Background “It's not what we do, it's the way that we do it”. Never has this maxim been truer in proteomics than now. Mass Spectrometry‐based proteomics/phosphoproteomics tools are critical to understand the structure and dynamics (spatial and temporal) of signalling that engages and migrates through the entire proteome. Approaches such as affinity purification followed by Mass Spectrometry (MS) have been used to elucidate relevant biological questions disease vs. health. Thousands of proteins interact via physical and chemical association. Moreover, certain proteins can covalently modify other proteins post‐translationally. These post‐translational modifications (PTMs) ultimately give rise to the emergent functions of cells in sequence, space and time. Findings Understanding the functions of phosphorylated proteins thus requires one to study proteomes as linked‐systems rather than collections of individual protein molecules. Indeed, the interacting proteome or protein‐network knowledge has recently received much attention, as network‐systems (signalling pathways) are effective snapshots in time, of the proteome as a whole. MS approaches are clearly essential, in spite of the difficulties of some low abundance proteins for future clinical advances. Conclusion Clinical proteomics‐MS has come a long way in the past decade in terms of technology/platform development, protein chemistry, and together with bioinformatics and other OMICS tools to identify molecular signatures of diseases based on protein pathways and signalling cascades. Hence, there is great promise for disease diagnosis, prognosis, and prediction of therapeutic outcome on an individualized basis. However, and as a general rule, without correct study design, strategy and implementation of robust analytical methodologies, the efforts, efficiency and expectations to make biomarkers (especially phosphorylated kinases) a useful reality in the near future, can easily be hampered.

Mass Spectrometry-based phosphoproteomics tools are critical to understand the structure and dynamics of signalling that engages and migrates through the entire proteome. Approaches such as affinity purification followed by Mass Spectrometry (MS) have been used to elucidate relevant biological questions in health and disease. Thousands of proteins interact via physical and chemical association. Certain proteins can covalently modify other proteins post-translationally. These post-translational modifications (PTMs) ultimately give rise to the emergent functions of cells in sequence, space and time.Understanding the functions of phosphorylated proteins thus requires one to study proteomes as linked-systems rather than collections of individual protein molecules.The interacting proteome or protein-network knowledge has recently received much attention, as networksystems (signalling pathways) are effective snapshots in time of the proteome as a whole. MS approaches are clearly essential, in spite of the difficulties of some low abundance proteins (e.g some kinases).

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Targeted therapy using EGFR tyrosine kinase inhibitor (TKI) is a standard therapy for a subset of non-small cell lung cancer (NSCLC) patients with lung adenocarcinomas (LADs) harboring EGFR kinase domain mutations; however, EGFR TKI therapy shows limited efficacy due to de novo and acquired resistance. Consequently, formulating strategies to potentiate the efficacy of EGFR TKI is of great interest. In EGFR TKI sensitive cells harboring EGFR mutation, it has been shown that EGFR inhibition induces autophagy to protect the cells from metabolic stress. Hydroxychloroquine (HQ), an inhibitor of autophagy, has been shown to potentiate EGFR TKIs in preclinical models, however, preliminary results from recent phase II clinical trials shows no added benefits to the development of resistance to erlotinib in patients with EGFR mutant NSCLC. The result suggests additional layers of mechanisms in controlling autophagy in EGFR mutated NSCLC. Furthermore, little is known about genomic alterations affecting these autophagy genes in lung cancer samples. The meta-analysis of The Cancer Genome Atlas (TCGA) database shows that essential genes for autophagic flux such as ATG5 and ATG7 tend to reduce their expression levels and/or are deleted in a significant proportion of LAD patients, suggesting a more complex scenario where the presence of these genetic alterations may lead to a structurally deficient autophagy. Besides, the detailed CNV analysis of the Cancer Cell Line Encyclopedia (CCLE) dataset suggests that a small subset of NSCLC cell lines may have lost ATG7 locus at chromosome 3. Our validation study showed that, as expected, EGFR-mutant H1650 cells exhibit an intragenic deletion at ATG7 and lack of protein expression. Moreover, functional assays of autophagic flow by western blot and confocal microscopy demonstrated that ATG7-deficient H1650 cells are not able to activate autophagy, whereas infection with lentivirus expressing ectopic ATG7 reconstituted autophagic flux and sensitivity to autophagy inhibitors including HQ. Taken together, our results suggest that genomic biomarkers based on autophagy genes could allow stratification of tumors, and selection of those candidates who could benefit from anti-autophagy therapy. Citation Format: Ines Pulido, Juan L. Pascual, Margaret Soucheray, Maria L. Rodriguez, Daniel T. Crespo, Salvador Aparisi, Joan A. Sirerol, Salvador Mena, Javier Pereda, Fatima Al-shahrour, Angel L. Ortega, Takeshi Shimamura, Julian Carretero. Genomic alterations of autophagy genes disrupts autophagic flux in human lung adenocarcinomas. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 753. doi:10.1158/1538-7445.AM2015-753

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