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1.
Cell ; 184(16): 4348-4371.e40, 2021 08 05.
Article in English | MEDLINE | ID: mdl-34358469

ABSTRACT

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.


Subject(s)
Carcinoma, Squamous Cell/genetics , Lung Neoplasms/genetics , Proteogenomics , Acetylation , Adult , Aged , Aged, 80 and over , Cluster Analysis , Cyclin-Dependent Kinase 4/genetics , Cyclin-Dependent Kinase 6/genetics , Epithelial-Mesenchymal Transition/genetics , Female , Gene Expression Regulation, Neoplastic , Humans , Male , Middle Aged , Mutation/genetics , Neoplasm Proteins/metabolism , Phosphorylation , Protein Binding , Receptor Tyrosine Kinase-like Orphan Receptors/metabolism , Receptors, Platelet-Derived Growth Factor/metabolism , Signal Transduction , Ubiquitination
2.
Cell ; 182(1): 200-225.e35, 2020 07 09.
Article in English | MEDLINE | ID: mdl-32649874

ABSTRACT

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.


Subject(s)
Adenocarcinoma of Lung/drug therapy , Adenocarcinoma of Lung/genetics , Lung Neoplasms/drug therapy , Lung Neoplasms/genetics , Proteogenomics , Adenocarcinoma of Lung/immunology , Adult , Aged , Aged, 80 and over , Biomarkers, Tumor/metabolism , Carcinogenesis/genetics , Carcinogenesis/pathology , DNA Copy Number Variations/genetics , DNA Methylation/genetics , Female , Humans , Lung Neoplasms/immunology , Male , Middle Aged , Mutation/genetics , Oncogene Proteins, Fusion , Phenotype , Phosphoproteins/metabolism , Proteome/metabolism
3.
Mol Cell Proteomics ; 18(7): 1468-1478, 2019 07.
Article in English | MEDLINE | ID: mdl-30967486

ABSTRACT

Isobaric stable isotope labeling using, for example, tandem mass tags (TMTs) is increasingly being applied for large-scale proteomic studies. Experiments focusing on proteoform analysis in drug time course or perturbation studies or in large patient cohorts greatly benefit from the reproducible quantification of single peptides across samples. However, such studies often require labeling of hundreds of micrograms of peptides such that the cost for labeling reagents represents a major contribution to the overall cost of an experiment. Here, we describe and evaluate a robust and cost-effective protocol for TMT labeling that reduces the quantity of required labeling reagent by a factor of eight and achieves complete labeling. Under- and overlabeling of peptides derived from complex digests of tissues and cell lines were systematically evaluated using peptide quantities of between 12.5 and 800 µg and TMT-to-peptide ratios (wt/wt) ranging from 8:1 to 1:2 at different TMT and peptide concentrations. When reaction volumes were reduced to maintain TMT and peptide concentrations of at least 10 mm and 2 g/l, respectively, TMT-to-peptide ratios as low as 1:1 (wt/wt) resulted in labeling efficiencies of > 99% and excellent intra- and interlaboratory reproducibility. The utility of the optimized protocol was further demonstrated in a deep-scale proteome and phosphoproteome analysis of patient-derived xenograft tumor tissue benchmarked against the labeling procedure recommended by the TMT vendor. Finally, we discuss the impact of labeling reaction parameters for N-hydroxysuccinimide ester-based chemistry and provide guidance on adopting efficient labeling protocols for different peptide quantities.


Subject(s)
Cost-Benefit Analysis , Isotope Labeling/economics , Mass Spectrometry , HeLa Cells , Humans , Jurkat Cells , Peptides/metabolism , Proteome/metabolism , Proteomics , Reference Standards , Reproducibility of Results
4.
bioRxiv ; 2024 Jul 29.
Article in English | MEDLINE | ID: mdl-39091817

ABSTRACT

The accuracy of crucial nuclear processes such as transcription, replication, and repair, depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed "DNA O-MAP", which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with sample multiplexed quantitative proteomics and next-generation sequencing to quantify DNA-protein and DNA-DNA interactions at specific genomic loci.

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