Phosphoproteomics of extracellular vesicles integrated with multiomics analysis reveals novel kinase networks for lung cancer

Abstract

Phosphorylation regulates the functions of proteins and aberrant phosphorylation often leads to a variety of diseases, including cancers. Extracellular vesicles (EVs) are important messengers in the microenvironment and their proteome contributes to cancer genesis and metastasis, while the kinases that driving EVs proteins' phosphorylation are less known. Clinical tissue samples from 13 patients with non-small-cell lung cancer (NSCLC) were utilized to isolate cancer EVs and adjacent normal EVs. Through quantitative phosphoproteomics analysis, 2473 phosphorylation sites on 1567 proteins were successfully identified and quantified.Accordingly, 152 kinases were identified, and 25 of them were differentially expressed. Based on Tied Diffusion through Interacting Events (TieDIE) algorithm, we integrated genomic and transcriptomic data sets of NSCLC from TCGA with our phosphoproteome data set to construct signaling networks. Through database integration and multiomics enrichment analysis, a compact network of 234 nodes with 1599 edges was constructed, which consisted of 34 transcription factors, 33 kinases, 63 aberrant genes, and 172 linking proteins. Rarely studied phosphorylation sites were specifically enriched. Key phosphoproteins of network nodes were validated in patients' EVs, including MAPK6 S189 , IKBKE S172 , SRC Y530 , CDK7 S164 , and CDK1 T14 . These networks depict intrinsic signal-regulation derived from EVs' phosphoproteins, providing a comprehensive and pathway-based strategy for in-depth lung cancer research.

Lung Cancer Proteogenomics: Shaping the Future of Clinical Investigation

“…Regarding the kinase network, 152 kinases were recognized, 25 of which had expression alterations. Key phosphoproteins of this study included MAPK6S189, IKBKES172, SRCY530, CDK7S164, and CDK1 [ 25 ].…”

“…Furthermore, this plethora of genomic information, analyzed in tandem with generated patient proteomic profiles and gene expression data, has enabled the discovery of novel drug targets and prognostic markers ( Table 2 ). Correlation analyses of mutations in genes and identified proteins have been presented by relevant studies [ 25 , 33 , 34 , 35 , 42 ]. For instance, Gillette et al [ 33 ] observed a correlation between RB1 mutation and CDK4 protein abundance and EGFR mutation with CTNNB1 protein expression.…”

“…Encompassing the integration of next generation sequencing (NGS) technology and mass spectrometry (MS) proteomics, proteogenomics is propelling the exploration of functional impacts associated with genetic alterations, including driver mutations and chromosomal aberrations. The combined genomic profiling and proteomic and phosphoproteomic analysis of clinical samples [ 24 , 25 ] is anticipated to provide a holistic view of disease severity and patient management.…”

Deciphering the SOX4/MAPK1 regulatory axis: a phosphoproteomic insight into IQGAP1 phosphorylation and pancreatic Cancer progression

“…Phosphoproteomics has emerged as a prominent field of research in recent years, offering a novel approach to elucidate phosphorylation events and their affiliated signaling pathways in cancer [ 7 – 9 ]. Phosphoproteomics uncovers the functions of diverse kinases and substrates in advancing tumors by examining protein phosphorylation sites [ 10 ]. SOX4, MAPK1, and IQGAP1 are all associated with the occurrence and progression of pancreatic cancer [ 11 , 12 ].…”