional primary microfluidic cultures may capture the dynamic tumor-immune interplay and provide insights on optimal treatment through reverse translation. Indeed, recent studies have shown that the release of CCL19 and CXCL13 in melanoma-derived microfluidic cultures correlates with clinical responses and it remains to be seen whether and how similar approaches may be applied to other types of cancer such as lung cancer.

The aim of this project is to interrogate the applicability of an innovative 3D microfluidic microculture, i.e. tumor-on-chip, in predicting real-time responses to PD1-blockade in NSCLC patients.

Bronchoscopic tumor biopsies are minimally invasive and are routinely obtained from advanced NSCLC patients, therefore they are ideal samples to be used for personalized drug screening purposes. We will develop and validate the first bronchoscopic biopsies-on-chip (BioOnChip) and we will conduct a prospective co-clinical trial by studying in parallel clinical responses (overall survival and progression-free survival) to a-PD1 monotherapy in treatment-naive advanced NSCLC patients (n=36) matched to their bronchoBOCs.

The responses of bronchoBOC to a-PD1 therapy will be profiled through proteome analysis using mass spectrometry (LC-MS/MS), FACS and cytometric bead arrays, accompanied by immunofluorescence imaging.

Artificial intelligence/machine learning approaches will be applied to BioOnChip profiles and clinical data, to identify the optimal predictive biomarker patterns to a-PD1 therapy. We will develop easy bioinformatics algorithms that can predict response to therapy.

The final products of this project will be:

A standardized pre-clinical platform for drug screening,
A Health Technology Assessment of its socioeconomic impact,
A user-friendly clinical prediction algorithm and online portal,
The first Greek spin-out company that offers tumor-on-chip platforms for drug screening to the pharma industry.