Background: All cancer treatments face the problem of drug resistance. Genetic factors that lead to treatment failure have been extensively studied in past decades. However, up to 40% of recurrent and resistant tumors have failed to identify a clear genetic cause. Accumulating evidence indicates that non-genetic mechanisms play an important role in primary and acquired drug resistance, but these processes have been largely overlooked. Interestingly, even under identical genetic backgrounds and in the absence of drug exposure, resistant cell fates are often predetermined by the cell"s intrinsic molecular makeup. This suggests that identifying these discrete molecular programs functionally linked to primary drug resistance could ultimately allow us to better stratify patients with the highest chance of treatment success. Cell heterogeneity is a well-recognized reason that significantly contributes to drug resistance. Recently, imaging-based single-cell proteomic studies revealed that approx. one-fifth of the proteome [MOU1] shows cell-to-cell variability emphasizing the importance of protein layer information in studying cell diversity linked to drug resistance. We therefore hypothesize that the analysis of single-cell proteome heterogeneity is another critical aspect of understanding primary drug resistance mechanisms.

Method & Results: We developed a new concept of imaging-based proteomics of single-cell derived colonies that combine the benefits from both single-cell and bulk proteomics concepts. In our approach, single-cell derived colonies can be imaged, isolated, and comprehensively profiled (6,000+ proteins) by proteomic profiling. Our method enables the integration of functional marker imaging (e.g. DNA damage marker) and cell morphology assessments with quantitative proteomics read-outs. As proof-of-concept experiment, we profiled a single-cell derived clonal head and neck cancer cell line to study sub-clonal proteome heterogeneity linked to primary drug resistance. Our data highlighted hundreds of proteins with subclone specific protein level changes including signatures previously associated with primary chemo-resistance. Interestingly, these findings also aligned with HNSCC patient tissue proteomes, underscoring the potential of this pipeline for bridging in vitro and in vivo results.

Conclusion: In conclusion, we propose an imaging-guided proteomics method of single-cell derived colonies, harnessing the strengths of both single-cell and bulk proteomics approaches. Our method has the potential to investigate non-genetic protein-level changes associated with drug resistance. This versatile pipeline can be adapted to address various research questions.