Autophagy is a crucial eukaryotic degradation pathway which is known to be perturbed in a wide range of diseases. This pathway involves the growing of a newly formed membrane-enclosed vesicle inside the cell, capturing parts of the cytoplasm and transporting them to the lysosome for hydrolysis. Autophagy provides the cell with the means to degrade large components such as damaged organelles or protein aggregates that cannot be degraded by the proteasome. Although it has long been assumed that autophagy is a bulk process capturing its cargo in a random manner, research from the last decade has uncovered numerous specialized selective autophagy pathways, targeting specific cargoes under certain stimuli for degradation. Accurate quantification of these pathway markers is crucial as it can be used as a proxy for the degradation of autophagy targets. Unfortunately, some markers are low-abundant proteins making them difficult to detect and to quantify in standard bottom-up proteomics approaches.

Common methods to investigate these processes generally rely on the quantification of single protein markers often failing to address the complexity and crosstalk of these selective mechanisms. Additionally, these methods often rely on the (over-)expression of fluorescent proteins making them unpractical with certain sample types.

Here, we introduce a targeted proteomics approach quantifying most characterized selective autophagy receptors and additional autophagy-relevant proteins as a tool to investigate autophagy selectivity. We compared our proteomic approach with state-of-the-art fluorescence-based approaches and reproduced respective results while also capturing more complex dynamics of organelle degradation. We next screened a panel of Melanoma-derived cell lines using this approach combined with data-independent expression proteomics to investigate how different cancers remodel their proteome in response to stress by selective autophagic activity.